Server events
These are events emitted from the OpenAI Realtime WebSocket server to the client.
Returned when an error occurs, which could be a client problem or a server problem. Most errors are recoverable and the session will stay open, we recommend to implementers to monitor and log error messages by default.
Details of the error.
Details of the error.
message: string A human-readable error message.
type: string The type of error (e.g., "invalid_request_error", "server_error").
code: optional string or null Error code, if any.
event_id: optional string or null The event_id of the client event that caused the error, if applicable.
param: optional string or null Parameter related to the error, if any.
Returned when a Session is created. Emitted automatically when a new connection is established as the first server event. This event will contain the default Session configuration.
session: RealtimeSessionCreateResponse { id, object, type, 13 more } or RealtimeTranscriptionSessionCreateResponse { id, object, type, 3 more } The session configuration.
session: RealtimeSessionCreateResponse { id, object, type, 13 more } or RealtimeTranscriptionSessionCreateResponse { id, object, type, 3 more }
The session configuration.
One of the following: RealtimeSessionCreateResponse { id, object, type, 13 more } 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.
type: "realtime" The type of session to create. Always realtime for the Realtime API.
audio: optional { input, output } Configuration for input and output audio.
input: optional { format, noise_reduction, transcription, turn_detection } format: optional RealtimeAudioFormats The format of the input audio.
One of the following: PCMAudio { rate, type } The PCM audio format. Only a 24kHz sample rate is supported.
rate: optional 24000 The sample rate of the audio. Always 24000.
type: optional "audio/pcm" The audio format. Always audio/pcm.
PCMUAudio { type } The G.711 μ-law format.
type: optional "audio/pcmu" The audio format. Always audio/pcmu.
PCMAAudio { type } The G.711 A-law format.
type: optional "audio/pcma" The audio format. Always audio/pcma.
noise_reduction: optional object or null (default: null) 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.
strength: optional number (default: 1) Input noise suppression strength. Higher values apply more suppression.
Defaults to 1 when noise reduction is first enabled. Omitting strength
from a session update preserves the current strength.
minimum0 maximum1 type: optional NoiseReductionType Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
One of the following: "near_field" "far_field" transcription: optional object or null 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.
keywords: optional array of string Words or phrases configured to guide transcription of the input audio.
language: optional string or null The language of the input audio.
languages: optional array of string The possible input audio languages configured for transcription, in ISO-639-1 format.
minItems1 model: optional string or "whisper-1" or "gpt-transcribe" or "gpt-live-transcribe" or 5 more The model used 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.
One of the following: string "whisper-1" or "gpt-transcribe" or "gpt-live-transcribe" or 5 more The model used 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.
One of the following: "gpt-transcribe" "gpt-live-transcribe" "gpt-realtime-whisper" "whisper-1" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-mini-transcribe" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-mini-transcribe-2025-12-15" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-transcribe" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-transcribe-diarize" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
prompt: optional string The prompt configured for input audio transcription, when present.
turn_detection: optional ServerVad or SemanticVad or null 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.
One of the following: ServerVad { type, create_response, idle_timeout_ms, 4 more } Server-side voice activity detection (VAD) which flips on when user speech is detected and off after a period of silence.
type: "server_vad" (default: "server_vad") Type of turn detection, server_vad to turn on simple Server VAD.
create_response: optional boolean (default: true) Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.
If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
idle_timeout_ms: optional integer or null 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.
minimum5000 maximum30000 interrupt_response: optional boolean (default: true) Whether or not to automatically interrupt (cancel) any ongoing response with output to the default
conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.
If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
prefix_padding_ms: optional 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: optional 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: optional 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.
SemanticVad { type, create_response, eagerness, interrupt_response } 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.
create_response: optional boolean (default: true) Whether or not to automatically generate a response when a VAD stop event occurs.
eagerness: optional "low" or "medium" or "high" or "auto" (default: "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.
One of the following: "low" "medium" "high" "auto" interrupt_response: optional boolean (default: true) Whether or not to automatically interrupt any ongoing response with output to the default
conversation (i.e. conversation of auto) when a VAD start event occurs.
output: optional { format, speed, voice } format: optional RealtimeAudioFormats The format of the output audio.
One of the following: PCMAudio { rate, type } The PCM audio format. Only a 24kHz sample rate is supported.
rate: optional 24000 The sample rate of the audio. Always 24000.
type: optional "audio/pcm" The audio format. Always audio/pcm.
PCMUAudio { type } The G.711 μ-law format.
type: optional "audio/pcmu" The audio format. Always audio/pcmu.
PCMAAudio { type } The G.711 A-law format.
type: optional "audio/pcma" The audio format. Always audio/pcma.
speed: optional number (default: 1) 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.
minimum0.25 maximum1.5 voice: optional string or "alloy" or "ash" or "ballad" or 7 more (default: "alloy") 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.
One of the following: string "alloy" or "ash" or "ballad" or 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.
One of the following: "alloy" "ash" "ballad" "coral" "echo" "sage" "shimmer" "verse" "marin" "cedar" expires_at: optional integer Expiration timestamp for the session, in seconds since epoch.
formatunixtime include: optional array of "item.input_audio_transcription.logprobs" or null Additional fields to include in server outputs.
item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
instructions: optional 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: optional number or "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.
One of the following: number "inf" model: optional string or "gpt-realtime" or "gpt-realtime-1.5" or "gpt-realtime-2" or 16 more The Realtime model used for this session.
One of the following: string "gpt-realtime" or "gpt-realtime-1.5" or "gpt-realtime-2" or 16 more The Realtime model used for this session.
One of the following: "gpt-realtime-1.5" "gpt-realtime-2" "gpt-realtime-2.1" "gpt-realtime-2.1-mini" "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-2025-10-06" "gpt-audio-1.5" "gpt-audio-mini-2025-10-06" "gpt-realtime" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-realtime-2025-08-28" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-realtime-mini" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-realtime-mini-2025-12-15" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-audio-mini" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-audio-mini-2025-12-15" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
output_modalities: optional array of "text" or "audio" (default: ["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.
One of the following: "text" "audio" prompt: optional ResponsePrompt or null Reference to a prompt template and its variables.
Learn more.
id: string The unique identifier of the prompt template to use.
variables: optional map[string or ResponseInputText or ResponseInputImage or ResponseInputFile] or null 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.
One of the following: string ResponseInputText { text, type, prompt_cache_breakpoint } A text input to the model.
text: string The text input to the model.
type: "input_text" (default: "input_text") The type of the input item. Always input_text.
prompt_cache_breakpoint: optional { mode, ttl } Marks the exact end of a reusable prompt prefix. When ttl is omitted, the breakpoint inherits the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
mode: "explicit" (default: "explicit") The breakpoint mode. Always explicit.
ttl: optional "30m" or "12h" The minimum lifetime of this cache breakpoint. Defaults to the request TTL.
One of the following: "30m" "12h" ResponseInputImage { detail, type, file_id, 2 more } An image input to the model. Learn about image inputs.
detail: ImageDetail The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.
One of the following: "low" "high" "auto" "original" type: "input_image" (default: "input_image") The type of the input item. Always input_image.
file_id: optional string or null The ID of the file to be sent to the model.
image_url: optional string or null The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.
formaturi prompt_cache_breakpoint: optional { mode, ttl } Marks the exact end of a reusable prompt prefix. When ttl is omitted, the breakpoint inherits the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
mode: "explicit" (default: "explicit") The breakpoint mode. Always explicit.
ttl: optional "30m" or "12h" The minimum lifetime of this cache breakpoint. Defaults to the request TTL.
One of the following: "30m" "12h" ResponseInputFile { type, detail, file_data, 4 more } A file input to the model.
type: "input_file" (default: "input_file") The type of the input item. Always input_file.
detail: optional "auto" or "low" or "high" The detail level of the file to be sent to the model. Use auto to let the system select the detail level; for GPT-5.6 and later models, auto uses high-quality rendering, which may increase input token usage. Use low for lower-cost rendering, or high to render the file at higher quality. Defaults to auto.
One of the following: "auto" "low" "high" file_data: optional string The content of the file to be sent to the model.
file_id: optional string or null The ID of the file to be sent to the model.
file_url: optional string The URL of the file to be sent to the model.
formaturi filename: optional string The name of the file to be sent to the model.
prompt_cache_breakpoint: optional { mode, ttl } Marks the exact end of a reusable prompt prefix. When ttl is omitted, the breakpoint inherits the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
mode: "explicit" (default: "explicit") The breakpoint mode. Always explicit.
ttl: optional "30m" or "12h" The minimum lifetime of this cache breakpoint. Defaults to the request TTL.
One of the following: "30m" "12h" version: optional string or null Optional version of the prompt template.
reasoning: optional RealtimeReasoning { effort } Configuration for reasoning-capable Realtime models such as gpt-realtime-2.
effort: optional RealtimeReasoningEffort (default: "low") Constrains effort on reasoning for reasoning-capable Realtime models such as
gpt-realtime-2.
One of the following: "minimal" "low" "medium" "high" "xhigh" tool_choice: optional ToolChoiceOptions or ToolChoiceFunction or ToolChoiceMcp (default: "auto") How the model chooses tools. Provide one of the string modes or force a specific
function/MCP tool.
One of the following: ToolChoiceOptions = "none" or "auto" or "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.
One of the following: "none" "auto" "required" ToolChoiceFunction { name, type } 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.
ToolChoiceMcp { server_label, type, name } 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.
name: optional string or null The name of the tool to call on the server.
tools: optional array of RealtimeFunctionTool or McpTool Tools available to the model.
One of the following: RealtimeFunctionTool { description, name, parameters, type } description: optional 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: optional string The name of the function.
parameters: optional unknown Parameters of the function in JSON Schema.
type: optional "function" The type of the tool, i.e. function.
McpTool { server_label, type, allowed_callers, 9 more } 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.
allowed_callers: optional array of "direct" or "programmatic" or null The tool invocation context(s).
minItems1 One of the following: "direct" "programmatic" allowed_tools: optional array of string or McpToolFilter or null List of allowed tool names or a filter object.
One of the following: McpAllowedTools = array of string A string array of allowed tool names
McpToolFilter { read_only, tool_names } A filter object to specify which tools are allowed.
read_only: optional boolean Indicates whether or not a tool modifies data or is read-only. If an
MCP server is annotated with readOnlyHint,
it will match this filter.
tool_names: optional array of string List of allowed tool names.
authorization: optional 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: optional "connector_dropbox" or "connector_gmail" or "connector_googlecalendar" or 5 more Deprecated.
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.
This field is deprecated for models released after September 1, 2026.
