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java/resources/realtime/index.md 2026-06-16 21:57 UTC to 2026-06-17 18:02 UTC

126 added, 56 removed.

2026
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Realtime

Domain Types

Audio Transcription

  • class AudioTranscription:

    • Optional<Delay> delay

      Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

      • MINIMAL("minimal")

      • LOW("low")

      • MEDIUM("medium")

      • HIGH("high")

      • XHIGH("xhigh")

    • Optional<String> language

      The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

    • Optional<Model> model

      The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

      • WHISPER_1("whisper-1")

      • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

      • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

      • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

      • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

      • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

    • Optional<String> prompt

      An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

Conversation Created Event

  • class ConversationCreatedEvent:

    Returned when a conversation is created. Emitted right after session creation.

    • Conversation conversation

      The conversation resource.

      • Optional<String> id

        The unique ID of the conversation.

      • Optional<Object> object_

        The object type, must be realtime.conversation.

        • REALTIME_CONVERSATION("realtime.conversation")
    • String eventId

      The unique ID of the server event.

    • JsonValue; type "conversation.created"constant

      The event type, must be conversation.created.

      • CONVERSATION_CREATED("conversation.created")

Conversation Item

  • class ConversationItem: A class that can be one of several variants.union

    A single item within a Realtime conversation.

    • class RealtimeConversationItemSystemMessage:

      A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

      • List<Content> content

        The content of the message.

        • Optional<String> text

          The text content.

        • Optional<Type> type

          The content type. Always input_text for system messages.

          • INPUT_TEXT("input_text")
      • JsonValue; role "system"constant

        The role of the message sender. Always system.

        • SYSTEM("system")
      • JsonValue; type "message"constant

        The type of the item. Always message.

        • MESSAGE("message")
      • Optional<String> id

        The unique ID of the item. This may be provided by the client or generated by the server.

      • Optional<Object> object_

        Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

        • REALTIME_ITEM("realtime.item")
      • Optional<Status> status

        The status of the item. Has no effect on the conversation.

        • COMPLETED("completed")

        • INCOMPLETE("incomplete")

        • IN_PROGRESS("in_progress")

    • class RealtimeConversationItemUserMessage:

      A user message item in a Realtime conversation.

      • List<Content> content

        The content of the message.

        • Optional<String> audio

          Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

        • Optional<Detail> detail

          The detail level of the image (for input_image). auto will default to high.

          • AUTO("auto")

          • LOW("low")

          • HIGH("high")

        • Optional<String> imageUrl

          Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

        • Optional<String> text

          The text content (for input_text).

        • Optional<String> transcript

          Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

        • Optional<Type> type

          The content type (input_text, input_audio, or input_image).

          • INPUT_TEXT("input_text")

          • INPUT_AUDIO("input_audio")

          • INPUT_IMAGE("input_image")

      • JsonValue; role "user"constant

        The role of the message sender. Always user.

        • USER("user")
      • JsonValue; type "message"constant

        The type of the item. Always message.

        • MESSAGE("message")
      • Optional<String> id

        The unique ID of the item. This may be provided by the client or generated by the server.

      • Optional<Object> object_

        Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

        • REALTIME_ITEM("realtime.item")
      • Optional<Status> status

        The status of the item. Has no effect on the conversation.

        • COMPLETED("completed")

        • INCOMPLETE("incomplete")

        • IN_PROGRESS("in_progress")

    • class RealtimeConversationItemAssistantMessage:

      An assistant message item in a Realtime conversation.

      • List<Content> content

        The content of the message.

        • Optional<String> audio

          Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

        • Optional<String> text

          The text content.

        • Optional<String> transcript

          The transcript of the audio content, this will always be present if the output type is audio.

        • Optional<Type> type

          The content type, output_text or output_audio depending on the session output_modalities configuration.

          • OUTPUT_TEXT("output_text")

          • OUTPUT_AUDIO("output_audio")

      • JsonValue; role "assistant"constant

        The role of the message sender. Always assistant.

        • ASSISTANT("assistant")
      • JsonValue; type "message"constant

        The type of the item. Always message.

        • MESSAGE("message")
      • Optional<String> id

        The unique ID of the item. This may be provided by the client or generated by the server.

      • Optional<Object> object_

        Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

        • REALTIME_ITEM("realtime.item")
      • Optional<Status> status

        The status of the item. Has no effect on the conversation.

        • COMPLETED("completed")

        • INCOMPLETE("incomplete")

        • IN_PROGRESS("in_progress")

    • class RealtimeConversationItemFunctionCall:

      A function call item in a Realtime conversation.

      • String arguments

        The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

      • String name

        The name of the function being called.

      • JsonValue; type "function_call"constant

        The type of the item. Always function_call.

        • FUNCTION_CALL("function_call")
      • Optional<String> id

        The unique ID of the item. This may be provided by the client or generated by the server.

      • Optional<String> callId

        The ID of the function call.

      • Optional<Object> object_

        Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

        • REALTIME_ITEM("realtime.item")
      • Optional<Status> status

        The status of the item. Has no effect on the conversation.

        • COMPLETED("completed")

        • INCOMPLETE("incomplete")

        • IN_PROGRESS("in_progress")

    • class RealtimeConversationItemFunctionCallOutput:

      A function call output item in a Realtime conversation.

      • String callId

        The ID of the function call this output is for.

      • String output

        The output of the function call, this is free text and can contain any information or simply be empty.

      • JsonValue; type "function_call_output"constant

        The type of the item. Always function_call_output.

        • FUNCTION_CALL_OUTPUT("function_call_output")
      • Optional<String> id

        The unique ID of the item. This may be provided by the client or generated by the server.

      • Optional<Object> object_

        Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

        • REALTIME_ITEM("realtime.item")
      • Optional<Status> status

        The status of the item. Has no effect on the conversation.

        • COMPLETED("completed")

        • INCOMPLETE("incomplete")

        • IN_PROGRESS("in_progress")

    • class RealtimeMcpApprovalResponse:

      A Realtime item responding to an MCP approval request.

      • String id

        The unique ID of the approval response.

      • String approvalRequestId

        The ID of the approval request being answered.

      • boolean approve

        Whether the request was approved.

      • JsonValue; type "mcp_approval_response"constant

        The type of the item. Always mcp_approval_response.

        • MCP_APPROVAL_RESPONSE("mcp_approval_response")
      • Optional<String> reason

        Optional reason for the decision.

    • class RealtimeMcpListTools:

      A Realtime item listing tools available on an MCP server.

      • String serverLabel

        The label of the MCP server.

      • List<Tool> tools

        The tools available on the server.

        • JsonValue inputSchema

          The JSON schema describing the tool's input.

        • String name

          The name of the tool.

        • Optional<JsonValue> annotations

          Additional annotations about the tool.

        • Optional<String> description

          The description of the tool.

      • JsonValue; type "mcp_list_tools"constant

        The type of the item. Always mcp_list_tools.

        • MCP_LIST_TOOLS("mcp_list_tools")
      • Optional<String> id

        The unique ID of the list.

    • class RealtimeMcpToolCall:

      A Realtime item representing an invocation of a tool on an MCP server.

      • String id

        The unique ID of the tool call.

      • String arguments

        A JSON string of the arguments passed to the tool.

      • String name

        The name of the tool that was run.

      • String serverLabel

        The label of the MCP server running the tool.

      • JsonValue; type "mcp_call"constant

        The type of the item. Always mcp_call.

        • MCP_CALL("mcp_call")
      • Optional<String> approvalRequestId

        The ID of an associated approval request, if any.

      • Optional<Error> error

        The error from the tool call, if any.

        • class RealtimeMcpProtocolError:

          • long code

          • String message

          • JsonValue; type "protocol_error"constant

            • PROTOCOL_ERROR("protocol_error")
        • class RealtimeMcpToolExecutionError:

          • String message

          • JsonValue; type "tool_execution_error"constant

            • TOOL_EXECUTION_ERROR("tool_execution_error")
        • class RealtimeMcphttpError:

          • long code

          • String message

          • JsonValue; type "http_error"constant

            • HTTP_ERROR("http_error")
      • Optional<String> output

        The output from the tool call.

    • class RealtimeMcpApprovalRequest:

      A Realtime item requesting human approval of a tool invocation.

      • String id

        The unique ID of the approval request.

      • String arguments

        A JSON string of arguments for the tool.

      • String name

        The name of the tool to run.

      • String serverLabel

        The label of the MCP server making the request.

      • JsonValue; type "mcp_approval_request"constant

        The type of the item. Always mcp_approval_request.

        • MCP_APPROVAL_REQUEST("mcp_approval_request")

Conversation Item Added

  • class ConversationItemAdded:

    Sent by the server when an Item is added to the default Conversation. This can happen in several cases:

    • When the client sends a conversation.item.create event.
    • When the input audio buffer is committed. In this case the item will be a user message containing the audio from the buffer.
    • When the model is generating a Response. In this case the conversation.item.added event will be sent when the model starts generating a specific Item, and thus it will not yet have any content (and status will be in_progress).

    The event will include the full content of the Item (except when model is generating a Response) except for audio data, which can be retrieved separately with a conversation.item.retrieve event if necessary.

    • String eventId

      The unique ID of the server event.

    • ConversationItem item

      A single item within a Realtime conversation.

      • class RealtimeConversationItemSystemMessage:

        A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

        • List<Content> content

          The content of the message.

          • Optional<String> text

            The text content.

          • Optional<Type> type

            The content type. Always input_text for system messages.

            • INPUT_TEXT("input_text")
        • JsonValue; role "system"constant

          The role of the message sender. Always system.

          • SYSTEM("system")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemUserMessage:

        A user message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<Detail> detail

            The detail level of the image (for input_image). auto will default to high.

            • AUTO("auto")

            • LOW("low")

            • HIGH("high")

          • Optional<String> imageUrl

            Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

          • Optional<String> text

            The text content (for input_text).

          • Optional<String> transcript

            Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

          • Optional<Type> type

            The content type (input_text, input_audio, or input_image).

            • INPUT_TEXT("input_text")

            • INPUT_AUDIO("input_audio")

            • INPUT_IMAGE("input_image")

        • JsonValue; role "user"constant

          The role of the message sender. Always user.

          • USER("user")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemAssistantMessage:

        An assistant message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<String> text

            The text content.

          • Optional<String> transcript

            The transcript of the audio content, this will always be present if the output type is audio.

          • Optional<Type> type

            The content type, output_text or output_audio depending on the session output_modalities configuration.

            • OUTPUT_TEXT("output_text")

            • OUTPUT_AUDIO("output_audio")

        • JsonValue; role "assistant"constant

          The role of the message sender. Always assistant.

          • ASSISTANT("assistant")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCall:

        A function call item in a Realtime conversation.

        • String arguments

          The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

        • String name

          The name of the function being called.

        • JsonValue; type "function_call"constant

          The type of the item. Always function_call.

          • FUNCTION_CALL("function_call")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<String> callId

          The ID of the function call.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCallOutput:

        A function call output item in a Realtime conversation.

        • String callId

          The ID of the function call this output is for.

        • String output

          The output of the function call, this is free text and can contain any information or simply be empty.

        • JsonValue; type "function_call_output"constant

          The type of the item. Always function_call_output.

          • FUNCTION_CALL_OUTPUT("function_call_output")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeMcpApprovalResponse:

        A Realtime item responding to an MCP approval request.

        • String id

          The unique ID of the approval response.

        • String approvalRequestId

          The ID of the approval request being answered.

        • boolean approve

          Whether the request was approved.

        • JsonValue; type "mcp_approval_response"constant

          The type of the item. Always mcp_approval_response.

          • MCP_APPROVAL_RESPONSE("mcp_approval_response")
        • Optional<String> reason

          Optional reason for the decision.

      • class RealtimeMcpListTools:

        A Realtime item listing tools available on an MCP server.

        • String serverLabel

          The label of the MCP server.

        • List<Tool> tools

          The tools available on the server.

          • JsonValue inputSchema

            The JSON schema describing the tool's input.

          • String name

            The name of the tool.

          • Optional<JsonValue> annotations

            Additional annotations about the tool.

          • Optional<String> description

            The description of the tool.

        • JsonValue; type "mcp_list_tools"constant

          The type of the item. Always mcp_list_tools.

          • MCP_LIST_TOOLS("mcp_list_tools")
        • Optional<String> id

          The unique ID of the list.

      • class RealtimeMcpToolCall:

        A Realtime item representing an invocation of a tool on an MCP server.

        • String id

          The unique ID of the tool call.

        • String arguments

          A JSON string of the arguments passed to the tool.

        • String name

          The name of the tool that was run.

        • String serverLabel

          The label of the MCP server running the tool.

        • JsonValue; type "mcp_call"constant

          The type of the item. Always mcp_call.

          • MCP_CALL("mcp_call")
        • Optional<String> approvalRequestId

          The ID of an associated approval request, if any.

        • Optional<Error> error

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError:

            • long code

            • String message

            • JsonValue; type "protocol_error"constant

              • PROTOCOL_ERROR("protocol_error")
          • class RealtimeMcpToolExecutionError:

            • String message

            • JsonValue; type "tool_execution_error"constant

              • TOOL_EXECUTION_ERROR("tool_execution_error")
          • class RealtimeMcphttpError:

            • long code

            • String message

            • JsonValue; type "http_error"constant

              • HTTP_ERROR("http_error")
        • Optional<String> output

          The output from the tool call.

      • class RealtimeMcpApprovalRequest:

        A Realtime item requesting human approval of a tool invocation.

        • String id

          The unique ID of the approval request.

        • String arguments

          A JSON string of arguments for the tool.

        • String name

          The name of the tool to run.

        • String serverLabel

          The label of the MCP server making the request.

        • JsonValue; type "mcp_approval_request"constant

          The type of the item. Always mcp_approval_request.

          • MCP_APPROVAL_REQUEST("mcp_approval_request")
    • JsonValue; type "conversation.item.added"constant

      The event type, must be conversation.item.added.

      • CONVERSATION_ITEM_ADDED("conversation.item.added")
    • Optional<String> previousItemId

      The ID of the item that precedes this one, if any. This is used to maintain ordering when items are inserted.

Conversation Item Create Event

  • class ConversationItemCreateEvent:

    Add a new Item to the Conversation's context, including messages, function calls, and function call responses. This event can be used both to populate a "history" of the conversation and to add new items mid-stream, but has the current limitation that it cannot populate assistant audio messages.

    If successful, the server will respond with a conversation.item.created event, otherwise an error event will be sent.

    • ConversationItem item

      A single item within a Realtime conversation.

      • class RealtimeConversationItemSystemMessage:

        A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

        • List<Content> content

          The content of the message.

          • Optional<String> text

            The text content.

          • Optional<Type> type

            The content type. Always input_text for system messages.

            • INPUT_TEXT("input_text")
        • JsonValue; role "system"constant

          The role of the message sender. Always system.

          • SYSTEM("system")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemUserMessage:

        A user message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<Detail> detail

            The detail level of the image (for input_image). auto will default to high.

            • AUTO("auto")

            • LOW("low")

            • HIGH("high")

          • Optional<String> imageUrl

            Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

          • Optional<String> text

            The text content (for input_text).

          • Optional<String> transcript

            Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

          • Optional<Type> type

            The content type (input_text, input_audio, or input_image).

            • INPUT_TEXT("input_text")

            • INPUT_AUDIO("input_audio")

            • INPUT_IMAGE("input_image")

        • JsonValue; role "user"constant

          The role of the message sender. Always user.

          • USER("user")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemAssistantMessage:

        An assistant message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<String> text

            The text content.

          • Optional<String> transcript

            The transcript of the audio content, this will always be present if the output type is audio.

          • Optional<Type> type

            The content type, output_text or output_audio depending on the session output_modalities configuration.

            • OUTPUT_TEXT("output_text")

            • OUTPUT_AUDIO("output_audio")

        • JsonValue; role "assistant"constant

          The role of the message sender. Always assistant.

          • ASSISTANT("assistant")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCall:

        A function call item in a Realtime conversation.

        • String arguments

          The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

        • String name

          The name of the function being called.

        • JsonValue; type "function_call"constant

          The type of the item. Always function_call.

          • FUNCTION_CALL("function_call")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<String> callId

          The ID of the function call.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCallOutput:

        A function call output item in a Realtime conversation.

        • String callId

          The ID of the function call this output is for.

        • String output

          The output of the function call, this is free text and can contain any information or simply be empty.

        • JsonValue; type "function_call_output"constant

          The type of the item. Always function_call_output.

          • FUNCTION_CALL_OUTPUT("function_call_output")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeMcpApprovalResponse:

        A Realtime item responding to an MCP approval request.

        • String id

          The unique ID of the approval response.

        • String approvalRequestId

          The ID of the approval request being answered.

        • boolean approve

          Whether the request was approved.

        • JsonValue; type "mcp_approval_response"constant

          The type of the item. Always mcp_approval_response.

          • MCP_APPROVAL_RESPONSE("mcp_approval_response")
        • Optional<String> reason

          Optional reason for the decision.

      • class RealtimeMcpListTools:

        A Realtime item listing tools available on an MCP server.

        • String serverLabel

          The label of the MCP server.

        • List<Tool> tools

          The tools available on the server.

          • JsonValue inputSchema

            The JSON schema describing the tool's input.

          • String name

            The name of the tool.

          • Optional<JsonValue> annotations

            Additional annotations about the tool.

          • Optional<String> description

            The description of the tool.

        • JsonValue; type "mcp_list_tools"constant

          The type of the item. Always mcp_list_tools.

          • MCP_LIST_TOOLS("mcp_list_tools")
        • Optional<String> id

          The unique ID of the list.

      • class RealtimeMcpToolCall:

        A Realtime item representing an invocation of a tool on an MCP server.

        • String id

          The unique ID of the tool call.

        • String arguments

          A JSON string of the arguments passed to the tool.

        • String name

          The name of the tool that was run.

        • String serverLabel

          The label of the MCP server running the tool.

        • JsonValue; type "mcp_call"constant

          The type of the item. Always mcp_call.

          • MCP_CALL("mcp_call")
        • Optional<String> approvalRequestId

          The ID of an associated approval request, if any.

        • Optional<Error> error

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError:

            • long code

            • String message

            • JsonValue; type "protocol_error"constant

              • PROTOCOL_ERROR("protocol_error")
          • class RealtimeMcpToolExecutionError:

            • String message

            • JsonValue; type "tool_execution_error"constant

              • TOOL_EXECUTION_ERROR("tool_execution_error")
          • class RealtimeMcphttpError:

            • long code

            • String message

            • JsonValue; type "http_error"constant

              • HTTP_ERROR("http_error")
        • Optional<String> output

          The output from the tool call.

      • class RealtimeMcpApprovalRequest:

        A Realtime item requesting human approval of a tool invocation.

        • String id

          The unique ID of the approval request.

        • String arguments

          A JSON string of arguments for the tool.

        • String name

          The name of the tool to run.

        • String serverLabel

          The label of the MCP server making the request.

        • JsonValue; type "mcp_approval_request"constant

          The type of the item. Always mcp_approval_request.

          • MCP_APPROVAL_REQUEST("mcp_approval_request")
    • JsonValue; type "conversation.item.create"constant

      The event type, must be conversation.item.create.

      • CONVERSATION_ITEM_CREATE("conversation.item.create")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

    • Optional<String> previousItemId

      The ID of the preceding item after which the new item will be inserted. If not set, the new item will be appended to the end of the conversation.

      If set to root, the new item will be added to the beginning of the conversation.

      If set to an existing ID, it allows an item to be inserted mid-conversation. If the ID cannot be found, an error will be returned and the item will not be added.

Conversation Item Created Event

  • class ConversationItemCreatedEvent:

    Returned when a conversation item is created. There are several scenarios that produce this event:

    • The server is generating a Response, which if successful will produce either one or two Items, which will be of type message (role assistant) or type function_call.

    • The input audio buffer has been committed, either by the client or the server (in server_vad mode). The server will take the content of the input audio buffer and add it to a new user message Item.

    • The client has sent a conversation.item.create event to add a new Item to the Conversation.

    • String eventId

      The unique ID of the server event.

    • ConversationItem item

      A single item within a Realtime conversation.

      • class RealtimeConversationItemSystemMessage:

        A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

        • List<Content> content

          The content of the message.

          • Optional<String> text

            The text content.

          • Optional<Type> type

            The content type. Always input_text for system messages.

            • INPUT_TEXT("input_text")
        • JsonValue; role "system"constant

          The role of the message sender. Always system.

          • SYSTEM("system")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemUserMessage:

        A user message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<Detail> detail

            The detail level of the image (for input_image). auto will default to high.

            • AUTO("auto")

            • LOW("low")

            • HIGH("high")

          • Optional<String> imageUrl

            Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

          • Optional<String> text

            The text content (for input_text).

          • Optional<String> transcript

            Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

          • Optional<Type> type

            The content type (input_text, input_audio, or input_image).

            • INPUT_TEXT("input_text")

            • INPUT_AUDIO("input_audio")

            • INPUT_IMAGE("input_image")

        • JsonValue; role "user"constant

          The role of the message sender. Always user.

          • USER("user")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemAssistantMessage:

        An assistant message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<String> text

            The text content.

          • Optional<String> transcript

            The transcript of the audio content, this will always be present if the output type is audio.

          • Optional<Type> type

            The content type, output_text or output_audio depending on the session output_modalities configuration.

            • OUTPUT_TEXT("output_text")

            • OUTPUT_AUDIO("output_audio")

        • JsonValue; role "assistant"constant

          The role of the message sender. Always assistant.

          • ASSISTANT("assistant")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCall:

        A function call item in a Realtime conversation.

        • String arguments

          The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

        • String name

          The name of the function being called.

        • JsonValue; type "function_call"constant

          The type of the item. Always function_call.

          • FUNCTION_CALL("function_call")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<String> callId

          The ID of the function call.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCallOutput:

        A function call output item in a Realtime conversation.

        • String callId

          The ID of the function call this output is for.

        • String output

          The output of the function call, this is free text and can contain any information or simply be empty.

        • JsonValue; type "function_call_output"constant

          The type of the item. Always function_call_output.

          • FUNCTION_CALL_OUTPUT("function_call_output")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeMcpApprovalResponse:

        A Realtime item responding to an MCP approval request.

        • String id

          The unique ID of the approval response.

        • String approvalRequestId

          The ID of the approval request being answered.

        • boolean approve

          Whether the request was approved.

        • JsonValue; type "mcp_approval_response"constant

          The type of the item. Always mcp_approval_response.

          • MCP_APPROVAL_RESPONSE("mcp_approval_response")
        • Optional<String> reason

          Optional reason for the decision.

      • class RealtimeMcpListTools:

        A Realtime item listing tools available on an MCP server.

        • String serverLabel

          The label of the MCP server.

        • List<Tool> tools

          The tools available on the server.

          • JsonValue inputSchema

            The JSON schema describing the tool's input.

          • String name

            The name of the tool.

          • Optional<JsonValue> annotations

            Additional annotations about the tool.

          • Optional<String> description

            The description of the tool.

        • JsonValue; type "mcp_list_tools"constant

          The type of the item. Always mcp_list_tools.

          • MCP_LIST_TOOLS("mcp_list_tools")
        • Optional<String> id

          The unique ID of the list.

      • class RealtimeMcpToolCall:

        A Realtime item representing an invocation of a tool on an MCP server.

        • String id

          The unique ID of the tool call.

        • String arguments

          A JSON string of the arguments passed to the tool.

        • String name

          The name of the tool that was run.

        • String serverLabel

          The label of the MCP server running the tool.

        • JsonValue; type "mcp_call"constant

          The type of the item. Always mcp_call.

          • MCP_CALL("mcp_call")
        • Optional<String> approvalRequestId

          The ID of an associated approval request, if any.

        • Optional<Error> error

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError:

            • long code

            • String message

            • JsonValue; type "protocol_error"constant

              • PROTOCOL_ERROR("protocol_error")
          • class RealtimeMcpToolExecutionError:

            • String message

            • JsonValue; type "tool_execution_error"constant

              • TOOL_EXECUTION_ERROR("tool_execution_error")
          • class RealtimeMcphttpError:

            • long code

            • String message

            • JsonValue; type "http_error"constant

              • HTTP_ERROR("http_error")
        • Optional<String> output

          The output from the tool call.

      • class RealtimeMcpApprovalRequest:

        A Realtime item requesting human approval of a tool invocation.

        • String id

          The unique ID of the approval request.

        • String arguments

          A JSON string of arguments for the tool.

        • String name

          The name of the tool to run.

        • String serverLabel

          The label of the MCP server making the request.

        • JsonValue; type "mcp_approval_request"constant

          The type of the item. Always mcp_approval_request.

          • MCP_APPROVAL_REQUEST("mcp_approval_request")
    • JsonValue; type "conversation.item.created"constant

      The event type, must be conversation.item.created.

      • CONVERSATION_ITEM_CREATED("conversation.item.created")
    • Optional<String> previousItemId

      The ID of the preceding item in the Conversation context, allows the client to understand the order of the conversation. Can be null if the item has no predecessor.

Conversation Item Delete Event

  • class ConversationItemDeleteEvent:

    Send this event when you want to remove any item from the conversation history. The server will respond with a conversation.item.deleted event, unless the item does not exist in the conversation history, in which case the server will respond with an error.

    • String itemId

      The ID of the item to delete.

    • JsonValue; type "conversation.item.delete"constant

      The event type, must be conversation.item.delete.

      • CONVERSATION_ITEM_DELETE("conversation.item.delete")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Conversation Item Deleted Event

  • class ConversationItemDeletedEvent:

    Returned when an item in the conversation is deleted by the client with a conversation.item.delete event. This event is used to synchronize the server's understanding of the conversation history with the client's view.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item that was deleted.

    • JsonValue; type "conversation.item.deleted"constant

      The event type, must be conversation.item.deleted.

      • CONVERSATION_ITEM_DELETED("conversation.item.deleted")

Conversation Item Done

  • class ConversationItemDone:

    Returned when a conversation item is finalized.

    The event will include the full content of the Item except for audio data, which can be retrieved separately with a conversation.item.retrieve event if needed.

    • String eventId

      The unique ID of the server event.

    • ConversationItem item

      A single item within a Realtime conversation.

      • class RealtimeConversationItemSystemMessage:

        A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

        • List<Content> content

          The content of the message.

          • Optional<String> text

            The text content.

          • Optional<Type> type

            The content type. Always input_text for system messages.

            • INPUT_TEXT("input_text")
        • JsonValue; role "system"constant

          The role of the message sender. Always system.

          • SYSTEM("system")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemUserMessage:

        A user message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<Detail> detail

            The detail level of the image (for input_image). auto will default to high.

            • AUTO("auto")

            • LOW("low")

            • HIGH("high")

          • Optional<String> imageUrl

            Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

          • Optional<String> text

            The text content (for input_text).

          • Optional<String> transcript

            Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

          • Optional<Type> type

            The content type (input_text, input_audio, or input_image).

            • INPUT_TEXT("input_text")

            • INPUT_AUDIO("input_audio")

            • INPUT_IMAGE("input_image")

        • JsonValue; role "user"constant

          The role of the message sender. Always user.

          • USER("user")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemAssistantMessage:

        An assistant message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<String> text

            The text content.

          • Optional<String> transcript

            The transcript of the audio content, this will always be present if the output type is audio.

          • Optional<Type> type

            The content type, output_text or output_audio depending on the session output_modalities configuration.

            • OUTPUT_TEXT("output_text")

            • OUTPUT_AUDIO("output_audio")

        • JsonValue; role "assistant"constant

          The role of the message sender. Always assistant.

          • ASSISTANT("assistant")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCall:

        A function call item in a Realtime conversation.

        • String arguments

          The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

        • String name

          The name of the function being called.

        • JsonValue; type "function_call"constant

          The type of the item. Always function_call.

          • FUNCTION_CALL("function_call")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<String> callId

          The ID of the function call.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCallOutput:

        A function call output item in a Realtime conversation.

        • String callId

          The ID of the function call this output is for.

        • String output

          The output of the function call, this is free text and can contain any information or simply be empty.

        • JsonValue; type "function_call_output"constant

          The type of the item. Always function_call_output.

          • FUNCTION_CALL_OUTPUT("function_call_output")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeMcpApprovalResponse:

        A Realtime item responding to an MCP approval request.

        • String id

          The unique ID of the approval response.

        • String approvalRequestId

          The ID of the approval request being answered.

        • boolean approve

          Whether the request was approved.

        • JsonValue; type "mcp_approval_response"constant

          The type of the item. Always mcp_approval_response.

          • MCP_APPROVAL_RESPONSE("mcp_approval_response")
        • Optional<String> reason

          Optional reason for the decision.

      • class RealtimeMcpListTools:

        A Realtime item listing tools available on an MCP server.

        • String serverLabel

          The label of the MCP server.

        • List<Tool> tools

          The tools available on the server.

          • JsonValue inputSchema

            The JSON schema describing the tool's input.

          • String name

            The name of the tool.

          • Optional<JsonValue> annotations

            Additional annotations about the tool.

          • Optional<String> description

            The description of the tool.

        • JsonValue; type "mcp_list_tools"constant

          The type of the item. Always mcp_list_tools.

          • MCP_LIST_TOOLS("mcp_list_tools")
        • Optional<String> id

          The unique ID of the list.

      • class RealtimeMcpToolCall:

        A Realtime item representing an invocation of a tool on an MCP server.

        • String id

          The unique ID of the tool call.

        • String arguments

          A JSON string of the arguments passed to the tool.

        • String name

          The name of the tool that was run.

        • String serverLabel

          The label of the MCP server running the tool.

        • JsonValue; type "mcp_call"constant

          The type of the item. Always mcp_call.

          • MCP_CALL("mcp_call")
        • Optional<String> approvalRequestId

          The ID of an associated approval request, if any.

        • Optional<Error> error

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError:

            • long code

            • String message

            • JsonValue; type "protocol_error"constant

              • PROTOCOL_ERROR("protocol_error")
          • class RealtimeMcpToolExecutionError:

            • String message

            • JsonValue; type "tool_execution_error"constant

              • TOOL_EXECUTION_ERROR("tool_execution_error")
          • class RealtimeMcphttpError:

            • long code

            • String message

            • JsonValue; type "http_error"constant

              • HTTP_ERROR("http_error")
        • Optional<String> output

          The output from the tool call.

      • class RealtimeMcpApprovalRequest:

        A Realtime item requesting human approval of a tool invocation.

        • String id

          The unique ID of the approval request.

        • String arguments

          A JSON string of arguments for the tool.

        • String name

          The name of the tool to run.

        • String serverLabel

          The label of the MCP server making the request.

        • JsonValue; type "mcp_approval_request"constant

          The type of the item. Always mcp_approval_request.

          • MCP_APPROVAL_REQUEST("mcp_approval_request")
    • JsonValue; type "conversation.item.done"constant

      The event type, must be conversation.item.done.

      • CONVERSATION_ITEM_DONE("conversation.item.done")
    • Optional<String> previousItemId

      The ID of the item that precedes this one, if any. This is used to maintain ordering when items are inserted.

Conversation Item Input Audio Transcription Completed Event

  • class ConversationItemInputAudioTranscriptionCompletedEvent:

    This event is the output of audio transcription for user audio written to the user audio buffer. Transcription begins when the input audio buffer is committed by the client or server (when VAD is enabled). Transcription runs asynchronously with Response creation, so this event may come before or after the Response events.

    Realtime API models accept audio natively, and thus input transcription is a separate process run on a separate ASR (Automatic Speech Recognition) model. The transcript may diverge somewhat from the model's interpretation, and should be treated as a rough guide.

    • long contentIndex

      The index of the content part containing the audio.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item containing the audio that is being transcribed.

    • String transcript

      The transcribed text.

    • JsonValue; type "conversation.item.input_audio_transcription.completed"constant

      The event type, must be conversation.item.input_audio_transcription.completed.

      • CONVERSATION_ITEM_INPUT_AUDIO_TRANSCRIPTION_COMPLETED("conversation.item.input_audio_transcription.completed")
    • Usage usage

      Usage statistics for the transcription, this is billed according to the ASR model's pricing rather than the realtime model's pricing.

      • class TranscriptTextUsageTokens:

        Usage statistics for models billed by token usage.

        • long inputTokens

          Number of input tokens billed for this request.

        • long outputTokens

          Number of output tokens generated.

        • long totalTokens

          Total number of tokens used (input + output).

        • JsonValue; type "tokens"constant

          The type of the usage object. Always tokens for this variant.

          • TOKENS("tokens")
        • Optional<InputTokenDetails> inputTokenDetails

          Details about the input tokens billed for this request.

          • Optional<Long> audioTokens

            Number of audio tokens billed for this request.

          • Optional<Long> textTokens

            Number of text tokens billed for this request.

      • class TranscriptTextUsageDuration:

        Usage statistics for models billed by audio input duration.

        • double seconds

          Duration of the input audio in seconds.

        • JsonValue; type "duration"constant

          The type of the usage object. Always duration for this variant.

          • DURATION("duration")
    • Optional<List<LogProbProperties>> logprobs

      The log probabilities of the transcription.

      • String token

        The token that was used to generate the log probability.

      • List<long> bytes

        The bytes that were used to generate the log probability.

      • double logprob

        The log probability of the token.

Conversation Item Input Audio Transcription Delta Event

  • class ConversationItemInputAudioTranscriptionDeltaEvent:

    Returned when the text value of an input audio transcription content part is updated with incremental transcription results.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item containing the audio that is being transcribed.

    • JsonValue; type "conversation.item.input_audio_transcription.delta"constant

      The event type, must be conversation.item.input_audio_transcription.delta.

      • CONVERSATION_ITEM_INPUT_AUDIO_TRANSCRIPTION_DELTA("conversation.item.input_audio_transcription.delta")
    • Optional<Long> contentIndex

      The index of the content part in the item's content array.

    • Optional<String> delta

      The text delta.

    • Optional<List<LogProbProperties>> logprobs

      The log probabilities of the transcription. These can be enabled by configurating the session with "include": ["item.input_audio_transcription.logprobs"]. Each entry in the array corresponds a log probability of which token would be selected for this chunk of transcription. This can help to identify if it was possible there were multiple valid options for a given chunk of transcription.

      • String token

        The token that was used to generate the log probability.

      • List<long> bytes

        The bytes that were used to generate the log probability.

      • double logprob

        The log probability of the token.

Conversation Item Input Audio Transcription Failed Event

  • class ConversationItemInputAudioTranscriptionFailedEvent:

    Returned when input audio transcription is configured, and a transcription request for a user message failed. These events are separate from other error events so that the client can identify the related Item.

    • long contentIndex

      The index of the content part containing the audio.

    • Error error

      Details of the transcription error.

      • Optional<String> code

        Error code, if any.

      • Optional<String> message

        A human-readable error message.

      • Optional<String> param

        Parameter related to the error, if any.

      • Optional<String> type

        The type of error.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the user message item.

    • JsonValue; type "conversation.item.input_audio_transcription.failed"constant

      The event type, must be conversation.item.input_audio_transcription.failed.

      • CONVERSATION_ITEM_INPUT_AUDIO_TRANSCRIPTION_FAILED("conversation.item.input_audio_transcription.failed")

Conversation Item Input Audio Transcription Segment

  • class ConversationItemInputAudioTranscriptionSegment:

    Returned when an input audio transcription segment is identified for an item.

    • String id

      The segment identifier.

    • long contentIndex

      The index of the input audio content part within the item.

    • double end

      End time of the segment in seconds.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item containing the input audio content.

    • String speaker

      The detected speaker label for this segment.

    • double start

      Start time of the segment in seconds.

    • String text

      The text for this segment.

    • JsonValue; type "conversation.item.input_audio_transcription.segment"constant

      The event type, must be conversation.item.input_audio_transcription.segment.

      • CONVERSATION_ITEM_INPUT_AUDIO_TRANSCRIPTION_SEGMENT("conversation.item.input_audio_transcription.segment")

Conversation Item Retrieve Event

  • class ConversationItemRetrieveEvent:

    Send this event when you want to retrieve the server's representation of a specific item in the conversation history. This is useful, for example, to inspect user audio after noise cancellation and VAD. The server will respond with a conversation.item.retrieved event, unless the item does not exist in the conversation history, in which case the server will respond with an error.

    • String itemId

      The ID of the item to retrieve.

    • JsonValue; type "conversation.item.retrieve"constant

      The event type, must be conversation.item.retrieve.

      • CONVERSATION_ITEM_RETRIEVE("conversation.item.retrieve")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Conversation Item Truncate Event

  • class ConversationItemTruncateEvent:

    Send this event to truncate a previous assistant message’s audio. The server will produce audio faster than realtime, so this event is useful when the user interrupts to truncate audio that has already been sent to the client but not yet played. This will synchronize the server's understanding of the audio with the client's playback.

    Truncating audio will delete the server-side text transcript to ensure there is not text in the context that hasn't been heard by the user.

    If successful, the server will respond with a conversation.item.truncated event.

    • long audioEndMs

      Inclusive duration up to which audio is truncated, in milliseconds. If the audio_end_ms is greater than the actual audio duration, the server will respond with an error.

    • long contentIndex

      The index of the content part to truncate. Set this to 0.

    • String itemId

      The ID of the assistant message item to truncate. Only assistant message items can be truncated.

    • JsonValue; type "conversation.item.truncate"constant

      The event type, must be conversation.item.truncate.

      • CONVERSATION_ITEM_TRUNCATE("conversation.item.truncate")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Conversation Item Truncated Event

  • class ConversationItemTruncatedEvent:

    Returned when an earlier assistant audio message item is truncated by the client with a conversation.item.truncate event. This event is used to synchronize the server's understanding of the audio with the client's playback.

    This action will truncate the audio and remove the server-side text transcript to ensure there is no text in the context that hasn't been heard by the user.

    • long audioEndMs

      The duration up to which the audio was truncated, in milliseconds.

    • long contentIndex

      The index of the content part that was truncated.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the assistant message item that was truncated.

    • JsonValue; type "conversation.item.truncated"constant

      The event type, must be conversation.item.truncated.

      • CONVERSATION_ITEM_TRUNCATED("conversation.item.truncated")

Conversation Item With Reference

  • class ConversationItemWithReference:

    The item to add to the conversation.

    • Optional<String> id

      For an item of type (message | function_call | function_call_output) this field allows the client to assign the unique ID of the item. It is not required because the server will generate one if not provided.

      For an item of type item_reference, this field is required and is a reference to any item that has previously existed in the conversation.

    • Optional<String> arguments

      The arguments of the function call (for function_call items).

    • Optional<String> callId

      The ID of the function call (for function_call and function_call_output items). If passed on a function_call_output item, the server will check that a function_call item with the same ID exists in the conversation history.

    • Optional<List<Content>> content

      The content of the message, applicable for message items.

      • Message items of role system support only input_text content

      • Message items of role user support input_text and input_audio content

      • Message items of role assistant support text content.

      • Optional<String> id

        ID of a previous conversation item to reference (for item_reference content types in response.create events). These can reference both client and server created items.

      • Optional<String> audio

        Base64-encoded audio bytes, used for input_audio content type.

      • Optional<String> text

        The text content, used for input_text and text content types.

      • Optional<String> transcript

        The transcript of the audio, used for input_audio content type.

      • Optional<Type> type

        The content type (input_text, input_audio, item_reference, text).

        • INPUT_TEXT("input_text")

        • INPUT_AUDIO("input_audio")

        • ITEM_REFERENCE("item_reference")

        • TEXT("text")

    • Optional<String> name

      The name of the function being called (for function_call items).

    • Optional<Object> object_

      Identifier for the API object being returned - always realtime.item.

      • REALTIME_ITEM("realtime.item")
    • Optional<String> output

      The output of the function call (for function_call_output items).

    • Optional<Role> role

      The role of the message sender (user, assistant, system), only applicable for message items.

      • USER("user")

      • ASSISTANT("assistant")

      • SYSTEM("system")

    • Optional<Status> status

      The status of the item (completed, incomplete, in_progress). These have no effect on the conversation, but are accepted for consistency with the conversation.item.created event.

      • COMPLETED("completed")

      • INCOMPLETE("incomplete")

      • IN_PROGRESS("in_progress")

    • Optional<Type> type

      The type of the item (message, function_call, function_call_output, item_reference).

      • MESSAGE("message")

      • FUNCTION_CALL("function_call")

      • FUNCTION_CALL_OUTPUT("function_call_output")

      • ITEM_REFERENCE("item_reference")

Input Audio Buffer Append Event

  • class InputAudioBufferAppendEvent:

    Send this event to append audio bytes to the input audio buffer. The audio buffer is temporary storage you can write to and later commit. A "commit" will create a new user message item in the conversation history from the buffer content and clear the buffer. Input audio transcription (if enabled) will be generated when the buffer is committed.

    If VAD is enabled the audio buffer is used to detect speech and the server will decide when to commit. When Server VAD is disabled, you must commit the audio buffer manually. Input audio noise reduction operates on writes to the audio buffer.

    The client may choose how much audio to place in each event up to a maximum of 15 MiB, for example streaming smaller chunks from the client may allow the VAD to be more responsive. Unlike most other client events, the server will not send a confirmation response to this event.

    • String audio

      Base64-encoded audio bytes. This must be in the format specified by the input_audio_format field in the session configuration.

    • JsonValue; type "input_audio_buffer.append"constant

      The event type, must be input_audio_buffer.append.

      • INPUT_AUDIO_BUFFER_APPEND("input_audio_buffer.append")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Input Audio Buffer Clear Event

  • class InputAudioBufferClearEvent:

    Send this event to clear the audio bytes in the buffer. The server will respond with an input_audio_buffer.cleared event.

    • JsonValue; type "input_audio_buffer.clear"constant

      The event type, must be input_audio_buffer.clear.

      • INPUT_AUDIO_BUFFER_CLEAR("input_audio_buffer.clear")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Input Audio Buffer Cleared Event

  • class InputAudioBufferClearedEvent:

    Returned when the input audio buffer is cleared by the client with a input_audio_buffer.clear event.

    • String eventId

      The unique ID of the server event.

    • JsonValue; type "input_audio_buffer.cleared"constant

      The event type, must be input_audio_buffer.cleared.

      • INPUT_AUDIO_BUFFER_CLEARED("input_audio_buffer.cleared")

Input Audio Buffer Commit Event

  • class InputAudioBufferCommitEvent:

    Send this event to commit the user input audio buffer, which will create a new user message item in the conversation. This event will produce an error if the input audio buffer is empty. When in Server VAD mode, the client does not need to send this event, the server will commit the audio buffer automatically.

    Committing the input audio buffer will trigger input audio transcription (if enabled in session configuration), but it will not create a response from the model. The server will respond with an input_audio_buffer.committed event.

    • JsonValue; type "input_audio_buffer.commit"constant

      The event type, must be input_audio_buffer.commit.

      • INPUT_AUDIO_BUFFER_COMMIT("input_audio_buffer.commit")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Input Audio Buffer Committed Event

  • class InputAudioBufferCommittedEvent:

    Returned when an input audio buffer is committed, either by the client or automatically in server VAD mode. The item_id property is the ID of the user message item that will be created, thus a conversation.item.created event will also be sent to the client.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the user message item that will be created.

    • JsonValue; type "input_audio_buffer.committed"constant

      The event type, must be input_audio_buffer.committed.

      • INPUT_AUDIO_BUFFER_COMMITTED("input_audio_buffer.committed")
    • Optional<String> previousItemId

      The ID of the preceding item after which the new item will be inserted. Can be null if the item has no predecessor.

Input Audio Buffer Dtmf Event Received Event

  • class InputAudioBufferDtmfEventReceivedEvent:

    SIP Only: Returned when an DTMF event is received. A DTMF event is a message that represents a telephone keypad press (0–9, *, #, A–D). The event property is the keypad that the user press. The received_at is the UTC Unix Timestamp that the server received the event.

    • String event

      The telephone keypad that was pressed by the user.

    • long receivedAt

      UTC Unix Timestamp when DTMF Event was received by server.

    • JsonValue; type "input_audio_buffer.dtmf_event_received"constant

      The event type, must be input_audio_buffer.dtmf_event_received.

      • INPUT_AUDIO_BUFFER_DTMF_EVENT_RECEIVED("input_audio_buffer.dtmf_event_received")

Input Audio Buffer Speech Started Event

  • class InputAudioBufferSpeechStartedEvent:

    Sent by the server when in server_vad mode to indicate that speech has been detected in the audio buffer. This can happen any time audio is added to the buffer (unless speech is already detected). The client may want to use this event to interrupt audio playback or provide visual feedback to the user.

    The client should expect to receive a input_audio_buffer.speech_stopped event when speech stops. The item_id property is the ID of the user message item that will be created when speech stops and will also be included in the input_audio_buffer.speech_stopped event (unless the client manually commits the audio buffer during VAD activation).

    • long audioStartMs

      Milliseconds from the start of all audio written to the buffer during the session when speech was first detected. This will correspond to the beginning of audio sent to the model, and thus includes the prefix_padding_ms configured in the Session.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the user message item that will be created when speech stops.

