Package videosdk.plugins.elevenlabs
Sub-modules
videosdk.plugins.elevenlabs.sttvideosdk.plugins.elevenlabs.tts
Classes
class ElevenLabsSTT (*,
api_key: str | None = None,
model_id: str = 'scribe_v2_realtime',
language_code: str = 'en',
sample_rate: int = 48000,
commit_strategy: str = 'vad',
vad_silence_threshold_secs: float = 0.8,
vad_threshold: float = 0.4,
min_speech_duration_ms: int = 50,
min_silence_duration_ms: int = 50,
base_url: str = 'wss://api.elevenlabs.io/v1/speech-to-text/realtime',
detect_language: bool = False)-
Expand source code
class ElevenLabsSTT(BaseSTT): """ ElevenLabs Realtime Speech-to-Text (STT) client. """ def __init__( self, *, api_key: str | None = None, model_id: str = "scribe_v2_realtime", language_code: str = "en", sample_rate: int = 48000, commit_strategy: str = "vad", vad_silence_threshold_secs: float = 0.8, vad_threshold: float = 0.4, min_speech_duration_ms: int = 50, min_silence_duration_ms: int = 50, base_url: str = "wss://api.elevenlabs.io/v1/speech-to-text/realtime", detect_language:bool = False ) -> None: """ Initialize the ElevenLabs STT client. Args: api_key: ElevenLabs API key for authentication. Defaults to env variable ELEVENLABS_API_KEY. model_id: STT model identifier. language_code: Language code for transcription. sample_rate: Sample rate of input audio in Hz. commit_strategy: Strategy for committing transcripts ('vad' is by default). vad_silence_threshold_secs: Duration of silence to detect end-of-speech. vad_threshold: Threshold for detecting voice activity. min_speech_duration_ms: Minimum duration in milliseconds for a speech segment. min_silence_duration_ms: Minimum duration in milliseconds of silence to consider end-of-speech. base_url: WebSocket endpoint for ElevenLabs STT. Raises: ValueError: If required parameters are missing or invalid. """ super().__init__() self.api_key = api_key or os.getenv("ELEVENLABS_API_KEY") if not self.api_key: raise ValueError("ElevenLabs API key must be provided via api_key or ELEVENLABS_API_KEY env var") self.model_id = model_id self.language_code = language_code self.commit_strategy = commit_strategy self.base_url = base_url self.sample_rate = sample_rate if self.sample_rate not in SUPPORTED_SAMPLE_RATES: raise ValueError(f"Unsupported sample_rate: {self.sample_rate}. Supported rates: {SUPPORTED_SAMPLE_RATES}") self.vad_silence_threshold_secs = vad_silence_threshold_secs self.vad_threshold = vad_threshold self.min_speech_duration_ms = min_speech_duration_ms self.min_silence_duration_ms = min_silence_duration_ms self.detect_language = detect_language self._last_final_text = "" self._last_final_time = 0.0 self._duplicate_suppression_window = 0.75 self._stream_buffer = bytearray() self._target_chunk_size = int(0.1 * self.sample_rate * 2) self.heartbeat = 15.0 self._session: Optional[aiohttp.ClientSession] = None self._ws: Optional[aiohttp.ClientWebSocketResponse] = None self._ws_task: Optional[asyncio.Task] = None async def process_audio( self, audio_frames: bytes, **kwargs: Any ) -> None: """ Process and send audio frames. Converts to mono (required by ElevenLabs) and buffers 100ms chunks to reduce overhead. """ if not self._ws or self._ws.closed: await self._connect_ws() if not self._ws_task or self._ws_task.done(): self._ws_task = asyncio.create_task(self._listen_for_responses()) elif self._ws_task and self._ws_task.done(): logger.warning("WebSocket listener stopped unexpectedly, restarting") self._ws_task = asyncio.create_task(self._listen_for_responses()) try: mono_audio = self._convert_to_mono(audio_frames) if not mono_audio: return self._stream_buffer.extend(mono_audio) while len(self._stream_buffer) >= self._target_chunk_size: chunk = self._stream_buffer[:self._target_chunk_size] await self._send_audio(chunk) self._stream_buffer = self._stream_buffer[self._target_chunk_size:] except Exception as e: logger.exception("Error in process_audio: %s", e) self.emit("error", str(e)) if self._ws: await self._ws.close() self._ws = None async def _connect_ws(self) -> None: if not self._session: self._session = aiohttp.ClientSession() language_code = None if self.detect_language else str(self.language_code) query_params = { "model_id": str(self.model_id), "audio_format": f"pcm_{self.sample_rate}", "commit_strategy": str(self.commit_strategy), "vad_silence_threshold_secs": self.vad_silence_threshold_secs, "vad_threshold": self.vad_threshold, "min_speech_duration_ms": self.min_speech_duration_ms, "min_silence_duration_ms": self.min_silence_duration_ms, "include_timestamps": True, "include_language_detection":self.detect_language } if language_code is not None: query_params["language_code"] = language_code ws_url = f"{self.base_url}?{urlencode(query_params)}" headers = {"xi-api-key": self.api_key} try: self._ws = await self._session.ws_connect(ws_url, headers=headers, heartbeat=self.heartbeat) logger.info("Connected to ElevenLabs Realtime STT WebSocket.") except Exception as e: logger.exception("Error connecting to ElevenLabs WebSocket: %s", e) raise async def _send_audio(self, audio_bytes: bytes) -> None: if not self._ws: return payload = { "message_type": "input_audio_chunk", "audio_base_64": base64.b64encode(audio_bytes).decode(), "sample_rate": self.sample_rate, } try: await self._ws.send_str(json.dumps(payload)) except Exception as e: logger.exception("Error sending audio chunk: %s", e) self.emit("error", str(e)) await self.aclose() def _convert_to_mono(self, audio_bytes: bytes) -> bytes: """ Convert input audio bytes to mono. """ if not audio_bytes: return b"" try: raw_audio = np.frombuffer(audio_bytes, dtype=np.int16) if raw_audio.size == 0: return b"" if raw_audio.size % 2 == 0: try: stereo = raw_audio.reshape(-1, 2).astype(np.float32) mono = stereo.mean(axis=1) return mono.astype(np.int16).tobytes() except ValueError: pass return audio_bytes except Exception as e: logger.error("Error converting to mono: %s", e) return b"" async def _listen_for_responses(self) -> None: """ Listen for incoming WebSocket messages from ElevenLabs STT. """ if not self._ws: return try: async for msg in self._ws: if msg.type == aiohttp.WSMsgType.TEXT: data = None try: data = msg.json() except Exception: try: data = json.loads(msg.data) except Exception: logger.debug("Received non-json ws text message") continue responses = await self._handle_ws_event(data) if responses: for r in responses: if self._transcript_callback: try: await self._transcript_callback(r) except Exception: logger.exception("Error in transcript callback") elif msg.type == aiohttp.WSMsgType.ERROR: logger.error("WebSocket error: %s", self._ws.exception()) self.emit("error", f"WebSocket error: {self._ws.exception()}") break elif msg.type == aiohttp.WSMsgType.CLOSED: logger.info("WebSocket closed by server.") break except asyncio.CancelledError: logger.debug("WebSocket listener cancelled") except Exception as e: logger.exception("Error in WebSocket listener: %s", e) self.emit("error", str(e)) finally: if self._ws: try: await self._ws.close() except Exception: pass self._ws = None self._ws_task = None async def _handle_ws_event(self, data: dict) -> List[STTResponse]: """ Process a single WebSocket event from ElevenLabs STT. Args: data: JSON-decoded WebSocket message. Returns: List of STTResponse objects for this event. """ responses: List[STTResponse] = [] message_type = data.get("message_type") logger.debug("Received WS event: %s", message_type) if message_type in STT_ERROR_MSGS: logger.error("ElevenLabs STT error: %s", data) self.emit("error", data) return responses if message_type == "session_started": global_event_emitter.emit("speech_session_started") return responses if message_type == "committed_transcript_with_timestamps": logger.debug("==== Received final transcript event: %s", data) text = data.get("text", "") clean_text = text.strip() if self.detect_language: language_code = data.get("language_code", None) self.language_code = language_code avg_conf, duration = self.get_avg_confidence_and_duration(data) now = time.time() if clean_text == "": global_event_emitter.emit("speech_stopped") self._last_final_text = "" self._last_final_time = now return responses resp = STTResponse( event_type=SpeechEventType.FINAL, data=SpeechData( text=clean_text, confidence=avg_conf, duration=duration, ), metadata={"model": self.model_id, "raw_event": data}, ) responses.append(resp) global_event_emitter.emit("speech_stopped") self._last_final_text = clean_text self._last_final_time = now return responses if message_type == "partial_transcript": text = data.get("text", "") clean_text = text.strip() if ( self._last_final_text and clean_text and clean_text == self._last_final_text and (time.time() - self._last_final_time) < self._duplicate_suppression_window ): logger.debug("Dropping duplicate partial matching recent final transcript") return responses resp = STTResponse( event_type=SpeechEventType.INTERIM, data=SpeechData( text=text, confidence=float(data.get("confidence", 0.0)), ), metadata={"model": self.model_id, "raw_event": data}, ) responses.append(resp) if clean_text: global_event_emitter.emit("speech_started") return responses logger.debug("Ignoring unrecognized message_type: %s", message_type) return responses async def aclose(self) -> None: """ Close the WebSocket connection and cleanup session resources. Cancels the listener task, closes WebSocket and HTTP session, and calls the parent class cleanup. """ if self._ws_task: self._ws_task.cancel() try: await self._ws_task except asyncio.CancelledError: pass self._ws_task = None if self._ws: try: await self._ws.close() except Exception: pass self._ws = None if self._session: try: await self._session.close() except Exception: pass finally: self._session = None await super().aclose() def get_avg_confidence_and_duration(self,payload: Dict) -> Tuple[float, float]: """ Computes: - Average confidence from log probabilities - Total transcript duration from last word end timestamp Args: payload (dict): Transcript JSON message Returns: (avg_confidence, duration) """ words = payload.get("words", []) total_confidence = 0.0 word_count = 0 last_end_time = 0.0 for w in words: if w.get("type") != "word": continue logprob = w.get("logprob") if logprob is not None: total_confidence += math.exp(logprob) word_count += 1 last_end_time = max(last_end_time, w.get("end", 0.0)) avg_confidence = total_confidence / word_count if word_count > 0 else 0.0 return avg_confidence, last_end_timeElevenLabs Realtime Speech-to-Text (STT) client.
Initialize the ElevenLabs STT client.
Args
api_key- ElevenLabs API key for authentication. Defaults to env variable ELEVENLABS_API_KEY.
model_id- STT model identifier.
language_code- Language code for transcription.
sample_rate- Sample rate of input audio in Hz.
commit_strategy- Strategy for committing transcripts ('vad' is by default).
vad_silence_threshold_secs- Duration of silence to detect end-of-speech.
vad_threshold- Threshold for detecting voice activity.
min_speech_duration_ms- Minimum duration in milliseconds for a speech segment.
min_silence_duration_ms- Minimum duration in milliseconds of silence to consider end-of-speech.
base_url- WebSocket endpoint for ElevenLabs STT.
Raises
ValueError- If required parameters are missing or invalid.
Ancestors
- videosdk.agents.stt.stt.STT
- videosdk.agents.event_emitter.EventEmitter
- typing.Generic
Methods
async def aclose(self) ‑> None-
Expand source code
async def aclose(self) -> None: """ Close the WebSocket connection and cleanup session resources. Cancels the listener task, closes WebSocket and HTTP session, and calls the parent class cleanup. """ if self._ws_task: self._ws_task.cancel() try: await self._ws_task except asyncio.CancelledError: pass self._ws_task = None if self._ws: try: await self._ws.close() except Exception: pass self._ws = None if self._session: try: await self._session.close() except Exception: pass finally: self._session = None await super().aclose()Close the WebSocket connection and cleanup session resources.
