Module livekit.plugins.openai.realtime
Classes
class RealtimeModel (*,
model: str = 'gpt-4o-realtime-preview',
voice: str = 'alloy',
modalities: "NotGivenOr[list[Literal['text', 'audio']]]" = NOT_GIVEN,
temperature: NotGivenOr[float] = NOT_GIVEN,
tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN,
base_url: NotGivenOr[str] = NOT_GIVEN,
input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN,
input_audio_noise_reduction: InputAudioNoiseReduction | None = None,
turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN,
speed: NotGivenOr[float] = NOT_GIVEN,
tracing: NotGivenOr[Tracing | None] = NOT_GIVEN,
api_key: str | None = None,
http_session: aiohttp.ClientSession | None = None,
azure_deployment: str | None = None,
entra_token: str | None = None,
api_version: str | None = None,
max_session_duration: NotGivenOr[float | None] = NOT_GIVEN,
conn_options: APIConnectOptions = APIConnectOptions(max_retry=3, retry_interval=2.0, timeout=10.0))-
Expand source code
class RealtimeModel(llm.RealtimeModel): @overload def __init__( self, *, model: str = "gpt-4o-realtime-preview", voice: str = "alloy", modalities: NotGivenOr[list[Literal["text", "audio"]]] = NOT_GIVEN, input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN, input_audio_noise_reduction: InputAudioNoiseReduction | None = None, turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN, temperature: NotGivenOr[float] = NOT_GIVEN, tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN, speed: NotGivenOr[float] = NOT_GIVEN, tracing: NotGivenOr[Tracing | None] = NOT_GIVEN, api_key: str | None = None, base_url: NotGivenOr[str] = NOT_GIVEN, http_session: aiohttp.ClientSession | None = None, max_session_duration: NotGivenOr[float | None] = NOT_GIVEN, conn_options: APIConnectOptions = DEFAULT_API_CONNECT_OPTIONS, ) -> None: ... @overload def __init__( self, *, azure_deployment: str | None = None, entra_token: str | None = None, api_key: str | None = None, api_version: str | None = None, base_url: NotGivenOr[str] = NOT_GIVEN, voice: str = "alloy", modalities: NotGivenOr[list[Literal["text", "audio"]]] = NOT_GIVEN, input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN, input_audio_noise_reduction: InputAudioNoiseReduction | None = None, turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN, temperature: NotGivenOr[float] = NOT_GIVEN, tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN, speed: NotGivenOr[float] = NOT_GIVEN, tracing: NotGivenOr[Tracing | None] = NOT_GIVEN, http_session: aiohttp.ClientSession | None = None, max_session_duration: NotGivenOr[float | None] = NOT_GIVEN, conn_options: APIConnectOptions = DEFAULT_API_CONNECT_OPTIONS, ) -> None: ... def __init__( self, *, model: str = "gpt-4o-realtime-preview", voice: str = "alloy", modalities: NotGivenOr[list[Literal["text", "audio"]]] = NOT_GIVEN, temperature: NotGivenOr[float] = NOT_GIVEN, tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN, base_url: NotGivenOr[str] = NOT_GIVEN, input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN, input_audio_noise_reduction: InputAudioNoiseReduction | None = None, turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN, speed: NotGivenOr[float] = NOT_GIVEN, tracing: NotGivenOr[Tracing | None] = NOT_GIVEN, api_key: str | None = None, http_session: aiohttp.ClientSession | None = None, azure_deployment: str | None = None, entra_token: str | None = None, api_version: str | None = None, max_session_duration: NotGivenOr[float | None] = NOT_GIVEN, conn_options: APIConnectOptions = DEFAULT_API_CONNECT_OPTIONS, ) -> None: modalities = modalities if is_given(modalities) else ["text", "audio"] super().__init__( capabilities=llm.RealtimeCapabilities( message_truncation=True, turn_detection=turn_detection is not None, user_transcription=input_audio_transcription is not None, auto_tool_reply_generation=False, audio_output="audio" in modalities, ) ) is_azure = ( api_version is not None or entra_token is not None or azure_deployment is not None ) api_key = api_key or os.environ.get("OPENAI_API_KEY") if api_key is None and not is_azure: raise ValueError( "The api_key client option must be set either by passing api_key " "to the client or by setting the OPENAI_API_KEY environment variable" ) if is_given(base_url): base_url_val = base_url else: if is_azure: azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT") if azure_endpoint is None: raise ValueError( "Missing Azure endpoint. Please pass base_url " "or set AZURE_OPENAI_ENDPOINT environment variable." ) base_url_val = f"{azure_endpoint.rstrip('/')}/openai" else: base_url_val = OPENAI_BASE_URL self._opts = _RealtimeOptions( model=model, voice=voice, temperature=temperature if is_given(temperature) else DEFAULT_TEMPERATURE, tool_choice=tool_choice or None, modalities=modalities, input_audio_transcription=input_audio_transcription if is_given(input_audio_transcription) else DEFAULT_INPUT_AUDIO_TRANSCRIPTION, input_audio_noise_reduction=input_audio_noise_reduction, turn_detection=turn_detection if is_given(turn_detection) else DEFAULT_TURN_DETECTION, api_key=api_key, base_url=base_url_val, is_azure=is_azure, azure_deployment=azure_deployment, entra_token=entra_token, api_version=api_version, max_response_output_tokens=DEFAULT_MAX_RESPONSE_OUTPUT_TOKENS, # type: ignore speed=speed if is_given(speed) else None, tracing=cast(Union[Tracing, None], tracing) if is_given(tracing) else None, max_session_duration=max_session_duration if is_given(max_session_duration) else DEFAULT_MAX_SESSION_DURATION, conn_options=conn_options, ) self._http_session = http_session self._http_session_owned = False self._sessions = weakref.WeakSet[RealtimeSession]() @classmethod def with_azure( cls, *, azure_deployment: str, azure_endpoint: str | None = None, api_version: str | None = None, api_key: str | None = None, entra_token: str | None = None, base_url: str | None = None, voice: str = "alloy", modalities: NotGivenOr[list[Literal["text", "audio"]]] = NOT_GIVEN, input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN, input_audio_noise_reduction: InputAudioNoiseReduction | None = None, turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN, temperature: float = 0.8, speed: NotGivenOr[float] = NOT_GIVEN, tracing: NotGivenOr[Tracing | None] = NOT_GIVEN, http_session: aiohttp.ClientSession | None = None, ) -> RealtimeModel: """ Create a RealtimeClient instance configured for Azure OpenAI Service. Args: azure_deployment (str): The name of your Azure OpenAI deployment. azure_endpoint (str or None, optional): The endpoint URL for your Azure OpenAI resource. If None, will attempt to read from the environment variable AZURE_OPENAI_ENDPOINT. api_version (str or None, optional): API version to use with Azure OpenAI Service. If None, will attempt to read from the environment variable OPENAI_API_VERSION. api_key (str or None, optional): Azure OpenAI API key. If None, will attempt to read from the environment variable AZURE_OPENAI_API_KEY. entra_token (str or None, optional): Azure Entra authentication token. Required if not using API key authentication. base_url (str or None, optional): Base URL for the API endpoint. If None, constructed from the azure_endpoint. voice (api_proto.Voice, optional): Voice setting for audio outputs. Defaults to "alloy". modalities (list[Literal["text", "audio"]], optional): Modalities to use for the session. Defaults to ["text", "audio"]. input_audio_transcription (InputTranscriptionOptions, optional): Options for transcribing input audio. Defaults to DEFAULT_INPUT_AUDIO_TRANSCRIPTION. input_audio_noise_reduction (InputAudioNoiseReduction or None, optional): Options for input audio 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. Defaults to None. turn_detection (ServerVadOptions, optional): Options for server-based voice activity detection (VAD). Defaults to DEFAULT_SERVER_VAD_OPTIONS. temperature (float, optional): Sampling temperature for response generation. Defaults to 0.8. max_response_output_tokens (int or Literal["inf"], optional): Maximum number of tokens in the response. Defaults to "inf". http_session (aiohttp.ClientSession or None, optional): Async HTTP session to use for requests. If None, a new session will be created. Returns: RealtimeClient: An instance of RealtimeClient configured for Azure OpenAI Service. Raises: ValueError: If required Azure parameters are missing or invalid. """ # noqa: E501 api_key = api_key or os.getenv("AZURE_OPENAI_API_KEY") if api_key is None and entra_token is None: raise ValueError( "Missing credentials. Please pass one of `api_key`, `entra_token`, " "or the `AZURE_OPENAI_API_KEY` environment variable." ) api_version = api_version or os.getenv("OPENAI_API_VERSION") if api_version is None: raise ValueError( "Must provide either the `api_version` argument or the " "`OPENAI_API_VERSION` environment variable" ) if base_url is None: azure_endpoint = azure_endpoint or os.getenv("AZURE_OPENAI_ENDPOINT") if azure_endpoint is None: raise ValueError( "Missing Azure endpoint. Please pass the `azure_endpoint` " "parameter or set the `AZURE_OPENAI_ENDPOINT` environment variable." ) base_url = f"{azure_endpoint.rstrip('/')}/openai" elif azure_endpoint is not None: raise ValueError("base_url and azure_endpoint are mutually exclusive") if not is_given(input_audio_transcription): input_audio_transcription = AZURE_DEFAULT_INPUT_AUDIO_TRANSCRIPTION if not is_given(turn_detection): turn_detection = AZURE_DEFAULT_TURN_DETECTION return cls( voice=voice, modalities=modalities, input_audio_transcription=input_audio_transcription, input_audio_noise_reduction=input_audio_noise_reduction, turn_detection=turn_detection, temperature=temperature, speed=speed, tracing=tracing, api_key=api_key, http_session=http_session, azure_deployment=azure_deployment, api_version=api_version, entra_token=entra_token, base_url=base_url, ) def update_options( self, *, voice: NotGivenOr[str] = NOT_GIVEN, temperature: NotGivenOr[float] = NOT_GIVEN, turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN, tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN, input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN, input_audio_noise_reduction: NotGivenOr[InputAudioNoiseReduction | None] = NOT_GIVEN, max_response_output_tokens: NotGivenOr[int | Literal["inf"] | None] = NOT_GIVEN, speed: NotGivenOr[float] = NOT_GIVEN, tracing: NotGivenOr[Tracing | None] = NOT_GIVEN, ) -> None: if is_given(voice): self._opts.voice = voice if is_given(temperature): self._opts.temperature = temperature if is_given(turn_detection): self._opts.turn_detection = turn_detection if is_given(tool_choice): self._opts.tool_choice = cast(Optional[llm.ToolChoice], tool_choice) if is_given(input_audio_transcription): self._opts.input_audio_transcription = input_audio_transcription if is_given(input_audio_noise_reduction): self._opts.input_audio_noise_reduction = input_audio_noise_reduction if is_given(max_response_output_tokens): self._opts.max_response_output_tokens = max_response_output_tokens # type: ignore if is_given(speed): self._opts.speed = speed if is_given(tracing): self._opts.tracing = cast(Union[Tracing, None], tracing) for sess in self._sessions: sess.update_options( voice=voice, temperature=temperature, turn_detection=turn_detection, tool_choice=tool_choice, input_audio_transcription=input_audio_transcription, max_response_output_tokens=max_response_output_tokens, speed=speed, tracing=tracing, ) def _ensure_http_session(self) -> aiohttp.ClientSession: if not self._http_session: try: self._http_session = utils.http_context.http_session() except RuntimeError: self._http_session = aiohttp.ClientSession() self._http_session_owned = True return self._http_session def session(self) -> RealtimeSession: sess = RealtimeSession(self) self._sessions.add(sess) return sess async def aclose(self) -> None: if self._http_session_owned and self._http_session: await self._http_session.close()Ancestors
- livekit.agents.llm.realtime.RealtimeModel
Static methods
def with_azure(*,
azure_deployment: str,
azure_endpoint: str | None = None,
api_version: str | None = None,
api_key: str | None = None,
entra_token: str | None = None,
base_url: str | None = None,
voice: str = 'alloy',
modalities: "NotGivenOr[list[Literal['text', 'audio']]]" = NOT_GIVEN,
input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN,
input_audio_noise_reduction: InputAudioNoiseReduction | None = None,
turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN,
temperature: float = 0.8,
speed: NotGivenOr[float] = NOT_GIVEN,
tracing: NotGivenOr[Tracing | None] = NOT_GIVEN,
http_session: aiohttp.ClientSession | None = None) ‑> livekit.plugins.openai.realtime.realtime_model.RealtimeModel-
Create a RealtimeClient instance configured for Azure OpenAI Service.
Args
azure_deployment:str- The name of your Azure OpenAI deployment.
azure_endpoint:strorNone, optional- The endpoint URL for your Azure OpenAI resource. If None, will attempt to read from the environment variable AZURE_OPENAI_ENDPOINT.
api_version:strorNone, optional- API version to use with Azure OpenAI Service. If None, will attempt to read from the environment variable OPENAI_API_VERSION.
api_key:strorNone, optional- Azure OpenAI API key. If None, will attempt to read from the environment variable AZURE_OPENAI_API_KEY.
entra_token:strorNone, optional- Azure Entra authentication token. Required if not using API key authentication.
base_url:strorNone, optional- Base URL for the API endpoint. If None, constructed from the azure_endpoint.
voice:api_proto.Voice, optional- Voice setting for audio outputs. Defaults to "alloy".
- modalities (list[Literal["text", "audio"]], optional): Modalities to use for the session. Defaults to ["text", "audio"].
input_audio_transcription:InputTranscriptionOptions, optional- Options for transcribing input audio. Defaults to DEFAULT_INPUT_AUDIO_TRANSCRIPTION.
input_audio_noise_reduction:InputAudioNoiseReductionorNone, optional- Options for input audio noise reduction.
near_fieldis for close-talking microphones such as headphones,far_fieldis for far-field microphones such as laptop or conference room microphones. Defaults to None. turn_detection:ServerVadOptions, optional- Options for server-based voice activity detection (VAD). Defaults to DEFAULT_SERVER_VAD_OPTIONS.
temperature:float, optional- Sampling temperature for response generation. Defaults to 0.8.
- max_response_output_tokens (int or Literal["inf"], optional): Maximum number of tokens in the response. Defaults to "inf".
http_session:aiohttp.ClientSessionorNone, optional- Async HTTP session to use for requests. If None, a new session will be created.
Returns
RealtimeClient- An instance of RealtimeClient configured for Azure OpenAI Service.
Raises
ValueError- If required Azure parameters are missing or invalid.