    • JsonValue; type "input_audio_buffer.speech_started"constant

      The event type, must be input_audio_buffer.speech_started.

      • INPUT_AUDIO_BUFFER_SPEECH_STARTED("input_audio_buffer.speech_started")

Input Audio Buffer Speech Stopped Event

  • class InputAudioBufferSpeechStoppedEvent:

    Returned in server_vad mode when the server detects the end of speech in the audio buffer. The server will also send an conversation.item.created event with the user message item that is created from the audio buffer.

    • long audioEndMs

      Milliseconds since the session started when speech stopped. This will correspond to the end of audio sent to the model, and thus includes the min_silence_duration_ms configured in the Session.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the user message item that will be created.

    • JsonValue; type "input_audio_buffer.speech_stopped"constant

      The event type, must be input_audio_buffer.speech_stopped.

      • INPUT_AUDIO_BUFFER_SPEECH_STOPPED("input_audio_buffer.speech_stopped")

Input Audio Buffer Timeout Triggered

  • class InputAudioBufferTimeoutTriggered:

    Returned when the Server VAD timeout is triggered for the input audio buffer. This is configured with idle_timeout_ms in the turn_detection settings of the session, and it indicates that there hasn't been any speech detected for the configured duration.

    The audio_start_ms and audio_end_ms fields indicate the segment of audio after the last model response up to the triggering time, as an offset from the beginning of audio written to the input audio buffer. This means it demarcates the segment of audio that was silent and the difference between the start and end values will roughly match the configured timeout.

    The empty audio will be committed to the conversation as an input_audio item (there will be a input_audio_buffer.committed event) and a model response will be generated. There may be speech that didn't trigger VAD but is still detected by the model, so the model may respond with something relevant to the conversation or a prompt to continue speaking.

    • long audioEndMs

      Millisecond offset of audio written to the input audio buffer at the time the timeout was triggered.

    • long audioStartMs

      Millisecond offset of audio written to the input audio buffer that was after the playback time of the last model response.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item associated with this segment.

    • JsonValue; type "input_audio_buffer.timeout_triggered"constant

      The event type, must be input_audio_buffer.timeout_triggered.

      • INPUT_AUDIO_BUFFER_TIMEOUT_TRIGGERED("input_audio_buffer.timeout_triggered")

Log Prob Properties

  • class LogProbProperties:

    A log probability object.

    • String token

      The token that was used to generate the log probability.

    • List<long> bytes

      The bytes that were used to generate the log probability.

    • double logprob

      The log probability of the token.

Mcp List Tools Completed

  • class McpListToolsCompleted:

    Returned when listing MCP tools has completed for an item.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the MCP list tools item.

    • JsonValue; type "mcp_list_tools.completed"constant

      The event type, must be mcp_list_tools.completed.

      • MCP_LIST_TOOLS_COMPLETED("mcp_list_tools.completed")

Mcp List Tools Failed

  • class McpListToolsFailed:

    Returned when listing MCP tools has failed for an item.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the MCP list tools item.

    • JsonValue; type "mcp_list_tools.failed"constant

      The event type, must be mcp_list_tools.failed.

      • MCP_LIST_TOOLS_FAILED("mcp_list_tools.failed")

Mcp List Tools In Progress

  • class McpListToolsInProgress:

    Returned when listing MCP tools is in progress for an item.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the MCP list tools item.

    • JsonValue; type "mcp_list_tools.in_progress"constant

      The event type, must be mcp_list_tools.in_progress.

      • MCP_LIST_TOOLS_IN_PROGRESS("mcp_list_tools.in_progress")

Noise Reduction Type

  • enum NoiseReductionType:

    Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

    • NEAR_FIELD("near_field")

    • FAR_FIELD("far_field")

Output Audio Buffer Clear Event

  • class OutputAudioBufferClearEvent:

    WebRTC/SIP Only: Emit to cut off the current audio response. This will trigger the server to stop generating audio and emit a output_audio_buffer.cleared event. This event should be preceded by a response.cancel client event to stop the generation of the current response. Learn more.

    • JsonValue; type "output_audio_buffer.clear"constant

      The event type, must be output_audio_buffer.clear.

      • OUTPUT_AUDIO_BUFFER_CLEAR("output_audio_buffer.clear")
    • Optional<String> eventId

      The unique ID of the client event used for error handling.

Rate Limits Updated Event

  • class RateLimitsUpdatedEvent:

    Emitted at the beginning of a Response to indicate the updated rate limits. When a Response is created some tokens will be "reserved" for the output tokens, the rate limits shown here reflect that reservation, which is then adjusted accordingly once the Response is completed.

    • String eventId

      The unique ID of the server event.

    • List<RateLimit> rateLimits

      List of rate limit information.

      • Optional<Long> limit

        The maximum allowed value for the rate limit.

      • Optional<Name> name

        The name of the rate limit (requests, tokens).

        • REQUESTS("requests")

        • TOKENS("tokens")

      • Optional<Long> remaining

        The remaining value before the limit is reached.

      • Optional<Double> resetSeconds

        Seconds until the rate limit resets.

    • JsonValue; type "rate_limits.updated"constant

      The event type, must be rate_limits.updated.

      • RATE_LIMITS_UPDATED("rate_limits.updated")

Realtime Audio Config

  • class RealtimeAudioConfig:

    Configuration for input and output audio.

    • Optional<RealtimeAudioConfigInput> input

      • Optional<RealtimeAudioFormats> format

        The format of the input audio.

        • AudioPcm

          • Optional<Rate> rate

            The sample rate of the audio. Always 24000.

            • _24000(24000)
          • Optional<Type> type

            The audio format. Always audio/pcm.

            • AUDIO_PCM("audio/pcm")
        • AudioPcmu

          • Optional<Type> type

            The audio format. Always audio/pcmu.

            • AUDIO_PCMU("audio/pcmu")
        • AudioPcma

          • Optional<Type> type

            The audio format. Always audio/pcma.

            • AUDIO_PCMA("audio/pcma")
      • Optional<NoiseReduction> noiseReduction

        Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

        • Optional<NoiseReductionType> type

          Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

          • NEAR_FIELD("near_field")

          • FAR_FIELD("far_field")

      • Optional<AudioTranscription> transcription

        Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

        • Optional<Delay> delay

          Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

          • MINIMAL("minimal")

          • LOW("low")

          • MEDIUM("medium")

          • HIGH("high")

          • XHIGH("xhigh")

        • Optional<String> language

          The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

        • Optional<Model> model

          The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

          • WHISPER_1("whisper-1")

          • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

          • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

          • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

          • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

          • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

        • Optional<String> prompt

          An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

      • Optional<RealtimeAudioInputTurnDetection> turnDetection

        Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

        Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

        Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

        For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

        • ServerVad

          • JsonValue; type "server_vad"constant

            Type of turn detection, server_vad to turn on simple Server VAD.

            • SERVER_VAD("server_vad")
          • Optional<Boolean> createResponse

            Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

            If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

          • Optional<Long> idleTimeoutMs

            Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

            The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

            An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

          • Optional<Boolean> interruptResponse

            Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

            If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

          • Optional<Long> prefixPaddingMs

            Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

          • Optional<Long> silenceDurationMs

            Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

          • Optional<Double> threshold

            Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

        • SemanticVad

          • JsonValue; type "semantic_vad"constant

            Type of turn detection, semantic_vad to turn on Semantic VAD.

            • SEMANTIC_VAD("semantic_vad")
          • Optional<Boolean> createResponse

            Whether or not to automatically generate a response when a VAD stop event occurs.

          • Optional<Eagerness> eagerness

            Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • AUTO("auto")

          • Optional<Boolean> interruptResponse

            Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

    • Optional<RealtimeAudioConfigOutput> output

      • Optional<RealtimeAudioFormats> format

        The format of the output audio.

      • Optional<Double> speed

        The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

        This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

      • Optional<Voice> voice

        The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

        • String

        • enum UnionMember1:

          • ALLOY("alloy")

          • ASH("ash")

          • BALLAD("ballad")

          • CORAL("coral")

          • ECHO("echo")

          • SAGE("sage")

          • SHIMMER("shimmer")

          • VERSE("verse")

          • MARIN("marin")

          • CEDAR("cedar")

        • class Id:

          Custom voice reference.

          • String id

            The custom voice ID, e.g. voice_1234.

Realtime Audio Config Input

  • class RealtimeAudioConfigInput:

    • Optional<RealtimeAudioFormats> format

      The format of the input audio.

      • AudioPcm

        • Optional<Rate> rate

          The sample rate of the audio. Always 24000.

          • _24000(24000)
        • Optional<Type> type

          The audio format. Always audio/pcm.

          • AUDIO_PCM("audio/pcm")
      • AudioPcmu

        • Optional<Type> type

          The audio format. Always audio/pcmu.

          • AUDIO_PCMU("audio/pcmu")
      • AudioPcma

        • Optional<Type> type

          The audio format. Always audio/pcma.

          • AUDIO_PCMA("audio/pcma")
    • Optional<NoiseReduction> noiseReduction

      Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

      • Optional<NoiseReductionType> type

        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

        • NEAR_FIELD("near_field")

        • FAR_FIELD("far_field")

    • Optional<AudioTranscription> transcription

      Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

      • Optional<Delay> delay

        Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

        • MINIMAL("minimal")

        • LOW("low")

        • MEDIUM("medium")

        • HIGH("high")

        • XHIGH("xhigh")

      • Optional<String> language

        The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

      • Optional<Model> model

        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

        • WHISPER_1("whisper-1")

        • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

        • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

        • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

        • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

        • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

      • Optional<String> prompt

        An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

    • Optional<RealtimeAudioInputTurnDetection> turnDetection

      Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

      Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

      Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

      For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

      • ServerVad

        • JsonValue; type "server_vad"constant

          Type of turn detection, server_vad to turn on simple Server VAD.

          • SERVER_VAD("server_vad")
        • Optional<Boolean> createResponse

          Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

          If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

        • Optional<Long> idleTimeoutMs

          Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

          The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

          An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

        • Optional<Boolean> interruptResponse

          Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

          If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

        • Optional<Long> prefixPaddingMs

          Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

        • Optional<Long> silenceDurationMs

          Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

        • Optional<Double> threshold

          Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

      • SemanticVad

        • JsonValue; type "semantic_vad"constant

          Type of turn detection, semantic_vad to turn on Semantic VAD.

          • SEMANTIC_VAD("semantic_vad")
        • Optional<Boolean> createResponse

          Whether or not to automatically generate a response when a VAD stop event occurs.

        • Optional<Eagerness> eagerness

          Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

          • LOW("low")

          • MEDIUM("medium")

          • HIGH("high")

          • AUTO("auto")

        • Optional<Boolean> interruptResponse

          Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

Realtime Audio Config Output

  • class RealtimeAudioConfigOutput:

    • Optional<RealtimeAudioFormats> format

      The format of the output audio.

      • AudioPcm

        • Optional<Rate> rate

          The sample rate of the audio. Always 24000.

          • _24000(24000)
        • Optional<Type> type

          The audio format. Always audio/pcm.

          • AUDIO_PCM("audio/pcm")
      • AudioPcmu

        • Optional<Type> type

          The audio format. Always audio/pcmu.

          • AUDIO_PCMU("audio/pcmu")
      • AudioPcma

        • Optional<Type> type

          The audio format. Always audio/pcma.

          • AUDIO_PCMA("audio/pcma")
    • Optional<Double> speed

      The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

      This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

    • Optional<Voice> voice

      The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

      • String

      • enum UnionMember1:

        • ALLOY("alloy")

        • ASH("ash")

        • BALLAD("ballad")

        • CORAL("coral")

        • ECHO("echo")

        • SAGE("sage")

        • SHIMMER("shimmer")

        • VERSE("verse")

        • MARIN("marin")

        • CEDAR("cedar")

      • class Id:

        Custom voice reference.

        • String id

          The custom voice ID, e.g. voice_1234.

Realtime Audio Formats

  • class RealtimeAudioFormats: A class that can be one of several variants.union

    The PCM audio format. Only a 24kHz sample rate is supported.

    • AudioPcm

      • Optional<Rate> rate

        The sample rate of the audio. Always 24000.

        • _24000(24000)
      • Optional<Type> type

        The audio format. Always audio/pcm.

        • AUDIO_PCM("audio/pcm")
    • AudioPcmu

      • Optional<Type> type

        The audio format. Always audio/pcmu.

        • AUDIO_PCMU("audio/pcmu")
    • AudioPcma

      • Optional<Type> type

        The audio format. Always audio/pcma.

        • AUDIO_PCMA("audio/pcma")

Realtime Audio Input Turn Detection

  • class RealtimeAudioInputTurnDetection: A class that can be one of several variants.union

    Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

    Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

    Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

    For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

    • ServerVad

      • JsonValue; type "server_vad"constant

        Type of turn detection, server_vad to turn on simple Server VAD.

        • SERVER_VAD("server_vad")
      • Optional<Boolean> createResponse

        Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

      • Optional<Long> idleTimeoutMs

        Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

        The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

        An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

      • Optional<Boolean> interruptResponse

        Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

      • Optional<Long> prefixPaddingMs

        Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

      • Optional<Long> silenceDurationMs

        Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

      • Optional<Double> threshold

        Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

    • SemanticVad

      • JsonValue; type "semantic_vad"constant

        Type of turn detection, semantic_vad to turn on Semantic VAD.

        • SEMANTIC_VAD("semantic_vad")
      • Optional<Boolean> createResponse

        Whether or not to automatically generate a response when a VAD stop event occurs.

      • Optional<Eagerness> eagerness

        Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

        • LOW("low")

        • MEDIUM("medium")

        • HIGH("high")

        • AUTO("auto")

      • Optional<Boolean> interruptResponse

        Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

Realtime Client Event

  • class RealtimeClientEvent: A class that can be one of several variants.union

    A realtime client event.

    • class ConversationItemCreateEvent:

      Add a new Item to the Conversation's context, including messages, function calls, and function call responses. This event can be used both to populate a "history" of the conversation and to add new items mid-stream, but has the current limitation that it cannot populate assistant audio messages.

      If successful, the server will respond with a conversation.item.created event, otherwise an error event will be sent.

      • ConversationItem item

        A single item within a Realtime conversation.

        • class RealtimeConversationItemSystemMessage:

          A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

          • List<Content> content

            The content of the message.

            • Optional<String> text

              The text content.

            • Optional<Type> type

              The content type. Always input_text for system messages.

              • INPUT_TEXT("input_text")
          • JsonValue; role "system"constant

            The role of the message sender. Always system.

            • SYSTEM("system")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemUserMessage:

          A user message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<Detail> detail

              The detail level of the image (for input_image). auto will default to high.

              • AUTO("auto")

              • LOW("low")

              • HIGH("high")

            • Optional<String> imageUrl

              Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

            • Optional<String> text

              The text content (for input_text).

            • Optional<String> transcript

              Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

            • Optional<Type> type

              The content type (input_text, input_audio, or input_image).

              • INPUT_TEXT("input_text")

              • INPUT_AUDIO("input_audio")

              • INPUT_IMAGE("input_image")

          • JsonValue; role "user"constant

            The role of the message sender. Always user.

            • USER("user")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemAssistantMessage:

          An assistant message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<String> text

              The text content.

            • Optional<String> transcript

              The transcript of the audio content, this will always be present if the output type is audio.

            • Optional<Type> type

              The content type, output_text or output_audio depending on the session output_modalities configuration.

              • OUTPUT_TEXT("output_text")

              • OUTPUT_AUDIO("output_audio")

          • JsonValue; role "assistant"constant

            The role of the message sender. Always assistant.

            • ASSISTANT("assistant")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCall:

          A function call item in a Realtime conversation.

          • String arguments

            The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

          • String name

            The name of the function being called.

          • JsonValue; type "function_call"constant

            The type of the item. Always function_call.

            • FUNCTION_CALL("function_call")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<String> callId

            The ID of the function call.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCallOutput:

          A function call output item in a Realtime conversation.

          • String callId

            The ID of the function call this output is for.

          • String output

            The output of the function call, this is free text and can contain any information or simply be empty.

          • JsonValue; type "function_call_output"constant

            The type of the item. Always function_call_output.

            • FUNCTION_CALL_OUTPUT("function_call_output")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeMcpApprovalResponse:

          A Realtime item responding to an MCP approval request.

          • String id

            The unique ID of the approval response.

          • String approvalRequestId

            The ID of the approval request being answered.

          • boolean approve

            Whether the request was approved.

          • JsonValue; type "mcp_approval_response"constant

            The type of the item. Always mcp_approval_response.

            • MCP_APPROVAL_RESPONSE("mcp_approval_response")
          • Optional<String> reason

            Optional reason for the decision.

        • class RealtimeMcpListTools:

          A Realtime item listing tools available on an MCP server.

          • String serverLabel

            The label of the MCP server.

          • List<Tool> tools

            The tools available on the server.

            • JsonValue inputSchema

              The JSON schema describing the tool's input.

            • String name

              The name of the tool.

            • Optional<JsonValue> annotations

              Additional annotations about the tool.

            • Optional<String> description

              The description of the tool.

          • JsonValue; type "mcp_list_tools"constant

            The type of the item. Always mcp_list_tools.

            • MCP_LIST_TOOLS("mcp_list_tools")
          • Optional<String> id

            The unique ID of the list.

        • class RealtimeMcpToolCall:

          A Realtime item representing an invocation of a tool on an MCP server.

          • String id

            The unique ID of the tool call.

          • String arguments

            A JSON string of the arguments passed to the tool.

          • String name

            The name of the tool that was run.

          • String serverLabel

            The label of the MCP server running the tool.

          • JsonValue; type "mcp_call"constant

            The type of the item. Always mcp_call.

            • MCP_CALL("mcp_call")
          • Optional<String> approvalRequestId

            The ID of an associated approval request, if any.

          • Optional<Error> error

            The error from the tool call, if any.

            • class RealtimeMcpProtocolError:

              • long code

              • String message

              • JsonValue; type "protocol_error"constant

                • PROTOCOL_ERROR("protocol_error")
            • class RealtimeMcpToolExecutionError:

              • String message

              • JsonValue; type "tool_execution_error"constant

                • TOOL_EXECUTION_ERROR("tool_execution_error")
            • class RealtimeMcphttpError:

              • long code

              • String message

              • JsonValue; type "http_error"constant

                • HTTP_ERROR("http_error")
          • Optional<String> output

            The output from the tool call.

        • class RealtimeMcpApprovalRequest:

          A Realtime item requesting human approval of a tool invocation.

          • String id

            The unique ID of the approval request.

          • String arguments

            A JSON string of arguments for the tool.

          • String name

            The name of the tool to run.

          • String serverLabel

            The label of the MCP server making the request.

          • JsonValue; type "mcp_approval_request"constant

            The type of the item. Always mcp_approval_request.

            • MCP_APPROVAL_REQUEST("mcp_approval_request")
      • JsonValue; type "conversation.item.create"constant

        The event type, must be conversation.item.create.

        • CONVERSATION_ITEM_CREATE("conversation.item.create")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

      • Optional<String> previousItemId

        The ID of the preceding item after which the new item will be inserted. If not set, the new item will be appended to the end of the conversation.

        If set to root, the new item will be added to the beginning of the conversation.

        If set to an existing ID, it allows an item to be inserted mid-conversation. If the ID cannot be found, an error will be returned and the item will not be added.

    • class ConversationItemDeleteEvent:

      Send this event when you want to remove any item from the conversation history. The server will respond with a conversation.item.deleted event, unless the item does not exist in the conversation history, in which case the server will respond with an error.

      • String itemId

        The ID of the item to delete.

      • JsonValue; type "conversation.item.delete"constant

        The event type, must be conversation.item.delete.

        • CONVERSATION_ITEM_DELETE("conversation.item.delete")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

    • class ConversationItemRetrieveEvent:

      Send this event when you want to retrieve the server's representation of a specific item in the conversation history. This is useful, for example, to inspect user audio after noise cancellation and VAD. The server will respond with a conversation.item.retrieved event, unless the item does not exist in the conversation history, in which case the server will respond with an error.

      • String itemId

        The ID of the item to retrieve.

      • JsonValue; type "conversation.item.retrieve"constant

        The event type, must be conversation.item.retrieve.

        • CONVERSATION_ITEM_RETRIEVE("conversation.item.retrieve")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

    • class ConversationItemTruncateEvent:

      Send this event to truncate a previous assistant message’s audio. The server will produce audio faster than realtime, so this event is useful when the user interrupts to truncate audio that has already been sent to the client but not yet played. This will synchronize the server's understanding of the audio with the client's playback.

      Truncating audio will delete the server-side text transcript to ensure there is not text in the context that hasn't been heard by the user.

      If successful, the server will respond with a conversation.item.truncated event.

      • long audioEndMs

        Inclusive duration up to which audio is truncated, in milliseconds. If the audio_end_ms is greater than the actual audio duration, the server will respond with an error.

      • long contentIndex

        The index of the content part to truncate. Set this to 0.

      • String itemId

        The ID of the assistant message item to truncate. Only assistant message items can be truncated.

      • JsonValue; type "conversation.item.truncate"constant

        The event type, must be conversation.item.truncate.

        • CONVERSATION_ITEM_TRUNCATE("conversation.item.truncate")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

    • class InputAudioBufferAppendEvent:

      Send this event to append audio bytes to the input audio buffer. The audio buffer is temporary storage you can write to and later commit. A "commit" will create a new user message item in the conversation history from the buffer content and clear the buffer. Input audio transcription (if enabled) will be generated when the buffer is committed.

      If VAD is enabled the audio buffer is used to detect speech and the server will decide when to commit. When Server VAD is disabled, you must commit the audio buffer manually. Input audio noise reduction operates on writes to the audio buffer.

      The client may choose how much audio to place in each event up to a maximum of 15 MiB, for example streaming smaller chunks from the client may allow the VAD to be more responsive. Unlike most other client events, the server will not send a confirmation response to this event.

      • String audio

        Base64-encoded audio bytes. This must be in the format specified by the input_audio_format field in the session configuration.

      • JsonValue; type "input_audio_buffer.append"constant

        The event type, must be input_audio_buffer.append.

        • INPUT_AUDIO_BUFFER_APPEND("input_audio_buffer.append")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

    • class InputAudioBufferClearEvent:

      Send this event to clear the audio bytes in the buffer. The server will respond with an input_audio_buffer.cleared event.

      • JsonValue; type "input_audio_buffer.clear"constant

        The event type, must be input_audio_buffer.clear.

        • INPUT_AUDIO_BUFFER_CLEAR("input_audio_buffer.clear")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

    • class OutputAudioBufferClearEvent:

      WebRTC/SIP Only: Emit to cut off the current audio response. This will trigger the server to stop generating audio and emit a output_audio_buffer.cleared event. This event should be preceded by a response.cancel client event to stop the generation of the current response. Learn more.

      • JsonValue; type "output_audio_buffer.clear"constant

        The event type, must be output_audio_buffer.clear.

        • OUTPUT_AUDIO_BUFFER_CLEAR("output_audio_buffer.clear")
      • Optional<String> eventId

        The unique ID of the client event used for error handling.

    • class InputAudioBufferCommitEvent:

      Send this event to commit the user input audio buffer, which will create a new user message item in the conversation. This event will produce an error if the input audio buffer is empty. When in Server VAD mode, the client does not need to send this event, the server will commit the audio buffer automatically.

      Committing the input audio buffer will trigger input audio transcription (if enabled in session configuration), but it will not create a response from the model. The server will respond with an input_audio_buffer.committed event.

      • JsonValue; type "input_audio_buffer.commit"constant

        The event type, must be input_audio_buffer.commit.

        • INPUT_AUDIO_BUFFER_COMMIT("input_audio_buffer.commit")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

    • class ResponseCancelEvent:

      Send this event to cancel an in-progress response. The server will respond with a response.done event with a status of response.status=cancelled. If there is no response to cancel, the server will respond with an error. It's safe to call response.cancel even if no response is in progress, an error will be returned the session will remain unaffected.

      • JsonValue; type "response.cancel"constant

        The event type, must be response.cancel.

        • RESPONSE_CANCEL("response.cancel")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

      • Optional<String> responseId

        A specific response ID to cancel - if not provided, will cancel an in-progress response in the default conversation.

    • class ResponseCreateEvent:

      This event instructs the server to create a Response, which means triggering model inference. When in Server VAD mode, the server will create Responses automatically.

      A Response will include at least one Item, and may have two, in which case the second will be a function call. These Items will be appended to the conversation history by default.

      The server will respond with a response.created event, events for Items and content created, and finally a response.done event to indicate the Response is complete.

      The response.create event includes inference configuration like instructions and tools. If these are set, they will override the Session's configuration for this Response only.

      Responses can be created out-of-band of the default Conversation, meaning that they can have arbitrary input, and it's possible to disable writing the output to the Conversation. Only one Response can write to the default Conversation at a time, but otherwise multiple Responses can be created in parallel. The metadata field is a good way to disambiguate multiple simultaneous Responses.

      Clients can set conversation to none to create a Response that does not write to the default Conversation. Arbitrary input can be provided with the input field, which is an array accepting raw Items and references to existing Items.

      • JsonValue; type "response.create"constant

        The event type, must be response.create.

        • RESPONSE_CREATE("response.create")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

      • Optional<RealtimeResponseCreateParams> response

        Create a new Realtime response with these parameters

        • Optional<RealtimeResponseCreateAudioOutput> audio

          Configuration for audio input and output.

          • Optional<Output> output

            • Optional<RealtimeAudioFormats> format

              The format of the output audio.

              • AudioPcm

                • Optional<Rate> rate

                  The sample rate of the audio. Always 24000.

                  • _24000(24000)
                • Optional<Type> type

                  The audio format. Always audio/pcm.

                  • AUDIO_PCM("audio/pcm")
              • AudioPcmu

                • Optional<Type> type

                  The audio format. Always audio/pcmu.

                  • AUDIO_PCMU("audio/pcmu")
              • AudioPcma

                • Optional<Type> type

                  The audio format. Always audio/pcma.

                  • AUDIO_PCMA("audio/pcma")
            • Optional<Voice> voice

              The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

              • String

              • enum UnionMember1:

                • ALLOY("alloy")

                • ASH("ash")

                • BALLAD("ballad")

                • CORAL("coral")

                • ECHO("echo")

                • SAGE("sage")

                • SHIMMER("shimmer")

                • VERSE("verse")

                • MARIN("marin")

                • CEDAR("cedar")

              • class Id:

                Custom voice reference.

                • String id

                  The custom voice ID, e.g. voice_1234.

        • Optional<Conversation> conversation

          Controls which conversation the response is added to. Currently supports auto and none, with auto as the default value. The auto value means that the contents of the response will be added to the default conversation. Set this to none to create an out-of-band response which will not add items to default conversation.

          • AUTO("auto")

          • NONE("none")

        • Optional<List<ConversationItem>> input

          Input items to include in the prompt for the model. Using this field creates a new context for this Response instead of using the default conversation. An empty array [] will clear the context for this Response. Note that this can include references to items that previously appeared in the session using their id.

          • class RealtimeConversationItemSystemMessage:

            A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

          • class RealtimeConversationItemUserMessage:

            A user message item in a Realtime conversation.

          • class RealtimeConversationItemAssistantMessage:

            An assistant message item in a Realtime conversation.

          • class RealtimeConversationItemFunctionCall:

            A function call item in a Realtime conversation.

          • class RealtimeConversationItemFunctionCallOutput:

            A function call output item in a Realtime conversation.

          • class RealtimeMcpApprovalResponse:

            A Realtime item responding to an MCP approval request.

          • class RealtimeMcpListTools:

            A Realtime item listing tools available on an MCP server.

          • class RealtimeMcpToolCall:

            A Realtime item representing an invocation of a tool on an MCP server.

          • class RealtimeMcpApprovalRequest:

            A Realtime item requesting human approval of a tool invocation.

        • Optional<String> instructions

          The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior. Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

        • Optional<MaxOutputTokens> maxOutputTokens

          Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

          • long

          • JsonValue;

            • INF("inf")
        • Optional<Metadata> metadata

          Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

          Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

        • Optional<List<OutputModality>> outputModalities

          The set of modalities the model used to respond, currently the only possible values are [\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the output to mode text will disable audio output from the model.

          • TEXT("text")

          • AUDIO("audio")

        • Optional<Boolean> parallelToolCalls

          Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

        • Optional<ResponsePrompt> prompt

          Reference to a prompt template and its variables. Learn more.

          • String id

            The unique identifier of the prompt template to use.

          • Optional<Variables> variables

            Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

            • String

            • class ResponseInputText:

              A text input to the model.

              • String text

                The text input to the model.

              • JsonValue; type "input_text"constant

                The type of the input item. Always input_text.

                • INPUT_TEXT("input_text")
            • class ResponseInputImage:

              An image input to the model. Learn about image inputs.

              • Detail detail

                The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

                • LOW("low")

                • HIGH("high")

                • AUTO("auto")

                • ORIGINAL("original")

              • JsonValue; type "input_image"constant

                The type of the input item. Always input_image.

                • INPUT_IMAGE("input_image")
              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> imageUrl

                The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

            • class ResponseInputFile:

              A file input to the model.

              • JsonValue; type "input_file"constant

                The type of the input item. Always input_file.

                • INPUT_FILE("input_file")
              • Optional<Detail> detail

                The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

                • LOW("low")

                • HIGH("high")

              • Optional<String> fileData

                The content of the file to be sent to the model.

              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> fileUrl

                The URL of the file to be sent to the model.

              • Optional<String> filename

                The name of the file to be sent to the model.

          • Optional<String> version

            Optional version of the prompt template.

        • Optional<RealtimeReasoning> reasoning

          Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

          • Optional<RealtimeReasoningEffort> effort

            Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

        • Optional<ToolChoice> toolChoice

          How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

          • enum ToolChoiceOptions:

            Controls which (if any) tool is called by the model.

            none means the model will not call any tool and instead generates a message.

            auto means the model can pick between generating a message or calling one or more tools.

            required means the model must call one or more tools.

            • NONE("none")

            • AUTO("auto")

            • REQUIRED("required")

          • class ToolChoiceFunction:

            Use this option to force the model to call a specific function.

            • String name

              The name of the function to call.

            • JsonValue; type "function"constant

              For function calling, the type is always function.

              • FUNCTION("function")
          • class ToolChoiceMcp:

            Use this option to force the model to call a specific tool on a remote MCP server.

            • String serverLabel

              The label of the MCP server to use.

            • JsonValue; type "mcp"constant

              For MCP tools, the type is always mcp.

              • MCP("mcp")
            • Optional<String> name

              The name of the tool to call on the server.

        • Optional<List<Tool>> tools

          Tools available to the model.

          • class RealtimeFunctionTool:

            • Optional<String> description

              The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

            • Optional<String> name

              The name of the function.

            • Optional<JsonValue> parameters

              Parameters of the function in JSON Schema.

            • Optional<Type> type

              The type of the tool, i.e. function.

              • FUNCTION("function")
          • class RealtimeResponseCreateMcpTool:

            Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

            • String serverLabel

              A label for this MCP server, used to identify it in tool calls.

            • JsonValue; type "mcp"constant

              The type of the MCP tool. Always mcp.

              • MCP("mcp")
            • Optional<AllowedTools> allowedTools

              List of allowed tool names or a filter object.

              • List<String>

              • class McpToolFilter:

                A filter object to specify which tools are allowed.

                • Optional<Boolean> readOnly

                  Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                • Optional<List<String>> toolNames

                  List of allowed tool names.

            • Optional<String> authorization

              An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

            • Optional<ConnectorId> connectorId

              Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

              Currently supported connector_id values are:

              • Dropbox: connector_dropbox

              • Gmail: connector_gmail

              • Google Calendar: connector_googlecalendar

              • Google Drive: connector_googledrive

              • Microsoft Teams: connector_microsoftteams

              • Outlook Calendar: connector_outlookcalendar

              • Outlook Email: connector_outlookemail

              • SharePoint: connector_sharepoint

              • CONNECTOR_DROPBOX("connector_dropbox")

              • CONNECTOR_GMAIL("connector_gmail")

              • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

              • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

              • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

              • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

              • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

              • CONNECTOR_SHAREPOINT("connector_sharepoint")

            • Optional<Boolean> deferLoading

              Whether this MCP tool is deferred and discovered via tool search.

            • Optional<Headers> headers

              Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

            • Optional<RequireApproval> requireApproval

              Specify which of the MCP server's tools require approval.

              • class McpToolApprovalFilter:

                Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

                • Optional<Always> always

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

                • Optional<Never> never

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

              • enum McpToolApprovalSetting:

                Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

                • ALWAYS("always")

                • NEVER("never")

            • Optional<String> serverDescription

              Optional description of the MCP server, used to provide more context.

            • Optional<String> serverUrl

              The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

            • Optional<String> tunnelId

              The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

    • class SessionUpdateEvent:

      Send this event to update the session’s configuration. The client may send this event at any time to update any field except for voice and model. voice can be updated only if there have been no other audio outputs yet.

      When the server receives a session.update, it will respond with a session.updated event showing the full, effective configuration. Only the fields that are present in the session.update are updated. To clear a field like instructions, pass an empty string. To clear a field like tools, pass an empty array. To clear a field like turn_detection, pass null.

      • Session session

        Update the Realtime session. Choose either a realtime session or a transcription session.

        • class RealtimeSessionCreateRequest:

          Realtime session object configuration.

          • JsonValue; type "realtime"constant

            The type of session to create. Always realtime for the Realtime API.

            • REALTIME("realtime")
          • Optional<RealtimeAudioConfig> audio

            Configuration for input and output audio.

            • Optional<RealtimeAudioConfigInput> input

              • Optional<RealtimeAudioFormats> format

                The format of the input audio.

              • Optional<NoiseReduction> noiseReduction

                Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

                • Optional<NoiseReductionType> type

                  Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                  • NEAR_FIELD("near_field")

                  • FAR_FIELD("far_field")

              • Optional<AudioTranscription> transcription

                Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

                • Optional<Delay> delay

                  Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

                  • MINIMAL("minimal")

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • XHIGH("xhigh")

                • Optional<String> language

                  The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

                • Optional<Model> model

                  The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

                  • WHISPER_1("whisper-1")

                  • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

                  • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

                  • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

                  • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

                  • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

                • Optional<String> prompt

                  An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

              • Optional<RealtimeAudioInputTurnDetection> turnDetection

                Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

                Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

                Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

                For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

                • ServerVad

                  • JsonValue; type "server_vad"constant

                    Type of turn detection, server_vad to turn on simple Server VAD.

                    • SERVER_VAD("server_vad")
                  • Optional<Boolean> createResponse

                    Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                    If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                  • Optional<Long> idleTimeoutMs

                    Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                    The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                    An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                  • Optional<Boolean> interruptResponse

                    Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                    If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                  • Optional<Long> prefixPaddingMs

                    Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                  • Optional<Long> silenceDurationMs

                    Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                  • Optional<Double> threshold

                    Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

                • SemanticVad

                  • JsonValue; type "semantic_vad"constant

                    Type of turn detection, semantic_vad to turn on Semantic VAD.

                    • SEMANTIC_VAD("semantic_vad")
                  • Optional<Boolean> createResponse

                    Whether or not to automatically generate a response when a VAD stop event occurs.

                  • Optional<Eagerness> eagerness

                    Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                    • LOW("low")

                    • MEDIUM("medium")

                    • HIGH("high")

                    • AUTO("auto")

                  • Optional<Boolean> interruptResponse

                    Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

            • Optional<RealtimeAudioConfigOutput> output

              • Optional<RealtimeAudioFormats> format

                The format of the output audio.

              • Optional<Double> speed

                The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

                This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

              • Optional<Voice> voice

                The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

                • String

                • enum UnionMember1:

                  • ALLOY("alloy")

                  • ASH("ash")

                  • BALLAD("ballad")

                  • CORAL("coral")

                  • ECHO("echo")

                  • SAGE("sage")

                  • SHIMMER("shimmer")

                  • VERSE("verse")

                  • MARIN("marin")

                  • CEDAR("cedar")

                • class Id:

                  Custom voice reference.

                  • String id

                    The custom voice ID, e.g. voice_1234.

          • Optional<List<Include>> include

            Additional fields to include in server outputs.

            item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

            • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
          • Optional<String> instructions

            The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

            Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

          • Optional<MaxOutputTokens> maxOutputTokens

            Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

            • long

            • JsonValue;

              • INF("inf")
          • Optional<Model> model

            The Realtime model used for this session.

            • GPT_REALTIME("gpt-realtime")

            • GPT_REALTIME_1_5("gpt-realtime-1.5")

            • GPT_REALTIME_2("gpt-realtime-2")

            • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

            • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

            • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

            • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

            • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

            • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

            • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

            • GPT_REALTIME_MINI("gpt-realtime-mini")

            • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

            • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

            • GPT_AUDIO_1_5("gpt-audio-1.5")

            • GPT_AUDIO_MINI("gpt-audio-mini")

            • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

            • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

          • Optional<List<OutputModality>> outputModalities

            The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

            • TEXT("text")

            • AUDIO("audio")

          • Optional<Boolean> parallelToolCalls

            Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

          • Optional<ResponsePrompt> prompt

            Reference to a prompt template and its variables. Learn more.

          • Optional<RealtimeReasoning> reasoning

            Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

          • Optional<RealtimeToolChoiceConfig> toolChoice

            How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

            • enum ToolChoiceOptions:

              Controls which (if any) tool is called by the model.

              none means the model will not call any tool and instead generates a message.

              auto means the model can pick between generating a message or calling one or more tools.

              required means the model must call one or more tools.

            • class ToolChoiceFunction:

              Use this option to force the model to call a specific function.

            • class ToolChoiceMcp:

              Use this option to force the model to call a specific tool on a remote MCP server.

          • Optional<List<RealtimeToolsConfigUnion>> tools

            Tools available to the model.

            • class RealtimeFunctionTool:

            • Mcp

              • String serverLabel

                A label for this MCP server, used to identify it in tool calls.

              • JsonValue; type "mcp"constant

                The type of the MCP tool. Always mcp.

                • MCP("mcp")
              • Optional<AllowedTools> allowedTools

                List of allowed tool names or a filter object.

                • List<String>

                • class McpToolFilter:

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

              • Optional<String> authorization

                An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

              • Optional<ConnectorId> connectorId

                Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

                Currently supported connector_id values are:

                • Dropbox: connector_dropbox

                • Gmail: connector_gmail

                • Google Calendar: connector_googlecalendar

                • Google Drive: connector_googledrive

                • Microsoft Teams: connector_microsoftteams

                • Outlook Calendar: connector_outlookcalendar

                • Outlook Email: connector_outlookemail

                • SharePoint: connector_sharepoint

                • CONNECTOR_DROPBOX("connector_dropbox")

                • CONNECTOR_GMAIL("connector_gmail")

                • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

                • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

                • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

                • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

                • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

                • CONNECTOR_SHAREPOINT("connector_sharepoint")

              • Optional<Boolean> deferLoading

                Whether this MCP tool is deferred and discovered via tool search.

              • Optional<Headers> headers

                Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

              • Optional<RequireApproval> requireApproval

                Specify which of the MCP server's tools require approval.

                • class McpToolApprovalFilter:

                  Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

                  • Optional<Always> always

                    A filter object to specify which tools are allowed.

                    • Optional<Boolean> readOnly

                      Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                    • Optional<List<String>> toolNames

                      List of allowed tool names.

                  • Optional<Never> never

                    A filter object to specify which tools are allowed.

                    • Optional<Boolean> readOnly

                      Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                    • Optional<List<String>> toolNames

                      List of allowed tool names.

                • enum McpToolApprovalSetting:

                  Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

                  • ALWAYS("always")

                  • NEVER("never")

              • Optional<String> serverDescription

                Optional description of the MCP server, used to provide more context.

              • Optional<String> serverUrl

                The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

              • Optional<String> tunnelId

                The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

          • Optional<RealtimeTracingConfig> tracing

            Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

            auto will create a trace for the session with default values for the workflow name, group id, and metadata.

            • JsonValue;

              • AUTO("auto")
            • TracingConfiguration

              • Optional<String> groupId

                The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

              • Optional<JsonValue> metadata

                The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

              • Optional<String> workflowName

                The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

          • Optional<RealtimeTruncation> truncation

            When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

            Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

            Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

            Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

            • RealtimeTruncationStrategy

              • AUTO("auto")

              • DISABLED("disabled")

            • class RealtimeTruncationRetentionRatio:

              Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

              • double retentionRatio

                Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

              • JsonValue; type "retention_ratio"constant

                Use retention ratio truncation.

                • RETENTION_RATIO("retention_ratio")
              • Optional<TokenLimits> tokenLimits

                Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

                • Optional<Long> postInstructions

                  Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

        • class RealtimeTranscriptionSessionCreateRequest:

          Realtime transcription session object configuration.

          • JsonValue; type "transcription"constant

            The type of session to create. Always transcription for transcription sessions.

            • TRANSCRIPTION("transcription")
          • Optional<RealtimeTranscriptionSessionAudio> audio

            Configuration for input and output audio.

            • Optional<RealtimeTranscriptionSessionAudioInput> input

              • Optional<RealtimeAudioFormats> format

                The PCM audio format. Only a 24kHz sample rate is supported.

              • Optional<NoiseReduction> noiseReduction

                Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

                • Optional<NoiseReductionType> type

                  Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

              • Optional<AudioTranscription> transcription

                Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

              • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

                Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

                Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

                Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

                For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

                • ServerVad

                  • JsonValue; type "server_vad"constant

                    Type of turn detection, server_vad to turn on simple Server VAD.

                    • SERVER_VAD("server_vad")
                  • Optional<Boolean> createResponse

                    Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                    If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                  • Optional<Long> idleTimeoutMs

                    Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                    The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                    An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                  • Optional<Boolean> interruptResponse

                    Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                    If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                  • Optional<Long> prefixPaddingMs

                    Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                  • Optional<Long> silenceDurationMs

                    Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                  • Optional<Double> threshold

                    Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

                • SemanticVad

                  • JsonValue; type "semantic_vad"constant

                    Type of turn detection, semantic_vad to turn on Semantic VAD.

                    • SEMANTIC_VAD("semantic_vad")
                  • Optional<Boolean> createResponse

                    Whether or not to automatically generate a response when a VAD stop event occurs.

                  • Optional<Eagerness> eagerness

                    Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                    • LOW("low")

                    • MEDIUM("medium")

                    • HIGH("high")

                    • AUTO("auto")

                  • Optional<Boolean> interruptResponse

                    Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

          • Optional<List<Include>> include

            Additional fields to include in server outputs.

            item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

            • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
      • JsonValue; type "session.update"constant

        The event type, must be session.update.

        • SESSION_UPDATE("session.update")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event. This is an arbitrary string that a client may assign. It will be passed back if there is an error with the event, but the corresponding session.updated event will not include it.

Realtime Conversation Item Assistant Message

  • class RealtimeConversationItemAssistantMessage:

    An assistant message item in a Realtime conversation.

    • List<Content> content

      The content of the message.

      • Optional<String> audio

        Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

      • Optional<String> text

        The text content.

      • Optional<String> transcript

        The transcript of the audio content, this will always be present if the output type is audio.

      • Optional<Type> type

        The content type, output_text or output_audio depending on the session output_modalities configuration.

        • OUTPUT_TEXT("output_text")

        • OUTPUT_AUDIO("output_audio")

    • JsonValue; role "assistant"constant

      The role of the message sender. Always assistant.

      • ASSISTANT("assistant")
    • JsonValue; type "message"constant

      The type of the item. Always message.

      • MESSAGE("message")
    • Optional<String> id

      The unique ID of the item. This may be provided by the client or generated by the server.

    • Optional<Object> object_

      Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

      • REALTIME_ITEM("realtime.item")
    • Optional<Status> status

      The status of the item. Has no effect on the conversation.

      • COMPLETED("completed")

      • INCOMPLETE("incomplete")

      • IN_PROGRESS("in_progress")

Realtime Conversation Item Function Call

  • class RealtimeConversationItemFunctionCall:

    A function call item in a Realtime conversation.

    • String arguments

      The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

    • String name

      The name of the function being called.

    • JsonValue; type "function_call"constant

      The type of the item. Always function_call.

      • FUNCTION_CALL("function_call")
    • Optional<String> id

      The unique ID of the item. This may be provided by the client or generated by the server.

    • Optional<String> callId

      The ID of the function call.

    • Optional<Object> object_

      Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

      • REALTIME_ITEM("realtime.item")
    • Optional<Status> status

      The status of the item. Has no effect on the conversation.

      • COMPLETED("completed")

      • INCOMPLETE("incomplete")

      • IN_PROGRESS("in_progress")

Realtime Conversation Item Function Call Output

  • class RealtimeConversationItemFunctionCallOutput:

    A function call output item in a Realtime conversation.

    • String callId

      The ID of the function call this output is for.

    • String output

      The output of the function call, this is free text and can contain any information or simply be empty.

    • JsonValue; type "function_call_output"constant

      The type of the item. Always function_call_output.

      • FUNCTION_CALL_OUTPUT("function_call_output")
    • Optional<String> id

      The unique ID of the item. This may be provided by the client or generated by the server.