Use server_url to connect to a remote MCP server, or tunnel_id to
connect through a Secure MCP Tunnel.
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
One of the following: "connector_dropbox" "connector_gmail" "connector_googlecalendar" "connector_googledrive" "connector_microsoftteams" "connector_outlookcalendar" "connector_outlookemail" "connector_sharepoint" defer_loading: optional boolean Whether this MCP tool is deferred and discovered via tool search.
headers: optional map[string] or null Optional HTTP headers to send to the MCP server. Use for authentication
or other purposes.
require_approval: optional McpToolApprovalFilter or "always" or "never" or null (default: "always") Specify which of the MCP server's tools require approval.
One of the following: McpToolApprovalFilter { always, never } Specify which of the MCP server's tools require approval. Can be
always, never, or a filter object associated with tools
that require approval.
always: optional { read_only, tool_names } A filter object to specify which tools are allowed.
read_only: optional boolean Indicates whether or not a tool modifies data or is read-only. If an
MCP server is annotated with readOnlyHint,
it will match this filter.
tool_names: optional array of string List of allowed tool names.
never: optional { read_only, tool_names } A filter object to specify which tools are allowed.
read_only: optional boolean Indicates whether or not a tool modifies data or is read-only. If an
MCP server is annotated with readOnlyHint,
it will match this filter.
tool_names: optional array of string List of allowed tool names.
McpToolApprovalSetting = "always" or "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.
One of the following: "always" "never" server_description: optional string Optional description of the MCP server, used to provide more context.
server_url: optional string The URL for the MCP server. One of server_url, connector_id, or
tunnel_id must be provided.
formaturi tunnel_id: optional 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.
pattern^tunnel_[a-z0-9]{32}$ tracing: optional "auto" or TracingConfiguration or null 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.
One of the following: Auto = "auto" Enables tracing and sets default values for tracing configuration options. Always auto.
TracingConfiguration { group_id, metadata, workflow_name } Granular configuration for tracing.
group_id: optional string The group id to attach to this trace to enable filtering and
grouping in the Traces Dashboard.
metadata: optional unknown The arbitrary metadata to attach to this trace to enable
filtering in the Traces Dashboard.
workflow_name: optional string The name of the workflow to attach to this trace. This is used to
name the trace in the Traces Dashboard.
truncation: optional RealtimeTruncation When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.
Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.
Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.
Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.
One of the following: "auto" or "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.
One of the following: "auto" "disabled" RetentionRatioTruncation { retention_ratio, type, token_limits } 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: number 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.
minimum0 maximum1 type: "retention_ratio" Use retention ratio truncation.
token_limits: optional { post_instructions } Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.
post_instructions: optional 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.
minimum0 RealtimeTranscriptionSessionCreateResponse { id, object, type, 3 more } 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.
audio: optional { input } Configuration for input audio for the session.
input: optional { format, noise_reduction, transcription, turn_detection } format: optional RealtimeAudioFormats The PCM audio format. Only a 24kHz sample rate is supported.
One of the following: PCMAudio { rate, type } The PCM audio format. Only a 24kHz sample rate is supported.
rate: optional 24000 The sample rate of the audio. Always 24000.
type: optional "audio/pcm" The audio format. Always audio/pcm.
PCMUAudio { type } The G.711 μ-law format.
type: optional "audio/pcmu" The audio format. Always audio/pcmu.
PCMAAudio { type } The G.711 A-law format.
type: optional "audio/pcma" The audio format. Always audio/pcma.
noise_reduction: optional object or null Configuration for input audio noise reduction.
strength: optional number (default: 1) Input noise suppression strength. Higher values apply more suppression.
Defaults to 1 when noise reduction is first enabled. Omitting strength
from a session update preserves the current strength.
minimum0 maximum1 type: optional NoiseReductionType Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
One of the following: "near_field" "far_field" transcription: optional object or null Configuration of the transcription model.
keywords: optional array of string Words or phrases configured to guide transcription of the input audio.
language: optional string or null The language of the input audio.
languages: optional array of string The possible input audio languages configured for transcription, in ISO-639-1 format.
minItems1 model: optional string or "whisper-1" or "gpt-transcribe" or "gpt-live-transcribe" or 5 more The model used 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.
One of the following: string "whisper-1" or "gpt-transcribe" or "gpt-live-transcribe" or 5 more The model used 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.
One of the following: "gpt-transcribe" "gpt-live-transcribe" "gpt-realtime-whisper" "whisper-1" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-mini-transcribe" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-mini-transcribe-2025-12-15" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-transcribe" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-transcribe-diarize" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
prompt: optional string The prompt configured for input audio transcription, when present.
turn_detection: optional RealtimeTranscriptionSessionTurnDetection or null 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: optional integer Amount of audio to include before the VAD detected speech (in
milliseconds). Defaults to 300ms.
silence_duration_ms: optional 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: optional number 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: optional string Type of turn detection, only server_vad is currently supported.
expires_at: optional integer Expiration timestamp for the session, in seconds since epoch.
formatunixtime include: optional array of "item.input_audio_transcription.logprobs" or null Additional fields to include in server outputs.
item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
Returned when a session is updated with a session.update event, unless
there is an error.
session: RealtimeSessionCreateResponse { id, object, type, 13 more } or RealtimeTranscriptionSessionCreateResponse { id, object, type, 3 more } The session configuration.
session: RealtimeSessionCreateResponse { id, object, type, 13 more } or RealtimeTranscriptionSessionCreateResponse { id, object, type, 3 more }
The session configuration.
One of the following: RealtimeSessionCreateResponse { id, object, type, 13 more } 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.
type: "realtime" The type of session to create. Always realtime for the Realtime API.
audio: optional { input, output } Configuration for input and output audio.
input: optional { format, noise_reduction, transcription, turn_detection } format: optional RealtimeAudioFormats The format of the input audio.
One of the following: PCMAudio { rate, type } The PCM audio format. Only a 24kHz sample rate is supported.
rate: optional 24000 The sample rate of the audio. Always 24000.
type: optional "audio/pcm" The audio format. Always audio/pcm.
PCMUAudio { type } The G.711 μ-law format.
type: optional "audio/pcmu" The audio format. Always audio/pcmu.
PCMAAudio { type } The G.711 A-law format.
type: optional "audio/pcma" The audio format. Always audio/pcma.
noise_reduction: optional object or null (default: null) 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.
strength: optional number (default: 1) Input noise suppression strength. Higher values apply more suppression.
Defaults to 1 when noise reduction is first enabled. Omitting strength
from a session update preserves the current strength.
minimum0 maximum1 type: optional NoiseReductionType Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
One of the following: "near_field" "far_field" transcription: optional object or null 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.
keywords: optional array of string Words or phrases configured to guide transcription of the input audio.
language: optional string or null The language of the input audio.
languages: optional array of string The possible input audio languages configured for transcription, in ISO-639-1 format.
minItems1 model: optional string or "whisper-1" or "gpt-transcribe" or "gpt-live-transcribe" or 5 more The model used 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.
One of the following: string "whisper-1" or "gpt-transcribe" or "gpt-live-transcribe" or 5 more The model used 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.
One of the following: "gpt-transcribe" "gpt-live-transcribe" "gpt-realtime-whisper" "whisper-1" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-mini-transcribe" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-mini-transcribe-2025-12-15" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-transcribe" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-transcribe-diarize" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
prompt: optional string The prompt configured for input audio transcription, when present.
turn_detection: optional ServerVad or SemanticVad or null 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.
One of the following: ServerVad { type, create_response, idle_timeout_ms, 4 more } Server-side voice activity detection (VAD) which flips on when user speech is detected and off after a period of silence.
type: "server_vad" (default: "server_vad") Type of turn detection, server_vad to turn on simple Server VAD.
create_response: optional boolean (default: true) Whether or not to automatically generate a response when a VAD stop event occurs. If interrupt_response is set to false this may fail to create a response if the model is already responding.
If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
idle_timeout_ms: optional integer or null 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.
minimum5000 maximum30000 interrupt_response: optional boolean (default: true) Whether or not to automatically interrupt (cancel) any ongoing response with output to the default
conversation (i.e. conversation of auto) when a VAD start event occurs. If true then the response will be cancelled, otherwise it will continue until complete.
If both create_response and interrupt_response are set to false, the model will never respond automatically but VAD events will still be emitted.
prefix_padding_ms: optional 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: optional 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: optional 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.
SemanticVad { type, create_response, eagerness, interrupt_response } 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.
create_response: optional boolean (default: true) Whether or not to automatically generate a response when a VAD stop event occurs.
eagerness: optional "low" or "medium" or "high" or "auto" (default: "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.
One of the following: "low" "medium" "high" "auto" interrupt_response: optional boolean (default: true) Whether or not to automatically interrupt any ongoing response with output to the default
conversation (i.e. conversation of auto) when a VAD start event occurs.
output: optional { format, speed, voice } format: optional RealtimeAudioFormats The format of the output audio.
One of the following: PCMAudio { rate, type } The PCM audio format. Only a 24kHz sample rate is supported.
rate: optional 24000 The sample rate of the audio. Always 24000.
type: optional "audio/pcm" The audio format. Always audio/pcm.
PCMUAudio { type } The G.711 μ-law format.
type: optional "audio/pcmu" The audio format. Always audio/pcmu.
PCMAAudio { type } The G.711 A-law format.
type: optional "audio/pcma" The audio format. Always audio/pcma.
speed: optional number (default: 1) 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.
minimum0.25 maximum1.5 voice: optional string or "alloy" or "ash" or "ballad" or 7 more (default: "alloy") 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.
One of the following: string "alloy" or "ash" or "ballad" or 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.
One of the following: "alloy" "ash" "ballad" "coral" "echo" "sage" "shimmer" "verse" "marin" "cedar" expires_at: optional integer Expiration timestamp for the session, in seconds since epoch.
formatunixtime include: optional array of "item.input_audio_transcription.logprobs" or null Additional fields to include in server outputs.
item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
instructions: optional 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: optional number or "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.
One of the following: number "inf" model: optional string or "gpt-realtime" or "gpt-realtime-1.5" or "gpt-realtime-2" or 16 more The Realtime model used for this session.
One of the following: string "gpt-realtime" or "gpt-realtime-1.5" or "gpt-realtime-2" or 16 more The Realtime model used for this session.
One of the following: "gpt-realtime-1.5" "gpt-realtime-2" "gpt-realtime-2.1" "gpt-realtime-2.1-mini" "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-2025-10-06" "gpt-audio-1.5" "gpt-audio-mini-2025-10-06" "gpt-realtime" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-realtime-2025-08-28" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-realtime-mini" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-realtime-mini-2025-12-15" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-audio-mini" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-audio-mini-2025-12-15" Deprecated. Announced shutdown date: 2027-01-20. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
output_modalities: optional array of "text" or "audio" (default: ["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.
