"""Classes for voice assistant pipelines.""" from __future__ import annotations import asyncio from collections.abc import AsyncIterable, Callable, Iterable from dataclasses import asdict, dataclass, field import logging from typing import Any, cast import voluptuous as vol from homeassistant.backports.enum import StrEnum from homeassistant.components import conversation, media_source, stt, tts, websocket_api from homeassistant.components.tts.media_source import ( generate_media_source_id as tts_generate_media_source_id, ) from homeassistant.core import Context, HomeAssistant, callback from homeassistant.exceptions import HomeAssistantError from homeassistant.helpers.collection import ( CollectionError, ItemNotFound, SerializedStorageCollection, StorageCollection, StorageCollectionWebsocket, ) from homeassistant.helpers.singleton import singleton from homeassistant.helpers.storage import Store from homeassistant.util import ( dt as dt_util, language as language_util, ulid as ulid_util, ) from homeassistant.util.limited_size_dict import LimitedSizeDict from .const import DOMAIN from .error import ( IntentRecognitionError, PipelineError, PipelineNotFound, SpeechToTextError, TextToSpeechError, ) _LOGGER = logging.getLogger(__name__) STORAGE_KEY = f"{DOMAIN}.pipelines" STORAGE_VERSION = 1 ENGINE_LANGUAGE_PAIRS = ( ("stt_engine", "stt_language"), ("tts_engine", "tts_language"), ) def validate_language(data: dict[str, Any]) -> Any: """Validate language settings.""" for engine, language in ENGINE_LANGUAGE_PAIRS: if data[engine] is not None and data[language] is None: raise vol.Invalid(f"Need language {language} for {engine} {data[engine]}") return data PIPELINE_FIELDS = { vol.Required("conversation_engine"): str, vol.Required("conversation_language"): str, vol.Required("language"): str, vol.Required("name"): str, vol.Required("stt_engine"): vol.Any(str, None), vol.Required("stt_language"): vol.Any(str, None), vol.Required("tts_engine"): vol.Any(str, None), vol.Required("tts_language"): vol.Any(str, None), vol.Required("tts_voice"): vol.Any(str, None), } STORED_PIPELINE_RUNS = 10 SAVE_DELAY = 10 async def _async_resolve_default_pipeline_settings( hass: HomeAssistant, stt_engine_id: str | None, tts_engine_id: str | None, ) -> dict[str, str | None]: """Resolve settings for a default pipeline. The default pipeline will use the homeassistant conversation agent and the default stt / tts engines if none are specified. """ conversation_language = "en" pipeline_language = "en" pipeline_name = "Home Assistant" stt_engine = None stt_language = None tts_engine = None tts_language = None tts_voice = None # Find a matching language supported by the Home Assistant conversation agent conversation_languages = language_util.matches( hass.config.language, await conversation.async_get_conversation_languages( hass, conversation.HOME_ASSISTANT_AGENT ), country=hass.config.country, ) if conversation_languages: pipeline_language = hass.config.language conversation_language = conversation_languages[0] if stt_engine_id is None: stt_engine_id = stt.async_default_engine(hass) if stt_engine_id is not None: stt_engine = stt.async_get_speech_to_text_engine(hass, stt_engine_id) if stt_engine is None: stt_engine_id = None if stt_engine: stt_languages = language_util.matches( pipeline_language, stt_engine.supported_languages, country=hass.config.country, ) if stt_languages: stt_language = stt_languages[0] else: _LOGGER.debug( "Speech-to-text engine '%s' does not support language '%s'", stt_engine_id, pipeline_language, ) stt_engine_id = None if tts_engine_id is None: tts_engine_id = tts.async_default_engine(hass) if tts_engine_id is not None: tts_engine = tts.get_engine_instance(hass, tts_engine_id) if tts_engine is None: tts_engine_id = None if tts_engine: tts_languages = language_util.matches( pipeline_language, tts_engine.supported_languages, country=hass.config.country, ) if tts_languages: tts_language = tts_languages[0] tts_voices = tts_engine.async_get_supported_voices(tts_language) if tts_voices: tts_voice = tts_voices[0].voice_id else: _LOGGER.debug( "Text-to-speech engine '%s' does not support language '%s'", tts_engine_id, pipeline_language, ) tts_engine_id = None if