    • Optional<Object> object_

      Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

      • REALTIME_ITEM("realtime.item")
    • Optional<Status> status

      The status of the item. Has no effect on the conversation.

      • COMPLETED("completed")

      • INCOMPLETE("incomplete")

      • IN_PROGRESS("in_progress")

Realtime Conversation Item System Message

  • class RealtimeConversationItemSystemMessage:

    A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

    • List<Content> content

      The content of the message.

      • Optional<String> text

        The text content.

      • Optional<Type> type

        The content type. Always input_text for system messages.

        • INPUT_TEXT("input_text")
    • JsonValue; role "system"constant

      The role of the message sender. Always system.

      • SYSTEM("system")
    • JsonValue; type "message"constant

      The type of the item. Always message.

      • MESSAGE("message")
    • Optional<String> id

      The unique ID of the item. This may be provided by the client or generated by the server.

    • Optional<Object> object_

      Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

      • REALTIME_ITEM("realtime.item")
    • Optional<Status> status

      The status of the item. Has no effect on the conversation.

      • COMPLETED("completed")

      • INCOMPLETE("incomplete")

      • IN_PROGRESS("in_progress")

Realtime Conversation Item User Message

  • class RealtimeConversationItemUserMessage:

    A user message item in a Realtime conversation.

    • List<Content> content

      The content of the message.

      • Optional<String> audio

        Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

      • Optional<Detail> detail

        The detail level of the image (for input_image). auto will default to high.

        • AUTO("auto")

        • LOW("low")

        • HIGH("high")

      • Optional<String> imageUrl

        Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

      • Optional<String> text

        The text content (for input_text).

      • Optional<String> transcript

        Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

      • Optional<Type> type

        The content type (input_text, input_audio, or input_image).

        • INPUT_TEXT("input_text")

        • INPUT_AUDIO("input_audio")

        • INPUT_IMAGE("input_image")

    • JsonValue; role "user"constant

      The role of the message sender. Always user.

      • USER("user")
    • JsonValue; type "message"constant

      The type of the item. Always message.

      • MESSAGE("message")
    • Optional<String> id

      The unique ID of the item. This may be provided by the client or generated by the server.

    • Optional<Object> object_

      Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

      • REALTIME_ITEM("realtime.item")
    • Optional<Status> status

      The status of the item. Has no effect on the conversation.

      • COMPLETED("completed")

      • INCOMPLETE("incomplete")

      • IN_PROGRESS("in_progress")

Realtime Error

  • class RealtimeError:

    Details of the error.

    • String message

      A human-readable error message.

    • String type

      The type of error (e.g., "invalid_request_error", "server_error").

    • Optional<String> code

      Error code, if any.

    • Optional<String> eventId

      The event_id of the client event that caused the error, if applicable.

    • Optional<String> param

      Parameter related to the error, if any.

Realtime Error Event

  • class RealtimeErrorEvent:

    Returned when an error occurs, which could be a client problem or a server problem. Most errors are recoverable and the session will stay open, we recommend to implementors to monitor and log error messages by default.

    • RealtimeError error

      Details of the error.

      • String message

        A human-readable error message.

      • String type

        The type of error (e.g., "invalid_request_error", "server_error").

      • Optional<String> code

        Error code, if any.

      • Optional<String> eventId

        The event_id of the client event that caused the error, if applicable.

      • Optional<String> param

        Parameter related to the error, if any.

    • String eventId

      The unique ID of the server event.

    • JsonValue; type "error"constant

      The event type, must be error.

      • ERROR("error")

Realtime Function Tool

  • class RealtimeFunctionTool:

    • Optional<String> description

      The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

    • Optional<String> name

      The name of the function.

    • Optional<JsonValue> parameters

      Parameters of the function in JSON Schema.

    • Optional<Type> type

      The type of the tool, i.e. function.

      • FUNCTION("function")

Realtime Mcp Approval Request

  • class RealtimeMcpApprovalRequest:

    A Realtime item requesting human approval of a tool invocation.

    • String id

      The unique ID of the approval request.

    • String arguments

      A JSON string of arguments for the tool.

    • String name

      The name of the tool to run.

    • String serverLabel

      The label of the MCP server making the request.

    • JsonValue; type "mcp_approval_request"constant

      The type of the item. Always mcp_approval_request.

      • MCP_APPROVAL_REQUEST("mcp_approval_request")

Realtime Mcp Approval Response

  • class RealtimeMcpApprovalResponse:

    A Realtime item responding to an MCP approval request.

    • String id

      The unique ID of the approval response.

    • String approvalRequestId

      The ID of the approval request being answered.

    • boolean approve

      Whether the request was approved.

    • JsonValue; type "mcp_approval_response"constant

      The type of the item. Always mcp_approval_response.

      • MCP_APPROVAL_RESPONSE("mcp_approval_response")
    • Optional<String> reason

      Optional reason for the decision.

Realtime Mcp List Tools

  • class RealtimeMcpListTools:

    A Realtime item listing tools available on an MCP server.

    • String serverLabel

      The label of the MCP server.

    • List<Tool> tools

      The tools available on the server.

      • JsonValue inputSchema

        The JSON schema describing the tool's input.

      • String name

        The name of the tool.

      • Optional<JsonValue> annotations

        Additional annotations about the tool.

      • Optional<String> description

        The description of the tool.

    • JsonValue; type "mcp_list_tools"constant

      The type of the item. Always mcp_list_tools.

      • MCP_LIST_TOOLS("mcp_list_tools")
    • Optional<String> id

      The unique ID of the list.

Realtime Mcp Protocol Error

  • class RealtimeMcpProtocolError:

    • long code

    • String message

    • JsonValue; type "protocol_error"constant

      • PROTOCOL_ERROR("protocol_error")

Realtime Mcp Tool Call

  • class RealtimeMcpToolCall:

    A Realtime item representing an invocation of a tool on an MCP server.

    • String id

      The unique ID of the tool call.

    • String arguments

      A JSON string of the arguments passed to the tool.

    • String name

      The name of the tool that was run.

    • String serverLabel

      The label of the MCP server running the tool.

    • JsonValue; type "mcp_call"constant

      The type of the item. Always mcp_call.

      • MCP_CALL("mcp_call")
    • Optional<String> approvalRequestId

      The ID of an associated approval request, if any.

    • Optional<Error> error

      The error from the tool call, if any.

      • class RealtimeMcpProtocolError:

        • long code

        • String message

        • JsonValue; type "protocol_error"constant

          • PROTOCOL_ERROR("protocol_error")
      • class RealtimeMcpToolExecutionError:

        • String message

        • JsonValue; type "tool_execution_error"constant

          • TOOL_EXECUTION_ERROR("tool_execution_error")
      • class RealtimeMcphttpError:

        • long code

        • String message

        • JsonValue; type "http_error"constant

          • HTTP_ERROR("http_error")
    • Optional<String> output

      The output from the tool call.

Realtime Mcp Tool Execution Error

  • class RealtimeMcpToolExecutionError:

    • String message

    • JsonValue; type "tool_execution_error"constant

      • TOOL_EXECUTION_ERROR("tool_execution_error")

Realtime Mcphttp Error

  • class RealtimeMcphttpError:

    • long code

    • String message

    • JsonValue; type "http_error"constant

      • HTTP_ERROR("http_error")

Realtime Reasoning

  • class RealtimeReasoning:

    Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

    • Optional<RealtimeReasoningEffort> effort

      Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

      • MINIMAL("minimal")

      • LOW("low")

      • MEDIUM("medium")

      • HIGH("high")

      • XHIGH("xhigh")

Realtime Reasoning Effort

  • enum RealtimeReasoningEffort:

    Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

    • MINIMAL("minimal")

    • LOW("low")

    • MEDIUM("medium")

    • HIGH("high")

    • XHIGH("xhigh")

Realtime Response

  • class RealtimeResponse:

    The response resource.

    • Optional<String> id

      The unique ID of the response, will look like resp_1234.

    • Optional<Audio> audio

      Configuration for audio output.

      • Optional<Output> output

        • Optional<RealtimeAudioFormats> format

          The format of the output audio.

          • AudioPcm

            • Optional<Rate> rate

              The sample rate of the audio. Always 24000.

              • _24000(24000)
            • Optional<Type> type

              The audio format. Always audio/pcm.

              • AUDIO_PCM("audio/pcm")
          • AudioPcmu

            • Optional<Type> type

              The audio format. Always audio/pcmu.

              • AUDIO_PCMU("audio/pcmu")
          • AudioPcma

            • Optional<Type> type

              The audio format. Always audio/pcma.

              • AUDIO_PCMA("audio/pcma")
        • Optional<Voice> voice

          The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. We recommend marin and cedar for best quality.

          • ALLOY("alloy")

          • ASH("ash")

          • BALLAD("ballad")

          • CORAL("coral")

          • ECHO("echo")

          • SAGE("sage")

          • SHIMMER("shimmer")

          • VERSE("verse")

          • MARIN("marin")

          • CEDAR("cedar")

    • Optional<String> conversationId

      Which conversation the response is added to, determined by the conversation field in the response.create event. If auto, the response will be added to the default conversation and the value of conversation_id will be an id like conv_1234. If none, the response will not be added to any conversation and the value of conversation_id will be null. If responses are being triggered automatically by VAD the response will be added to the default conversation

    • Optional<MaxOutputTokens> maxOutputTokens

      Maximum number of output tokens for a single assistant response, inclusive of tool calls, that was used in this response.

      • long

      • JsonValue;

        • INF("inf")
    • Optional<Metadata> metadata

      Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

      Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

    • Optional<Object> object_

      The object type, must be realtime.response.

      • REALTIME_RESPONSE("realtime.response")
    • Optional<List<ConversationItem>> output

      The list of output items generated by the response.

      • class RealtimeConversationItemSystemMessage:

        A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

        • List<Content> content

          The content of the message.

          • Optional<String> text

            The text content.

          • Optional<Type> type

            The content type. Always input_text for system messages.

            • INPUT_TEXT("input_text")
        • JsonValue; role "system"constant

          The role of the message sender. Always system.

          • SYSTEM("system")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemUserMessage:

        A user message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<Detail> detail

            The detail level of the image (for input_image). auto will default to high.

            • AUTO("auto")

            • LOW("low")

            • HIGH("high")

          • Optional<String> imageUrl

            Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

          • Optional<String> text

            The text content (for input_text).

          • Optional<String> transcript

            Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

          • Optional<Type> type

            The content type (input_text, input_audio, or input_image).

            • INPUT_TEXT("input_text")

            • INPUT_AUDIO("input_audio")

            • INPUT_IMAGE("input_image")

        • JsonValue; role "user"constant

          The role of the message sender. Always user.

          • USER("user")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemAssistantMessage:

        An assistant message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<String> text

            The text content.

          • Optional<String> transcript

            The transcript of the audio content, this will always be present if the output type is audio.

          • Optional<Type> type

            The content type, output_text or output_audio depending on the session output_modalities configuration.

            • OUTPUT_TEXT("output_text")

            • OUTPUT_AUDIO("output_audio")

        • JsonValue; role "assistant"constant

          The role of the message sender. Always assistant.

          • ASSISTANT("assistant")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCall:

        A function call item in a Realtime conversation.

        • String arguments

          The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

        • String name

          The name of the function being called.

        • JsonValue; type "function_call"constant

          The type of the item. Always function_call.

          • FUNCTION_CALL("function_call")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<String> callId

          The ID of the function call.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCallOutput:

        A function call output item in a Realtime conversation.

        • String callId

          The ID of the function call this output is for.

        • String output

          The output of the function call, this is free text and can contain any information or simply be empty.

        • JsonValue; type "function_call_output"constant

          The type of the item. Always function_call_output.

          • FUNCTION_CALL_OUTPUT("function_call_output")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeMcpApprovalResponse:

        A Realtime item responding to an MCP approval request.

        • String id

          The unique ID of the approval response.

        • String approvalRequestId

          The ID of the approval request being answered.

        • boolean approve

          Whether the request was approved.

        • JsonValue; type "mcp_approval_response"constant

          The type of the item. Always mcp_approval_response.

          • MCP_APPROVAL_RESPONSE("mcp_approval_response")
        • Optional<String> reason

          Optional reason for the decision.

      • class RealtimeMcpListTools:

        A Realtime item listing tools available on an MCP server.

        • String serverLabel

          The label of the MCP server.

        • List<Tool> tools

          The tools available on the server.

          • JsonValue inputSchema

            The JSON schema describing the tool's input.

          • String name

            The name of the tool.

          • Optional<JsonValue> annotations

            Additional annotations about the tool.

          • Optional<String> description

            The description of the tool.

        • JsonValue; type "mcp_list_tools"constant

          The type of the item. Always mcp_list_tools.

          • MCP_LIST_TOOLS("mcp_list_tools")
        • Optional<String> id

          The unique ID of the list.

      • class RealtimeMcpToolCall:

        A Realtime item representing an invocation of a tool on an MCP server.

        • String id

          The unique ID of the tool call.

        • String arguments

          A JSON string of the arguments passed to the tool.

        • String name

          The name of the tool that was run.

        • String serverLabel

          The label of the MCP server running the tool.

        • JsonValue; type "mcp_call"constant

          The type of the item. Always mcp_call.

          • MCP_CALL("mcp_call")
        • Optional<String> approvalRequestId

          The ID of an associated approval request, if any.

        • Optional<Error> error

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError:

            • long code

            • String message

            • JsonValue; type "protocol_error"constant

              • PROTOCOL_ERROR("protocol_error")
          • class RealtimeMcpToolExecutionError:

            • String message

            • JsonValue; type "tool_execution_error"constant

              • TOOL_EXECUTION_ERROR("tool_execution_error")
          • class RealtimeMcphttpError:

            • long code

            • String message

            • JsonValue; type "http_error"constant

              • HTTP_ERROR("http_error")
        • Optional<String> output

          The output from the tool call.

      • class RealtimeMcpApprovalRequest:

        A Realtime item requesting human approval of a tool invocation.

        • String id

          The unique ID of the approval request.

        • String arguments

          A JSON string of arguments for the tool.

        • String name

          The name of the tool to run.

        • String serverLabel

          The label of the MCP server making the request.

        • JsonValue; type "mcp_approval_request"constant

          The type of the item. Always mcp_approval_request.

          • MCP_APPROVAL_REQUEST("mcp_approval_request")
    • Optional<List<OutputModality>> outputModalities

      The set of modalities the model used to respond, currently the only possible values are [\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the output to mode text will disable audio output from the model.

      • TEXT("text")

      • AUDIO("audio")

    • Optional<Status> status

      The final status of the response (completed, cancelled, failed, or incomplete, in_progress).

      • COMPLETED("completed")

      • CANCELLED("cancelled")

      • FAILED("failed")

      • INCOMPLETE("incomplete")

      • IN_PROGRESS("in_progress")

    • Optional<RealtimeResponseStatus> statusDetails

      Additional details about the status.

      • Optional<Error> error

        A description of the error that caused the response to fail, populated when the status is failed.

        • Optional<String> code

          Error code, if any.

        • Optional<String> type

          The type of error.

      • Optional<Reason> reason

        The reason the Response did not complete. For a cancelled Response, one of turn_detected (the server VAD detected a new start of speech) or client_cancelled (the client sent a cancel event). For an incomplete Response, one of max_output_tokens or content_filter (the server-side safety filter activated and cut off the response).

        • TURN_DETECTED("turn_detected")

        • CLIENT_CANCELLED("client_cancelled")

        • MAX_OUTPUT_TOKENS("max_output_tokens")

        • CONTENT_FILTER("content_filter")

      • Optional<Type> type

        The type of error that caused the response to fail, corresponding with the status field (completed, cancelled, incomplete, failed).

        • COMPLETED("completed")

        • CANCELLED("cancelled")

        • INCOMPLETE("incomplete")

        • FAILED("failed")

    • Optional<RealtimeResponseUsage> usage

      Usage statistics for the Response, this will correspond to billing. A Realtime API session will maintain a conversation context and append new Items to the Conversation, thus output from previous turns (text and audio tokens) will become the input for later turns.

      • Optional<RealtimeResponseUsageInputTokenDetails> inputTokenDetails

        Details about the input tokens used in the Response. Cached tokens are tokens from previous turns in the conversation that are included as context for the current response. Cached tokens here are counted as a subset of input tokens, meaning input tokens will include cached and uncached tokens.

        • Optional<Long> audioTokens

          The number of audio tokens used as input for the Response.

        • Optional<Long> cachedTokens

          The number of cached tokens used as input for the Response.

        • Optional<CachedTokensDetails> cachedTokensDetails

          Details about the cached tokens used as input for the Response.

          • Optional<Long> audioTokens

            The number of cached audio tokens used as input for the Response.

          • Optional<Long> imageTokens

            The number of cached image tokens used as input for the Response.

          • Optional<Long> textTokens

            The number of cached text tokens used as input for the Response.

        • Optional<Long> imageTokens

          The number of image tokens used as input for the Response.

        • Optional<Long> textTokens

          The number of text tokens used as input for the Response.

      • Optional<Long> inputTokens

        The number of input tokens used in the Response, including text and audio tokens.

      • Optional<RealtimeResponseUsageOutputTokenDetails> outputTokenDetails

        Details about the output tokens used in the Response.

        • Optional<Long> audioTokens

          The number of audio tokens used in the Response.

        • Optional<Long> textTokens

          The number of text tokens used in the Response.

      • Optional<Long> outputTokens

        The number of output tokens sent in the Response, including text and audio tokens.

      • Optional<Long> totalTokens

        The total number of tokens in the Response including input and output text and audio tokens.

Realtime Response Create Audio Output

  • class RealtimeResponseCreateAudioOutput:

    Configuration for audio input and output.

    • Optional<Output> output

      • Optional<RealtimeAudioFormats> format

        The format of the output audio.

        • AudioPcm

          • Optional<Rate> rate

            The sample rate of the audio. Always 24000.

            • _24000(24000)
          • Optional<Type> type

            The audio format. Always audio/pcm.

            • AUDIO_PCM("audio/pcm")
        • AudioPcmu

          • Optional<Type> type

            The audio format. Always audio/pcmu.

            • AUDIO_PCMU("audio/pcmu")
        • AudioPcma

          • Optional<Type> type

            The audio format. Always audio/pcma.

            • AUDIO_PCMA("audio/pcma")
      • Optional<Voice> voice

        The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

        • String

        • enum UnionMember1:

          • ALLOY("alloy")

          • ASH("ash")

          • BALLAD("ballad")

          • CORAL("coral")

          • ECHO("echo")

          • SAGE("sage")

          • SHIMMER("shimmer")

          • VERSE("verse")

          • MARIN("marin")

          • CEDAR("cedar")

        • class Id:

          Custom voice reference.

          • String id

            The custom voice ID, e.g. voice_1234.

Realtime Response Create Mcp Tool

  • class RealtimeResponseCreateMcpTool:

    Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

    • String serverLabel

      A label for this MCP server, used to identify it in tool calls.

    • JsonValue; type "mcp"constant

      The type of the MCP tool. Always mcp.

      • MCP("mcp")
    • Optional<AllowedTools> allowedTools

      List of allowed tool names or a filter object.

      • List<String>

      • class McpToolFilter:

        A filter object to specify which tools are allowed.

        • Optional<Boolean> readOnly

          Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

        • Optional<List<String>> toolNames

          List of allowed tool names.

    • Optional<String> authorization

      An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

    • Optional<ConnectorId> connectorId

      Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

      Currently supported connector_id values are:

      • Dropbox: connector_dropbox

      • Gmail: connector_gmail

      • Google Calendar: connector_googlecalendar

      • Google Drive: connector_googledrive

      • Microsoft Teams: connector_microsoftteams

      • Outlook Calendar: connector_outlookcalendar

      • Outlook Email: connector_outlookemail

      • SharePoint: connector_sharepoint

      • CONNECTOR_DROPBOX("connector_dropbox")

      • CONNECTOR_GMAIL("connector_gmail")

      • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

      • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

      • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

      • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

      • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

      • CONNECTOR_SHAREPOINT("connector_sharepoint")

    • Optional<Boolean> deferLoading

      Whether this MCP tool is deferred and discovered via tool search.

    • Optional<Headers> headers

      Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

    • Optional<RequireApproval> requireApproval

      Specify which of the MCP server's tools require approval.

      • class McpToolApprovalFilter:

        Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

        • Optional<Always> always

          A filter object to specify which tools are allowed.

          • Optional<Boolean> readOnly

            Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

          • Optional<List<String>> toolNames

            List of allowed tool names.

        • Optional<Never> never

          A filter object to specify which tools are allowed.

          • Optional<Boolean> readOnly

            Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

          • Optional<List<String>> toolNames

            List of allowed tool names.

      • enum McpToolApprovalSetting:

        Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

        • ALWAYS("always")

        • NEVER("never")

    • Optional<String> serverDescription

      Optional description of the MCP server, used to provide more context.

    • Optional<String> serverUrl

      The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

    • Optional<String> tunnelId

      The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

Realtime Response Create Params

  • class RealtimeResponseCreateParams:

    Create a new Realtime response with these parameters

    • Optional<RealtimeResponseCreateAudioOutput> audio

      Configuration for audio input and output.

      • Optional<Output> output

        • Optional<RealtimeAudioFormats> format

          The format of the output audio.

          • AudioPcm

            • Optional<Rate> rate

              The sample rate of the audio. Always 24000.

              • _24000(24000)
            • Optional<Type> type

              The audio format. Always audio/pcm.

              • AUDIO_PCM("audio/pcm")
          • AudioPcmu

            • Optional<Type> type

              The audio format. Always audio/pcmu.

              • AUDIO_PCMU("audio/pcmu")
          • AudioPcma

            • Optional<Type> type

              The audio format. Always audio/pcma.

              • AUDIO_PCMA("audio/pcma")
        • Optional<Voice> voice

          The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

          • String

          • enum UnionMember1:

            • ALLOY("alloy")

            • ASH("ash")

            • BALLAD("ballad")

            • CORAL("coral")

            • ECHO("echo")

            • SAGE("sage")

            • SHIMMER("shimmer")

            • VERSE("verse")

            • MARIN("marin")

            • CEDAR("cedar")

          • class Id:

            Custom voice reference.

            • String id

              The custom voice ID, e.g. voice_1234.

    • Optional<Conversation> conversation

      Controls which conversation the response is added to. Currently supports auto and none, with auto as the default value. The auto value means that the contents of the response will be added to the default conversation. Set this to none to create an out-of-band response which will not add items to default conversation.

      • AUTO("auto")

      • NONE("none")

    • Optional<List<ConversationItem>> input

      Input items to include in the prompt for the model. Using this field creates a new context for this Response instead of using the default conversation. An empty array [] will clear the context for this Response. Note that this can include references to items that previously appeared in the session using their id.

      • class RealtimeConversationItemSystemMessage:

        A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

        • List<Content> content

          The content of the message.

          • Optional<String> text

            The text content.

          • Optional<Type> type

            The content type. Always input_text for system messages.

            • INPUT_TEXT("input_text")
        • JsonValue; role "system"constant

          The role of the message sender. Always system.

          • SYSTEM("system")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemUserMessage:

        A user message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<Detail> detail

            The detail level of the image (for input_image). auto will default to high.

            • AUTO("auto")

            • LOW("low")

            • HIGH("high")

          • Optional<String> imageUrl

            Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

          • Optional<String> text

            The text content (for input_text).

          • Optional<String> transcript

            Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

          • Optional<Type> type

            The content type (input_text, input_audio, or input_image).

            • INPUT_TEXT("input_text")

            • INPUT_AUDIO("input_audio")

            • INPUT_IMAGE("input_image")

        • JsonValue; role "user"constant

          The role of the message sender. Always user.

          • USER("user")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemAssistantMessage:

        An assistant message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<String> text

            The text content.

          • Optional<String> transcript

            The transcript of the audio content, this will always be present if the output type is audio.

          • Optional<Type> type

            The content type, output_text or output_audio depending on the session output_modalities configuration.

            • OUTPUT_TEXT("output_text")

            • OUTPUT_AUDIO("output_audio")

        • JsonValue; role "assistant"constant

          The role of the message sender. Always assistant.

          • ASSISTANT("assistant")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCall:

        A function call item in a Realtime conversation.

        • String arguments

          The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

        • String name

          The name of the function being called.

        • JsonValue; type "function_call"constant

          The type of the item. Always function_call.

          • FUNCTION_CALL("function_call")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<String> callId

          The ID of the function call.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCallOutput:

        A function call output item in a Realtime conversation.

        • String callId

          The ID of the function call this output is for.

        • String output

          The output of the function call, this is free text and can contain any information or simply be empty.

        • JsonValue; type "function_call_output"constant

          The type of the item. Always function_call_output.

          • FUNCTION_CALL_OUTPUT("function_call_output")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeMcpApprovalResponse:

        A Realtime item responding to an MCP approval request.

        • String id

          The unique ID of the approval response.

        • String approvalRequestId

          The ID of the approval request being answered.

        • boolean approve

          Whether the request was approved.

        • JsonValue; type "mcp_approval_response"constant

          The type of the item. Always mcp_approval_response.

          • MCP_APPROVAL_RESPONSE("mcp_approval_response")
        • Optional<String> reason

          Optional reason for the decision.

      • class RealtimeMcpListTools:

        A Realtime item listing tools available on an MCP server.

        • String serverLabel

          The label of the MCP server.

        • List<Tool> tools

          The tools available on the server.

          • JsonValue inputSchema

            The JSON schema describing the tool's input.

          • String name

            The name of the tool.

          • Optional<JsonValue> annotations

            Additional annotations about the tool.

          • Optional<String> description

            The description of the tool.

        • JsonValue; type "mcp_list_tools"constant

          The type of the item. Always mcp_list_tools.

          • MCP_LIST_TOOLS("mcp_list_tools")
        • Optional<String> id

          The unique ID of the list.

      • class RealtimeMcpToolCall:

        A Realtime item representing an invocation of a tool on an MCP server.

        • String id

          The unique ID of the tool call.

        • String arguments

          A JSON string of the arguments passed to the tool.

        • String name

          The name of the tool that was run.

        • String serverLabel

          The label of the MCP server running the tool.

        • JsonValue; type "mcp_call"constant

          The type of the item. Always mcp_call.

          • MCP_CALL("mcp_call")
        • Optional<String> approvalRequestId

          The ID of an associated approval request, if any.

        • Optional<Error> error

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError:

            • long code

            • String message

            • JsonValue; type "protocol_error"constant

              • PROTOCOL_ERROR("protocol_error")
          • class RealtimeMcpToolExecutionError:

            • String message

            • JsonValue; type "tool_execution_error"constant

              • TOOL_EXECUTION_ERROR("tool_execution_error")
          • class RealtimeMcphttpError:

            • long code

            • String message

            • JsonValue; type "http_error"constant

              • HTTP_ERROR("http_error")
        • Optional<String> output

          The output from the tool call.

      • class RealtimeMcpApprovalRequest:

        A Realtime item requesting human approval of a tool invocation.

        • String id

          The unique ID of the approval request.

        • String arguments

          A JSON string of arguments for the tool.

        • String name

          The name of the tool to run.

        • String serverLabel

          The label of the MCP server making the request.

        • JsonValue; type "mcp_approval_request"constant

          The type of the item. Always mcp_approval_request.

          • MCP_APPROVAL_REQUEST("mcp_approval_request")
    • Optional<String> instructions

      The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior. Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

    • Optional<MaxOutputTokens> maxOutputTokens

      Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

      • long

      • JsonValue;

        • INF("inf")
    • Optional<Metadata> metadata

      Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

      Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

    • Optional<List<OutputModality>> outputModalities

      The set of modalities the model used to respond, currently the only possible values are [\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the output to mode text will disable audio output from the model.

      • TEXT("text")

      • AUDIO("audio")

    • Optional<Boolean> parallelToolCalls

      Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

    • Optional<ResponsePrompt> prompt

      Reference to a prompt template and its variables. Learn more.

      • String id

        The unique identifier of the prompt template to use.

      • Optional<Variables> variables

        Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

        • String

        • class ResponseInputText:

          A text input to the model.

          • String text

            The text input to the model.

          • JsonValue; type "input_text"constant

            The type of the input item. Always input_text.

            • INPUT_TEXT("input_text")
        • class ResponseInputImage:

          An image input to the model. Learn about image inputs.

          • Detail detail

            The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

            • LOW("low")

            • HIGH("high")

            • AUTO("auto")

            • ORIGINAL("original")

          • JsonValue; type "input_image"constant

            The type of the input item. Always input_image.

            • INPUT_IMAGE("input_image")
          • Optional<String> fileId

            The ID of the file to be sent to the model.

          • Optional<String> imageUrl

            The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

        • class ResponseInputFile:

          A file input to the model.

          • JsonValue; type "input_file"constant

            The type of the input item. Always input_file.

            • INPUT_FILE("input_file")
          • Optional<Detail> detail

            The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

            • LOW("low")

            • HIGH("high")

          • Optional<String> fileData

            The content of the file to be sent to the model.

          • Optional<String> fileId

            The ID of the file to be sent to the model.

          • Optional<String> fileUrl

            The URL of the file to be sent to the model.

          • Optional<String> filename

            The name of the file to be sent to the model.

      • Optional<String> version

        Optional version of the prompt template.

    • Optional<RealtimeReasoning> reasoning

      Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

      • Optional<RealtimeReasoningEffort> effort

        Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

        • MINIMAL("minimal")

        • LOW("low")

        • MEDIUM("medium")

        • HIGH("high")

        • XHIGH("xhigh")

    • Optional<ToolChoice> toolChoice

      How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

      • enum ToolChoiceOptions:

        Controls which (if any) tool is called by the model.

        none means the model will not call any tool and instead generates a message.

        auto means the model can pick between generating a message or calling one or more tools.

        required means the model must call one or more tools.

        • NONE("none")

        • AUTO("auto")

        • REQUIRED("required")

      • class ToolChoiceFunction:

        Use this option to force the model to call a specific function.

        • String name

          The name of the function to call.

        • JsonValue; type "function"constant

          For function calling, the type is always function.

          • FUNCTION("function")
      • class ToolChoiceMcp:

        Use this option to force the model to call a specific tool on a remote MCP server.

        • String serverLabel

          The label of the MCP server to use.

        • JsonValue; type "mcp"constant

          For MCP tools, the type is always mcp.

          • MCP("mcp")
        • Optional<String> name

          The name of the tool to call on the server.

    • Optional<List<Tool>> tools

      Tools available to the model.

      • class RealtimeFunctionTool:

        • Optional<String> description

          The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

        • Optional<String> name

          The name of the function.

        • Optional<JsonValue> parameters

          Parameters of the function in JSON Schema.

        • Optional<Type> type

          The type of the tool, i.e. function.

          • FUNCTION("function")
      • class RealtimeResponseCreateMcpTool:

        Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

        • String serverLabel

          A label for this MCP server, used to identify it in tool calls.

        • JsonValue; type "mcp"constant

          The type of the MCP tool. Always mcp.

          • MCP("mcp")
        • Optional<AllowedTools> allowedTools

          List of allowed tool names or a filter object.

          • List<String>

          • class McpToolFilter:

            A filter object to specify which tools are allowed.

            • Optional<Boolean> readOnly

              Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

            • Optional<List<String>> toolNames

              List of allowed tool names.

        • Optional<String> authorization

          An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

        • Optional<ConnectorId> connectorId

          Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

          Currently supported connector_id values are:

          • Dropbox: connector_dropbox

          • Gmail: connector_gmail

          • Google Calendar: connector_googlecalendar

          • Google Drive: connector_googledrive

          • Microsoft Teams: connector_microsoftteams

          • Outlook Calendar: connector_outlookcalendar

          • Outlook Email: connector_outlookemail

          • SharePoint: connector_sharepoint

          • CONNECTOR_DROPBOX("connector_dropbox")

          • CONNECTOR_GMAIL("connector_gmail")

          • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

          • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

          • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

          • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

          • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

          • CONNECTOR_SHAREPOINT("connector_sharepoint")

        • Optional<Boolean> deferLoading

          Whether this MCP tool is deferred and discovered via tool search.

        • Optional<Headers> headers

          Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

        • Optional<RequireApproval> requireApproval

          Specify which of the MCP server's tools require approval.

          • class McpToolApprovalFilter:

            Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

            • Optional<Always> always

              A filter object to specify which tools are allowed.

              • Optional<Boolean> readOnly

                Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

              • Optional<List<String>> toolNames

                List of allowed tool names.

            • Optional<Never> never

              A filter object to specify which tools are allowed.

              • Optional<Boolean> readOnly

                Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

              • Optional<List<String>> toolNames

                List of allowed tool names.

          • enum McpToolApprovalSetting:

            Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

            • ALWAYS("always")

            • NEVER("never")

        • Optional<String> serverDescription

          Optional description of the MCP server, used to provide more context.

        • Optional<String> serverUrl

          The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

        • Optional<String> tunnelId

          The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

Realtime Response Status

  • class RealtimeResponseStatus:

    Additional details about the status.

    • Optional<Error> error

      A description of the error that caused the response to fail, populated when the status is failed.

      • Optional<String> code

        Error code, if any.

      • Optional<String> type

        The type of error.

    • Optional<Reason> reason

      The reason the Response did not complete. For a cancelled Response, one of turn_detected (the server VAD detected a new start of speech) or client_cancelled (the client sent a cancel event). For an incomplete Response, one of max_output_tokens or content_filter (the server-side safety filter activated and cut off the response).

      • TURN_DETECTED("turn_detected")

      • CLIENT_CANCELLED("client_cancelled")

      • MAX_OUTPUT_TOKENS("max_output_tokens")

      • CONTENT_FILTER("content_filter")

    • Optional<Type> type

      The type of error that caused the response to fail, corresponding with the status field (completed, cancelled, incomplete, failed).

      • COMPLETED("completed")

      • CANCELLED("cancelled")

      • INCOMPLETE("incomplete")

      • FAILED("failed")

Realtime Response Usage

  • class RealtimeResponseUsage:

    Usage statistics for the Response, this will correspond to billing. A Realtime API session will maintain a conversation context and append new Items to the Conversation, thus output from previous turns (text and audio tokens) will become the input for later turns.

    • Optional<RealtimeResponseUsageInputTokenDetails> inputTokenDetails

      Details about the input tokens used in the Response. Cached tokens are tokens from previous turns in the conversation that are included as context for the current response. Cached tokens here are counted as a subset of input tokens, meaning input tokens will include cached and uncached tokens.

      • Optional<Long> audioTokens

        The number of audio tokens used as input for the Response.

      • Optional<Long> cachedTokens

        The number of cached tokens used as input for the Response.

      • Optional<CachedTokensDetails> cachedTokensDetails

        Details about the cached tokens used as input for the Response.

        • Optional<Long> audioTokens

          The number of cached audio tokens used as input for the Response.

        • Optional<Long> imageTokens

          The number of cached image tokens used as input for the Response.

        • Optional<Long> textTokens

          The number of cached text tokens used as input for the Response.

      • Optional<Long> imageTokens

        The number of image tokens used as input for the Response.

      • Optional<Long> textTokens

        The number of text tokens used as input for the Response.

    • Optional<Long> inputTokens

      The number of input tokens used in the Response, including text and audio tokens.

    • Optional<RealtimeResponseUsageOutputTokenDetails> outputTokenDetails

      Details about the output tokens used in the Response.

      • Optional<Long> audioTokens

        The number of audio tokens used in the Response.

      • Optional<Long> textTokens

        The number of text tokens used in the Response.

    • Optional<Long> outputTokens

      The number of output tokens sent in the Response, including text and audio tokens.

    • Optional<Long> totalTokens

      The total number of tokens in the Response including input and output text and audio tokens.

Realtime Response Usage Input Token Details

  • class RealtimeResponseUsageInputTokenDetails:

    Details about the input tokens used in the Response. Cached tokens are tokens from previous turns in the conversation that are included as context for the current response. Cached tokens here are counted as a subset of input tokens, meaning input tokens will include cached and uncached tokens.

    • Optional<Long> audioTokens

      The number of audio tokens used as input for the Response.

    • Optional<Long> cachedTokens

      The number of cached tokens used as input for the Response.

    • Optional<CachedTokensDetails> cachedTokensDetails

      Details about the cached tokens used as input for the Response.

      • Optional<Long> audioTokens

        The number of cached audio tokens used as input for the Response.

      • Optional<Long> imageTokens

        The number of cached image tokens used as input for the Response.

      • Optional<Long> textTokens

        The number of cached text tokens used as input for the Response.

    • Optional<Long> imageTokens

      The number of image tokens used as input for the Response.

    • Optional<Long> textTokens

      The number of text tokens used as input for the Response.

Realtime Response Usage Output Token Details

  • class RealtimeResponseUsageOutputTokenDetails:

    Details about the output tokens used in the Response.

    • Optional<Long> audioTokens

      The number of audio tokens used in the Response.

    • Optional<Long> textTokens

      The number of text tokens used in the Response.

Realtime Server Event

  • class RealtimeServerEvent: A class that can be one of several variants.union

    A realtime server event.

    • class ConversationCreatedEvent:

      Returned when a conversation is created. Emitted right after session creation.

      • Conversation conversation

        The conversation resource.

        • Optional<String> id

          The unique ID of the conversation.

        • Optional<Object> object_

          The object type, must be realtime.conversation.

          • REALTIME_CONVERSATION("realtime.conversation")
      • String eventId

        The unique ID of the server event.

      • JsonValue; type "conversation.created"constant

        The event type, must be conversation.created.

        • CONVERSATION_CREATED("conversation.created")
    • class ConversationItemCreatedEvent:

      Returned when a conversation item is created. There are several scenarios that produce this event:

      • The server is generating a Response, which if successful will produce either one or two Items, which will be of type message (role assistant) or type function_call.

      • The input audio buffer has been committed, either by the client or the server (in server_vad mode). The server will take the content of the input audio buffer and add it to a new user message Item.

      • The client has sent a conversation.item.create event to add a new Item to the Conversation.

      • String eventId

        The unique ID of the server event.

      • ConversationItem item

        A single item within a Realtime conversation.

        • class RealtimeConversationItemSystemMessage:

          A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

          • List<Content> content

            The content of the message.

            • Optional<String> text

              The text content.

            • Optional<Type> type

              The content type. Always input_text for system messages.

              • INPUT_TEXT("input_text")
          • JsonValue; role "system"constant

            The role of the message sender. Always system.

            • SYSTEM("system")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemUserMessage:

          A user message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<Detail> detail

              The detail level of the image (for input_image). auto will default to high.

              • AUTO("auto")

              • LOW("low")

              • HIGH("high")

            • Optional<String> imageUrl

              Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

            • Optional<String> text

              The text content (for input_text).

            • Optional<String> transcript

              Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

            • Optional<Type> type

              The content type (input_text, input_audio, or input_image).

              • INPUT_TEXT("input_text")

              • INPUT_AUDIO("input_audio")

              • INPUT_IMAGE("input_image")

          • JsonValue; role "user"constant

            The role of the message sender. Always user.

            • USER("user")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemAssistantMessage:

          An assistant message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<String> text

              The text content.

            • Optional<String> transcript

              The transcript of the audio content, this will always be present if the output type is audio.

            • Optional<Type> type

              The content type, output_text or output_audio depending on the session output_modalities configuration.

              • OUTPUT_TEXT("output_text")

              • OUTPUT_AUDIO("output_audio")

          • JsonValue; role "assistant"constant

            The role of the message sender. Always assistant.

            • ASSISTANT("assistant")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCall:

          A function call item in a Realtime conversation.

          • String arguments

            The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

          • String name

            The name of the function being called.

          • JsonValue; type "function_call"constant

            The type of the item. Always function_call.

            • FUNCTION_CALL("function_call")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<String> callId

            The ID of the function call.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCallOutput:

          A function call output item in a Realtime conversation.

          • String callId

            The ID of the function call this output is for.

          • String output

            The output of the function call, this is free text and can contain any information or simply be empty.

          • JsonValue; type "function_call_output"constant

            The type of the item. Always function_call_output.

            • FUNCTION_CALL_OUTPUT("function_call_output")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeMcpApprovalResponse:

          A Realtime item responding to an MCP approval request.

          • String id

            The unique ID of the approval response.

          • String approvalRequestId

            The ID of the approval request being answered.

          • boolean approve

            Whether the request was approved.

          • JsonValue; type "mcp_approval_response"constant

            The type of the item. Always mcp_approval_response.

            • MCP_APPROVAL_RESPONSE("mcp_approval_response")
          • Optional<String> reason

            Optional reason for the decision.

        • class RealtimeMcpListTools:

          A Realtime item listing tools available on an MCP server.

          • String serverLabel

            The label of the MCP server.

          • List<Tool> tools

            The tools available on the server.

            • JsonValue inputSchema

              The JSON schema describing the tool's input.

            • String name

              The name of the tool.

            • Optional<JsonValue> annotations

              Additional annotations about the tool.

            • Optional<String> description

              The description of the tool.

          • JsonValue; type "mcp_list_tools"constant

            The type of the item. Always mcp_list_tools.

            • MCP_LIST_TOOLS("mcp_list_tools")
          • Optional<String> id

            The unique ID of the list.

        • class RealtimeMcpToolCall:

          A Realtime item representing an invocation of a tool on an MCP server.

          • String id

            The unique ID of the tool call.

          • String arguments

            A JSON string of the arguments passed to the tool.

          • String name

            The name of the tool that was run.

          • String serverLabel

            The label of the MCP server running the tool.

          • JsonValue; type "mcp_call"constant

            The type of the item. Always mcp_call.

            • MCP_CALL("mcp_call")
          • Optional<String> approvalRequestId

            The ID of an associated approval request, if any.

          • Optional<Error> error

            The error from the tool call, if any.

            • class RealtimeMcpProtocolError:

              • long code

              • String message

              • JsonValue; type "protocol_error"constant

                • PROTOCOL_ERROR("protocol_error")
            • class RealtimeMcpToolExecutionError:

              • String message

              • JsonValue; type "tool_execution_error"constant

                • TOOL_EXECUTION_ERROR("tool_execution_error")
            • class RealtimeMcphttpError:

              • long code

              • String message

              • JsonValue; type "http_error"constant

                • HTTP_ERROR("http_error")
          • Optional<String> output

            The output from the tool call.

        • class RealtimeMcpApprovalRequest:

          A Realtime item requesting human approval of a tool invocation.

          • String id

            The unique ID of the approval request.

          • String arguments

            A JSON string of arguments for the tool.

          • String name

            The name of the tool to run.

          • String serverLabel

            The label of the MCP server making the request.

          • JsonValue; type "mcp_approval_request"constant

            The type of the item. Always mcp_approval_request.

            • MCP_APPROVAL_REQUEST("mcp_approval_request")
      • JsonValue; type "conversation.item.created"constant

        The event type, must be conversation.item.created.

        • CONVERSATION_ITEM_CREATED("conversation.item.created")
      • Optional<String> previousItemId

        The ID of the preceding item in the Conversation context, allows the client to understand the order of the conversation. Can be null if the item has no predecessor.

    • class ConversationItemDeletedEvent:

      Returned when an item in the conversation is deleted by the client with a conversation.item.delete event. This event is used to synchronize the server's understanding of the conversation history with the client's view.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item that was deleted.

      • JsonValue; type "conversation.item.deleted"constant

        The event type, must be conversation.item.deleted.

        • CONVERSATION_ITEM_DELETED("conversation.item.deleted")
    • class ConversationItemInputAudioTranscriptionCompletedEvent:

      This event is the output of audio transcription for user audio written to the user audio buffer. Transcription begins when the input audio buffer is committed by the client or server (when VAD is enabled). Transcription runs asynchronously with Response creation, so this event may come before or after the Response events.

      Realtime API models accept audio natively, and thus input transcription is a separate process run on a separate ASR (Automatic Speech Recognition) model. The transcript may diverge somewhat from the model's interpretation, and should be treated as a rough guide.

      • long contentIndex

        The index of the content part containing the audio.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item containing the audio that is being transcribed.

      • String transcript

        The transcribed text.

      • JsonValue; type "conversation.item.input_audio_transcription.completed"constant

        The event type, must be conversation.item.input_audio_transcription.completed.

        • CONVERSATION_ITEM_INPUT_AUDIO_TRANSCRIPTION_COMPLETED("conversation.item.input_audio_transcription.completed")
      • Usage usage

        Usage statistics for the transcription, this is billed according to the ASR model's pricing rather than the realtime model's pricing.

        • class TranscriptTextUsageTokens:

          Usage statistics for models billed by token usage.

          • long inputTokens

            Number of input tokens billed for this request.

          • long outputTokens

            Number of output tokens generated.

          • long totalTokens

            Total number of tokens used (input + output).

          • JsonValue; type "tokens"constant

            The type of the usage object. Always tokens for this variant.

            • TOKENS("tokens")
          • Optional<InputTokenDetails> inputTokenDetails

            Details about the input tokens billed for this request.

            • Optional<Long> audioTokens

              Number of audio tokens billed for this request.

            • Optional<Long> textTokens

              Number of text tokens billed for this request.

        • class TranscriptTextUsageDuration:

          Usage statistics for models billed by audio input duration.