Cancels the listener task, closes WebSocket and HTTP session, and calls the parent class cleanup.
def get_avg_confidence_and_duration(self, payload: Dict) ‑> Tuple[float, float]-
Expand source code
def get_avg_confidence_and_duration(self,payload: Dict) -> Tuple[float, float]: """ Computes: - Average confidence from log probabilities - Total transcript duration from last word end timestamp Args: payload (dict): Transcript JSON message Returns: (avg_confidence, duration) """ words = payload.get("words", []) total_confidence = 0.0 word_count = 0 last_end_time = 0.0 for w in words: if w.get("type") != "word": continue logprob = w.get("logprob") if logprob is not None: total_confidence += math.exp(logprob) word_count += 1 last_end_time = max(last_end_time, w.get("end", 0.0)) avg_confidence = total_confidence / word_count if word_count > 0 else 0.0 return avg_confidence, last_end_timeComputes: - Average confidence from log probabilities - Total transcript duration from last word end timestamp
Args
payload:dict- Transcript JSON message
Returns
(avg_confidence, duration)
async def process_audio(self, audio_frames: bytes, **kwargs: Any) ‑> None-
Expand source code
async def process_audio( self, audio_frames: bytes, **kwargs: Any ) -> None: """ Process and send audio frames. Converts to mono (required by ElevenLabs) and buffers 100ms chunks to reduce overhead. """ if not self._ws or self._ws.closed: await self._connect_ws() if not self._ws_task or self._ws_task.done(): self._ws_task = asyncio.create_task(self._listen_for_responses()) elif self._ws_task and self._ws_task.done(): logger.warning("WebSocket listener stopped unexpectedly, restarting") self._ws_task = asyncio.create_task(self._listen_for_responses()) try: mono_audio = self._convert_to_mono(audio_frames) if not mono_audio: return self._stream_buffer.extend(mono_audio) while len(self._stream_buffer) >= self._target_chunk_size: chunk = self._stream_buffer[:self._target_chunk_size] await self._send_audio(chunk) self._stream_buffer = self._stream_buffer[self._target_chunk_size:] except Exception as e: logger.exception("Error in process_audio: %s", e) self.emit("error", str(e)) if self._ws: await self._ws.close() self._ws = NoneProcess and send audio frames. Converts to mono (required by ElevenLabs) and buffers 100ms chunks to reduce overhead.
class ElevenLabsTTS (*,
api_key: str | None = None,
model: str = 'eleven_flash_v2_5',
voice: str = 'ErXwobaYiN019PkySvjV',
speed: float = 1.0,
response_format: str = 'pcm_24000',
voice_settings: VoiceSettings | None = None,
base_url: str = 'https://api.elevenlabs.io/v1',
enable_streaming: bool = True,
inactivity_timeout: int = 300,
language: str = 'en',
enable_ssml_parsing: bool = False,
apply_text_normalization: "Literal['auto', 'on', 'off']" = 'auto',
auto_mode: bool = False)-
Expand source code
class ElevenLabsTTS(TTS): def __init__( self, *, api_key: str | None = None, model: str = DEFAULT_MODEL, voice: str = DEFAULT_VOICE_ID, speed: float = 1.0, response_format: str = "pcm_24000", voice_settings: VoiceSettings | None = None, base_url: str = API_BASE_URL, enable_streaming: bool = True, inactivity_timeout: int = WS_INACTIVITY_TIMEOUT, language: str = "en", enable_ssml_parsing:bool=False, apply_text_normalization:Literal["auto","on","off"]="auto", auto_mode:bool=False ) -> None: """Initialize the ElevenLabs TTS plugin. Args: api_key (Optional[str], optional): ElevenLabs API key. Uses ELEVENLABS_API_KEY environment variable if not provided. Defaults to None. model (str): The model to use for the TTS plugin. Defaults to "eleven_flash_v2_5". voice (str): The voice to use for the TTS plugin. Defaults to "EXAVITQu4vr4xnSDxMaL". speed (float): The speed to use for the TTS plugin. Defaults to 1.0. response_format (str): The response format to use for the TTS plugin. Defaults to "pcm_24000". voice_settings (Optional[VoiceSettings], optional): The voice settings to use for the TTS plugin. Defaults to None. base_url (str): The base URL to use for the TTS plugin. Defaults to "https://api.elevenlabs.io/v1". enable_streaming (bool): Whether to enable streaming for the TTS plugin. Defaults to