stt_engine_id == "cloud" and tts_engine_id == "cloud": pipeline_name = "Home Assistant Cloud" return { "conversation_engine": conversation.HOME_ASSISTANT_AGENT, "conversation_language": conversation_language, "language": hass.config.language, "name": pipeline_name, "stt_engine": stt_engine_id, "stt_language": stt_language, "tts_engine": tts_engine_id, "tts_language": tts_language, "tts_voice": tts_voice, } async def _async_create_default_pipeline( hass: HomeAssistant, pipeline_store: PipelineStorageCollection ) -> Pipeline: """Create a default pipeline. The default pipeline will use the homeassistant conversation agent and the default stt / tts engines. """ pipeline_settings = await _async_resolve_default_pipeline_settings(hass, None, None) return await pipeline_store.async_create_item(pipeline_settings) async def async_create_default_pipeline( hass: HomeAssistant, stt_engine_id: str, tts_engine_id: str ) -> Pipeline | None: """Create a pipeline with default settings. The default pipeline will use the homeassistant conversation agent and the specified stt / tts engines. """ pipeline_data: PipelineData = hass.data[DOMAIN] pipeline_store = pipeline_data.pipeline_store pipeline_settings = await _async_resolve_default_pipeline_settings( hass, stt_engine_id, tts_engine_id ) if ( pipeline_settings["stt_engine"] != stt_engine_id or pipeline_settings["tts_engine"] != tts_engine_id ): return None return await pipeline_store.async_create_item(pipeline_settings) @callback def async_get_pipeline(hass: HomeAssistant, pipeline_id: str | None = None) -> Pipeline: """Get a pipeline by id or the preferred pipeline.""" pipeline_data: PipelineData = hass.data[DOMAIN] if pipeline_id is None: # A pipeline was not specified, use the preferred one pipeline_id = pipeline_data.pipeline_store.async_get_preferred_item() pipeline = pipeline_data.pipeline_store.data.get(pipeline_id) # If invalid pipeline ID was specified if pipeline is None: raise PipelineNotFound( "pipeline_not_found", f"Pipeline {pipeline_id} not found" ) return pipeline @callback def async_get_pipelines(hass: HomeAssistant) -> Iterable[Pipeline]: """Get all pipelines.""" pipeline_data: PipelineData = hass.data[DOMAIN] return pipeline_data.pipeline_store.data.values() class PipelineEventType(StrEnum): """Event types emitted during a pipeline run.""" RUN_START = "run-start" RUN_END = "run-end" STT_START = "stt-start" STT_END = "stt-end" INTENT_START = "intent-start" INTENT_END = "intent-end" TTS_START = "tts-start" TTS_END = "tts-end" ERROR = "error" @dataclass(frozen=True) class PipelineEvent: """Events emitted during a pipeline run.""" type: PipelineEventType data: dict[str, Any] | None = None timestamp: str = field(default_factory=lambda: dt_util.utcnow().isoformat()) PipelineEventCallback = Callable[[PipelineEvent], None] @dataclass(frozen=True) class Pipeline: """A voice assistant pipeline.""" conversation_engine: str conversation_language: str language: str name: str stt_engine: str | None stt_language: str | None tts_engine: str | None tts_language: str | None tts_voice: str | None id: str = field(default_factory=ulid_util.ulid) def to_json(self) -> dict[str, Any]: """Return a JSON serializable representation for storage.""" return { "conversation_engine": self.conversation_engine, "conversation_language": self.conversation_language, "id": self.id, "language": self.language, "name": self.name, "stt_engine": self.stt_engine, "stt_language": self.stt_language, "tts_engine": self.tts_engine, "tts_language": self.tts_language, "tts_voice": self.tts_voice, } class PipelineStage(StrEnum): """Stages of a pipeline.""" STT = "stt" INTENT = "intent" TTS = "tts" PIPELINE_STAGE_ORDER = [ PipelineStage.STT, PipelineStage.INTENT, PipelineStage.TTS, ] class PipelineRunValidationError(Exception): """Error when a pipeline run is not valid.""" class InvalidPipelineStagesError(PipelineRunValidationError): """Error when given an invalid combination of start/end stages.""" def __init__( self, start_stage: PipelineStage, end_stage: PipelineStage, ) -> None: """Set error message.""" super().