          • double seconds

            Duration of the input audio in seconds.

          • JsonValue; type "duration"constant

            The type of the usage object. Always duration for this variant.

            • DURATION("duration")
      • Optional<List<LogProbProperties>> logprobs

        The log probabilities of the transcription.

        • String token

          The token that was used to generate the log probability.

        • List<long> bytes

          The bytes that were used to generate the log probability.

        • double logprob

          The log probability of the token.

    • class ConversationItemInputAudioTranscriptionDeltaEvent:

      Returned when the text value of an input audio transcription content part is updated with incremental transcription results.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item containing the audio that is being transcribed.

      • JsonValue; type "conversation.item.input_audio_transcription.delta"constant

        The event type, must be conversation.item.input_audio_transcription.delta.

        • CONVERSATION_ITEM_INPUT_AUDIO_TRANSCRIPTION_DELTA("conversation.item.input_audio_transcription.delta")
      • Optional<Long> contentIndex

        The index of the content part in the item's content array.

      • Optional<String> delta

        The text delta.

      • Optional<List<LogProbProperties>> logprobs

        The log probabilities of the transcription. These can be enabled by configurating the session with "include": ["item.input_audio_transcription.logprobs"]. Each entry in the array corresponds a log probability of which token would be selected for this chunk of transcription. This can help to identify if it was possible there were multiple valid options for a given chunk of transcription.

        • String token

          The token that was used to generate the log probability.

        • List<long> bytes

          The bytes that were used to generate the log probability.

        • double logprob

          The log probability of the token.

    • class ConversationItemInputAudioTranscriptionFailedEvent:

      Returned when input audio transcription is configured, and a transcription request for a user message failed. These events are separate from other error events so that the client can identify the related Item.

      • long contentIndex

        The index of the content part containing the audio.

      • Error error

        Details of the transcription error.

        • Optional<String> code

          Error code, if any.

        • Optional<String> message

          A human-readable error message.

        • Optional<String> param

          Parameter related to the error, if any.

        • Optional<String> type

          The type of error.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the user message item.

      • JsonValue; type "conversation.item.input_audio_transcription.failed"constant

        The event type, must be conversation.item.input_audio_transcription.failed.

        • CONVERSATION_ITEM_INPUT_AUDIO_TRANSCRIPTION_FAILED("conversation.item.input_audio_transcription.failed")
    • ConversationItemRetrieved

      • String eventId

        The unique ID of the server event.

      • ConversationItem item

        A single item within a Realtime conversation.

      • JsonValue; type "conversation.item.retrieved"constant

        The event type, must be conversation.item.retrieved.

        • CONVERSATION_ITEM_RETRIEVED("conversation.item.retrieved")
    • class ConversationItemTruncatedEvent:

      Returned when an earlier assistant audio message item is truncated by the client with a conversation.item.truncate event. This event is used to synchronize the server's understanding of the audio with the client's playback.

      This action will truncate the audio and remove the server-side text transcript to ensure there is no text in the context that hasn't been heard by the user.

      • long audioEndMs

        The duration up to which the audio was truncated, in milliseconds.

      • long contentIndex

        The index of the content part that was truncated.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the assistant message item that was truncated.

      • JsonValue; type "conversation.item.truncated"constant

        The event type, must be conversation.item.truncated.

        • CONVERSATION_ITEM_TRUNCATED("conversation.item.truncated")
    • class RealtimeErrorEvent:

      Returned when an error occurs, which could be a client problem or a server problem. Most errors are recoverable and the session will stay open, we recommend to implementors to monitor and log error messages by default.

      • RealtimeError error

        Details of the error.

        • String message

          A human-readable error message.

        • String type

          The type of error (e.g., "invalid_request_error", "server_error").

        • Optional<String> code

          Error code, if any.

        • Optional<String> eventId

          The event_id of the client event that caused the error, if applicable.

        • Optional<String> param

          Parameter related to the error, if any.

      • String eventId

        The unique ID of the server event.

      • JsonValue; type "error"constant

        The event type, must be error.

        • ERROR("error")
    • class InputAudioBufferClearedEvent:

      Returned when the input audio buffer is cleared by the client with a input_audio_buffer.clear event.

      • String eventId

        The unique ID of the server event.

      • JsonValue; type "input_audio_buffer.cleared"constant

        The event type, must be input_audio_buffer.cleared.

        • INPUT_AUDIO_BUFFER_CLEARED("input_audio_buffer.cleared")
    • class InputAudioBufferCommittedEvent:

      Returned when an input audio buffer is committed, either by the client or automatically in server VAD mode. The item_id property is the ID of the user message item that will be created, thus a conversation.item.created event will also be sent to the client.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the user message item that will be created.

      • JsonValue; type "input_audio_buffer.committed"constant

        The event type, must be input_audio_buffer.committed.

        • INPUT_AUDIO_BUFFER_COMMITTED("input_audio_buffer.committed")
      • Optional<String> previousItemId

        The ID of the preceding item after which the new item will be inserted. Can be null if the item has no predecessor.

    • class InputAudioBufferDtmfEventReceivedEvent:

      SIP Only: Returned when an DTMF event is received. A DTMF event is a message that represents a telephone keypad press (0–9, *, #, A–D). The event property is the keypad that the user press. The received_at is the UTC Unix Timestamp that the server received the event.

      • String event

        The telephone keypad that was pressed by the user.

      • long receivedAt

        UTC Unix Timestamp when DTMF Event was received by server.

      • JsonValue; type "input_audio_buffer.dtmf_event_received"constant

        The event type, must be input_audio_buffer.dtmf_event_received.

        • INPUT_AUDIO_BUFFER_DTMF_EVENT_RECEIVED("input_audio_buffer.dtmf_event_received")
    • class InputAudioBufferSpeechStartedEvent:

      Sent by the server when in server_vad mode to indicate that speech has been detected in the audio buffer. This can happen any time audio is added to the buffer (unless speech is already detected). The client may want to use this event to interrupt audio playback or provide visual feedback to the user.

      The client should expect to receive a input_audio_buffer.speech_stopped event when speech stops. The item_id property is the ID of the user message item that will be created when speech stops and will also be included in the input_audio_buffer.speech_stopped event (unless the client manually commits the audio buffer during VAD activation).

      • long audioStartMs

        Milliseconds from the start of all audio written to the buffer during the session when speech was first detected. This will correspond to the beginning of audio sent to the model, and thus includes the prefix_padding_ms configured in the Session.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the user message item that will be created when speech stops.

      • JsonValue; type "input_audio_buffer.speech_started"constant

        The event type, must be input_audio_buffer.speech_started.

        • INPUT_AUDIO_BUFFER_SPEECH_STARTED("input_audio_buffer.speech_started")
    • class InputAudioBufferSpeechStoppedEvent:

      Returned in server_vad mode when the server detects the end of speech in the audio buffer. The server will also send an conversation.item.created event with the user message item that is created from the audio buffer.

      • long audioEndMs

        Milliseconds since the session started when speech stopped. This will correspond to the end of audio sent to the model, and thus includes the min_silence_duration_ms configured in the Session.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the user message item that will be created.

      • JsonValue; type "input_audio_buffer.speech_stopped"constant

        The event type, must be input_audio_buffer.speech_stopped.

        • INPUT_AUDIO_BUFFER_SPEECH_STOPPED("input_audio_buffer.speech_stopped")
    • class RateLimitsUpdatedEvent:

      Emitted at the beginning of a Response to indicate the updated rate limits. When a Response is created some tokens will be "reserved" for the output tokens, the rate limits shown here reflect that reservation, which is then adjusted accordingly once the Response is completed.

      • String eventId

        The unique ID of the server event.

      • List<RateLimit> rateLimits

        List of rate limit information.

        • Optional<Long> limit

          The maximum allowed value for the rate limit.

        • Optional<Name> name

          The name of the rate limit (requests, tokens).

          • REQUESTS("requests")

          • TOKENS("tokens")

        • Optional<Long> remaining

          The remaining value before the limit is reached.

        • Optional<Double> resetSeconds

          Seconds until the rate limit resets.

      • JsonValue; type "rate_limits.updated"constant

        The event type, must be rate_limits.updated.

        • RATE_LIMITS_UPDATED("rate_limits.updated")
    • class ResponseAudioDeltaEvent:

      Returned when the model-generated audio is updated.

      • long contentIndex

        The index of the content part in the item's content array.

      • String delta

        Base64-encoded audio data delta.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • JsonValue; type "response.output_audio.delta"constant

        The event type, must be response.output_audio.delta.

        • RESPONSE_OUTPUT_AUDIO_DELTA("response.output_audio.delta")
    • class ResponseAudioDoneEvent:

      Returned when the model-generated audio is done. Also emitted when a Response is interrupted, incomplete, or cancelled.

      • long contentIndex

        The index of the content part in the item's content array.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • JsonValue; type "response.output_audio.done"constant

        The event type, must be response.output_audio.done.

        • RESPONSE_OUTPUT_AUDIO_DONE("response.output_audio.done")
    • class ResponseAudioTranscriptDeltaEvent:

      Returned when the model-generated transcription of audio output is updated.

      • long contentIndex

        The index of the content part in the item's content array.

      • String delta

        The transcript delta.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • JsonValue; type "response.output_audio_transcript.delta"constant

        The event type, must be response.output_audio_transcript.delta.

        • RESPONSE_OUTPUT_AUDIO_TRANSCRIPT_DELTA("response.output_audio_transcript.delta")
    • class ResponseAudioTranscriptDoneEvent:

      Returned when the model-generated transcription of audio output is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.

      • long contentIndex

        The index of the content part in the item's content array.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • String transcript

        The final transcript of the audio.

      • JsonValue; type "response.output_audio_transcript.done"constant

        The event type, must be response.output_audio_transcript.done.

        • RESPONSE_OUTPUT_AUDIO_TRANSCRIPT_DONE("response.output_audio_transcript.done")
    • class ResponseContentPartAddedEvent:

      Returned when a new content part is added to an assistant message item during response generation.

      • long contentIndex

        The index of the content part in the item's content array.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item to which the content part was added.

      • long outputIndex

        The index of the output item in the response.

      • Part part

        The content part that was added.

        • Optional<String> audio

          Base64-encoded audio data (if type is "audio").

        • Optional<String> text

          The text content (if type is "text").

        • Optional<String> transcript

          The transcript of the audio (if type is "audio").

        • Optional<Type> type

          The content type ("text", "audio").

          • TEXT("text")

          • AUDIO("audio")

      • String responseId

        The ID of the response.

      • JsonValue; type "response.content_part.added"constant

        The event type, must be response.content_part.added.

        • RESPONSE_CONTENT_PART_ADDED("response.content_part.added")
    • class ResponseContentPartDoneEvent:

      Returned when a content part is done streaming in an assistant message item. Also emitted when a Response is interrupted, incomplete, or cancelled.

      • long contentIndex

        The index of the content part in the item's content array.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item.

      • long outputIndex

        The index of the output item in the response.

      • Part part

        The content part that is done.

        • Optional<String> audio

          Base64-encoded audio data (if type is "audio").

        • Optional<String> text

          The text content (if type is "text").

        • Optional<String> transcript

          The transcript of the audio (if type is "audio").

        • Optional<Type> type

          The content type ("text", "audio").

          • TEXT("text")

          • AUDIO("audio")

      • String responseId

        The ID of the response.

      • JsonValue; type "response.content_part.done"constant

        The event type, must be response.content_part.done.

        • RESPONSE_CONTENT_PART_DONE("response.content_part.done")
    • class ResponseCreatedEvent:

      Returned when a new Response is created. The first event of response creation, where the response is in an initial state of in_progress.

      • String eventId

        The unique ID of the server event.

      • RealtimeResponse response

        The response resource.

        • Optional<String> id

          The unique ID of the response, will look like resp_1234.

        • Optional<Audio> audio

          Configuration for audio output.

          • Optional<Output> output

            • Optional<RealtimeAudioFormats> format

              The format of the output audio.

              • AudioPcm

                • Optional<Rate> rate

                  The sample rate of the audio. Always 24000.

                  • _24000(24000)
                • Optional<Type> type

                  The audio format. Always audio/pcm.

                  • AUDIO_PCM("audio/pcm")
              • AudioPcmu

                • Optional<Type> type

                  The audio format. Always audio/pcmu.

                  • AUDIO_PCMU("audio/pcmu")
              • AudioPcma

                • Optional<Type> type

                  The audio format. Always audio/pcma.

                  • AUDIO_PCMA("audio/pcma")
            • Optional<Voice> voice

              The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. We recommend marin and cedar for best quality.

              • ALLOY("alloy")

              • ASH("ash")

              • BALLAD("ballad")

              • CORAL("coral")

              • ECHO("echo")

              • SAGE("sage")

              • SHIMMER("shimmer")

              • VERSE("verse")

              • MARIN("marin")

              • CEDAR("cedar")

        • Optional<String> conversationId

          Which conversation the response is added to, determined by the conversation field in the response.create event. If auto, the response will be added to the default conversation and the value of conversation_id will be an id like conv_1234. If none, the response will not be added to any conversation and the value of conversation_id will be null. If responses are being triggered automatically by VAD the response will be added to the default conversation

        • Optional<MaxOutputTokens> maxOutputTokens

          Maximum number of output tokens for a single assistant response, inclusive of tool calls, that was used in this response.

          • long

          • JsonValue;

            • INF("inf")
        • Optional<Metadata> metadata

          Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

          Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

        • Optional<Object> object_

          The object type, must be realtime.response.

          • REALTIME_RESPONSE("realtime.response")
        • Optional<List<ConversationItem>> output

          The list of output items generated by the response.

          • class RealtimeConversationItemSystemMessage:

            A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

          • class RealtimeConversationItemUserMessage:

            A user message item in a Realtime conversation.

          • class RealtimeConversationItemAssistantMessage:

            An assistant message item in a Realtime conversation.

          • class RealtimeConversationItemFunctionCall:

            A function call item in a Realtime conversation.

          • class RealtimeConversationItemFunctionCallOutput:

            A function call output item in a Realtime conversation.

          • class RealtimeMcpApprovalResponse:

            A Realtime item responding to an MCP approval request.

          • class RealtimeMcpListTools:

            A Realtime item listing tools available on an MCP server.

          • class RealtimeMcpToolCall:

            A Realtime item representing an invocation of a tool on an MCP server.

          • class RealtimeMcpApprovalRequest:

            A Realtime item requesting human approval of a tool invocation.

        • Optional<List<OutputModality>> outputModalities

          The set of modalities the model used to respond, currently the only possible values are [\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the output to mode text will disable audio output from the model.

          • TEXT("text")

          • AUDIO("audio")

        • Optional<Status> status

          The final status of the response (completed, cancelled, failed, or incomplete, in_progress).

          • COMPLETED("completed")

          • CANCELLED("cancelled")

          • FAILED("failed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

        • Optional<RealtimeResponseStatus> statusDetails

          Additional details about the status.

          • Optional<Error> error

            A description of the error that caused the response to fail, populated when the status is failed.

            • Optional<String> code

              Error code, if any.

            • Optional<String> type

              The type of error.

          • Optional<Reason> reason

            The reason the Response did not complete. For a cancelled Response, one of turn_detected (the server VAD detected a new start of speech) or client_cancelled (the client sent a cancel event). For an incomplete Response, one of max_output_tokens or content_filter (the server-side safety filter activated and cut off the response).

            • TURN_DETECTED("turn_detected")

            • CLIENT_CANCELLED("client_cancelled")

            • MAX_OUTPUT_TOKENS("max_output_tokens")

            • CONTENT_FILTER("content_filter")

          • Optional<Type> type

            The type of error that caused the response to fail, corresponding with the status field (completed, cancelled, incomplete, failed).

            • COMPLETED("completed")

            • CANCELLED("cancelled")

            • INCOMPLETE("incomplete")

            • FAILED("failed")

        • Optional<RealtimeResponseUsage> usage

          Usage statistics for the Response, this will correspond to billing. A Realtime API session will maintain a conversation context and append new Items to the Conversation, thus output from previous turns (text and audio tokens) will become the input for later turns.

          • Optional<RealtimeResponseUsageInputTokenDetails> inputTokenDetails

            Details about the input tokens used in the Response. Cached tokens are tokens from previous turns in the conversation that are included as context for the current response. Cached tokens here are counted as a subset of input tokens, meaning input tokens will include cached and uncached tokens.

            • Optional<Long> audioTokens

              The number of audio tokens used as input for the Response.

            • Optional<Long> cachedTokens

              The number of cached tokens used as input for the Response.

            • Optional<CachedTokensDetails> cachedTokensDetails

              Details about the cached tokens used as input for the Response.

              • Optional<Long> audioTokens

                The number of cached audio tokens used as input for the Response.

              • Optional<Long> imageTokens

                The number of cached image tokens used as input for the Response.

              • Optional<Long> textTokens

                The number of cached text tokens used as input for the Response.

            • Optional<Long> imageTokens

              The number of image tokens used as input for the Response.

            • Optional<Long> textTokens

              The number of text tokens used as input for the Response.

          • Optional<Long> inputTokens

            The number of input tokens used in the Response, including text and audio tokens.

          • Optional<RealtimeResponseUsageOutputTokenDetails> outputTokenDetails

            Details about the output tokens used in the Response.

            • Optional<Long> audioTokens

              The number of audio tokens used in the Response.

            • Optional<Long> textTokens

              The number of text tokens used in the Response.

          • Optional<Long> outputTokens

            The number of output tokens sent in the Response, including text and audio tokens.

          • Optional<Long> totalTokens

            The total number of tokens in the Response including input and output text and audio tokens.

      • JsonValue; type "response.created"constant

        The event type, must be response.created.

        • RESPONSE_CREATED("response.created")
    • class ResponseDoneEvent:

      Returned when a Response is done streaming. Always emitted, no matter the final state. The Response object included in the response.done event will include all output Items in the Response but will omit the raw audio data.

      Clients should check the status field of the Response to determine if it was successful (completed) or if there was another outcome: cancelled, failed, or incomplete.

      A response will contain all output items that were generated during the response, excluding any audio content.

      • String eventId

        The unique ID of the server event.

      • RealtimeResponse response

        The response resource.

      • JsonValue; type "response.done"constant

        The event type, must be response.done.

        • RESPONSE_DONE("response.done")
    • class ResponseFunctionCallArgumentsDeltaEvent:

      Returned when the model-generated function call arguments are updated.

      • String callId

        The ID of the function call.

      • String delta

        The arguments delta as a JSON string.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the function call item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • JsonValue; type "response.function_call_arguments.delta"constant

        The event type, must be response.function_call_arguments.delta.

        • RESPONSE_FUNCTION_CALL_ARGUMENTS_DELTA("response.function_call_arguments.delta")
    • class ResponseFunctionCallArgumentsDoneEvent:

      Returned when the model-generated function call arguments are done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.

      • String arguments

        The final arguments as a JSON string.

      • String callId

        The ID of the function call.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the function call item.

      • String name

        The name of the function that was called.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • JsonValue; type "response.function_call_arguments.done"constant

        The event type, must be response.function_call_arguments.done.

        • RESPONSE_FUNCTION_CALL_ARGUMENTS_DONE("response.function_call_arguments.done")
    • class ResponseOutputItemAddedEvent:

      Returned when a new Item is created during Response generation.

      • String eventId

        The unique ID of the server event.

      • ConversationItem item

        A single item within a Realtime conversation.

      • long outputIndex

        The index of the output item in the Response.

      • String responseId

        The ID of the Response to which the item belongs.

      • JsonValue; type "response.output_item.added"constant

        The event type, must be response.output_item.added.

        • RESPONSE_OUTPUT_ITEM_ADDED("response.output_item.added")
    • class ResponseOutputItemDoneEvent:

      Returned when an Item is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.

      • String eventId

        The unique ID of the server event.

      • ConversationItem item

        A single item within a Realtime conversation.

      • long outputIndex

        The index of the output item in the Response.

      • String responseId

        The ID of the Response to which the item belongs.

      • JsonValue; type "response.output_item.done"constant

        The event type, must be response.output_item.done.

        • RESPONSE_OUTPUT_ITEM_DONE("response.output_item.done")
    • class ResponseTextDeltaEvent:

      Returned when the text value of an "output_text" content part is updated.

      • long contentIndex

        The index of the content part in the item's content array.

      • String delta

        The text delta.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • JsonValue; type "response.output_text.delta"constant

        The event type, must be response.output_text.delta.

        • RESPONSE_OUTPUT_TEXT_DELTA("response.output_text.delta")
    • class ResponseTextDoneEvent:

      Returned when the text value of an "output_text" content part is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.

      • long contentIndex

        The index of the content part in the item's content array.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • String text

        The final text content.

      • JsonValue; type "response.output_text.done"constant

        The event type, must be response.output_text.done.

        • RESPONSE_OUTPUT_TEXT_DONE("response.output_text.done")
    • class SessionCreatedEvent:

      Returned when a Session is created. Emitted automatically when a new connection is established as the first server event. This event will contain the default Session configuration.

      • String eventId

        The unique ID of the server event.

      • Session session

        The session configuration.

        • class RealtimeSessionCreateRequest:

          Realtime session object configuration.

          • JsonValue; type "realtime"constant

            The type of session to create. Always realtime for the Realtime API.

            • REALTIME("realtime")
          • Optional<RealtimeAudioConfig> audio

            Configuration for input and output audio.

            • Optional<RealtimeAudioConfigInput> input

              • Optional<RealtimeAudioFormats> format

                The format of the input audio.

              • Optional<NoiseReduction> noiseReduction

                Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

                • Optional<NoiseReductionType> type

                  Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                  • NEAR_FIELD("near_field")

                  • FAR_FIELD("far_field")

              • Optional<AudioTranscription> transcription

                Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

                • Optional<Delay> delay

                  Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

                  • MINIMAL("minimal")

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • XHIGH("xhigh")

                • Optional<String> language

                  The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

                • Optional<Model> model

                  The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

                  • WHISPER_1("whisper-1")

                  • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

                  • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

                  • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

                  • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

                  • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

                • Optional<String> prompt

                  An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

              • Optional<RealtimeAudioInputTurnDetection> turnDetection

                Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

                Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

                Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

                For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

                • ServerVad

                  • JsonValue; type "server_vad"constant

                    Type of turn detection, server_vad to turn on simple Server VAD.

                    • SERVER_VAD("server_vad")
                  • Optional<Boolean> createResponse

                    Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                    If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                  • Optional<Long> idleTimeoutMs

                    Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                    The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                    An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                  • Optional<Boolean> interruptResponse

                    Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                    If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                  • Optional<Long> prefixPaddingMs

                    Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                  • Optional<Long> silenceDurationMs

                    Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                  • Optional<Double> threshold

                    Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

                • SemanticVad

                  • JsonValue; type "semantic_vad"constant

                    Type of turn detection, semantic_vad to turn on Semantic VAD.

                    • SEMANTIC_VAD("semantic_vad")
                  • Optional<Boolean> createResponse

                    Whether or not to automatically generate a response when a VAD stop event occurs.

                  • Optional<Eagerness> eagerness

                    Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                    • LOW("low")

                    • MEDIUM("medium")

                    • HIGH("high")

                    • AUTO("auto")

                  • Optional<Boolean> interruptResponse

                    Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

            • Optional<RealtimeAudioConfigOutput> output

              • Optional<RealtimeAudioFormats> format

                The format of the output audio.

              • Optional<Double> speed

                The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

                This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

              • Optional<Voice> voice

                The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

                • String

                • enum UnionMember1:

                  • ALLOY("alloy")

                  • ASH("ash")

                  • BALLAD("ballad")

                  • CORAL("coral")

                  • ECHO("echo")

                  • SAGE("sage")

                  • SHIMMER("shimmer")

                  • VERSE("verse")

                  • MARIN("marin")

                  • CEDAR("cedar")

                • class Id:

                  Custom voice reference.

                  • String id

                    The custom voice ID, e.g. voice_1234.

          • Optional<List<Include>> include

            Additional fields to include in server outputs.

            item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

            • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
          • Optional<String> instructions

            The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

            Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

          • Optional<MaxOutputTokens> maxOutputTokens

            Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

            • long

            • JsonValue;

              • INF("inf")
          • Optional<Model> model

            The Realtime model used for this session.

            • GPT_REALTIME("gpt-realtime")

            • GPT_REALTIME_1_5("gpt-realtime-1.5")

            • GPT_REALTIME_2("gpt-realtime-2")

            • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

            • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

            • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

            • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

            • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

            • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

            • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

            • GPT_REALTIME_MINI("gpt-realtime-mini")

            • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

            • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

            • GPT_AUDIO_1_5("gpt-audio-1.5")

            • GPT_AUDIO_MINI("gpt-audio-mini")

            • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

            • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

          • Optional<List<OutputModality>> outputModalities

            The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

            • TEXT("text")

            • AUDIO("audio")

          • Optional<Boolean> parallelToolCalls

            Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

          • Optional<ResponsePrompt> prompt

            Reference to a prompt template and its variables. Learn more.

            • String id

              The unique identifier of the prompt template to use.

            • Optional<Variables> variables

              Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

              • String

              • class ResponseInputText:

                A text input to the model.

                • String text

                  The text input to the model.

                • JsonValue; type "input_text"constant

                  The type of the input item. Always input_text.

                  • INPUT_TEXT("input_text")
              • class ResponseInputImage:

                An image input to the model. Learn about image inputs.

                • Detail detail

                  The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

                  • LOW("low")

                  • HIGH("high")

                  • AUTO("auto")

                  • ORIGINAL("original")

                • JsonValue; type "input_image"constant

                  The type of the input item. Always input_image.

                  • INPUT_IMAGE("input_image")
                • Optional<String> fileId

                  The ID of the file to be sent to the model.

                • Optional<String> imageUrl

                  The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

              • class ResponseInputFile:

                A file input to the model.

                • JsonValue; type "input_file"constant

                  The type of the input item. Always input_file.

                  • INPUT_FILE("input_file")
                • Optional<Detail> detail

                  The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

                  • LOW("low")

                  • HIGH("high")

                • Optional<String> fileData

                  The content of the file to be sent to the model.

                • Optional<String> fileId

                  The ID of the file to be sent to the model.

                • Optional<String> fileUrl

                  The URL of the file to be sent to the model.

                • Optional<String> filename

                  The name of the file to be sent to the model.

            • Optional<String> version

              Optional version of the prompt template.

          • Optional<RealtimeReasoning> reasoning

            Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

            • Optional<RealtimeReasoningEffort> effort

              Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

              • MINIMAL("minimal")

              • LOW("low")

              • MEDIUM("medium")

              • HIGH("high")

              • XHIGH("xhigh")

          • Optional<RealtimeToolChoiceConfig> toolChoice

            How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

            • enum ToolChoiceOptions:

              Controls which (if any) tool is called by the model.

              none means the model will not call any tool and instead generates a message.

              auto means the model can pick between generating a message or calling one or more tools.

              required means the model must call one or more tools.

              • NONE("none")

              • AUTO("auto")

              • REQUIRED("required")

            • class ToolChoiceFunction:

              Use this option to force the model to call a specific function.

              • String name

                The name of the function to call.

              • JsonValue; type "function"constant

                For function calling, the type is always function.

                • FUNCTION("function")
            • class ToolChoiceMcp:

              Use this option to force the model to call a specific tool on a remote MCP server.

              • String serverLabel

                The label of the MCP server to use.

              • JsonValue; type "mcp"constant

                For MCP tools, the type is always mcp.

                • MCP("mcp")
              • Optional<String> name

                The name of the tool to call on the server.

          • Optional<List<RealtimeToolsConfigUnion>> tools

            Tools available to the model.

            • class RealtimeFunctionTool:

              • Optional<String> description

                The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

              • Optional<String> name

                The name of the function.

              • Optional<JsonValue> parameters

                Parameters of the function in JSON Schema.

              • Optional<Type> type

                The type of the tool, i.e. function.

                • FUNCTION("function")
            • Mcp

              • String serverLabel

                A label for this MCP server, used to identify it in tool calls.

              • JsonValue; type "mcp"constant

                The type of the MCP tool. Always mcp.

                • MCP("mcp")
              • Optional<AllowedTools> allowedTools

                List of allowed tool names or a filter object.

                • List<String>

                • class McpToolFilter:

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

              • Optional<String> authorization

                An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

              • Optional<ConnectorId> connectorId

                Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

                Currently supported connector_id values are:

                • Dropbox: connector_dropbox

                • Gmail: connector_gmail

                • Google Calendar: connector_googlecalendar

                • Google Drive: connector_googledrive

                • Microsoft Teams: connector_microsoftteams

                • Outlook Calendar: connector_outlookcalendar

                • Outlook Email: connector_outlookemail

                • SharePoint: connector_sharepoint

                • CONNECTOR_DROPBOX("connector_dropbox")

                • CONNECTOR_GMAIL("connector_gmail")

                • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

                • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

                • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

                • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

                • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

                • CONNECTOR_SHAREPOINT("connector_sharepoint")

              • Optional<Boolean> deferLoading

                Whether this MCP tool is deferred and discovered via tool search.

              • Optional<Headers> headers

                Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

              • Optional<RequireApproval> requireApproval

                Specify which of the MCP server's tools require approval.

                • class McpToolApprovalFilter:

                  Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

                  • Optional<Always> always

                    A filter object to specify which tools are allowed.

                    • Optional<Boolean> readOnly

                      Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                    • Optional<List<String>> toolNames

                      List of allowed tool names.

                  • Optional<Never> never

                    A filter object to specify which tools are allowed.

                    • Optional<Boolean> readOnly

                      Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                    • Optional<List<String>> toolNames

                      List of allowed tool names.

                • enum McpToolApprovalSetting:

                  Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

                  • ALWAYS("always")

                  • NEVER("never")

              • Optional<String> serverDescription

                Optional description of the MCP server, used to provide more context.

              • Optional<String> serverUrl

                The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

              • Optional<String> tunnelId

                The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

          • Optional<RealtimeTracingConfig> tracing

            Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

            auto will create a trace for the session with default values for the workflow name, group id, and metadata.

            • JsonValue;

              • AUTO("auto")
            • TracingConfiguration

              • Optional<String> groupId

                The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

              • Optional<JsonValue> metadata

                The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

              • Optional<String> workflowName

                The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

          • Optional<RealtimeTruncation> truncation

            When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

            Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

            Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

            Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

            • RealtimeTruncationStrategy

              • AUTO("auto")

              • DISABLED("disabled")

            • class RealtimeTruncationRetentionRatio:

              Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

              • double retentionRatio

                Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

              • JsonValue; type "retention_ratio"constant

                Use retention ratio truncation.

                • RETENTION_RATIO("retention_ratio")
              • Optional<TokenLimits> tokenLimits

                Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

                • Optional<Long> postInstructions

                  Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

        • class RealtimeTranscriptionSessionCreateRequest:

          Realtime transcription session object configuration.

          • JsonValue; type "transcription"constant

            The type of session to create. Always transcription for transcription sessions.

            • TRANSCRIPTION("transcription")
          • Optional<RealtimeTranscriptionSessionAudio> audio

            Configuration for input and output audio.

            • Optional<RealtimeTranscriptionSessionAudioInput> input

              • Optional<RealtimeAudioFormats> format

                The PCM audio format. Only a 24kHz sample rate is supported.

              • Optional<NoiseReduction> noiseReduction

                Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

                • Optional<NoiseReductionType> type

                  Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

              • Optional<AudioTranscription> transcription

                Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

              • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

                Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

                Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

                Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

                For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

                • ServerVad

                  • JsonValue; type "server_vad"constant

                    Type of turn detection, server_vad to turn on simple Server VAD.

                    • SERVER_VAD("server_vad")
                  • Optional<Boolean> createResponse

                    Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                    If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                  • Optional<Long> idleTimeoutMs

                    Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                    The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                    An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                  • Optional<Boolean> interruptResponse

                    Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                    If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                  • Optional<Long> prefixPaddingMs

                    Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                  • Optional<Long> silenceDurationMs

                    Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                  • Optional<Double> threshold

                    Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

                • SemanticVad

                  • JsonValue; type "semantic_vad"constant

                    Type of turn detection, semantic_vad to turn on Semantic VAD.

                    • SEMANTIC_VAD("semantic_vad")
                  • Optional<Boolean> createResponse

                    Whether or not to automatically generate a response when a VAD stop event occurs.

                  • Optional<Eagerness> eagerness

                    Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                    • LOW("low")

                    • MEDIUM("medium")

                    • HIGH("high")

                    • AUTO("auto")

                  • Optional<Boolean> interruptResponse

                    Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

          • Optional<List<Include>> include

            Additional fields to include in server outputs.

            item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

            • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
      • JsonValue; type "session.created"constant

        The event type, must be session.created.

        • SESSION_CREATED("session.created")
    • class SessionUpdatedEvent:

      Returned when a session is updated with a session.update event, unless there is an error.

      • String eventId

        The unique ID of the server event.

      • Session session

        The session configuration.

        • class RealtimeSessionCreateRequest:

          Realtime session object configuration.

        • class RealtimeTranscriptionSessionCreateRequest:

          Realtime transcription session object configuration.

      • JsonValue; type "session.updated"constant

        The event type, must be session.updated.

        • SESSION_UPDATED("session.updated")
    • OutputAudioBufferStarted

      • String eventId

        The unique ID of the server event.

      • String responseId

        The unique ID of the response that produced the audio.

      • JsonValue; type "output_audio_buffer.started"constant

        The event type, must be output_audio_buffer.started.

        • OUTPUT_AUDIO_BUFFER_STARTED("output_audio_buffer.started")
    • OutputAudioBufferStopped

      • String eventId

        The unique ID of the server event.

      • String responseId

        The unique ID of the response that produced the audio.

      • JsonValue; type "output_audio_buffer.stopped"constant

        The event type, must be output_audio_buffer.stopped.

        • OUTPUT_AUDIO_BUFFER_STOPPED("output_audio_buffer.stopped")
    • OutputAudioBufferCleared

      • String eventId

        The unique ID of the server event.

      • String responseId

        The unique ID of the response that produced the audio.

      • JsonValue; type "output_audio_buffer.cleared"constant

        The event type, must be output_audio_buffer.cleared.

        • OUTPUT_AUDIO_BUFFER_CLEARED("output_audio_buffer.cleared")
    • class ConversationItemAdded:

      Sent by the server when an Item is added to the default Conversation. This can happen in several cases:

      • When the client sends a conversation.item.create event.
      • When the input audio buffer is committed. In this case the item will be a user message containing the audio from the buffer.
      • When the model is generating a Response. In this case the conversation.item.added event will be sent when the model starts generating a specific Item, and thus it will not yet have any content (and status will be in_progress).

      The event will include the full content of the Item (except when model is generating a Response) except for audio data, which can be retrieved separately with a conversation.item.retrieve event if necessary.

      • String eventId

        The unique ID of the server event.

      • ConversationItem item

        A single item within a Realtime conversation.

      • JsonValue; type "conversation.item.added"constant

        The event type, must be conversation.item.added.

        • CONVERSATION_ITEM_ADDED("conversation.item.added")
      • Optional<String> previousItemId

        The ID of the item that precedes this one, if any. This is used to maintain ordering when items are inserted.

    • class ConversationItemDone:

      Returned when a conversation item is finalized.

      The event will include the full content of the Item except for audio data, which can be retrieved separately with a conversation.item.retrieve event if needed.

      • String eventId

        The unique ID of the server event.

      • ConversationItem item

        A single item within a Realtime conversation.

      • JsonValue; type "conversation.item.done"constant

        The event type, must be conversation.item.done.

        • CONVERSATION_ITEM_DONE("conversation.item.done")
      • Optional<String> previousItemId

        The ID of the item that precedes this one, if any. This is used to maintain ordering when items are inserted.

    • class InputAudioBufferTimeoutTriggered:

      Returned when the Server VAD timeout is triggered for the input audio buffer. This is configured with idle_timeout_ms in the turn_detection settings of the session, and it indicates that there hasn't been any speech detected for the configured duration.

      The audio_start_ms and audio_end_ms fields indicate the segment of audio after the last model response up to the triggering time, as an offset from the beginning of audio written to the input audio buffer. This means it demarcates the segment of audio that was silent and the difference between the start and end values will roughly match the configured timeout.

      The empty audio will be committed to the conversation as an input_audio item (there will be a input_audio_buffer.committed event) and a model response will be generated. There may be speech that didn't trigger VAD but is still detected by the model, so the model may respond with something relevant to the conversation or a prompt to continue speaking.

      • long audioEndMs

        Millisecond offset of audio written to the input audio buffer at the time the timeout was triggered.

      • long audioStartMs

        Millisecond offset of audio written to the input audio buffer that was after the playback time of the last model response.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item associated with this segment.

      • JsonValue; type "input_audio_buffer.timeout_triggered"constant

        The event type, must be input_audio_buffer.timeout_triggered.

        • INPUT_AUDIO_BUFFER_TIMEOUT_TRIGGERED("input_audio_buffer.timeout_triggered")
    • class ConversationItemInputAudioTranscriptionSegment:

      Returned when an input audio transcription segment is identified for an item.

      • String id

        The segment identifier.

      • long contentIndex

        The index of the input audio content part within the item.

      • double end

        End time of the segment in seconds.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the item containing the input audio content.

      • String speaker

        The detected speaker label for this segment.

      • double start

        Start time of the segment in seconds.

      • String text

        The text for this segment.

      • JsonValue; type "conversation.item.input_audio_transcription.segment"constant

        The event type, must be conversation.item.input_audio_transcription.segment.

        • CONVERSATION_ITEM_INPUT_AUDIO_TRANSCRIPTION_SEGMENT("conversation.item.input_audio_transcription.segment")
    • class McpListToolsInProgress:

      Returned when listing MCP tools is in progress for an item.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the MCP list tools item.

      • JsonValue; type "mcp_list_tools.in_progress"constant

        The event type, must be mcp_list_tools.in_progress.

        • MCP_LIST_TOOLS_IN_PROGRESS("mcp_list_tools.in_progress")
    • class McpListToolsCompleted:

      Returned when listing MCP tools has completed for an item.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the MCP list tools item.

      • JsonValue; type "mcp_list_tools.completed"constant

        The event type, must be mcp_list_tools.completed.

        • MCP_LIST_TOOLS_COMPLETED("mcp_list_tools.completed")
    • class McpListToolsFailed:

      Returned when listing MCP tools has failed for an item.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the MCP list tools item.

      • JsonValue; type "mcp_list_tools.failed"constant

        The event type, must be mcp_list_tools.failed.

        • MCP_LIST_TOOLS_FAILED("mcp_list_tools.failed")
    • class ResponseMcpCallArgumentsDelta:

      Returned when MCP tool call arguments are updated during response generation.

      • String delta

        The JSON-encoded arguments delta.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the MCP tool call item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • JsonValue; type "response.mcp_call_arguments.delta"constant

        The event type, must be response.mcp_call_arguments.delta.

        • RESPONSE_MCP_CALL_ARGUMENTS_DELTA("response.mcp_call_arguments.delta")
      • Optional<String> obfuscation

        If present, indicates the delta text was obfuscated.

    • class ResponseMcpCallArgumentsDone:

      Returned when MCP tool call arguments are finalized during response generation.

      • String arguments

        The final JSON-encoded arguments string.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the MCP tool call item.

      • long outputIndex

        The index of the output item in the response.

      • String responseId

        The ID of the response.

      • JsonValue; type "response.mcp_call_arguments.done"constant

        The event type, must be response.mcp_call_arguments.done.

        • RESPONSE_MCP_CALL_ARGUMENTS_DONE("response.mcp_call_arguments.done")
    • class ResponseMcpCallInProgress:

      Returned when an MCP tool call has started and is in progress.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the MCP tool call item.

      • long outputIndex

        The index of the output item in the response.

      • JsonValue; type "response.mcp_call.in_progress"constant

        The event type, must be response.mcp_call.in_progress.

        • RESPONSE_MCP_CALL_IN_PROGRESS("response.mcp_call.in_progress")
    • class ResponseMcpCallCompleted:

      Returned when an MCP tool call has completed successfully.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the MCP tool call item.

      • long outputIndex

        The index of the output item in the response.

      • JsonValue; type "response.mcp_call.completed"constant

        The event type, must be response.mcp_call.completed.

        • RESPONSE_MCP_CALL_COMPLETED("response.mcp_call.completed")
    • class ResponseMcpCallFailed:

      Returned when an MCP tool call has failed.

      • String eventId

        The unique ID of the server event.

      • String itemId

        The ID of the MCP tool call item.

      • long outputIndex

        The index of the output item in the response.

      • JsonValue; type "response.mcp_call.failed"constant

        The event type, must be response.mcp_call.failed.

        • RESPONSE_MCP_CALL_FAILED("response.mcp_call.failed")

Realtime Session

  • class RealtimeSession:

    Realtime session object for the beta interface.

    • Optional<String> id

      Unique identifier for the session that looks like sess_1234567890abcdef.

    • Optional<Long> expiresAt

      Expiration timestamp for the session, in seconds since epoch.

    • Optional<List<Include>> include

      Additional fields to include in server outputs.

      • item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

      • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")

    • Optional<InputAudioFormat> inputAudioFormat

      The format of input audio. Options are pcm16, g711_ulaw, or g711_alaw. For pcm16, input audio must be 16-bit PCM at a 24kHz sample rate, single channel (mono), and little-endian byte order.

      • PCM16("pcm16")

      • G711_ULAW("g711_ulaw")

      • G711_ALAW("g711_alaw")

    • Optional<InputAudioNoiseReduction> inputAudioNoiseReduction

      Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

      • Optional<NoiseReductionType> type

        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

        • NEAR_FIELD("near_field")

        • FAR_FIELD("far_field")

    • Optional<AudioTranscription> inputAudioTranscription

      Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

      • Optional<Delay> delay

        Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

        • MINIMAL("minimal")

        • LOW("low")

        • MEDIUM("medium")

        • HIGH("high")

        • XHIGH("xhigh")

      • Optional<String> language

        The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

      • Optional<Model> model

        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

        • WHISPER_1("whisper-1")

        • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

        • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

        • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

        • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

        • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

      • Optional<String> prompt

        An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

    • Optional<String> instructions

      The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

      Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

    • Optional<MaxResponseOutputTokens> maxResponseOutputTokens

      Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

      • long

      • JsonValue;

        • INF("inf")
    • Optional<List<Modality>> modalities

      The set of modalities the model can respond with. To disable audio, set this to ["text"].

      • TEXT("text")

      • AUDIO("audio")

    • Optional<Model> model

      The Realtime model used for this session.

      • GPT_REALTIME("gpt-realtime")

      • GPT_REALTIME_1_5("gpt-realtime-1.5")

      • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

      • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

      • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

      • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

      • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

      • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

      • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

      • GPT_REALTIME_MINI("gpt-realtime-mini")

      • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

      • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

      • GPT_AUDIO_1_5("gpt-audio-1.5")

      • GPT_AUDIO_MINI("gpt-audio-mini")

      • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

      • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

    • Optional<Object> object_

      The object type. Always realtime.session.

      • REALTIME_SESSION("realtime.session")
    • Optional<OutputAudioFormat> outputAudioFormat

      The format of output audio. Options are pcm16, g711_ulaw, or g711_alaw. For pcm16, output audio is sampled at a rate of 24kHz.

      • PCM16("pcm16")

      • G711_ULAW("g711_ulaw")

      • G711_ALAW("g711_alaw")

    • Optional<ResponsePrompt> prompt

      Reference to a prompt template and its variables. Learn more.

      • String id

        The unique identifier of the prompt template to use.

      • Optional<Variables> variables

        Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

        • String

        • class ResponseInputText:

          A text input to the model.

          • String text

            The text input to the model.

          • JsonValue; type "input_text"constant

            The type of the input item. Always input_text.

            • INPUT_TEXT("input_text")
        • class ResponseInputImage:

          An image input to the model. Learn about image inputs.

          • Detail detail

            The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

            • LOW("low")

            • HIGH("high")

            • AUTO("auto")

            • ORIGINAL("original")

          • JsonValue; type "input_image"constant

            The type of the input item. Always input_image.

            • INPUT_IMAGE("input_image")
          • Optional<String> fileId

            The ID of the file to be sent to the model.

          • Optional<String> imageUrl

            The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

        • class ResponseInputFile:

          A file input to the model.

          • JsonValue; type "input_file"constant

            The type of the input item. Always input_file.

            • INPUT_FILE("input_file")
          • Optional<Detail> detail

            The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

            • LOW("low")

            • HIGH("high")

          • Optional<String> fileData

            The content of the file to be sent to the model.

          • Optional<String> fileId

            The ID of the file to be sent to the model.

          • Optional<String> fileUrl

            The URL of the file to be sent to the model.

          • Optional<String> filename

            The name of the file to be sent to the model.

      • Optional<String> version

        Optional version of the prompt template.

    • Optional<Double> speed

      The speed of the model's spoken response. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

    • Optional<Double> temperature

      Sampling temperature for the model, limited to [0.6, 1.2]. For audio models a temperature of 0.8 is highly recommended for best performance.

    • Optional<String> toolChoice

      How the model chooses tools. Options are auto, none, required, or specify a function.