Methods
async def aclose(self) ‑> None-
Expand source code
async def aclose(self) -> None: if self._http_session_owned and self._http_session: await self._http_session.close() def session(self) ‑> livekit.plugins.openai.realtime.realtime_model.RealtimeSession-
Expand source code
def session(self) -> RealtimeSession: sess = RealtimeSession(self) self._sessions.add(sess) return sess def update_options(self,
*,
voice: NotGivenOr[str] = NOT_GIVEN,
temperature: NotGivenOr[float] = NOT_GIVEN,
turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN,
tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN,
input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN,
input_audio_noise_reduction: NotGivenOr[InputAudioNoiseReduction | None] = NOT_GIVEN,
max_response_output_tokens: "NotGivenOr[int | Literal['inf'] | None]" = NOT_GIVEN,
speed: NotGivenOr[float] = NOT_GIVEN,
tracing: NotGivenOr[Tracing | None] = NOT_GIVEN) ‑> None-
Expand source code
def update_options( self, *, voice: NotGivenOr[str] = NOT_GIVEN, temperature: NotGivenOr[float] = NOT_GIVEN, turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN, tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN, input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN, input_audio_noise_reduction: NotGivenOr[InputAudioNoiseReduction | None] = NOT_GIVEN, max_response_output_tokens: NotGivenOr[int | Literal["inf"] | None] = NOT_GIVEN, speed: NotGivenOr[float] = NOT_GIVEN, tracing: NotGivenOr[Tracing | None] = NOT_GIVEN, ) -> None: if is_given(voice): self._opts.voice = voice if is_given(temperature): self._opts.temperature = temperature if is_given(turn_detection): self._opts.turn_detection = turn_detection if is_given(tool_choice): self._opts.tool_choice = cast(Optional[llm.ToolChoice], tool_choice) if is_given(input_audio_transcription): self._opts.input_audio_transcription = input_audio_transcription if is_given(input_audio_noise_reduction): self._opts.input_audio_noise_reduction = input_audio_noise_reduction if is_given(max_response_output_tokens): self._opts.max_response_output_tokens = max_response_output_tokens # type: ignore if is_given(speed): self._opts.speed = speed if is_given(tracing): self._opts.tracing = cast(Union[Tracing, None], tracing) for sess in self._sessions: sess.update_options( voice=voice, temperature=temperature, turn_detection=turn_detection, tool_choice=tool_choice, input_audio_transcription=input_audio_transcription, max_response_output_tokens=max_response_output_tokens, speed=speed, tracing=tracing, )
class RealtimeSession (realtime_model: RealtimeModel)-
Expand source code
class RealtimeSession( llm.RealtimeSession[Literal["openai_server_event_received", "openai_client_event_queued"]] ): """ A session for the OpenAI Realtime API. This class is used to interact with the OpenAI Realtime API. It is responsible for sending events to the OpenAI Realtime API and receiving events from it. It exposes two more events: - openai_server_event_received: expose the raw server events from the OpenAI Realtime API - openai_client_event_queued: expose the raw client events sent to the OpenAI Realtime API """ def __init__(self, realtime_model: RealtimeModel) -> None: super().__init__(realtime_model) self._realtime_model: RealtimeModel = realtime_model self._tools = llm.ToolContext.empty() self._msg_ch = utils.aio.Chan[Union[RealtimeClientEvent, dict[str, Any]]]() self._input_resampler: rtc.AudioResampler | None = None self._instructions: str | None = None self._main_atask = asyncio.create_task(self._main_task(), name="RealtimeSession._main_task") self.send_event(self._create_session_update_event()) self._response_created_futures: dict[str, asyncio.Future[llm.GenerationCreatedEvent]] = {} self._item_delete_future: dict[str, asyncio.Future] = {} self._item_create_future: dict[str, asyncio.Future] = {} self._current_generation: _ResponseGeneration | None = None self._remote_chat_ctx = llm.remote_chat_context.RemoteChatContext() self._update_chat_ctx_lock = asyncio.Lock() self._update_fnc_ctx_lock = asyncio.Lock() # 100ms chunks self._bstream = utils.audio.AudioByteStream( SAMPLE_RATE, NUM_CHANNELS, samples_per_channel=SAMPLE_RATE // 10 ) self._pushed_duration_s: float = 0 # duration of audio pushed to the OpenAI Realtime API def send_event(self, event: RealtimeClientEvent | dict[str, Any]) -> None: with contextlib.suppress(utils.aio.channel.ChanClosed): self._msg_ch.send_nowait(event) @utils.log_exceptions(logger=logger) async def _main_task(self) -> None: num_retries: int = 0 max_retries = self._realtime_model._opts.conn_options.max_retry async def _reconnect() -> None: logger.debug( "reconnecting to OpenAI Realtime API", extra={"max_session_duration": self._realtime_model._opts.max_session_duration}, ) events: list[RealtimeClientEvent] = [] # options and instructions events.append(self._create_session_update_event()) # tools tools = list(self._tools.function_tools.values()) if tools: events.append(self._create_tools_update_event(tools)) # chat context chat_ctx = self.chat_ctx.copy( exclude_function_call=True, exclude_instructions=True, exclude_empty_message=True, ) old_chat_ctx_copy = copy.deepcopy(self._remote_chat_ctx) self._remote_chat_ctx = llm.remote_chat_context.RemoteChatContext() events.extend(self._create_update_chat_ctx_events(chat_ctx)) try: for ev in events: msg = ev.model_dump(by_alias=True, exclude_unset=True, exclude_defaults=False) self.emit("openai_client_event_queued", msg) await ws_conn.send_str(json.dumps(msg)) except Exception as e: self._remote_chat_ctx = old_chat_ctx_copy # restore the old chat context raise APIConnectionError( message=( "Failed to send message to OpenAI Realtime API during session re-connection" ), ) from e logger.debug("reconnected to OpenAI Realtime API") self.emit("session_reconnected", llm.RealtimeSessionReconnectedEvent()) reconnecting = False while not self._msg_ch.closed: try: ws_conn = await self._create_ws_conn() if reconnecting: await _reconnect() num_retries = 0 # reset the retry counter await self._run_ws(ws_conn) except APIError as e: if max_retries == 0 or not e.retryable: self._emit_error(e, recoverable=False) raise elif num_retries == max_retries: self._emit_error(e, recoverable=False) raise APIConnectionError( f"OpenAI Realtime API connection failed after {num_retries} attempts", ) from e else: self._emit_error(e, recoverable=True) retry_interval = self._realtime_model._opts.conn_options._interval_for_retry( num_retries ) logger.warning( f"OpenAI Realtime API connection failed, retrying in {retry_interval}s", exc_info=e, extra={"attempt": num_retries, "max_retries": max_retries}, ) await asyncio.sleep(retry_interval) num_retries += 1 except Exception as e: self._emit_error(e, recoverable=False) raise reconnecting = True async def _create_ws_conn(self) -> aiohttp.ClientWebSocketResponse: headers = {"User-Agent": "LiveKit Agents"} if self._realtime_model._opts.is_azure: if self._realtime_model._opts.entra_token: headers["Authorization"] = f"Bearer {self._realtime_model._opts.entra_token}" if self._realtime_model._opts.api_key: headers["api-key"] = self._realtime_model._opts.api_key else: headers["Authorization"] = f"Bearer {self._realtime_model._opts.api_key}" headers["OpenAI-Beta"] = "realtime=v1" url = process_base_url( self._realtime_model._opts.base_url, self._realtime_model._opts.model, is_azure=self._realtime_model._opts.is_azure, api_version=self._realtime_model._opts.api_version, azure_deployment=self._realtime_model._opts.azure_deployment, ) if lk_oai_debug: logger.debug(f"connecting to Realtime API: {url}") try: return await asyncio.wait_for( self._realtime_model._ensure_http_session().ws_connect(url=url, headers=headers), self._realtime_model._opts.conn_options.timeout, ) except asyncio.TimeoutError as e: raise APIConnectionError( message="OpenAI Realtime API connection timed out", ) from e async def _run_ws(self, ws_conn: aiohttp.ClientWebSocketResponse) -> None: closing = False @utils.log_exceptions(logger=logger) async def _send_task() -> None: nonlocal closing async for msg in self._msg_ch: try: if isinstance(msg, BaseModel): msg = msg.model_dump( by_alias=True, exclude_unset=True, exclude_defaults=False ) self.emit("openai_client_event_queued", msg) await ws_conn.send_str(json.dumps(msg)) if lk_oai_debug: msg_copy = msg.copy() if msg_copy["type"] == "input_audio_buffer.append": msg_copy = {**msg_copy, "audio": "..."} logger.debug(f">>> {msg_copy}") except Exception: break closing = True await ws_conn.close() @utils.log_exceptions(logger=logger) async def _recv_task() -> None: while True: msg = await ws_conn.receive() if msg.type in ( aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSE, aiohttp.WSMsgType.CLOSING, ): if closing: # closing is expected, see _send_task return # this will trigger a reconnection raise APIConnectionError(message="OpenAI S2S connection closed unexpectedly") if msg.type != aiohttp.WSMsgType.TEXT: continue event = json.loads(msg.data) # emit the raw json dictionary instead of the BaseModel because different # providers can have different event types that are not part of the OpenAI Realtime API # noqa: E501 self.emit("openai_server_event_received", event) try: if lk_oai_debug: event_copy = event.copy() if event_copy["type"] == "response.audio.delta": event_copy = {**event_copy, "delta": "..."} logger.debug(f"<<< {event_copy}") if event["type"] == "input_audio_buffer.speech_started": self._handle_input_audio_buffer_speech_started( InputAudioBufferSpeechStartedEvent.construct(**event) ) elif event["type"] == "input_audio_buffer.speech_stopped": self._handle_input_audio_buffer_speech_stopped( InputAudioBufferSpeechStoppedEvent.construct(**event) ) elif event["type"] == "response.created": self._handle_response_created(ResponseCreatedEvent.construct(**event)) elif event["type"] == "response.output_item.added": self._handle_response_output_item_added( ResponseOutputItemAddedEvent.construct(**event) ) elif event["type"] == "response.content_part.added": self._handle_response_content_part_added( ResponseContentPartAddedEvent.construct(**event) ) elif event["type"] == "conversation.item.created": self._handle_conversion_item_created( ConversationItemCreatedEvent.construct(**event) ) elif event["type"] == "conversation.item.deleted": self._handle_conversion_item_deleted( ConversationItemDeletedEvent.construct(**event) ) elif event["type"] == "conversation.item.input_audio_transcription.completed": self._handle_conversion_item_input_audio_transcription_completed( ConversationItemInputAudioTranscriptionCompletedEvent.construct(**event) ) elif event["type"] == "conversation.item.input_audio_transcription.failed": self._handle_conversion_item_input_audio_transcription_failed( ConversationItemInputAudioTranscriptionFailedEvent.construct(**event) ) elif event["type"] == "response.text.delta": self._handle_response_text_delta(ResponseTextDeltaEvent.construct(**event)) elif event["type"] == "response.text.done": self._handle_response_text_done(ResponseTextDoneEvent.construct(**event)) elif event["type"] == "response.audio_transcript.delta": self._handle_response_audio_transcript_delta(event) elif event["type"] == "response.audio.delta": self._handle_response_audio_delta( ResponseAudioDeltaEvent.construct(**event) ) elif event["type"] == "response.audio_transcript.done": self._handle_response_audio_transcript_done( ResponseAudioTranscriptDoneEvent.construct(**event) ) elif event["type"] == "response.audio.done": self._handle_response_audio_done(ResponseAudioDoneEvent.construct(**event)) elif event["type"] == "response.output_item.done": self._handle_response_output_item_done( ResponseOutputItemDoneEvent.construct(**event) ) elif event["type"] == "response.done": self._handle_response_done(ResponseDoneEvent.construct(**event)) elif event["type"] == "error": self._handle_error(ErrorEvent.construct(**event)) except Exception: if event["type"] == "response.audio.delta": event["delta"] = event["delta"][:10] + "..." logger.exception("failed to handle event", extra={"event": event}) tasks = [ asyncio.create_task(_recv_task(), name="_recv_task"), asyncio.create_task(_send_task(), name="_send_task"), ] wait_reconnect_task: asyncio.Task | None = None if self._realtime_model._opts.max_session_duration is not None: wait_reconnect_task = asyncio.create_task( asyncio.sleep(self._realtime_model._opts.max_session_duration), name="_timeout_task", ) tasks.append(wait_reconnect_task) try: done, _ = await asyncio.wait(tasks, return_when=asyncio.FIRST_COMPLETED) # propagate exceptions from completed tasks for task in done: if task != wait_reconnect_task: task.result() if wait_reconnect_task and wait_reconnect_task in done and self._current_generation: # wait for the current generation to complete before reconnecting await self._current_generation._done_fut closing = True finally: await utils.aio.cancel_and_wait(*tasks) await ws_conn.close() def _create_session_update_event(self) -> SessionUpdateEvent: input_audio_transcription_opts = self._realtime_model._opts.input_audio_transcription input_audio_transcription = ( session_update_event.SessionInputAudioTranscription.model_validate( input_audio_transcription_opts.model_dump( by_alias=True, exclude_unset=True, exclude_defaults=True, ) ) if input_audio_transcription_opts else None ) turn_detection_opts = self._realtime_model._opts.turn_detection turn_detection = ( session_update_event.SessionTurnDetection.model_validate( turn_detection_opts.model_dump( by_alias=True, exclude_unset=True, exclude_defaults=True, ) ) if turn_detection_opts else None ) tracing_opts = self._realtime_model._opts.tracing if isinstance(tracing_opts, TracingTracingConfiguration): tracing: session_update_event.SessionTracing | None = ( session_update_event.SessionTracingTracingConfiguration.model_validate( tracing_opts.model_dump( by_alias=True, exclude_unset=True, exclude_defaults=True, ) ) ) else: tracing = tracing_opts kwargs: dict[str, Any] = { "model": self._realtime_model._opts.model, "voice": self._realtime_model._opts.voice, "input_audio_format": "pcm16", "output_audio_format": "pcm16", "modalities": self._realtime_model._opts.modalities, "turn_detection": turn_detection, "input_audio_transcription": input_audio_transcription, "input_audio_noise_reduction": self._realtime_model._opts.input_audio_noise_reduction, "temperature": self._realtime_model._opts.temperature, "tool_choice": _to_oai_tool_choice(self._realtime_model._opts.tool_choice), } if self._instructions is not None: kwargs["instructions"] = self._instructions if