True. inactivity_timeout (int): The inactivity timeout to use for the TTS plugin. Defaults to 300. language (str): The language to use for the TTS plugin. Defaults to "en". enable_ssml_parsing(bool): Whether to enable SSML parsing. apply_text_normalization:This parameter controls text normalization with three modes - "auto", "on", and "off". When set to auto, the system will automatically decide whether to apply text normalization (e.g., spelling out numbers) with "on", text normalization will always be applied, while with "off", it will be skipped. For "eleven_turbo_v2_5" and "eleven_flash_v2_5" models, text normalization can only be enabled with Enterprise plans. Defaults to "auto". auto_mode (bool): Reduces latency by disabling chunk schedule and buffers. Recommended for full sentences/phrases. """ super().__init__( sample_rate=ELEVENLABS_SAMPLE_RATE, num_channels=ELEVENLABS_CHANNELS ) self.model = model self.voice = voice self.speed = speed self.language = language self.enable_ssml_parsing = enable_ssml_parsing self.apply_text_normalization = apply_text_normalization self.auto_mode = auto_mode self.audio_track = None self.loop = None self.response_format = response_format self.base_url = base_url self.enable_streaming = enable_streaming self.voice_settings = voice_settings or VoiceSettings() self.inactivity_timeout = inactivity_timeout self._first_chunk_sent = False self._ws_session = None self._ws_connection = None self.api_key = api_key or os.getenv("ELEVENLABS_API_KEY") if not self.api_key: raise ValueError( "ElevenLabs API key must be provided either through api_key parameter or ELEVENLABS_API_KEY environment variable") self._session = httpx.AsyncClient( timeout=httpx.Timeout(connect=15.0, read=30.0, write=5.0, pool=5.0), follow_redirects=True, ) self._streams = weakref.WeakSet() self._send_task: asyncio.Task | None = None self._recv_task: asyncio.Task | None = None self._should_stop = False self._connection_lock = asyncio.Lock() self._ws_voice_id: str | None = None self._active_contexts: set[str] = set() self._context_futures: dict[str, asyncio.Future[None]] = {} def reset_first_audio_tracking(self) -> None: """Reset the first audio tracking state for next TTS task""" self._first_chunk_sent = False async def synthesize( self, text: AsyncIterator[str] | str, voice_id: Optional[str] = None, **kwargs: Any, ) -> None: try: if not self.audio_track or not self.loop: self.emit("error", "Audio track or event loop not set") return target_voice = voice_id or self.voice self._should_stop = False if self.enable_streaming: await self._stream_synthesis(text, target_voice) else: if isinstance(text, AsyncIterator): async for segment in segment_text(text): if self._should_stop: break await self._chunked_synthesis(segment, target_voice) else: await self._chunked_synthesis(text, target_voice) except Exception as e: self.emit("error", f"TTS synthesis failed: {str(e)}") raise async def _chunked_synthesis(self, text: str, voice_id: str) -> None: """Non-streaming synthesis using the standard API""" url = f"{self.base_url}/text-to-speech/{voice_id}/stream" params = { "model_id": self.model, "output_format": self.response_format, "language_code": self.language, "enable_ssml_parsing":self.enable_ssml_parsing, "apply_text_normalization":self.apply_text_normalization, "auto_mode":self.auto_mode } headers = { "xi-api-key": self.api_key, "Content-Type": "application/json", } payload = { "text": text, "voice_settings": { "stability": self.voice_settings.stability, "similarity_boost": self.voice_settings.similarity_boost, "style": self.voice_settings.style, "use_speaker_boost": self.voice_settings.use_speaker_boost, }, } try: async with self._session.stream( "POST", url, headers=headers, json=payload, params=params ) as response: response.raise_for_status() async for chunk in response.aiter_bytes(): if self._should_stop: break if chunk: await self._stream_audio_chunks(chunk) except httpx.HTTPStatusError as e: self.emit( "error", f"HTTP error {e.response.status_code}: {e.response.text}") raise except Exception as e: self.emit("error", f"Chunked synthesis failed: {str(e)}") raise async def _stream_synthesis(self, text: Union[AsyncIterator[str], str], voice_id: str) -> None: """WebSocket-based streaming synthesis using multi-context connection""" try: await self._ensure_connection(voice_id) context_id = uuid.uuid4().hex[:12] done_future: asyncio.Future[None] = asyncio.get_event_loop().create_future() self.register_context(context_id, done_future) async def _single_chunk_gen(s: str) -> AsyncIterator[str]: yield s async def _send_chunks() -> None: try: first_message_sent = False if isinstance(text, str): async for segment in segment_text(_single_chunk_gen(text)): if self._should_stop: break await self.send_text(context_id, f"{segment} ", voice_settings=None if first_message_sent else self._voice_settings_dict(), flush=True) first_message_sent = True else: async for chunk in text: if self._should_stop: break await self.send_text(context_id, f"{chunk} ", voice_settings=None if first_message_sent else self._voice_settings_dict()) first_message_sent = True if not self._should_stop: await self.flush_context(context_id) await self.close_context(context_id) except Exception as e: if not done_future.done(): done_future.set_exception(e) sender = asyncio.create_task(_send_chunks()) await done_future await sender except Exception as e: self.emit("error", f"Streaming synthesis failed: {str(e)}") raise def _voice_settings_dict(self) -> dict[str, Any]: return { "stability": self.voice_settings.stability, "similarity_boost": self.voice_settings.similarity_boost, "style": self.voice_settings.style, "use_speaker_boost": self.voice_settings.use_speaker_boost, } async def _stream_audio_chunks(self, audio_bytes: bytes) -> None: if not audio_bytes or self._should_stop: return if not self._first_chunk_sent and hasattr(self, '_first_audio_callback') and self._first_audio_callback: self._first_chunk_sent = True asyncio.create_task(self._first_audio_callback()) if self.audio_track and self.loop: await self.audio_track.add_new_bytes(audio_bytes) async def interrupt(self) -> None: """Simple but effective interruption""" self._should_stop = True if self.audio_track: self.audio_track.interrupt() await self.close_all_contexts() async def aclose(self) -> None: """Cleanup resources""" self._should_stop = True for task in [self._send_task, self._recv_task]: if task and not task.done(): task.cancel() for stream in list(self._streams): try: await stream.aclose() except Exception: pass self._streams.clear() if self._ws_connection and not self._ws_connection.closed: try: await self._ws_connection.send_str(json.dumps({"close_socket": True})) except Exception: pass await self._ws_connection.close() if self._ws_session and not self._ws_session.closed: await self._ws_session.close() self._ws_connection = None self._ws_session = None if self._session: await self._session.aclose() await super().aclose() async def _ensure_connection(self, voice_id: str) -> None: async with self._connection_lock: if self._ws_connection and not self._ws_connection.closed and self._ws_voice_id == voice_id: return if self._ws_connection and not self._ws_connection.closed: try: await self._ws_connection.send_str(json.dumps({"close_socket": True})) except Exception: pass await self._ws_connection.close() if self._ws_session and not self._ws_session.closed: await self._ws_session.close() self._ws_session = aiohttp.ClientSession() self._ws_voice_id = voice_id ws_url = f"{self.base_url}/text-to-speech/{voice_id}/multi-stream-input".replace("https://", "wss://").replace("http://", "ws://") params = { "model_id": self.model, "output_format": self.response_format, "inactivity_timeout": self.inactivity_timeout, } param_string = "&".join([f"{k}={v}" for k, v in params.items()]) full_ws_url = f"{ws_url}?