afa880f523
Register the worker with PipelineRunner.add_workers() before calling run() instead. The worker argument still works but now emits a DeprecationWarning and will be removed in a future release. Update the runner docstrings, the run_test() helper, and all examples (including the asyncio.gather() forms) to use the new pattern.
144 lines
4.8 KiB
Python
144 lines
4.8 KiB
Python
#
|
|
# Copyright (c) 2024-2026, Daily
|
|
#
|
|
# SPDX-License-Identifier: BSD 2-Clause License
|
|
#
|
|
|
|
|
|
import os
|
|
|
|
from dotenv import load_dotenv
|
|
from loguru import logger
|
|
|
|
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
|
from pipecat.frames.frames import TTSSpeakFrame
|
|
from pipecat.pipeline.pipeline import Pipeline
|
|
from pipecat.pipeline.runner import PipelineRunner
|
|
from pipecat.pipeline.worker import PipelineParams, PipelineWorker
|
|
from pipecat.processors.aggregators.llm_context import LLMContext
|
|
from pipecat.processors.aggregators.llm_response_universal import (
|
|
LLMContextAggregatorPair,
|
|
LLMUserAggregatorParams,
|
|
)
|
|
from pipecat.runner.types import RunnerArguments
|
|
from pipecat.runner.utils import create_transport
|
|
from pipecat.services.cartesia.tts import CartesiaTTSService
|
|
from pipecat.services.deepgram.stt import DeepgramSTTService
|
|
from pipecat.services.openai.llm import OpenAILLMService
|
|
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
|
from pipecat.transports.daily.transport import DailyParams
|
|
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
|
|
from pipecat.turns.user_start import TranscriptionUserTurnStartStrategy
|
|
from pipecat.turns.user_turn_strategies import UserTurnStrategies
|
|
|
|
load_dotenv(override=True)
|
|
|
|
|
|
# We use lambdas to defer transport parameter creation until the transport
|
|
# type is selected at runtime.
|
|
transport_params = {
|
|
"daily": lambda: DailyParams(
|
|
audio_in_enabled=True,
|
|
audio_out_enabled=True,
|
|
),
|
|
"twilio": lambda: FastAPIWebsocketParams(
|
|
audio_in_enabled=True,
|
|
audio_out_enabled=True,
|
|
),
|
|
"webrtc": lambda: TransportParams(
|
|
audio_in_enabled=True,
|
|
audio_out_enabled=True,
|
|
),
|
|
}
|
|
|
|
|
|
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
|
|
logger.info(f"Starting bot")
|
|
|
|
stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
|
|
|
|
tts = CartesiaTTSService(
|
|
api_key=os.environ["CARTESIA_API_KEY"],
|
|
settings=CartesiaTTSService.Settings(
|
|
voice="d4db5fb9-f44b-4bd1-85fa-192e0f0d75f9", # Spanish-speaking Lady
|
|
),
|
|
)
|
|
|
|
llm = OpenAILLMService(
|
|
api_key=os.environ["OPENAI_API_KEY"],
|
|
settings=OpenAILLMService.Settings(
|
|
system_instruction="You are a live translation assistant. Your sole purpose is to translate English text into Spanish. When you receive English text from the user, immediately translate it into natural, fluent Spanish. Do not add explanations, commentary, or extra information—only provide the Spanish translation of the text you receive.",
|
|
),
|
|
)
|
|
|
|
context = LLMContext()
|
|
|
|
# We use the TranscriptionUserTurnStartStrategy to start a new user turn
|
|
# every time a transcription is received. We disable interruptions, so the
|
|
# user can continue speaking while the bot is transcribing, without
|
|
# interrupting the bot.
|
|
user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
|
|
context,
|
|
user_params=LLMUserAggregatorParams(
|
|
user_turn_strategies=UserTurnStrategies(
|
|
start=[TranscriptionUserTurnStartStrategy(enable_interruptions=False)],
|
|
),
|
|
vad_analyzer=SileroVADAnalyzer(),
|
|
),
|
|
)
|
|
|
|
pipeline = Pipeline(
|
|
[
|
|
transport.input(), # Transport user input
|
|
stt, # STT
|
|
user_aggregator, # User responses
|
|
llm, # LLM
|
|
tts, # TTS (bot will speak the chosen language)
|
|
transport.output(), # Transport bot output
|
|
assistant_aggregator, # Assistant spoken responses
|
|
]
|
|
)
|
|
|
|
worker = PipelineWorker(
|
|
pipeline,
|
|
params=PipelineParams(
|
|
enable_metrics=True,
|
|
enable_usage_metrics=True,
|
|
),
|
|
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
|
)
|
|
|
|
@transport.event_handler("on_client_connected")
|
|
async def on_client_connected(transport, client):
|
|
logger.info(f"Client connected")
|
|
await worker.queue_frames(
|
|
[
|
|
TTSSpeakFrame(
|
|
text="Hello, welcome to live translation. Everything you say will be automatically translated to Spanish. Let's begin!",
|
|
append_to_context=True,
|
|
),
|
|
]
|
|
)
|
|
|
|
@transport.event_handler("on_client_disconnected")
|
|
async def on_client_disconnected(transport, client):
|
|
logger.info(f"Client disconnected")
|
|
await worker.cancel()
|
|
|
|
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
|
|
|
|
await runner.add_workers(worker)
|
|
await runner.run()
|
|
|
|
|
|
async def bot(runner_args: RunnerArguments):
|
|
"""Main bot entry point compatible with Pipecat Cloud."""
|
|
transport = await create_transport(runner_args, transport_params)
|
|
await run_bot(transport, runner_args)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
from pipecat.runner.run import main
|
|
|
|
main()
|