self._realtime_model._opts.speed is not None: kwargs["speed"] = self._realtime_model._opts.speed if tracing: kwargs["tracing"] = tracing # initial session update return SessionUpdateEvent( type="session.update", # Using model_construct since OpenAI restricts voices to those defined in the BaseModel. # noqa: E501 # Other providers support different voices, so we need to accommodate that. session=session_update_event.Session.model_construct(**kwargs), event_id=utils.shortuuid("session_update_"), ) @property def chat_ctx(self) -> llm.ChatContext: return self._remote_chat_ctx.to_chat_ctx() @property def tools(self) -> llm.ToolContext: return self._tools.copy() def update_options( self, *, tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN, voice: NotGivenOr[str] = NOT_GIVEN, temperature: NotGivenOr[float] = NOT_GIVEN, turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN, max_response_output_tokens: NotGivenOr[int | Literal["inf"] | None] = NOT_GIVEN, input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN, input_audio_noise_reduction: NotGivenOr[InputAudioNoiseReduction | None] = NOT_GIVEN, speed: NotGivenOr[float] = NOT_GIVEN, tracing: NotGivenOr[Tracing | None] = NOT_GIVEN, ) -> None: kwargs: dict[str, Any] = {} if is_given(tool_choice): tool_choice = cast(Optional[llm.ToolChoice], tool_choice) self._realtime_model._opts.tool_choice = tool_choice kwargs["tool_choice"] = _to_oai_tool_choice(tool_choice) if is_given(voice): self._realtime_model._opts.voice = voice kwargs["voice"] = voice if is_given(temperature): self._realtime_model._opts.temperature = temperature kwargs["temperature"] = temperature if is_given(turn_detection): self._realtime_model._opts.turn_detection = turn_detection kwargs["turn_detection"] = turn_detection if is_given(max_response_output_tokens): self._realtime_model._opts.max_response_output_tokens = max_response_output_tokens # type: ignore kwargs["max_response_output_tokens"] = max_response_output_tokens if is_given(input_audio_transcription): self._realtime_model._opts.input_audio_transcription = input_audio_transcription kwargs["input_audio_transcription"] = input_audio_transcription if is_given(input_audio_noise_reduction): self._realtime_model._opts.input_audio_noise_reduction = input_audio_noise_reduction kwargs["input_audio_noise_reduction"] = input_audio_noise_reduction if is_given(speed): self._realtime_model._opts.speed = speed kwargs["speed"] = speed if is_given(tracing): self._realtime_model._opts.tracing = cast(Union[Tracing, None], tracing) kwargs["tracing"] = cast(Union[Tracing, None], tracing) if kwargs: self.send_event( SessionUpdateEvent( type="session.update", session=session_update_event.Session.model_construct(**kwargs), event_id=utils.shortuuid("options_update_"), ) ) async def update_chat_ctx(self, chat_ctx: llm.ChatContext) -> None: async with self._update_chat_ctx_lock: events = self._create_update_chat_ctx_events(chat_ctx) futs: list[asyncio.Future[None]] = [] for ev in events: futs.append(f := asyncio.Future[None]()) if isinstance(ev, ConversationItemDeleteEvent): self._item_delete_future[ev.item_id] = f elif isinstance(ev, ConversationItemCreateEvent): assert ev.item.id is not None self._item_create_future[ev.item.id] = f self.send_event(ev) if not futs: return try: await asyncio.wait_for(asyncio.gather(*futs, return_exceptions=True), timeout=5.0) except asyncio.TimeoutError: raise llm.RealtimeError("update_chat_ctx timed out.") from None def _create_update_chat_ctx_events( self, chat_ctx: llm.ChatContext ) -> list[ConversationItemCreateEvent | ConversationItemDeleteEvent]: events: list[ConversationItemCreateEvent | ConversationItemDeleteEvent] = [] diff_ops = llm.utils.compute_chat_ctx_diff(self._remote_chat_ctx.to_chat_ctx(), chat_ctx) def _delete_item(msg_id: str) -> None: events.append( ConversationItemDeleteEvent( type="conversation.item.delete", item_id=msg_id, event_id=utils.shortuuid("chat_ctx_delete_"), ) ) def _create_item(previous_msg_id: str | None, msg_id: str) -> None: chat_item = chat_ctx.get_by_id(msg_id) assert chat_item is not None events.append( ConversationItemCreateEvent( type="conversation.item.create", item=_livekit_item_to_openai_item(chat_item), previous_item_id=("root" if previous_msg_id is None else previous_msg_id), event_id=utils.shortuuid("chat_ctx_create_"), ) ) for msg_id in diff_ops.to_remove: _delete_item(msg_id) for previous_msg_id, msg_id in diff_ops.to_create: _create_item(previous_msg_id, msg_id) # update the items with the same id but different content for previous_msg_id, msg_id in diff_ops.to_update: _delete_item(msg_id) _create_item(previous_msg_id, msg_id) return events async def update_tools(self, tools: list[llm.FunctionTool | llm.RawFunctionTool]) -> None: async with self._update_fnc_ctx_lock: ev = self._create_tools_update_event(tools) self.send_event(ev) assert ev.session.tools is not None retained_tool_names = {name for t in ev.session.tools if (name := t.name) is not None} retained_tools = [ tool for tool in tools if (is_function_tool(tool) and get_function_info(tool).name in retained_tool_names) or ( is_raw_function_tool(tool) and get_raw_function_info(tool).name in retained_tool_names ) ] self._tools = llm.ToolContext(retained_tools) def _create_tools_update_event( self, tools: list[llm.FunctionTool | llm.RawFunctionTool] ) -> SessionUpdateEvent: oai_tools: list[session_update_event.SessionTool] = [] retained_tools: list[llm.FunctionTool | llm.RawFunctionTool] = [] for tool in tools: if is_function_tool(tool): tool_desc = llm.utils.build_legacy_openai_schema(tool, internally_tagged=True) elif is_raw_function_tool(tool): tool_info = get_raw_function_info(tool) tool_desc = tool_info.raw_schema tool_desc["type"] = "function" # internally tagged else: logger.error( "OpenAI Realtime API doesn't support this tool type", extra={"tool": tool} ) continue try: session_tool = session_update_event.SessionTool.model_validate(tool_desc) oai_tools.append(session_tool) retained_tools.append(tool) except ValidationError: logger.error( "OpenAI Realtime API doesn't support this tool", extra={"tool": tool_desc}, ) continue return SessionUpdateEvent( type="session.update", session=session_update_event.Session.model_construct( model=self._realtime_model._opts.model, tools=oai_tools, ), event_id=utils.shortuuid("tools_update_"), ) async def update_instructions(self, instructions: str) -> None: event_id = utils.shortuuid("instructions_update_") # f = asyncio.Future() # self._response_futures[event_id] = f self.send_event( SessionUpdateEvent( type="session.update", session=session_update_event.Session.model_construct(instructions=instructions), event_id=event_id, ) ) self._instructions = instructions def push_audio(self, frame: rtc.AudioFrame) -> None: for f in self._resample_audio(frame): data = f.data.tobytes() for nf in self._bstream.write(data): self.send_event( InputAudioBufferAppendEvent( type="input_audio_buffer.append", audio=base64.b64encode(nf.data).decode("utf-8"), ) ) self._pushed_duration_s += nf.duration def push_video(self, frame: rtc.VideoFrame) -> None: pass def commit_audio(self) -> None: if self._pushed_duration_s > 0.1: # OpenAI requires at least 100ms of audio self.send_event(InputAudioBufferCommitEvent(type="input_audio_buffer.commit")) self._pushed_duration_s = 0 def clear_audio(self) -> None: self.send_event(InputAudioBufferClearEvent(type="input_audio_buffer.clear")) self._pushed_duration_s = 0 def generate_reply( self, *, instructions: NotGivenOr[str] = NOT_GIVEN ) -> asyncio.Future[llm.GenerationCreatedEvent]: event_id = utils.shortuuid("response_create_") fut = asyncio.Future[llm.GenerationCreatedEvent]() self._response_created_futures[event_id] = fut self.send_event( ResponseCreateEvent( type="response.create", event_id=event_id, response=Response( instructions=instructions or None, metadata={"client_event_id": event_id}, ), ) ) def _on_timeout() -> None: if fut and not fut.done(): fut.set_exception(llm.RealtimeError("generate_reply timed out.")) handle = asyncio.get_event_loop().call_later(5.0, _on_timeout) fut.add_done_callback(lambda _: handle.cancel()) return fut def interrupt(self) -> None: self.send_event(ResponseCancelEvent(type="response.cancel")) def truncate( self, *, message_id: str, modalities: list[Literal["text", "audio"]], audio_end_ms: int, audio_transcript: NotGivenOr[str] = NOT_GIVEN, ) -> None: if "audio" in modalities: self.send_event( ConversationItemTruncateEvent( type="conversation.item.truncate", content_index=0, item_id=message_id, audio_end_ms=audio_end_ms, ) ) elif utils.is_given(audio_transcript): # sync the forwarded text to the remote chat ctx chat_ctx = self.chat_ctx.copy() if (idx := chat_ctx.index_by_id(message_id)) is not None: new_item = copy.copy(chat_ctx.items[idx]) assert new_item.type == "message" new_item.content = [audio_transcript] chat_ctx.items[idx] = new_item events = self._create_update_chat_ctx_events(chat_ctx) for ev in events: self.send_event(ev) async def aclose(self) -> None: self._msg_ch.close() await self._main_atask def _resample_audio(self, frame: rtc.AudioFrame) -> Iterator[rtc.AudioFrame]: if self._input_resampler: if frame.sample_rate != self._input_resampler._input_rate: # input audio changed to a different sample rate self._input_resampler = None if self._input_resampler is None and ( frame.sample_rate != SAMPLE_RATE or frame.num_channels != NUM_CHANNELS ): self._input_resampler = rtc.AudioResampler( input_rate=frame.sample_rate, output_rate=SAMPLE_RATE, num_channels=NUM_CHANNELS, ) if self._input_resampler: # TODO(long): flush the resampler when the input source is changed yield from self._input_resampler.push(frame) else: yield frame def _handle_input_audio_buffer_speech_started( self, _: InputAudioBufferSpeechStartedEvent ) -> None: self.emit("input_speech_started", llm.InputSpeechStartedEvent()) def _handle_input_audio_buffer_speech_stopped( self, _: InputAudioBufferSpeechStoppedEvent ) -> None: user_transcription_enabled = ( self._realtime_model._opts.input_audio_transcription is not None ) self.emit( "input_speech_stopped", llm.InputSpeechStoppedEvent(user_transcription_enabled=user_transcription_enabled), ) def _handle_response_created(self, event: ResponseCreatedEvent) -> None: assert event.response.id is not None, "response.id is None" self._current_generation = _ResponseGeneration( message_ch=utils.aio.Chan(), function_ch=utils.aio.Chan(), messages={}, _created_timestamp=time.time(), _done_fut=asyncio.Future(), ) generation_ev = llm.GenerationCreatedEvent( message_stream=self._current_generation.message_ch, function_stream=self._current_generation.function_ch, user_initiated=False, ) if ( isinstance(event.response.metadata, dict) and (client_event_id := event.response.metadata.get("client_event_id")) and (fut := self._response_created_futures.pop(client_event_id, None)) ): generation_ev.user_initiated = True fut.set_result(generation_ev) self.emit("generation_created", generation_ev) def _handle_response_output_item_added(self, event: ResponseOutputItemAddedEvent) -> None: assert self._current_generation is not None, "current_generation is None" assert (item_id := event.item.id) is not None, "item.id is None" assert (item_type := event.item.type) is not None, "item.type is None" if item_type == "message": item_generation = _MessageGeneration( message_id=item_id, text_ch=utils.aio.Chan(), audio_ch=utils.aio.Chan(), modalities=asyncio.Future(), ) if not self._realtime_model.capabilities.audio_output: item_generation.audio_ch.close() item_generation.modalities.set_result(["text"]) self._current_generation.message_ch.send_nowait( llm.MessageGeneration( message_id=item_id, text_stream=item_generation.text_ch, audio_stream=item_generation.audio_ch, modalities=item_generation.modalities, ) ) self._current_generation.messages[item_id] = item_generation def _handle_response_content_part_added(self, event: ResponseContentPartAddedEvent) -> None: assert self._current_generation is not None, "current_generation is None" assert (item_id := event.item_id) is not None, "item_id is None" assert (item_type := event.part.type) is not None, "part.type is None" if item_type == "text" and self._realtime_model.capabilities.audio_output: logger.warning("Text response received from OpenAI Realtime API in audio modality.") with contextlib.suppress(asyncio.InvalidStateError): self._current_generation.messages[item_id].modalities.set_result( ["text"] if item_type == "text" else ["audio", "text"] ) def _handle_conversion_item_created(self, event: ConversationItemCreatedEvent) -> None: assert event.item.id is not None, "item.id is None" try: self._remote_chat_ctx.insert( event.previous_item_id, _openai_item_to_livekit_item(event.item) ) except ValueError as e: logger.warning( f"failed to insert item `{event.item.id}`: {str(e)}", ) if fut := self._item_create_future.pop(event.item.id, None): fut.set_result(None) def _handle_conversion_item_deleted(self, event: ConversationItemDeletedEvent) -> None: assert event.item_id is not None, "item_id is None" try: self._remote_chat_ctx.delete(event.item_id) except ValueError as e: logger.warning( f"failed to delete item `{event.item_id}`: {str(e)}", ) if fut := self._item_delete_future.pop(event.item_id, None): fut.set_result(None) def _handle_conversion_item_input_audio_transcription_completed( self, event: ConversationItemInputAudioTranscriptionCompletedEvent ) -> None: if remote_item := self._remote_chat_ctx.get(event.item_id): assert isinstance(remote_item.item, llm.ChatMessage) remote_item.item.content.append(event.transcript) self.emit( "input_audio_transcription_completed", llm.InputTranscriptionCompleted( item_id=event.item_id, transcript=event.transcript, is_final=True, ), ) def _handle_conversion_item_input_audio_transcription_failed( self, event: ConversationItemInputAudioTranscriptionFailedEvent ) -> None: logger.error( "OpenAI Realtime API failed to transcribe input audio", extra={"error": event.error}, ) def _handle_response_text_delta(self, event: ResponseTextDeltaEvent) -> None: assert self._current_generation is not None, "current_generation is None" item_generation = self._current_generation.messages[event.item_id] item_generation.text_ch.send_nowait(event.delta) item_generation.audio_transcript += event.delta def _handle_response_text_done(self, event: ResponseTextDoneEvent) -> None: assert self._current_generation is not None, "current_generation is None" def _handle_response_audio_transcript_delta(self, event: dict[str, Any]) -> None: assert self._current_generation is not