One of the following: "text" "audio" prompt: optional ResponsePrompt or null Reference to a prompt template and its variables.
Learn more.
id: string The unique identifier of the prompt template to use.
variables: optional map[string or ResponseInputText or ResponseInputImage or ResponseInputFile] or null 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.
One of the following: string ResponseInputText { text, type, prompt_cache_breakpoint } A text input to the model.
text: string The text input to the model.
type: "input_text" (default: "input_text") The type of the input item. Always input_text.
prompt_cache_breakpoint: optional { mode, ttl } Marks the exact end of a reusable prompt prefix. When ttl is omitted, the breakpoint inherits the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
mode: "explicit" (default: "explicit") The breakpoint mode. Always explicit.
ttl: optional "30m" or "12h" The minimum lifetime of this cache breakpoint. Defaults to the request TTL.
One of the following: "30m" "12h" ResponseInputImage { detail, type, file_id, 2 more } An image input to the model. Learn about image inputs.
detail: ImageDetail The detail level of the image to be sent to the model. One of high, low, auto, or original. Defaults to auto.
One of the following: "low" "high" "auto" "original" type: "input_image" (default: "input_image") The type of the input item. Always input_image.
file_id: optional string or null The ID of the file to be sent to the model.
image_url: optional string or null The URL of the image to be sent to the model. A fully qualified URL or base64 encoded image in a data URL.
formaturi prompt_cache_breakpoint: optional { mode, ttl } Marks the exact end of a reusable prompt prefix. When ttl is omitted, the breakpoint inherits the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
mode: "explicit" (default: "explicit") The breakpoint mode. Always explicit.
ttl: optional "30m" or "12h" The minimum lifetime of this cache breakpoint. Defaults to the request TTL.
One of the following: "30m" "12h" ResponseInputFile { type, detail, file_data, 4 more } A file input to the model.
type: "input_file" (default: "input_file") The type of the input item. Always input_file.
detail: optional "auto" or "low" or "high" The detail level of the file to be sent to the model. Use auto to let the system select the detail level; for GPT-5.6 and later models, auto uses high-quality rendering, which may increase input token usage. Use low for lower-cost rendering, or high to render the file at higher quality. Defaults to auto.
One of the following: "auto" "low" "high" file_data: optional string The content of the file to be sent to the model.
file_id: optional string or null The ID of the file to be sent to the model.
file_url: optional string The URL of the file to be sent to the model.
formaturi filename: optional string The name of the file to be sent to the model.
prompt_cache_breakpoint: optional { mode, ttl } Marks the exact end of a reusable prompt prefix. When ttl is omitted, the breakpoint inherits the request's prompt_cache_options.ttl; the boundary is not rounded to a token block.
mode: "explicit" (default: "explicit") The breakpoint mode. Always explicit.
ttl: optional "30m" or "12h" The minimum lifetime of this cache breakpoint. Defaults to the request TTL.
One of the following: "30m" "12h" version: optional string or null Optional version of the prompt template.
reasoning: optional RealtimeReasoning { effort } Configuration for reasoning-capable Realtime models such as gpt-realtime-2.
effort: optional RealtimeReasoningEffort (default: "low") Constrains effort on reasoning for reasoning-capable Realtime models such as
gpt-realtime-2.
One of the following: "minimal" "low" "medium" "high" "xhigh" tool_choice: optional ToolChoiceOptions or ToolChoiceFunction or ToolChoiceMcp (default: "auto") How the model chooses tools. Provide one of the string modes or force a specific
function/MCP tool.
One of the following: ToolChoiceOptions = "none" or "auto" or "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.
One of the following: "none" "auto" "required" ToolChoiceFunction { name, type } 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.
ToolChoiceMcp { server_label, type, name } 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.
name: optional string or null The name of the tool to call on the server.
tools: optional array of RealtimeFunctionTool or McpTool Tools available to the model.
One of the following: RealtimeFunctionTool { description, name, parameters, type } description: optional 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: optional string The name of the function.
parameters: optional unknown Parameters of the function in JSON Schema.
type: optional "function" The type of the tool, i.e. function.
McpTool { server_label, type, allowed_callers, 9 more } 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.
allowed_callers: optional array of "direct" or "programmatic" or null The tool invocation context(s).
minItems1 One of the following: "direct" "programmatic" allowed_tools: optional array of string or McpToolFilter or null List of allowed tool names or a filter object.
One of the following: McpAllowedTools = array of string A string array of allowed tool names
McpToolFilter { read_only, tool_names } A filter object to specify which tools are allowed.
read_only: optional boolean Indicates whether or not a tool modifies data or is read-only. If an
MCP server is annotated with readOnlyHint,
it will match this filter.
tool_names: optional array of string List of allowed tool names.
authorization: optional 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: optional "connector_dropbox" or "connector_gmail" or "connector_googlecalendar" or 5 more Deprecated.
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.
This field is deprecated for models released after September 1, 2026.
Use server_url to connect to a remote MCP server, or tunnel_id to
connect through a Secure MCP Tunnel.
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
One of the following: "connector_dropbox" "connector_gmail" "connector_googlecalendar" "connector_googledrive" "connector_microsoftteams" "connector_outlookcalendar" "connector_outlookemail" "connector_sharepoint" defer_loading: optional boolean Whether this MCP tool is deferred and discovered via tool search.
headers: optional map[string] or null Optional HTTP headers to send to the MCP server. Use for authentication
or other purposes.
require_approval: optional McpToolApprovalFilter or "always" or "never" or null (default: "always") Specify which of the MCP server's tools require approval.
One of the following: McpToolApprovalFilter { always, never } Specify which of the MCP server's tools require approval. Can be
always, never, or a filter object associated with tools
that require approval.
always: optional { read_only, tool_names } A filter object to specify which tools are allowed.
read_only: optional boolean Indicates whether or not a tool modifies data or is read-only. If an
MCP server is annotated with readOnlyHint,
it will match this filter.
tool_names: optional array of string List of allowed tool names.
never: optional { read_only, tool_names } A filter object to specify which tools are allowed.
read_only: optional boolean Indicates whether or not a tool modifies data or is read-only. If an
MCP server is annotated with readOnlyHint,
it will match this filter.
tool_names: optional array of string List of allowed tool names.
McpToolApprovalSetting = "always" or "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.
One of the following: "always" "never" server_description: optional string Optional description of the MCP server, used to provide more context.
server_url: optional string The URL for the MCP server. One of server_url, connector_id, or
tunnel_id must be provided.
formaturi tunnel_id: optional 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.
pattern^tunnel_[a-z0-9]{32}$ tracing: optional "auto" or TracingConfiguration or null 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.
One of the following: Auto = "auto" Enables tracing and sets default values for tracing configuration options. Always auto.
TracingConfiguration { group_id, metadata, workflow_name } Granular configuration for tracing.
group_id: optional string The group id to attach to this trace to enable filtering and
grouping in the Traces Dashboard.
metadata: optional unknown The arbitrary metadata to attach to this trace to enable
filtering in the Traces Dashboard.
workflow_name: optional string The name of the workflow to attach to this trace. This is used to
name the trace in the Traces Dashboard.
truncation: optional RealtimeTruncation When the number of tokens in a conversation exceeds the model's input token limit, the conversation be truncated, meaning messages (starting from the oldest) will not be included in the model's context. A 32k context model with 4,096 max output tokens can only include 28,224 tokens in the context before truncation occurs.
Clients can configure truncation behavior to truncate with a lower max token limit, which is an effective way to control token usage and cost.
Truncation will reduce the number of cached tokens on the next turn (busting the cache), since messages are dropped from the beginning of the context. However, clients can also configure truncation to retain messages up to a fraction of the maximum context size, which will reduce the need for future truncations and thus improve the cache rate.
Truncation can be disabled entirely, which means the server will never truncate but would instead return an error if the conversation exceeds the model's input token limit.
One of the following: "auto" or "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.
One of the following: "auto" "disabled" RetentionRatioTruncation { retention_ratio, type, token_limits } 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: number 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.
minimum0 maximum1 type: "retention_ratio" Use retention ratio truncation.
token_limits: optional { post_instructions } Optional custom token limits for this truncation strategy. If not provided, the model's default token limits will be used.
post_instructions: optional 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.
minimum0 RealtimeTranscriptionSessionCreateResponse { id, object, type, 3 more } 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.
audio: optional { input } Configuration for input audio for the session.
input: optional { format, noise_reduction, transcription, turn_detection } format: optional RealtimeAudioFormats The PCM audio format. Only a 24kHz sample rate is supported.
One of the following: PCMAudio { rate, type } The PCM audio format. Only a 24kHz sample rate is supported.
rate: optional 24000 The sample rate of the audio. Always 24000.
type: optional "audio/pcm" The audio format. Always audio/pcm.
PCMUAudio { type } The G.711 μ-law format.
type: optional "audio/pcmu" The audio format. Always audio/pcmu.
PCMAAudio { type } The G.711 A-law format.
type: optional "audio/pcma" The audio format. Always audio/pcma.
noise_reduction: optional object or null Configuration for input audio noise reduction.
strength: optional number (default: 1) Input noise suppression strength. Higher values apply more suppression.
Defaults to 1 when noise reduction is first enabled. Omitting strength
from a session update preserves the current strength.
minimum0 maximum1 type: optional NoiseReductionType Type of noise reduction. near_field is for close-talking microphones such as headphones, far_field is for far-field microphones such as laptop or conference room microphones.
One of the following: "near_field" "far_field" transcription: optional object or null Configuration of the transcription model.
keywords: optional array of string Words or phrases configured to guide transcription of the input audio.
language: optional string or null The language of the input audio.
languages: optional array of string The possible input audio languages configured for transcription, in ISO-639-1 format.
minItems1 model: optional string or "whisper-1" or "gpt-transcribe" or "gpt-live-transcribe" or 5 more The model used 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.
One of the following: string "whisper-1" or "gpt-transcribe" or "gpt-live-transcribe" or 5 more The model used 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.
One of the following: "gpt-transcribe" "gpt-live-transcribe" "gpt-realtime-whisper" "whisper-1" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-mini-transcribe" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-mini-transcribe-2025-12-15" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-transcribe" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
"gpt-4o-transcribe-diarize" Deprecated. Announced shutdown date: 2027-02-26. See https://developers.openai.com/api/docs/deprecations for details and recommended replacements.
prompt: optional string The prompt configured for input audio transcription, when present.
turn_detection: optional RealtimeTranscriptionSessionTurnDetection or null 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: optional integer Amount of audio to include before the VAD detected speech (in
milliseconds). Defaults to 300ms.
silence_duration_ms: optional 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: optional number 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: optional string Type of turn detection, only server_vad is currently supported.
expires_at: optional integer Expiration timestamp for the session, in seconds since epoch.
formatunixtime include: optional array of "item.input_audio_transcription.logprobs" or null Additional fields to include in server outputs.
item.input_audio_transcription.logprobs: Include logprobs for input audio transcription.
