Client Secrets

Create client secret

realtime.client_secrets.create(**kwargs) -> ClientSecretCreateResponse

post /realtime/client_secrets

Create a Realtime client secret with an associated session configuration.

Client secrets are short-lived tokens that can be passed to a client app, such as a web frontend or mobile client, which grants access to the Realtime API without leaking your main API key. You can configure a custom TTL for each client secret.

You can also attach session configuration options to the client secret, which will be applied to any sessions created using that client secret, but these can also be overridden by the client connection.

Learn more about authentication with client secrets over WebRTC.

Returns the created client secret and the effective session object. The client secret is a string that looks like ek_1234.

Parameters

• expires_after: ExpiresAfter{ anchor, seconds}

  Configuration for the client secret expiration. Expiration refers to the time after which a client secret will no longer be valid for creating sessions. The session itself may continue after that time once started. A secret can be used to create multiple sessions until it expires.

  • anchor: :created_at

    The anchor point for the client secret expiration, meaning that seconds will be added to the created_at time of the client secret to produce an expiration timestamp. Only created_at is currently supported.

    • :created_at

  • seconds: Integer

    The number of seconds from the anchor point to the expiration. Select a value between 10 and 7200 (2 hours). This default to 600 seconds (10 minutes) if not specified.

• session: RealtimeSessionCreateRequest | RealtimeTranscriptionSessionCreateRequest

  Session configuration to use for the client secret. Choose either a realtime session or a transcription session.

  • class RealtimeSessionCreateRequest

    Realtime session object configuration.

    • type: :realtime

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

      • :realtime

    • audio: RealtimeAudioConfig

      Configuration for input and output audio.

      • input: RealtimeAudioConfigInput

        • format_: RealtimeAudioFormats

          The format of the input audio.

          • class AudioPCM

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

            • rate: 24000

              The sample rate of the audio. Always 24000.

              • 24000

            • type: :"audio/pcm"

              The audio format. Always audio/pcm.

              • :"audio/pcm"

          • class AudioPCMU

            The G.711 μ-law format.

            • type: :"audio/pcmu"

              The audio format. Always audio/pcmu.

              • :"audio/pcmu"

          • class AudioPCMA

            The G.711 A-law format.

            • type: :"audio/pcma"

              The audio format. Always audio/pcma.

              • :"audio/pcma"

        • noise_reduction: NoiseReduction{ type}

          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: 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: 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: :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: String

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

          • model: String | :"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.

            • String = String

            • Model = :"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: String

            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: 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: :server_vad

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

              • :server_vad

            • create_response: 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: Integer

              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: 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: Integer

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

            • silence_duration_ms: Integer

              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: 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: :semantic_vad

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

              • :semantic_vad

            • create_response: bool

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

            • eagerness: :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: 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: RealtimeAudioConfigOutput

        • format_: RealtimeAudioFormats

          The format of the output audio.

        • speed: 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: String | :alloy | :ash | :ballad | 7 more | ID{ id}

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

          • String = String

          • Voice = :alloy | :ash | :ballad | 7 more

            • :alloy

            • :ash

            • :ballad

            • :coral

            • :echo

            • :sage

            • :shimmer

            • :verse

            • :marin

            • :cedar

          • class ID

            Custom voice reference.

            • id: String

              The custom voice ID, e.g. voice_1234.

    • include: Array[:"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: String

      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: Integer | :inf

      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.

      • Integer = Integer

      • MaxOutputTokens = :inf

        • :inf

    • model: String | :"gpt-realtime" | :"gpt-realtime-1.5" | :"gpt-realtime-2" | 14 more

      The Realtime model used for this session.

      • String = String

      • Model = :"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: Array[: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: bool

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

    • prompt: ResponsePrompt

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

      • id: String

        The unique identifier of the prompt template to use.

      • variables: Hash[Symbol, String | ResponseInputText | ResponseInputImage | ResponseInputFile]

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

        • String = String

        • class ResponseInputText

          A text input to the model.

          • text: String

            The text input to the model.