None, "current_generation is None" item_id = event["item_id"] delta = event["delta"] if (start_time := event.get("start_time")) is not None: delta = io.TimedString(delta, start_time=start_time) item_generation = self._current_generation.messages[item_id] item_generation.text_ch.send_nowait(delta) item_generation.audio_transcript += delta def _handle_response_audio_delta(self, event: ResponseAudioDeltaEvent) -> None: assert self._current_generation is not None, "current_generation is None" item_generation = self._current_generation.messages[event.item_id] if not item_generation.modalities.done(): item_generation.modalities.set_result(["audio", "text"]) data = base64.b64decode(event.delta) item_generation.audio_ch.send_nowait( rtc.AudioFrame( data=data, sample_rate=SAMPLE_RATE, num_channels=NUM_CHANNELS, samples_per_channel=len(data) // 2, ) ) def _handle_response_audio_transcript_done(self, _: ResponseAudioTranscriptDoneEvent) -> None: assert self._current_generation is not None, "current_generation is None" def _handle_response_audio_done(self, _: ResponseAudioDoneEvent) -> None: assert self._current_generation is not None, "current_generation is None" def _handle_response_output_item_done(self, event: ResponseOutputItemDoneEvent) -> None: assert self._current_generation is not None, "current_generation is None" assert (item_id := event.item.id) is not None, "item.id is None" assert (item_type := event.item.type) is not None, "item.type is None" if item_type == "function_call": item = event.item assert item.call_id is not None, "call_id is None" assert item.name is not None, "name is None" assert item.arguments is not None, "arguments is None" self._current_generation.function_ch.send_nowait( llm.FunctionCall( call_id=item.call_id, name=item.name, arguments=item.arguments, ) ) elif item_type == "message": item_generation = self._current_generation.messages[item_id] item_generation.text_ch.close() item_generation.audio_ch.close() if not item_generation.modalities.done(): # in case message modalities is not set, this shouldn't happen item_generation.modalities.set_result(self._realtime_model._opts.modalities) def _handle_response_done(self, event: ResponseDoneEvent) -> None: if self._current_generation is None: return # OpenAI has a race condition where we could receive response.done without any previous response.created (This happens generally during interruption) # noqa: E501 assert self._current_generation is not None, "current_generation is None" created_timestamp = self._current_generation._created_timestamp first_token_timestamp = self._current_generation._first_token_timestamp for generation in self._current_generation.messages.values(): # close all messages that haven't been closed yet if not generation.text_ch.closed: generation.text_ch.close() if not generation.audio_ch.closed: generation.audio_ch.close() if not generation.modalities.done(): generation.modalities.set_result(self._realtime_model._opts.modalities) self._current_generation.function_ch.close() self._current_generation.message_ch.close() for item_id, item_generation in self._current_generation.messages.items(): if (remote_item := self._remote_chat_ctx.get(item_id)) and isinstance( remote_item.item, llm.ChatMessage ): remote_item.item.content.append(item_generation.audio_transcript) with contextlib.suppress(asyncio.InvalidStateError): self._current_generation._done_fut.set_result(None) self._current_generation = None # calculate metrics usage = ( event.response.usage.model_dump(exclude_defaults=True) if event.response.usage else {} ) ttft = first_token_timestamp - created_timestamp if first_token_timestamp else -1 duration = time.time() - created_timestamp metrics = RealtimeModelMetrics( timestamp=created_timestamp, request_id=event.response.id or "", ttft=ttft, duration=duration, cancelled=event.response.status == "cancelled", label=self._realtime_model._label, input_tokens=usage.get("input_tokens", 0), output_tokens=usage.get("output_tokens", 0), total_tokens=usage.get("total_tokens", 0), tokens_per_second=usage.get("output_tokens", 0) / duration, input_token_details=RealtimeModelMetrics.InputTokenDetails( audio_tokens=usage.get("input_token_details", {}).get("audio_tokens", 0), cached_tokens=usage.get("input_token_details", {}).get("cached_tokens", 0), text_tokens=usage.get("input_token_details", {}).get("text_tokens", 0), cached_tokens_details=RealtimeModelMetrics.CachedTokenDetails( text_tokens=usage.get("input_token_details", {}) .get("cached_tokens_details", {}) .get("text_tokens", 0), audio_tokens=usage.get("input_token_details", {}) .get("cached_tokens_details", {}) .get("audio_tokens", 0), image_tokens=usage.get("input_token_details", {}) .get("cached_tokens_details", {}) .get("image_tokens", 0), ), image_tokens=0, ), output_token_details=RealtimeModelMetrics.OutputTokenDetails( text_tokens=usage.get("output_token_details", {}).get("text_tokens", 0), audio_tokens=usage.get("output_token_details", {}).get("audio_tokens", 0), image_tokens=0, ), ) self.emit("metrics_collected", metrics) self._handle_response_done_but_not_complete(event) def _handle_response_done_but_not_complete(self, event: ResponseDoneEvent) -> None: """Handle response done but not complete, i.e. cancelled, incomplete or failed. For example this method will emit an error if we receive a "failed" status, e.g. with type "invalid_request_error" due to code "inference_rate_limit_exceeded". In other failures it will emit a debug level log. """ if event.response.status == "completed": return if event.response.status == "failed": if event.response.status_details and hasattr(event.response.status_details, "error"): error_type = getattr(event.response.status_details.error, "type", "unknown") error_body = event.response.status_details.error message = f"OpenAI Realtime API response failed with error type: {error_type}" else: error_body = None message = "OpenAI Realtime API response failed with unknown error" self._emit_error( APIError( message=message, body=error_body, retryable=True, ), # all possible faulures undocumented by openai, # so we assume optimistically all retryable/recoverable recoverable=True, ) elif event.response.status in {"cancelled", "incomplete"}: logger.debug( "OpenAI Realtime API response done but not complete with status: %s", event.response.status, extra={ "event_id": event.response.id, "event_response_status": event.response.status, }, ) else: logger.debug("Unknown response status: %s", event.response.status) def _handle_error(self, event: ErrorEvent) -> None: if event.error.message.startswith("Cancellation failed"): return logger.error( "OpenAI Realtime API returned an error", extra={"error": event.error}, ) self._emit_error( APIError( message="OpenAI Realtime API returned an error", body=event.error, retryable=True, ), recoverable=True, ) # TODO: set exception for the response future if it exists def _emit_error(self, error: Exception, recoverable: bool) -> None: self.emit( "error", llm.RealtimeModelError( timestamp=time.time(), label=self._realtime_model._label, error=error, recoverable=recoverable, ), )A session for the OpenAI Realtime API.
This class is used to interact with the OpenAI Realtime API. It is responsible for sending events to the OpenAI Realtime API and receiving events from it.