{param_string}" headers = {"xi-api-key": self.api_key} self._ws_connection = await asyncio.wait_for(self._ws_session.ws_connect(full_ws_url, headers=headers), timeout=10.0) if self._recv_task and not self._recv_task.done(): self._recv_task.cancel() self._recv_task = asyncio.create_task(self._recv_loop()) def register_context(self, context_id: str, done_future: asyncio.Future[None]) -> None: self._context_futures[context_id] = done_future async def send_text( self, context_id: str, text: str, *, voice_settings: Optional[dict[str, Any]] = None, flush: bool = False, ) -> None: if not self._ws_connection or self._ws_connection.closed: raise RuntimeError("WebSocket connection is closed") if context_id not in self._active_contexts: init_msg = { "context_id": context_id, "text": " ", } if voice_settings: init_msg["voice_settings"] = voice_settings await self._ws_connection.send_str(json.dumps(init_msg)) self._active_contexts.add(context_id) pkt: dict[str, Any] = {"context_id": context_id, "text": text} if flush: pkt["flush"] = True await self._ws_connection.send_str(json.dumps(pkt)) async def flush_context(self, context_id: str) -> None: if not self._ws_connection or self._ws_connection.closed: return await self._ws_connection.send_str(json.dumps({"context_id": context_id, "flush": True})) async def close_context(self, context_id: str) -> None: if not self._ws_connection or self._ws_connection.closed: return await self._ws_connection.send_str(json.dumps({"context_id": context_id, "close_context": True})) async def close_all_contexts(self) -> None: try: for context_id in list(self._active_contexts): await self.close_context(context_id) except Exception: pass async def _recv_loop(self) -> None: try: while self._ws_connection and not self._ws_connection.closed: msg = await self._ws_connection.receive() if msg.type == aiohttp.WSMsgType.TEXT: data = json.loads(msg.data) if data.get("error"): ctx_id = data.get("contextId") fut = self._context_futures.get(ctx_id) if fut and not fut.done(): fut.set_exception(RuntimeError(data["error"])) continue if data.get("audio"): audio_chunk = base64.b64decode(data["audio"]) if isinstance(data["audio"], str) else None if audio_chunk: if not self._first_chunk_sent and hasattr(self, '_first_audio_callback') and self._first_audio_callback: self._first_chunk_sent = True asyncio.create_task(self._first_audio_callback()) if self.audio_track: await self.audio_track.add_new_bytes(audio_chunk) if data.get("is_final") or data.get("isFinal"): ctx_id = data.get("contextId") if ctx_id: fut = self._context_futures.pop(ctx_id, None) self._active_contexts.discard(ctx_id) if fut and not fut.done(): fut.set_result(None) elif msg.type in (aiohttp.WSMsgType.CLOSED, aiohttp.WSMsgType.CLOSE, aiohttp.WSMsgType.CLOSING): break except Exception: for fut in self._context_futures.values(): if not fut.done(): fut.set_exception(RuntimeError("WebSocket receive loop error")) self._context_futures.clear()Base class for Text-to-Speech implementations
Initialize the ElevenLabs TTS plugin.
Args
api_key:Optional[str], optional- ElevenLabs API key. Uses ELEVENLABS_API_KEY environment variable if not provided. Defaults to None.
model:str- The model to use for the TTS plugin. Defaults to "eleven_flash_v2_5".
voice:str- The voice to use for the TTS plugin. Defaults to "EXAVITQu4vr4xnSDxMaL".
speed:float- The speed to use for the TTS plugin. Defaults to 1.0.
response_format:str- The response format to use for the TTS plugin. Defaults to "pcm_24000".
voice_settings:Optional[VoiceSettings], optional- The voice settings to use for the TTS plugin. Defaults to None.
base_url:str- The base URL to use for the TTS plugin. Defaults to "https://api.elevenlabs.io/v1".
enable_streaming:bool- Whether to enable streaming for the TTS plugin. Defaults to True.
inactivity_timeout:int- The inactivity timeout to use for the TTS plugin. Defaults to 300.
language:str- The language to use for the TTS plugin. Defaults to "en".
- enable_ssml_parsing(bool): Whether to enable SSML parsing.
- apply_text_normalization:This parameter controls text normalization with three modes - "auto", "on", and "off".
- When set to auto, the system will automatically decide whether to apply text normalization (e.g., spelling out numbers)
- with "on", text normalization will always be applied, while with "off", it will be skipped.
- For "eleven_turbo_v2_5" and "eleven_flash_v2_5" models, text normalization can only be enabled with Enterprise plans. Defaults to "auto".
auto_mode:bool- Reduces latency by disabling chunk schedule and buffers. Recommended for full sentences/phrases.