__init__( f"Invalid stage combination: start={start_stage}, end={end_stage}" ) @dataclass class PipelineRun: """Running context for a pipeline.""" hass: HomeAssistant context: Context pipeline: Pipeline start_stage: PipelineStage end_stage: PipelineStage event_callback: PipelineEventCallback language: str = None # type: ignore[assignment] runner_data: Any | None = None intent_agent: str | None = None tts_audio_output: str | None = None id: str = field(default_factory=ulid_util.ulid) stt_provider: stt.SpeechToTextEntity | stt.Provider = field(init=False) tts_engine: str = field(init=False) tts_options: dict | None = field(init=False, default=None) def __post_init__(self) -> None: """Set language for pipeline.""" self.language = self.pipeline.language or self.hass.config.language # stt -> intent -> tts if PIPELINE_STAGE_ORDER.index(self.end_stage) < PIPELINE_STAGE_ORDER.index( self.start_stage ): raise InvalidPipelineStagesError(self.start_stage, self.end_stage) pipeline_data: PipelineData = self.hass.data[DOMAIN] if self.pipeline.id not in pipeline_data.pipeline_runs: pipeline_data.pipeline_runs[self.pipeline.id] = LimitedSizeDict( size_limit=STORED_PIPELINE_RUNS ) pipeline_data.pipeline_runs[self.pipeline.id][self.id] = PipelineRunDebug() @callback def process_event(self, event: PipelineEvent) -> None: """Log an event and call listener.""" self.event_callback(event) pipeline_data: PipelineData = self.hass.data[DOMAIN] if self.id not in pipeline_data.pipeline_runs[self.pipeline.id]: # This run has been evicted from the logged pipeline runs already return pipeline_data.pipeline_runs[self.pipeline.id][self.id].events.append(event) def start(self) -> None: """Emit run start event.""" data = { "pipeline": self.pipeline.id, "language": self.language, } if self.runner_data is not None: data["runner_data"] = self.runner_data self.process_event(PipelineEvent(PipelineEventType.RUN_START, data)) def end(self) -> None: """Emit run end event.""" self.process_event( PipelineEvent( PipelineEventType.RUN_END, ) ) async def prepare_speech_to_text(self, metadata: stt.SpeechMetadata) -> None: """Prepare speech-to-text.""" # pipeline.stt_engine can't be None or this function is not called stt_provider = stt.async_get_speech_to_text_engine( self.hass, self.pipeline.stt_engine, # type: ignore[arg-type] ) if stt_provider is None: engine = self.pipeline.stt_engine raise SpeechToTextError( code="stt-provider-missing", message=f"No speech-to-text provider for: {engine}", ) metadata.language = self.pipeline.stt_language or self.language if not stt_provider.check_metadata(metadata): raise SpeechToTextError( code="stt-provider-unsupported-metadata", message=( f"Provider {stt_provider.name} does not support input speech " f"to text metadata {metadata}" ), ) self.stt_provider = stt_provider async def speech_to_text( self, metadata: stt.SpeechMetadata, stream: AsyncIterable[bytes], ) -> str: """Run speech-to-text portion of pipeline. Returns the spoken text.""" if isinstance(self.stt_provider, stt.Provider): engine = self.stt_provider.name else: engine = self.stt_provider.entity_id self.process_event( PipelineEvent( PipelineEventType.STT_START, { "engine": engine, "metadata": asdict(metadata), }, ) ) try: # Transcribe audio stream result = await self.stt_provider.async_process_audio_stream( metadata, stream ) except Exception as src_error: _LOGGER.exception("Unexpected error during speech-to-text") raise SpeechToTextError( code="stt-stream-failed", message="Unexpected error during speech-to-text", ) from src_error _LOGGER.debug("speech-to-text result %s", result) if result.result != stt.SpeechResultState.SUCCESS: raise SpeechToTextError( code="stt-stream-failed", message="speech-to-text failed", ) if not result.text: raise SpeechToTextError( code="stt-no-text-recognized", message="No text recognized" ) self.process_event( PipelineEvent( PipelineEventType.STT_END, { "stt_output": { "text": result.text, } }, ) ) return result.text async def prepare_recognize_intent(self) -> None: """Prepare recognizing an intent.""" agent_info = conversation.async_get_agent_info( self.hass, # If no conversation engine is set, use the Home Assistant agent # (the conversation integration default is currently the last one set) self.pipeline.conversation_engine or conversation.HOME_ASSISTANT_AGENT, ) if agent_info is None: engine = self.pipeline.conversation_engine or "default" raise IntentRecognitionError( code="intent-not-supported", message=f"Intent recognition engine {engine} is not found", ) self.intent_agent = agent_info.id async def recognize_intent( self, intent_input: str, conversation_id: str | None, device_id: str | None ) -> str: """Run intent recognition portion of pipeline. Returns text to speak.""" if self.intent_agent is None: raise RuntimeError("Recognize intent was not prepared") self.process_event( PipelineEvent( PipelineEventType.INTENT_START, { "engine": self.intent_agent, "language": self.pipeline.conversation_language, "intent_input": intent_input, "conversation_id": conversation_id, "device_id": device_id, }, ) ) try: conversation_result = await conversation.async_converse( hass=self.hass, text=intent_input, conversation_id=conversation_id, device_id=device_id, context=self.context, language=self.pipeline.conversation_language, agent_id=self.intent_agent, ) except Exception as src_error: _LOGGER.exception("Unexpected error during intent recognition") raise IntentRecognitionError( code="intent-failed", message="Unexpected error during intent recognition", ) from src_error _LOGGER.debug("conversation result %s", conversation_result) self.process_event( PipelineEvent( PipelineEventType.INTENT_END, {"intent_output": conversation_result.as_dict()}, ) ) speech: str = conversation_result.response.speech.get("plain", {}).get( "speech", "" ) return speech async def prepare_text_to_speech(self) -> None: """Prepare text-to-speech.""" # pipeline.tts_engine can't be None or this function is not called engine = cast(str, self.pipeline.tts_engine) tts_options = {} if self.pipeline.tts_voice is not None: tts_options[tts.ATTR_VOICE] = self.pipeline.tts_voice if self.tts_audio_output is not None: tts_options[tts.ATTR_AUDIO_OUTPUT] = self.tts_audio_output try: options_supported = await tts.async_support_options( self.hass, engine, self.pipeline.tts_language, tts_options, ) except HomeAssistantError as err: raise TextToSpeechError( code="tts-not-supported", message=f"Text-to-speech engine '{engine}' not found", ) from err if not options_supported: raise TextToSpeechError( code="tts-not-supported", message=( f"Text-to-speech engine {engine} " f"does not support language {self.pipeline.tts_language} or options {tts_options}" ), ) self.tts_engine = engine self.tts_options = tts_options async def text_to_speech(self, tts_input: str) -> str: """Run text-to-speech portion of pipeline. Returns URL of TTS audio.""" self.process_event( PipelineEvent( PipelineEventType.TTS_START, { "engine": self.tts_engine, "language": self.pipeline.tts_language, "voice": self.pipeline.tts_voice, "tts_input": tts_input, }, ) ) try: # Synthesize audio and get URL tts_media_id = tts_generate_media_source_id( self.hass, tts_input, engine=self.tts_engine, language=self.pipeline.tts_language, options=self.tts_options, ) tts_media = await media_source.async_resolve_media( self.hass, tts_media_id, None, ) except Exception as src_error: _LOGGER.exception("Unexpected error during text-to-speech") raise TextToSpeechError( code="tts-failed", message="Unexpected error during text-to-speech", ) from src_error _LOGGER.debug("TTS result %s", tts_media) self.process_event( PipelineEvent( PipelineEventType.TTS_END, { "tts_output": { "media_id": tts_media_id, **asdict(tts_media), } }, ) ) return tts_media.url @dataclass class PipelineInput: """Input to a pipeline run.""" run: PipelineRun stt_metadata: stt.SpeechMetadata | None = None """Metadata of stt input audio. Required when start_stage = stt.""" stt_stream: AsyncIterable[bytes] | None = None """Input audio for stt. Required when start_stage = stt.""" intent_input: str | None = None """Input for conversation agent. Required when start_stage = intent.""" tts_input: str | None = None """Input for text-to-speech. Required when start_stage = tts.""" conversation_id: str | None = None device_id: str | None = None async def execute(self) -> None: """Run pipeline.""" self.run.start() current_stage = self.run.start_stage try: # speech-to-text intent_input = self.intent_input if current_stage == PipelineStage.STT: assert self.stt_metadata is not None assert