          • type: :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: :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: :input_image

            The type of the input item. Always input_image.

            • :input_image

          • file_id: String

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

          • image_url: String

            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: :input_file

            The type of the input item. Always input_file.

            • :input_file

          • detail: :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: String

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

          • file_id: String

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

          • file_url: String

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

          • filename: String

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

      • version: String

        Optional version of the prompt template.

    • reasoning: RealtimeReasoning

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

      • effort: RealtimeReasoningEffort

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

        • :minimal

        • :low

        • :medium

        • :high

        • :xhigh

    • tool_choice: RealtimeToolChoiceConfig

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

      • ToolChoiceOptions = :none | :auto | :required

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

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

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

        required means the model must call one or more tools.

        • :none

        • :auto

        • :required

      • class ToolChoiceFunction

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

        • name: String

          The name of the function to call.

        • type: :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: String

          The label of the MCP server to use.

        • type: :mcp

          For MCP tools, the type is always mcp.

          • :mcp

        • name: String

          The name of the tool to call on the server.

    • tools: RealtimeToolsConfig

      Tools available to the model.

      • class RealtimeFunctionTool

        • description: String

          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: String

          The name of the function.

        • parameters: untyped

          Parameters of the function in JSON Schema.

        • type: :function

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

          • :function

      • class Mcp

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

        • server_label: String

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

        • type: :mcp

          The type of the MCP tool. Always mcp.

          • :mcp

        • allowed_tools: Array[String] | McpToolFilter{ read_only, tool_names}

          List of allowed tool names or a filter object.

          • McpAllowedTools = Array[String]

            A string array of allowed tool names

          • class McpToolFilter

            A filter object to specify which tools are allowed.

            • read_only: 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: Array[String]

              List of allowed tool names.

        • authorization: String

          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: :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: bool

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

        • headers: Hash[Symbol, String]

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

        • require_approval: McpToolApprovalFilter{ always, never} | :always | :never

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

          • class McpToolApprovalFilter

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

            • always: Always{ read_only, tool_names}

              A filter object to specify which tools are allowed.

              • read_only: 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: Array[String]

                List of allowed tool names.

            • never: Never{ read_only, tool_names}

              A filter object to specify which tools are allowed.

              • read_only: 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: Array[String]

                List of allowed tool names.

          • McpToolApprovalSetting = :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: String

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

        • server_url: String

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

        • tunnel_id: String

          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: 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.

      • RealtimeTracingConfig = :auto

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

        • :auto

      • class TracingConfiguration

        Granular configuration for tracing.

        • group_id: String

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

        • metadata: untyped

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

        • workflow_name: String

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

    • truncation: 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.

      • RealtimeTruncationStrategy = :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: :retention_ratio

          Use retention ratio truncation.

          • :retention_ratio

        • token_limits: TokenLimits{ post_instructions}

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

          • post_instructions: Integer

            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: :transcription

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

      • :transcription

    • audio: RealtimeTranscriptionSessionAudio

      Configuration for input and output audio.

      • input: RealtimeTranscriptionSessionAudioInput

        • format_: RealtimeAudioFormats

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

        • noise_reduction: NoiseReduction{ type}

          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: 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: 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: 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: :server_vad

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

              • :server_vad

            • create_response: 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: Integer

              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: 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: Integer

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

            • silence_duration_ms: Integer

              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: 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: :semantic_vad

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

              • :semantic_vad

            • create_response: bool

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

            • eagerness: :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: 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: Array[:"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"

Returns

• class ClientSecretCreateResponse

  Response from creating a session and client secret for the Realtime API.

  • expires_at: Integer

    Expiration timestamp for the client secret, in seconds since epoch.

  • session: RealtimeSessionCreateResponse | RealtimeTranscriptionSessionCreateResponse

    The session configuration for either a realtime or transcription session.

    • class RealtimeSessionCreateResponse

      A Realtime session configuration object.

      • id: String

        Unique identifier for the session that looks like sess_1234567890abcdef.