Ancestors
- videosdk.agents.tts.tts.TTS
- videosdk.agents.event_emitter.EventEmitter
- typing.Generic
Methods
async def aclose(self) ‑> None-
Expand source code
async def aclose(self) -> None: """Cleanup resources""" self._should_stop = True for task in [self._send_task, self._recv_task]: if task and not task.done(): task.cancel() for stream in list(self._streams): try: await stream.aclose() except Exception: pass self._streams.clear() if self._ws_connection and not self._ws_connection.closed: try: await self._ws_connection.send_str(json.dumps({"close_socket": True})) except Exception: pass await self._ws_connection.close() if self._ws_session and not self._ws_session.closed: await self._ws_session.close() self._ws_connection = None self._ws_session = None if self._session: await self._session.aclose() await super().aclose()Cleanup resources
async def close_all_contexts(self) ‑> None-
Expand source code
async def close_all_contexts(self) -> None: try: for context_id in list(self._active_contexts): await self.close_context(context_id) except Exception: pass async def close_context(self, context_id: str) ‑> None-
Expand source code
async def close_context(self, context_id: str) -> None: if not self._ws_connection or self._ws_connection.closed: return await self._ws_connection.send_str(json.dumps({"context_id": context_id, "close_context": True})) async def flush_context(self, context_id: str) ‑> None-
Expand source code
async def flush_context(self, context_id: str) -> None: if not self._ws_connection or self._ws_connection.closed: return await self._ws_connection.send_str(json.dumps({"context_id": context_id, "flush": True})) async def interrupt(self) ‑> None-
Expand source code
async def interrupt(self) -> None: """Simple but effective interruption""" self._should_stop = True if self.audio_track: self.audio_track.interrupt() await self.close_all_contexts()Simple but effective interruption
def register_context(self, context_id: str, done_future: asyncio.Future[None]) ‑> None-
Expand source code
def register_context(self, context_id: str, done_future: asyncio.Future[None]) -> None: self._context_futures[context_id] = done_future def reset_first_audio_tracking(self) ‑> None-
Expand source code
def reset_first_audio_tracking(self) -> None: """Reset the first audio tracking state for next TTS task""" self._first_chunk_sent = FalseReset the first audio tracking state for next TTS task
async def send_text(self,
context_id: str,
text: str,
*,
voice_settings: Optional[dict[str, Any]] = None,
flush: bool = False) ‑> None-
Expand source code
async def send_text( self, context_id: str, text: str, *, voice_settings: Optional[dict[str, Any]] = None, flush: bool = False, ) -> None: if not self._ws_connection or self._ws_connection.closed: raise RuntimeError("WebSocket connection is closed") if context_id not in self._active_contexts: init_msg = { "context_id": context_id, "text": " ", } if voice_settings: init_msg["voice_settings"] = voice_settings await self._ws_connection.send_str(json.dumps(init_msg)) self._active_contexts.add(context_id) pkt: dict[str, Any] = {"context_id": context_id, "text": text} if flush: pkt["flush"] = True await self._ws_connection.send_str(json.dumps(pkt)) async def synthesize(self,
text: AsyncIterator[str] | str,
voice_id: Optional[str] = None,
**kwargs: Any) ‑> None-
Expand source code
async def synthesize( self, text: AsyncIterator[str] | str, voice_id: Optional[str] = None, **kwargs: Any, ) -> None: try: if not self.audio_track or not self.loop: self.emit("error", "Audio track or event loop not set") return target_voice = voice_id or self.voice self._should_stop = False if self.enable_streaming: await self._stream_synthesis(text, target_voice) else: if isinstance(text, AsyncIterator): async for segment in segment_text(text): if self._should_stop: break await self._chunked_synthesis(segment, target_voice) else: await self._chunked_synthesis(text, target_voice) except Exception as e: self.emit("error", f"TTS synthesis failed: {str(e)}") raiseConvert text to speech
Args
text- Text to convert to speech (either string or async iterator of strings)
voice_id- Optional voice identifier
**kwargs- Additional provider-specific arguments
Returns
None
class VoiceSettings (stability: float = 0.71,
similarity_boost: float = 0.5,
style: float = 0.0,
use_speaker_boost: bool = True)-
Expand source code
@dataclass class VoiceSettings: stability: float = 0.71 similarity_boost: float = 0.5 style: float = 0.0 use_speaker_boost: bool = TrueVoiceSettings(stability: 'float' = 0.71, similarity_boost: 'float' = 0.5, style: 'float' = 0.0, use_speaker_boost: 'bool' = True)
Instance variables
var similarity_boost : floatvar stability : floatvar style : floatvar use_speaker_boost : bool