Realtime

realtime.connect(RealtimeConnectParams**kwargs)

**** ``

The Realtime API enables you to build low-latency, multi-modal conversational experiences. It currently supports text and audio as both input and output, as well as function calling.

Some notable benefits of the API include:

• Native speech-to-speech: Skipping an intermediate text format means low latency and nuanced output.
• Natural, steerable voices: The models have natural inflection and can laugh, whisper, and adhere to tone direction.
• Simultaneous multimodal output: Text is useful for moderation; faster-than-realtime audio ensures stable playback.

The Realtime API is a stateful, event-based API that communicates over a WebSocket.

Parameters

• call_id: Optional[str]

• model: Optional[str]

Example

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ.get("OPENAI_API_KEY"),  # This is the default and can be omitted
)
client.realtime.connect()

Domain Types

Audio Transcription

• class AudioTranscription: …

  • delay: Optional[Literal["minimal", "low", "medium", 2 more]]

    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"

    • "low"

    • "medium"

    • "high"

    • "xhigh"

  • language: Optional[str]

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

  • model: Optional[Union[str, Literal["whisper-1", "gpt-4o-mini-transcribe", "gpt-4o-mini-transcribe-2025-12-15", 3 more], null]]

    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.

    • str

    • Literal["whisper-1", "gpt-4o-mini-transcribe", "gpt-4o-mini-transcribe-2025-12-15", 3 more]

      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"

      • "gpt-4o-mini-transcribe"

      • "gpt-4o-mini-transcribe-2025-12-15"

      • "gpt-4o-transcribe"

      • "gpt-4o-transcribe-diarize"

      • "gpt-realtime-whisper"

  • prompt: Optional[str]

    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.

    • id: Optional[str]

      The unique ID of the conversation.

    • object: Optional[Literal["realtime.conversation"]]

      The object type, must be realtime.conversation.

      • "realtime.conversation"

  • event_id: str

    The unique ID of the server event.

  • type: Literal["conversation.created"]

    The event type, must be conversation.created.

    • "conversation.created"

Conversation Item

• ConversationItem

  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.

    • content: List[Content]

      The content of the message.

      • text: Optional[str]

        The text content.

      • type: Optional[Literal["input_text"]]

        The content type. Always input_text for system messages.

        • "input_text"

    • role: Literal["system"]

      The role of the message sender. Always system.

      • "system"

    • type: Literal["message"]

      The type of the item. Always message.

      • "message"

    • id: Optional[str]

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

    • object: Optional[Literal["realtime.item"]]

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

      • "realtime.item"

    • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

      • "completed"

      • "incomplete"

      • "in_progress"

  • class RealtimeConversationItemUserMessage: …

    A user message item in a Realtime conversation.

    • content: List[Content]

      The content of the message.

      • audio: Optional[str]

        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.

      • detail: Optional[Literal["auto", "low", "high"]]

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

        • "auto"

        • "low"

        • "high"

      • image_url: Optional[str]

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

      • text: Optional[str]

        The text content (for input_text).

      • transcript: Optional[str]

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

      • type: Optional[Literal["input_text", "input_audio", "input_image"]]

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

        • "input_text"

        • "input_audio"

        • "input_image"

    • role: Literal["user"]

      The role of the message sender. Always user.

      • "user"

    • type: Literal["message"]

      The type of the item. Always message.

      • "message"

    • id: Optional[str]

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

    • object: Optional[Literal["realtime.item"]]

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

      • "realtime.item"

    • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

      • "completed"

      • "incomplete"

      • "in_progress"

  • class RealtimeConversationItemAssistantMessage: …

    An assistant message item in a Realtime conversation.

    • content: List[Content]

      The content of the message.

      • audio: Optional[str]

        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.

      • text: Optional[str]

        The text content.

      • transcript: Optional[str]

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

      • type: Optional[Literal["output_text", "output_audio"]]

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

        • "output_text"

        • "output_audio"

    • role: Literal["assistant"]

      The role of the message sender. Always assistant.

      • "assistant"

    • type: Literal["message"]

      The type of the item. Always message.

      • "message"

    • id: Optional[str]

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

    • object: Optional[Literal["realtime.item"]]

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

      • "realtime.item"

    • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

      • "completed"

      • "incomplete"

      • "in_progress"

  • class RealtimeConversationItemFunctionCall: …

    A function call item in a Realtime conversation.

    • arguments: str

      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}.

    • name: str

      The name of the function being called.

    • type: Literal["function_call"]

      The type of the item. Always function_call.

      • "function_call"

    • id: Optional[str]

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

    • call_id: Optional[str]

      The ID of the function call.

    • object: Optional[Literal["realtime.item"]]

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

      • "realtime.item"

    • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

      • "completed"

      • "incomplete"

      • "in_progress"

  • class RealtimeConversationItemFunctionCallOutput: …

    A function call output item in a Realtime conversation.

    • call_id: str

      The ID of the function call this output is for.

    • output: str

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

    • type: Literal["function_call_output"]

      The type of the item. Always function_call_output.

      • "function_call_output"

    • id: Optional[str]

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

    • object: Optional[Literal["realtime.item"]]

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

      • "realtime.item"

    • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

      • "completed"

      • "incomplete"

      • "in_progress"

  • class RealtimeMcpApprovalResponse: …

    A Realtime item responding to an MCP approval request.

    • id: str

      The unique ID of the approval response.

    • approval_request_id: str

      The ID of the approval request being answered.

    • approve: bool

      Whether the request was approved.

    • type: Literal["mcp_approval_response"]

      The type of the item. Always mcp_approval_response.

      • "mcp_approval_response"

    • reason: Optional[str]

      Optional reason for the decision.

  • class RealtimeMcpListTools: …

    A Realtime item listing tools available on an MCP server.

    • server_label: str

      The label of the MCP server.

    • tools: List[Tool]

      The tools available on the server.

      • input_schema: object

        The JSON schema describing the tool's input.

      • name: str

        The name of the tool.

      • annotations: Optional[object]

        Additional annotations about the tool.

      • description: Optional[str]

        The description of the tool.

    • type: Literal["mcp_list_tools"]

      The type of the item. Always mcp_list_tools.

      • "mcp_list_tools"

    • id: Optional[str]

      The unique ID of the list.

  • class RealtimeMcpToolCall: …

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

    • id: str

      The unique ID of the tool call.

    • arguments: str

      A JSON string of the arguments passed to the tool.

    • name: str

      The name of the tool that was run.

    • server_label: str

      The label of the MCP server running the tool.

    • type: Literal["mcp_call"]

      The type of the item. Always mcp_call.

      • "mcp_call"

    • approval_request_id: Optional[str]

      The ID of an associated approval request, if any.

    • error: Optional[Error]

      The error from the tool call, if any.

      • class RealtimeMcpProtocolError: …

        • code: int

        • message: str

        • type: Literal["protocol_error"]

          • "protocol_error"

      • class RealtimeMcpToolExecutionError: …

        • message: str

        • type: Literal["tool_execution_error"]

          • "tool_execution_error"

      • class RealtimeMcphttpError: …

        • code: int

        • message: str

        • type: Literal["http_error"]

          • "http_error"

    • output: Optional[str]

      The output from the tool call.

  • class RealtimeMcpApprovalRequest: …

    A Realtime item requesting human approval of a tool invocation.

    • id: str

      The unique ID of the approval request.

    • arguments: str

      A JSON string of arguments for the tool.

    • name: str

      The name of the tool to run.

    • server_label: str

      The label of the MCP server making the request.

    • type: Literal["mcp_approval_request"]

      The type of the item. Always 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.

  • event_id: str

    The unique ID of the server event.

  • item: ConversationItem

    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.

      • content: List[Content]

        The content of the message.

        • text: Optional[str]

          The text content.

        • type: Optional[Literal["input_text"]]

          The content type. Always input_text for system messages.

          • "input_text"

      • role: Literal["system"]

        The role of the message sender. Always system.

        • "system"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemUserMessage: …

      A user message item in a Realtime conversation.

      • content: List[Content]

        The content of the message.

        • audio: Optional[str]

          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.

        • detail: Optional[Literal["auto", "low", "high"]]

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

          • "auto"

          • "low"

          • "high"

        • image_url: Optional[str]

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

        • text: Optional[str]

          The text content (for input_text).

        • transcript: Optional[str]

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

        • type: Optional[Literal["input_text", "input_audio", "input_image"]]

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

          • "input_text"

          • "input_audio"

          • "input_image"

      • role: Literal["user"]

        The role of the message sender. Always user.

        • "user"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemAssistantMessage: …

      An assistant message item in a Realtime conversation.

      • content: List[Content]

        The content of the message.

        • audio: Optional[str]

          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.

        • text: Optional[str]

          The text content.

        • transcript: Optional[str]

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

        • type: Optional[Literal["output_text", "output_audio"]]

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

          • "output_text"

          • "output_audio"

      • role: Literal["assistant"]

        The role of the message sender. Always assistant.