      • object: :"realtime.session"

        The object type. Always realtime.session.

        • :"realtime.session"

      • type: :realtime

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

        • :realtime

      • audio: Audio{ input, output}

        Configuration for input and output audio.

        • input: Input{ format_, noise_reduction, transcription, turn_detection}

          • format_: RealtimeAudioFormats

            The format of the input audio.

            • class AudioPCM

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

              • rate: 24000

                The sample rate of the audio. Always 24000.

                • 24000

              • type: :"audio/pcm"

                The audio format. Always audio/pcm.

                • :"audio/pcm"

            • class AudioPCMU

              The G.711 μ-law format.

              • type: :"audio/pcmu"

                The audio format. Always audio/pcmu.

                • :"audio/pcmu"

            • class AudioPCMA

              The G.711 A-law format.

              • type: :"audio/pcma"

                The audio format. Always audio/pcma.

                • :"audio/pcma"

          • noise_reduction: NoiseReduction{ type}

            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: 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: AudioTranscription

            • delay: :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: String

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

            • model: String | :"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.

              • String = String

              • Model = :"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: String

              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: ServerVad{ type, create_response, idle_timeout_ms, 4 more} | SemanticVad{ type, create_response, eagerness, interrupt_response}

            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: :server_vad

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

                • :server_vad

              • create_response: 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: Integer

                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: 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: Integer

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

              • silence_duration_ms: Integer

                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: 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: :semantic_vad

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

                • :semantic_vad

              • create_response: bool

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

              • eagerness: :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: 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: Output{ format_, speed, voice}

          • format_: RealtimeAudioFormats

            The format of the output audio.

          • speed: 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: String | :alloy | :ash | :ballad | 7 more

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

            • String = String

            • Voice = :alloy | :ash | :ballad | 7 more

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

              • :alloy

              • :ash

              • :ballad

              • :coral

              • :echo

              • :sage

              • :shimmer

              • :verse

              • :marin

              • :cedar

      • expires_at: Integer

        Expiration timestamp for the session, in seconds since epoch.

      • include: Array[:"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: String

        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: Integer | :inf

        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.

        • Integer = Integer

        • MaxOutputTokens = :inf

          • :inf

      • model: String | :"gpt-realtime" | :"gpt-realtime-1.5" | :"gpt-realtime-2" | 14 more

        The Realtime model used for this session.

        • String = String

        • Model = :"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: Array[: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

      • prompt: ResponsePrompt

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

        • id: String

          The unique identifier of the prompt template to use.

        • variables: Hash[Symbol, String | ResponseInputText | ResponseInputImage | ResponseInputFile]

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

          • String = String

          • class ResponseInputText

            A text input to the model.

            • text: String

              The text input to the model.

            • type: :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: :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: :input_image

              The type of the input item. Always input_image.

              • :input_image

            • file_id: String

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

            • image_url: String

              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: :input_file

              The type of the input item. Always input_file.

              • :input_file

            • detail: :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: String

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

            • file_id: String

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

            • file_url: String

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

            • filename: String

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

        • version: String

          Optional version of the prompt template.

      • reasoning: RealtimeReasoning

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

        • effort: RealtimeReasoningEffort

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

          • :minimal

          • :low

          • :medium

          • :high

          • :xhigh

      • tool_choice: ToolChoiceOptions | ToolChoiceFunction | ToolChoiceMcp

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

        • ToolChoiceOptions = :none | :auto | :required

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

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

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

          required means the model must call one or more tools.

          • :none

          • :auto

          • :required

        • class ToolChoiceFunction

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

          • name: String

            The name of the function to call.

          • type: :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: String

            The label of the MCP server to use.

          • type: :mcp

            For MCP tools, the type is always mcp.

            • :mcp

          • name: String

            The name of the tool to call on the server.

      • tools: Array[RealtimeFunctionTool | McpTool{ server_label, type, allowed_tools, 8 more}]

        Tools available to the model.

        • class RealtimeFunctionTool

          • description: String

            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: String

            The name of the function.