Sent by the server when an Item is added to the default Conversation. This can happen in several cases:
- When the client sends a
conversation.item.createevent. - When the input audio buffer is committed. In this case the item will be a user message containing the audio from the buffer.
- When the model is generating a Response. In this case the
conversation.item.addedevent will be sent when the model starts generating a specific Item, and thus it will not yet have any content (andstatuswill bein_progress).
The event will include the full content of the Item (except when model is generating a Response) except for audio data, which can be retrieved separately with a conversation.item.retrieve event if necessary.
A single item within a Realtime conversation.
A single item within a Realtime conversation.
One of the following: RealtimeConversationItemSystemMessage { content, role, type, 3 more } A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.
content: array of { text, type } The content of the message.
text: optional string The text content.
type: optional "input_text" The content type. Always input_text for system messages.
role: "system" The role of the message sender. Always system.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemUserMessage { content, role, type, 3 more } A user message item in a Realtime conversation.
content: array of { audio, detail, image_url, 3 more } The content of the message.
audio: optional string Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
detail: optional "auto" or "low" or "high" (default: "auto") The detail level of the image (for input_image). auto will default to high.
One of the following: "auto" "low" "high" image_url: optional string Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.
formaturi text: optional string The text content (for input_text).
transcript: optional string Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.
type: optional "input_text" or "input_audio" or "input_image" The content type (input_text, input_audio, or input_image).
One of the following: "input_text" "input_audio" "input_image" role: "user" The role of the message sender. Always user.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemAssistantMessage { content, role, type, 3 more } An assistant message item in a Realtime conversation.
content: array of { audio, text, transcript, type } The content of the message.
audio: optional string Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
text: optional string The text content.
transcript: optional string The transcript of the audio content, this will always be present if the output type is audio.
type: optional "output_text" or "output_audio" The content type, output_text or output_audio depending on the session output_modalities configuration.
One of the following: "output_text" "output_audio" role: "assistant" The role of the message sender. Always assistant.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCall { arguments, name, type, 4 more } A function call item in a Realtime conversation.
arguments: string The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.
name: string The name of the function being called.
type: "function_call" The type of the item. Always function_call.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
call_id: optional string The ID of the function call.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCallOutput { call_id, output, type, 3 more } A function call output item in a Realtime conversation.
call_id: string The ID of the function call this output is for.
output: string The output of the function call, this is free text and can contain any information or simply be empty.
type: "function_call_output" The type of the item. Always function_call_output.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeMcpApprovalResponse { id, approval_request_id, approve, 2 more } A Realtime item responding to an MCP approval request.
id: string The unique ID of the approval response.
approval_request_id: string The ID of the approval request being answered.
approve: boolean Whether the request was approved.
type: "mcp_approval_response" The type of the item. Always mcp_approval_response.
reason: optional string or null Optional reason for the decision.
RealtimeMcpListTools { server_label, tools, type, id } A Realtime item listing tools available on an MCP server.
server_label: string The label of the MCP server.
tools: array of { input_schema, name, annotations, description } The tools available on the server.
input_schema: unknown The JSON schema describing the tool's input.
name: string The name of the tool.
annotations: optional unknown or null Additional annotations about the tool.
description: optional string or null The description of the tool.
type: "mcp_list_tools" The type of the item. Always mcp_list_tools.
id: optional string The unique ID of the list.
RealtimeMcpToolCall { id, arguments, name, 5 more } A Realtime item representing an invocation of a tool on an MCP server.
id: string The unique ID of the tool call.
arguments: string A JSON string of the arguments passed to the tool.
name: string The name of the tool that was run.
server_label: string The label of the MCP server running the tool.
type: "mcp_call" The type of the item. Always mcp_call.
approval_request_id: optional string or null The ID of an associated approval request, if any.
error: optional RealtimeMcpProtocolError or RealtimeMcpToolExecutionError or RealtimeMcphttpError or null The error from the tool call, if any.
One of the following: RealtimeMcpProtocolError { code, message, type } code: integer message: string type: "protocol_error" RealtimeMcpToolExecutionError { message, type } message: string type: "tool_execution_error" RealtimeMcphttpError { code, message, type } code: integer message: string type: "http_error" output: optional string or null The output from the tool call.
RealtimeMcpApprovalRequest { id, arguments, name, 2 more } A Realtime item requesting human approval of a tool invocation.
id: string The unique ID of the approval request.
arguments: string A JSON string of arguments for the tool.
name: string The name of the tool to run.
server_label: string The label of the MCP server making the request.
type: "mcp_approval_request" The type of the item. Always mcp_approval_request.
Returned when a conversation item is finalized.
The event will include the full content of the Item except for audio data, which can be retrieved separately with a conversation.item.retrieve event if needed.
A single item within a Realtime conversation.
A single item within a Realtime conversation.
One of the following: RealtimeConversationItemSystemMessage { content, role, type, 3 more } A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.
content: array of { text, type } The content of the message.
text: optional string The text content.
type: optional "input_text" The content type. Always input_text for system messages.
role: "system" The role of the message sender. Always system.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemUserMessage { content, role, type, 3 more } A user message item in a Realtime conversation.
content: array of { audio, detail, image_url, 3 more } The content of the message.
audio: optional string Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
detail: optional "auto" or "low" or "high" (default: "auto") The detail level of the image (for input_image). auto will default to high.
One of the following: "auto" "low" "high" image_url: optional string Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.
formaturi text: optional string The text content (for input_text).
transcript: optional string Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.
type: optional "input_text" or "input_audio" or "input_image" The content type (input_text, input_audio, or input_image).
One of the following: "input_text" "input_audio" "input_image" role: "user" The role of the message sender. Always user.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemAssistantMessage { content, role, type, 3 more } An assistant message item in a Realtime conversation.
content: array of { audio, text, transcript, type } The content of the message.
audio: optional string Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
text: optional string The text content.
transcript: optional string The transcript of the audio content, this will always be present if the output type is audio.
type: optional "output_text" or "output_audio" The content type, output_text or output_audio depending on the session output_modalities configuration.
One of the following: "output_text" "output_audio" role: "assistant" The role of the message sender. Always assistant.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCall { arguments, name, type, 4 more } A function call item in a Realtime conversation.
arguments: string The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.
name: string The name of the function being called.
type: "function_call" The type of the item. Always function_call.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
call_id: optional string The ID of the function call.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCallOutput { call_id, output, type, 3 more } A function call output item in a Realtime conversation.
call_id: string The ID of the function call this output is for.
output: string The output of the function call, this is free text and can contain any information or simply be empty.
type: "function_call_output" The type of the item. Always function_call_output.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeMcpApprovalResponse { id, approval_request_id, approve, 2 more } A Realtime item responding to an MCP approval request.
id: string The unique ID of the approval response.
approval_request_id: string The ID of the approval request being answered.
approve: boolean Whether the request was approved.
type: "mcp_approval_response" The type of the item. Always mcp_approval_response.
reason: optional string or null Optional reason for the decision.
RealtimeMcpListTools { server_label, tools, type, id } A Realtime item listing tools available on an MCP server.
server_label: string The label of the MCP server.
tools: array of { input_schema, name, annotations, description } The tools available on the server.
input_schema: unknown The JSON schema describing the tool's input.
name: string The name of the tool.
annotations: optional unknown or null Additional annotations about the tool.
description: optional string or null The description of the tool.
type: "mcp_list_tools" The type of the item. Always mcp_list_tools.
id: optional string The unique ID of the list.
RealtimeMcpToolCall { id, arguments, name, 5 more } A Realtime item representing an invocation of a tool on an MCP server.
id: string The unique ID of the tool call.
arguments: string A JSON string of the arguments passed to the tool.
name: string The name of the tool that was run.
server_label: string The label of the MCP server running the tool.
type: "mcp_call" The type of the item. Always mcp_call.
approval_request_id: optional string or null The ID of an associated approval request, if any.
error: optional RealtimeMcpProtocolError or RealtimeMcpToolExecutionError or RealtimeMcphttpError or null The error from the tool call, if any.
One of the following: RealtimeMcpProtocolError { code, message, type } code: integer message: string type: "protocol_error" RealtimeMcpToolExecutionError { message, type } message: string type: "tool_execution_error" RealtimeMcphttpError { code, message, type } code: integer message: string type: "http_error" output: optional string or null The output from the tool call.
RealtimeMcpApprovalRequest { id, arguments, name, 2 more } A Realtime item requesting human approval of a tool invocation.
id: string The unique ID of the approval request.
arguments: string A JSON string of arguments for the tool.
name: string The name of the tool to run.
server_label: string The label of the MCP server making the request.
type: "mcp_approval_request" The type of the item. Always mcp_approval_request.
Returned when a conversation item is retrieved with conversation.item.retrieve. This is provided as a way to fetch the server's representation of an item, for example to get access to the post-processed audio data after noise cancellation and VAD. It includes the full content of the Item, including audio data.
A single item within a Realtime conversation.
A single item within a Realtime conversation.
One of the following: RealtimeConversationItemSystemMessage { content, role, type, 3 more } A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.
content: array of { text, type } The content of the message.
text: optional string The text content.
type: optional "input_text" The content type. Always input_text for system messages.
role: "system" The role of the message sender. Always system.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemUserMessage { content, role, type, 3 more } A user message item in a Realtime conversation.
content: array of { audio, detail, image_url, 3 more } The content of the message.
audio: optional string Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
detail: optional "auto" or "low" or "high" (default: "auto") The detail level of the image (for input_image). auto will default to high.
One of the following: "auto" "low" "high" image_url: optional string Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.
formaturi text: optional string The text content (for input_text).
transcript: optional string Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.
type: optional "input_text" or "input_audio" or "input_image" The content type (input_text, input_audio, or input_image).
One of the following: "input_text" "input_audio" "input_image" role: "user" The role of the message sender. Always user.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemAssistantMessage { content, role, type, 3 more } An assistant message item in a Realtime conversation.
content: array of { audio, text, transcript, type } The content of the message.
audio: optional string Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
text: optional string The text content.
transcript: optional string The transcript of the audio content, this will always be present if the output type is audio.
type: optional "output_text" or "output_audio" The content type, output_text or output_audio depending on the session output_modalities configuration.