        • "assistant"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemFunctionCall: …

      A function call item in a Realtime conversation.

      • arguments: str

        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}.

      • name: str

        The name of the function being called.

      • type: Literal["function_call"]

        The type of the item. Always function_call.

        • "function_call"

      • id: Optional[str]

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

      • call_id: Optional[str]

        The ID of the function call.

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemFunctionCallOutput: …

      A function call output item in a Realtime conversation.

      • call_id: str

        The ID of the function call this output is for.

      • output: str

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

      • type: Literal["function_call_output"]

        The type of the item. Always function_call_output.

        • "function_call_output"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeMcpApprovalResponse: …

      A Realtime item responding to an MCP approval request.

      • id: str

        The unique ID of the approval response.

      • approval_request_id: str

        The ID of the approval request being answered.

      • approve: bool

        Whether the request was approved.

      • type: Literal["mcp_approval_response"]

        The type of the item. Always mcp_approval_response.

        • "mcp_approval_response"

      • reason: Optional[str]

        Optional reason for the decision.

    • class RealtimeMcpListTools: …

      A Realtime item listing tools available on an MCP server.

      • server_label: str

        The label of the MCP server.

      • tools: List[Tool]

        The tools available on the server.

        • input_schema: object

          The JSON schema describing the tool's input.

        • name: str

          The name of the tool.

        • annotations: Optional[object]

          Additional annotations about the tool.

        • description: Optional[str]

          The description of the tool.

      • type: Literal["mcp_list_tools"]

        The type of the item. Always mcp_list_tools.

        • "mcp_list_tools"

      • id: Optional[str]

        The unique ID of the list.

    • class RealtimeMcpToolCall: …

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

      • id: str

        The unique ID of the tool call.

      • arguments: str

        A JSON string of the arguments passed to the tool.

      • name: str

        The name of the tool that was run.

      • server_label: str

        The label of the MCP server running the tool.

      • type: Literal["mcp_call"]

        The type of the item. Always mcp_call.

        • "mcp_call"

      • approval_request_id: Optional[str]

        The ID of an associated approval request, if any.

      • error: Optional[Error]

        The error from the tool call, if any.

        • class RealtimeMcpProtocolError: …

          • code: int

          • message: str

          • type: Literal["protocol_error"]

            • "protocol_error"

        • class RealtimeMcpToolExecutionError: …

          • message: str

          • type: Literal["tool_execution_error"]

            • "tool_execution_error"

        • class RealtimeMcphttpError: …

          • code: int

          • message: str

          • type: Literal["http_error"]

            • "http_error"

      • output: Optional[str]

        The output from the tool call.

    • class RealtimeMcpApprovalRequest: …

      A Realtime item requesting human approval of a tool invocation.

      • id: str

        The unique ID of the approval request.

      • arguments: str

        A JSON string of arguments for the tool.

      • name: str

        The name of the tool to run.

      • server_label: str

        The label of the MCP server making the request.

      • type: Literal["mcp_approval_request"]

        The type of the item. Always mcp_approval_request.

        • "mcp_approval_request"

  • type: Literal["conversation.item.added"]

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

    • "conversation.item.added"

  • previous_item_id: Optional[str]

    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.

  • item: ConversationItem

    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.

      • content: List[Content]

        The content of the message.

        • text: Optional[str]

          The text content.

        • type: Optional[Literal["input_text"]]

          The content type. Always input_text for system messages.

          • "input_text"

      • role: Literal["system"]

        The role of the message sender. Always system.

        • "system"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemUserMessage: …

      A user message item in a Realtime conversation.

      • content: List[Content]

        The content of the message.

        • audio: Optional[str]

          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.

        • detail: Optional[Literal["auto", "low", "high"]]

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

          • "auto"

          • "low"

          • "high"

        • image_url: Optional[str]

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

        • text: Optional[str]

          The text content (for input_text).

        • transcript: Optional[str]

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

        • type: Optional[Literal["input_text", "input_audio", "input_image"]]

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

          • "input_text"

          • "input_audio"

          • "input_image"

      • role: Literal["user"]

        The role of the message sender. Always user.

        • "user"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemAssistantMessage: …

      An assistant message item in a Realtime conversation.

      • content: List[Content]

        The content of the message.

        • audio: Optional[str]

          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.

        • text: Optional[str]

          The text content.

        • transcript: Optional[str]

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

        • type: Optional[Literal["output_text", "output_audio"]]

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

          • "output_text"

          • "output_audio"

      • role: Literal["assistant"]

        The role of the message sender. Always assistant.

        • "assistant"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemFunctionCall: …

      A function call item in a Realtime conversation.

      • arguments: str

        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}.

      • name: str

        The name of the function being called.

      • type: Literal["function_call"]

        The type of the item. Always function_call.

        • "function_call"

      • id: Optional[str]

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

      • call_id: Optional[str]

        The ID of the function call.

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemFunctionCallOutput: …

      A function call output item in a Realtime conversation.

      • call_id: str

        The ID of the function call this output is for.

      • output: str

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

      • type: Literal["function_call_output"]

        The type of the item. Always function_call_output.

        • "function_call_output"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeMcpApprovalResponse: …

      A Realtime item responding to an MCP approval request.

      • id: str

        The unique ID of the approval response.

      • approval_request_id: str

        The ID of the approval request being answered.

      • approve: bool

        Whether the request was approved.

      • type: Literal["mcp_approval_response"]

        The type of the item. Always mcp_approval_response.

        • "mcp_approval_response"

      • reason: Optional[str]

        Optional reason for the decision.

    • class RealtimeMcpListTools: …

      A Realtime item listing tools available on an MCP server.

      • server_label: str

        The label of the MCP server.

      • tools: List[Tool]

        The tools available on the server.

        • input_schema: object

          The JSON schema describing the tool's input.

        • name: str

          The name of the tool.

        • annotations: Optional[object]

          Additional annotations about the tool.

        • description: Optional[str]

          The description of the tool.

      • type: Literal["mcp_list_tools"]

        The type of the item. Always mcp_list_tools.

        • "mcp_list_tools"

      • id: Optional[str]

        The unique ID of the list.

    • class RealtimeMcpToolCall: …

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

      • id: str

        The unique ID of the tool call.

      • arguments: str

        A JSON string of the arguments passed to the tool.

      • name: str

        The name of the tool that was run.

      • server_label: str

        The label of the MCP server running the tool.

      • type: Literal["mcp_call"]

        The type of the item. Always mcp_call.

        • "mcp_call"

      • approval_request_id: Optional[str]

        The ID of an associated approval request, if any.

      • error: Optional[Error]

        The error from the tool call, if any.

        • class RealtimeMcpProtocolError: …

          • code: int

          • message: str

          • type: Literal["protocol_error"]

            • "protocol_error"

        • class RealtimeMcpToolExecutionError: …

          • message: str

          • type: Literal["tool_execution_error"]

            • "tool_execution_error"

        • class RealtimeMcphttpError: …

          • code: int

          • message: str

          • type: Literal["http_error"]

            • "http_error"

      • output: Optional[str]

        The output from the tool call.

    • class RealtimeMcpApprovalRequest: …

      A Realtime item requesting human approval of a tool invocation.

      • id: str

        The unique ID of the approval request.

      • arguments: str

        A JSON string of arguments for the tool.

      • name: str

        The name of the tool to run.

      • server_label: str

        The label of the MCP server making the request.

      • type: Literal["mcp_approval_request"]

        The type of the item. Always mcp_approval_request.

        • "mcp_approval_request"

  • type: Literal["conversation.item.create"]

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

    • "conversation.item.create"

  • event_id: Optional[str]

    Optional client-generated ID used to identify this event.

  • previous_item_id: Optional[str]

    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.

  • event_id: str

    The unique ID of the server event.

  • item: ConversationItem

    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.

      • content: List[Content]

        The content of the message.

        • text: Optional[str]

          The text content.

        • type: Optional[Literal["input_text"]]

          The content type. Always input_text for system messages.

          • "input_text"

      • role: Literal["system"]

        The role of the message sender. Always system.

        • "system"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemUserMessage: …

      A user message item in a Realtime conversation.

      • content: List[Content]

        The content of the message.

        • audio: Optional[str]

          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.

        • detail: Optional[Literal["auto", "low", "high"]]

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

          • "auto"

          • "low"

          • "high"

        • image_url: Optional[str]

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

        • text: Optional[str]

          The text content (for input_text).

        • transcript: Optional[str]

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

        • type: Optional[Literal["input_text", "input_audio", "input_image"]]

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

          • "input_text"

          • "input_audio"

          • "input_image"

      • role: Literal["user"]

        The role of the message sender. Always user.

        • "user"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemAssistantMessage: …

      An assistant message item in a Realtime conversation.

      • content: List[Content]

        The content of the message.

        • audio: Optional[str]

          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.

        • text: Optional[str]

          The text content.

