135 lines
4.6 KiB
Python
135 lines
4.6 KiB
Python
#
|
||
# Copyright (c) 2024–2025, Daily
|
||
#
|
||
# SPDX-License-Identifier: BSD 2-Clause License
|
||
#
|
||
|
||
import asyncio
|
||
import os
|
||
import sys
|
||
from typing import Any, Mapping
|
||
|
||
import aiohttp
|
||
from dotenv import load_dotenv
|
||
from loguru import logger
|
||
|
||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||
from pipecat.pipeline.pipeline import Pipeline
|
||
from pipecat.pipeline.runner import PipelineRunner
|
||
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||
from pipecat.services.cartesia import CartesiaTTSService
|
||
from pipecat.services.deepgram import DeepgramSTTService
|
||
from pipecat.services.openai import OpenAILLMService
|
||
from pipecat.services.tavus import TavusVideoService
|
||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||
|
||
load_dotenv(override=True)
|
||
|
||
logger.remove(0)
|
||
logger.add(sys.stderr, level="DEBUG")
|
||
|
||
|
||
async def main():
|
||
async with aiohttp.ClientSession() as session:
|
||
tavus = TavusVideoService(
|
||
api_key=os.getenv("TAVUS_API_KEY"),
|
||
replica_id=os.getenv("TAVUS_REPLICA_ID"),
|
||
session=session,
|
||
)
|
||
|
||
# get persona, look up persona_name, set this as the bot name to ignore
|
||
persona_name = await tavus.get_persona_name()
|
||
room_url = await tavus.initialize()
|
||
|
||
transport = DailyTransport(
|
||
room_url=room_url,
|
||
token=None,
|
||
bot_name="Pipecat bot",
|
||
params=DailyParams(
|
||
vad_enabled=True,
|
||
vad_analyzer=SileroVADAnalyzer(),
|
||
vad_audio_passthrough=True,
|
||
),
|
||
)
|
||
|
||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||
|
||
tts = CartesiaTTSService(
|
||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||
voice_id="a167e0f3-df7e-4d52-a9c3-f949145efdab",
|
||
)
|
||
|
||
llm = OpenAILLMService(model="gpt-4o-mini")
|
||
|
||
messages = [
|
||
{
|
||
"role": "system",
|
||
"content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
|
||
},
|
||
]
|
||
|
||
context = OpenAILLMContext(messages)
|
||
context_aggregator = llm.create_context_aggregator(context)
|
||
|
||
pipeline = Pipeline(
|
||
[
|
||
transport.input(), # Transport user input
|
||
stt, # STT
|
||
context_aggregator.user(), # User responses
|
||
llm, # LLM
|
||
tts, # TTS
|
||
tavus, # Tavus output layer
|
||
transport.output(), # Transport bot output
|
||
context_aggregator.assistant(), # Assistant spoken responses
|
||
]
|
||
)
|
||
|
||
task = PipelineTask(
|
||
pipeline,
|
||
params=PipelineParams(
|
||
# We just use 16000 because that's what Tavus is expecting and
|
||
# we avoid resampling.
|
||
audio_in_sample_rate=16000,
|
||
audio_out_sample_rate=16000,
|
||
allow_interruptions=True,
|
||
enable_metrics=True,
|
||
enable_usage_metrics=True,
|
||
report_only_initial_ttfb=True,
|
||
),
|
||
)
|
||
|
||
@transport.event_handler("on_participant_joined")
|
||
async def on_participant_joined(
|
||
transport: DailyTransport, participant: Mapping[str, Any]
|
||
) -> None:
|
||
# Ignore the Tavus replica's microphone
|
||
if participant.get("info", {}).get("userName", "") == persona_name:
|
||
logger.debug(f"Ignoring {participant['id']}'s microphone")
|
||
await transport.update_subscriptions(
|
||
participant_settings={
|
||
participant["id"]: {
|
||
"media": {"microphone": "unsubscribed"},
|
||
}
|
||
}
|
||
)
|
||
|
||
if participant.get("info", {}).get("userName", "") != persona_name:
|
||
# Kick off the conversation.
|
||
messages.append(
|
||
{"role": "system", "content": "Please introduce yourself to the user."}
|
||
)
|
||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||
|
||
@transport.event_handler("on_participant_left")
|
||
async def on_participant_left(transport, participant, reason):
|
||
await task.cancel()
|
||
|
||
runner = PipelineRunner()
|
||
|
||
await runner.run(task)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
asyncio.run(main())
|