    • Optional<List<RealtimeFunctionTool>> tools

      Tools (functions) available to the model.

      • Optional<String> description

        The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

      • Optional<String> name

        The name of the function.

      • Optional<JsonValue> parameters

        Parameters of the function in JSON Schema.

      • Optional<Type> type

        The type of the tool, i.e. function.

        • FUNCTION("function")
    • Optional<Tracing> tracing

      Configuration options for tracing. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

      auto will create a trace for the session with default values for the workflow name, group id, and metadata.

      • JsonValue;

        • AUTO("auto")
      • class TracingConfiguration:

        Granular configuration for tracing.

        • Optional<String> groupId

          The group id to attach to this trace to enable filtering and grouping in the traces dashboard.

        • Optional<JsonValue> metadata

          The arbitrary metadata to attach to this trace to enable filtering in the traces dashboard.

        • Optional<String> workflowName

          The name of the workflow to attach to this trace. This is used to name the trace in the traces dashboard.

    • Optional<TurnDetection> turnDetection

      Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

      Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

      Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

      For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

      • class ServerVad:

        Server-side voice activity detection (VAD) which flips on when user speech is detected and off after a period of silence.

        • JsonValue; type "server_vad"constant

          Type of turn detection, server_vad to turn on simple Server VAD.

          • SERVER_VAD("server_vad")
        • Optional<Boolean> createResponse

          Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

          If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

        • Optional<Long> idleTimeoutMs

          Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

          The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

          An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

        • Optional<Boolean> interruptResponse

          Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

          If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

        • Optional<Long> prefixPaddingMs

          Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

        • Optional<Long> silenceDurationMs

          Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

        • Optional<Double> threshold

          Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

      • class SemanticVad:

        Server-side semantic turn detection which uses a model to determine when the user has finished speaking.

        • JsonValue; type "semantic_vad"constant

          Type of turn detection, semantic_vad to turn on Semantic VAD.

          • SEMANTIC_VAD("semantic_vad")
        • Optional<Boolean> createResponse

          Whether or not to automatically generate a response when a VAD stop event occurs.

        • Optional<Eagerness> eagerness

          Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

          • LOW("low")

          • MEDIUM("medium")

          • HIGH("high")

          • AUTO("auto")

        • Optional<Boolean> interruptResponse

          Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

    • Optional<Voice> voice

      The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, and verse.

      • ALLOY("alloy")

      • ASH("ash")

      • BALLAD("ballad")

      • CORAL("coral")

      • ECHO("echo")

      • SAGE("sage")

      • SHIMMER("shimmer")

      • VERSE("verse")

      • MARIN("marin")

      • CEDAR("cedar")

Realtime Session Create Request

  • class RealtimeSessionCreateRequest:

    Realtime session object configuration.

    • JsonValue; type "realtime"constant

      The type of session to create. Always realtime for the Realtime API.

      • REALTIME("realtime")
    • Optional<RealtimeAudioConfig> audio

      Configuration for input and output audio.

      • Optional<RealtimeAudioConfigInput> input

        • Optional<RealtimeAudioFormats> format

          The format of the input audio.

          • AudioPcm

            • Optional<Rate> rate

              The sample rate of the audio. Always 24000.

              • _24000(24000)
            • Optional<Type> type

              The audio format. Always audio/pcm.

              • AUDIO_PCM("audio/pcm")
          • AudioPcmu

            • Optional<Type> type

              The audio format. Always audio/pcmu.

              • AUDIO_PCMU("audio/pcmu")
          • AudioPcma

            • Optional<Type> type

              The audio format. Always audio/pcma.

              • AUDIO_PCMA("audio/pcma")
        • Optional<NoiseReduction> noiseReduction

          Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

          • Optional<NoiseReductionType> type

            Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • NEAR_FIELD("near_field")

            • FAR_FIELD("far_field")

        • Optional<AudioTranscription> transcription

          Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

          • Optional<Delay> delay

            Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

          • Optional<String> language

            The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

          • Optional<Model> model

            The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

            • WHISPER_1("whisper-1")

            • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

            • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

            • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

            • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

            • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

          • Optional<String> prompt

            An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

        • Optional<RealtimeAudioInputTurnDetection> turnDetection

          Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

          Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

          Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

          For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

          • ServerVad

            • JsonValue; type "server_vad"constant

              Type of turn detection, server_vad to turn on simple Server VAD.

              • SERVER_VAD("server_vad")
            • Optional<Boolean> createResponse

              Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

              If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

            • Optional<Long> idleTimeoutMs

              Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

              The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

              An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

            • Optional<Boolean> interruptResponse

              Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

              If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

            • Optional<Long> prefixPaddingMs

              Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

            • Optional<Long> silenceDurationMs

              Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

            • Optional<Double> threshold

              Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

          • SemanticVad

            • JsonValue; type "semantic_vad"constant

              Type of turn detection, semantic_vad to turn on Semantic VAD.

              • SEMANTIC_VAD("semantic_vad")
            • Optional<Boolean> createResponse

              Whether or not to automatically generate a response when a VAD stop event occurs.

            • Optional<Eagerness> eagerness

              Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

              • LOW("low")

              • MEDIUM("medium")

              • HIGH("high")

              • AUTO("auto")

            • Optional<Boolean> interruptResponse

              Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

      • Optional<RealtimeAudioConfigOutput> output

        • Optional<RealtimeAudioFormats> format

          The format of the output audio.

        • Optional<Double> speed

          The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

          This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

        • Optional<Voice> voice

          The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

          • String

          • enum UnionMember1:

            • ALLOY("alloy")

            • ASH("ash")

            • BALLAD("ballad")

            • CORAL("coral")

            • ECHO("echo")

            • SAGE("sage")

            • SHIMMER("shimmer")

            • VERSE("verse")

            • MARIN("marin")

            • CEDAR("cedar")

          • class Id:

            Custom voice reference.

            • String id

              The custom voice ID, e.g. voice_1234.

    • Optional<List<Include>> include

      Additional fields to include in server outputs.

      item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

      • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
    • Optional<String> instructions

      The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

      Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

    • Optional<MaxOutputTokens> maxOutputTokens

      Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

      • long

      • JsonValue;

        • INF("inf")
    • Optional<Model> model

      The Realtime model used for this session.

      • GPT_REALTIME("gpt-realtime")

      • GPT_REALTIME_1_5("gpt-realtime-1.5")

      • GPT_REALTIME_2("gpt-realtime-2")

      • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

      • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

      • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

      • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

      • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

      • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

      • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

      • GPT_REALTIME_MINI("gpt-realtime-mini")

      • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

      • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

      • GPT_AUDIO_1_5("gpt-audio-1.5")

      • GPT_AUDIO_MINI("gpt-audio-mini")

      • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

      • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

    • Optional<List<OutputModality>> outputModalities

      The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

      • TEXT("text")

      • AUDIO("audio")

    • Optional<Boolean> parallelToolCalls

      Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

    • Optional<ResponsePrompt> prompt

      Reference to a prompt template and its variables. Learn more.

      • String id

        The unique identifier of the prompt template to use.

      • Optional<Variables> variables

        Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

        • String

        • class ResponseInputText:

          A text input to the model.

          • String text

            The text input to the model.

          • JsonValue; type "input_text"constant

            The type of the input item. Always input_text.

            • INPUT_TEXT("input_text")
        • class ResponseInputImage:

          An image input to the model. Learn about image inputs.

          • Detail detail

            The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

            • LOW("low")

            • HIGH("high")

            • AUTO("auto")

            • ORIGINAL("original")

          • JsonValue; type "input_image"constant

            The type of the input item. Always input_image.

            • INPUT_IMAGE("input_image")
          • Optional<String> fileId

            The ID of the file to be sent to the model.

          • Optional<String> imageUrl

            The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

        • class ResponseInputFile:

          A file input to the model.

          • JsonValue; type "input_file"constant

            The type of the input item. Always input_file.

            • INPUT_FILE("input_file")
          • Optional<Detail> detail

            The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

            • LOW("low")

            • HIGH("high")

          • Optional<String> fileData

            The content of the file to be sent to the model.

          • Optional<String> fileId

            The ID of the file to be sent to the model.

          • Optional<String> fileUrl

            The URL of the file to be sent to the model.

          • Optional<String> filename

            The name of the file to be sent to the model.

      • Optional<String> version

        Optional version of the prompt template.

    • Optional<RealtimeReasoning> reasoning

      Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

      • Optional<RealtimeReasoningEffort> effort

        Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

        • MINIMAL("minimal")

        • LOW("low")

        • MEDIUM("medium")

        • HIGH("high")

        • XHIGH("xhigh")

    • Optional<RealtimeToolChoiceConfig> toolChoice

      How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

      • enum ToolChoiceOptions:

        Controls which (if any) tool is called by the model.

        none means the model will not call any tool and instead generates a message.

        auto means the model can pick between generating a message or calling one or more tools.

        required means the model must call one or more tools.

        • NONE("none")

        • AUTO("auto")

        • REQUIRED("required")

      • class ToolChoiceFunction:

        Use this option to force the model to call a specific function.

        • String name

          The name of the function to call.

        • JsonValue; type "function"constant

          For function calling, the type is always function.

          • FUNCTION("function")
      • class ToolChoiceMcp:

        Use this option to force the model to call a specific tool on a remote MCP server.

        • String serverLabel

          The label of the MCP server to use.

        • JsonValue; type "mcp"constant

          For MCP tools, the type is always mcp.

          • MCP("mcp")
        • Optional<String> name

          The name of the tool to call on the server.

    • Optional<List<RealtimeToolsConfigUnion>> tools

      Tools available to the model.

      • class RealtimeFunctionTool:

        • Optional<String> description

          The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

        • Optional<String> name

          The name of the function.

        • Optional<JsonValue> parameters

          Parameters of the function in JSON Schema.

        • Optional<Type> type

          The type of the tool, i.e. function.

          • FUNCTION("function")
      • Mcp

        • String serverLabel

          A label for this MCP server, used to identify it in tool calls.

        • JsonValue; type "mcp"constant

          The type of the MCP tool. Always mcp.

          • MCP("mcp")
        • Optional<AllowedTools> allowedTools

          List of allowed tool names or a filter object.

          • List<String>

          • class McpToolFilter:

            A filter object to specify which tools are allowed.

            • Optional<Boolean> readOnly

              Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

            • Optional<List<String>> toolNames

              List of allowed tool names.

        • Optional<String> authorization

          An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

        • Optional<ConnectorId> connectorId

          Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

          Currently supported connector_id values are:

          • Dropbox: connector_dropbox

          • Gmail: connector_gmail

          • Google Calendar: connector_googlecalendar

          • Google Drive: connector_googledrive

          • Microsoft Teams: connector_microsoftteams

          • Outlook Calendar: connector_outlookcalendar

          • Outlook Email: connector_outlookemail

          • SharePoint: connector_sharepoint

          • CONNECTOR_DROPBOX("connector_dropbox")

          • CONNECTOR_GMAIL("connector_gmail")

          • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

          • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

          • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

          • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

          • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

          • CONNECTOR_SHAREPOINT("connector_sharepoint")

        • Optional<Boolean> deferLoading

          Whether this MCP tool is deferred and discovered via tool search.

        • Optional<Headers> headers

          Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

        • Optional<RequireApproval> requireApproval

          Specify which of the MCP server's tools require approval.

          • class McpToolApprovalFilter:

            Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

            • Optional<Always> always

              A filter object to specify which tools are allowed.

              • Optional<Boolean> readOnly

                Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

              • Optional<List<String>> toolNames

                List of allowed tool names.

            • Optional<Never> never

              A filter object to specify which tools are allowed.

              • Optional<Boolean> readOnly

                Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

              • Optional<List<String>> toolNames

                List of allowed tool names.

          • enum McpToolApprovalSetting:

            Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

            • ALWAYS("always")

            • NEVER("never")

        • Optional<String> serverDescription

          Optional description of the MCP server, used to provide more context.

        • Optional<String> serverUrl

          The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

        • Optional<String> tunnelId

          The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

    • Optional<RealtimeTracingConfig> tracing

      Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

      auto will create a trace for the session with default values for the workflow name, group id, and metadata.

      • JsonValue;

        • AUTO("auto")
      • TracingConfiguration

        • Optional<String> groupId

          The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

        • Optional<JsonValue> metadata

          The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

        • Optional<String> workflowName

          The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

    • Optional<RealtimeTruncation> truncation

      When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

      Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

      Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

      Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

      • RealtimeTruncationStrategy

        • AUTO("auto")

        • DISABLED("disabled")

      • class RealtimeTruncationRetentionRatio:

        Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

        • double retentionRatio

          Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

        • JsonValue; type "retention_ratio"constant

          Use retention ratio truncation.

          • RETENTION_RATIO("retention_ratio")
        • Optional<TokenLimits> tokenLimits

          Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

          • Optional<Long> postInstructions

            Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

Realtime Tool Choice Config

  • class RealtimeToolChoiceConfig: A class that can be one of several variants.union

    How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

    • enum ToolChoiceOptions:

      Controls which (if any) tool is called by the model.

      none means the model will not call any tool and instead generates a message.

      auto means the model can pick between generating a message or calling one or more tools.

      required means the model must call one or more tools.

      • NONE("none")

      • AUTO("auto")

      • REQUIRED("required")

    • class ToolChoiceFunction:

      Use this option to force the model to call a specific function.

      • String name

        The name of the function to call.

      • JsonValue; type "function"constant

        For function calling, the type is always function.

        • FUNCTION("function")
    • class ToolChoiceMcp:

      Use this option to force the model to call a specific tool on a remote MCP server.

      • String serverLabel

        The label of the MCP server to use.

      • JsonValue; type "mcp"constant

        For MCP tools, the type is always mcp.

        • MCP("mcp")
      • Optional<String> name

        The name of the tool to call on the server.

Realtime Tools Config Union

  • class RealtimeToolsConfigUnion: A class that can be one of several variants.union

    Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

    • class RealtimeFunctionTool:

      • Optional<String> description

        The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

      • Optional<String> name

        The name of the function.

      • Optional<JsonValue> parameters

        Parameters of the function in JSON Schema.

      • Optional<Type> type

        The type of the tool, i.e. function.

        • FUNCTION("function")
    • Mcp

      • String serverLabel

        A label for this MCP server, used to identify it in tool calls.

      • JsonValue; type "mcp"constant

        The type of the MCP tool. Always mcp.

        • MCP("mcp")
      • Optional<AllowedTools> allowedTools

        List of allowed tool names or a filter object.

        • List<String>

        • class McpToolFilter:

          A filter object to specify which tools are allowed.

          • Optional<Boolean> readOnly

            Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

          • Optional<List<String>> toolNames

            List of allowed tool names.

      • Optional<String> authorization

        An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

      • Optional<ConnectorId> connectorId

        Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

        Currently supported connector_id values are:

        • Dropbox: connector_dropbox

        • Gmail: connector_gmail

        • Google Calendar: connector_googlecalendar

        • Google Drive: connector_googledrive

        • Microsoft Teams: connector_microsoftteams

        • Outlook Calendar: connector_outlookcalendar

        • Outlook Email: connector_outlookemail

        • SharePoint: connector_sharepoint

        • CONNECTOR_DROPBOX("connector_dropbox")

        • CONNECTOR_GMAIL("connector_gmail")

        • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

        • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

        • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

        • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

        • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

        • CONNECTOR_SHAREPOINT("connector_sharepoint")

      • Optional<Boolean> deferLoading

        Whether this MCP tool is deferred and discovered via tool search.

      • Optional<Headers> headers

        Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

      • Optional<RequireApproval> requireApproval

        Specify which of the MCP server's tools require approval.

        • class McpToolApprovalFilter:

          Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

          • Optional<Always> always

            A filter object to specify which tools are allowed.

            • Optional<Boolean> readOnly

              Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

            • Optional<List<String>> toolNames

              List of allowed tool names.

          • Optional<Never> never

            A filter object to specify which tools are allowed.

            • Optional<Boolean> readOnly

              Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

            • Optional<List<String>> toolNames

              List of allowed tool names.

        • enum McpToolApprovalSetting:

          Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

          • ALWAYS("always")

          • NEVER("never")

      • Optional<String> serverDescription

        Optional description of the MCP server, used to provide more context.

      • Optional<String> serverUrl

        The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

      • Optional<String> tunnelId

        The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

Realtime Tracing Config

  • class RealtimeTracingConfig: A class that can be one of several variants.union

    Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

    auto will create a trace for the session with default values for the workflow name, group id, and metadata.

    • JsonValue;

      • AUTO("auto")
    • TracingConfiguration

      • Optional<String> groupId

        The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

      • Optional<JsonValue> metadata

        The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

      • Optional<String> workflowName

        The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

Realtime Transcription Session Audio

  • class RealtimeTranscriptionSessionAudio:

    Configuration for input and output audio.

    • Optional<RealtimeTranscriptionSessionAudioInput> input

      • Optional<RealtimeAudioFormats> format

        The PCM audio format. Only a 24kHz sample rate is supported.

        • AudioPcm

          • Optional<Rate> rate

            The sample rate of the audio. Always 24000.

            • _24000(24000)
          • Optional<Type> type

            The audio format. Always audio/pcm.

            • AUDIO_PCM("audio/pcm")
        • AudioPcmu

          • Optional<Type> type

            The audio format. Always audio/pcmu.

            • AUDIO_PCMU("audio/pcmu")
        • AudioPcma

          • Optional<Type> type

            The audio format. Always audio/pcma.

            • AUDIO_PCMA("audio/pcma")
      • Optional<NoiseReduction> noiseReduction

        Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

        • Optional<NoiseReductionType> type

          Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

          • NEAR_FIELD("near_field")

          • FAR_FIELD("far_field")

      • Optional<AudioTranscription> transcription

        Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

        • Optional<Delay> delay

          Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

          • MINIMAL("minimal")

          • LOW("low")

          • MEDIUM("medium")

          • HIGH("high")

          • XHIGH("xhigh")

        • Optional<String> language

          The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

        • Optional<Model> model

          The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

          • WHISPER_1("whisper-1")

          • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

          • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

          • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

          • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

          • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

        • Optional<String> prompt

          An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

      • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

        Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

        Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

        Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

        For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

        • ServerVad

          • JsonValue; type "server_vad"constant

            Type of turn detection, server_vad to turn on simple Server VAD.

            • SERVER_VAD("server_vad")
          • Optional<Boolean> createResponse

            Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

            If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

          • Optional<Long> idleTimeoutMs

            Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

            The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

            An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

          • Optional<Boolean> interruptResponse

            Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

            If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

          • Optional<Long> prefixPaddingMs

            Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

          • Optional<Long> silenceDurationMs

            Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

          • Optional<Double> threshold

            Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

        • SemanticVad

          • JsonValue; type "semantic_vad"constant

            Type of turn detection, semantic_vad to turn on Semantic VAD.

            • SEMANTIC_VAD("semantic_vad")
          • Optional<Boolean> createResponse

            Whether or not to automatically generate a response when a VAD stop event occurs.

          • Optional<Eagerness> eagerness

            Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • AUTO("auto")

          • Optional<Boolean> interruptResponse

            Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

Realtime Transcription Session Audio Input

  • class RealtimeTranscriptionSessionAudioInput:

    • Optional<RealtimeAudioFormats> format

      The PCM audio format. Only a 24kHz sample rate is supported.

      • AudioPcm

        • Optional<Rate> rate

          The sample rate of the audio. Always 24000.

          • _24000(24000)
        • Optional<Type> type

          The audio format. Always audio/pcm.

          • AUDIO_PCM("audio/pcm")
      • AudioPcmu

        • Optional<Type> type

          The audio format. Always audio/pcmu.

          • AUDIO_PCMU("audio/pcmu")
      • AudioPcma

        • Optional<Type> type

          The audio format. Always audio/pcma.

          • AUDIO_PCMA("audio/pcma")
    • Optional<NoiseReduction> noiseReduction

      Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

      • Optional<NoiseReductionType> type

        Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

        • NEAR_FIELD("near_field")

        • FAR_FIELD("far_field")

    • Optional<AudioTranscription> transcription

      Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

      • Optional<Delay> delay

        Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

        • MINIMAL("minimal")

        • LOW("low")

        • MEDIUM("medium")

        • HIGH("high")

        • XHIGH("xhigh")

      • Optional<String> language

        The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

      • Optional<Model> model

        The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

        • WHISPER_1("whisper-1")

        • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

        • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

        • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

        • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

        • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

      • Optional<String> prompt

        An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

    • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

      Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

      Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

      Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

      For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

      • ServerVad

        • JsonValue; type "server_vad"constant

          Type of turn detection, server_vad to turn on simple Server VAD.

          • SERVER_VAD("server_vad")
        • Optional<Boolean> createResponse

          Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

          If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

        • Optional<Long> idleTimeoutMs

          Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

          The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

          An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

        • Optional<Boolean> interruptResponse

          Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

          If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

        • Optional<Long> prefixPaddingMs

          Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

        • Optional<Long> silenceDurationMs

          Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

        • Optional<Double> threshold

          Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

      • SemanticVad

        • JsonValue; type "semantic_vad"constant

          Type of turn detection, semantic_vad to turn on Semantic VAD.

          • SEMANTIC_VAD("semantic_vad")
        • Optional<Boolean> createResponse

          Whether or not to automatically generate a response when a VAD stop event occurs.

        • Optional<Eagerness> eagerness

          Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

          • LOW("low")

          • MEDIUM("medium")

          • HIGH("high")

          • AUTO("auto")

        • Optional<Boolean> interruptResponse

          Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

Realtime Transcription Session Audio Input Turn Detection

  • class RealtimeTranscriptionSessionAudioInputTurnDetection: A class that can be one of several variants.union

    Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

    Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

    Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

    For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

    • ServerVad

      • JsonValue; type "server_vad"constant

        Type of turn detection, server_vad to turn on simple Server VAD.

        • SERVER_VAD("server_vad")
      • Optional<Boolean> createResponse

        Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

      • Optional<Long> idleTimeoutMs

        Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

        The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

        An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

      • Optional<Boolean> interruptResponse

        Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

        If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

      • Optional<Long> prefixPaddingMs

        Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

      • Optional<Long> silenceDurationMs

        Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

      • Optional<Double> threshold

        Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

    • SemanticVad

      • JsonValue; type "semantic_vad"constant

        Type of turn detection, semantic_vad to turn on Semantic VAD.

        • SEMANTIC_VAD("semantic_vad")
      • Optional<Boolean> createResponse

        Whether or not to automatically generate a response when a VAD stop event occurs.

      • Optional<Eagerness> eagerness

        Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

        • LOW("low")

        • MEDIUM("medium")

        • HIGH("high")

        • AUTO("auto")

      • Optional<Boolean> interruptResponse

        Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

Realtime Transcription Session Create Request

  • class RealtimeTranscriptionSessionCreateRequest:

    Realtime transcription session object configuration.

    • JsonValue; type "transcription"constant

      The type of session to create. Always transcription for transcription sessions.

      • TRANSCRIPTION("transcription")
    • Optional<RealtimeTranscriptionSessionAudio> audio

      Configuration for input and output audio.

      • Optional<RealtimeTranscriptionSessionAudioInput> input

        • Optional<RealtimeAudioFormats> format

          The PCM audio format. Only a 24kHz sample rate is supported.

          • AudioPcm

            • Optional<Rate> rate

              The sample rate of the audio. Always 24000.

              • _24000(24000)
            • Optional<Type> type

              The audio format. Always audio/pcm.

              • AUDIO_PCM("audio/pcm")
          • AudioPcmu

            • Optional<Type> type

              The audio format. Always audio/pcmu.

              • AUDIO_PCMU("audio/pcmu")
          • AudioPcma

            • Optional<Type> type

              The audio format. Always audio/pcma.

              • AUDIO_PCMA("audio/pcma")
        • Optional<NoiseReduction> noiseReduction

          Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

          • Optional<NoiseReductionType> type

            Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • NEAR_FIELD("near_field")

            • FAR_FIELD("far_field")

        • Optional<AudioTranscription> transcription

          Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

          • Optional<Delay> delay

            Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

          • Optional<String> language

            The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

          • Optional<Model> model

            The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

            • WHISPER_1("whisper-1")

            • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

            • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

            • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

            • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

            • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

          • Optional<String> prompt

            An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

        • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

          Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

          Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

          Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

          For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

          • ServerVad

            • JsonValue; type "server_vad"constant

              Type of turn detection, server_vad to turn on simple Server VAD.

              • SERVER_VAD("server_vad")
            • Optional<Boolean> createResponse

              Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

              If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

            • Optional<Long> idleTimeoutMs

              Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

              The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

              An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

            • Optional<Boolean> interruptResponse

              Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

              If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

            • Optional<Long> prefixPaddingMs

              Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

            • Optional<Long> silenceDurationMs

              Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

            • Optional<Double> threshold

              Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

          • SemanticVad

            • JsonValue; type "semantic_vad"constant

              Type of turn detection, semantic_vad to turn on Semantic VAD.

              • SEMANTIC_VAD("semantic_vad")
            • Optional<Boolean> createResponse

              Whether or not to automatically generate a response when a VAD stop event occurs.

            • Optional<Eagerness> eagerness

              Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

              • LOW("low")

              • MEDIUM("medium")

              • HIGH("high")

              • AUTO("auto")

            • Optional<Boolean> interruptResponse

              Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

    • Optional<List<Include>> include

      Additional fields to include in server outputs.

      item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

      • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")

Realtime Translation Client Event

  • class RealtimeTranslationClientEvent: A class that can be one of several variants.union

    A Realtime translation client event.

    • class RealtimeTranslationSessionUpdateEvent:

      Send this event to update the translation session configuration. Translation sessions support updates to audio.output.language, audio.input.transcription, and audio.input.noise_reduction.

      • RealtimeTranslationSessionUpdateRequest session

        Translation session fields to update. The session type and model are set at creation and cannot be changed with session.update.

        • Optional<Audio> audio

          Configuration for translation input and output audio.

          • Optional<Input> input

            • Optional<NoiseReduction> noiseReduction

              Optional input noise reduction. Set to null to disable it.

              • NoiseReductionType type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                • NEAR_FIELD("near_field")

                • FAR_FIELD("far_field")

            • Optional<Transcription> transcription

              Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

              • String model

                The transcription model to use for source transcript deltas.

          • Optional<Output> output

            • Optional<String> language

              Target language for translated output audio and transcript deltas.

      • JsonValue; type "session.update"constant

        The event type, must be session.update.

        • SESSION_UPDATE("session.update")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

    • class RealtimeTranslationInputAudioBufferAppendEvent:

      Send this event to append audio bytes to the translation session input audio buffer.

      WebSocket translation sessions accept base64-encoded 24 kHz PCM16 mono little-endian raw audio bytes. Unsupported websocket audio formats return a validation error because lower-quality audio materially degrades translation quality.

      Translation consumes 200 ms engine frames. For best realtime behavior, append audio in 200 ms chunks. If a chunk is shorter, the server buffers it until it has enough audio for one frame. If a chunk is longer, the server splits it into 200 ms frames and enqueues them back-to-back.

      Keep appending silence while the session is active. If a client stops sending audio and later resumes, model time treats the resumed audio as contiguous with the previous audio rather than as a real-world pause.

      • String audio

        Base64-encoded 24 kHz PCM16 mono audio bytes.

      • JsonValue; type "session.input_audio_buffer.append"constant

        The event type, must be session.input_audio_buffer.append.

        • SESSION_INPUT_AUDIO_BUFFER_APPEND("session.input_audio_buffer.append")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

    • class RealtimeTranslationSessionCloseEvent:

      Gracefully close the realtime translation session. The server flushes pending input audio and emits any remaining translated output before closing the session.

      • JsonValue; type "session.close"constant

        The event type, must be session.close.

        • SESSION_CLOSE("session.close")
      • Optional<String> eventId

        Optional client-generated ID used to identify this event.

Realtime Translation Client Secret Create Request

  • class RealtimeTranslationClientSecretCreateRequest:

    Create a translation session and client secret for the Realtime API.

    • RealtimeTranslationSessionCreateRequest session

      Realtime translation session configuration. Translation sessions stream source audio in and translated audio plus transcript deltas out continuously.

      • String model

        The Realtime translation model used for this session.

      • Optional<Audio> audio

        Configuration for translation input and output audio.

        • Optional<Input> input

          • Optional<NoiseReduction> noiseReduction

            Optional input noise reduction. Set to null to disable it.

            • NoiseReductionType type

              Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

              • NEAR_FIELD("near_field")

              • FAR_FIELD("far_field")

          • Optional<Transcription> transcription

            Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

            • String model

              The transcription model to use for source transcript deltas.

        • Optional<Output> output

          • Optional<String> language

            Target language for translated output audio and transcript deltas.

    • Optional<ExpiresAfter> expiresAfter

      Configuration for the client secret expiration. Expiration refers to the time after which a client secret will no longer be valid for creating sessions. The session itself may continue after that time once started. A secret can be used to create multiple sessions until it expires.

      • Optional<Anchor> anchor

        The anchor point for the client secret expiration, meaning that seconds will be added to the created_at time of the client secret to produce an expiration timestamp. Only created_at is currently supported.

        • CREATED_AT("created_at")
      • Optional<Long> seconds

        The number of seconds from the anchor point to the expiration. Select a value between 10 and 7200 (2 hours). This default to 600 seconds (10 minutes) if not specified.

Realtime Translation Client Secret Create Response

  • class RealtimeTranslationClientSecretCreateResponse:

    Response from creating a translation session and client secret for the Realtime API.

    • long expiresAt

      Expiration timestamp for the client secret, in seconds since epoch.

    • RealtimeTranslationSession session

      A Realtime translation session. Translation sessions continuously translate input audio into the configured output language.

      • String id

        Unique identifier for the session that looks like sess_1234567890abcdef.

      • Audio audio

        Configuration for translation input and output audio.

        • Optional<Input> input

          • Optional<NoiseReduction> noiseReduction

            Optional input noise reduction.

            • NoiseReductionType type

              Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

              • NEAR_FIELD("near_field")

              • FAR_FIELD("far_field")

          • Optional<Transcription> transcription

            Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

            • String model

              The transcription model used for source transcript deltas.

        • Optional<Output> output

          • Optional<String> language

            Target language for translated output audio and transcript deltas.

      • long expiresAt

        Expiration timestamp for the session, in seconds since epoch.

      • String model

        The Realtime translation model used for this session. This field is set at session creation and cannot be changed with session.update.

      • JsonValue; type "translation"constant

        The session type. Always translation for Realtime translation sessions.

        • TRANSLATION("translation")
    • String value

      The generated client secret value.

Realtime Translation Input Audio Buffer Append Event

  • class RealtimeTranslationInputAudioBufferAppendEvent:

    Send this event to append audio bytes to the translation session input audio buffer.

    WebSocket translation sessions accept base64-encoded 24 kHz PCM16 mono little-endian raw audio bytes. Unsupported websocket audio formats return a validation error because lower-quality audio materially degrades translation quality.

    Translation consumes 200 ms engine frames. For best realtime behavior, append audio in 200 ms chunks. If a chunk is shorter, the server buffers it until it has enough audio for one frame. If a chunk is longer, the server splits it into 200 ms frames and enqueues them back-to-back.

    Keep appending silence while the session is active. If a client stops sending audio and later resumes, model time treats the resumed audio as contiguous with the previous audio rather than as a real-world pause.

    • String audio

      Base64-encoded 24 kHz PCM16 mono audio bytes.

    • JsonValue; type "session.input_audio_buffer.append"constant

      The event type, must be session.input_audio_buffer.append.

      • SESSION_INPUT_AUDIO_BUFFER_APPEND("session.input_audio_buffer.append")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Realtime Translation Input Transcript Delta Event

  • class RealtimeTranslationInputTranscriptDeltaEvent:

    Returned when optional source-language transcript text is available. This event is emitted only when audio.input.transcription is configured.

    Transcript deltas are append-only text fragments. Clients should not insert unconditional spaces between deltas.

    • String delta

      Append-only source-language transcript text.

    • String eventId

      The unique ID of the server event.

    • JsonValue; type "session.input_transcript.delta"constant

      The event type, must be session.input_transcript.delta.

      • SESSION_INPUT_TRANSCRIPT_DELTA("session.input_transcript.delta")
    • Optional<Long> elapsedMs

      Timing metadata for stream alignment, derived from the translation frame when available. It advances in 200 ms increments, but multiple transcript deltas may share the same elapsed_ms. Treat it as alignment metadata, not a unique transcript-delta identifier.

Realtime Translation Output Audio Delta Event

  • class RealtimeTranslationOutputAudioDeltaEvent:

    Returned when translated output audio is available. Output audio deltas are 200 ms frames of PCM16 audio.

    • String delta

      Base64-encoded translated audio data.

    • String eventId

      The unique ID of the server event.

    • JsonValue; type "session.output_audio.delta"constant

      The event type, must be session.output_audio.delta.

      • SESSION_OUTPUT_AUDIO_DELTA("session.output_audio.delta")
    • Optional<Long> channels

      Number of audio channels.

    • Optional<Long> elapsedMs

      Timing metadata for stream alignment, derived from the translation frame when available. Treat elapsed_ms as alignment metadata, not a unique event identifier.

    • Optional<Format> format

      Audio encoding for delta.

      • PCM16("pcm16")
    • Optional<Long> sampleRate

      Sample rate of the audio delta.

Realtime Translation Output Transcript Delta Event

  • class RealtimeTranslationOutputTranscriptDeltaEvent:

    Returned when translated transcript text is available.

    Transcript deltas are append-only text fragments. Clients should not insert unconditional spaces between deltas.

    • String delta

      Append-only transcript text for the translated output audio.

    • String eventId

      The unique ID of the server event.

    • JsonValue; type "session.output_transcript.delta"constant

      The event type, must be session.output_transcript.delta.

      • SESSION_OUTPUT_TRANSCRIPT_DELTA("session.output_transcript.delta")
    • Optional<Long> elapsedMs

      Timing metadata for stream alignment, derived from the translation frame when available. It advances in 200 ms increments, but multiple transcript deltas may share the same elapsed_ms. Treat it as alignment metadata, not a unique transcript-delta identifier.

Realtime Translation Server Event

  • class RealtimeTranslationServerEvent: A class that can be one of several variants.union

    A Realtime translation server event.

    • class RealtimeErrorEvent:

      Returned when an error occurs, which could be a client problem or a server problem. Most errors are recoverable and the session will stay open, we recommend to implementors to monitor and log error messages by default.

      • RealtimeError error

        Details of the error.

        • String message

          A human-readable error message.

        • String type

          The type of error (e.g., "invalid_request_error", "server_error").

        • Optional<String> code

          Error code, if any.

        • Optional<String> eventId

          The event_id of the client event that caused the error, if applicable.

        • Optional<String> param

          Parameter related to the error, if any.

      • String eventId

        The unique ID of the server event.

      • JsonValue; type "error"constant

        The event type, must be error.

        • ERROR("error")
    • class RealtimeTranslationSessionCreatedEvent:

      Returned when a translation session is created. Emitted automatically when a new connection is established as the first server event. This event contains the default translation session configuration.

      • String eventId

        The unique ID of the server event.

      • RealtimeTranslationSession session

        The translation session configuration.

        • String id

          Unique identifier for the session that looks like sess_1234567890abcdef.

        • Audio audio

          Configuration for translation input and output audio.

          • Optional<Input> input

            • Optional<NoiseReduction> noiseReduction

              Optional input noise reduction.

              • NoiseReductionType type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                • NEAR_FIELD("near_field")

                • FAR_FIELD("far_field")

            • Optional<Transcription> transcription

              Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

              • String model

                The transcription model used for source transcript deltas.

          • Optional<Output> output

            • Optional<String> language

              Target language for translated output audio and transcript deltas.

        • long expiresAt

          Expiration timestamp for the session, in seconds since epoch.

        • String model

          The Realtime translation model used for this session. This field is set at session creation and cannot be changed with session.update.

        • JsonValue; type "translation"constant

          The session type. Always translation for Realtime translation sessions.

          • TRANSLATION("translation")
      • JsonValue; type "session.created"constant

        The event type, must be session.created.

        • SESSION_CREATED("session.created")
    • class RealtimeTranslationSessionUpdatedEvent:

      Returned when a translation session is updated with a session.update event, unless there is an error.

      • String eventId

        The unique ID of the server event.

      • RealtimeTranslationSession session

        The translation session configuration.

      • JsonValue; type "session.updated"constant

        The event type, must be session.updated.

        • SESSION_UPDATED("session.updated")
    • class RealtimeTranslationSessionClosedEvent:

      Returned when a realtime translation session is closed.

      • String eventId

        The unique ID of the server event.

      • JsonValue; type "session.closed"constant

        The event type, must be session.closed.

        • SESSION_CLOSED("session.closed")
    • class RealtimeTranslationInputTranscriptDeltaEvent:

      Returned when optional source-language transcript text is available. This event is emitted only when audio.input.transcription is configured.

      Transcript deltas are append-only text fragments. Clients should not insert unconditional spaces between deltas.

      • String delta

        Append-only source-language transcript text.

      • String eventId

        The unique ID of the server event.

      • JsonValue; type "session.input_transcript.delta"constant

        The event type, must be session.input_transcript.delta.

        • SESSION_INPUT_TRANSCRIPT_DELTA("session.input_transcript.delta")
      • Optional<Long> elapsedMs

        Timing metadata for stream alignment, derived from the translation frame when available. It advances in 200 ms increments, but multiple transcript deltas may share the same elapsed_ms. Treat it as alignment metadata, not a unique transcript-delta identifier.

    • class RealtimeTranslationOutputTranscriptDeltaEvent:

      Returned when translated transcript text is available.

      Transcript deltas are append-only text fragments. Clients should not insert unconditional spaces between deltas.

      • String delta

        Append-only transcript text for the translated output audio.

      • String eventId

        The unique ID of the server event.

      • JsonValue; type "session.output_transcript.delta"constant

        The event type, must be session.output_transcript.delta.

        • SESSION_OUTPUT_TRANSCRIPT_DELTA("session.output_transcript.delta")
      • Optional<Long> elapsedMs

        Timing metadata for stream alignment, derived from the translation frame when available. It advances in 200 ms increments, but multiple transcript deltas may share the same elapsed_ms. Treat it as alignment metadata, not a unique transcript-delta identifier.

    • class RealtimeTranslationOutputAudioDeltaEvent:

      Returned when translated output audio is available. Output audio deltas are 200 ms frames of PCM16 audio.

      • String delta

        Base64-encoded translated audio data.

      • String eventId

        The unique ID of the server event.

      • JsonValue; type "session.output_audio.delta"constant

        The event type, must be session.output_audio.delta.

        • SESSION_OUTPUT_AUDIO_DELTA("session.output_audio.delta")
      • Optional<Long> channels

        Number of audio channels.

      • Optional<Long> elapsedMs

        Timing metadata for stream alignment, derived from the translation frame when available. Treat elapsed_ms as alignment metadata, not a unique event identifier.

      • Optional<Format> format

        Audio encoding for delta.

        • PCM16("pcm16")
      • Optional<Long> sampleRate

        Sample rate of the audio delta.

Realtime Translation Session

  • class RealtimeTranslationSession:

    A Realtime translation session. Translation sessions continuously translate input audio into the configured output language.

    • String id

      Unique identifier for the session that looks like sess_1234567890abcdef.

    • Audio audio

      Configuration for translation input and output audio.

      • Optional<Input> input

        • Optional<NoiseReduction> noiseReduction

          Optional input noise reduction.

          • NoiseReductionType type

            Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • NEAR_FIELD("near_field")

            • FAR_FIELD("far_field")

        • Optional<Transcription> transcription

          Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

          • String model

            The transcription model used for source transcript deltas.

      • Optional<Output> output

        • Optional<String> language

          Target language for translated output audio and transcript deltas.

    • long expiresAt

      Expiration timestamp for the session, in seconds since epoch.

    • String model

      The Realtime translation model used for this session. This field is set at session creation and cannot be changed with session.update.

    • JsonValue; type "translation"constant

      The session type. Always translation for Realtime translation sessions.

      • TRANSLATION("translation")

Realtime Translation Session Close Event

  • class RealtimeTranslationSessionCloseEvent:

    Gracefully close the realtime translation session. The server flushes pending input audio and emits any remaining translated output before closing the session.

    • JsonValue; type "session.close"constant

      The event type, must be session.close.

      • SESSION_CLOSE("session.close")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Realtime Translation Session Closed Event

  • class RealtimeTranslationSessionClosedEvent:

    Returned when a realtime translation session is closed.

    • String eventId

      The unique ID of the server event.

    • JsonValue; type "session.closed"constant

      The event type, must be session.closed.

      • SESSION_CLOSED("session.closed")

Realtime Translation Session Create Request

  • class RealtimeTranslationSessionCreateRequest:

    Realtime translation session configuration. Translation sessions stream source audio in and translated audio plus transcript deltas out continuously.

    • String model

      The Realtime translation model used for this session.

    • Optional<Audio> audio

      Configuration for translation input and output audio.

      • Optional<Input> input

        • Optional<NoiseReduction> noiseReduction

          Optional input noise reduction. Set to null to disable it.

          • NoiseReductionType type

            Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • NEAR_FIELD("near_field")

            • FAR_FIELD("far_field")

        • Optional<Transcription> transcription

          Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

          • String model

            The transcription model to use for source transcript deltas.

      • Optional<Output> output

        • Optional<String> language

          Target language for translated output audio and transcript deltas.

Realtime Translation Session Created Event

  • class RealtimeTranslationSessionCreatedEvent:

    Returned when a translation session is created. Emitted automatically when a new connection is established as the first server event. This event contains the default translation session configuration.

    • String eventId

      The unique ID of the server event.

    • RealtimeTranslationSession session

      The translation session configuration.

      • String id

        Unique identifier for the session that looks like sess_1234567890abcdef.

      • Audio audio

        Configuration for translation input and output audio.

        • Optional<Input> input

          • Optional<NoiseReduction> noiseReduction

            Optional input noise reduction.

            • NoiseReductionType type

              Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

              • NEAR_FIELD("near_field")

              • FAR_FIELD("far_field")

          • Optional<Transcription> transcription

            Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

            • String model

              The transcription model used for source transcript deltas.

        • Optional<Output> output

          • Optional<String> language

            Target language for translated output audio and transcript deltas.

      • long expiresAt

        Expiration timestamp for the session, in seconds since epoch.

      • String model

        The Realtime translation model used for this session. This field is set at session creation and cannot be changed with session.update.

      • JsonValue; type "translation"constant

        The session type. Always translation for Realtime translation sessions.

        • TRANSLATION("translation")
    • JsonValue; type "session.created"constant

      The event type, must be session.created.

      • SESSION_CREATED("session.created")

Realtime Translation Session Update Event

  • class RealtimeTranslationSessionUpdateEvent:

    Send this event to update the translation session configuration. Translation sessions support updates to audio.output.language, audio.input.transcription, and audio.input.noise_reduction.

    • RealtimeTranslationSessionUpdateRequest session

      Translation session fields to update. The session type and model are set at creation and cannot be changed with session.update.

      • Optional<Audio> audio

        Configuration for translation input and output audio.

        • Optional<Input> input

          • Optional<NoiseReduction> noiseReduction

            Optional input noise reduction. Set to null to disable it.

            • NoiseReductionType type

              Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

              • NEAR_FIELD("near_field")

              • FAR_FIELD("far_field")

          • Optional<Transcription> transcription

            Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

            • String model

              The transcription model to use for source transcript deltas.

        • Optional<Output> output

          • Optional<String> language

            Target language for translated output audio and transcript deltas.

    • JsonValue; type "session.update"constant

      The event type, must be session.update.

      • SESSION_UPDATE("session.update")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Realtime Translation Session Update Request

  • class RealtimeTranslationSessionUpdateRequest:

    Realtime translation session fields that can be updated with session.update.

    • Optional<Audio> audio

      Configuration for translation input and output audio.

      • Optional<Input> input

        • Optional<NoiseReduction> noiseReduction

          Optional input noise reduction. Set to null to disable it.

          • NoiseReductionType type

            Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • NEAR_FIELD("near_field")

            • FAR_FIELD("far_field")

        • Optional<Transcription> transcription

          Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

          • String model

            The transcription model to use for source transcript deltas.

      • Optional<Output> output

        • Optional<String> language

          Target language for translated output audio and transcript deltas.

Realtime Translation Session Updated Event

  • class RealtimeTranslationSessionUpdatedEvent:

    Returned when a translation session is updated with a session.update event, unless there is an error.

    • String eventId

      The unique ID of the server event.

    • RealtimeTranslationSession session

      The translation session configuration.

      • String id

        Unique identifier for the session that looks like sess_1234567890abcdef.

      • Audio audio

        Configuration for translation input and output audio.

        • Optional<Input> input

          • Optional<NoiseReduction> noiseReduction

            Optional input noise reduction.

            • NoiseReductionType type

              Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

              • NEAR_FIELD("near_field")

              • FAR_FIELD("far_field")

          • Optional<Transcription> transcription

            Optional source-language transcription. When configured, the server emits session.input_transcript.delta events. Translation itself still runs from the input audio stream.

            • String model

              The transcription model used for source transcript deltas.

        • Optional<Output> output

          • Optional<String> language

            Target language for translated output audio and transcript deltas.