        • transcript: Optional[str]

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

        • type: Optional[Literal["output_text", "output_audio"]]

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

          • "output_text"

          • "output_audio"

      • role: Literal["assistant"]

        The role of the message sender. Always assistant.

        • "assistant"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemFunctionCall: …

      A function call item in a Realtime conversation.

      • arguments: str

        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}.

      • name: str

        The name of the function being called.

      • type: Literal["function_call"]

        The type of the item. Always function_call.

        • "function_call"

      • id: Optional[str]

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

      • call_id: Optional[str]

        The ID of the function call.

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemFunctionCallOutput: …

      A function call output item in a Realtime conversation.

      • call_id: str

        The ID of the function call this output is for.

      • output: str

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

      • type: Literal["function_call_output"]

        The type of the item. Always function_call_output.

        • "function_call_output"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeMcpApprovalResponse: …

      A Realtime item responding to an MCP approval request.

      • id: str

        The unique ID of the approval response.

      • approval_request_id: str

        The ID of the approval request being answered.

      • approve: bool

        Whether the request was approved.

      • type: Literal["mcp_approval_response"]

        The type of the item. Always mcp_approval_response.

        • "mcp_approval_response"

      • reason: Optional[str]

        Optional reason for the decision.

    • class RealtimeMcpListTools: …

      A Realtime item listing tools available on an MCP server.

      • server_label: str

        The label of the MCP server.

      • tools: List[Tool]

        The tools available on the server.

        • input_schema: object

          The JSON schema describing the tool's input.

        • name: str

          The name of the tool.

        • annotations: Optional[object]

          Additional annotations about the tool.

        • description: Optional[str]

          The description of the tool.

      • type: Literal["mcp_list_tools"]

        The type of the item. Always mcp_list_tools.

        • "mcp_list_tools"

      • id: Optional[str]

        The unique ID of the list.

    • class RealtimeMcpToolCall: …

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

      • id: str

        The unique ID of the tool call.

      • arguments: str

        A JSON string of the arguments passed to the tool.

      • name: str

        The name of the tool that was run.

      • server_label: str

        The label of the MCP server running the tool.

      • type: Literal["mcp_call"]

        The type of the item. Always mcp_call.

        • "mcp_call"

      • approval_request_id: Optional[str]

        The ID of an associated approval request, if any.

      • error: Optional[Error]

        The error from the tool call, if any.

        • class RealtimeMcpProtocolError: …

          • code: int

          • message: str

          • type: Literal["protocol_error"]

            • "protocol_error"

        • class RealtimeMcpToolExecutionError: …

          • message: str

          • type: Literal["tool_execution_error"]

            • "tool_execution_error"

        • class RealtimeMcphttpError: …

          • code: int

          • message: str

          • type: Literal["http_error"]

            • "http_error"

      • output: Optional[str]

        The output from the tool call.

    • class RealtimeMcpApprovalRequest: …

      A Realtime item requesting human approval of a tool invocation.

      • id: str

        The unique ID of the approval request.

      • arguments: str

        A JSON string of arguments for the tool.

      • name: str

        The name of the tool to run.

      • server_label: str

        The label of the MCP server making the request.

      • type: Literal["mcp_approval_request"]

        The type of the item. Always mcp_approval_request.

        • "mcp_approval_request"

  • type: Literal["conversation.item.created"]

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

    • "conversation.item.created"

  • previous_item_id: Optional[str]

    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.

  • item_id: str

    The ID of the item to delete.

  • type: Literal["conversation.item.delete"]

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

    • "conversation.item.delete"

  • event_id: Optional[str]

    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.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

    The ID of the item that was deleted.

  • type: Literal["conversation.item.deleted"]

    The event type, must be 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.

  • event_id: str

    The unique ID of the server event.

  • item: ConversationItem

    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.

      • content: List[Content]

        The content of the message.

        • text: Optional[str]

          The text content.

        • type: Optional[Literal["input_text"]]

          The content type. Always input_text for system messages.

          • "input_text"

      • role: Literal["system"]

        The role of the message sender. Always system.

        • "system"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemUserMessage: …

      A user message item in a Realtime conversation.

      • content: List[Content]

        The content of the message.

        • audio: Optional[str]

          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.

        • detail: Optional[Literal["auto", "low", "high"]]

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

          • "auto"

          • "low"

          • "high"

        • image_url: Optional[str]

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

        • text: Optional[str]

          The text content (for input_text).

        • transcript: Optional[str]

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

        • type: Optional[Literal["input_text", "input_audio", "input_image"]]

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

          • "input_text"

          • "input_audio"

          • "input_image"

      • role: Literal["user"]

        The role of the message sender. Always user.

        • "user"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemAssistantMessage: …

      An assistant message item in a Realtime conversation.

      • content: List[Content]

        The content of the message.

        • audio: Optional[str]

          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.

        • text: Optional[str]

          The text content.

        • transcript: Optional[str]

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

        • type: Optional[Literal["output_text", "output_audio"]]

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

          • "output_text"

          • "output_audio"

      • role: Literal["assistant"]

        The role of the message sender. Always assistant.

        • "assistant"

      • type: Literal["message"]

        The type of the item. Always message.

        • "message"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemFunctionCall: …

      A function call item in a Realtime conversation.

      • arguments: str

        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}.

      • name: str

        The name of the function being called.

      • type: Literal["function_call"]

        The type of the item. Always function_call.

        • "function_call"

      • id: Optional[str]

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

      • call_id: Optional[str]

        The ID of the function call.

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeConversationItemFunctionCallOutput: …

      A function call output item in a Realtime conversation.

      • call_id: str

        The ID of the function call this output is for.

      • output: str

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

      • type: Literal["function_call_output"]

        The type of the item. Always function_call_output.

        • "function_call_output"

      • id: Optional[str]

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

      • object: Optional[Literal["realtime.item"]]

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

        • "realtime.item"

      • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

        • "completed"

        • "incomplete"

        • "in_progress"

    • class RealtimeMcpApprovalResponse: …

      A Realtime item responding to an MCP approval request.

      • id: str

        The unique ID of the approval response.

      • approval_request_id: str

        The ID of the approval request being answered.

      • approve: bool

        Whether the request was approved.

      • type: Literal["mcp_approval_response"]

        The type of the item. Always mcp_approval_response.

        • "mcp_approval_response"

      • reason: Optional[str]

        Optional reason for the decision.

    • class RealtimeMcpListTools: …

      A Realtime item listing tools available on an MCP server.

      • server_label: str

        The label of the MCP server.

      • tools: List[Tool]

        The tools available on the server.

        • input_schema: object

          The JSON schema describing the tool's input.

        • name: str

          The name of the tool.

        • annotations: Optional[object]

          Additional annotations about the tool.

        • description: Optional[str]

          The description of the tool.

      • type: Literal["mcp_list_tools"]

        The type of the item. Always mcp_list_tools.

        • "mcp_list_tools"

      • id: Optional[str]

        The unique ID of the list.

    • class RealtimeMcpToolCall: …

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

      • id: str

        The unique ID of the tool call.

      • arguments: str

        A JSON string of the arguments passed to the tool.

      • name: str

        The name of the tool that was run.

      • server_label: str

        The label of the MCP server running the tool.

      • type: Literal["mcp_call"]

        The type of the item. Always mcp_call.

        • "mcp_call"

      • approval_request_id: Optional[str]

        The ID of an associated approval request, if any.

      • error: Optional[Error]

        The error from the tool call, if any.

        • class RealtimeMcpProtocolError: …

          • code: int

          • message: str

          • type: Literal["protocol_error"]

            • "protocol_error"

        • class RealtimeMcpToolExecutionError: …

          • message: str

          • type: Literal["tool_execution_error"]

            • "tool_execution_error"

        • class RealtimeMcphttpError: …

          • code: int

          • message: str

          • type: Literal["http_error"]

            • "http_error"

      • output: Optional[str]

        The output from the tool call.

    • class RealtimeMcpApprovalRequest: …

      A Realtime item requesting human approval of a tool invocation.

      • id: str

        The unique ID of the approval request.

      • arguments: str

        A JSON string of arguments for the tool.

      • name: str

        The name of the tool to run.

      • server_label: str

        The label of the MCP server making the request.

      • type: Literal["mcp_approval_request"]

        The type of the item. Always mcp_approval_request.

        • "mcp_approval_request"

  • type: Literal["conversation.item.done"]

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

    • "conversation.item.done"

  • previous_item_id: Optional[str]

    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.

  • content_index: int

    The index of the content part containing the audio.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

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

  • transcript: str

    The transcribed text.

  • type: Literal["conversation.item.input_audio_transcription.completed"]

    The event type, must be 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 UsageTranscriptTextUsageTokens: …

      Usage statistics for models billed by token usage.

      • input_tokens: int

        Number of input tokens billed for this request.

      • output_tokens: int

        Number of output tokens generated.

      • total_tokens: int

        Total number of tokens used (input + output).

      • type: Literal["tokens"]

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

        • "tokens"

      • input_token_details: Optional[UsageTranscriptTextUsageTokensInputTokenDetails]

        Details about the input tokens billed for this request.