One of the following: "output_text" "output_audio" role: "assistant" The role of the message sender. Always assistant.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCall { arguments, name, type, 4 more } A function call item in a Realtime conversation.
arguments: string The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.
name: string The name of the function being called.
type: "function_call" The type of the item. Always function_call.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
call_id: optional string The ID of the function call.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCallOutput { call_id, output, type, 3 more } A function call output item in a Realtime conversation.
call_id: string The ID of the function call this output is for.
output: string The output of the function call, this is free text and can contain any information or simply be empty.
type: "function_call_output" The type of the item. Always function_call_output.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeMcpApprovalResponse { id, approval_request_id, approve, 2 more } A Realtime item responding to an MCP approval request.
id: string The unique ID of the approval response.
approval_request_id: string The ID of the approval request being answered.
approve: boolean Whether the request was approved.
type: "mcp_approval_response" The type of the item. Always mcp_approval_response.
reason: optional string or null Optional reason for the decision.
RealtimeMcpListTools { server_label, tools, type, id } A Realtime item listing tools available on an MCP server.
server_label: string The label of the MCP server.
tools: array of { input_schema, name, annotations, description } The tools available on the server.
input_schema: unknown The JSON schema describing the tool's input.
name: string The name of the tool.
annotations: optional unknown or null Additional annotations about the tool.
description: optional string or null The description of the tool.
type: "mcp_list_tools" The type of the item. Always mcp_list_tools.
id: optional string The unique ID of the list.
RealtimeMcpToolCall { id, arguments, name, 5 more } A Realtime item representing an invocation of a tool on an MCP server.
id: string The unique ID of the tool call.
arguments: string A JSON string of the arguments passed to the tool.
name: string The name of the tool that was run.
server_label: string The label of the MCP server running the tool.
type: "mcp_call" The type of the item. Always mcp_call.
approval_request_id: optional string or null The ID of an associated approval request, if any.
error: optional RealtimeMcpProtocolError or RealtimeMcpToolExecutionError or RealtimeMcphttpError or null The error from the tool call, if any.
One of the following: RealtimeMcpProtocolError { code, message, type } code: integer message: string type: "protocol_error" RealtimeMcpToolExecutionError { message, type } message: string type: "tool_execution_error" RealtimeMcphttpError { code, message, type } code: integer message: string type: "http_error" output: optional string or null The output from the tool call.
RealtimeMcpApprovalRequest { id, arguments, name, 2 more } A Realtime item requesting human approval of a tool invocation.
id: string The unique ID of the approval request.
arguments: string A JSON string of arguments for the tool.
name: string The name of the tool to run.
server_label: string The label of the MCP server making the request.
type: "mcp_approval_request" The type of the item. Always mcp_approval_request.
This event is the output of audio transcription for user audio written to the user audio buffer. Transcription begins when the input audio buffer is committed by the client or server (when VAD is enabled). Transcription runs asynchronously with Response creation, so this event may come before or after the Response events.
Realtime API models accept audio natively, and thus input transcription is a separate process run on a separate ASR (Automatic Speech Recognition) model. The transcript may diverge somewhat from the model's interpretation, and should be treated as a rough guide.
type: "conversation.item.input_audio_transcription.completed"
The event type, must be
conversation.item.input_audio_transcription.completed.
usage: Tokens { input_tokens, output_tokens, total_tokens, 2 more } or Duration { seconds, type } Usage statistics for the transcription, this is billed according to the ASR model's pricing rather than the realtime model's pricing.
usage: Tokens { input_tokens, output_tokens, total_tokens, 2 more } or Duration { seconds, type }
Usage statistics for the transcription, this is billed according to the ASR model's pricing rather than the realtime model's pricing.
One of the following: Tokens { input_tokens, output_tokens, total_tokens, 2 more } Usage statistics for models billed by token usage.
input_tokens: integer Number of input tokens billed for this request.
output_tokens: integer Number of output tokens generated.
total_tokens: integer Total number of tokens used (input + output).
type: "tokens" The type of the usage object. Always tokens for this variant.
input_token_details: optional { audio_tokens, text_tokens } Details about the input tokens billed for this request.
audio_tokens: optional integer Number of audio tokens billed for this request.
text_tokens: optional integer Number of text tokens billed for this request.
Duration { seconds, type } Usage statistics for models billed by audio input duration.
seconds: number Duration of the input audio in seconds.
formatdouble type: "duration" The type of the usage object. Always duration for this variant.
The languages detected in the audio. Returned by gpt-transcribe. An empty array indicates that no language could be reliably detected.
The languages detected in the audio. Returned by gpt-transcribe. An empty array indicates that no language could be reliably detected.
Returned when the text value of an input audio transcription content part is updated with incremental transcription results.
type: "conversation.item.input_audio_transcription.delta"
The event type, must be conversation.item.input_audio_transcription.delta.
The log probabilities of the transcription. These can be enabled by configuring the session with "include": ["item.input_audio_transcription.logprobs"]. Each entry in the array corresponds a log probability of which token would be selected for this chunk of transcription. This can help to identify if it was possible there were multiple valid options for a given chunk of transcription.
The log probabilities of the transcription. These can be enabled by configuring the session with "include": ["item.input_audio_transcription.logprobs"]. Each entry in the array corresponds a log probability of which token would be selected for this chunk of transcription. This can help to identify if it was possible there were multiple valid options for a given chunk of transcription.
token: string The token that was used to generate the log probability.
bytes: array of number The bytes that were used to generate the log probability.
logprob: number The log probability of the token.
Returned when an input audio transcription segment is identified for an item.
Returned when input audio transcription is configured, and a transcription
request for a user message failed. These events are separate from other
error events so that the client can identify the related Item.
Returned when an earlier assistant audio message item is truncated by the
client with a conversation.item.truncate event. This event is used to
synchronize the server's understanding of the audio with the client's playback.
This action will truncate the audio and remove the server-side text transcript to ensure there is no text in the context that hasn't been heard by the user.
Returned when an item in the conversation is deleted by the client with a
conversation.item.delete event. This event is used to synchronize the
server's understanding of the conversation history with the client's view.
Returned when an input audio buffer is committed, either by the client or
automatically in server VAD mode. The item_id property is the ID of the user
message item that will be created, thus a conversation.item.created event
will also be sent to the client.
SIP Only: Returned when an DTMF event is received. A DTMF event is a message that
represents a telephone keypad press (0–9, *, #, A–D). The event property
is the keypad that the user press. The received_at is the UTC Unix Timestamp
that the server received the event.
Sent by the server when in server_vad mode to indicate that speech has been
detected in the audio buffer. This can happen any time audio is added to the
buffer (unless speech is already detected). The client may want to use this
event to interrupt audio playback or provide visual feedback to the user.
The client should expect to receive a input_audio_buffer.speech_stopped event
when speech stops. The item_id property is the ID of the user message item
that will be created when speech stops and will also be included in the
input_audio_buffer.speech_stopped event (unless the client manually commits
the audio buffer during VAD activation).
Returned in server_vad mode when the server detects the end of speech in
the audio buffer. The server will also send an conversation.item.created
event with the user message item that is created from the audio buffer.
Returned when the Server VAD timeout is triggered for the input audio buffer. This is configured
with idle_timeout_ms in the turn_detection settings of the session, and it indicates that
there hasn't been any speech detected for the configured duration.
The audio_start_ms and audio_end_ms fields indicate the segment of audio after the last
model response up to the triggering time, as an offset from the beginning of audio written
to the input audio buffer. This means it demarcates the segment of audio that was silent and
the difference between the start and end values will roughly match the configured timeout.
The empty audio will be committed to the conversation as an input_audio item (there will be a
input_audio_buffer.committed event) and a model response will be generated. There may be speech
that didn't trigger VAD but is still detected by the model, so the model may respond with
something relevant to the conversation or a prompt to continue speaking.
WebRTC/SIP Only: Emitted when the server begins streaming audio to the client. This event is
emitted after an audio content part has been added (response.content_part.added)
to the response.
Learn more.
WebRTC/SIP Only: Emitted when the output audio buffer has been completely drained on the server,
and no more audio is forthcoming. This event is emitted after the full response
data has been sent to the client (response.done).
Learn more.
WebRTC/SIP Only: Emitted when the output audio buffer is cleared. This happens either in VAD
mode when the user has interrupted (input_audio_buffer.speech_started),
or when the client has emitted the output_audio_buffer.clear event to manually
cut off the current audio response.
Learn more.
Returned when a new Response is created. The first event of response creation,
where the response is in an initial state of in_progress.
The response resource.
The response resource.
id: optional string The unique ID of the response, will look like resp_1234.
audio: optional { output } Configuration for audio output.
output: optional { format, voice } format: optional RealtimeAudioFormats The format of the output audio.
One of the following: PCMAudio { rate, type } The PCM audio format. Only a 24kHz sample rate is supported.
rate: optional 24000 The sample rate of the audio. Always 24000.
type: optional "audio/pcm" The audio format. Always audio/pcm.
PCMUAudio { type } The G.711 μ-law format.
type: optional "audio/pcmu" The audio format. Always audio/pcmu.
PCMAAudio { type } The G.711 A-law format.
type: optional "audio/pcma" The audio format. Always audio/pcma.
voice: optional string or "alloy" or "ash" or "ballad" or 7 more (default: "alloy") 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.
One of the following: string "alloy" or "ash" or "ballad" or 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.
One of the following: "alloy" "ash" "ballad" "coral" "echo" "sage" "shimmer" "verse" "marin" "cedar" conversation_id: optional string Which conversation the response is added to, determined by the conversation
field in the response.create event. If auto, the response will be added to
the default conversation and the value of conversation_id will be an id like
conv_1234. If none, the response will not be added to any conversation and
the value of conversation_id will be null. If responses are being triggered
automatically by VAD the response will be added to the default conversation
max_output_tokens: optional number or "inf" Maximum number of output tokens for a single assistant response,
inclusive of tool calls, that was used in this response.
One of the following: number "inf" metadata: optional Metadata or null Set of 16 key-value pairs that can be attached to an object. This can be
useful for storing additional information about the object in a structured
format, and querying for objects via API or the dashboard.
Keys are strings with a maximum length of 64 characters. Values are strings
with a maximum length of 512 characters.
object: optional "realtime.response" The object type, must be realtime.response.
output: optional array of ConversationItem The list of output items generated by the response.
One of the following: RealtimeConversationItemSystemMessage { content, role, type, 3 more } A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.
content: array of { text, type } The content of the message.
text: optional string The text content.
type: optional "input_text" The content type. Always input_text for system messages.
role: "system" The role of the message sender. Always system.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemUserMessage { content, role, type, 3 more } A user message item in a Realtime conversation.
content: array of { audio, detail, image_url, 3 more } The content of the message.
audio: optional string Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
detail: optional "auto" or "low" or "high" (default: "auto") The detail level of the image (for input_image). auto will default to high.