      • long expiresAt

        Expiration timestamp for the session, in seconds since epoch.

      • String model

        The Realtime translation model used for this session. This field is set at session creation and cannot be changed with session.update.

      • JsonValue; type "translation"constant

        The session type. Always translation for Realtime translation sessions.

        • TRANSLATION("translation")
    • JsonValue; type "session.updated"constant

      The event type, must be session.updated.

      • SESSION_UPDATED("session.updated")

Realtime Truncation

  • class RealtimeTruncation: A class that can be one of several variants.union

    When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

    Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

    Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

    Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

    • RealtimeTruncationStrategy

      • AUTO("auto")

      • DISABLED("disabled")

    • class RealtimeTruncationRetentionRatio:

      Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

      • double retentionRatio

        Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

      • JsonValue; type "retention_ratio"constant

        Use retention ratio truncation.

        • RETENTION_RATIO("retention_ratio")
      • Optional<TokenLimits> tokenLimits

        Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

        • Optional<Long> postInstructions

          Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

Realtime Truncation Retention Ratio

  • class RealtimeTruncationRetentionRatio:

    Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

    • double retentionRatio

      Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

    • JsonValue; type "retention_ratio"constant

      Use retention ratio truncation.

      • RETENTION_RATIO("retention_ratio")
    • Optional<TokenLimits> tokenLimits

      Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

      • Optional<Long> postInstructions

        Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

Response Audio Delta Event

  • class ResponseAudioDeltaEvent:

    Returned when the model-generated audio is updated.

    • long contentIndex

      The index of the content part in the item's content array.

    • String delta

      Base64-encoded audio data delta.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • JsonValue; type "response.output_audio.delta"constant

      The event type, must be response.output_audio.delta.

      • RESPONSE_OUTPUT_AUDIO_DELTA("response.output_audio.delta")

Response Audio Done Event

  • class ResponseAudioDoneEvent:

    Returned when the model-generated audio is done. Also emitted when a Response is interrupted, incomplete, or cancelled.

    • long contentIndex

      The index of the content part in the item's content array.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • JsonValue; type "response.output_audio.done"constant

      The event type, must be response.output_audio.done.

      • RESPONSE_OUTPUT_AUDIO_DONE("response.output_audio.done")

Response Audio Transcript Delta Event

  • class ResponseAudioTranscriptDeltaEvent:

    Returned when the model-generated transcription of audio output is updated.

    • long contentIndex

      The index of the content part in the item's content array.

    • String delta

      The transcript delta.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • JsonValue; type "response.output_audio_transcript.delta"constant

      The event type, must be response.output_audio_transcript.delta.

      • RESPONSE_OUTPUT_AUDIO_TRANSCRIPT_DELTA("response.output_audio_transcript.delta")

Response Audio Transcript Done Event

  • class ResponseAudioTranscriptDoneEvent:

    Returned when the model-generated transcription of audio output is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.

    • long contentIndex

      The index of the content part in the item's content array.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • String transcript

      The final transcript of the audio.

    • JsonValue; type "response.output_audio_transcript.done"constant

      The event type, must be response.output_audio_transcript.done.

      • RESPONSE_OUTPUT_AUDIO_TRANSCRIPT_DONE("response.output_audio_transcript.done")

Response Cancel Event

  • class ResponseCancelEvent:

    Send this event to cancel an in-progress response. The server will respond with a response.done event with a status of response.status=cancelled. If there is no response to cancel, the server will respond with an error. It's safe to call response.cancel even if no response is in progress, an error will be returned the session will remain unaffected.

    • JsonValue; type "response.cancel"constant

      The event type, must be response.cancel.

      • RESPONSE_CANCEL("response.cancel")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

    • Optional<String> responseId

      A specific response ID to cancel - if not provided, will cancel an in-progress response in the default conversation.

Response Content Part Added Event

  • class ResponseContentPartAddedEvent:

    Returned when a new content part is added to an assistant message item during response generation.

    • long contentIndex

      The index of the content part in the item's content array.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item to which the content part was added.

    • long outputIndex

      The index of the output item in the response.

    • Part part

      The content part that was added.

      • Optional<String> audio

        Base64-encoded audio data (if type is "audio").

      • Optional<String> text

        The text content (if type is "text").

      • Optional<String> transcript

        The transcript of the audio (if type is "audio").

      • Optional<Type> type

        The content type ("text", "audio").

        • TEXT("text")

        • AUDIO("audio")

    • String responseId

      The ID of the response.

    • JsonValue; type "response.content_part.added"constant

      The event type, must be response.content_part.added.

      • RESPONSE_CONTENT_PART_ADDED("response.content_part.added")

Response Content Part Done Event

  • class ResponseContentPartDoneEvent:

    Returned when a content part is done streaming in an assistant message item. Also emitted when a Response is interrupted, incomplete, or cancelled.

    • long contentIndex

      The index of the content part in the item's content array.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item.

    • long outputIndex

      The index of the output item in the response.

    • Part part

      The content part that is done.

      • Optional<String> audio

        Base64-encoded audio data (if type is "audio").

      • Optional<String> text

        The text content (if type is "text").

      • Optional<String> transcript

        The transcript of the audio (if type is "audio").

      • Optional<Type> type

        The content type ("text", "audio").

        • TEXT("text")

        • AUDIO("audio")

    • String responseId

      The ID of the response.

    • JsonValue; type "response.content_part.done"constant

      The event type, must be response.content_part.done.

      • RESPONSE_CONTENT_PART_DONE("response.content_part.done")

Response Create Event

  • class ResponseCreateEvent:

    This event instructs the server to create a Response, which means triggering model inference. When in Server VAD mode, the server will create Responses automatically.

    A Response will include at least one Item, and may have two, in which case the second will be a function call. These Items will be appended to the conversation history by default.

    The server will respond with a response.created event, events for Items and content created, and finally a response.done event to indicate the Response is complete.

    The response.create event includes inference configuration like instructions and tools. If these are set, they will override the Session's configuration for this Response only.

    Responses can be created out-of-band of the default Conversation, meaning that they can have arbitrary input, and it's possible to disable writing the output to the Conversation. Only one Response can write to the default Conversation at a time, but otherwise multiple Responses can be created in parallel. The metadata field is a good way to disambiguate multiple simultaneous Responses.

    Clients can set conversation to none to create a Response that does not write to the default Conversation. Arbitrary input can be provided with the input field, which is an array accepting raw Items and references to existing Items.

    • JsonValue; type "response.create"constant

      The event type, must be response.create.

      • RESPONSE_CREATE("response.create")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

    • Optional<RealtimeResponseCreateParams> response

      Create a new Realtime response with these parameters

      • Optional<RealtimeResponseCreateAudioOutput> audio

        Configuration for audio input and output.

        • Optional<Output> output

          • Optional<RealtimeAudioFormats> format

            The format of the output audio.

            • AudioPcm

              • Optional<Rate> rate

                The sample rate of the audio. Always 24000.

                • _24000(24000)
              • Optional<Type> type

                The audio format. Always audio/pcm.

                • AUDIO_PCM("audio/pcm")
            • AudioPcmu

              • Optional<Type> type

                The audio format. Always audio/pcmu.

                • AUDIO_PCMU("audio/pcmu")
            • AudioPcma

              • Optional<Type> type

                The audio format. Always audio/pcma.

                • AUDIO_PCMA("audio/pcma")
          • Optional<Voice> voice

            The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

            • String

            • enum UnionMember1:

              • ALLOY("alloy")

              • ASH("ash")

              • BALLAD("ballad")

              • CORAL("coral")

              • ECHO("echo")

              • SAGE("sage")

              • SHIMMER("shimmer")

              • VERSE("verse")

              • MARIN("marin")

              • CEDAR("cedar")

            • class Id:

              Custom voice reference.

              • String id

                The custom voice ID, e.g. voice_1234.

      • Optional<Conversation> conversation

        Controls which conversation the response is added to. Currently supports auto and none, with auto as the default value. The auto value means that the contents of the response will be added to the default conversation. Set this to none to create an out-of-band response which will not add items to default conversation.

        • AUTO("auto")

        • NONE("none")

      • Optional<List<ConversationItem>> input

        Input items to include in the prompt for the model. Using this field creates a new context for this Response instead of using the default conversation. An empty array [] will clear the context for this Response. Note that this can include references to items that previously appeared in the session using their id.

        • class RealtimeConversationItemSystemMessage:

          A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

          • List<Content> content

            The content of the message.

            • Optional<String> text

              The text content.

            • Optional<Type> type

              The content type. Always input_text for system messages.

              • INPUT_TEXT("input_text")
          • JsonValue; role "system"constant

            The role of the message sender. Always system.

            • SYSTEM("system")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemUserMessage:

          A user message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<Detail> detail

              The detail level of the image (for input_image). auto will default to high.

              • AUTO("auto")

              • LOW("low")

              • HIGH("high")

            • Optional<String> imageUrl

              Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

            • Optional<String> text

              The text content (for input_text).

            • Optional<String> transcript

              Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

            • Optional<Type> type

              The content type (input_text, input_audio, or input_image).

              • INPUT_TEXT("input_text")

              • INPUT_AUDIO("input_audio")

              • INPUT_IMAGE("input_image")

          • JsonValue; role "user"constant

            The role of the message sender. Always user.

            • USER("user")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemAssistantMessage:

          An assistant message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<String> text

              The text content.

            • Optional<String> transcript

              The transcript of the audio content, this will always be present if the output type is audio.

            • Optional<Type> type

              The content type, output_text or output_audio depending on the session output_modalities configuration.

              • OUTPUT_TEXT("output_text")

              • OUTPUT_AUDIO("output_audio")

          • JsonValue; role "assistant"constant

            The role of the message sender. Always assistant.

            • ASSISTANT("assistant")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCall:

          A function call item in a Realtime conversation.

          • String arguments

            The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

          • String name

            The name of the function being called.

          • JsonValue; type "function_call"constant

            The type of the item. Always function_call.

            • FUNCTION_CALL("function_call")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<String> callId

            The ID of the function call.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCallOutput:

          A function call output item in a Realtime conversation.

          • String callId

            The ID of the function call this output is for.

          • String output

            The output of the function call, this is free text and can contain any information or simply be empty.

          • JsonValue; type "function_call_output"constant

            The type of the item. Always function_call_output.

            • FUNCTION_CALL_OUTPUT("function_call_output")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeMcpApprovalResponse:

          A Realtime item responding to an MCP approval request.

          • String id

            The unique ID of the approval response.

          • String approvalRequestId

            The ID of the approval request being answered.

          • boolean approve

            Whether the request was approved.

          • JsonValue; type "mcp_approval_response"constant

            The type of the item. Always mcp_approval_response.

            • MCP_APPROVAL_RESPONSE("mcp_approval_response")
          • Optional<String> reason

            Optional reason for the decision.

        • class RealtimeMcpListTools:

          A Realtime item listing tools available on an MCP server.

          • String serverLabel

            The label of the MCP server.

          • List<Tool> tools

            The tools available on the server.

            • JsonValue inputSchema

              The JSON schema describing the tool's input.

            • String name

              The name of the tool.

            • Optional<JsonValue> annotations

              Additional annotations about the tool.

            • Optional<String> description

              The description of the tool.

          • JsonValue; type "mcp_list_tools"constant

            The type of the item. Always mcp_list_tools.

            • MCP_LIST_TOOLS("mcp_list_tools")
          • Optional<String> id

            The unique ID of the list.

        • class RealtimeMcpToolCall:

          A Realtime item representing an invocation of a tool on an MCP server.

          • String id

            The unique ID of the tool call.

          • String arguments

            A JSON string of the arguments passed to the tool.

          • String name

            The name of the tool that was run.

          • String serverLabel

            The label of the MCP server running the tool.

          • JsonValue; type "mcp_call"constant

            The type of the item. Always mcp_call.

            • MCP_CALL("mcp_call")
          • Optional<String> approvalRequestId

            The ID of an associated approval request, if any.

          • Optional<Error> error

            The error from the tool call, if any.

            • class RealtimeMcpProtocolError:

              • long code

              • String message

              • JsonValue; type "protocol_error"constant

                • PROTOCOL_ERROR("protocol_error")
            • class RealtimeMcpToolExecutionError:

              • String message

              • JsonValue; type "tool_execution_error"constant

                • TOOL_EXECUTION_ERROR("tool_execution_error")
            • class RealtimeMcphttpError:

              • long code

              • String message

              • JsonValue; type "http_error"constant

                • HTTP_ERROR("http_error")
          • Optional<String> output

            The output from the tool call.

        • class RealtimeMcpApprovalRequest:

          A Realtime item requesting human approval of a tool invocation.

          • String id

            The unique ID of the approval request.

          • String arguments

            A JSON string of arguments for the tool.

          • String name

            The name of the tool to run.

          • String serverLabel

            The label of the MCP server making the request.

          • JsonValue; type "mcp_approval_request"constant

            The type of the item. Always mcp_approval_request.

            • MCP_APPROVAL_REQUEST("mcp_approval_request")
      • Optional<String> instructions

        The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior. Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

      • Optional<MaxOutputTokens> maxOutputTokens

        Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

        • long

        • JsonValue;

          • INF("inf")
      • Optional<Metadata> metadata

        Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

        Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

      • Optional<List<OutputModality>> outputModalities

        The set of modalities the model used to respond, currently the only possible values are [\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the output to mode text will disable audio output from the model.

        • TEXT("text")

        • AUDIO("audio")

      • Optional<Boolean> parallelToolCalls

        Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

      • Optional<ResponsePrompt> prompt

        Reference to a prompt template and its variables. Learn more.

        • String id

          The unique identifier of the prompt template to use.

        • Optional<Variables> variables

          Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

          • String

          • class ResponseInputText:

            A text input to the model.

            • String text

              The text input to the model.

            • JsonValue; type "input_text"constant

              The type of the input item. Always input_text.

              • INPUT_TEXT("input_text")
          • class ResponseInputImage:

            An image input to the model. Learn about image inputs.

            • Detail detail

              The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

              • LOW("low")

              • HIGH("high")

              • AUTO("auto")

              • ORIGINAL("original")

            • JsonValue; type "input_image"constant

              The type of the input item. Always input_image.

              • INPUT_IMAGE("input_image")
            • Optional<String> fileId

              The ID of the file to be sent to the model.

            • Optional<String> imageUrl

              The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

          • class ResponseInputFile:

            A file input to the model.

            • JsonValue; type "input_file"constant

              The type of the input item. Always input_file.

              • INPUT_FILE("input_file")
            • Optional<Detail> detail

              The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

              • LOW("low")

              • HIGH("high")

            • Optional<String> fileData

              The content of the file to be sent to the model.

            • Optional<String> fileId

              The ID of the file to be sent to the model.

            • Optional<String> fileUrl

              The URL of the file to be sent to the model.

            • Optional<String> filename

              The name of the file to be sent to the model.

        • Optional<String> version

          Optional version of the prompt template.

      • Optional<RealtimeReasoning> reasoning

        Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

        • Optional<RealtimeReasoningEffort> effort

          Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

          • MINIMAL("minimal")

          • LOW("low")

          • MEDIUM("medium")

          • HIGH("high")

          • XHIGH("xhigh")

      • Optional<ToolChoice> toolChoice

        How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

        • enum ToolChoiceOptions:

          Controls which (if any) tool is called by the model.

          none means the model will not call any tool and instead generates a message.

          auto means the model can pick between generating a message or calling one or more tools.

          required means the model must call one or more tools.

          • NONE("none")

          • AUTO("auto")

          • REQUIRED("required")

        • class ToolChoiceFunction:

          Use this option to force the model to call a specific function.

          • String name

            The name of the function to call.

          • JsonValue; type "function"constant

            For function calling, the type is always function.

            • FUNCTION("function")
        • class ToolChoiceMcp:

          Use this option to force the model to call a specific tool on a remote MCP server.

          • String serverLabel

            The label of the MCP server to use.

          • JsonValue; type "mcp"constant

            For MCP tools, the type is always mcp.

            • MCP("mcp")
          • Optional<String> name

            The name of the tool to call on the server.

      • Optional<List<Tool>> tools

        Tools available to the model.

        • class RealtimeFunctionTool:

          • Optional<String> description

            The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

          • Optional<String> name

            The name of the function.

          • Optional<JsonValue> parameters

            Parameters of the function in JSON Schema.

          • Optional<Type> type

            The type of the tool, i.e. function.

            • FUNCTION("function")
        • class RealtimeResponseCreateMcpTool:

          Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

          • String serverLabel

            A label for this MCP server, used to identify it in tool calls.

          • JsonValue; type "mcp"constant

            The type of the MCP tool. Always mcp.

            • MCP("mcp")
          • Optional<AllowedTools> allowedTools

            List of allowed tool names or a filter object.

            • List<String>

            • class McpToolFilter:

              A filter object to specify which tools are allowed.

              • Optional<Boolean> readOnly

                Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

              • Optional<List<String>> toolNames

                List of allowed tool names.

          • Optional<String> authorization

            An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

          • Optional<ConnectorId> connectorId

            Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

            Currently supported connector_id values are:

            • Dropbox: connector_dropbox

            • Gmail: connector_gmail

            • Google Calendar: connector_googlecalendar

            • Google Drive: connector_googledrive

            • Microsoft Teams: connector_microsoftteams

            • Outlook Calendar: connector_outlookcalendar

            • Outlook Email: connector_outlookemail

            • SharePoint: connector_sharepoint

            • CONNECTOR_DROPBOX("connector_dropbox")

            • CONNECTOR_GMAIL("connector_gmail")

            • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

            • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

            • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

            • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

            • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

            • CONNECTOR_SHAREPOINT("connector_sharepoint")

          • Optional<Boolean> deferLoading

            Whether this MCP tool is deferred and discovered via tool search.

          • Optional<Headers> headers

            Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

          • Optional<RequireApproval> requireApproval

            Specify which of the MCP server's tools require approval.

            • class McpToolApprovalFilter:

              Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

              • Optional<Always> always

                A filter object to specify which tools are allowed.

                • Optional<Boolean> readOnly

                  Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                • Optional<List<String>> toolNames

                  List of allowed tool names.

              • Optional<Never> never

                A filter object to specify which tools are allowed.

                • Optional<Boolean> readOnly

                  Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                • Optional<List<String>> toolNames

                  List of allowed tool names.

            • enum McpToolApprovalSetting:

              Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

              • ALWAYS("always")

              • NEVER("never")

          • Optional<String> serverDescription

            Optional description of the MCP server, used to provide more context.

          • Optional<String> serverUrl

            The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

          • Optional<String> tunnelId

            The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

Response Created Event

  • class ResponseCreatedEvent:

    Returned when a new Response is created. The first event of response creation, where the response is in an initial state of in_progress.

    • String eventId

      The unique ID of the server event.

    • RealtimeResponse response

      The response resource.

      • Optional<String> id

        The unique ID of the response, will look like resp_1234.

      • Optional<Audio> audio

        Configuration for audio output.

        • Optional<Output> output

          • Optional<RealtimeAudioFormats> format

            The format of the output audio.

            • AudioPcm

              • Optional<Rate> rate

                The sample rate of the audio. Always 24000.

                • _24000(24000)
              • Optional<Type> type

                The audio format. Always audio/pcm.

                • AUDIO_PCM("audio/pcm")
            • AudioPcmu

              • Optional<Type> type

                The audio format. Always audio/pcmu.

                • AUDIO_PCMU("audio/pcmu")
            • AudioPcma

              • Optional<Type> type

                The audio format. Always audio/pcma.

                • AUDIO_PCMA("audio/pcma")
          • Optional<Voice> voice

            The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. We recommend marin and cedar for best quality.

            • ALLOY("alloy")

            • ASH("ash")

            • BALLAD("ballad")

            • CORAL("coral")

            • ECHO("echo")

            • SAGE("sage")

            • SHIMMER("shimmer")

            • VERSE("verse")

            • MARIN("marin")

            • CEDAR("cedar")

      • Optional<String> conversationId

        Which conversation the response is added to, determined by the conversation field in the response.create event. If auto, the response will be added to the default conversation and the value of conversation_id will be an id like conv_1234. If none, the response will not be added to any conversation and the value of conversation_id will be null. If responses are being triggered automatically by VAD the response will be added to the default conversation

      • Optional<MaxOutputTokens> maxOutputTokens

        Maximum number of output tokens for a single assistant response, inclusive of tool calls, that was used in this response.

        • long

        • JsonValue;

          • INF("inf")
      • Optional<Metadata> metadata

        Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

        Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

      • Optional<Object> object_

        The object type, must be realtime.response.

        • REALTIME_RESPONSE("realtime.response")
      • Optional<List<ConversationItem>> output

        The list of output items generated by the response.

        • class RealtimeConversationItemSystemMessage:

          A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

          • List<Content> content

            The content of the message.

            • Optional<String> text

              The text content.

            • Optional<Type> type

              The content type. Always input_text for system messages.

              • INPUT_TEXT("input_text")
          • JsonValue; role "system"constant

            The role of the message sender. Always system.

            • SYSTEM("system")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemUserMessage:

          A user message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<Detail> detail

              The detail level of the image (for input_image). auto will default to high.

              • AUTO("auto")

              • LOW("low")

              • HIGH("high")

            • Optional<String> imageUrl

              Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

            • Optional<String> text

              The text content (for input_text).

            • Optional<String> transcript

              Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

            • Optional<Type> type

              The content type (input_text, input_audio, or input_image).

              • INPUT_TEXT("input_text")

              • INPUT_AUDIO("input_audio")

              • INPUT_IMAGE("input_image")

          • JsonValue; role "user"constant

            The role of the message sender. Always user.

            • USER("user")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemAssistantMessage:

          An assistant message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<String> text

              The text content.

            • Optional<String> transcript

              The transcript of the audio content, this will always be present if the output type is audio.

            • Optional<Type> type

              The content type, output_text or output_audio depending on the session output_modalities configuration.

              • OUTPUT_TEXT("output_text")

              • OUTPUT_AUDIO("output_audio")

          • JsonValue; role "assistant"constant

            The role of the message sender. Always assistant.

            • ASSISTANT("assistant")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCall:

          A function call item in a Realtime conversation.

          • String arguments

            The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

          • String name

            The name of the function being called.

          • JsonValue; type "function_call"constant

            The type of the item. Always function_call.

            • FUNCTION_CALL("function_call")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<String> callId

            The ID of the function call.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCallOutput:

          A function call output item in a Realtime conversation.

          • String callId

            The ID of the function call this output is for.

          • String output

            The output of the function call, this is free text and can contain any information or simply be empty.

          • JsonValue; type "function_call_output"constant

            The type of the item. Always function_call_output.

            • FUNCTION_CALL_OUTPUT("function_call_output")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeMcpApprovalResponse:

          A Realtime item responding to an MCP approval request.

          • String id

            The unique ID of the approval response.

          • String approvalRequestId

            The ID of the approval request being answered.

          • boolean approve

            Whether the request was approved.

          • JsonValue; type "mcp_approval_response"constant

            The type of the item. Always mcp_approval_response.

            • MCP_APPROVAL_RESPONSE("mcp_approval_response")
          • Optional<String> reason

            Optional reason for the decision.

        • class RealtimeMcpListTools:

          A Realtime item listing tools available on an MCP server.

          • String serverLabel

            The label of the MCP server.

          • List<Tool> tools

            The tools available on the server.

            • JsonValue inputSchema

              The JSON schema describing the tool's input.

            • String name

              The name of the tool.

            • Optional<JsonValue> annotations

              Additional annotations about the tool.

            • Optional<String> description

              The description of the tool.

          • JsonValue; type "mcp_list_tools"constant

            The type of the item. Always mcp_list_tools.

            • MCP_LIST_TOOLS("mcp_list_tools")
          • Optional<String> id

            The unique ID of the list.

        • class RealtimeMcpToolCall:

          A Realtime item representing an invocation of a tool on an MCP server.

          • String id

            The unique ID of the tool call.

          • String arguments

            A JSON string of the arguments passed to the tool.

          • String name

            The name of the tool that was run.

          • String serverLabel

            The label of the MCP server running the tool.

          • JsonValue; type "mcp_call"constant

            The type of the item. Always mcp_call.

            • MCP_CALL("mcp_call")
          • Optional<String> approvalRequestId

            The ID of an associated approval request, if any.

          • Optional<Error> error

            The error from the tool call, if any.

            • class RealtimeMcpProtocolError:

              • long code

              • String message

              • JsonValue; type "protocol_error"constant

                • PROTOCOL_ERROR("protocol_error")
            • class RealtimeMcpToolExecutionError:

              • String message

              • JsonValue; type "tool_execution_error"constant

                • TOOL_EXECUTION_ERROR("tool_execution_error")
            • class RealtimeMcphttpError:

              • long code

              • String message

              • JsonValue; type "http_error"constant

                • HTTP_ERROR("http_error")
          • Optional<String> output

            The output from the tool call.

        • class RealtimeMcpApprovalRequest:

          A Realtime item requesting human approval of a tool invocation.

          • String id

            The unique ID of the approval request.

          • String arguments

            A JSON string of arguments for the tool.

          • String name

            The name of the tool to run.

          • String serverLabel

            The label of the MCP server making the request.

          • JsonValue; type "mcp_approval_request"constant

            The type of the item. Always mcp_approval_request.

            • MCP_APPROVAL_REQUEST("mcp_approval_request")
      • Optional<List<OutputModality>> outputModalities

        The set of modalities the model used to respond, currently the only possible values are [\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the output to mode text will disable audio output from the model.

        • TEXT("text")

        • AUDIO("audio")

      • Optional<Status> status

        The final status of the response (completed, cancelled, failed, or incomplete, in_progress).

        • COMPLETED("completed")

        • CANCELLED("cancelled")

        • FAILED("failed")

        • INCOMPLETE("incomplete")

        • IN_PROGRESS("in_progress")

      • Optional<RealtimeResponseStatus> statusDetails

        Additional details about the status.

        • Optional<Error> error

          A description of the error that caused the response to fail, populated when the status is failed.

          • Optional<String> code

            Error code, if any.

          • Optional<String> type

            The type of error.

        • Optional<Reason> reason

          The reason the Response did not complete. For a cancelled Response, one of turn_detected (the server VAD detected a new start of speech) or client_cancelled (the client sent a cancel event). For an incomplete Response, one of max_output_tokens or content_filter (the server-side safety filter activated and cut off the response).

          • TURN_DETECTED("turn_detected")

          • CLIENT_CANCELLED("client_cancelled")

          • MAX_OUTPUT_TOKENS("max_output_tokens")

          • CONTENT_FILTER("content_filter")

        • Optional<Type> type

          The type of error that caused the response to fail, corresponding with the status field (completed, cancelled, incomplete, failed).

          • COMPLETED("completed")

          • CANCELLED("cancelled")

          • INCOMPLETE("incomplete")

          • FAILED("failed")

      • Optional<RealtimeResponseUsage> usage

        Usage statistics for the Response, this will correspond to billing. A Realtime API session will maintain a conversation context and append new Items to the Conversation, thus output from previous turns (text and audio tokens) will become the input for later turns.

        • Optional<RealtimeResponseUsageInputTokenDetails> inputTokenDetails

          Details about the input tokens used in the Response. Cached tokens are tokens from previous turns in the conversation that are included as context for the current response. Cached tokens here are counted as a subset of input tokens, meaning input tokens will include cached and uncached tokens.

          • Optional<Long> audioTokens

            The number of audio tokens used as input for the Response.

          • Optional<Long> cachedTokens

            The number of cached tokens used as input for the Response.

          • Optional<CachedTokensDetails> cachedTokensDetails

            Details about the cached tokens used as input for the Response.

            • Optional<Long> audioTokens

              The number of cached audio tokens used as input for the Response.

            • Optional<Long> imageTokens

              The number of cached image tokens used as input for the Response.

            • Optional<Long> textTokens

              The number of cached text tokens used as input for the Response.

          • Optional<Long> imageTokens

            The number of image tokens used as input for the Response.

          • Optional<Long> textTokens

            The number of text tokens used as input for the Response.

        • Optional<Long> inputTokens

          The number of input tokens used in the Response, including text and audio tokens.

        • Optional<RealtimeResponseUsageOutputTokenDetails> outputTokenDetails

          Details about the output tokens used in the Response.

          • Optional<Long> audioTokens

            The number of audio tokens used in the Response.

          • Optional<Long> textTokens

            The number of text tokens used in the Response.

        • Optional<Long> outputTokens

          The number of output tokens sent in the Response, including text and audio tokens.

        • Optional<Long> totalTokens

          The total number of tokens in the Response including input and output text and audio tokens.

    • JsonValue; type "response.created"constant

      The event type, must be response.created.

      • RESPONSE_CREATED("response.created")

Response Done Event

  • class ResponseDoneEvent:

    Returned when a Response is done streaming. Always emitted, no matter the final state. The Response object included in the response.done event will include all output Items in the Response but will omit the raw audio data.

    Clients should check the status field of the Response to determine if it was successful (completed) or if there was another outcome: cancelled, failed, or incomplete.

    A response will contain all output items that were generated during the response, excluding any audio content.

    • String eventId

      The unique ID of the server event.

    • RealtimeResponse response

      The response resource.

      • Optional<String> id

        The unique ID of the response, will look like resp_1234.

      • Optional<Audio> audio

        Configuration for audio output.

        • Optional<Output> output

          • Optional<RealtimeAudioFormats> format

            The format of the output audio.

            • AudioPcm

              • Optional<Rate> rate

                The sample rate of the audio. Always 24000.

                • _24000(24000)
              • Optional<Type> type

                The audio format. Always audio/pcm.

                • AUDIO_PCM("audio/pcm")
            • AudioPcmu

              • Optional<Type> type

                The audio format. Always audio/pcmu.

                • AUDIO_PCMU("audio/pcmu")
            • AudioPcma

              • Optional<Type> type

                The audio format. Always audio/pcma.

                • AUDIO_PCMA("audio/pcma")
          • Optional<Voice> voice

            The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. We recommend marin and cedar for best quality.

            • ALLOY("alloy")

            • ASH("ash")

            • BALLAD("ballad")

            • CORAL("coral")

            • ECHO("echo")

            • SAGE("sage")

            • SHIMMER("shimmer")

            • VERSE("verse")

            • MARIN("marin")

            • CEDAR("cedar")

      • Optional<String> conversationId

        Which conversation the response is added to, determined by the conversation field in the response.create event. If auto, the response will be added to the default conversation and the value of conversation_id will be an id like conv_1234. If none, the response will not be added to any conversation and the value of conversation_id will be null. If responses are being triggered automatically by VAD the response will be added to the default conversation

      • Optional<MaxOutputTokens> maxOutputTokens

        Maximum number of output tokens for a single assistant response, inclusive of tool calls, that was used in this response.

        • long

        • JsonValue;

          • INF("inf")
      • Optional<Metadata> metadata

        Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format, and querying for objects via API or the dashboard.

        Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.

      • Optional<Object> object_

        The object type, must be realtime.response.

        • REALTIME_RESPONSE("realtime.response")
      • Optional<List<ConversationItem>> output

        The list of output items generated by the response.

        • class RealtimeConversationItemSystemMessage:

          A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

          • List<Content> content

            The content of the message.

            • Optional<String> text

              The text content.

            • Optional<Type> type

              The content type. Always input_text for system messages.

              • INPUT_TEXT("input_text")
          • JsonValue; role "system"constant

            The role of the message sender. Always system.

            • SYSTEM("system")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemUserMessage:

          A user message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<Detail> detail

              The detail level of the image (for input_image). auto will default to high.

              • AUTO("auto")

              • LOW("low")

              • HIGH("high")

            • Optional<String> imageUrl

              Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

            • Optional<String> text

              The text content (for input_text).

            • Optional<String> transcript

              Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

            • Optional<Type> type

              The content type (input_text, input_audio, or input_image).

              • INPUT_TEXT("input_text")

              • INPUT_AUDIO("input_audio")

              • INPUT_IMAGE("input_image")

          • JsonValue; role "user"constant

            The role of the message sender. Always user.

            • USER("user")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemAssistantMessage:

          An assistant message item in a Realtime conversation.

          • List<Content> content

            The content of the message.

            • Optional<String> audio

              Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

            • Optional<String> text

              The text content.

            • Optional<String> transcript

              The transcript of the audio content, this will always be present if the output type is audio.

            • Optional<Type> type

              The content type, output_text or output_audio depending on the session output_modalities configuration.

              • OUTPUT_TEXT("output_text")

              • OUTPUT_AUDIO("output_audio")

          • JsonValue; role "assistant"constant

            The role of the message sender. Always assistant.

            • ASSISTANT("assistant")
          • JsonValue; type "message"constant

            The type of the item. Always message.

            • MESSAGE("message")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCall:

          A function call item in a Realtime conversation.

          • String arguments

            The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

          • String name

            The name of the function being called.

          • JsonValue; type "function_call"constant

            The type of the item. Always function_call.

            • FUNCTION_CALL("function_call")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<String> callId

            The ID of the function call.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeConversationItemFunctionCallOutput:

          A function call output item in a Realtime conversation.

          • String callId

            The ID of the function call this output is for.

          • String output

            The output of the function call, this is free text and can contain any information or simply be empty.

          • JsonValue; type "function_call_output"constant

            The type of the item. Always function_call_output.

            • FUNCTION_CALL_OUTPUT("function_call_output")
          • Optional<String> id

            The unique ID of the item. This may be provided by the client or generated by the server.

          • Optional<Object> object_

            Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

            • REALTIME_ITEM("realtime.item")
          • Optional<Status> status

            The status of the item. Has no effect on the conversation.

            • COMPLETED("completed")

            • INCOMPLETE("incomplete")

            • IN_PROGRESS("in_progress")

        • class RealtimeMcpApprovalResponse:

          A Realtime item responding to an MCP approval request.

          • String id

            The unique ID of the approval response.

          • String approvalRequestId

            The ID of the approval request being answered.

          • boolean approve

            Whether the request was approved.

          • JsonValue; type "mcp_approval_response"constant

            The type of the item. Always mcp_approval_response.

            • MCP_APPROVAL_RESPONSE("mcp_approval_response")
          • Optional<String> reason

            Optional reason for the decision.

        • class RealtimeMcpListTools:

          A Realtime item listing tools available on an MCP server.

          • String serverLabel

            The label of the MCP server.

          • List<Tool> tools

            The tools available on the server.

            • JsonValue inputSchema

              The JSON schema describing the tool's input.

            • String name

              The name of the tool.

            • Optional<JsonValue> annotations

              Additional annotations about the tool.

            • Optional<String> description

              The description of the tool.

          • JsonValue; type "mcp_list_tools"constant

            The type of the item. Always mcp_list_tools.

            • MCP_LIST_TOOLS("mcp_list_tools")
          • Optional<String> id

            The unique ID of the list.

        • class RealtimeMcpToolCall:

          A Realtime item representing an invocation of a tool on an MCP server.

          • String id

            The unique ID of the tool call.

          • String arguments

            A JSON string of the arguments passed to the tool.

          • String name

            The name of the tool that was run.

          • String serverLabel

            The label of the MCP server running the tool.

          • JsonValue; type "mcp_call"constant

            The type of the item. Always mcp_call.

            • MCP_CALL("mcp_call")
          • Optional<String> approvalRequestId

            The ID of an associated approval request, if any.

          • Optional<Error> error

            The error from the tool call, if any.

            • class RealtimeMcpProtocolError:

              • long code

              • String message

              • JsonValue; type "protocol_error"constant

                • PROTOCOL_ERROR("protocol_error")
            • class RealtimeMcpToolExecutionError:

              • String message

              • JsonValue; type "tool_execution_error"constant

                • TOOL_EXECUTION_ERROR("tool_execution_error")
            • class RealtimeMcphttpError:

              • long code

              • String message

              • JsonValue; type "http_error"constant

                • HTTP_ERROR("http_error")
          • Optional<String> output

            The output from the tool call.

        • class RealtimeMcpApprovalRequest:

          A Realtime item requesting human approval of a tool invocation.

          • String id

            The unique ID of the approval request.

          • String arguments

            A JSON string of arguments for the tool.

          • String name

            The name of the tool to run.

          • String serverLabel

            The label of the MCP server making the request.

          • JsonValue; type "mcp_approval_request"constant

            The type of the item. Always mcp_approval_request.

            • MCP_APPROVAL_REQUEST("mcp_approval_request")
      • Optional<List<OutputModality>> outputModalities

        The set of modalities the model used to respond, currently the only possible values are [\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the output to mode text will disable audio output from the model.

        • TEXT("text")

        • AUDIO("audio")

      • Optional<Status> status

        The final status of the response (completed, cancelled, failed, or incomplete, in_progress).

        • COMPLETED("completed")

        • CANCELLED("cancelled")

        • FAILED("failed")

        • INCOMPLETE("incomplete")

        • IN_PROGRESS("in_progress")

      • Optional<RealtimeResponseStatus> statusDetails

        Additional details about the status.

        • Optional<Error> error

          A description of the error that caused the response to fail, populated when the status is failed.

          • Optional<String> code

            Error code, if any.

          • Optional<String> type

            The type of error.

        • Optional<Reason> reason

          The reason the Response did not complete. For a cancelled Response, one of turn_detected (the server VAD detected a new start of speech) or client_cancelled (the client sent a cancel event). For an incomplete Response, one of max_output_tokens or content_filter (the server-side safety filter activated and cut off the response).

          • TURN_DETECTED("turn_detected")

          • CLIENT_CANCELLED("client_cancelled")

          • MAX_OUTPUT_TOKENS("max_output_tokens")

          • CONTENT_FILTER("content_filter")

        • Optional<Type> type

          The type of error that caused the response to fail, corresponding with the status field (completed, cancelled, incomplete, failed).

          • COMPLETED("completed")

          • CANCELLED("cancelled")

          • INCOMPLETE("incomplete")

          • FAILED("failed")

      • Optional<RealtimeResponseUsage> usage

        Usage statistics for the Response, this will correspond to billing. A Realtime API session will maintain a conversation context and append new Items to the Conversation, thus output from previous turns (text and audio tokens) will become the input for later turns.

        • Optional<RealtimeResponseUsageInputTokenDetails> inputTokenDetails

          Details about the input tokens used in the Response. Cached tokens are tokens from previous turns in the conversation that are included as context for the current response. Cached tokens here are counted as a subset of input tokens, meaning input tokens will include cached and uncached tokens.

          • Optional<Long> audioTokens

            The number of audio tokens used as input for the Response.

          • Optional<Long> cachedTokens

            The number of cached tokens used as input for the Response.

          • Optional<CachedTokensDetails> cachedTokensDetails

            Details about the cached tokens used as input for the Response.

            • Optional<Long> audioTokens

              The number of cached audio tokens used as input for the Response.

            • Optional<Long> imageTokens

              The number of cached image tokens used as input for the Response.

            • Optional<Long> textTokens

              The number of cached text tokens used as input for the Response.

          • Optional<Long> imageTokens

            The number of image tokens used as input for the Response.

          • Optional<Long> textTokens

            The number of text tokens used as input for the Response.

        • Optional<Long> inputTokens

          The number of input tokens used in the Response, including text and audio tokens.

        • Optional<RealtimeResponseUsageOutputTokenDetails> outputTokenDetails

          Details about the output tokens used in the Response.

          • Optional<Long> audioTokens

            The number of audio tokens used in the Response.

          • Optional<Long> textTokens

            The number of text tokens used in the Response.

        • Optional<Long> outputTokens

          The number of output tokens sent in the Response, including text and audio tokens.

        • Optional<Long> totalTokens

          The total number of tokens in the Response including input and output text and audio tokens.

    • JsonValue; type "response.done"constant

      The event type, must be response.done.

      • RESPONSE_DONE("response.done")

Response Function Call Arguments Delta Event

  • class ResponseFunctionCallArgumentsDeltaEvent:

    Returned when the model-generated function call arguments are updated.

    • String callId

      The ID of the function call.

    • String delta

      The arguments delta as a JSON string.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the function call item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • JsonValue; type "response.function_call_arguments.delta"constant

      The event type, must be response.function_call_arguments.delta.

      • RESPONSE_FUNCTION_CALL_ARGUMENTS_DELTA("response.function_call_arguments.delta")

Response Function Call Arguments Done Event

  • class ResponseFunctionCallArgumentsDoneEvent:

    Returned when the model-generated function call arguments are done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.

    • String arguments

      The final arguments as a JSON string.

    • String callId

      The ID of the function call.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the function call item.

    • String name

      The name of the function that was called.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • JsonValue; type "response.function_call_arguments.done"constant

      The event type, must be response.function_call_arguments.done.

      • RESPONSE_FUNCTION_CALL_ARGUMENTS_DONE("response.function_call_arguments.done")

Response Mcp Call Arguments Delta

  • class ResponseMcpCallArgumentsDelta:

    Returned when MCP tool call arguments are updated during response generation.

    • String delta

      The JSON-encoded arguments delta.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the MCP tool call item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • JsonValue; type "response.mcp_call_arguments.delta"constant

      The event type, must be response.mcp_call_arguments.delta.

      • RESPONSE_MCP_CALL_ARGUMENTS_DELTA("response.mcp_call_arguments.delta")
    • Optional<String> obfuscation

      If present, indicates the delta text was obfuscated.

Response Mcp Call Arguments Done

  • class ResponseMcpCallArgumentsDone:

    Returned when MCP tool call arguments are finalized during response generation.

    • String arguments

      The final JSON-encoded arguments string.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the MCP tool call item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • JsonValue; type "response.mcp_call_arguments.done"constant

      The event type, must be response.mcp_call_arguments.done.

      • RESPONSE_MCP_CALL_ARGUMENTS_DONE("response.mcp_call_arguments.done")

Response Mcp Call Completed

  • class ResponseMcpCallCompleted:

    Returned when an MCP tool call has completed successfully.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the MCP tool call item.

    • long outputIndex

      The index of the output item in the response.

    • JsonValue; type "response.mcp_call.completed"constant

      The event type, must be response.mcp_call.completed.

      • RESPONSE_MCP_CALL_COMPLETED("response.mcp_call.completed")

Response Mcp Call Failed

  • class ResponseMcpCallFailed:

    Returned when an MCP tool call has failed.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the MCP tool call item.

    • long outputIndex

      The index of the output item in the response.

    • JsonValue; type "response.mcp_call.failed"constant

      The event type, must be response.mcp_call.failed.

      • RESPONSE_MCP_CALL_FAILED("response.mcp_call.failed")

Response Mcp Call In Progress

  • class ResponseMcpCallInProgress:

    Returned when an MCP tool call has started and is in progress.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the MCP tool call item.

    • long outputIndex

      The index of the output item in the response.

    • JsonValue; type "response.mcp_call.in_progress"constant

      The event type, must be response.mcp_call.in_progress.

      • RESPONSE_MCP_CALL_IN_PROGRESS("response.mcp_call.in_progress")

Response Output Item Added Event

  • class ResponseOutputItemAddedEvent:

    Returned when a new Item is created during Response generation.

    • String eventId

      The unique ID of the server event.

    • ConversationItem item

      A single item within a Realtime conversation.

      • class RealtimeConversationItemSystemMessage:

        A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

        • List<Content> content

          The content of the message.

          • Optional<String> text

            The text content.

          • Optional<Type> type

            The content type. Always input_text for system messages.

            • INPUT_TEXT("input_text")
        • JsonValue; role "system"constant

          The role of the message sender. Always system.

          • SYSTEM("system")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemUserMessage:

        A user message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<Detail> detail

            The detail level of the image (for input_image). auto will default to high.

            • AUTO("auto")

            • LOW("low")

            • HIGH("high")

          • Optional<String> imageUrl

            Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

          • Optional<String> text

            The text content (for input_text).

          • Optional<String> transcript

            Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

          • Optional<Type> type

            The content type (input_text, input_audio, or input_image).

            • INPUT_TEXT("input_text")

            • INPUT_AUDIO("input_audio")

            • INPUT_IMAGE("input_image")

        • JsonValue; role "user"constant

          The role of the message sender. Always user.

          • USER("user")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemAssistantMessage:

        An assistant message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<String> text

            The text content.

          • Optional<String> transcript

            The transcript of the audio content, this will always be present if the output type is audio.

          • Optional<Type> type

            The content type, output_text or output_audio depending on the session output_modalities configuration.

            • OUTPUT_TEXT("output_text")

            • OUTPUT_AUDIO("output_audio")

        • JsonValue; role "assistant"constant

          The role of the message sender. Always assistant.

          • ASSISTANT("assistant")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCall:

        A function call item in a Realtime conversation.

        • String arguments

          The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

        • String name

          The name of the function being called.

        • JsonValue; type "function_call"constant

          The type of the item. Always function_call.

          • FUNCTION_CALL("function_call")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<String> callId

          The ID of the function call.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCallOutput:

        A function call output item in a Realtime conversation.

        • String callId

          The ID of the function call this output is for.

        • String output

          The output of the function call, this is free text and can contain any information or simply be empty.

        • JsonValue; type "function_call_output"constant

          The type of the item. Always function_call_output.

          • FUNCTION_CALL_OUTPUT("function_call_output")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeMcpApprovalResponse:

        A Realtime item responding to an MCP approval request.

