---
title: "Accept call"
method: POST
path: "/realtime/calls/{call_id}/accept"
tags: ["Realtime"]
---

# Accept call

`POST /realtime/calls/{call_id}/accept`

Accept an incoming SIP call and configure the realtime session that will
handle it.

## Path parameters

- `call_id` string, required

## Request body

- RealtimeSessionCreateRequestGA — Realtime session object configuration.
  - `type` 'realtime', required — The type of session to create. Always `realtime` for the Realtime API.
  - `output_modalities` string[] — 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.
  - `model` union — The Realtime model used for this session.
    - string
    - 'gpt-realtime' | 'gpt-realtime-1.5' | 'gpt-realtime-2' | 'gpt-realtime-2.1' | 'gpt-realtime-2.1-mini' | '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'
  - `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.
  - `audio` object — Configuration for input and output audio.
    - `input` object
      - `format` union
        - object — The PCM audio format. Only a 24kHz sample rate is supported.
          - `type` 'audio/pcm' — The audio format. Always `audio/pcm`.
          - `rate` 24000 — The sample rate of the audio. Always `24000`.
        - object — The G.711 μ-law format.
          - `type` 'audio/pcmu' — The audio format. Always `audio/pcmu`.
        - object — The G.711 A-law format.
          - `type` 'audio/pcma' — The audio format. Always `audio/pcma`.
      - `transcription` AudioTranscription
        - `model` union — The model to use for transcription. Current options are `whisper-1`, `gpt-transcribe`, `gpt-live-transcribe`, `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
          - 'whisper-1' | 'gpt-transcribe' | 'gpt-live-transcribe' | 'gpt-4o-mini-transcribe' | 'gpt-4o-mini-transcribe-2025-12-15' | 'gpt-4o-transcribe' | 'gpt-4o-transcribe-diarize' | 'gpt-realtime-whisper'
        - `language` string — The language of the input audio. Supplying the input language in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) (e.g. `en`) format will improve accuracy and latency.
        - `languages` string[] — Possible languages of the input audio, in [ISO-639-1](https://en.wikipedia.org/wiki/List_of_ISO_639-1_codes) format. Supported by `gpt-transcribe` and `gpt-live-transcribe`.
        - `keywords` string[] — Words or phrases to guide transcription of the input audio. Supported by `gpt-transcribe` and `gpt-live-transcribe`.
        - `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](https://platform.openai.com/docs/guides/speech-to-text#prompting). 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.
        - `delay` 'minimal' | 'low' | 'medium' | 'high' | 'xhigh' — 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.
      - `noise_reduction` object — 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` 'near_field' | 'far_field' — Type of noise reduction. `near_field` is for close-talking microphones such as headphones, `far_field` is for far-field microphones such as laptop or conference room microphones.
      - `turn_detection` union
        - object — Server-side voice activity detection (VAD) which flips on when user speech is detected and off after a period of silence.
          - `type` 'server_vad', required — Type of turn detection, `server_vad` to turn on simple Server VAD.
          - `threshold` number — 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.
          - `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.
          - `create_response` boolean — 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.
          - `interrupt_response` boolean — 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.
          - `idle_timeout_ms` integer, nullable — 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.
        - object — Server-side semantic turn detection which uses a model to determine when the user has finished speaking.
          - `type` 'semantic_vad', required — Type of turn detection, `semantic_vad` to turn on Semantic VAD.
          - `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.
          - `create_response` boolean — Whether or not to automatically generate a response when a VAD stop event occurs.
          - `interrupt_response` boolean — 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` object
      - `format` union
        - object — The PCM audio format. Only a 24kHz sample rate is supported.
          - `type` 'audio/pcm' — The audio format. Always `audio/pcm`.
          - `rate` 24000 — The sample rate of the audio. Always `24000`.
        - object — The G.711 μ-law format.
          - `type` 'audio/pcmu' — The audio format. Always `audio/pcmu`.
        - object — The G.711 A-law format.
          - `type` 'audio/pcma' — The audio format. Always `audio/pcma`.
      - `voice` union — A built-in voice name or a custom voice reference.
        - union
          - string
          - 'alloy' | 'ash' | 'ballad' | 'coral' | 'echo' | 'sage' | 'shimmer' | 'verse' | 'marin' | 'cedar'
        - object — Custom voice reference.
          - `id` string, required — The custom voice ID, e.g. `voice_1234`.
      - `speed` number — 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.
  - `include` string[] — Additional fields to include in server outputs. `item.input_audio_transcription.logprobs`: Include logprobs for input audio transcription.
  - `tracing` union — Realtime API can write session traces to the [Traces Dashboard](https://platform.openai.com/logs?api=traces). 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.
    - 'auto' — Enables tracing and sets default values for tracing configuration options. Always `auto`.
