433 lines
15 KiB
Python
433 lines
15 KiB
Python
#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import base64
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import json
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import uuid
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from typing import AsyncGenerator, Optional
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import aiohttp
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from loguru import logger
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from pydantic import BaseModel
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from pipecat.frames.frames import (
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CancelFrame,
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EndFrame,
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ErrorFrame,
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Frame,
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StartFrame,
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StartInterruptionFrame,
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TTSAudioRawFrame,
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TTSStartedFrame,
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TTSStoppedFrame,
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)
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from pipecat.processors.frame_processor import FrameDirection
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from pipecat.services.tts_service import AudioContextWordTTSService, TTSService
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from pipecat.transcriptions.language import Language
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from pipecat.utils.text.base_text_aggregator import BaseTextAggregator
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from pipecat.utils.text.skip_tags_aggregator import SkipTagsAggregator
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try:
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import websockets
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except ModuleNotFoundError as e:
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logger.error(f"Exception: {e}")
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logger.error("In order to use Rime, you need to `pip install pipecat-ai[rime]`.")
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raise Exception(f"Missing module: {e}")
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def language_to_rime_language(language: Language) -> str:
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"""Convert pipecat Language to Rime language code.
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Args:
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language: The pipecat Language enum value.
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Returns:
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str: Three-letter language code used by Rime (e.g., 'eng' for English).
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"""
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LANGUAGE_MAP = {
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Language.EN: "eng",
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Language.ES: "spa",
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}
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return LANGUAGE_MAP.get(language, "eng")
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class RimeTTSService(AudioContextWordTTSService):
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"""Text-to-Speech service using Rime's websocket API.
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Uses Rime's websocket JSON API to convert text to speech with word-level timing
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information. Supports interruptions and maintains context across multiple messages
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within a turn.
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"""
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class InputParams(BaseModel):
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"""Configuration parameters for Rime TTS service."""
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language: Optional[Language] = Language.EN
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speed_alpha: Optional[float] = 1.0
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reduce_latency: Optional[bool] = False
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pause_between_brackets: Optional[bool] = False
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phonemize_between_brackets: Optional[bool] = False
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def __init__(
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self,
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*,
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api_key: str,
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voice_id: str,
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url: str = "wss://users.rime.ai/ws2",
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model: str = "mistv2",
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sample_rate: Optional[int] = None,
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params: InputParams = InputParams(),
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text_aggregator: Optional[BaseTextAggregator] = None,
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**kwargs,
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):
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"""Initialize Rime TTS service.
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Args:
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api_key: Rime API key for authentication.
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voice_id: ID of the voice to use.
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url: Rime websocket API endpoint.
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model: Model ID to use for synthesis.
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sample_rate: Audio sample rate in Hz.
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params: Additional configuration parameters.
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"""
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# Initialize with parent class settings for proper frame handling
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super().__init__(
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aggregate_sentences=True,
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push_text_frames=False,
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push_stop_frames=True,
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pause_frame_processing=True,
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sample_rate=sample_rate,
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text_aggregator=text_aggregator or SkipTagsAggregator([("spell(", ")")]),
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**kwargs,
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)
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# Store service configuration
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self._api_key = api_key
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self._url = url
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self._voice_id = voice_id
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self._model = model
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self._settings = {
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"speaker": voice_id,
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"modelId": model,
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"audioFormat": "pcm",
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"samplingRate": 0,
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"lang": self.language_to_service_language(params.language)
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if params.language
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else "eng",
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"speedAlpha": params.speed_alpha,
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"reduceLatency": params.reduce_latency,
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"pauseBetweenBrackets": json.dumps(params.pause_between_brackets),
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"phonemizeBetweenBrackets": json.dumps(params.phonemize_between_brackets),
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}
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# State tracking
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self._context_id = None # Tracks current turn
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self._receive_task = None
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self._cumulative_time = 0 # Accumulates time across messages
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def can_generate_metrics(self) -> bool:
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return True
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def language_to_service_language(self, language: Language) -> str | None:
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"""Convert pipecat language to Rime language code."""
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return language_to_rime_language(language)
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async def set_model(self, model: str):
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"""Update the TTS model."""
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self._model = model
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await super().set_model(model)
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def _build_msg(self, text: str = "") -> dict:
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"""Build JSON message for Rime API."""
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return {"text": text, "contextId": self._context_id}
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def _build_clear_msg(self) -> dict:
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"""Build clear operation message."""
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return {"operation": "clear"}
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def _build_eos_msg(self) -> dict:
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"""Build end-of-stream operation message."""