          • parameters: untyped

            Parameters of the function in JSON Schema.

          • type: :function

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

            • :function

        • class McpTool

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

          • server_label: String

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

          • type: :mcp

            The type of the MCP tool. Always mcp.

            • :mcp

          • allowed_tools: Array[String] | McpToolFilter{ read_only, tool_names}

            List of allowed tool names or a filter object.

            • McpAllowedTools = Array[String]

              A string array of allowed tool names

            • class McpToolFilter

              A filter object to specify which tools are allowed.

              • read_only: 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: Array[String]

                List of allowed tool names.

          • authorization: String

            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: :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: bool

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

          • headers: Hash[Symbol, String]

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

          • require_approval: McpToolApprovalFilter{ always, never} | :always | :never

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

            • class McpToolApprovalFilter

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

              • always: Always{ read_only, tool_names}

                A filter object to specify which tools are allowed.

                • read_only: 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: Array[String]

                  List of allowed tool names.

              • never: Never{ read_only, tool_names}

                A filter object to specify which tools are allowed.

                • read_only: 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: Array[String]

                  List of allowed tool names.

            • McpToolApprovalSetting = :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: String

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

          • server_url: String

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

          • tunnel_id: String

            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: :auto | TracingConfiguration{ group_id, metadata, workflow_name}

        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.

        • Tracing = :auto

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

          • :auto

        • class TracingConfiguration

          Granular configuration for tracing.

          • group_id: String

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

          • metadata: untyped

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

          • workflow_name: String

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

      • truncation: 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.

        • RealtimeTruncationStrategy = :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: :retention_ratio

            Use retention ratio truncation.

            • :retention_ratio

          • token_limits: TokenLimits{ post_instructions}

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

            • post_instructions: Integer

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

    • class RealtimeTranscriptionSessionCreateResponse

      A Realtime transcription session configuration object.

      • id: String

        Unique identifier for the session that looks like sess_1234567890abcdef.

      • object: String

        The object type. Always realtime.transcription_session.

      • type: :transcription

        The type of session. Always transcription for transcription sessions.

        • :transcription

      • audio: Audio{ input}

        Configuration for input audio for the session.

        • input: Input{ format_, noise_reduction, transcription, turn_detection}

          • format_: RealtimeAudioFormats

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

          • noise_reduction: NoiseReduction{ type}

            Configuration for input audio noise reduction.

            • type: 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: AudioTranscription

          • turn_detection: RealtimeTranscriptionSessionTurnDetection

            Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.

            • prefix_padding_ms: Integer

              Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

            • silence_duration_ms: Integer

              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: Float

              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.

            • type: String

              Type of turn detection, only server_vad is currently supported.

      • expires_at: Integer

        Expiration timestamp for the session, in seconds since epoch.

      • include: Array[:"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"

  • value: String

    The generated client secret value.

Example

require "openai"

openai = OpenAI::Client.new(api_key: "My API Key")

client_secret = openai.realtime.client_secrets.create

puts(client_secret)

Response

{
  "expires_at": 0,
  "session": {
    "id": "id",
    "object": "realtime.session",
    "type": "realtime",
    "audio": {
      "input": {
        "format": {
          "rate": 24000,
          "type": "audio/pcm"
        },
        "noise_reduction": {
          "type": "near_field"
        },
        "transcription": {
          "delay": "minimal",
          "language": "language",
          "model": "whisper-1",
          "prompt": "prompt"
        },
        "turn_detection": {
          "type": "server_vad",
          "create_response": true,
          "idle_timeout_ms": 5000,
          "interrupt_response": true,
          "prefix_padding_ms": 0,
          "silence_duration_ms": 0,
          "threshold": 0
        }
      },
      "output": {
        "format": {
          "rate": 24000,
          "type": "audio/pcm"
        },
        "speed": 0.25,
        "voice": "ash"
      }
    },
    "expires_at": 0,
    "include": [
      "item.input_audio_transcription.logprobs"
    ],
    "instructions": "instructions",
    "max_output_tokens": "inf",
    "model": "gpt-realtime",
    "output_modalities": [
      "text"
    ],
    "prompt": {
      "id": "id",
      "variables": {
        "foo": "string"
      },
      "version": "version"
    },
    "reasoning": {
      "effort": "minimal"
    },
    "tool_choice": "none",
    "tools": [
      {
        "description": "description",
        "name": "name",
        "parameters": {},
        "type": "function"
      }
    ],
    "tracing": "auto",
    "truncation": "auto"
  },
  "value": "value"
}