        • audio_tokens: Optional[int]

          Number of audio tokens billed for this request.

        • text_tokens: Optional[int]

          Number of text tokens billed for this request.

    • class UsageTranscriptTextUsageDuration: …

      Usage statistics for models billed by audio input duration.

      • seconds: float

        Duration of the input audio in seconds.

      • type: Literal["duration"]

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

        • "duration"

  • logprobs: Optional[List[LogProbProperties]]

    The log probabilities of the transcription.

    • token: str

      The token that was used to generate the log probability.

    • bytes: List[int]

      The bytes that were used to generate the log probability.

    • logprob: float

      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.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

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

  • type: Literal["conversation.item.input_audio_transcription.delta"]

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

    • "conversation.item.input_audio_transcription.delta"

  • content_index: Optional[int]

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

  • delta: Optional[str]

    The text delta.

  • logprobs: Optional[List[LogProbProperties]]

    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.

    • token: str

      The token that was used to generate the log probability.

    • bytes: List[int]

      The bytes that were used to generate the log probability.

    • logprob: float

      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.

  • content_index: int

    The index of the content part containing the audio.

  • error: Error

    Details of the transcription error.

    • code: Optional[str]

      Error code, if any.

    • message: Optional[str]

      A human-readable error message.

    • param: Optional[str]

      Parameter related to the error, if any.

    • type: Optional[str]

      The type of error.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

    The ID of the user message item.

  • type: Literal["conversation.item.input_audio_transcription.failed"]

    The event type, must be 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.

  • id: str

    The segment identifier.

  • content_index: int

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

  • end: float

    End time of the segment in seconds.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

    The ID of the item containing the input audio content.

  • speaker: str

    The detected speaker label for this segment.

  • start: float

    Start time of the segment in seconds.

  • text: str

    The text for this segment.

  • type: Literal["conversation.item.input_audio_transcription.segment"]

    The event type, must be 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.

  • item_id: str

    The ID of the item to retrieve.

  • type: Literal["conversation.item.retrieve"]

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

    • "conversation.item.retrieve"

  • event_id: Optional[str]

    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.

  • audio_end_ms: int

    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.

  • content_index: int

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

  • item_id: str

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

  • type: Literal["conversation.item.truncate"]

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

    • "conversation.item.truncate"

  • event_id: Optional[str]

    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.

  • audio_end_ms: int

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

  • content_index: int

    The index of the content part that was truncated.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

    The ID of the assistant message item that was truncated.

  • type: Literal["conversation.item.truncated"]

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

    • "conversation.item.truncated"

Conversation Item With Reference

• class ConversationItemWithReference: …

  The item to add to the conversation.

  • id: Optional[str]

    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.

  • arguments: Optional[str]

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

  • call_id: Optional[str]

    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.

  • content: Optional[List[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.

    • id: Optional[str]

      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.

    • audio: Optional[str]

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

    • text: Optional[str]

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

    • transcript: Optional[str]

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

    • type: Optional[Literal["input_text", "input_audio", "item_reference", "text"]]

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

      • "input_text"

      • "input_audio"

      • "item_reference"

      • "text"

  • name: Optional[str]

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

  • object: Optional[Literal["realtime.item"]]

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

    • "realtime.item"

  • output: Optional[str]

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

  • role: Optional[Literal["user", "assistant", "system"]]

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

    • "user"

    • "assistant"

    • "system"

  • status: Optional[Literal["completed", "incomplete", "in_progress"]]

    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"

    • "incomplete"

    • "in_progress"

  • type: Optional[Literal["message", "function_call", "function_call_output", "item_reference"]]

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

    • "message"

    • "function_call"

    • "function_call_output"

    • "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.

  • audio: str

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

  • type: Literal["input_audio_buffer.append"]

    The event type, must be input_audio_buffer.append.

    • "input_audio_buffer.append"

  • event_id: Optional[str]

    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.

  • type: Literal["input_audio_buffer.clear"]

    The event type, must be input_audio_buffer.clear.

    • "input_audio_buffer.clear"

  • event_id: Optional[str]

    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.

  • event_id: str

    The unique ID of the server event.

  • type: Literal["input_audio_buffer.cleared"]

    The event type, must be 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.

  • type: Literal["input_audio_buffer.commit"]

    The event type, must be input_audio_buffer.commit.

    • "input_audio_buffer.commit"

  • event_id: Optional[str]

    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.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

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

  • type: Literal["input_audio_buffer.committed"]

    The event type, must be input_audio_buffer.committed.

    • "input_audio_buffer.committed"

  • previous_item_id: Optional[str]

    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.

  • event: str

    The telephone keypad that was pressed by the user.

  • received_at: int

    UTC Unix Timestamp when DTMF Event was received by server.

  • type: Literal["input_audio_buffer.dtmf_event_received"]

    The event type, must be 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).

  • audio_start_ms: int

    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.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

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

  • type: Literal["input_audio_buffer.speech_started"]

    The event type, must be 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.

  • audio_end_ms: int

    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.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

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

  • type: Literal["input_audio_buffer.speech_stopped"]

    The event type, must be 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.

  • audio_end_ms: int

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

  • audio_start_ms: int

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

  • event_id: str

    The unique ID of the server event.

  • item_id: str

    The ID of the item associated with this segment.

  • type: Literal["input_audio_buffer.timeout_triggered"]

    The event type, must be input_audio_buffer.timeout_triggered.

    • "input_audio_buffer.timeout_triggered"

Log Prob Properties

• class LogProbProperties: …

  A log probability object.

  • token: str

    The token that was used to generate the log probability.

  • bytes: List[int]

    The bytes that were used to generate the log probability.

  • logprob: float

    The log probability of the token.

Mcp List Tools Completed

• class McpListToolsCompleted: …

  Returned when listing MCP tools has completed for an item.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

    The ID of the MCP list tools item.

  • type: Literal["mcp_list_tools.completed"]

    The event type, must be mcp_list_tools.completed.

    • "mcp_list_tools.completed"

Mcp List Tools Failed

• class McpListToolsFailed: …

  Returned when listing MCP tools has failed for an item.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

    The ID of the MCP list tools item.

  • type: Literal["mcp_list_tools.failed"]

    The event type, must be 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.

  • event_id: str

    The unique ID of the server event.

  • item_id: str

    The ID of the MCP list tools item.

  • type: Literal["mcp_list_tools.in_progress"]

    The event type, must be mcp_list_tools.in_progress.

    • "mcp_list_tools.in_progress"

Noise Reduction Type

• Literal["near_field", "far_field"]

  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"

  • "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.

  • type: Literal["output_audio_buffer.clear"]

    The event type, must be output_audio_buffer.clear.

    • "output_audio_buffer.clear"

  • event_id: Optional[str]

    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.

  • event_id: str

    The unique ID of the server event.

  • rate_limits: List[RateLimit]

    List of rate limit information.

    • limit: Optional[int]

      The maximum allowed value for the rate limit.

    • name: Optional[Literal["requests", "tokens"]]

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

      • "requests"

      • "tokens"

    • remaining: Optional[int]

      The remaining value before the limit is reached.

    • reset_seconds: Optional[float]

      Seconds until the rate limit resets.

  • type: Literal["rate_limits.updated"]

    The event type, must be rate_limits.updated.

    • "rate_limits.updated"

Realtime Audio Config

• class RealtimeAudioConfig: …

  Configuration for input and output audio.

  • input: Optional[RealtimeAudioConfigInput]

    • format: Optional[RealtimeAudioFormats]

      The format of the input audio.

      • class AudioPCM: …

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

        • rate: Optional[Literal[24000]]

          The sample rate of the audio. Always 24000.

          • 24000

        • type: Optional[Literal["audio/pcm"]]

          The audio format. Always audio/pcm.

          • "audio/pcm"

      • class AudioPCMU: …

        The G.711 μ-law format.

        • type: Optional[Literal["audio/pcmu"]]

          The audio format. Always audio/pcmu.

          • "audio/pcmu"

      • class AudioPCMA: …

        The G.711 A-law format.

        • type: Optional[Literal["audio/pcma"]]

          The audio format. Always audio/pcma.

          • "audio/pcma"

    • noise_reduction: Optional[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.

      • type: Optional[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"

        • "far_field"

    • transcription: Optional[AudioTranscription]

      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.

      • delay: Optional[Literal["minimal", "low", "medium", 2 more]]

        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"

        • "low"

        • "medium"

        • "high"

        • "xhigh"

      • language: Optional[str]

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

      • model: Optional[Union[str, Literal["whisper-1", "gpt-4o-mini-transcribe", "gpt-4o-mini-transcribe-2025-12-15", 3 more], null]]

        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.

        • str

        • Literal["whisper-1", "gpt-4o-mini-transcribe", "gpt-4o-mini-transcribe-2025-12-15", 3 more]

          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"

          • "gpt-4o-mini-transcribe"

          • "gpt-4o-mini-transcribe-2025-12-15"

          • "gpt-4o-transcribe"

          • "gpt-4o-transcribe-diarize"

          • "gpt-realtime-whisper"

      • prompt: Optional[str]

        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.