One of the following: "auto" "low" "high" image_url: optional string Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.
formaturi text: optional string The text content (for input_text).
transcript: optional string Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.
type: optional "input_text" or "input_audio" or "input_image" The content type (input_text, input_audio, or input_image).
One of the following: "input_text" "input_audio" "input_image" role: "user" The role of the message sender. Always user.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemAssistantMessage { content, role, type, 3 more } An assistant message item in a Realtime conversation.
content: array of { audio, text, transcript, type } The content of the message.
audio: optional string Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
text: optional string The text content.
transcript: optional string The transcript of the audio content, this will always be present if the output type is audio.
type: optional "output_text" or "output_audio" The content type, output_text or output_audio depending on the session output_modalities configuration.
One of the following: "output_text" "output_audio" role: "assistant" The role of the message sender. Always assistant.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCall { arguments, name, type, 4 more } A function call item in a Realtime conversation.
arguments: string The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.
name: string The name of the function being called.
type: "function_call" The type of the item. Always function_call.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
call_id: optional string The ID of the function call.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCallOutput { call_id, output, type, 3 more } A function call output item in a Realtime conversation.
call_id: string The ID of the function call this output is for.
output: string The output of the function call, this is free text and can contain any information or simply be empty.
type: "function_call_output" The type of the item. Always function_call_output.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeMcpApprovalResponse { id, approval_request_id, approve, 2 more } A Realtime item responding to an MCP approval request.
id: string The unique ID of the approval response.
approval_request_id: string The ID of the approval request being answered.
approve: boolean Whether the request was approved.
type: "mcp_approval_response" The type of the item. Always mcp_approval_response.
reason: optional string or null Optional reason for the decision.
RealtimeMcpListTools { server_label, tools, type, id } A Realtime item listing tools available on an MCP server.
server_label: string The label of the MCP server.
tools: array of { input_schema, name, annotations, description } The tools available on the server.
input_schema: unknown The JSON schema describing the tool's input.
name: string The name of the tool.
annotations: optional unknown or null Additional annotations about the tool.
description: optional string or null The description of the tool.
type: "mcp_list_tools" The type of the item. Always mcp_list_tools.
id: optional string The unique ID of the list.
RealtimeMcpToolCall { id, arguments, name, 5 more } A Realtime item representing an invocation of a tool on an MCP server.
id: string The unique ID of the tool call.
arguments: string A JSON string of the arguments passed to the tool.
name: string The name of the tool that was run.
server_label: string The label of the MCP server running the tool.
type: "mcp_call" The type of the item. Always mcp_call.
approval_request_id: optional string or null The ID of an associated approval request, if any.
error: optional RealtimeMcpProtocolError or RealtimeMcpToolExecutionError or RealtimeMcphttpError or null The error from the tool call, if any.
One of the following: RealtimeMcpProtocolError { code, message, type } code: integer message: string type: "protocol_error" RealtimeMcpToolExecutionError { message, type } message: string type: "tool_execution_error" RealtimeMcphttpError { code, message, type } code: integer message: string type: "http_error" output: optional string or null The output from the tool call.
RealtimeMcpApprovalRequest { id, arguments, name, 2 more } A Realtime item requesting human approval of a tool invocation.
id: string The unique ID of the approval request.
arguments: string A JSON string of arguments for the tool.
name: string The name of the tool to run.
server_label: string The label of the MCP server making the request.
type: "mcp_approval_request" The type of the item. Always mcp_approval_request.
output_modalities: optional array of "text" or "audio" The set of modalities the model used to respond, currently the only possible values are
[\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the
output to mode text will disable audio output from the model.
One of the following: "text" "audio" status: optional "completed" or "cancelled" or "failed" or 2 more The final status of the response (completed, cancelled, failed, or
incomplete, in_progress).
One of the following: "completed" "cancelled" "failed" "incomplete" "in_progress" status_details: optional RealtimeResponseStatus { error, reason, type } Additional details about the status.
error: optional { code, message, type } A description of the error that caused the response to fail,
populated when the status is failed.
code: optional string Error code, if any.
message: optional string A human-readable error message.
type: optional string The type of error.
reason: optional "turn_detected" or "client_cancelled" or "max_output_tokens" or "content_filter" The reason the Response did not complete. For a cancelled Response, one of turn_detected (the server VAD detected a new start of speech) or client_cancelled (the client sent a cancel event). For an incomplete Response, one of max_output_tokens or content_filter (the server-side safety filter activated and cut off the response).
One of the following: "turn_detected" "client_cancelled" "max_output_tokens" "content_filter" type: optional "completed" or "cancelled" or "failed" or "incomplete" The type of error that caused the response to fail, corresponding
with the status field (completed, cancelled, incomplete,
failed).
One of the following: "completed" "cancelled" "failed" "incomplete" usage: optional RealtimeResponseUsage { input_token_details, input_tokens, output_token_details, 2 more } Usage statistics for the Response, this will correspond to billing. A
Realtime API session will maintain a conversation context and append new
Items to the Conversation, thus output from previous turns (text and
audio tokens) will become the input for later turns.
input_token_details: optional RealtimeResponseUsageInputTokenDetails { audio_tokens, cached_tokens, cached_tokens_details, 2 more } Details about the input tokens used in the Response. Cached tokens are tokens from previous turns in the conversation that are included as context for the current response. Cached tokens here are counted as a subset of input tokens, meaning input tokens will include cached and uncached tokens.
audio_tokens: optional integer The number of audio tokens used as input for the Response.
cached_tokens: optional integer The number of cached tokens used as input for the Response.
cached_tokens_details: optional { audio_tokens, image_tokens, text_tokens } Details about the cached tokens used as input for the Response.
audio_tokens: optional integer The number of cached audio tokens used as input for the Response.
image_tokens: optional integer The number of cached image tokens used as input for the Response.
text_tokens: optional integer The number of cached text tokens used as input for the Response.
image_tokens: optional integer The number of image tokens used as input for the Response.
text_tokens: optional integer The number of text tokens used as input for the Response.
input_tokens: optional integer The number of input tokens used in the Response, including text and
audio tokens.
output_token_details: optional RealtimeResponseUsageOutputTokenDetails { audio_tokens, text_tokens } Details about the output tokens used in the Response.
audio_tokens: optional integer The number of audio tokens used in the Response.
text_tokens: optional integer The number of text tokens used in the Response.
output_tokens: optional integer The number of output tokens sent in the Response, including text and
audio tokens.
total_tokens: optional integer The total number of tokens in the Response including input and output
text and audio tokens.
Returned when a Response is done streaming. Always emitted, no matter the
final state. The Response object included in the response.done event will
include all output Items in the Response but will omit the raw audio data.
Clients should check the status field of the Response to determine if it was successful
(completed) or if there was another outcome: cancelled, failed, or incomplete.
A response will contain all output items that were generated during the response, excluding any audio content.
The response resource.
The response resource.
id: optional string The unique ID of the response, will look like resp_1234.
audio: optional { output } Configuration for audio output.
output: optional { format, voice } format: optional RealtimeAudioFormats The format of the output audio.
One of the following: PCMAudio { rate, type } The PCM audio format. Only a 24kHz sample rate is supported.
rate: optional 24000 The sample rate of the audio. Always 24000.
type: optional "audio/pcm" The audio format. Always audio/pcm.
PCMUAudio { type } The G.711 μ-law format.
type: optional "audio/pcmu" The audio format. Always audio/pcmu.
PCMAAudio { type } The G.711 A-law format.
type: optional "audio/pcma" The audio format. Always audio/pcma.
voice: optional string or "alloy" or "ash" or "ballad" or 7 more (default: "alloy") 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.
One of the following: string "alloy" or "ash" or "ballad" or 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.
One of the following: "alloy" "ash" "ballad" "coral" "echo" "sage" "shimmer" "verse" "marin" "cedar" conversation_id: optional string Which conversation the response is added to, determined by the conversation
field in the response.create event. If auto, the response will be added to
the default conversation and the value of conversation_id will be an id like
conv_1234. If none, the response will not be added to any conversation and
the value of conversation_id will be null. If responses are being triggered
automatically by VAD the response will be added to the default conversation
max_output_tokens: optional number or "inf" Maximum number of output tokens for a single assistant response,
inclusive of tool calls, that was used in this response.
One of the following: number "inf" metadata: optional Metadata or null Set of 16 key-value pairs that can be attached to an object. This can be
useful for storing additional information about the object in a structured
format, and querying for objects via API or the dashboard.
Keys are strings with a maximum length of 64 characters. Values are strings
with a maximum length of 512 characters.
object: optional "realtime.response" The object type, must be realtime.response.
output: optional array of ConversationItem The list of output items generated by the response.
One of the following: RealtimeConversationItemSystemMessage { content, role, type, 3 more } A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.
content: array of { text, type } The content of the message.
text: optional string The text content.
type: optional "input_text" The content type. Always input_text for system messages.
role: "system" The role of the message sender. Always system.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemUserMessage { content, role, type, 3 more } A user message item in a Realtime conversation.
content: array of { audio, detail, image_url, 3 more } The content of the message.
audio: optional string Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
detail: optional "auto" or "low" or "high" (default: "auto") The detail level of the image (for input_image). auto will default to high.
One of the following: "auto" "low" "high" image_url: optional string Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.
formaturi text: optional string The text content (for input_text).
transcript: optional string Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.
type: optional "input_text" or "input_audio" or "input_image" The content type (input_text, input_audio, or input_image).
One of the following: "input_text" "input_audio" "input_image" role: "user" The role of the message sender. Always user.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemAssistantMessage { content, role, type, 3 more } An assistant message item in a Realtime conversation.
content: array of { audio, text, transcript, type } The content of the message.
audio: optional string Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
text: optional string The text content.
transcript: optional string The transcript of the audio content, this will always be present if the output type is audio.
type: optional "output_text" or "output_audio" The content type, output_text or output_audio depending on the session output_modalities configuration.
One of the following: "output_text" "output_audio" role: "assistant" The role of the message sender. Always assistant.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCall { arguments, name, type, 4 more } A function call item in a Realtime conversation.
arguments: string The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.
name: string The name of the function being called.
type: "function_call" The type of the item. Always function_call.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
call_id: optional string The ID of the function call.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCallOutput { call_id, output, type, 3 more } A function call output item in a Realtime conversation.
call_id: string The ID of the function call this output is for.
output: string The output of the function call, this is free text and can contain any information or simply be empty.
type: "function_call_output" The type of the item. Always function_call_output.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeMcpApprovalResponse { id, approval_request_id, approve, 2 more } A Realtime item responding to an MCP approval request.
id: string The unique ID of the approval response.
approval_request_id: string The ID of the approval request being answered.
approve: boolean Whether the request was approved.
type: "mcp_approval_response" The type of the item. Always mcp_approval_response.
reason: optional string or null Optional reason for the decision.