Domain Types

Realtime Session Create Response

• class RealtimeSessionCreateResponse

  A Realtime session configuration object.

  • id: String

    Unique identifier for the session that looks like sess_1234567890abcdef.

  • object: :"realtime.session"

    The object type. Always realtime.session.

    • :"realtime.session"

  • type: :realtime

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

    • :realtime

  • audio: Audio{ input, output}

    Configuration for input and output audio.

    • input: Input{ format_, noise_reduction, transcription, turn_detection}

      • format_: RealtimeAudioFormats

        The format of the input audio.

        • class AudioPCM

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

          • rate: 24000

            The sample rate of the audio. Always 24000.

            • 24000

          • type: :"audio/pcm"

            The audio format. Always audio/pcm.

            • :"audio/pcm"

        • class AudioPCMU

          The G.711 μ-law format.

          • type: :"audio/pcmu"

            The audio format. Always audio/pcmu.

            • :"audio/pcmu"

        • class AudioPCMA

          The G.711 A-law format.

          • type: :"audio/pcma"

            The audio format. Always audio/pcma.

            • :"audio/pcma"

      • noise_reduction: NoiseReduction{ type}

        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: 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: AudioTranscription

        • delay: :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: String

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

        • model: String | :"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.

          • String = String

          • Model = :"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: String

          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: ServerVad{ type, create_response, idle_timeout_ms, 4 more} | SemanticVad{ type, create_response, eagerness, interrupt_response}

        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: :server_vad

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

            • :server_vad

          • create_response: 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: Integer

            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: 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: Integer

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

          • silence_duration_ms: Integer

            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: 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: :semantic_vad

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

            • :semantic_vad

          • create_response: bool

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

          • eagerness: :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: 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: Output{ format_, speed, voice}

      • format_: RealtimeAudioFormats

        The format of the output audio.

      • speed: 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: String | :alloy | :ash | :ballad | 7 more

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

        • String = String

        • Voice = :alloy | :ash | :ballad | 7 more

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

          • :alloy

          • :ash

          • :ballad

          • :coral

          • :echo

          • :sage

          • :shimmer

          • :verse

          • :marin

          • :cedar

  • expires_at: Integer

    Expiration timestamp for the session, in seconds since epoch.

  • include: Array[:"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: String

    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: Integer | :inf

    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.

    • Integer = Integer

    • MaxOutputTokens = :inf

      • :inf

  • model: String | :"gpt-realtime" | :"gpt-realtime-1.5" | :"gpt-realtime-2" | 14 more

    The Realtime model used for this session.

    • String = String

    • Model = :"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: Array[: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

  • prompt: ResponsePrompt

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

    • id: String

      The unique identifier of the prompt template to use.

    • variables: Hash[Symbol, String | ResponseInputText | ResponseInputImage | ResponseInputFile]

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

      • String = String

      • class ResponseInputText

        A text input to the model.

        • text: String

          The text input to the model.

        • type: :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: :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: :input_image

          The type of the input item. Always input_image.

          • :input_image

        • file_id: String

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

        • image_url: String

          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: :input_file

          The type of the input item. Always input_file.

          • :input_file

        • detail: :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: String

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

        • file_id: String

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

        • file_url: String

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

        • filename: String

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

    • version: String

      Optional version of the prompt template.

  • reasoning: RealtimeReasoning

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

    • effort: RealtimeReasoningEffort

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

      • :minimal

      • :low

      • :medium

      • :high

      • :xhigh

  • tool_choice: ToolChoiceOptions | ToolChoiceFunction | ToolChoiceMcp

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

    • ToolChoiceOptions = :none | :auto | :required

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

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

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

      required means the model must call one or more tools.