    • turn_detection: Optional[RealtimeAudioInputTurnDetection]

      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.

        • type: Literal["server_vad"]

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

          • "server_vad"

        • create_response: Optional[bool]

          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.

        • idle_timeout_ms: Optional[int]

          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.

        • interrupt_response: Optional[bool]

          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.

        • prefix_padding_ms: Optional[int]

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

        • silence_duration_ms: Optional[int]

          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.

        • threshold: Optional[float]

          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.

        • type: Literal["semantic_vad"]

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

          • "semantic_vad"

        • create_response: Optional[bool]

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

        • eagerness: Optional[Literal["low", "medium", "high", "auto"]]

          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"

          • "medium"

          • "high"

          • "auto"

        • interrupt_response: Optional[bool]

          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.

  • output: Optional[RealtimeAudioConfigOutput]

    • format: Optional[RealtimeAudioFormats]

      The format of the output audio.

    • speed: Optional[float]

      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.

    • voice: Optional[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.

      • str

      • Literal["alloy", "ash", "ballad", 7 more]

        • "alloy"

        • "ash"

        • "ballad"

        • "coral"

        • "echo"

        • "sage"

        • "shimmer"

        • "verse"

        • "marin"

        • "cedar"

      • class VoiceID: …

        Custom voice reference.

        • id: str

          The custom voice ID, e.g. voice_1234.

Realtime Audio Config Input

• class RealtimeAudioConfigInput: …

  • format: Optional[RealtimeAudioFormats]

    The format of the input audio.

    • class AudioPCM: …

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

      • rate: Optional[Literal[24000]]

        The sample rate of the audio. Always 24000.

        • 24000

      • type: Optional[Literal["audio/pcm"]]

        The audio format. Always audio/pcm.

        • "audio/pcm"

    • class AudioPCMU: …

      The G.711 μ-law format.

      • type: Optional[Literal["audio/pcmu"]]

        The audio format. Always audio/pcmu.

        • "audio/pcmu"

    • class AudioPCMA: …

      The G.711 A-law format.

      • type: Optional[Literal["audio/pcma"]]

        The audio format. Always audio/pcma.

        • "audio/pcma"

  • noise_reduction: Optional[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.

    • type: Optional[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"

      • "far_field"

  • transcription: Optional[AudioTranscription]

    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.

    • delay: Optional[Literal["minimal", "low", "medium", 2 more]]

      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"

      • "low"

      • "medium"

      • "high"

      • "xhigh"

    • language: Optional[str]

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

    • model: Optional[Union[str, Literal["whisper-1", "gpt-4o-mini-transcribe", "gpt-4o-mini-transcribe-2025-12-15", 3 more], null]]

      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.

      • str

      • Literal["whisper-1", "gpt-4o-mini-transcribe", "gpt-4o-mini-transcribe-2025-12-15", 3 more]

        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"

        • "gpt-4o-mini-transcribe"

        • "gpt-4o-mini-transcribe-2025-12-15"

        • "gpt-4o-transcribe"

        • "gpt-4o-transcribe-diarize"

        • "gpt-realtime-whisper"

    • prompt: Optional[str]

      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.

  • turn_detection: Optional[RealtimeAudioInputTurnDetection]

    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.

      • type: Literal["server_vad"]

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

        • "server_vad"

      • create_response: Optional[bool]

        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.

      • idle_timeout_ms: Optional[int]

        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.

      • interrupt_response: Optional[bool]

        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.

      • prefix_padding_ms: Optional[int]

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

      • silence_duration_ms: Optional[int]

        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.

      • threshold: Optional[float]

        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.

      • type: Literal["semantic_vad"]

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

        • "semantic_vad"

      • create_response: Optional[bool]

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

      • eagerness: Optional[Literal["low", "medium", "high", "auto"]]

        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"

        • "medium"

        • "high"

        • "auto"

      • interrupt_response: Optional[bool]

        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: …

  • format: Optional[RealtimeAudioFormats]

    The format of the output audio.

    • class AudioPCM: …

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

      • rate: Optional[Literal[24000]]

        The sample rate of the audio. Always 24000.

        • 24000

      • type: Optional[Literal["audio/pcm"]]

        The audio format. Always audio/pcm.

        • "audio/pcm"

    • class AudioPCMU: …

      The G.711 μ-law format.

      • type: Optional[Literal["audio/pcmu"]]

        The audio format. Always audio/pcmu.

        • "audio/pcmu"

    • class AudioPCMA: …

      The G.711 A-law format.

      • type: Optional[Literal["audio/pcma"]]

        The audio format. Always audio/pcma.

        • "audio/pcma"

  • speed: Optional[float]

    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.

  • voice: Optional[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.

    • str

    • Literal["alloy", "ash", "ballad", 7 more]

      • "alloy"

      • "ash"

      • "ballad"

      • "coral"

      • "echo"

      • "sage"

      • "shimmer"

      • "verse"

      • "marin"

      • "cedar"

    • class VoiceID: …

      Custom voice reference.

      • id: str

        The custom voice ID, e.g. voice_1234.

Realtime Audio Formats

• RealtimeAudioFormats

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

  • class AudioPCM: …

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

    • rate: Optional[Literal[24000]]

      The sample rate of the audio. Always 24000.

      • 24000

    • type: Optional[Literal["audio/pcm"]]

      The audio format. Always audio/pcm.

      • "audio/pcm"

  • class AudioPCMU: …

    The G.711 μ-law format.

    • type: Optional[Literal["audio/pcmu"]]

      The audio format. Always audio/pcmu.

      • "audio/pcmu"

  • class AudioPCMA: …

    The G.711 A-law format.

    • type: Optional[Literal["audio/pcma"]]

      The audio format. Always audio/pcma.

      • "audio/pcma"

Realtime Audio Input Turn Detection

• Optional[RealtimeAudioInputTurnDetection]

  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.

    • type: Literal["server_vad"]

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

      • "server_vad"

    • create_response: Optional[bool]

      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.

    • idle_timeout_ms: Optional[int]

      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.

    • interrupt_response: Optional[bool]

      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.

    • prefix_padding_ms: Optional[int]

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

    • silence_duration_ms: Optional[int]

      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.

    • threshold: Optional[float]

      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.

    • type: Literal["semantic_vad"]

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

      • "semantic_vad"

    • create_response: Optional[bool]

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

    • eagerness: Optional[Literal["low", "medium", "high", "auto"]]

      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"

      • "medium"

      • "high"

      • "auto"

    • interrupt_response: Optional[bool]

      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

• RealtimeClientEvent

  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.

    • item: ConversationItem

      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.

        • content: List[Content]

          The content of the message.

          • text: Optional[str]

            The text content.

          • type: Optional[Literal["input_text"]]

            The content type. Always input_text for system messages.

            • "input_text"

        • role: Literal["system"]

          The role of the message sender. Always system.

          • "system"

        • type: Literal["message"]

          The type of the item. Always message.

          • "message"

        • id: Optional[str]

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

        • object: Optional[Literal["realtime.item"]]

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

          • "realtime.item"

        • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

          • "completed"

          • "incomplete"

          • "in_progress"

      • class RealtimeConversationItemUserMessage: …

        A user message item in a Realtime conversation.

        • content: List[Content]

          The content of the message.

          • audio: Optional[str]

            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.

          • detail: Optional[Literal["auto", "low", "high"]]

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

            • "auto"

            • "low"

            • "high"

          • image_url: Optional[str]

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

          • text: Optional[str]

            The text content (for input_text).

          • transcript: Optional[str]

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

          • type: Optional[Literal["input_text", "input_audio", "input_image"]]

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

            • "input_text"

            • "input_audio"

            • "input_image"

        • role: Literal["user"]

          The role of the message sender. Always user.

          • "user"

        • type: Literal["message"]

          The type of the item. Always message.

          • "message"

        • id: Optional[str]

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

        • object: Optional[Literal["realtime.item"]]

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

          • "realtime.item"

        • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

          • "completed"

          • "incomplete"

          • "in_progress"

      • class RealtimeConversationItemAssistantMessage: …

        An assistant message item in a Realtime conversation.

        • content: List[Content]

          The content of the message.

          • audio: Optional[str]

            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.

          • text: Optional[str]

            The text content.

          • transcript: Optional[str]

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

          • type: Optional[Literal["output_text", "output_audio"]]

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

            • "output_text"

            • "output_audio"

        • role: Literal["assistant"]

          The role of the message sender. Always assistant.

          • "assistant"

        • type: Literal["message"]

          The type of the item. Always message.

          • "message"

        • id: Optional[str]

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

        • object: Optional[Literal["realtime.item"]]

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

          • "realtime.item"

        • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

          • "completed"

          • "incomplete"

          • "in_progress"

      • class RealtimeConversationItemFunctionCall: …

        A function call item in a Realtime conversation.