self.stt_stream is not None intent_input = await self.run.speech_to_text( self.stt_metadata, self.stt_stream, ) current_stage = PipelineStage.INTENT if self.run.end_stage != PipelineStage.STT: tts_input = self.tts_input if current_stage == PipelineStage.INTENT: assert intent_input is not None tts_input = await self.run.recognize_intent( intent_input, self.conversation_id, self.device_id, ) current_stage = PipelineStage.TTS if self.run.end_stage != PipelineStage.INTENT: if current_stage == PipelineStage.TTS: assert tts_input is not None await self.run.text_to_speech(tts_input) except PipelineError as err: self.run.process_event( PipelineEvent( PipelineEventType.ERROR, {"code": err.code, "message": err.message}, ) ) return self.run.end() async def validate(self) -> None: """Validate pipeline input against start stage.""" if self.run.start_stage == PipelineStage.STT: if self.run.pipeline.stt_engine is None: raise PipelineRunValidationError( "the pipeline does not support speech-to-text" ) if self.stt_metadata is None: raise PipelineRunValidationError( "stt_metadata is required for speech-to-text" ) if self.stt_stream is None: raise PipelineRunValidationError( "stt_stream is required for speech-to-text" ) elif self.run.start_stage == PipelineStage.INTENT: if self.intent_input is None: raise PipelineRunValidationError( "intent_input is required for intent recognition" ) elif self.run.start_stage == PipelineStage.TTS: if self.tts_input is None: raise PipelineRunValidationError( "tts_input is required for text-to-speech" ) if self.run.end_stage == PipelineStage.TTS: if self.run.pipeline.tts_engine is None: raise PipelineRunValidationError( "the pipeline does not support text-to-speech" ) start_stage_index = PIPELINE_STAGE_ORDER.index(self.run.start_stage) end_stage_index = PIPELINE_STAGE_ORDER.index(self.run.end_stage) prepare_tasks = [] if ( start_stage_index <= PIPELINE_STAGE_ORDER.index(PipelineStage.STT) <= end_stage_index ): # self.stt_metadata can't be None or we'd raise above prepare_tasks.append(self.run.prepare_speech_to_text(self.stt_metadata)) # type: ignore[arg-type] if ( start_stage_index <= PIPELINE_STAGE_ORDER.index(PipelineStage.INTENT) <= end_stage_index ): prepare_tasks.append(self.run.prepare_recognize_intent()) if ( start_stage_index <= PIPELINE_STAGE_ORDER.index(PipelineStage.TTS) <= end_stage_index ): prepare_tasks.append(self.run.prepare_text_to_speech()) if prepare_tasks: await asyncio.gather(*prepare_tasks) class PipelinePreferred(CollectionError): """Raised when attempting to delete the preferred pipelen.""" def __init__(self, item_id: str) -> None: """Initialize pipeline preferred error.""" super().__init__(f"Item {item_id} preferred.") self.item_id = item_id class SerializedPipelineStorageCollection(SerializedStorageCollection): """Serialized pipeline storage collection.""" preferred_item: str class PipelineStorageCollection( StorageCollection[Pipeline, SerializedPipelineStorageCollection] ): """Pipeline storage collection.""" _preferred_item: str async def _async_load_data(self) -> SerializedPipelineStorageCollection | None: """Load the data.""" if not (data := await super()._async_load_data()): pipeline = await _async_create_default_pipeline(self.hass, self) self._preferred_item = pipeline.id return data self._preferred_item = data["preferred_item"] return data async def _process_create_data(self, data: dict) -> dict: """Validate the config is valid.""" validated_data: dict = validate_language(data) return validated_data @callback def _get_suggested_id(self, info: dict) -> str: """Suggest an ID based on the config.""" return ulid_util.ulid() async def _update_data(self, item: Pipeline, update_data: dict) -> Pipeline: """Return a new updated item.""" update_data = validate_language(update_data) return Pipeline(id=item.id, **update_data) def _create_item(self, item_id: str, data: dict) -> Pipeline: """Create an item from validated config.""" return Pipeline(id=item_id, **data) def _deserialize_item(self, data: dict) -> Pipeline: """Create an item from its serialized representation.""" return Pipeline(**data) def _serialize_item(self, item_id: str, item: Pipeline) -> dict: """Return the serialized representation of an