      • :none

      • :auto

      • :required

    • class ToolChoiceFunction

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

      • name: String

        The name of the function to call.

      • type: :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: String

        The label of the MCP server to use.

      • type: :mcp

        For MCP tools, the type is always mcp.

        • :mcp

      • name: String

        The name of the tool to call on the server.

  • tools: Array[RealtimeFunctionTool | McpTool{ server_label, type, allowed_tools, 8 more}]

    Tools available to the model.

    • class RealtimeFunctionTool

      • description: String

        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: String

        The name of the function.

      • parameters: untyped

        Parameters of the function in JSON Schema.

      • type: :function

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

        • :function

    • class McpTool

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

      • server_label: String

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

      • type: :mcp

        The type of the MCP tool. Always mcp.

        • :mcp

      • allowed_tools: Array[String] | McpToolFilter{ read_only, tool_names}

        List of allowed tool names or a filter object.

        • McpAllowedTools = Array[String]

          A string array of allowed tool names

        • class McpToolFilter

          A filter object to specify which tools are allowed.

          • read_only: 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: Array[String]

            List of allowed tool names.

      • authorization: String

        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: :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: bool

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

      • headers: Hash[Symbol, String]

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

      • require_approval: McpToolApprovalFilter{ always, never} | :always | :never

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

        • class McpToolApprovalFilter

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

          • always: Always{ read_only, tool_names}

            A filter object to specify which tools are allowed.

            • read_only: 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: Array[String]

              List of allowed tool names.

          • never: Never{ read_only, tool_names}

            A filter object to specify which tools are allowed.

            • read_only: 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: Array[String]

              List of allowed tool names.

        • McpToolApprovalSetting = :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: String

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

      • server_url: String

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

      • tunnel_id: String

        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: :auto | TracingConfiguration{ group_id, metadata, workflow_name}

    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.

    • Tracing = :auto

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

      • :auto

    • class TracingConfiguration

      Granular configuration for tracing.

      • group_id: String

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

      • metadata: untyped

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

      • workflow_name: String

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

  • truncation: 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.

    • RealtimeTruncationStrategy = :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: :retention_ratio

        Use retention ratio truncation.

        • :retention_ratio

      • token_limits: TokenLimits{ post_instructions}

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

        • post_instructions: Integer

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

Realtime Transcription Session Create Response

• class RealtimeTranscriptionSessionCreateResponse

  A Realtime transcription session configuration object.

  • id: String

    Unique identifier for the session that looks like sess_1234567890abcdef.

  • object: String

    The object type. Always realtime.transcription_session.

  • type: :transcription

    The type of session. Always transcription for transcription sessions.

    • :transcription

  • audio: Audio{ input}

    Configuration for input audio for the session.

    • input: Input{ format_, noise_reduction, transcription, turn_detection}

      • format_: 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: 24000

            The sample rate of the audio. Always 24000.

            • 24000

          • type: :"audio/pcm"

            The audio format. Always audio/pcm.

            • :"audio/pcm"

        • class AudioPCMU

          The G.711 μ-law format.

          • type: :"audio/pcmu"

            The audio format. Always audio/pcmu.

            • :"audio/pcmu"

        • class AudioPCMA

          The G.711 A-law format.

          • type: :"audio/pcma"

            The audio format. Always audio/pcma.

            • :"audio/pcma"

      • noise_reduction: NoiseReduction{ type}

        Configuration for input audio noise reduction.

        • type: 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: AudioTranscription

        • delay: :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: String

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

        • model: String | :"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.

          • String = String

          • Model = :"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: String

          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: RealtimeTranscriptionSessionTurnDetection

        Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.

        • prefix_padding_ms: Integer

          Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

        • silence_duration_ms: Integer

          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: Float

          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.

        • type: String

          Type of turn detection, only server_vad is currently supported.