        • String id

          The unique ID of the approval response.

        • String approvalRequestId

          The ID of the approval request being answered.

        • boolean approve

          Whether the request was approved.

        • JsonValue; type "mcp_approval_response"constant

          The type of the item. Always mcp_approval_response.

          • MCP_APPROVAL_RESPONSE("mcp_approval_response")
        • Optional<String> reason

          Optional reason for the decision.

      • class RealtimeMcpListTools:

        A Realtime item listing tools available on an MCP server.

        • String serverLabel

          The label of the MCP server.

        • List<Tool> tools

          The tools available on the server.

          • JsonValue inputSchema

            The JSON schema describing the tool's input.

          • String name

            The name of the tool.

          • Optional<JsonValue> annotations

            Additional annotations about the tool.

          • Optional<String> description

            The description of the tool.

        • JsonValue; type "mcp_list_tools"constant

          The type of the item. Always mcp_list_tools.

          • MCP_LIST_TOOLS("mcp_list_tools")
        • Optional<String> id

          The unique ID of the list.

      • class RealtimeMcpToolCall:

        A Realtime item representing an invocation of a tool on an MCP server.

        • String id

          The unique ID of the tool call.

        • String arguments

          A JSON string of the arguments passed to the tool.

        • String name

          The name of the tool that was run.

        • String serverLabel

          The label of the MCP server running the tool.

        • JsonValue; type "mcp_call"constant

          The type of the item. Always mcp_call.

          • MCP_CALL("mcp_call")
        • Optional<String> approvalRequestId

          The ID of an associated approval request, if any.

        • Optional<Error> error

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError:

            • long code

            • String message

            • JsonValue; type "protocol_error"constant

              • PROTOCOL_ERROR("protocol_error")
          • class RealtimeMcpToolExecutionError:

            • String message

            • JsonValue; type "tool_execution_error"constant

              • TOOL_EXECUTION_ERROR("tool_execution_error")
          • class RealtimeMcphttpError:

            • long code

            • String message

            • JsonValue; type "http_error"constant

              • HTTP_ERROR("http_error")
        • Optional<String> output

          The output from the tool call.

      • class RealtimeMcpApprovalRequest:

        A Realtime item requesting human approval of a tool invocation.

        • String id

          The unique ID of the approval request.

        • String arguments

          A JSON string of arguments for the tool.

        • String name

          The name of the tool to run.

        • String serverLabel

          The label of the MCP server making the request.

        • JsonValue; type "mcp_approval_request"constant

          The type of the item. Always mcp_approval_request.

          • MCP_APPROVAL_REQUEST("mcp_approval_request")
    • long outputIndex

      The index of the output item in the Response.

    • String responseId

      The ID of the Response to which the item belongs.

    • JsonValue; type "response.output_item.added"constant

      The event type, must be response.output_item.added.

      • RESPONSE_OUTPUT_ITEM_ADDED("response.output_item.added")

Response Output Item Done Event

  • class ResponseOutputItemDoneEvent:

    Returned when an Item is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.

    • String eventId

      The unique ID of the server event.

    • ConversationItem item

      A single item within a Realtime conversation.

      • class RealtimeConversationItemSystemMessage:

        A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.

        • List<Content> content

          The content of the message.

          • Optional<String> text

            The text content.

          • Optional<Type> type

            The content type. Always input_text for system messages.

            • INPUT_TEXT("input_text")
        • JsonValue; role "system"constant

          The role of the message sender. Always system.

          • SYSTEM("system")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemUserMessage:

        A user message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<Detail> detail

            The detail level of the image (for input_image). auto will default to high.

            • AUTO("auto")

            • LOW("low")

            • HIGH("high")

          • Optional<String> imageUrl

            Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.

          • Optional<String> text

            The text content (for input_text).

          • Optional<String> transcript

            Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.

          • Optional<Type> type

            The content type (input_text, input_audio, or input_image).

            • INPUT_TEXT("input_text")

            • INPUT_AUDIO("input_audio")

            • INPUT_IMAGE("input_image")

        • JsonValue; role "user"constant

          The role of the message sender. Always user.

          • USER("user")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemAssistantMessage:

        An assistant message item in a Realtime conversation.

        • List<Content> content

          The content of the message.

          • Optional<String> audio

            Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.

          • Optional<String> text

            The text content.

          • Optional<String> transcript

            The transcript of the audio content, this will always be present if the output type is audio.

          • Optional<Type> type

            The content type, output_text or output_audio depending on the session output_modalities configuration.

            • OUTPUT_TEXT("output_text")

            • OUTPUT_AUDIO("output_audio")

        • JsonValue; role "assistant"constant

          The role of the message sender. Always assistant.

          • ASSISTANT("assistant")
        • JsonValue; type "message"constant

          The type of the item. Always message.

          • MESSAGE("message")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCall:

        A function call item in a Realtime conversation.

        • String arguments

          The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.

        • String name

          The name of the function being called.

        • JsonValue; type "function_call"constant

          The type of the item. Always function_call.

          • FUNCTION_CALL("function_call")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<String> callId

          The ID of the function call.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeConversationItemFunctionCallOutput:

        A function call output item in a Realtime conversation.

        • String callId

          The ID of the function call this output is for.

        • String output

          The output of the function call, this is free text and can contain any information or simply be empty.

        • JsonValue; type "function_call_output"constant

          The type of the item. Always function_call_output.

          • FUNCTION_CALL_OUTPUT("function_call_output")
        • Optional<String> id

          The unique ID of the item. This may be provided by the client or generated by the server.

        • Optional<Object> object_

          Identifier for the API object being returned - always realtime.item. Optional when creating a new item.

          • REALTIME_ITEM("realtime.item")
        • Optional<Status> status

          The status of the item. Has no effect on the conversation.

          • COMPLETED("completed")

          • INCOMPLETE("incomplete")

          • IN_PROGRESS("in_progress")

      • class RealtimeMcpApprovalResponse:

        A Realtime item responding to an MCP approval request.

        • String id

          The unique ID of the approval response.

        • String approvalRequestId

          The ID of the approval request being answered.

        • boolean approve

          Whether the request was approved.

        • JsonValue; type "mcp_approval_response"constant

          The type of the item. Always mcp_approval_response.

          • MCP_APPROVAL_RESPONSE("mcp_approval_response")
        • Optional<String> reason

          Optional reason for the decision.

      • class RealtimeMcpListTools:

        A Realtime item listing tools available on an MCP server.

        • String serverLabel

          The label of the MCP server.

        • List<Tool> tools

          The tools available on the server.

          • JsonValue inputSchema

            The JSON schema describing the tool's input.

          • String name

            The name of the tool.

          • Optional<JsonValue> annotations

            Additional annotations about the tool.

          • Optional<String> description

            The description of the tool.

        • JsonValue; type "mcp_list_tools"constant

          The type of the item. Always mcp_list_tools.

          • MCP_LIST_TOOLS("mcp_list_tools")
        • Optional<String> id

          The unique ID of the list.

      • class RealtimeMcpToolCall:

        A Realtime item representing an invocation of a tool on an MCP server.

        • String id

          The unique ID of the tool call.

        • String arguments

          A JSON string of the arguments passed to the tool.

        • String name

          The name of the tool that was run.

        • String serverLabel

          The label of the MCP server running the tool.

        • JsonValue; type "mcp_call"constant

          The type of the item. Always mcp_call.

          • MCP_CALL("mcp_call")
        • Optional<String> approvalRequestId

          The ID of an associated approval request, if any.

        • Optional<Error> error

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError:

            • long code

            • String message

            • JsonValue; type "protocol_error"constant

              • PROTOCOL_ERROR("protocol_error")
          • class RealtimeMcpToolExecutionError:

            • String message

            • JsonValue; type "tool_execution_error"constant

              • TOOL_EXECUTION_ERROR("tool_execution_error")
          • class RealtimeMcphttpError:

            • long code

            • String message

            • JsonValue; type "http_error"constant

              • HTTP_ERROR("http_error")
        • Optional<String> output

          The output from the tool call.

      • class RealtimeMcpApprovalRequest:

        A Realtime item requesting human approval of a tool invocation.

        • String id

          The unique ID of the approval request.

        • String arguments

          A JSON string of arguments for the tool.

        • String name

          The name of the tool to run.

        • String serverLabel

          The label of the MCP server making the request.

        • JsonValue; type "mcp_approval_request"constant

          The type of the item. Always mcp_approval_request.

          • MCP_APPROVAL_REQUEST("mcp_approval_request")
    • long outputIndex

      The index of the output item in the Response.

    • String responseId

      The ID of the Response to which the item belongs.

    • JsonValue; type "response.output_item.done"constant

      The event type, must be response.output_item.done.

      • RESPONSE_OUTPUT_ITEM_DONE("response.output_item.done")

Response Text Delta Event

  • class ResponseTextDeltaEvent:

    Returned when the text value of an "output_text" content part is updated.

    • long contentIndex

      The index of the content part in the item's content array.

    • String delta

      The text delta.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • JsonValue; type "response.output_text.delta"constant

      The event type, must be response.output_text.delta.

      • RESPONSE_OUTPUT_TEXT_DELTA("response.output_text.delta")

Response Text Done Event

  • class ResponseTextDoneEvent:

    Returned when the text value of an "output_text" content part is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.

    • long contentIndex

      The index of the content part in the item's content array.

    • String eventId

      The unique ID of the server event.

    • String itemId

      The ID of the item.

    • long outputIndex

      The index of the output item in the response.

    • String responseId

      The ID of the response.

    • String text

      The final text content.

    • JsonValue; type "response.output_text.done"constant

      The event type, must be response.output_text.done.

      • RESPONSE_OUTPUT_TEXT_DONE("response.output_text.done")

Session Created Event

  • class SessionCreatedEvent:

    Returned when a Session is created. Emitted automatically when a new connection is established as the first server event. This event will contain the default Session configuration.

    • String eventId

      The unique ID of the server event.

    • Session session

      The session configuration.

      • class RealtimeSessionCreateRequest:

        Realtime session object configuration.

        • JsonValue; type "realtime"constant

          The type of session to create. Always realtime for the Realtime API.

          • REALTIME("realtime")
        • Optional<RealtimeAudioConfig> audio

          Configuration for input and output audio.

          • Optional<RealtimeAudioConfigInput> input

            • Optional<RealtimeAudioFormats> format

              The format of the input audio.

              • AudioPcm

                • Optional<Rate> rate

                  The sample rate of the audio. Always 24000.

                  • _24000(24000)
                • Optional<Type> type

                  The audio format. Always audio/pcm.

                  • AUDIO_PCM("audio/pcm")
              • AudioPcmu

                • Optional<Type> type

                  The audio format. Always audio/pcmu.

                  • AUDIO_PCMU("audio/pcmu")
              • AudioPcma

                • Optional<Type> type

                  The audio format. Always audio/pcma.

                  • AUDIO_PCMA("audio/pcma")
            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                • NEAR_FIELD("near_field")

                • FAR_FIELD("far_field")

            • Optional<AudioTranscription> transcription

              Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

              • Optional<Delay> delay

                Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

                • MINIMAL("minimal")

                • LOW("low")

                • MEDIUM("medium")

                • HIGH("high")

                • XHIGH("xhigh")

              • Optional<String> language

                The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

              • Optional<Model> model

                The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

                • WHISPER_1("whisper-1")

                • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

                • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

                • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

                • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

                • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

              • Optional<String> prompt

                An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

            • Optional<RealtimeAudioInputTurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • ServerVad

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • SemanticVad

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

          • Optional<RealtimeAudioConfigOutput> output

            • Optional<RealtimeAudioFormats> format

              The format of the output audio.

            • Optional<Double> speed

              The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

              This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

            • Optional<Voice> voice

              The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

              • String

              • enum UnionMember1:

                • ALLOY("alloy")

                • ASH("ash")

                • BALLAD("ballad")

                • CORAL("coral")

                • ECHO("echo")

                • SAGE("sage")

                • SHIMMER("shimmer")

                • VERSE("verse")

                • MARIN("marin")

                • CEDAR("cedar")

              • class Id:

                Custom voice reference.

                • String id

                  The custom voice ID, e.g. voice_1234.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
        • Optional<String> instructions

          The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

          Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

        • Optional<MaxOutputTokens> maxOutputTokens

          Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

          • long

          • JsonValue;

            • INF("inf")
        • Optional<Model> model

          The Realtime model used for this session.

          • GPT_REALTIME("gpt-realtime")

          • GPT_REALTIME_1_5("gpt-realtime-1.5")

          • GPT_REALTIME_2("gpt-realtime-2")

          • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

          • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

          • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

          • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

          • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

          • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

          • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

          • GPT_REALTIME_MINI("gpt-realtime-mini")

          • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

          • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

          • GPT_AUDIO_1_5("gpt-audio-1.5")

          • GPT_AUDIO_MINI("gpt-audio-mini")

          • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

          • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

        • Optional<List<OutputModality>> outputModalities

          The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

          • TEXT("text")

          • AUDIO("audio")

        • Optional<Boolean> parallelToolCalls

          Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

        • Optional<ResponsePrompt> prompt

          Reference to a prompt template and its variables. Learn more.

          • String id

            The unique identifier of the prompt template to use.

          • Optional<Variables> variables

            Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

            • String

            • class ResponseInputText:

              A text input to the model.

              • String text

                The text input to the model.

              • JsonValue; type "input_text"constant

                The type of the input item. Always input_text.

                • INPUT_TEXT("input_text")
            • class ResponseInputImage:

              An image input to the model. Learn about image inputs.

              • Detail detail

                The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

                • LOW("low")

                • HIGH("high")

                • AUTO("auto")

                • ORIGINAL("original")

              • JsonValue; type "input_image"constant

                The type of the input item. Always input_image.

                • INPUT_IMAGE("input_image")
              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> imageUrl

                The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

            • class ResponseInputFile:

              A file input to the model.

              • JsonValue; type "input_file"constant

                The type of the input item. Always input_file.

                • INPUT_FILE("input_file")
              • Optional<Detail> detail

                The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

                • LOW("low")

                • HIGH("high")

              • Optional<String> fileData

                The content of the file to be sent to the model.

              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> fileUrl

                The URL of the file to be sent to the model.

              • Optional<String> filename

                The name of the file to be sent to the model.

          • Optional<String> version

            Optional version of the prompt template.

        • Optional<RealtimeReasoning> reasoning

          Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

          • Optional<RealtimeReasoningEffort> effort

            Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

        • Optional<RealtimeToolChoiceConfig> toolChoice

          How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

          • enum ToolChoiceOptions:

            Controls which (if any) tool is called by the model.

            none means the model will not call any tool and instead generates a message.

            auto means the model can pick between generating a message or calling one or more tools.

            required means the model must call one or more tools.

            • NONE("none")

            • AUTO("auto")

            • REQUIRED("required")

          • class ToolChoiceFunction:

            Use this option to force the model to call a specific function.

            • String name

              The name of the function to call.

            • JsonValue; type "function"constant

              For function calling, the type is always function.

              • FUNCTION("function")
          • class ToolChoiceMcp:

            Use this option to force the model to call a specific tool on a remote MCP server.

            • String serverLabel

              The label of the MCP server to use.

            • JsonValue; type "mcp"constant

              For MCP tools, the type is always mcp.

              • MCP("mcp")
            • Optional<String> name

              The name of the tool to call on the server.

        • Optional<List<RealtimeToolsConfigUnion>> tools

          Tools available to the model.

          • class RealtimeFunctionTool:

            • Optional<String> description

              The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

            • Optional<String> name

              The name of the function.

            • Optional<JsonValue> parameters

              Parameters of the function in JSON Schema.

            • Optional<Type> type

              The type of the tool, i.e. function.

              • FUNCTION("function")
          • Mcp

            • String serverLabel

              A label for this MCP server, used to identify it in tool calls.

            • JsonValue; type "mcp"constant

              The type of the MCP tool. Always mcp.

              • MCP("mcp")
            • Optional<AllowedTools> allowedTools

              List of allowed tool names or a filter object.

              • List<String>

              • class McpToolFilter:

                A filter object to specify which tools are allowed.

                • Optional<Boolean> readOnly

                  Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                • Optional<List<String>> toolNames

                  List of allowed tool names.

            • Optional<String> authorization

              An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

            • Optional<ConnectorId> connectorId

              Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

              Currently supported connector_id values are:

              • Dropbox: connector_dropbox

              • Gmail: connector_gmail

              • Google Calendar: connector_googlecalendar

              • Google Drive: connector_googledrive

              • Microsoft Teams: connector_microsoftteams

              • Outlook Calendar: connector_outlookcalendar

              • Outlook Email: connector_outlookemail

              • SharePoint: connector_sharepoint

              • CONNECTOR_DROPBOX("connector_dropbox")

              • CONNECTOR_GMAIL("connector_gmail")

              • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

              • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

              • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

              • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

              • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

              • CONNECTOR_SHAREPOINT("connector_sharepoint")

            • Optional<Boolean> deferLoading

              Whether this MCP tool is deferred and discovered via tool search.

            • Optional<Headers> headers

              Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

            • Optional<RequireApproval> requireApproval

              Specify which of the MCP server's tools require approval.

              • class McpToolApprovalFilter:

                Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

                • Optional<Always> always

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

                • Optional<Never> never

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

              • enum McpToolApprovalSetting:

                Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

                • ALWAYS("always")

                • NEVER("never")

            • Optional<String> serverDescription

              Optional description of the MCP server, used to provide more context.

            • Optional<String> serverUrl

              The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

            • Optional<String> tunnelId

              The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

        • Optional<RealtimeTracingConfig> tracing

          Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

          auto will create a trace for the session with default values for the workflow name, group id, and metadata.

          • JsonValue;

            • AUTO("auto")
          • TracingConfiguration

            • Optional<String> groupId

              The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

            • Optional<JsonValue> metadata

              The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

            • Optional<String> workflowName

              The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

        • Optional<RealtimeTruncation> truncation

          When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

          Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

          Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

          Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

          • RealtimeTruncationStrategy

            • AUTO("auto")

            • DISABLED("disabled")

          • class RealtimeTruncationRetentionRatio:

            Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

            • double retentionRatio

              Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

            • JsonValue; type "retention_ratio"constant

              Use retention ratio truncation.

              • RETENTION_RATIO("retention_ratio")
            • Optional<TokenLimits> tokenLimits

              Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

              • Optional<Long> postInstructions

                Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

      • class RealtimeTranscriptionSessionCreateRequest:

        Realtime transcription session object configuration.

        • JsonValue; type "transcription"constant

          The type of session to create. Always transcription for transcription sessions.

          • TRANSCRIPTION("transcription")
        • Optional<RealtimeTranscriptionSessionAudio> audio

          Configuration for input and output audio.

          • Optional<RealtimeTranscriptionSessionAudioInput> input

            • Optional<RealtimeAudioFormats> format

              The PCM audio format. Only a 24kHz sample rate is supported.

            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • Optional<AudioTranscription> transcription

              Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

            • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • ServerVad

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • SemanticVad

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
    • JsonValue; type "session.created"constant

      The event type, must be session.created.

      • SESSION_CREATED("session.created")

Session Update Event

  • class SessionUpdateEvent:

    Send this event to update the session’s configuration. The client may send this event at any time to update any field except for voice and model. voice can be updated only if there have been no other audio outputs yet.

    When the server receives a session.update, it will respond with a session.updated event showing the full, effective configuration. Only the fields that are present in the session.update are updated. To clear a field like instructions, pass an empty string. To clear a field like tools, pass an empty array. To clear a field like turn_detection, pass null.

    • Session session

      Update the Realtime session. Choose either a realtime session or a transcription session.

      • class RealtimeSessionCreateRequest:

        Realtime session object configuration.

        • JsonValue; type "realtime"constant

          The type of session to create. Always realtime for the Realtime API.

          • REALTIME("realtime")
        • Optional<RealtimeAudioConfig> audio

          Configuration for input and output audio.

          • Optional<RealtimeAudioConfigInput> input

            • Optional<RealtimeAudioFormats> format

              The format of the input audio.

              • AudioPcm

                • Optional<Rate> rate

                  The sample rate of the audio. Always 24000.

                  • _24000(24000)
                • Optional<Type> type

                  The audio format. Always audio/pcm.

                  • AUDIO_PCM("audio/pcm")
              • AudioPcmu

                • Optional<Type> type

                  The audio format. Always audio/pcmu.

                  • AUDIO_PCMU("audio/pcmu")
              • AudioPcma

                • Optional<Type> type

                  The audio format. Always audio/pcma.

                  • AUDIO_PCMA("audio/pcma")
            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                • NEAR_FIELD("near_field")

                • FAR_FIELD("far_field")

            • Optional<AudioTranscription> transcription

              Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

              • Optional<Delay> delay

                Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

                • MINIMAL("minimal")

                • LOW("low")

                • MEDIUM("medium")

                • HIGH("high")

                • XHIGH("xhigh")

              • Optional<String> language

                The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

              • Optional<Model> model

                The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

                • WHISPER_1("whisper-1")

                • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

                • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

                • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

                • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

                • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

              • Optional<String> prompt

                An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

            • Optional<RealtimeAudioInputTurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • ServerVad

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • SemanticVad

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

          • Optional<RealtimeAudioConfigOutput> output

            • Optional<RealtimeAudioFormats> format

              The format of the output audio.

            • Optional<Double> speed

              The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

              This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

            • Optional<Voice> voice

              The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

              • String

              • enum UnionMember1:

                • ALLOY("alloy")

                • ASH("ash")

                • BALLAD("ballad")

                • CORAL("coral")

                • ECHO("echo")

                • SAGE("sage")

                • SHIMMER("shimmer")

                • VERSE("verse")

                • MARIN("marin")

                • CEDAR("cedar")

              • class Id:

                Custom voice reference.

                • String id

                  The custom voice ID, e.g. voice_1234.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
        • Optional<String> instructions

          The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

          Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

        • Optional<MaxOutputTokens> maxOutputTokens

          Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

          • long

          • JsonValue;

            • INF("inf")
        • Optional<Model> model

          The Realtime model used for this session.

          • GPT_REALTIME("gpt-realtime")

          • GPT_REALTIME_1_5("gpt-realtime-1.5")

          • GPT_REALTIME_2("gpt-realtime-2")

          • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

          • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

          • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

          • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

          • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

          • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

          • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

          • GPT_REALTIME_MINI("gpt-realtime-mini")

          • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

          • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

          • GPT_AUDIO_1_5("gpt-audio-1.5")

          • GPT_AUDIO_MINI("gpt-audio-mini")

          • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

          • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

        • Optional<List<OutputModality>> outputModalities

          The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

          • TEXT("text")

          • AUDIO("audio")

        • Optional<Boolean> parallelToolCalls

          Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

        • Optional<ResponsePrompt> prompt

          Reference to a prompt template and its variables. Learn more.

          • String id

            The unique identifier of the prompt template to use.

          • Optional<Variables> variables

            Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

            • String

            • class ResponseInputText:

              A text input to the model.

              • String text

                The text input to the model.

              • JsonValue; type "input_text"constant

                The type of the input item. Always input_text.

                • INPUT_TEXT("input_text")
            • class ResponseInputImage:

              An image input to the model. Learn about image inputs.

              • Detail detail

                The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

                • LOW("low")

                • HIGH("high")

                • AUTO("auto")

                • ORIGINAL("original")

              • JsonValue; type "input_image"constant

                The type of the input item. Always input_image.

                • INPUT_IMAGE("input_image")
              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> imageUrl

                The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

            • class ResponseInputFile:

              A file input to the model.

              • JsonValue; type "input_file"constant

                The type of the input item. Always input_file.

                • INPUT_FILE("input_file")
              • Optional<Detail> detail

                The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

                • LOW("low")

                • HIGH("high")

              • Optional<String> fileData

                The content of the file to be sent to the model.

              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> fileUrl

                The URL of the file to be sent to the model.

              • Optional<String> filename

                The name of the file to be sent to the model.

          • Optional<String> version

            Optional version of the prompt template.

        • Optional<RealtimeReasoning> reasoning

          Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

          • Optional<RealtimeReasoningEffort> effort

            Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

        • Optional<RealtimeToolChoiceConfig> toolChoice

          How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

          • enum ToolChoiceOptions:

            Controls which (if any) tool is called by the model.

            none means the model will not call any tool and instead generates a message.

            auto means the model can pick between generating a message or calling one or more tools.

            required means the model must call one or more tools.

            • NONE("none")

            • AUTO("auto")

            • REQUIRED("required")

          • class ToolChoiceFunction:

            Use this option to force the model to call a specific function.

            • String name

              The name of the function to call.

            • JsonValue; type "function"constant

              For function calling, the type is always function.

              • FUNCTION("function")
          • class ToolChoiceMcp:

            Use this option to force the model to call a specific tool on a remote MCP server.

            • String serverLabel

              The label of the MCP server to use.

            • JsonValue; type "mcp"constant

              For MCP tools, the type is always mcp.

              • MCP("mcp")
            • Optional<String> name

              The name of the tool to call on the server.

        • Optional<List<RealtimeToolsConfigUnion>> tools

          Tools available to the model.

          • class RealtimeFunctionTool:

            • Optional<String> description

              The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

            • Optional<String> name

              The name of the function.

            • Optional<JsonValue> parameters

              Parameters of the function in JSON Schema.

            • Optional<Type> type

              The type of the tool, i.e. function.

              • FUNCTION("function")
          • Mcp

            • String serverLabel

              A label for this MCP server, used to identify it in tool calls.

            • JsonValue; type "mcp"constant

              The type of the MCP tool. Always mcp.

              • MCP("mcp")
            • Optional<AllowedTools> allowedTools

              List of allowed tool names or a filter object.

              • List<String>

              • class McpToolFilter:

                A filter object to specify which tools are allowed.

                • Optional<Boolean> readOnly

                  Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                • Optional<List<String>> toolNames

                  List of allowed tool names.

            • Optional<String> authorization

              An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

            • Optional<ConnectorId> connectorId

              Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

              Currently supported connector_id values are:

              • Dropbox: connector_dropbox

              • Gmail: connector_gmail

              • Google Calendar: connector_googlecalendar

              • Google Drive: connector_googledrive

              • Microsoft Teams: connector_microsoftteams

              • Outlook Calendar: connector_outlookcalendar

              • Outlook Email: connector_outlookemail

              • SharePoint: connector_sharepoint

              • CONNECTOR_DROPBOX("connector_dropbox")

              • CONNECTOR_GMAIL("connector_gmail")

              • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

              • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

              • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

              • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

              • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

              • CONNECTOR_SHAREPOINT("connector_sharepoint")

            • Optional<Boolean> deferLoading

              Whether this MCP tool is deferred and discovered via tool search.

            • Optional<Headers> headers

              Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

            • Optional<RequireApproval> requireApproval

              Specify which of the MCP server's tools require approval.

              • class McpToolApprovalFilter:

                Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

                • Optional<Always> always

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

                • Optional<Never> never

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

              • enum McpToolApprovalSetting:

                Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

                • ALWAYS("always")

                • NEVER("never")

            • Optional<String> serverDescription

              Optional description of the MCP server, used to provide more context.

            • Optional<String> serverUrl

              The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

            • Optional<String> tunnelId

              The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

        • Optional<RealtimeTracingConfig> tracing

          Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

          auto will create a trace for the session with default values for the workflow name, group id, and metadata.

          • JsonValue;

            • AUTO("auto")
          • TracingConfiguration

            • Optional<String> groupId

              The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

            • Optional<JsonValue> metadata

              The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

            • Optional<String> workflowName

              The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

        • Optional<RealtimeTruncation> truncation

          When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

          Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

          Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

          Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

          • RealtimeTruncationStrategy

            • AUTO("auto")

            • DISABLED("disabled")

          • class RealtimeTruncationRetentionRatio:

            Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

            • double retentionRatio

              Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

            • JsonValue; type "retention_ratio"constant

              Use retention ratio truncation.

              • RETENTION_RATIO("retention_ratio")
            • Optional<TokenLimits> tokenLimits

              Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

              • Optional<Long> postInstructions

                Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

      • class RealtimeTranscriptionSessionCreateRequest:

        Realtime transcription session object configuration.

        • JsonValue; type "transcription"constant

          The type of session to create. Always transcription for transcription sessions.

          • TRANSCRIPTION("transcription")
        • Optional<RealtimeTranscriptionSessionAudio> audio

          Configuration for input and output audio.

          • Optional<RealtimeTranscriptionSessionAudioInput> input

            • Optional<RealtimeAudioFormats> format

              The PCM audio format. Only a 24kHz sample rate is supported.

            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • Optional<AudioTranscription> transcription

              Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

            • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • ServerVad

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • SemanticVad

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
    • JsonValue; type "session.update"constant

      The event type, must be session.update.

      • SESSION_UPDATE("session.update")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event. This is an arbitrary string that a client may assign. It will be passed back if there is an error with the event, but the corresponding session.updated event will not include it.

Session Updated Event

  • class SessionUpdatedEvent:

    Returned when a session is updated with a session.update event, unless there is an error.

    • String eventId

      The unique ID of the server event.

    • Session session

      The session configuration.

      • class RealtimeSessionCreateRequest:

        Realtime session object configuration.

        • JsonValue; type "realtime"constant

          The type of session to create. Always realtime for the Realtime API.

          • REALTIME("realtime")
        • Optional<RealtimeAudioConfig> audio

          Configuration for input and output audio.

          • Optional<RealtimeAudioConfigInput> input

            • Optional<RealtimeAudioFormats> format

              The format of the input audio.

              • AudioPcm

                • Optional<Rate> rate

                  The sample rate of the audio. Always 24000.

                  • _24000(24000)
                • Optional<Type> type

                  The audio format. Always audio/pcm.

                  • AUDIO_PCM("audio/pcm")
              • AudioPcmu

                • Optional<Type> type

                  The audio format. Always audio/pcmu.

                  • AUDIO_PCMU("audio/pcmu")
              • AudioPcma

                • Optional<Type> type

                  The audio format. Always audio/pcma.

                  • AUDIO_PCMA("audio/pcma")
            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                • NEAR_FIELD("near_field")

                • FAR_FIELD("far_field")

            • Optional<AudioTranscription> transcription

              Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

              • Optional<Delay> delay

                Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

                • MINIMAL("minimal")

                • LOW("low")

                • MEDIUM("medium")

                • HIGH("high")

                • XHIGH("xhigh")

              • Optional<String> language

                The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

              • Optional<Model> model

                The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

                • WHISPER_1("whisper-1")

                • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

                • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

                • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

                • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

                • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

              • Optional<String> prompt

                An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

            • Optional<RealtimeAudioInputTurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • ServerVad

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • SemanticVad

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

          • Optional<RealtimeAudioConfigOutput> output

            • Optional<RealtimeAudioFormats> format

              The format of the output audio.

            • Optional<Double> speed

              The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

              This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

            • Optional<Voice> voice

              The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

              • String

              • enum UnionMember1:

                • ALLOY("alloy")

                • ASH("ash")

                • BALLAD("ballad")

                • CORAL("coral")

                • ECHO("echo")

                • SAGE("sage")

                • SHIMMER("shimmer")

                • VERSE("verse")

                • MARIN("marin")

                • CEDAR("cedar")

              • class Id:

                Custom voice reference.

                • String id

                  The custom voice ID, e.g. voice_1234.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
        • Optional<String> instructions

          The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

          Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

        • Optional<MaxOutputTokens> maxOutputTokens

          Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

          • long

          • JsonValue;

            • INF("inf")
        • Optional<Model> model

          The Realtime model used for this session.

          • GPT_REALTIME("gpt-realtime")

          • GPT_REALTIME_1_5("gpt-realtime-1.5")

          • GPT_REALTIME_2("gpt-realtime-2")

          • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

          • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

          • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

          • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

          • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

          • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

          • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

          • GPT_REALTIME_MINI("gpt-realtime-mini")

          • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

          • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

          • GPT_AUDIO_1_5("gpt-audio-1.5")

          • GPT_AUDIO_MINI("gpt-audio-mini")

          • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

          • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

        • Optional<List<OutputModality>> outputModalities

          The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

          • TEXT("text")

          • AUDIO("audio")

        • Optional<Boolean> parallelToolCalls

          Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

        • Optional<ResponsePrompt> prompt

          Reference to a prompt template and its variables. Learn more.

          • String id

            The unique identifier of the prompt template to use.

          • Optional<Variables> variables

            Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

            • String

            • class ResponseInputText:

              A text input to the model.

              • String text

                The text input to the model.

              • JsonValue; type "input_text"constant

                The type of the input item. Always input_text.

                • INPUT_TEXT("input_text")
            • class ResponseInputImage:

              An image input to the model. Learn about image inputs.

              • Detail detail

                The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

                • LOW("low")

                • HIGH("high")

                • AUTO("auto")

                • ORIGINAL("original")

              • JsonValue; type "input_image"constant

                The type of the input item. Always input_image.

                • INPUT_IMAGE("input_image")
              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> imageUrl

                The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

            • class ResponseInputFile:

              A file input to the model.

              • JsonValue; type "input_file"constant

                The type of the input item. Always input_file.

                • INPUT_FILE("input_file")
              • Optional<Detail> detail

                The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

                • LOW("low")

                • HIGH("high")

              • Optional<String> fileData

                The content of the file to be sent to the model.

              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> fileUrl

                The URL of the file to be sent to the model.

              • Optional<String> filename

                The name of the file to be sent to the model.

          • Optional<String> version

            Optional version of the prompt template.

        • Optional<RealtimeReasoning> reasoning

          Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

          • Optional<RealtimeReasoningEffort> effort

            Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

        • Optional<RealtimeToolChoiceConfig> toolChoice

          How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

          • enum ToolChoiceOptions:

            Controls which (if any) tool is called by the model.

            none means the model will not call any tool and instead generates a message.

            auto means the model can pick between generating a message or calling one or more tools.

            required means the model must call one or more tools.

            • NONE("none")

            • AUTO("auto")

            • REQUIRED("required")

          • class ToolChoiceFunction:

            Use this option to force the model to call a specific function.

            • String name

              The name of the function to call.

            • JsonValue; type "function"constant

              For function calling, the type is always function.

              • FUNCTION("function")
          • class ToolChoiceMcp:

            Use this option to force the model to call a specific tool on a remote MCP server.

            • String serverLabel

              The label of the MCP server to use.

            • JsonValue; type "mcp"constant

              For MCP tools, the type is always mcp.

              • MCP("mcp")
            • Optional<String> name

              The name of the tool to call on the server.

        • Optional<List<RealtimeToolsConfigUnion>> tools

          Tools available to the model.

          • class RealtimeFunctionTool:

            • Optional<String> description

              The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

            • Optional<String> name

              The name of the function.

            • Optional<JsonValue> parameters

              Parameters of the function in JSON Schema.

            • Optional<Type> type

              The type of the tool, i.e. function.

              • FUNCTION("function")
          • Mcp

            • String serverLabel

              A label for this MCP server, used to identify it in tool calls.

            • JsonValue; type "mcp"constant

              The type of the MCP tool. Always mcp.

              • MCP("mcp")
            • Optional<AllowedTools> allowedTools

              List of allowed tool names or a filter object.

              • List<String>

              • class McpToolFilter:

                A filter object to specify which tools are allowed.

                • Optional<Boolean> readOnly

                  Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                • Optional<List<String>> toolNames

                  List of allowed tool names.

            • Optional<String> authorization

              An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

            • Optional<ConnectorId> connectorId

              Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

              Currently supported connector_id values are:

              • Dropbox: connector_dropbox

              • Gmail: connector_gmail

              • Google Calendar: connector_googlecalendar

              • Google Drive: connector_googledrive

              • Microsoft Teams: connector_microsoftteams

              • Outlook Calendar: connector_outlookcalendar

              • Outlook Email: connector_outlookemail

              • SharePoint: connector_sharepoint

              • CONNECTOR_DROPBOX("connector_dropbox")

              • CONNECTOR_GMAIL("connector_gmail")

              • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

              • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

              • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

              • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

              • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

              • CONNECTOR_SHAREPOINT("connector_sharepoint")

            • Optional<Boolean> deferLoading

              Whether this MCP tool is deferred and discovered via tool search.

            • Optional<Headers> headers

              Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

            • Optional<RequireApproval> requireApproval

              Specify which of the MCP server's tools require approval.

              • class McpToolApprovalFilter:

                Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

                • Optional<Always> always

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

                • Optional<Never> never

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

              • enum McpToolApprovalSetting:

                Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

                • ALWAYS("always")

                • NEVER("never")

            • Optional<String> serverDescription

              Optional description of the MCP server, used to provide more context.

            • Optional<String> serverUrl

              The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

            • Optional<String> tunnelId

              The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

        • Optional<RealtimeTracingConfig> tracing

          Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

          auto will create a trace for the session with default values for the workflow name, group id, and metadata.

          • JsonValue;

            • AUTO("auto")
          • TracingConfiguration

            • Optional<String> groupId

              The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

            • Optional<JsonValue> metadata

              The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

            • Optional<String> workflowName

              The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

        • Optional<RealtimeTruncation> truncation

          When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

          Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

          Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

          Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

          • RealtimeTruncationStrategy

            • AUTO("auto")

            • DISABLED("disabled")

          • class RealtimeTruncationRetentionRatio:

            Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

            • double retentionRatio

              Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

            • JsonValue; type "retention_ratio"constant

              Use retention ratio truncation.

              • RETENTION_RATIO("retention_ratio")
            • Optional<TokenLimits> tokenLimits

              Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

              • Optional<Long> postInstructions

                Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

      • class RealtimeTranscriptionSessionCreateRequest:

        Realtime transcription session object configuration.

        • JsonValue; type "transcription"constant

          The type of session to create. Always transcription for transcription sessions.

          • TRANSCRIPTION("transcription")
        • Optional<RealtimeTranscriptionSessionAudio> audio

          Configuration for input and output audio.

          • Optional<RealtimeTranscriptionSessionAudioInput> input

            • Optional<RealtimeAudioFormats> format

              The PCM audio format. Only a 24kHz sample rate is supported.

            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • Optional<AudioTranscription> transcription

              Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

            • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • ServerVad

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • SemanticVad

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
    • JsonValue; type "session.updated"constant

      The event type, must be session.updated.

      • SESSION_UPDATED("session.updated")

Transcription Session Update

  • class TranscriptionSessionUpdate:

    Send this event to update a transcription session.

    • Session session

      Realtime transcription session object configuration.

      • Optional<List<Include>> include

        The set of items to include in the transcription. Current available items are: item.input_audio_transcription.logprobs

        • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
      • Optional<InputAudioFormat> inputAudioFormat

        The format of input audio. Options are pcm16, g711_ulaw, or g711_alaw. For pcm16, input audio must be 16-bit PCM at a 24kHz sample rate, single channel (mono), and little-endian byte order.

        • PCM16("pcm16")

        • G711_ULAW("g711_ulaw")

        • G711_ALAW("g711_alaw")

      • Optional<InputAudioNoiseReduction> inputAudioNoiseReduction

        Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

        • Optional<NoiseReductionType> type

          Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

          • NEAR_FIELD("near_field")

          • FAR_FIELD("far_field")

      • Optional<AudioTranscription> inputAudioTranscription

        Configuration for input audio transcription. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

        • Optional<Delay> delay

          Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

          • MINIMAL("minimal")

          • LOW("low")

          • MEDIUM("medium")

          • HIGH("high")

          • XHIGH("xhigh")

        • Optional<String> language

          The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

        • Optional<Model> model

          The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

          • WHISPER_1("whisper-1")

          • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

          • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

          • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

          • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

          • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

        • Optional<String> prompt

          An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

      • Optional<TurnDetection> turnDetection

        Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

        • Optional<Long> prefixPaddingMs

          Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

        • Optional<Long> silenceDurationMs

          Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

        • Optional<Double> threshold

          Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

        • Optional<Type> type

          Type of turn detection. Only server_vad is currently supported for transcription sessions.

          • SERVER_VAD("server_vad")
    • JsonValue; type "transcription_session.update"constant

      The event type, must be transcription_session.update.

      • TRANSCRIPTION_SESSION_UPDATE("transcription_session.update")
    • Optional<String> eventId

      Optional client-generated ID used to identify this event.

Transcription Session Updated Event

  • class TranscriptionSessionUpdatedEvent:

    Returned when a transcription session is updated with a transcription_session.update event, unless there is an error.

    • String eventId

      The unique ID of the server event.

    • Session session

      A new Realtime transcription session configuration.

      When a session is created on the server via REST API, the session object also contains an ephemeral key. Default TTL for keys is 10 minutes. This property is not present when a session is updated via the WebSocket API.

      • ClientSecret clientSecret

        Ephemeral key returned by the API. Only present when the session is created on the server via REST API.

        • long expiresAt

          Timestamp for when the token expires. Currently, all tokens expire after one minute.

        • String value

          Ephemeral key usable in client environments to authenticate connections to the Realtime API. Use this in client-side environments rather than a standard API token, which should only be used server-side.

      • Optional<String> inputAudioFormat

        The format of input audio. Options are pcm16, g711_ulaw, or g711_alaw.

      • Optional<AudioTranscription> inputAudioTranscription

        • Optional<Delay> delay

          Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

          • MINIMAL("minimal")

          • LOW("low")

          • MEDIUM("medium")

          • HIGH("high")

          • XHIGH("xhigh")

        • Optional<String> language

          The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

        • Optional<Model> model

          The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

          • WHISPER_1("whisper-1")

          • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

          • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

          • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

          • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

          • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

        • Optional<String> prompt

          An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

      • Optional<List<Modality>> modalities

        The set of modalities the model can respond with. To disable audio, set this to ["text"].

        • TEXT("text")

        • AUDIO("audio")

      • Optional<TurnDetection> turnDetection

        Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

        • Optional<Long> prefixPaddingMs

          Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

        • Optional<Long> silenceDurationMs

          Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

        • Optional<Double> threshold

          Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

        • Optional<String> type

          Type of turn detection, only server_vad is currently supported.

    • JsonValue; type "transcription_session.updated"constant

      The event type, must be transcription_session.updated.

      • TRANSCRIPTION_SESSION_UPDATED("transcription_session.updated")

Client Secrets

Create client secret

ClientSecretCreateResponse realtime().clientSecrets().create(ClientSecretCreateParamsparams = ClientSecretCreateParams.none(), RequestOptionsrequestOptions = RequestOptions.none())

post /realtime/client_secrets

Create a Realtime client secret with an associated session configuration.

Client secrets are short-lived tokens that can be passed to a client app, such as a web frontend or mobile client, which grants access to the Realtime API without leaking your main API key. You can configure a custom TTL for each client secret.

You can also attach session configuration options to the client secret, which will be applied to any sessions created using that client secret, but these can also be overridden by the client connection.

Learn more about authentication with client secrets over WebRTC.

Returns the created client secret and the effective session object. The client secret is a string that looks like ek_1234.

Parameters

  • ClientSecretCreateParams params

    • Optional<ExpiresAfter> expiresAfter

      Configuration for the client secret expiration. Expiration refers to the time after which a client secret will no longer be valid for creating sessions. The session itself may continue after that time once started. A secret can be used to create multiple sessions until it expires.

      • Optional<Anchor> anchor

        The anchor point for the client secret expiration, meaning that seconds will be added to the created_at time of the client secret to produce an expiration timestamp. Only created_at is currently supported.

        • CREATED_AT("created_at")
      • Optional<Long> seconds

        The number of seconds from the anchor point to the expiration. Select a value between 10 and 7200 (2 hours). This default to 600 seconds (10 minutes) if not specified.

    • Optional<Session> session

      Session configuration to use for the client secret. Choose either a realtime session or a transcription session.

      • class RealtimeSessionCreateRequest:

        Realtime session object configuration.

        • JsonValue; type "realtime"constant

          The type of session to create. Always realtime for the Realtime API.

          • REALTIME("realtime")
        • Optional<RealtimeAudioConfig> audio

          Configuration for input and output audio.

          • Optional<RealtimeAudioConfigInput> input

            • Optional<RealtimeAudioFormats> format

              The format of the input audio.

              • AudioPcm

                • Optional<Rate> rate

                  The sample rate of the audio. Always 24000.

                  • _24000(24000)
                • Optional<Type> type

                  The audio format. Always audio/pcm.

                  • AUDIO_PCM("audio/pcm")
              • AudioPcmu

                • Optional<Type> type

                  The audio format. Always audio/pcmu.

                  • AUDIO_PCMU("audio/pcmu")
              • AudioPcma

                • Optional<Type> type

                  The audio format. Always audio/pcma.

                  • AUDIO_PCMA("audio/pcma")
            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                • NEAR_FIELD("near_field")

                • FAR_FIELD("far_field")

            • Optional<AudioTranscription> transcription

              Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

              • Optional<Delay> delay

                Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

                • MINIMAL("minimal")

                • LOW("low")

                • MEDIUM("medium")

                • HIGH("high")

                • XHIGH("xhigh")

              • Optional<String> language

                The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

              • Optional<Model> model

                The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

                • WHISPER_1("whisper-1")

                • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

                • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

                • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

                • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

                • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

              • Optional<String> prompt

                An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

            • Optional<RealtimeAudioInputTurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • ServerVad

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • SemanticVad

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

          • Optional<RealtimeAudioConfigOutput> output

            • Optional<RealtimeAudioFormats> format

              The format of the output audio.