RealtimeMcpListTools { server_label, tools, type, id } A Realtime item listing tools available on an MCP server.
server_label: string The label of the MCP server.
tools: array of { input_schema, name, annotations, description } The tools available on the server.
input_schema: unknown The JSON schema describing the tool's input.
name: string The name of the tool.
annotations: optional unknown or null Additional annotations about the tool.
description: optional string or null The description of the tool.
type: "mcp_list_tools" The type of the item. Always mcp_list_tools.
id: optional string The unique ID of the list.
RealtimeMcpToolCall { id, arguments, name, 5 more } A Realtime item representing an invocation of a tool on an MCP server.
id: string The unique ID of the tool call.
arguments: string A JSON string of the arguments passed to the tool.
name: string The name of the tool that was run.
server_label: string The label of the MCP server running the tool.
type: "mcp_call" The type of the item. Always mcp_call.
approval_request_id: optional string or null The ID of an associated approval request, if any.
error: optional RealtimeMcpProtocolError or RealtimeMcpToolExecutionError or RealtimeMcphttpError or null The error from the tool call, if any.
One of the following: RealtimeMcpProtocolError { code, message, type } code: integer message: string type: "protocol_error" RealtimeMcpToolExecutionError { message, type } message: string type: "tool_execution_error" RealtimeMcphttpError { code, message, type } code: integer message: string type: "http_error" output: optional string or null The output from the tool call.
RealtimeMcpApprovalRequest { id, arguments, name, 2 more } A Realtime item requesting human approval of a tool invocation.
id: string The unique ID of the approval request.
arguments: string A JSON string of arguments for the tool.
name: string The name of the tool to run.
server_label: string The label of the MCP server making the request.
type: "mcp_approval_request" The type of the item. Always mcp_approval_request.
output_modalities: optional array of "text" or "audio" The set of modalities the model used to respond, currently the only possible values are
[\"audio\"], [\"text\"]. Audio output always include a text transcript. Setting the
output to mode text will disable audio output from the model.
One of the following: "text" "audio" status: optional "completed" or "cancelled" or "failed" or 2 more The final status of the response (completed, cancelled, failed, or
incomplete, in_progress).
One of the following: "completed" "cancelled" "failed" "incomplete" "in_progress" status_details: optional RealtimeResponseStatus { error, reason, type } Additional details about the status.
error: optional { code, message, type } A description of the error that caused the response to fail,
populated when the status is failed.
code: optional string Error code, if any.
message: optional string A human-readable error message.
type: optional string The type of error.
reason: optional "turn_detected" or "client_cancelled" or "max_output_tokens" or "content_filter" The reason the Response did not complete. For a cancelled Response, one of turn_detected (the server VAD detected a new start of speech) or client_cancelled (the client sent a cancel event). For an incomplete Response, one of max_output_tokens or content_filter (the server-side safety filter activated and cut off the response).
One of the following: "turn_detected" "client_cancelled" "max_output_tokens" "content_filter" type: optional "completed" or "cancelled" or "failed" or "incomplete" The type of error that caused the response to fail, corresponding
with the status field (completed, cancelled, incomplete,
failed).
One of the following: "completed" "cancelled" "failed" "incomplete" usage: optional RealtimeResponseUsage { input_token_details, input_tokens, output_token_details, 2 more } Usage statistics for the Response, this will correspond to billing. A
Realtime API session will maintain a conversation context and append new
Items to the Conversation, thus output from previous turns (text and
audio tokens) will become the input for later turns.
input_token_details: optional RealtimeResponseUsageInputTokenDetails { audio_tokens, cached_tokens, cached_tokens_details, 2 more } Details about the input tokens used in the Response. Cached tokens are tokens from previous turns in the conversation that are included as context for the current response. Cached tokens here are counted as a subset of input tokens, meaning input tokens will include cached and uncached tokens.
audio_tokens: optional integer The number of audio tokens used as input for the Response.
cached_tokens: optional integer The number of cached tokens used as input for the Response.
cached_tokens_details: optional { audio_tokens, image_tokens, text_tokens } Details about the cached tokens used as input for the Response.
audio_tokens: optional integer The number of cached audio tokens used as input for the Response.
image_tokens: optional integer The number of cached image tokens used as input for the Response.
text_tokens: optional integer The number of cached text tokens used as input for the Response.
image_tokens: optional integer The number of image tokens used as input for the Response.
text_tokens: optional integer The number of text tokens used as input for the Response.
input_tokens: optional integer The number of input tokens used in the Response, including text and
audio tokens.
output_token_details: optional RealtimeResponseUsageOutputTokenDetails { audio_tokens, text_tokens } Details about the output tokens used in the Response.
audio_tokens: optional integer The number of audio tokens used in the Response.
text_tokens: optional integer The number of text tokens used in the Response.
output_tokens: optional integer The number of output tokens sent in the Response, including text and
audio tokens.
total_tokens: optional integer The total number of tokens in the Response including input and output
text and audio tokens.
Returned when a new Item is created during Response generation.
A single item within a Realtime conversation.
A single item within a Realtime conversation.
One of the following: RealtimeConversationItemSystemMessage { content, role, type, 3 more } A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.
content: array of { text, type } The content of the message.
text: optional string The text content.
type: optional "input_text" The content type. Always input_text for system messages.
role: "system" The role of the message sender. Always system.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemUserMessage { content, role, type, 3 more } A user message item in a Realtime conversation.
content: array of { audio, detail, image_url, 3 more } The content of the message.
audio: optional string Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
detail: optional "auto" or "low" or "high" (default: "auto") The detail level of the image (for input_image). auto will default to high.
One of the following: "auto" "low" "high" image_url: optional string Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.
formaturi text: optional string The text content (for input_text).
transcript: optional string Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.
type: optional "input_text" or "input_audio" or "input_image" The content type (input_text, input_audio, or input_image).
One of the following: "input_text" "input_audio" "input_image" role: "user" The role of the message sender. Always user.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemAssistantMessage { content, role, type, 3 more } An assistant message item in a Realtime conversation.
content: array of { audio, text, transcript, type } The content of the message.
audio: optional string Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
text: optional string The text content.
transcript: optional string The transcript of the audio content, this will always be present if the output type is audio.
type: optional "output_text" or "output_audio" The content type, output_text or output_audio depending on the session output_modalities configuration.
One of the following: "output_text" "output_audio" role: "assistant" The role of the message sender. Always assistant.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCall { arguments, name, type, 4 more } A function call item in a Realtime conversation.
arguments: string The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.
name: string The name of the function being called.
type: "function_call" The type of the item. Always function_call.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
call_id: optional string The ID of the function call.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCallOutput { call_id, output, type, 3 more } A function call output item in a Realtime conversation.
call_id: string The ID of the function call this output is for.
output: string The output of the function call, this is free text and can contain any information or simply be empty.
type: "function_call_output" The type of the item. Always function_call_output.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeMcpApprovalResponse { id, approval_request_id, approve, 2 more } A Realtime item responding to an MCP approval request.
id: string The unique ID of the approval response.
approval_request_id: string The ID of the approval request being answered.
approve: boolean Whether the request was approved.
type: "mcp_approval_response" The type of the item. Always mcp_approval_response.
reason: optional string or null Optional reason for the decision.
RealtimeMcpListTools { server_label, tools, type, id } A Realtime item listing tools available on an MCP server.
server_label: string The label of the MCP server.
tools: array of { input_schema, name, annotations, description } The tools available on the server.
input_schema: unknown The JSON schema describing the tool's input.
name: string The name of the tool.
annotations: optional unknown or null Additional annotations about the tool.
description: optional string or null The description of the tool.
type: "mcp_list_tools" The type of the item. Always mcp_list_tools.
id: optional string The unique ID of the list.
RealtimeMcpToolCall { id, arguments, name, 5 more } A Realtime item representing an invocation of a tool on an MCP server.
id: string The unique ID of the tool call.
arguments: string A JSON string of the arguments passed to the tool.
name: string The name of the tool that was run.
server_label: string The label of the MCP server running the tool.
type: "mcp_call" The type of the item. Always mcp_call.
approval_request_id: optional string or null The ID of an associated approval request, if any.
error: optional RealtimeMcpProtocolError or RealtimeMcpToolExecutionError or RealtimeMcphttpError or null The error from the tool call, if any.
One of the following: RealtimeMcpProtocolError { code, message, type } code: integer message: string type: "protocol_error" RealtimeMcpToolExecutionError { message, type } message: string type: "tool_execution_error" RealtimeMcphttpError { code, message, type } code: integer message: string type: "http_error" output: optional string or null The output from the tool call.
RealtimeMcpApprovalRequest { id, arguments, name, 2 more } A Realtime item requesting human approval of a tool invocation.
id: string The unique ID of the approval request.
arguments: string A JSON string of arguments for the tool.
name: string The name of the tool to run.
server_label: string The label of the MCP server making the request.
type: "mcp_approval_request" The type of the item. Always mcp_approval_request.
Returned when an Item is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.
A single item within a Realtime conversation.
A single item within a Realtime conversation.
One of the following: RealtimeConversationItemSystemMessage { content, role, type, 3 more } A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.
content: array of { text, type } The content of the message.
text: optional string The text content.
type: optional "input_text" The content type. Always input_text for system messages.
role: "system" The role of the message sender. Always system.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemUserMessage { content, role, type, 3 more } A user message item in a Realtime conversation.
content: array of { audio, detail, image_url, 3 more } The content of the message.
audio: optional string Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
detail: optional "auto" or "low" or "high" (default: "auto") The detail level of the image (for input_image). auto will default to high.
One of the following: "auto" "low" "high" image_url: optional string Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.
formaturi text: optional string The text content (for input_text).
transcript: optional string Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.
type: optional "input_text" or "input_audio" or "input_image" The content type (input_text, input_audio, or input_image).
One of the following: "input_text" "input_audio" "input_image" role: "user" The role of the message sender. Always user.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemAssistantMessage { content, role, type, 3 more } An assistant message item in a Realtime conversation.
content: array of { audio, text, transcript, type } The content of the message.
audio: optional string Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
text: optional string The text content.
transcript: optional string The transcript of the audio content, this will always be present if the output type is audio.
type: optional "output_text" or "output_audio" The content type, output_text or output_audio depending on the session output_modalities configuration.