  • expires_at: Integer

    Expiration timestamp for the session, in seconds since epoch.

  • include: Array[:"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"

Realtime Transcription Session Turn Detection

• class RealtimeTranscriptionSessionTurnDetection

  Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.

  • prefix_padding_ms: Integer

    Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

  • silence_duration_ms: Integer

    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: Float

    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.

  • type: String

    Type of turn detection, only server_vad is currently supported.

Client Secret Create Response

• class ClientSecretCreateResponse

  Response from creating a session and client secret for the Realtime API.

  • expires_at: Integer

    Expiration timestamp for the client secret, in seconds since epoch.

  • session: RealtimeSessionCreateResponse | RealtimeTranscriptionSessionCreateResponse

    The session configuration for either a realtime or transcription session.

    • class RealtimeSessionCreateResponse

      A Realtime session configuration object.

      • id: String

        Unique identifier for the session that looks like sess_1234567890abcdef.

      • object: :"realtime.session"

        The object type. Always realtime.session.

        • :"realtime.session"

      • type: :realtime

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

        • :realtime

      • audio: Audio{ input, output}

        Configuration for input and output audio.

        • input: Input{ format_, noise_reduction, transcription, turn_detection}

          • format_: RealtimeAudioFormats

            The format of the input audio.

            • class AudioPCM

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

              • rate: 24000

                The sample rate of the audio. Always 24000.

                • 24000

              • type: :"audio/pcm"

                The audio format. Always audio/pcm.

                • :"audio/pcm"

            • class AudioPCMU

              The G.711 μ-law format.

              • type: :"audio/pcmu"

                The audio format. Always audio/pcmu.

                • :"audio/pcmu"

            • class AudioPCMA

              The G.711 A-law format.

              • type: :"audio/pcma"

                The audio format. Always audio/pcma.

                • :"audio/pcma"

          • noise_reduction: NoiseReduction{ type}

            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: 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: AudioTranscription

            • delay: :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: String

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

            • model: String | :"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.

              • String = String

              • Model = :"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: String

              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: ServerVad{ type, create_response, idle_timeout_ms, 4 more} | SemanticVad{ type, create_response, eagerness, interrupt_response}

            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: :server_vad

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

                • :server_vad

              • create_response: 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: Integer

                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: 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: Integer

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

              • silence_duration_ms: Integer

                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: 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: :semantic_vad

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

                • :semantic_vad

              • create_response: bool

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

              • eagerness: :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: 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: Output{ format_, speed, voice}

          • format_: RealtimeAudioFormats

            The format of the output audio.

          • speed: 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: String | :alloy | :ash | :ballad | 7 more

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

            • String = String

            • Voice = :alloy | :ash | :ballad | 7 more

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

              • :alloy

              • :ash

              • :ballad

              • :coral

              • :echo

              • :sage

              • :shimmer

              • :verse

              • :marin

              • :cedar

      • expires_at: Integer

        Expiration timestamp for the session, in seconds since epoch.

      • include: Array[:"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: String

        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: Integer | :inf

        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.

        • Integer = Integer

        • MaxOutputTokens = :inf

          • :inf

      • model: String | :"gpt-realtime" | :"gpt-realtime-1.5" | :"gpt-realtime-2" | 14 more

        The Realtime model used for this session.

        • String = String

        • Model = :"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: Array[: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

      • prompt: ResponsePrompt

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

        • id: String

          The unique identifier of the prompt template to use.

        • variables: Hash[Symbol, String | ResponseInputText | ResponseInputImage | ResponseInputFile]

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

          • String = String

          • class ResponseInputText

            A text input to the model.

            • text: String

              The text input to the model.

            • type: :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: :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: :input_image

              The type of the input item. Always input_image.

              • :input_image

            • file_id: String

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

            • image_url: String

              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: :input_file

              The type of the input item. Always input_file.

              • :input_file

            • detail: :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: String

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

            • file_id: String

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

            • file_url: String

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

            • filename: String

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

        • version: String

          Optional version of the prompt template.