        • arguments: str

          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}.

        • name: str

          The name of the function being called.

        • type: Literal["function_call"]

          The type of the item. Always function_call.

          • "function_call"

        • id: Optional[str]

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

        • call_id: Optional[str]

          The ID of the function call.

        • object: Optional[Literal["realtime.item"]]

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

          • "realtime.item"

        • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

          • "completed"

          • "incomplete"

          • "in_progress"

      • class RealtimeConversationItemFunctionCallOutput: …

        A function call output item in a Realtime conversation.

        • call_id: str

          The ID of the function call this output is for.

        • output: str

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

        • type: Literal["function_call_output"]

          The type of the item. Always function_call_output.

          • "function_call_output"

        • id: Optional[str]

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

        • object: Optional[Literal["realtime.item"]]

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

          • "realtime.item"

        • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

          • "completed"

          • "incomplete"

          • "in_progress"

      • class RealtimeMcpApprovalResponse: …

        A Realtime item responding to an MCP approval request.

        • id: str

          The unique ID of the approval response.

        • approval_request_id: str

          The ID of the approval request being answered.

        • approve: bool

          Whether the request was approved.

        • type: Literal["mcp_approval_response"]

          The type of the item. Always mcp_approval_response.

          • "mcp_approval_response"

        • reason: Optional[str]

          Optional reason for the decision.

      • class RealtimeMcpListTools: …

        A Realtime item listing tools available on an MCP server.

        • server_label: str

          The label of the MCP server.

        • tools: List[Tool]

          The tools available on the server.

          • input_schema: object

            The JSON schema describing the tool's input.

          • name: str

            The name of the tool.

          • annotations: Optional[object]

            Additional annotations about the tool.

          • description: Optional[str]

            The description of the tool.

        • type: Literal["mcp_list_tools"]

          The type of the item. Always mcp_list_tools.

          • "mcp_list_tools"

        • id: Optional[str]

          The unique ID of the list.

      • class RealtimeMcpToolCall: …

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

        • id: str

          The unique ID of the tool call.

        • arguments: str

          A JSON string of the arguments passed to the tool.

        • name: str

          The name of the tool that was run.

        • server_label: str

          The label of the MCP server running the tool.

        • type: Literal["mcp_call"]

          The type of the item. Always mcp_call.

          • "mcp_call"

        • approval_request_id: Optional[str]

          The ID of an associated approval request, if any.

        • error: Optional[Error]

          The error from the tool call, if any.

          • class RealtimeMcpProtocolError: …

            • code: int

            • message: str

            • type: Literal["protocol_error"]

              • "protocol_error"

          • class RealtimeMcpToolExecutionError: …

            • message: str

            • type: Literal["tool_execution_error"]

              • "tool_execution_error"

          • class RealtimeMcphttpError: …

            • code: int

            • message: str

            • type: Literal["http_error"]

              • "http_error"

        • output: Optional[str]

          The output from the tool call.

      • class RealtimeMcpApprovalRequest: …

        A Realtime item requesting human approval of a tool invocation.

        • id: str

          The unique ID of the approval request.

        • arguments: str

          A JSON string of arguments for the tool.

        • name: str

          The name of the tool to run.

        • server_label: str

          The label of the MCP server making the request.

        • type: Literal["mcp_approval_request"]

          The type of the item. Always mcp_approval_request.

          • "mcp_approval_request"

    • type: Literal["conversation.item.create"]

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

      • "conversation.item.create"

    • event_id: Optional[str]

      Optional client-generated ID used to identify this event.

    • previous_item_id: Optional[str]

      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.

    • item_id: str

      The ID of the item to delete.

    • type: Literal["conversation.item.delete"]

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

      • "conversation.item.delete"

    • event_id: Optional[str]

      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.

    • item_id: str

      The ID of the item to retrieve.

    • type: Literal["conversation.item.retrieve"]

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

      • "conversation.item.retrieve"

    • event_id: Optional[str]

      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.

    • audio_end_ms: int

      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.

    • content_index: int

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

    • item_id: str

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

    • type: Literal["conversation.item.truncate"]

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

      • "conversation.item.truncate"

    • event_id: Optional[str]

      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.

    • audio: str

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

    • type: Literal["input_audio_buffer.append"]

      The event type, must be input_audio_buffer.append.

      • "input_audio_buffer.append"

    • event_id: Optional[str]

      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.

    • type: Literal["input_audio_buffer.clear"]

      The event type, must be input_audio_buffer.clear.

      • "input_audio_buffer.clear"

    • event_id: Optional[str]

      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.

    • type: Literal["output_audio_buffer.clear"]

      The event type, must be output_audio_buffer.clear.

      • "output_audio_buffer.clear"

    • event_id: Optional[str]

      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.

    • type: Literal["input_audio_buffer.commit"]

      The event type, must be input_audio_buffer.commit.

      • "input_audio_buffer.commit"

    • event_id: Optional[str]

      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.

    • type: Literal["response.cancel"]

      The event type, must be response.cancel.

      • "response.cancel"

    • event_id: Optional[str]

      Optional client-generated ID used to identify this event.

    • response_id: Optional[str]

      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.

    • type: Literal["response.create"]

      The event type, must be response.create.

      • "response.create"

    • event_id: Optional[str]

      Optional client-generated ID used to identify this event.

    • response: Optional[RealtimeResponseCreateParams]

      Create a new Realtime response with these parameters

      • audio: Optional[RealtimeResponseCreateAudioOutput]

        Configuration for audio input and output.

        • output: Optional[Output]

          • format: Optional[RealtimeAudioFormats]

            The format of the output audio.

            • class AudioPCM: …

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

              • rate: Optional[Literal[24000]]

                The sample rate of the audio. Always 24000.

                • 24000

              • type: Optional[Literal["audio/pcm"]]

                The audio format. Always audio/pcm.

                • "audio/pcm"

            • class AudioPCMU: …

              The G.711 μ-law format.

              • type: Optional[Literal["audio/pcmu"]]

                The audio format. Always audio/pcmu.

                • "audio/pcmu"

            • class AudioPCMA: …

              The G.711 A-law format.

              • type: Optional[Literal["audio/pcma"]]

                The audio format. Always audio/pcma.

                • "audio/pcma"

          • voice: Optional[OutputVoice]

            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.

            • str

            • Literal["alloy", "ash", "ballad", 7 more]

              • "alloy"

              • "ash"

              • "ballad"

              • "coral"

              • "echo"

              • "sage"

              • "shimmer"

              • "verse"

              • "marin"

              • "cedar"

            • class OutputVoiceID: …

              Custom voice reference.

              • id: str

                The custom voice ID, e.g. voice_1234.

      • conversation: Optional[Union[str, Literal["auto", "none"], null]]

        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.

        • str

        • Literal["auto", "none"]

          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"

          • "none"

      • input: Optional[List[ConversationItem]]

        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.

      • instructions: Optional[str]

        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.

      • max_output_tokens: Optional[Union[int, Literal["inf"], null]]

        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.

        • int

        • Literal["inf"]

          • "inf"

      • metadata: Optional[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.

      • output_modalities: Optional[List[Literal["text", "audio"]]]

        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"

        • "audio"

      • parallel_tool_calls: Optional[bool]

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

      • prompt: Optional[ResponsePrompt]

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

        • id: str

          The unique identifier of the prompt template to use.

        • variables: Optional[Dict[str, 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.

          • str

          • class ResponseInputText: …

            A text input to the model.

            • text: str

              The text input to the model.

            • type: Literal["input_text"]

              The type of the input item. Always input_text.

              • "input_text"

          • class ResponseInputImage: …

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

            • detail: Literal["low", "high", "auto", "original"]

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

              • "low"

              • "high"

              • "auto"

              • "original"

            • type: Literal["input_image"]

              The type of the input item. Always input_image.

              • "input_image"

            • file_id: Optional[str]

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

            • image_url: Optional[str]

              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.

            • type: Literal["input_file"]

              The type of the input item. Always input_file.

              • "input_file"

            • detail: Optional[Literal["low", "high"]]

              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"

              • "high"

            • file_data: Optional[str]

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

            • file_id: Optional[str]

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

            • file_url: Optional[str]

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

            • filename: Optional[str]

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

        • version: Optional[str]

          Optional version of the prompt template.

      • reasoning: Optional[RealtimeReasoning]

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

        • effort: Optional[RealtimeReasoningEffort]

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

          • "minimal"

          • "low"

          • "medium"

          • "high"

          • "xhigh"

      • tool_choice: Optional[ToolChoice]

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

        • Literal["none", "auto", "required"]

          • "none"

          • "auto"

          • "required"

        • class ToolChoiceFunction: …

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

          • name: str

            The name of the function to call.

          • type: Literal["function"]

            For function calling, the type is always function.

            • "function"

        • class ToolChoiceMcp: …

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

          • server_label: str

            The label of the MCP server to use.

          • type: Literal["mcp"]

            For MCP tools, the type is always mcp.