    - object — Granular configuration for tracing.
      - `workflow_name` string — The name of the workflow to attach to this trace. This is used to name the trace in the Traces Dashboard.
      - `group_id` string — The group id to attach to this trace to enable filtering and grouping in the Traces Dashboard.
      - `metadata` object — The arbitrary metadata to attach to this trace to enable filtering in the Traces Dashboard.
  - `tools` union[] — Tools available to the model.
    - union
      - RealtimeFunctionTool
        - `type` 'function' — The type of the tool, i.e. `function`.
        - `name` string — The name of the function.
        - `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).
        - `parameters` object — Parameters of the function in JSON Schema.
      - MCPTool — Give the model access to additional tools via remote Model Context Protocol (MCP) servers. [Learn more about MCP](https://platform.openai.com/docs/guides/tools-remote-mcp).
        - `type` 'mcp', required — The type of the MCP tool. Always `mcp`.
        - `server_label` string, required — A label for this MCP server, used to identify it in tool calls.
        - `server_url` string, uri — The URL for the MCP server. One of `server_url`, `connector_id`, or `tunnel_id` must be provided.
        - `connector_id` 'connector_dropbox' | 'connector_gmail' | 'connector_googlecalendar' | 'connector_googledrive' | 'connector_microsoftteams' | 'connector_outlookcalendar' | 'connector_outlookemail' | 'connector_sharepoint' — 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](https://platform.openai.com/docs/guides/tools-remote-mcp#connectors). 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`
        - `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.
        - `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.
        - `server_description` string — Optional description of the MCP server, used to provide more context.
        - `headers` object, nullable — Optional HTTP headers to send to the MCP server. Use for authentication or other purposes.
        - `allowed_tools` union
          - string[] — A string array of allowed tool names
          - MCPToolFilter — A filter object to specify which tools are allowed.
            - `tool_names` string[] — List of allowed tool names.
            - `read_only` boolean — Indicates whether or not a tool modifies data or is read-only. If an MCP server is [annotated with `readOnlyHint`](https://modelcontextprotocol.io/specification/2025-06-18/schema#toolannotations-readonlyhint), it will match this filter.
        - `allowed_callers` CallableToolAllowedCaller[], nullable — The tool invocation context(s).
        - `require_approval` union
          - object — 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` MCPToolFilter — A filter object to specify which tools are allowed.
              - …
            - `never` MCPToolFilter — A filter object to specify which tools are allowed.
              - …
          - '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.
        - `defer_loading` boolean — Whether this MCP tool is deferred and discovered via tool search.
  - `tool_choice` union — How the model chooses tools. Provide one of the string modes or force a specific function/MCP tool.
    - '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.
    - ToolChoiceFunction — Use this option to force the model to call a specific function.
      - `type` 'function', required — For function calling, the type is always `function`.
      - `name` string, required — The name of the function to call.
    - ToolChoiceMCP — Use this option to force the model to call a specific tool on a remote MCP server.
      - `type` 'mcp', required — For MCP tools, the type is always `mcp`.
      - `server_label` string, required — The label of the MCP server to use.
      - `name` string, nullable — The name of the tool to call on the server.
  - `parallel_tool_calls` boolean — Whether the model may call multiple tools in parallel. Only supported by reasoning Realtime models such as `gpt-realtime-2`.
  - `reasoning` RealtimeReasoning — Configuration for reasoning-capable Realtime models such as `gpt-realtime-2`.
    - `effort` 'minimal' | 'low' | 'medium' | 'high' | 'xhigh' — Constrains effort on reasoning for reasoning-capable Realtime models such as `gpt-realtime-2`.
  - `max_output_tokens` union — 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
    - 'inf'
  - `truncation` union — When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs. Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost. Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate. Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.
    - '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.
    - object — 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.
      - `type` 'retention_ratio', required — Use retention ratio truncation.
      - `retention_ratio` number, required — 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.
      - `token_limits` object — 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.
  - `prompt` Prompt, nullable — Reference to a prompt template and its variables. [Learn more](https://platform.openai.com/docs/guides/text?api-mode=responses#reusable-prompts).
    - `id` string, required — The unique identifier of the prompt template to use.
    - `version` string, nullable — Optional version of the prompt template.
    - `variables` ResponsePromptVariables, nullable — 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.

## Response `200`

Call accepted successfully.

---

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