      • reasoning: RealtimeReasoning

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

        • effort: RealtimeReasoningEffort

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

          • :minimal

          • :low

          • :medium

          • :high

          • :xhigh

      • tool_choice: ToolChoiceOptions | ToolChoiceFunction | ToolChoiceMcp

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

        • ToolChoiceOptions = :none | :auto | :required

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

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

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

          required means the model must call one or more tools.

          • :none

          • :auto

          • :required

        • class ToolChoiceFunction

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

          • name: String

            The name of the function to call.

          • type: :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: String

            The label of the MCP server to use.

          • type: :mcp

            For MCP tools, the type is always mcp.

            • :mcp

          • name: String

            The name of the tool to call on the server.

      • tools: Array[RealtimeFunctionTool | McpTool{ server_label, type, allowed_tools, 8 more}]

        Tools available to the model.

        • class RealtimeFunctionTool

          • description: String

            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: String

            The name of the function.

          • parameters: untyped

            Parameters of the function in JSON Schema.

          • type: :function

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

            • :function

        • class McpTool

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

          • server_label: String

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

          • type: :mcp

            The type of the MCP tool. Always mcp.

            • :mcp

          • allowed_tools: Array[String] | McpToolFilter{ read_only, tool_names}

            List of allowed tool names or a filter object.

            • McpAllowedTools = Array[String]

              A string array of allowed tool names

            • class McpToolFilter

              A filter object to specify which tools are allowed.

              • read_only: 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: Array[String]

                List of allowed tool names.

          • authorization: String

            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: :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: bool

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

          • headers: Hash[Symbol, String]

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

          • require_approval: McpToolApprovalFilter{ always, never} | :always | :never

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

            • class McpToolApprovalFilter

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

              • always: Always{ read_only, tool_names}

                A filter object to specify which tools are allowed.

                • read_only: 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: Array[String]

                  List of allowed tool names.

              • never: Never{ read_only, tool_names}

                A filter object to specify which tools are allowed.

                • read_only: 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: Array[String]

                  List of allowed tool names.

            • McpToolApprovalSetting = :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: String

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

          • server_url: String

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

          • tunnel_id: String

            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: :auto | TracingConfiguration{ group_id, metadata, workflow_name}

        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.

        • Tracing = :auto

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

          • :auto

        • class TracingConfiguration

          Granular configuration for tracing.

          • group_id: String

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

          • metadata: untyped

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

          • workflow_name: String

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

      • truncation: 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.

        • RealtimeTruncationStrategy = :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: :retention_ratio

            Use retention ratio truncation.

            • :retention_ratio

          • token_limits: TokenLimits{ post_instructions}

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

            • post_instructions: Integer

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

    • class RealtimeTranscriptionSessionCreateResponse

      A Realtime transcription session configuration object.

      • id: String

        Unique identifier for the session that looks like sess_1234567890abcdef.

      • object: String

        The object type. Always realtime.transcription_session.

      • type: :transcription

        The type of session. Always transcription for transcription sessions.

        • :transcription

      • audio: Audio{ input}

        Configuration for input audio for the session.

        • input: Input{ format_, noise_reduction, transcription, turn_detection}

          • format_: RealtimeAudioFormats

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

          • noise_reduction: NoiseReduction{ type}

            Configuration for input audio noise reduction.

            • type: 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: AudioTranscription

          • turn_detection: RealtimeTranscriptionSessionTurnDetection

            Configuration for turn detection. Can be set to null to turn off. Server VAD means that the model will detect the start and end of speech based on audio volume and respond at the end of user speech. For gpt-realtime-whisper, this must be null; VAD is not supported.

            • prefix_padding_ms: Integer

              Amount of audio to include before the VAD detected speech (in milliseconds). Defaults to 300ms.

            • silence_duration_ms: Integer

              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: Float

              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.

            • type: String

              Type of turn detection, only server_vad is currently supported.

      • expires_at: Integer

        Expiration timestamp for the session, in seconds since epoch.

      • include: Array[:"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"

  • value: String

    The generated client secret value.