            • "mcp"

          • name: Optional[str]

            The name of the tool to call on the server.

      • tools: Optional[List[Tool]]

        Tools available to the model.

        • class RealtimeFunctionTool: …

          • description: Optional[str]

            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).

          • name: Optional[str]

            The name of the function.

          • parameters: Optional[object]

            Parameters of the function in JSON Schema.

          • type: Optional[Literal["function"]]

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

            • "function"

        • class RealtimeResponseCreateMcpTool: …

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

          • server_label: str

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

          • type: Literal["mcp"]

            The type of the MCP tool. Always mcp.

            • "mcp"

          • allowed_tools: Optional[AllowedTools]

            List of allowed tool names or a filter object.

            • List[str]

              A string array of allowed tool names

            • class AllowedToolsMcpToolFilter: …

              A filter object to specify which tools are allowed.

              • read_only: Optional[bool]

                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.

              • tool_names: Optional[List[str]]

                List of allowed tool names.

          • authorization: Optional[str]

            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.

          • connector_id: Optional[Literal["connector_dropbox", "connector_gmail", "connector_googlecalendar", 5 more]]

            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_gmail"

            • "connector_googlecalendar"

            • "connector_googledrive"

            • "connector_microsoftteams"

            • "connector_outlookcalendar"

            • "connector_outlookemail"

            • "connector_sharepoint"

          • defer_loading: Optional[bool]

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

          • headers: Optional[Dict[str, str]]

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

          • require_approval: Optional[RequireApproval]

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

            • class RequireApprovalMcpToolApprovalFilter: …

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

              • always: Optional[RequireApprovalMcpToolApprovalFilterAlways]

                A filter object to specify which tools are allowed.

                • read_only: Optional[bool]

                  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.

                • tool_names: Optional[List[str]]

                  List of allowed tool names.

              • never: Optional[RequireApprovalMcpToolApprovalFilterNever]

                A filter object to specify which tools are allowed.

                • read_only: Optional[bool]

                  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.

                • tool_names: Optional[List[str]]

                  List of allowed tool names.

            • Literal["always", "never"]

              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"

              • "never"

          • server_description: Optional[str]

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

          • server_url: Optional[str]

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

          • tunnel_id: Optional[str]

            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.

        • type: Literal["realtime"]

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

          • "realtime"

        • audio: Optional[RealtimeAudioConfig]

          Configuration for input and output audio.

          • input: Optional[RealtimeAudioConfigInput]

            • format: Optional[RealtimeAudioFormats]

              The format of the input audio.

            • noise_reduction: Optional[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.

              • type: Optional[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"

                • "far_field"

            • transcription: Optional[AudioTranscription]

              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.

              • delay: Optional[Literal["minimal", "low", "medium", 2 more]]

                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"

                • "low"

                • "medium"

                • "high"

                • "xhigh"

              • language: Optional[str]

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

              • model: Optional[Union[str, Literal["whisper-1", "gpt-4o-mini-transcribe", "gpt-4o-mini-transcribe-2025-12-15", 3 more], null]]

                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.

                • str

                • Literal["whisper-1", "gpt-4o-mini-transcribe", "gpt-4o-mini-transcribe-2025-12-15", 3 more]

                  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"

                  • "gpt-4o-mini-transcribe"

                  • "gpt-4o-mini-transcribe-2025-12-15"

                  • "gpt-4o-transcribe"

                  • "gpt-4o-transcribe-diarize"

                  • "gpt-realtime-whisper"

              • prompt: Optional[str]

                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.

            • turn_detection: Optional[RealtimeAudioInputTurnDetection]

              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.

                • type: Literal["server_vad"]

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

                  • "server_vad"

                • create_response: Optional[bool]

                  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.

                • idle_timeout_ms: Optional[int]

                  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.

                • interrupt_response: Optional[bool]

                  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.

                • prefix_padding_ms: Optional[int]

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

                • silence_duration_ms: Optional[int]

                  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.

                • threshold: Optional[float]

                  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.

                • type: Literal["semantic_vad"]

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

                  • "semantic_vad"

                • create_response: Optional[bool]

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

                • eagerness: Optional[Literal["low", "medium", "high", "auto"]]

                  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"

                  • "medium"

                  • "high"

                  • "auto"

                • interrupt_response: Optional[bool]

                  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.

          • output: Optional[RealtimeAudioConfigOutput]

            • format: Optional[RealtimeAudioFormats]

              The format of the output audio.

            • speed: Optional[float]

              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.

            • voice: Optional[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.

              • str

              • Literal["alloy", "ash", "ballad", 7 more]

                • "alloy"

                • "ash"

                • "ballad"

                • "coral"

                • "echo"

                • "sage"

                • "shimmer"

                • "verse"

                • "marin"

                • "cedar"

              • class VoiceID: …

                Custom voice reference.

                • id: str

                  The custom voice ID, e.g. voice_1234.

        • include: Optional[List[Literal["item.input_audio_transcription.logprobs"]]]

          Additional fields to include in server outputs.

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

          • "item.input_audio_transcription.logprobs"

        • instructions: Optional[str]

          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.

        • max_output_tokens: Optional[Union[int, Literal["inf"], null]]

          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.

          • int

          • Literal["inf"]

            • "inf"

        • model: Optional[Union[str, Literal["gpt-realtime", "gpt-realtime-1.5", "gpt-realtime-2", 14 more], null]]

          The Realtime model used for this session.

          • str

          • Literal["gpt-realtime", "gpt-realtime-1.5", "gpt-realtime-2", 14 more]

            The Realtime model used for this session.

            • "gpt-realtime"

            • "gpt-realtime-1.5"

            • "gpt-realtime-2"

            • "gpt-realtime-2025-08-28"

            • "gpt-4o-realtime-preview"

            • "gpt-4o-realtime-preview-2024-10-01"

            • "gpt-4o-realtime-preview-2024-12-17"

            • "gpt-4o-realtime-preview-2025-06-03"

            • "gpt-4o-mini-realtime-preview"

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

            • "gpt-realtime-mini"

            • "gpt-realtime-mini-2025-10-06"

            • "gpt-realtime-mini-2025-12-15"

            • "gpt-audio-1.5"

            • "gpt-audio-mini"

            • "gpt-audio-mini-2025-10-06"

            • "gpt-audio-mini-2025-12-15"

        • output_modalities: Optional[List[Literal["text", "audio"]]]

          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"

          • "audio"

        • parallel_tool_calls: Optional[bool]

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

        • prompt: Optional[ResponsePrompt]

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

        • reasoning: Optional[RealtimeReasoning]

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

        • tool_choice: Optional[RealtimeToolChoiceConfig]

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

          • Literal["none", "auto", "required"]

            • "none"

            • "auto"

            • "required"

          • 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.

        • tools: Optional[RealtimeToolsConfig]

          Tools available to the model.

          • class RealtimeFunctionTool: …

          • class Mcp: …

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

            • server_label: str

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

            • type: Literal["mcp"]

              The type of the MCP tool. Always mcp.

              • "mcp"

            • allowed_tools: Optional[McpAllowedTools]

              List of allowed tool names or a filter object.

              • List[str]

                A string array of allowed tool names

              • class McpAllowedToolsMcpToolFilter: …

                A filter object to specify which tools are allowed.

                • read_only: Optional[bool]

                  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.

                • tool_names: Optional[List[str]]

                  List of allowed tool names.

            • authorization: Optional[str]

              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.

            • connector_id: Optional[Literal["connector_dropbox", "connector_gmail", "connector_googlecalendar", 5 more]]

              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_gmail"

              • "connector_googlecalendar"

              • "connector_googledrive"

              • "connector_microsoftteams"

              • "connector_outlookcalendar"

              • "connector_outlookemail"

              • "connector_sharepoint"

            • defer_loading: Optional[bool]

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

            • headers: Optional[Dict[str, str]]

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

            • require_approval: Optional[McpRequireApproval]

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

              • class McpRequireApprovalMcpToolApprovalFilter: …

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

                • always: Optional[McpRequireApprovalMcpToolApprovalFilterAlways]

                  A filter object to specify which tools are allowed.

                  • read_only: Optional[bool]

                    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.

                  • tool_names: Optional[List[str]]

                    List of allowed tool names.

                • never: Optional[McpRequireApprovalMcpToolApprovalFilterNever]

                  A filter object to specify which tools are allowed.

                  • read_only: Optional[bool]

                    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.

                  • tool_names: Optional[List[str]]

                    List of allowed tool names.

              • Literal["always", "never"]

                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"

                • "never"

            • server_description: Optional[str]

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

            • server_url: Optional[str]

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

            • tunnel_id: Optional[str]

              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.

        • tracing: Optional[RealtimeTracingConfig]

          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.

          • Literal["auto"]

            Enables tracing and sets default values for tracing configuration options. Always auto.

            • "auto"

          • class TracingConfiguration: …

            Granular configuration for tracing.

