146 lines
5.0 KiB
Python
146 lines
5.0 KiB
Python
#
|
||
# Copyright (c) 2024–2025, Daily
|
||
#
|
||
# SPDX-License-Identifier: BSD 2-Clause License
|
||
#
|
||
|
||
import asyncio
|
||
import os
|
||
import sys
|
||
|
||
import aiohttp
|
||
from dotenv import load_dotenv
|
||
from loguru import logger
|
||
from runner import configure
|
||
|
||
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
||
from pipecat.frames.frames import EndFrame, TTSSpeakFrame
|
||
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.processors.user_idle_processor import UserIdleProcessor
|
||
from pipecat.services.cartesia import CartesiaTTSService
|
||
from pipecat.services.openai import OpenAILLMService
|
||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||
|
||
load_dotenv(override=True)
|
||
|
||
logger.remove(0)
|
||
logger.add(sys.stderr, level="DEBUG")
|
||
|
||
|
||
# Example callback using the new style with retry control
|
||
async def handle_user_idle(processor: UserIdleProcessor, retry_count: int) -> bool:
|
||
if retry_count == 1:
|
||
# First attempt: Add a gentle prompt to the conversation
|
||
messages.append(
|
||
{
|
||
"role": "system",
|
||
"content": "The user has been quiet for a while. Politely and concisely ask if they're still there.",
|
||
}
|
||
)
|
||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||
return True
|
||
elif retry_count == 2:
|
||
# Second attempt: More direct prompt
|
||
messages.append(
|
||
{
|
||
"role": "system",
|
||
"content": "The user is still inactive. Concisely ask if they would like to continue the conversation.",
|
||
}
|
||
)
|
||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||
return True
|
||
else:
|
||
# Third attempt: End the conversation
|
||
await task.queue_frames(
|
||
[TTSSpeakFrame("It seems like you're busy right now. Have a nice day!")]
|
||
)
|
||
await asyncio.sleep(3)
|
||
await task.queue_frame(EndFrame())
|
||
return False
|
||
|
||
|
||
async def main():
|
||
global task, messages, context_aggregator # Make these accessible to the idle handler
|
||
|
||
async with aiohttp.ClientSession() as session:
|
||
(room_url, token) = await configure(session)
|
||
|
||
transport = DailyTransport(
|
||
room_url,
|
||
token,
|
||
"Respond bot",
|
||
DailyParams(
|
||
audio_out_enabled=True,
|
||
transcription_enabled=True,
|
||
vad_enabled=True,
|
||
vad_analyzer=SileroVADAnalyzer(),
|
||
),
|
||
)
|
||
|
||
tts = CartesiaTTSService(
|
||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||
voice_id="79a125e8-cd45-4c13-8a67-188112f4dd22", # British Lady
|
||
)
|
||
|
||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4")
|
||
|
||
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)
|
||
|
||
# Create the idle processor
|
||
idle_processor = UserIdleProcessor(
|
||
callback=handle_user_idle,
|
||
timeout=5.0, # 5 seconds of inactivity before triggering
|
||
)
|
||
|
||
pipeline = Pipeline(
|
||
[
|
||
transport.input(), # Transport user input
|
||
idle_processor, # Add the idle processor
|
||
context_aggregator.user(), # User responses
|
||
llm, # LLM
|
||
tts, # TTS
|
||
transport.output(), # Transport bot output
|
||
context_aggregator.assistant(), # Assistant spoken responses
|
||
]
|
||
)
|
||
|
||
task = PipelineTask(
|
||
pipeline,
|
||
PipelineParams(
|
||
allow_interruptions=True,
|
||
enable_metrics=True,
|
||
enable_usage_metrics=True,
|
||
report_only_initial_ttfb=True,
|
||
),
|
||
)
|
||
|
||
@transport.event_handler("on_first_participant_joined")
|
||
async def on_first_participant_joined(transport, participant):
|
||
await transport.capture_participant_transcription(participant["id"])
|
||
# 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.queue_frame(EndFrame())
|
||
|
||
runner = PipelineRunner()
|
||
|
||
await runner.run(task)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
asyncio.run(main())
|