One of the following: "output_text" "output_audio" role: "assistant" The role of the message sender. Always assistant.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCall { arguments, name, type, 4 more } A function call item in a Realtime conversation.
arguments: string The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.
name: string The name of the function being called.
type: "function_call" The type of the item. Always function_call.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
call_id: optional string The ID of the function call.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCallOutput { call_id, output, type, 3 more } A function call output item in a Realtime conversation.
call_id: string The ID of the function call this output is for.
output: string The output of the function call, this is free text and can contain any information or simply be empty.
type: "function_call_output" The type of the item. Always function_call_output.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeMcpApprovalResponse { id, approval_request_id, approve, 2 more } A Realtime item responding to an MCP approval request.
id: string The unique ID of the approval response.
approval_request_id: string The ID of the approval request being answered.
approve: boolean Whether the request was approved.
type: "mcp_approval_response" The type of the item. Always mcp_approval_response.
reason: optional string or null Optional reason for the decision.
RealtimeMcpListTools { server_label, tools, type, id } A Realtime item listing tools available on an MCP server.
server_label: string The label of the MCP server.
tools: array of { input_schema, name, annotations, description } The tools available on the server.
input_schema: unknown The JSON schema describing the tool's input.
name: string The name of the tool.
annotations: optional unknown or null Additional annotations about the tool.
description: optional string or null The description of the tool.
type: "mcp_list_tools" The type of the item. Always mcp_list_tools.
id: optional string The unique ID of the list.
RealtimeMcpToolCall { id, arguments, name, 5 more } A Realtime item representing an invocation of a tool on an MCP server.
id: string The unique ID of the tool call.
arguments: string A JSON string of the arguments passed to the tool.
name: string The name of the tool that was run.
server_label: string The label of the MCP server running the tool.
type: "mcp_call" The type of the item. Always mcp_call.
approval_request_id: optional string or null The ID of an associated approval request, if any.
error: optional RealtimeMcpProtocolError or RealtimeMcpToolExecutionError or RealtimeMcphttpError or null The error from the tool call, if any.
One of the following: RealtimeMcpProtocolError { code, message, type } code: integer message: string type: "protocol_error" RealtimeMcpToolExecutionError { message, type } message: string type: "tool_execution_error" RealtimeMcphttpError { code, message, type } code: integer message: string type: "http_error" output: optional string or null The output from the tool call.
RealtimeMcpApprovalRequest { id, arguments, name, 2 more } A Realtime item requesting human approval of a tool invocation.
id: string The unique ID of the approval request.
arguments: string A JSON string of arguments for the tool.
name: string The name of the tool to run.
server_label: string The label of the MCP server making the request.
type: "mcp_approval_request" The type of the item. Always mcp_approval_request.
Returned when a new content part is added to an assistant message item during response generation.
part: object { audio, text, transcript, type } The content part that was added.
part: object { audio, text, transcript, type }
The content part that was added.
audio: optional string Base64-encoded audio data (if type is "audio").
text: optional string The text content (if type is "text").
transcript: optional string The transcript of the audio (if type is "audio").
type: optional "audio" or "text" The content type ("text", "audio").
One of the following: "audio" "text"
Returned when a content part is done streaming in an assistant message item. Also emitted when a Response is interrupted, incomplete, or cancelled.
part: object { audio, text, transcript, type } The content part that is done.
part: object { audio, text, transcript, type }
The content part that is done.
audio: optional string Base64-encoded audio data (if type is "audio").
text: optional string The text content (if type is "text").
transcript: optional string The transcript of the audio (if type is "audio").
type: optional "audio" or "text" The content type ("text", "audio").
One of the following: "audio" "text"
Returned when the text value of an "output_text" content part is updated.
Returned when the text value of an "output_text" content part is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.
Returned when the model-generated transcription of audio output is updated.
Returned when the model-generated transcription of audio output is done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.
Returned when the model-generated audio is updated.
Returned when the model-generated audio is done. Also emitted when a Response is interrupted, incomplete, or cancelled.
Returned when the model-generated function call arguments are updated.
Returned when the model-generated function call arguments are done streaming. Also emitted when a Response is interrupted, incomplete, or cancelled.
Returned when MCP tool call arguments are updated during response generation.
Returned when MCP tool call arguments are finalized during response generation.
Returned when an MCP tool call has started and is in progress.
Returned when an MCP tool call has completed successfully.
Emitted at the beginning of a Response to indicate the updated rate limits. When a Response is created some tokens will be "reserved" for the output tokens, the rate limits shown here reflect that reservation, which is then adjusted accordingly once the Response is completed.
rate_limits: array of object { limit, name, remaining, reset_seconds } List of rate limit information.
rate_limits: array of object { limit, name, remaining, reset_seconds }
List of rate limit information.
limit: optional integer The maximum allowed value for the rate limit.
name: optional "requests" or "tokens" The name of the rate limit (requests, tokens).
One of the following: "requests" "tokens" remaining: optional integer The remaining value before the limit is reached.
reset_seconds: optional number Seconds until the rate limit resets.
Returned when a conversation item is created. There are several scenarios that produce this event:
- The server is generating a Response, which if successful will produce
either one or two Items, which will be of type
message(roleassistant) or typefunction_call. - The input audio buffer has been committed, either by the client or the
server (in
server_vadmode). The server will take the content of the input audio buffer and add it to a new user message Item. - The client has sent a
conversation.item.createevent to add a new Item to the Conversation.
A single item within a Realtime conversation.
A single item within a Realtime conversation.
One of the following: RealtimeConversationItemSystemMessage { content, role, type, 3 more } A system message in a Realtime conversation can be used to provide additional context or instructions to the model. This is similar but distinct from the instruction prompt provided at the start of a conversation, as system messages can be added at any point in the conversation. For major changes to the conversation's behavior, use instructions, but for smaller updates (e.g. "the user is now asking about a different topic"), use system messages.
content: array of { text, type } The content of the message.
text: optional string The text content.
type: optional "input_text" The content type. Always input_text for system messages.
role: "system" The role of the message sender. Always system.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemUserMessage { content, role, type, 3 more } A user message item in a Realtime conversation.
content: array of { audio, detail, image_url, 3 more } The content of the message.
audio: optional string Base64-encoded audio bytes (for input_audio), these will be parsed as the format specified in the session input audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
detail: optional "auto" or "low" or "high" (default: "auto") The detail level of the image (for input_image). auto will default to high.
One of the following: "auto" "low" "high" image_url: optional string Base64-encoded image bytes (for input_image) as a data URI. For example data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAA.... Supported formats are PNG and JPEG.
formaturi text: optional string The text content (for input_text).
transcript: optional string Transcript of the audio (for input_audio). This is not sent to the model, but will be attached to the message item for reference.
type: optional "input_text" or "input_audio" or "input_image" The content type (input_text, input_audio, or input_image).
One of the following: "input_text" "input_audio" "input_image" role: "user" The role of the message sender. Always user.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemAssistantMessage { content, role, type, 3 more } An assistant message item in a Realtime conversation.
content: array of { audio, text, transcript, type } The content of the message.
audio: optional string Base64-encoded audio bytes, these will be parsed as the format specified in the session output audio type configuration. This defaults to PCM 16-bit 24kHz mono if not specified.
text: optional string The text content.
transcript: optional string The transcript of the audio content, this will always be present if the output type is audio.
type: optional "output_text" or "output_audio" The content type, output_text or output_audio depending on the session output_modalities configuration.
One of the following: "output_text" "output_audio" role: "assistant" The role of the message sender. Always assistant.
type: "message" The type of the item. Always message.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCall { arguments, name, type, 4 more } A function call item in a Realtime conversation.
arguments: string The arguments of the function call. This is a JSON-encoded string representing the arguments passed to the function, for example {"arg1": "value1", "arg2": 42}.
name: string The name of the function being called.
type: "function_call" The type of the item. Always function_call.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
call_id: optional string The ID of the function call.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeConversationItemFunctionCallOutput { call_id, output, type, 3 more } A function call output item in a Realtime conversation.
call_id: string The ID of the function call this output is for.
output: string The output of the function call, this is free text and can contain any information or simply be empty.
type: "function_call_output" The type of the item. Always function_call_output.
id: optional string The unique ID of the item. This may be provided by the client or generated by the server.
object: optional "realtime.item" Identifier for the API object being returned - always realtime.item. Optional when creating a new item.
status: optional "completed" or "incomplete" or "in_progress" The status of the item. Has no effect on the conversation.
One of the following: "completed" "incomplete" "in_progress" RealtimeMcpApprovalResponse { id, approval_request_id, approve, 2 more } A Realtime item responding to an MCP approval request.
id: string The unique ID of the approval response.
approval_request_id: string The ID of the approval request being answered.
approve: boolean Whether the request was approved.
type: "mcp_approval_response" The type of the item. Always mcp_approval_response.
reason: optional string or null Optional reason for the decision.
RealtimeMcpListTools { server_label, tools, type, id } A Realtime item listing tools available on an MCP server.
server_label: string The label of the MCP server.
tools: array of { input_schema, name, annotations, description } The tools available on the server.
input_schema: unknown The JSON schema describing the tool's input.
name: string The name of the tool.
annotations: optional unknown or null Additional annotations about the tool.
description: optional string or null The description of the tool.
type: "mcp_list_tools" The type of the item. Always mcp_list_tools.
id: optional string The unique ID of the list.
RealtimeMcpToolCall { id, arguments, name, 5 more } A Realtime item representing an invocation of a tool on an MCP server.
id: string The unique ID of the tool call.
arguments: string A JSON string of the arguments passed to the tool.
name: string The name of the tool that was run.
server_label: string The label of the MCP server running the tool.
type: "mcp_call" The type of the item. Always mcp_call.
approval_request_id: optional string or null The ID of an associated approval request, if any.
error: optional RealtimeMcpProtocolError or RealtimeMcpToolExecutionError or RealtimeMcphttpError or null The error from the tool call, if any.
One of the following: RealtimeMcpProtocolError { code, message, type } code: integer message: string type: "protocol_error" RealtimeMcpToolExecutionError { message, type } message: string type: "tool_execution_error" RealtimeMcphttpError { code, message, type } code: integer message: string type: "http_error" output: optional string or null The output from the tool call.
RealtimeMcpApprovalRequest { id, arguments, name, 2 more } A Realtime item requesting human approval of a tool invocation.
id: string The unique ID of the approval request.
arguments: string A JSON string of arguments for the tool.
name: string The name of the tool to run.
server_label: string The label of the MCP server making the request.
type: "mcp_approval_request" The type of the item. Always mcp_approval_request.