            • group_id: Optional[str]

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

            • metadata: Optional[object]

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

            • workflow_name: Optional[str]

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

        • truncation: Optional[RealtimeTruncation]

          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.

          • Literal["auto", "disabled"]

            The truncation strategy to use for the session. auto is the default truncation strategy. disabled will disable truncation and emit errors when the conversation exceeds the input token limit.

            • "auto"

            • "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.

            • retention_ratio: float

              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.

            • type: Literal["retention_ratio"]

              Use retention ratio truncation.

              • "retention_ratio"

            • token_limits: Optional[TokenLimits]

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

              • post_instructions: Optional[int]

                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.

        • type: Literal["transcription"]

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

          • "transcription"

        • audio: Optional[RealtimeTranscriptionSessionAudio]

          Configuration for input and output audio.

          • input: Optional[RealtimeTranscriptionSessionAudioInput]

            • format: Optional[RealtimeAudioFormats]

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

            • noise_reduction: Optional[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.

              • type: Optional[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.

            • transcription: Optional[AudioTranscription]

              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.

            • turn_detection: Optional[RealtimeTranscriptionSessionAudioInputTurnDetection]

              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.

                • type: Literal["server_vad"]

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

                  • "server_vad"

                • create_response: Optional[bool]

                  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.

                • idle_timeout_ms: Optional[int]

                  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.

                • interrupt_response: Optional[bool]

                  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.

                • prefix_padding_ms: Optional[int]

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

                • silence_duration_ms: Optional[int]

                  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.

                • threshold: Optional[float]

                  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.

                • type: Literal["semantic_vad"]

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

                  • "semantic_vad"

                • create_response: Optional[bool]

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

                • eagerness: Optional[Literal["low", "medium", "high", "auto"]]

                  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"

                  • "medium"

                  • "high"

                  • "auto"

                • interrupt_response: Optional[bool]

                  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.

        • include: Optional[List[Literal["item.input_audio_transcription.logprobs"]]]

          Additional fields to include in server outputs.

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

          • "item.input_audio_transcription.logprobs"

    • type: Literal["session.update"]

      The event type, must be session.update.

      • "session.update"

    • event_id: Optional[str]

      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.

  • content: List[Content]

    The content of the message.

    • audio: Optional[str]

      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.

    • text: Optional[str]

      The text content.

    • transcript: Optional[str]

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

    • type: Optional[Literal["output_text", "output_audio"]]

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

      • "output_text"

      • "output_audio"

  • role: Literal["assistant"]

    The role of the message sender. Always assistant.

    • "assistant"

  • type: Literal["message"]

    The type of the item. Always message.

    • "message"

  • id: Optional[str]

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

  • object: Optional[Literal["realtime.item"]]

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

    • "realtime.item"

  • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

    • "completed"

    • "incomplete"

    • "in_progress"

Realtime Conversation Item Function Call

• class RealtimeConversationItemFunctionCall: …

  A function call item in a Realtime conversation.

  • arguments: str

    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}.

  • name: str

    The name of the function being called.

  • type: Literal["function_call"]

    The type of the item. Always function_call.

    • "function_call"

  • id: Optional[str]

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

  • call_id: Optional[str]

    The ID of the function call.

  • object: Optional[Literal["realtime.item"]]

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

    • "realtime.item"

  • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

    • "completed"

    • "incomplete"

    • "in_progress"

Realtime Conversation Item Function Call Output

• class RealtimeConversationItemFunctionCallOutput: …

  A function call output item in a Realtime conversation.

  • call_id: str

    The ID of the function call this output is for.

  • output: str

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

  • type: Literal["function_call_output"]

    The type of the item. Always function_call_output.

    • "function_call_output"

  • id: Optional[str]

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

  • object: Optional[Literal["realtime.item"]]

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

    • "realtime.item"

  • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

    • "completed"

    • "incomplete"

    • "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.

  • content: List[Content]

    The content of the message.

    • text: Optional[str]

      The text content.

    • type: Optional[Literal["input_text"]]

      The content type. Always input_text for system messages.

      • "input_text"

  • role: Literal["system"]

    The role of the message sender. Always system.

    • "system"

  • type: Literal["message"]

    The type of the item. Always message.

    • "message"

  • id: Optional[str]

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

  • object: Optional[Literal["realtime.item"]]

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

    • "realtime.item"

  • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

    • "completed"

    • "incomplete"

    • "in_progress"

Realtime Conversation Item User Message

• class RealtimeConversationItemUserMessage: …

  A user message item in a Realtime conversation.

  • content: List[Content]

    The content of the message.

    • audio: Optional[str]

      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.

    • detail: Optional[Literal["auto", "low", "high"]]

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

      • "auto"

      • "low"

      • "high"

    • image_url: Optional[str]

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

    • text: Optional[str]

      The text content (for input_text).

    • transcript: Optional[str]

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

    • type: Optional[Literal["input_text", "input_audio", "input_image"]]

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

      • "input_text"

      • "input_audio"

      • "input_image"

  • role: Literal["user"]

    The role of the message sender. Always user.

    • "user"

  • type: Literal["message"]

    The type of the item. Always message.

    • "message"

  • id: Optional[str]

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

  • object: Optional[Literal["realtime.item"]]

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

    • "realtime.item"

  • status: Optional[Literal["completed", "incomplete", "in_progress"]]

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

    • "completed"

    • "incomplete"

    • "in_progress"

Realtime Error

• class RealtimeError: …

  Details of the error.

  • message: str

    A human-readable error message.

  • type: str

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

  • code: Optional[str]

    Error code, if any.

  • event_id: Optional[str]

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

  • param: Optional[str]

    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.

  • error: RealtimeError

    Details of the error.

    • message: str

      A human-readable error message.

    • type: str

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

    • code: Optional[str]

      Error code, if any.

    • event_id: Optional[str]

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

    • param: Optional[str]

      Parameter related to the error, if any.

  • event_id: str

    The unique ID of the server event.

  • type: Literal["error"]

    The event type, must be error.

    • "error"

Realtime Function Tool

• class RealtimeFunctionTool: …

  • description: Optional[str]

    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).

  • name: Optional[str]

    The name of the function.

  • parameters: Optional[object]

    Parameters of the function in JSON Schema.

  • type: Optional[Literal["function"]]

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

    • "function"

Realtime Mcp Approval Request

• class RealtimeMcpApprovalRequest: …

  A Realtime item requesting human approval of a tool invocation.

  • id: str

    The unique ID of the approval request.

  • arguments: str

    A JSON string of arguments for the tool.

  • name: str

    The name of the tool to run.

  • server_label: str

    The label of the MCP server making the request.

  • type: Literal["mcp_approval_request"]

    The type of the item. Always mcp_approval_request.

    • "mcp_approval_request"

Realtime Mcp Approval Response

• class RealtimeMcpApprovalResponse: …

  A Realtime item responding to an MCP approval request.

  • id: str

    The unique ID of the approval response.

  • approval_request_id: str

    The ID of the approval request being answered.

  • approve: bool

    Whether the request was approved.

  • type: Literal["mcp_approval_response"]

    The type of the item. Always mcp_approval_response.

    • "mcp_approval_response"

  • reason: Optional[str]

    Optional reason for the decision.

Realtime Mcp List Tools

• class RealtimeMcpListTools: …

  A Realtime item listing tools available on an MCP server.

  • server_label: str

    The label of the MCP server.

  • tools: List[Tool]

    The tools available on the server.

    • input_schema: object

      The JSON schema describing the tool's input.

    • name: str

      The name of the tool.

    • annotations: Optional[object]

      Additional annotations about the tool.

    • description: Optional[str]

      The description of the tool.

  • type: Literal["mcp_list_tools"]

    The type of the item. Always mcp_list_tools.

    • "mcp_list_tools"

  • id: Optional[str]

    The unique ID of the list.

Realtime Mcp Protocol Error

• class RealtimeMcpProtocolError: …

  • code: int

  • message: str

  • type: Literal["protocol_error"]

    • "protocol_error"

Realtime Mcp Tool Call

• class RealtimeMcpToolCall: …

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

  • id: str

    The unique ID of the tool call.

  • arguments: str

    A JSON string of the arguments passed to the tool.

  • name: str

    The name of the tool that was run.

  • server_label: str

    The label of the MCP server running the tool.

  • type: Literal["mcp_call"]

    The type of the item. Always mcp_call.

    • "mcp_call"

  • approval_request_id: Optional[str]

    The ID of an associated approval request, if any.

  • error: Optional[Error]

    The error from the tool call, if any.

    • class RealtimeMcpProtocolError: …

      • code: int

      • message: str

      • type: Literal["protocol_error"]

        • "protocol_error"

    • class RealtimeMcpToolExecutionError: …

      • message: str

      • type: Literal["tool_execution_error"]

        • "tool_execution_error"

    • class RealtimeMcphttpError: …

      • code: int

      • message: str

      • type: Literal["http_error"]

        • "http_error"

  • output: Optional[str]

    The output from the tool call.