It exposes two more events: - openai_server_event_received: expose the raw server events from the OpenAI Realtime API - openai_client_event_queued: expose the raw client events sent to the OpenAI Realtime API
Ancestors
- livekit.agents.llm.realtime.RealtimeSession
- abc.ABC
- EventEmitter
- typing.Generic
Instance variables
prop chat_ctx : llm.ChatContext-
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@property def chat_ctx(self) -> llm.ChatContext: return self._remote_chat_ctx.to_chat_ctx() prop tools : llm.ToolContext-
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@property def tools(self) -> llm.ToolContext: return self._tools.copy()
Methods
async def aclose(self) ‑> None-
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async def aclose(self) -> None: self._msg_ch.close() await self._main_atask def clear_audio(self) ‑> None-
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def clear_audio(self) -> None: self.send_event(InputAudioBufferClearEvent(type="input_audio_buffer.clear")) self._pushed_duration_s = 0 def commit_audio(self) ‑> None-
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def commit_audio(self) -> None: if self._pushed_duration_s > 0.1: # OpenAI requires at least 100ms of audio self.send_event(InputAudioBufferCommitEvent(type="input_audio_buffer.commit")) self._pushed_duration_s = 0 def generate_reply(self, *, instructions: NotGivenOr[str] = NOT_GIVEN) ‑> _asyncio.Future[livekit.agents.llm.realtime.GenerationCreatedEvent]-
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def generate_reply( self, *, instructions: NotGivenOr[str] = NOT_GIVEN ) -> asyncio.Future[llm.GenerationCreatedEvent]: event_id = utils.shortuuid("response_create_") fut = asyncio.Future[llm.GenerationCreatedEvent]() self._response_created_futures[event_id] = fut self.send_event( ResponseCreateEvent( type="response.create", event_id=event_id, response=Response( instructions=instructions or None, metadata={"client_event_id": event_id}, ), ) ) def _on_timeout() -> None: if fut and not fut.done(): fut.set_exception(llm.RealtimeError("generate_reply timed out.")) handle = asyncio.get_event_loop().call_later(5.0, _on_timeout) fut.add_done_callback(lambda _: handle.cancel()) return fut def interrupt(self) ‑> None-
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def interrupt(self) -> None: self.send_event(ResponseCancelEvent(type="response.cancel")) def push_audio(self, frame: rtc.AudioFrame) ‑> None-
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def push_audio(self, frame: rtc.AudioFrame) -> None: for f in self._resample_audio(frame): data = f.data.tobytes() for nf in self._bstream.write(data): self.send_event( InputAudioBufferAppendEvent( type="input_audio_buffer.append", audio=base64.b64encode(nf.data).decode("utf-8"), ) ) self._pushed_duration_s += nf.duration def push_video(self, frame: rtc.VideoFrame) ‑> None-
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def push_video(self, frame: rtc.VideoFrame) -> None: pass def send_event(self, event: RealtimeClientEvent | dict[str, Any]) ‑> None-
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def send_event(self, event: RealtimeClientEvent | dict[str, Any]) -> None: with contextlib.suppress(utils.aio.channel.ChanClosed): self._msg_ch.send_nowait(event) def truncate(self,
*,
message_id: str,
modalities: "list[Literal['text', 'audio']]",
audio_end_ms: int,
audio_transcript: NotGivenOr[str] = NOT_GIVEN) ‑> None-
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def truncate( self, *, message_id: str, modalities: list[Literal["text", "audio"]], audio_end_ms: int, audio_transcript: NotGivenOr[str] = NOT_GIVEN, ) -> None: if "audio" in modalities: self.send_event( ConversationItemTruncateEvent( type="conversation.item.truncate", content_index=0, item_id=message_id, audio_end_ms=audio_end_ms, ) ) elif utils.is_given(audio_transcript): # sync the forwarded text to the remote chat ctx chat_ctx = self.chat_ctx.copy() if (idx := chat_ctx.index_by_id(message_id)) is not None: new_item = copy.copy(chat_ctx.items[idx]) assert new_item.type == "message" new_item.content = [audio_transcript] chat_ctx.items[idx] = new_item events = self._create_update_chat_ctx_events(chat_ctx) for ev in events: self.send_event(ev) async def update_chat_ctx(self, chat_ctx: llm.ChatContext) ‑> None-
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async def update_chat_ctx(self, chat_ctx: llm.ChatContext) -> None: async with self._update_chat_ctx_lock: events = self._create_update_chat_ctx_events(chat_ctx) futs: list[asyncio.Future[None]] = [] for ev in events: futs.append(f := asyncio.Future[None]()) if isinstance(ev, ConversationItemDeleteEvent): self._item_delete_future[ev.item_id] = f elif isinstance(ev, ConversationItemCreateEvent): assert ev.item.id is not None self._item_create_future[ev.item.id] = f self.send_event(ev) if not futs: return try: await asyncio.wait_for(asyncio.gather(*futs, return_exceptions=True), timeout=5.0) except asyncio.TimeoutError: raise llm.RealtimeError("update_chat_ctx timed out.") from None async def update_instructions(self, instructions: str) ‑> None-
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async def update_instructions(self, instructions: str) -> None: event_id = utils.shortuuid("instructions_update_") # f = asyncio.Future() # self._response_futures[event_id] = f self.send_event( SessionUpdateEvent( type="session.update", session=session_update_event.Session.model_construct(instructions=instructions), event_id=event_id, ) ) self._instructions = instructions def update_options(self,
*,
tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN,
voice: NotGivenOr[str] = NOT_GIVEN,
temperature: NotGivenOr[float] = NOT_GIVEN,
turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN,
max_response_output_tokens: "NotGivenOr[int | Literal['inf'] | None]" = NOT_GIVEN,
input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN,
input_audio_noise_reduction: NotGivenOr[InputAudioNoiseReduction | None] = NOT_GIVEN,
speed: NotGivenOr[float] = NOT_GIVEN,
tracing: NotGivenOr[Tracing | None] = NOT_GIVEN) ‑> None-
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def update_options( self, *, tool_choice: NotGivenOr[llm.ToolChoice | None] = NOT_GIVEN, voice: NotGivenOr[str] = NOT_GIVEN, temperature: NotGivenOr[float] = NOT_GIVEN, turn_detection: NotGivenOr[TurnDetection | None] = NOT_GIVEN, max_response_output_tokens: NotGivenOr[int | Literal["inf"] | None] = NOT_GIVEN, input_audio_transcription: NotGivenOr[InputAudioTranscription | None] = NOT_GIVEN, input_audio_noise_reduction: NotGivenOr[InputAudioNoiseReduction | None] = NOT_GIVEN, speed: NotGivenOr[float] = NOT_GIVEN, tracing: NotGivenOr[Tracing | None] = NOT_GIVEN, ) -> None: kwargs: dict[str, Any] = {} if is_given(tool_choice): tool_choice = cast(Optional[llm.ToolChoice], tool_choice) self._realtime_model._opts.tool_choice = tool_choice kwargs["tool_choice"] = _to_oai_tool_choice(tool_choice) if is_given(voice): self._realtime_model._opts.voice = voice kwargs["voice"] = voice if is_given(temperature): self._realtime_model._opts.temperature = temperature kwargs["temperature"] = temperature if is_given(turn_detection): self._realtime_model._opts.turn_detection = turn_detection kwargs["turn_detection"] = turn_detection if is_given(max_response_output_tokens): self._realtime_model._opts.max_response_output_tokens = max_response_output_tokens # type: ignore kwargs["max_response_output_tokens"] = max_response_output_tokens if is_given(input_audio_transcription): self._realtime_model._opts.input_audio_transcription = input_audio_transcription kwargs["input_audio_transcription"] = input_audio_transcription if is_given(input_audio_noise_reduction): self._realtime_model._opts.input_audio_noise_reduction = input_audio_noise_reduction kwargs["input_audio_noise_reduction"] = input_audio_noise_reduction if is_given(speed): self._realtime_model._opts.speed = speed kwargs["speed"] = speed if is_given(tracing): self._realtime_model._opts.tracing = cast(Union[Tracing, None], tracing) kwargs["tracing"] = cast(Union[Tracing, None], tracing) if kwargs: self.send_event( SessionUpdateEvent( type="session.update", session=session_update_event.Session.model_construct(**kwargs), event_id=utils.shortuuid("options_update_"), ) ) async def update_tools(self, tools: list[llm.FunctionTool | llm.RawFunctionTool]) ‑> None-
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async def update_tools(self, tools: list[llm.FunctionTool | llm.RawFunctionTool]) -> None: async with self._update_fnc_ctx_lock: ev = self._create_tools_update_event(tools) self.send_event(ev) assert ev.session.tools is not None retained_tool_names = {name for t in ev.session.tools if (name := t.name) is not None} retained_tools = [ tool for tool in tools if (is_function_tool(tool) and get_function_info(tool).name in retained_tool_names) or ( is_raw_function_tool(tool) and get_raw_function_info(tool).name in retained_tool_names ) ] self._tools = llm.ToolContext(retained_tools)
Inherited members