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return {"operation": "eos"}
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async def start(self, frame: StartFrame):
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"""Start the service and establish websocket connection."""
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await super().start(frame)
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self._settings["samplingRate"] = self.sample_rate
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await self._connect()
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async def stop(self, frame: EndFrame):
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"""Stop the service and close connection."""
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await super().stop(frame)
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await self._disconnect()
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async def cancel(self, frame: CancelFrame):
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"""Cancel current operation and clean up."""
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await super().cancel(frame)
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await self._disconnect()
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async def _connect(self):
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"""Establish websocket connection and start receive task."""
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await self._connect_websocket()
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if self._websocket and not self._receive_task:
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self._receive_task = self.create_task(self._receive_task_handler(self._report_error))
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async def _disconnect(self):
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"""Close websocket connection and clean up tasks."""
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if self._receive_task:
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await self.cancel_task(self._receive_task)
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self._receive_task = None
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await self._disconnect_websocket()
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async def _connect_websocket(self):
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"""Connect to Rime websocket API with configured settings."""
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try:
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if self._websocket and self._websocket.open:
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return
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params = "&".join(f"{k}={v}" for k, v in self._settings.items())
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url = f"{self._url}?{params}"
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headers = {"Authorization": f"Bearer {self._api_key}"}
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self._websocket = await websockets.connect(url, extra_headers=headers)
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except Exception as e:
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logger.error(f"{self} initialization error: {e}")
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self._websocket = None
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await self._call_event_handler("on_connection_error", f"{e}")
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async def _disconnect_websocket(self):
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"""Close websocket connection and reset state."""
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try:
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await self.stop_all_metrics()
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if self._websocket:
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await self._websocket.send(json.dumps(self._build_eos_msg()))
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await self._websocket.close()
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except Exception as e:
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logger.error(f"{self} error closing websocket: {e}")
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finally:
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self._context_id = None
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self._websocket = None
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def _get_websocket(self):
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"""Get active websocket connection or raise exception."""
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if self._websocket:
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return self._websocket
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raise Exception("Websocket not connected")
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async def _handle_interruption(self, frame: StartInterruptionFrame, direction: FrameDirection):
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"""Handle interruption by clearing current context."""
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await super()._handle_interruption(frame, direction)
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await self.stop_all_metrics()
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if self._context_id:
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await self._get_websocket().send(json.dumps(self._build_clear_msg()))
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self._context_id = None
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def _calculate_word_times(self, words: list, starts: list, ends: list) -> list:
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"""Calculate word timing pairs with proper spacing and punctuation.
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Args:
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words: List of words from Rime.
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starts: List of start times for each word.
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ends: List of end times for each word.
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Returns:
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List of (word, timestamp) pairs with proper timing.
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"""
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word_pairs = []
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for i, (word, start_time, _) in enumerate(zip(words, starts, ends)):
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if not word.strip():
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continue
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# Adjust timing by adding cumulative time
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adjusted_start = start_time + self._cumulative_time
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# Handle punctuation by appending to previous word
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is_punctuation = bool(word.strip(",.!?") == "")
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if is_punctuation and word_pairs:
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prev_word, prev_time = word_pairs[-1]
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word_pairs[-1] = (prev_word + word, prev_time)
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else:
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word_pairs.append((word, adjusted_start))
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return word_pairs
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async def flush_audio(self):
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if not self._context_id or not self._websocket:
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return
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logger.trace(f"{self}: flushing audio")
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await self._get_websocket().send(json.dumps({"text": " "}))
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self._context_id = None
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async def _receive_messages(self):
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"""Process incoming websocket messages."""
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async for message in self._get_websocket():
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msg = json.loads(message)
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if not msg or not self.audio_context_available(msg["contextId"]):
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continue
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if msg["type"] == "chunk":
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# Process audio chunk
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await self.stop_ttfb_metrics()
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self.start_word_timestamps()
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frame = TTSAudioRawFrame(
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audio=base64.b64decode(msg["data"]),
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sample_rate=self.sample_rate,
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num_channels=1,
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)
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await self.append_to_audio_context(msg["contextId"], frame)
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elif msg["type"] == "timestamps":
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# Process word timing information
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timestamps = msg.get("word_timestamps", {})
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words = timestamps.get("words", [])
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starts = timestamps.get("start", [])
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ends = timestamps.get("end", [])
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if words and starts:
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# Calculate word timing pairs
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word_pairs = self._calculate_word_times(words, starts, ends)
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if word_pairs:
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await self.add_word_timestamps(word_pairs)
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self._cumulative_time = ends[-1] + self._cumulative_time
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logger.debug(f"Updated cumulative time to: {self._cumulative_time}")
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elif msg["type"] == "error":
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logger.error(f"{self} error: {msg}")
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await self.push_frame(TTSStoppedFrame())
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await self.stop_all_metrics()
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await self.push_error(ErrorFrame(f"{self} error: {msg['message']}"))
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self._context_id = None
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async def push_frame(self, frame: Frame, direction: FrameDirection = FrameDirection.DOWNSTREAM):
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"""Push frame and handle end-of-turn conditions."""