item for storing.""" return item.to_json() async def async_delete_item(self, item_id: str) -> None: """Delete item.""" if self._preferred_item == item_id: raise PipelinePreferred(item_id) await super().async_delete_item(item_id) @callback def async_get_preferred_item(self) -> str: """Get the id of the preferred item.""" return self._preferred_item @callback def async_set_preferred_item(self, item_id: str) -> None: """Set the preferred pipeline.""" if item_id not in self.data: raise ItemNotFound(item_id) self._preferred_item = item_id self._async_schedule_save() @callback def _data_to_save(self) -> SerializedPipelineStorageCollection: """Return JSON-compatible date for storing to file.""" base_data = super()._base_data_to_save() return { "items": base_data["items"], "preferred_item": self._preferred_item, } class PipelineStorageCollectionWebsocket( StorageCollectionWebsocket[PipelineStorageCollection] ): """Class to expose storage collection management over websocket.""" @callback def async_setup( self, hass: HomeAssistant, *, create_list: bool = True, create_create: bool = True, ) -> None: """Set up the websocket commands.""" super().async_setup(hass, create_list=create_list, create_create=create_create) websocket_api.async_register_command( hass, f"{self.api_prefix}/get", self.ws_get_item, websocket_api.BASE_COMMAND_MESSAGE_SCHEMA.extend( { vol.Required("type"): f"{self.api_prefix}/get", vol.Optional(self.item_id_key): str, } ), ) websocket_api.async_register_command( hass, f"{self.api_prefix}/set_preferred", websocket_api.require_admin( websocket_api.async_response(self.ws_set_preferred_item) ), websocket_api.BASE_COMMAND_MESSAGE_SCHEMA.extend( { vol.Required("type"): f"{self.api_prefix}/set_preferred", vol.Required(self.item_id_key): str, } ), ) async def ws_delete_item( self, hass: HomeAssistant, connection: websocket_api.ActiveConnection, msg: dict ) -> None: """Delete an item.""" try: await super().ws_delete_item(hass, connection, msg) except PipelinePreferred as exc: connection.send_error( msg["id"], websocket_api.const.ERR_NOT_ALLOWED, str(exc) ) @callback def ws_get_item( self, hass: HomeAssistant, connection: websocket_api.ActiveConnection, msg: dict ) -> None: """Get an item.""" item_id = msg.get(self.item_id_key) if item_id is None: item_id = self.storage_collection.async_get_preferred_item() if item_id not in self.storage_collection.data: connection.send_error( msg["id"], websocket_api.const.ERR_NOT_FOUND, f"Unable to find {self.item_id_key} {item_id}", ) return connection.send_result(msg["id"], self.storage_collection.data[item_id]) @callback def ws_list_item( self, hass: HomeAssistant, connection: websocket_api.ActiveConnection, msg: dict ) -> None: """List items.""" connection.send_result( msg["id"], { "pipelines": self.storage_collection.async_items(), "preferred_pipeline": self.storage_collection.async_get_preferred_item(), }, ) async def ws_set_preferred_item( self, hass: HomeAssistant, connection: websocket_api.ActiveConnection, msg: dict[str, Any], ) -> None: """Set the preferred item.""" try: self.storage_collection.async_set_preferred_item(msg[self.item_id_key]) except ItemNotFound: connection.send_error( msg["id"], websocket_api.const.ERR_NOT_FOUND, "unknown item" ) return connection.send_result(msg["id"]) @dataclass class PipelineData: """Store and debug data stored in hass.data.""" pipeline_runs: dict[str, LimitedSizeDict[str, PipelineRunDebug]] pipeline_store: PipelineStorageCollection pipeline_devices: set[str] = field(default_factory=set, init=False) @dataclass class PipelineRunDebug: """Debug data for a pipelinerun.""" events: list[PipelineEvent] = field(default_factory=list, init=False) timestamp: str = field( default_factory=lambda: dt_util.utcnow().isoformat(), init=False, ) @singleton(DOMAIN) async def async_setup_pipeline_store(hass: HomeAssistant) -> PipelineData: """Set up the pipeline storage collection.""" pipeline_store = PipelineStorageCollection( Store(hass, STORAGE_VERSION, STORAGE_KEY) ) await pipeline_store.async_load() PipelineStorageCollectionWebsocket( pipeline_store, f"{DOMAIN}/pipeline", "pipeline", PIPELINE_FIELDS, PIPELINE_FIELDS, ).async_setup(hass) return PipelineData({}, pipeline_store)