            • Optional<Double> speed

              The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

              This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

            • Optional<Voice> voice

              The voice the model uses to respond. Supported built-in voices are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. You may also provide a custom voice object with an id, for example { "id": "voice_1234" }. Voice cannot be changed during the session once the model has responded with audio at least once. We recommend marin and cedar for best quality.

              • String

              • enum UnionMember1:

                • ALLOY("alloy")

                • ASH("ash")

                • BALLAD("ballad")

                • CORAL("coral")

                • ECHO("echo")

                • SAGE("sage")

                • SHIMMER("shimmer")

                • VERSE("verse")

                • MARIN("marin")

                • CEDAR("cedar")

              • class Id:

                Custom voice reference.

                • String id

                  The custom voice ID, e.g. voice_1234.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
        • Optional<String> instructions

          The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

          Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

        • Optional<MaxOutputTokens> maxOutputTokens

          Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

          • long

          • JsonValue;

            • INF("inf")
        • Optional<Model> model

          The Realtime model used for this session.

          • GPT_REALTIME("gpt-realtime")

          • GPT_REALTIME_1_5("gpt-realtime-1.5")

          • GPT_REALTIME_2("gpt-realtime-2")

          • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

          • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

          • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

          • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

          • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

          • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

          • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

          • GPT_REALTIME_MINI("gpt-realtime-mini")

          • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

          • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

          • GPT_AUDIO_1_5("gpt-audio-1.5")

          • GPT_AUDIO_MINI("gpt-audio-mini")

          • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

          • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

        • Optional<List<OutputModality>> outputModalities

          The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

          • TEXT("text")

          • AUDIO("audio")

        • Optional<Boolean> parallelToolCalls

          Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as gpt-realtime-2.

        • Optional<ResponsePrompt> prompt

          Reference to a prompt template and its variables. Learn more.

          • String id

            The unique identifier of the prompt template to use.

          • Optional<Variables> variables

            Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

            • String

            • class ResponseInputText:

              A text input to the model.

              • String text

                The text input to the model.

              • JsonValue; type "input_text"constant

                The type of the input item. Always input_text.

                • INPUT_TEXT("input_text")
            • class ResponseInputImage:

              An image input to the model. Learn about image inputs.

              • Detail detail

                The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

                • LOW("low")

                • HIGH("high")

                • AUTO("auto")

                • ORIGINAL("original")

              • JsonValue; type "input_image"constant

                The type of the input item. Always input_image.

                • INPUT_IMAGE("input_image")
              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> imageUrl

                The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

            • class ResponseInputFile:

              A file input to the model.

              • JsonValue; type "input_file"constant

                The type of the input item. Always input_file.

                • INPUT_FILE("input_file")
              • Optional<Detail> detail

                The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

                • LOW("low")

                • HIGH("high")

              • Optional<String> fileData

                The content of the file to be sent to the model.

              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> fileUrl

                The URL of the file to be sent to the model.

              • Optional<String> filename

                The name of the file to be sent to the model.

          • Optional<String> version

            Optional version of the prompt template.

        • Optional<RealtimeReasoning> reasoning

          Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

          • Optional<RealtimeReasoningEffort> effort

            Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

        • Optional<RealtimeToolChoiceConfig> toolChoice

          How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

          • enum ToolChoiceOptions:

            Controls which (if any) tool is called by the model.

            none means the model will not call any tool and instead generates a message.

            auto means the model can pick between generating a message or calling one or more tools.

            required means the model must call one or more tools.

            • NONE("none")

            • AUTO("auto")

            • REQUIRED("required")

          • class ToolChoiceFunction:

            Use this option to force the model to call a specific function.

            • String name

              The name of the function to call.

            • JsonValue; type "function"constant

              For function calling, the type is always function.

              • FUNCTION("function")
          • class ToolChoiceMcp:

            Use this option to force the model to call a specific tool on a remote MCP server.

            • String serverLabel

              The label of the MCP server to use.

            • JsonValue; type "mcp"constant

              For MCP tools, the type is always mcp.

              • MCP("mcp")
            • Optional<String> name

              The name of the tool to call on the server.

        • Optional<List<RealtimeToolsConfigUnion>> tools

          Tools available to the model.

          • class RealtimeFunctionTool:

            • Optional<String> description

              The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

            • Optional<String> name

              The name of the function.

            • Optional<JsonValue> parameters

              Parameters of the function in JSON Schema.

            • Optional<Type> type

              The type of the tool, i.e. function.

              • FUNCTION("function")
          • Mcp

            • String serverLabel

              A label for this MCP server, used to identify it in tool calls.

            • JsonValue; type "mcp"constant

              The type of the MCP tool. Always mcp.

              • MCP("mcp")
            • Optional<AllowedTools> allowedTools

              List of allowed tool names or a filter object.

              • List<String>

              • class McpToolFilter:

                A filter object to specify which tools are allowed.

                • Optional<Boolean> readOnly

                  Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                • Optional<List<String>> toolNames

                  List of allowed tool names.

            • Optional<String> authorization

              An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

            • Optional<ConnectorId> connectorId

              Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

              Currently supported connector_id values are:

              • Dropbox: connector_dropbox

              • Gmail: connector_gmail

              • Google Calendar: connector_googlecalendar

              • Google Drive: connector_googledrive

              • Microsoft Teams: connector_microsoftteams

              • Outlook Calendar: connector_outlookcalendar

              • Outlook Email: connector_outlookemail

              • SharePoint: connector_sharepoint

              • CONNECTOR_DROPBOX("connector_dropbox")

              • CONNECTOR_GMAIL("connector_gmail")

              • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

              • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

              • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

              • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

              • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

              • CONNECTOR_SHAREPOINT("connector_sharepoint")

            • Optional<Boolean> deferLoading

              Whether this MCP tool is deferred and discovered via tool search.

            • Optional<Headers> headers

              Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

            • Optional<RequireApproval> requireApproval

              Specify which of the MCP server's tools require approval.

              • class McpToolApprovalFilter:

                Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

                • Optional<Always> always

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

                • Optional<Never> never

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

              • enum McpToolApprovalSetting:

                Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

                • ALWAYS("always")

                • NEVER("never")

            • Optional<String> serverDescription

              Optional description of the MCP server, used to provide more context.

            • Optional<String> serverUrl

              The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

            • Optional<String> tunnelId

              The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

        • Optional<RealtimeTracingConfig> tracing

          Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

          auto will create a trace for the session with default values for the workflow name, group id, and metadata.

          • JsonValue;

            • AUTO("auto")
          • TracingConfiguration

            • Optional<String> groupId

              The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

            • Optional<JsonValue> metadata

              The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

            • Optional<String> workflowName

              The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

        • Optional<RealtimeTruncation> truncation

          When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

          Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

          Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

          Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

          • RealtimeTruncationStrategy

            • AUTO("auto")

            • DISABLED("disabled")

          • class RealtimeTruncationRetentionRatio:

            Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

            • double retentionRatio

              Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

            • JsonValue; type "retention_ratio"constant

              Use retention ratio truncation.

              • RETENTION_RATIO("retention_ratio")
            • Optional<TokenLimits> tokenLimits

              Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

              • Optional<Long> postInstructions

                Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

      • class RealtimeTranscriptionSessionCreateRequest:

        Realtime transcription session object configuration.

        • JsonValue; type "transcription"constant

          The type of session to create. Always transcription for transcription sessions.

          • TRANSCRIPTION("transcription")
        • Optional<RealtimeTranscriptionSessionAudio> audio

          Configuration for input and output audio.

          • Optional<RealtimeTranscriptionSessionAudioInput> input

            • Optional<RealtimeAudioFormats> format

              The PCM audio format. Only a 24kHz sample rate is supported.

            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • Optional<AudioTranscription> transcription

              Configuration for input audio transcription, defaults to off and can be set to null to turn off once on. Input audio transcription is not native to the model, since the model consumes audio directly. Transcription runs asynchronously through the /audio/transcriptions endpoint and should be treated as guidance of input audio content rather than precisely what the model heard. The client can optionally set the language and prompt for transcription, these offer additional guidance to the transcription service.

            • Optional<RealtimeTranscriptionSessionAudioInputTurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • ServerVad

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • SemanticVad

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")

Returns

  • class ClientSecretCreateResponse:

    Response from creating a session and client secret for the Realtime API.

    • long expiresAt

      Expiration timestamp for the client secret, in seconds since epoch.

    • Session session

      The session configuration for either a realtime or transcription session.

      • class RealtimeSessionCreateResponse:

        A Realtime session configuration object.

        • String id

          Unique identifier for the session that looks like sess_1234567890abcdef.

        • JsonValue; object_ "realtime.session"constant

          The object type. Always realtime.session.

          • REALTIME_SESSION("realtime.session")
        • JsonValue; type "realtime"constant

          The type of session to create. Always realtime for the Realtime API.

          • REALTIME("realtime")
        • Optional<Audio> audio

          Configuration for input and output audio.

          • Optional<Input> input

            • Optional<RealtimeAudioFormats> format

              The format of the input audio.

              • AudioPcm

                • Optional<Rate> rate

                  The sample rate of the audio. Always 24000.

                  • _24000(24000)
                • Optional<Type> type

                  The audio format. Always audio/pcm.

                  • AUDIO_PCM("audio/pcm")
              • AudioPcmu

                • Optional<Type> type

                  The audio format. Always audio/pcmu.

                  • AUDIO_PCMU("audio/pcmu")
              • AudioPcma

                • Optional<Type> type

                  The audio format. Always audio/pcma.

                  • AUDIO_PCMA("audio/pcma")
            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

                • NEAR_FIELD("near_field")

                • FAR_FIELD("far_field")

            • Optional<AudioTranscription> transcription

              • Optional<Delay> delay

                Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

                • MINIMAL("minimal")

                • LOW("low")

                • MEDIUM("medium")

                • HIGH("high")

                • XHIGH("xhigh")

              • Optional<String> language

                The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

              • Optional<Model> model

                The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

                • WHISPER_1("whisper-1")

                • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

                • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

                • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

                • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

                • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

              • Optional<String> prompt

                An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

            • Optional<TurnDetection> turnDetection

              Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

              Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

              Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

              For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

              • class ServerVad:

                Server-side voice activity detection (VAD) which flips on when user speech is detected and off after a period of silence.

                • JsonValue; type "server_vad"constant

                  Type of turn detection, server_vad to turn on simple Server VAD.

                  • SERVER_VAD("server_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> idleTimeoutMs

                  Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

                  The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

                  An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

                  If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

                • Optional<Long> prefixPaddingMs

                  Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

                • Optional<Long> silenceDurationMs

                  Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

                • Optional<Double> threshold

                  Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • class SemanticVad:

                Server-side semantic turn detection which uses a model to determine when the user has finished speaking.

                • JsonValue; type "semantic_vad"constant

                  Type of turn detection, semantic_vad to turn on Semantic VAD.

                  • SEMANTIC_VAD("semantic_vad")
                • Optional<Boolean> createResponse

                  Whether or not to automatically generate a response when a VAD stop event occurs.

                • Optional<Eagerness> eagerness

                  Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

                  • LOW("low")

                  • MEDIUM("medium")

                  • HIGH("high")

                  • AUTO("auto")

                • Optional<Boolean> interruptResponse

                  Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

          • Optional<Output> output

            • Optional<RealtimeAudioFormats> format

              The format of the output audio.

            • Optional<Double> speed

              The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

              This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

            • Optional<Voice> voice

              The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. We recommend marin and cedar for best quality.

              • ALLOY("alloy")

              • ASH("ash")

              • BALLAD("ballad")

              • CORAL("coral")

              • ECHO("echo")

              • SAGE("sage")

              • SHIMMER("shimmer")

              • VERSE("verse")

              • MARIN("marin")

              • CEDAR("cedar")

        • Optional<Long> expiresAt

          Expiration timestamp for the session, in seconds since epoch.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
        • Optional<String> instructions

          The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

          Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

        • Optional<MaxOutputTokens> maxOutputTokens

          Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

          • long

          • JsonValue;

            • INF("inf")
        • Optional<Model> model

          The Realtime model used for this session.

          • GPT_REALTIME("gpt-realtime")

          • GPT_REALTIME_1_5("gpt-realtime-1.5")

          • GPT_REALTIME_2("gpt-realtime-2")

          • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

          • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

          • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

          • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

          • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

          • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

          • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

          • GPT_REALTIME_MINI("gpt-realtime-mini")

          • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

          • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

          • GPT_AUDIO_1_5("gpt-audio-1.5")

          • GPT_AUDIO_MINI("gpt-audio-mini")

          • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

          • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

        • Optional<List<OutputModality>> outputModalities

          The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

          • TEXT("text")

          • AUDIO("audio")

        • Optional<ResponsePrompt> prompt

          Reference to a prompt template and its variables. Learn more.

          • String id

            The unique identifier of the prompt template to use.

          • Optional<Variables> variables

            Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

            • String

            • class ResponseInputText:

              A text input to the model.

              • String text

                The text input to the model.

              • JsonValue; type "input_text"constant

                The type of the input item. Always input_text.

                • INPUT_TEXT("input_text")
            • class ResponseInputImage:

              An image input to the model. Learn about image inputs.

              • Detail detail

                The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

                • LOW("low")

                • HIGH("high")

                • AUTO("auto")

                • ORIGINAL("original")

              • JsonValue; type "input_image"constant

                The type of the input item. Always input_image.

                • INPUT_IMAGE("input_image")
              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> imageUrl

                The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

            • class ResponseInputFile:

              A file input to the model.

              • JsonValue; type "input_file"constant

                The type of the input item. Always input_file.

                • INPUT_FILE("input_file")
              • Optional<Detail> detail

                The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

                • LOW("low")

                • HIGH("high")

              • Optional<String> fileData

                The content of the file to be sent to the model.

              • Optional<String> fileId

                The ID of the file to be sent to the model.

              • Optional<String> fileUrl

                The URL of the file to be sent to the model.

              • Optional<String> filename

                The name of the file to be sent to the model.

          • Optional<String> version

            Optional version of the prompt template.

        • Optional<RealtimeReasoning> reasoning

          Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

          • Optional<RealtimeReasoningEffort> effort

            Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

        • Optional<ToolChoice> toolChoice

          How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

          • enum ToolChoiceOptions:

            Controls which (if any) tool is called by the model.

            none means the model will not call any tool and instead generates a message.

            auto means the model can pick between generating a message or calling one or more tools.

            required means the model must call one or more tools.

            • NONE("none")

            • AUTO("auto")

            • REQUIRED("required")

          • class ToolChoiceFunction:

            Use this option to force the model to call a specific function.

            • String name

              The name of the function to call.

            • JsonValue; type "function"constant

              For function calling, the type is always function.

              • FUNCTION("function")
          • class ToolChoiceMcp:

            Use this option to force the model to call a specific tool on a remote MCP server.

            • String serverLabel

              The label of the MCP server to use.

            • JsonValue; type "mcp"constant

              For MCP tools, the type is always mcp.

              • MCP("mcp")
            • Optional<String> name

              The name of the tool to call on the server.

        • Optional<List<Tool>> tools

          Tools available to the model.

          • class RealtimeFunctionTool:

            • Optional<String> description

              The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

            • Optional<String> name

              The name of the function.

            • Optional<JsonValue> parameters

              Parameters of the function in JSON Schema.

            • Optional<Type> type

              The type of the tool, i.e. function.

              • FUNCTION("function")
          • class McpTool:

            Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

            • String serverLabel

              A label for this MCP server, used to identify it in tool calls.

            • JsonValue; type "mcp"constant

              The type of the MCP tool. Always mcp.

              • MCP("mcp")
            • Optional<AllowedTools> allowedTools

              List of allowed tool names or a filter object.

              • List<String>

              • class McpToolFilter:

                A filter object to specify which tools are allowed.

                • Optional<Boolean> readOnly

                  Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                • Optional<List<String>> toolNames

                  List of allowed tool names.

            • Optional<String> authorization

              An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

            • Optional<ConnectorId> connectorId

              Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

              Currently supported connector_id values are:

              • Dropbox: connector_dropbox

              • Gmail: connector_gmail

              • Google Calendar: connector_googlecalendar

              • Google Drive: connector_googledrive

              • Microsoft Teams: connector_microsoftteams

              • Outlook Calendar: connector_outlookcalendar

              • Outlook Email: connector_outlookemail

              • SharePoint: connector_sharepoint

              • CONNECTOR_DROPBOX("connector_dropbox")

              • CONNECTOR_GMAIL("connector_gmail")

              • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

              • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

              • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

              • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

              • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

              • CONNECTOR_SHAREPOINT("connector_sharepoint")

            • Optional<Boolean> deferLoading

              Whether this MCP tool is deferred and discovered via tool search.

            • Optional<Headers> headers

              Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

            • Optional<RequireApproval> requireApproval

              Specify which of the MCP server's tools require approval.

              • class McpToolApprovalFilter:

                Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

                • Optional<Always> always

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

                • Optional<Never> never

                  A filter object to specify which tools are allowed.

                  • Optional<Boolean> readOnly

                    Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

                  • Optional<List<String>> toolNames

                    List of allowed tool names.

              • enum McpToolApprovalSetting:

                Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

                • ALWAYS("always")

                • NEVER("never")

            • Optional<String> serverDescription

              Optional description of the MCP server, used to provide more context.

            • Optional<String> serverUrl

              The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

            • Optional<String> tunnelId

              The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

        • Optional<Tracing> tracing

          Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

          auto will create a trace for the session with default values for the workflow name, group id, and metadata.

          • JsonValue;

            • AUTO("auto")
          • class TracingConfiguration:

            Granular configuration for tracing.

            • Optional<String> groupId

              The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

            • Optional<JsonValue> metadata

              The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

            • Optional<String> workflowName

              The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

        • Optional<RealtimeTruncation> truncation

          When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

          Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

          Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

          Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

          • RealtimeTruncationStrategy

            • AUTO("auto")

            • DISABLED("disabled")

          • class RealtimeTruncationRetentionRatio:

            Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

            • double retentionRatio

              Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

            • JsonValue; type "retention_ratio"constant

              Use retention ratio truncation.

              • RETENTION_RATIO("retention_ratio")
            • Optional<TokenLimits> tokenLimits

              Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

              • Optional<Long> postInstructions

                Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

      • class RealtimeTranscriptionSessionCreateResponse:

        A Realtime transcription session configuration object.

        • String id

          Unique identifier for the session that looks like sess_1234567890abcdef.

        • String object_

          The object type. Always realtime.transcription_session.

        • JsonValue; type "transcription"constant

          The type of session. Always transcription for transcription sessions.

          • TRANSCRIPTION("transcription")
        • Optional<Audio> audio

          Configuration for input audio for the session.

          • Optional<Input> input

            • Optional<RealtimeAudioFormats> format

              The PCM audio format. Only a 24kHz sample rate is supported.

            • Optional<NoiseReduction> noiseReduction

              Configuration for input audio noise reduction.

              • Optional<NoiseReductionType> type

                Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • Optional<AudioTranscription> transcription

            • Optional<RealtimeTranscriptionSessionTurnDetection> turnDetection

              Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.

              • Optional<Long> prefixPaddingMs

                Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

              • Optional<Long> silenceDurationMs

                Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

              • Optional<Double> threshold

                Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

              • Optional<String> type

                Type of turn detection, only server_vad is currently supported.

        • Optional<Long> expiresAt

          Expiration timestamp for the session, in seconds since epoch.

        • Optional<List<Include>> include

          Additional fields to include in server outputs.

          • item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

          • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")

    • String value

      The generated client secret value.

Example

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.realtime.clientsecrets.ClientSecretCreateParams;
import com.openai.models.realtime.clientsecrets.ClientSecretCreateResponse;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        ClientSecretCreateResponse clientSecret = client.realtime().clientSecrets().create();
    }
}

Response

{
  "expires_at": 0,
  "session": {
    "id": "id",
    "object": "realtime.session",
    "type": "realtime",
    "audio": {
      "input": {
        "format": {
          "rate": 24000,
          "type": "audio/pcm"
        },
        "noise_reduction": {
          "type": "near_field"
        },
        "transcription": {
          "delay": "minimal",
          "language": "language",
          "model": "whisper-1",
          "prompt": "prompt"
        },
        "turn_detection": {
          "type": "server_vad",
          "create_response": true,
          "idle_timeout_ms": 5000,
          "interrupt_response": true,
          "prefix_padding_ms": 0,
          "silence_duration_ms": 0,
          "threshold": 0
        }
      },
      "output": {
        "format": {
          "rate": 24000,
          "type": "audio/pcm"
        },
        "speed": 0.25,
        "voice": "ash"
      }
    },
    "expires_at": 0,
    "include": [
      "item.input_audio_transcription.logprobs"
    ],
    "instructions": "instructions",
    "max_output_tokens": "inf",
    "model": "gpt-realtime",
    "output_modalities": [
      "text"
    ],
    "prompt": {
      "id": "id",
      "variables": {
        "foo": "string"
      },
      "version": "version"
    },
    "reasoning": {
      "effort": "minimal"
    },
    "tool_choice": "none",
    "tools": [
      {
        "description": "description",
        "name": "name",
        "parameters": {},
        "type": "function"
      }
    ],
    "tracing": "auto",
    "truncation": "auto"
  },
  "value": "value"
}

Domain Types

Realtime Session Create Response

  • class RealtimeSessionCreateResponse:

    A Realtime session configuration object.

    • String id

      Unique identifier for the session that looks like sess_1234567890abcdef.

    • JsonValue; object_ "realtime.session"constant

      The object type. Always realtime.session.

      • REALTIME_SESSION("realtime.session")
    • JsonValue; type "realtime"constant

      The type of session to create. Always realtime for the Realtime API.

      • REALTIME("realtime")
    • Optional<Audio> audio

      Configuration for input and output audio.

      • Optional<Input> input

        • Optional<RealtimeAudioFormats> format

          The format of the input audio.

          • AudioPcm

            • Optional<Rate> rate

              The sample rate of the audio. Always 24000.

              • _24000(24000)
            • Optional<Type> type

              The audio format. Always audio/pcm.

              • AUDIO_PCM("audio/pcm")
          • AudioPcmu

            • Optional<Type> type

              The audio format. Always audio/pcmu.

              • AUDIO_PCMU("audio/pcmu")
          • AudioPcma

            • Optional<Type> type

              The audio format. Always audio/pcma.

              • AUDIO_PCMA("audio/pcma")
        • Optional<NoiseReduction> noiseReduction

          Configuration for input audio noise reduction. This can be set to null to turn off. Noise reduction filters audio added to the input audio buffer before it is sent to VAD and the model. Filtering the audio can improve VAD and turn detection accuracy (reducing false positives) and model performance by improving perception of the input audio.

          • Optional<NoiseReductionType> type

            Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • NEAR_FIELD("near_field")

            • FAR_FIELD("far_field")

        • Optional<AudioTranscription> transcription

          • Optional<Delay> delay

            Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

          • Optional<String> language

            The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

          • Optional<Model> model

            The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

            • WHISPER_1("whisper-1")

            • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

            • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

            • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

            • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

            • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

          • Optional<String> prompt

            An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

        • Optional<TurnDetection> turnDetection

          Configuration for turn detection, ether Server VAD or Semantic VAD. This can be set to null to turn off, in which case the client must manually trigger model response.

          Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech.

          Semantic VAD is more advanced and uses a turn detection model (in conjunction with VAD) to semantically estimate whether the user has finished speaking, then dynamically sets a timeout based on this probability. For example, if user audio trails off with "uhhm", the model will score a low probability of turn end and wait longer for the user to continue speaking. This can be useful for more natural conversations, but may have a higher latency.

          For gpt-realtime-whisper transcription sessions, turn detection must be set to null; VAD is not supported.

          • class ServerVad:

            Server-side voice activity detection (VAD) which flips on when user speech is detected and off after a period of silence.

            • JsonValue; type "server_vad"constant

              Type of turn detection, server_vad to turn on simple Server VAD.

              • SERVER_VAD("server_vad")
            • Optional<Boolean> createResponse

              Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.

              If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

            • Optional<Long> idleTimeoutMs

              Optional timeout after which a model response will be triggered automatically. This is useful for situations in which a long pause from the user is unexpected, such as a phone call. The model will effectively prompt the user to continue the conversation based on the current context.

              The timeout value will be applied after the last model response's audio has finished playing, i.e. it's set to the response.done time plus audio playback duration.

              An input_audio_buffer.timeout_triggered event (plus events associated with the Response) will be emitted when the timeout is reached. Idle timeout is currently only supported for server_vad mode.

            • Optional<Boolean> interruptResponse

              Whether or not to automatically interrupt (cancel) any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.

              If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.

            • Optional<Long> prefixPaddingMs

              Used only for server_vad mode. Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

            • Optional<Long> silenceDurationMs

              Used only for server_vad mode. Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

            • Optional<Double> threshold

              Used only for server_vad mode. Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

          • class SemanticVad:

            Server-side semantic turn detection which uses a model to determine when the user has finished speaking.

            • JsonValue; type "semantic_vad"constant

              Type of turn detection, semantic_vad to turn on Semantic VAD.

              • SEMANTIC_VAD("semantic_vad")
            • Optional<Boolean> createResponse

              Whether or not to automatically generate a response when a VAD stop event occurs.

            • Optional<Eagerness> eagerness

              Used only for semantic_vad mode. The eagerness of the model to respond. low will wait longer for the user to continue speaking, high will respond more quickly. auto is the default and is equivalent to medium. low, medium, and high have max timeouts of 8s, 4s, and 2s respectively.

              • LOW("low")

              • MEDIUM("medium")

              • HIGH("high")

              • AUTO("auto")

            • Optional<Boolean> interruptResponse

              Whether or not to automatically interrupt any ongoing response with output to the default conversation (i.e. conversation of auto) when a VAD start event occurs.

      • Optional<Output> output

        • Optional<RealtimeAudioFormats> format

          The format of the output audio.

        • Optional<Double> speed

          The speed of the model's spoken response as a multiple of the original speed. 1.0 is the default speed. 0.25 is the minimum speed. 1.5 is the maximum speed. This value can only be changed in between model turns, not while a response is in progress.

          This parameter is a post-processing adjustment to the audio after it is generated, it's also possible to prompt the model to speak faster or slower.

        • Optional<Voice> voice

          The voice the model uses to respond. Voice cannot be changed during the session once the model has responded with audio at least once. Current voice options are alloy, ash, ballad, coral, echo, sage, shimmer, verse, marin, and cedar. We recommend marin and cedar for best quality.

          • ALLOY("alloy")

          • ASH("ash")

          • BALLAD("ballad")

          • CORAL("coral")

          • ECHO("echo")

          • SAGE("sage")

          • SHIMMER("shimmer")

          • VERSE("verse")

          • MARIN("marin")

          • CEDAR("cedar")

    • Optional<Long> expiresAt

      Expiration timestamp for the session, in seconds since epoch.

    • Optional<List<Include>> include

      Additional fields to include in server outputs.

      item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

      • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")
    • Optional<String> instructions

      The default system instructions (i.e. system message) prepended to model calls. This field allows the client to guide the model on desired responses. The model can be instructed on response content and format, (e.g. "be extremely succinct", "act friendly", "here are examples of good responses") and on audio behavior (e.g. "talk quickly", "inject emotion into your voice", "laugh frequently"). The instructions are not guaranteed to be followed by the model, but they provide guidance to the model on the desired behavior.

      Note that the server sets default instructions which will be used if this field is not set and are visible in the session.created event at the start of the session.

    • Optional<MaxOutputTokens> maxOutputTokens

      Maximum number of output tokens for a single assistant response, inclusive of tool calls. Provide an integer between 1 and 4096 to limit output tokens, or inf for the maximum available tokens for a given model. Defaults to inf.

      • long

      • JsonValue;

        • INF("inf")
    • Optional<Model> model

      The Realtime model used for this session.

      • GPT_REALTIME("gpt-realtime")

      • GPT_REALTIME_1_5("gpt-realtime-1.5")

      • GPT_REALTIME_2("gpt-realtime-2")

      • GPT_REALTIME_2025_08_28("gpt-realtime-2025-08-28")

      • GPT_4O_REALTIME_PREVIEW("gpt-4o-realtime-preview")

      • GPT_4O_REALTIME_PREVIEW_2024_10_01("gpt-4o-realtime-preview-2024-10-01")

      • GPT_4O_REALTIME_PREVIEW_2024_12_17("gpt-4o-realtime-preview-2024-12-17")

      • GPT_4O_REALTIME_PREVIEW_2025_06_03("gpt-4o-realtime-preview-2025-06-03")

      • GPT_4O_MINI_REALTIME_PREVIEW("gpt-4o-mini-realtime-preview")

      • GPT_4O_MINI_REALTIME_PREVIEW_2024_12_17("gpt-4o-mini-realtime-preview-2024-12-17")

      • GPT_REALTIME_MINI("gpt-realtime-mini")

      • GPT_REALTIME_MINI_2025_10_06("gpt-realtime-mini-2025-10-06")

      • GPT_REALTIME_MINI_2025_12_15("gpt-realtime-mini-2025-12-15")

      • GPT_AUDIO_1_5("gpt-audio-1.5")

      • GPT_AUDIO_MINI("gpt-audio-mini")

      • GPT_AUDIO_MINI_2025_10_06("gpt-audio-mini-2025-10-06")

      • GPT_AUDIO_MINI_2025_12_15("gpt-audio-mini-2025-12-15")

    • Optional<List<OutputModality>> outputModalities

      The set of modalities the model can respond with. It defaults to ["audio"], indicating that the model will respond with audio plus a transcript. ["text"] can be used to make the model respond with text only. It is not possible to request both text and audio at the same time.

      • TEXT("text")

      • AUDIO("audio")

    • Optional<ResponsePrompt> prompt

      Reference to a prompt template and its variables. Learn more.

      • String id

        The unique identifier of the prompt template to use.

      • Optional<Variables> variables

        Optional map of values to substitute in for variables in your prompt. The substitution values can either be strings, or other Response input types like images or files.

        • String

        • class ResponseInputText:

          A text input to the model.

          • String text

            The text input to the model.

          • JsonValue; type "input_text"constant

            The type of the input item. Always input_text.

            • INPUT_TEXT("input_text")
        • class ResponseInputImage:

          An image input to the model. Learn about image inputs.

          • Detail detail

            The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.

            • LOW("low")

            • HIGH("high")

            • AUTO("auto")

            • ORIGINAL("original")

          • JsonValue; type "input_image"constant

            The type of the input item. Always input_image.

            • INPUT_IMAGE("input_image")
          • Optional<String> fileId

            The ID of the file to be sent to the model.

          • Optional<String> imageUrl

            The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.

        • class ResponseInputFile:

          A file input to the model.

          • JsonValue; type "input_file"constant

            The type of the input item. Always input_file.

            • INPUT_FILE("input_file")
          • Optional<Detail> detail

            The detail level of the file to be sent to the model. Use low for the default rendering behavior, or high to render the file at higher quality. Defaults to low.

            • LOW("low")

            • HIGH("high")

          • Optional<String> fileData

            The content of the file to be sent to the model.

          • Optional<String> fileId

            The ID of the file to be sent to the model.

          • Optional<String> fileUrl

            The URL of the file to be sent to the model.

          • Optional<String> filename

            The name of the file to be sent to the model.

      • Optional<String> version

        Optional version of the prompt template.

    • Optional<RealtimeReasoning> reasoning

      Configuration for reasoning-capable Realtime models such as gpt-realtime-2.

      • Optional<RealtimeReasoningEffort> effort

        Constrains effort on reasoning for reasoning-capable Realtime models such as gpt-realtime-2.

        • MINIMAL("minimal")

        • LOW("low")

        • MEDIUM("medium")

        • HIGH("high")

        • XHIGH("xhigh")

    • Optional<ToolChoice> toolChoice

      How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.

      • enum ToolChoiceOptions:

        Controls which (if any) tool is called by the model.

        none means the model will not call any tool and instead generates a message.

        auto means the model can pick between generating a message or calling one or more tools.

        required means the model must call one or more tools.

        • NONE("none")

        • AUTO("auto")

        • REQUIRED("required")

      • class ToolChoiceFunction:

        Use this option to force the model to call a specific function.

        • String name

          The name of the function to call.

        • JsonValue; type "function"constant

          For function calling, the type is always function.

          • FUNCTION("function")
      • class ToolChoiceMcp:

        Use this option to force the model to call a specific tool on a remote MCP server.

        • String serverLabel

          The label of the MCP server to use.

        • JsonValue; type "mcp"constant

          For MCP tools, the type is always mcp.

          • MCP("mcp")
        • Optional<String> name

          The name of the tool to call on the server.

    • Optional<List<Tool>> tools

      Tools available to the model.

      • class RealtimeFunctionTool:

        • Optional<String> description

          The description of the function, including guidance on when and how to call it, and guidance about what to tell the user when calling (if anything).

        • Optional<String> name

          The name of the function.

        • Optional<JsonValue> parameters

          Parameters of the function in JSON Schema.

        • Optional<Type> type

          The type of the tool, i.e. function.

          • FUNCTION("function")
      • class McpTool:

        Give the model access to additional tools via remote Model Context Protocol (MCP) servers. Learn more about MCP.

        • String serverLabel

          A label for this MCP server, used to identify it in tool calls.

        • JsonValue; type "mcp"constant

          The type of the MCP tool. Always mcp.

          • MCP("mcp")
        • Optional<AllowedTools> allowedTools

          List of allowed tool names or a filter object.

          • List<String>

          • class McpToolFilter:

            A filter object to specify which tools are allowed.

            • Optional<Boolean> readOnly

              Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

            • Optional<List<String>> toolNames

              List of allowed tool names.

        • Optional<String> authorization

          An OAuth access token that can be used with a remote MCP server, either with a custom MCP server URL or a service connector. Your application must handle the OAuth authorization flow and provide the token here.

        • Optional<ConnectorId> connectorId

          Identifier for service connectors, like those available in ChatGPT. One of server_url, connector_id, or tunnel_id must be provided. Learn more about service connectors here.

          Currently supported connector_id values are:

          • Dropbox: connector_dropbox

          • Gmail: connector_gmail

          • Google Calendar: connector_googlecalendar

          • Google Drive: connector_googledrive

          • Microsoft Teams: connector_microsoftteams

          • Outlook Calendar: connector_outlookcalendar

          • Outlook Email: connector_outlookemail

          • SharePoint: connector_sharepoint

          • CONNECTOR_DROPBOX("connector_dropbox")

          • CONNECTOR_GMAIL("connector_gmail")

          • CONNECTOR_GOOGLECALENDAR("connector_googlecalendar")

          • CONNECTOR_GOOGLEDRIVE("connector_googledrive")

          • CONNECTOR_MICROSOFTTEAMS("connector_microsoftteams")

          • CONNECTOR_OUTLOOKCALENDAR("connector_outlookcalendar")

          • CONNECTOR_OUTLOOKEMAIL("connector_outlookemail")

          • CONNECTOR_SHAREPOINT("connector_sharepoint")

        • Optional<Boolean> deferLoading

          Whether this MCP tool is deferred and discovered via tool search.

        • Optional<Headers> headers

          Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.

        • Optional<RequireApproval> requireApproval

          Specify which of the MCP server's tools require approval.

          • class McpToolApprovalFilter:

            Specify which of the MCP server's tools require approval. Can be always, never, or a filter object associated with tools that require approval.

            • Optional<Always> always

              A filter object to specify which tools are allowed.

              • Optional<Boolean> readOnly

                Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

              • Optional<List<String>> toolNames

                List of allowed tool names.

            • Optional<Never> never

              A filter object to specify which tools are allowed.

              • Optional<Boolean> readOnly

                Indicates whether or not a tool modifies data or is read-only. If an MCP server is annotated with readOnlyHint, it will match this filter.

              • Optional<List<String>> toolNames

                List of allowed tool names.

          • enum McpToolApprovalSetting:

            Specify a single approval policy for all tools. One of always or never. When set to always, all tools will require approval. When set to never, all tools will not require approval.

            • ALWAYS("always")

            • NEVER("never")

        • Optional<String> serverDescription

          Optional description of the MCP server, used to provide more context.

        • Optional<String> serverUrl

          The URL for the MCP server. One of server_url, connector_id, or tunnel_id must be provided.

        • Optional<String> tunnelId

          The Secure MCP Tunnel ID to use instead of a direct server URL. One of server_url, connector_id, or tunnel_id must be provided.

    • Optional<Tracing> tracing

      Realtime API can write session traces to the Traces Dashboard. Set to null to disable tracing. Once tracing is enabled for a session, the configuration cannot be modified.

      auto will create a trace for the session with default values for the workflow name, group id, and metadata.

      • JsonValue;

        • AUTO("auto")
      • class TracingConfiguration:

        Granular configuration for tracing.

        • Optional<String> groupId

          The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.

        • Optional<JsonValue> metadata

          The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.

        • Optional<String> workflowName

          The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.

    • Optional<RealtimeTruncation> truncation

      When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.

      Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.

      Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.

      Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.

      • RealtimeTruncationStrategy

        • AUTO("auto")

        • DISABLED("disabled")

      • class RealtimeTruncationRetentionRatio:

        Retain a fraction of the conversation tokens when the conversation exceeds the input token limit. This allows you to amortize truncations across multiple turns, which can help improve cached token usage.

        • double retentionRatio

          Fraction of post-instruction conversation tokens to retain (0.0 - 1.0) when the conversation exceeds the input token limit. Setting this to 0.8 means that messages will be dropped until 80% of the maximum allowed tokens are used. This helps reduce the frequency of truncations and improve cache rates.

        • JsonValue; type "retention_ratio"constant

          Use retention ratio truncation.

          • RETENTION_RATIO("retention_ratio")
        • Optional<TokenLimits> tokenLimits

          Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.

          • Optional<Long> postInstructions

            Maximum tokens allowed in the conversation after instructions (which including tool definitions). For example, setting this to 5,000 would mean that truncation would occur when the conversation exceeds 5,000 tokens after instructions. This cannot be higher than the model's context window size minus the maximum output tokens.

Realtime Transcription Session Create Response

  • class RealtimeTranscriptionSessionCreateResponse:

    A Realtime transcription session configuration object.

    • String id

      Unique identifier for the session that looks like sess_1234567890abcdef.

    • String object_

      The object type. Always realtime.transcription_session.

    • JsonValue; type "transcription"constant

      The type of session. Always transcription for transcription sessions.

      • TRANSCRIPTION("transcription")
    • Optional<Audio> audio

      Configuration for input audio for the session.

      • Optional<Input> input

        • Optional<RealtimeAudioFormats> format

          The PCM audio format. Only a 24kHz sample rate is supported.

          • AudioPcm

            • Optional<Rate> rate

              The sample rate of the audio. Always 24000.

              • _24000(24000)
            • Optional<Type> type

              The audio format. Always audio/pcm.

              • AUDIO_PCM("audio/pcm")
          • AudioPcmu

            • Optional<Type> type

              The audio format. Always audio/pcmu.

              • AUDIO_PCMU("audio/pcmu")
          • AudioPcma

            • Optional<Type> type

              The audio format. Always audio/pcma.

              • AUDIO_PCMA("audio/pcma")
        • Optional<NoiseReduction> noiseReduction

          Configuration for input audio noise reduction.

          • Optional<NoiseReductionType> type

            Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.

            • NEAR_FIELD("near_field")

            • FAR_FIELD("far_field")

        • Optional<AudioTranscription> transcription

          • Optional<Delay> delay

            Controls how long the model waits before emitting transcription text. Higher values can improve transcription accuracy at the cost of latency. Only supported with gpt-realtime-whisper in GA Realtime sessions.

            • MINIMAL("minimal")

            • LOW("low")

            • MEDIUM("medium")

            • HIGH("high")

            • XHIGH("xhigh")

          • Optional<String> language

            The language of the input audio. Supplying the input language in ISO-639-1 (e.g. en) format will improve accuracy and latency.

          • Optional<Model> model

            The model to use for transcription. Current options are whisper-1, gpt-4o-mini-transcribe, gpt-4o-mini-transcribe-2025-12-15, gpt-4o-transcribe, gpt-4o-transcribe-diarize, and gpt-realtime-whisper. Use gpt-4o-transcribe-diarize when you need diarization with speaker labels.

            • WHISPER_1("whisper-1")

            • GPT_4O_MINI_TRANSCRIBE("gpt-4o-mini-transcribe")

            • GPT_4O_MINI_TRANSCRIBE_2025_12_15("gpt-4o-mini-transcribe-2025-12-15")

            • GPT_4O_TRANSCRIBE("gpt-4o-transcribe")

            • GPT_4O_TRANSCRIBE_DIARIZE("gpt-4o-transcribe-diarize")

            • GPT_REALTIME_WHISPER("gpt-realtime-whisper")

          • Optional<String> prompt

            An optional text to guide the model's style or continue a previous audio segment. For whisper-1, the prompt is a list of keywords. For gpt-4o-transcribe models (excluding gpt-4o-transcribe-diarize), the prompt is a free text string, for example "expect words related to technology". Prompt is not supported with gpt-realtime-whisper in GA Realtime sessions.

        • Optional<RealtimeTranscriptionSessionTurnDetection> turnDetection

          Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.

          • Optional<Long> prefixPaddingMs

            Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

          • Optional<Long> silenceDurationMs

            Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

          • Optional<Double> threshold

            Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

          • Optional<String> type

            Type of turn detection, only server_vad is currently supported.

    • Optional<Long> expiresAt

      Expiration timestamp for the session, in seconds since epoch.

    • Optional<List<Include>> include

      Additional fields to include in server outputs.

      • item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.

      • ITEM_INPUT_AUDIO_TRANSCRIPTION_LOGPROBS("item.input_audio_transcription.logprobs")

Realtime Transcription Session Turn Detection

  • class RealtimeTranscriptionSessionTurnDetection:

    Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.

    • Optional<Long> prefixPaddingMs

      Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

    • Optional<Long> silenceDurationMs

      Duration of silence to detect speech stop (in milliseconds). Defaults to 500ms. With shorter values the model will respond more quickly, but may jump in on short pauses from the user.

    • Optional<Double> threshold

      Activation threshold for VAD (0.0 to 1.0), this defaults to 0.5. A higher threshold will require louder audio to activate the model, and thus might perform better in noisy environments.

    • Optional<String> type

      Type of turn detection, only server_vad is currently supported.

Calls

Accept call

realtime().calls().accept(CallAcceptParamsparams, RequestOptionsrequestOptions = RequestOptions.none())

post /realtime/calls/{call_id}/accept

Accept an incoming SIP call and configure the realtime session that will handle it.

Parameters

  • CallAcceptParams params

    • Optional<String> callId

    • RealtimeSessionCreateRequest realtimeSessionCreateRequest

      Realtime session object configuration.

Example

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.realtime.RealtimeSessionCreateRequest;
import com.openai.models.realtime.calls.CallAcceptParams;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        CallAcceptParams params = CallAcceptParams.builder()
            .callId("call_id")
            .realtimeSessionCreateRequest(RealtimeSessionCreateRequest.builder().build())
            .build();
        client.realtime().calls().accept(params);
    }
}

Hang up call

realtime().calls().hangup(CallHangupParamsparams = CallHangupParams.none(), RequestOptionsrequestOptions = RequestOptions.none())

post /realtime/calls/{call_id}/hangup

End an active Realtime API call, whether it was initiated over SIP or WebRTC.

Parameters

  • CallHangupParams params

    • Optional<String> callId

Example

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.realtime.calls.CallHangupParams;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        client.realtime().calls().hangup("call_id");
    }
}

Refer call

realtime().calls().refer(CallReferParamsparams, RequestOptionsrequestOptions = RequestOptions.none())

post /realtime/calls/{call_id}/refer

Transfer an active SIP call to a new destination using the SIP REFER verb.

Parameters

  • CallReferParams params

    • Optional<String> callId

    • String targetUri

      URI that should appear in the SIP Refer-To header. Supports values like tel:+14155550123 or sip:agent@example.com.

Example

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.realtime.calls.CallReferParams;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        CallReferParams params = CallReferParams.builder()
            .callId("call_id")
            .targetUri("tel:+14155550123")
            .build();
        client.realtime().calls().refer(params);
    }
}

Reject call

realtime().calls().reject(CallRejectParamsparams = CallRejectParams.none(), RequestOptionsrequestOptions = RequestOptions.none())

post /realtime/calls/{call_id}/reject

Decline an incoming SIP call by returning a SIP status code to the caller.

Parameters

  • CallRejectParams params

    • Optional<String> callId

    • Optional<Long> statusCode

      SIP response code to send back to the caller. Defaults to 603 (Decline) when omitted.

Example

package com.openai.example;

import com.openai.client.OpenAIClient;
import com.openai.client.okhttp.OpenAIOkHttpClient;
import com.openai.models.realtime.calls.CallRejectParams;

public final class Main {
    private Main() {}

    public static void main(String[] args) {
        OpenAIClient client = OpenAIOkHttpClient.fromEnv();

        client.realtime().calls().reject("call_id");
    }
}

Translations

Client Secrets

Sessions

Transcription Sessions