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await super().push_frame(frame, direction)
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if isinstance(frame, (TTSStoppedFrame, StartInterruptionFrame)):
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if isinstance(frame, TTSStoppedFrame):
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await self.add_word_timestamps([("Reset", 0)])
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async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
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"""Generate speech from text.
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Args:
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text: The text to convert to speech.
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Yields:
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Frames containing audio data and timing information.
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"""
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logger.debug(f"{self}: Generating TTS [{text}]")
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try:
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if not self._websocket or self._websocket.closed:
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await self._connect()
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try:
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if not self._context_id:
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await self.start_ttfb_metrics()
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yield TTSStartedFrame()
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self._cumulative_time = 0
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self._context_id = str(uuid.uuid4())
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await self.create_audio_context(self._context_id)
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msg = self._build_msg(text=text)
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await self._get_websocket().send(json.dumps(msg))
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await self.start_tts_usage_metrics(text)
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except Exception as e:
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logger.error(f"{self} error sending message: {e}")
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yield TTSStoppedFrame()
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await self._disconnect()
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await self._connect()
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return
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yield None
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except Exception as e:
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logger.error(f"{self} exception: {e}")
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class RimeHttpTTSService(TTSService):
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class InputParams(BaseModel):
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pause_between_brackets: Optional[bool] = False
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phonemize_between_brackets: Optional[bool] = False
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inline_speed_alpha: Optional[str] = None
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speed_alpha: Optional[float] = 1.0
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reduce_latency: Optional[bool] = False
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def __init__(
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self,
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*,
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api_key: str,
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voice_id: str,
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aiohttp_session: aiohttp.ClientSession,
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model: str = "mistv2",
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sample_rate: Optional[int] = None,
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params: InputParams = InputParams(),
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**kwargs,
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):
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super().__init__(sample_rate=sample_rate, **kwargs)
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self._api_key = api_key
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self._session = aiohttp_session
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self._base_url = "https://users.rime.ai/v1/rime-tts"
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self._settings = {
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"speedAlpha": params.speed_alpha,
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"reduceLatency": params.reduce_latency,
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"pauseBetweenBrackets": params.pause_between_brackets,
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"phonemizeBetweenBrackets": params.phonemize_between_brackets,
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}
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self.set_voice(voice_id)
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self.set_model_name(model)
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if params.inline_speed_alpha:
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self._settings["inlineSpeedAlpha"] = params.inline_speed_alpha
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def can_generate_metrics(self) -> bool:
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return True
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async def run_tts(self, text: str) -> AsyncGenerator[Frame, None]:
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logger.debug(f"{self}: Generating TTS [{text}]")
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headers = {
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"Accept": "audio/pcm",
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"Authorization": f"Bearer {self._api_key}",
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"Content-Type": "application/json",
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}
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payload = self._settings.copy()
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payload["text"] = text
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payload["speaker"] = self._voice_id
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payload["modelId"] = self._model_name
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payload["samplingRate"] = self.sample_rate
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try:
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await self.start_ttfb_metrics()
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async with self._session.post(
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self._base_url, json=payload, headers=headers
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) as response:
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if response.status != 200:
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error_message = f"Rime TTS error: HTTP {response.status}"
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logger.error(error_message)
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yield ErrorFrame(error=error_message)
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return
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await self.start_tts_usage_metrics(text)
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yield TTSStartedFrame()
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# Process the streaming response
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CHUNK_SIZE = 1024
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async for chunk in response.content.iter_chunked(CHUNK_SIZE):
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if len(chunk) > 0:
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await self.stop_ttfb_metrics()
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frame = TTSAudioRawFrame(chunk, self.sample_rate, 1)
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yield frame
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except Exception as e:
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logger.exception(f"Error generating TTS: {e}")
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yield ErrorFrame(error=f"Rime TTS error: {str(e)}")
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finally:
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await self.stop_ttfb_metrics()
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yield TTSStoppedFrame()
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