192 lines
6.0 KiB
Python
192 lines
6.0 KiB
Python
#
|
|
# Copyright (c) 2024, Daily
|
|
#
|
|
# SPDX-License-Identifier: BSD 2-Clause License
|
|
#
|
|
|
|
import asyncio
|
|
import os
|
|
import sys
|
|
import time
|
|
|
|
import aiohttp
|
|
from loguru import logger
|
|
from runner import configure
|
|
|
|
from pipecat.audio.vad.silero import SileroVADAnalyzer
|
|
from pipecat.frames.frames import (
|
|
BotSpeakingFrame,
|
|
EndFrame,
|
|
Frame,
|
|
InputAudioRawFrame,
|
|
StartInterruptionFrame,
|
|
StopInterruptionFrame,
|
|
TextFrame,
|
|
TranscriptionFrame,
|
|
TTSAudioRawFrame,
|
|
UserStartedSpeakingFrame,
|
|
UserStoppedSpeakingFrame,
|
|
)
|
|
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.frame_processor import FrameDirection, FrameProcessor
|
|
from pipecat.services.cartesia import CartesiaTTSService
|
|
from pipecat.services.openai import OpenAILLMService
|
|
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
|
|
|
logger.remove(0)
|
|
logger.add(sys.stderr, level="DEBUG")
|
|
|
|
|
|
class DebugProcessor(FrameProcessor):
|
|
def __init__(self, name, **kwargs):
|
|
self._name = name
|
|
super().__init__(**kwargs)
|
|
|
|
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
|
await super().process_frame(frame, direction)
|
|
if not (
|
|
isinstance(frame, InputAudioRawFrame)
|
|
or isinstance(frame, BotSpeakingFrame)
|
|
or isinstance(frame, UserStoppedSpeakingFrame)
|
|
or isinstance(frame, TTSAudioRawFrame)
|
|
or isinstance(frame, TextFrame)
|
|
):
|
|
logger.debug(f"--- {self._name}: {frame} {direction}")
|
|
await self.push_frame(frame, direction)
|
|
|
|
|
|
async def main():
|
|
async with aiohttp.ClientSession() as session:
|
|
(room_url, _) = await configure(session)
|
|
|
|
transport = DailyTransport(
|
|
room_url,
|
|
None,
|
|
"AI 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.environ["OPENAI_API_KEY"], model="gpt-4o")
|
|
|
|
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.",
|
|
},
|
|
]
|
|
|
|
dp = DebugProcessor("dp")
|
|
|
|
context = OpenAILLMContext(messages)
|
|
context_aggregator = llm.create_context_aggregator(context)
|
|
|
|
runner = PipelineRunner()
|
|
|
|
task = PipelineTask(
|
|
Pipeline(
|
|
[
|
|
# transport.input(),
|
|
context_aggregator.user(),
|
|
llm,
|
|
dp,
|
|
tts,
|
|
transport.output(),
|
|
context_aggregator.assistant(),
|
|
]
|
|
),
|
|
PipelineParams(
|
|
allow_interruptions=True,
|
|
),
|
|
)
|
|
|
|
# Register an event handler so we can play the audio when the
|
|
# participant joins.
|
|
@transport.event_handler("on_first_participant_joined")
|
|
async def on_first_participant_joined(transport, participant):
|
|
participant_id = participant.get("info", {}).get("participantId", "")
|
|
|
|
# Create frames for 600 seconds
|
|
start_time = time.time()
|
|
while time.time() - start_time < 300:
|
|
elapsed_time = round(time.time() - start_time)
|
|
logger.info(f"Running for {elapsed_time} seconds")
|
|
await task.queue_frame(
|
|
StartInterruptionFrame(),
|
|
)
|
|
await asyncio.sleep(1)
|
|
|
|
await task.queue_frame(
|
|
UserStartedSpeakingFrame(),
|
|
)
|
|
|
|
await asyncio.sleep(1)
|
|
|
|
await task.queue_frame(
|
|
TranscriptionFrame("Tell me more about your company.", participant_id, time.time()),
|
|
)
|
|
|
|
await asyncio.sleep(1)
|
|
|
|
await task.queue_frame(
|
|
StopInterruptionFrame(),
|
|
)
|
|
|
|
await asyncio.sleep(1)
|
|
|
|
await task.queue_frame(
|
|
UserStoppedSpeakingFrame(),
|
|
)
|
|
|
|
await asyncio.sleep(5)
|
|
|
|
await task.queue_frame(StartInterruptionFrame())
|
|
await asyncio.sleep(1)
|
|
|
|
await task.queue_frame(
|
|
UserStartedSpeakingFrame(),
|
|
)
|
|
|
|
await asyncio.sleep(1)
|
|
|
|
await task.queue_frame(
|
|
TranscriptionFrame("Give me a list of appointment dates.", participant_id, time.time()),
|
|
)
|
|
|
|
await asyncio.sleep(1)
|
|
|
|
await task.queue_frames(
|
|
StopInterruptionFrame(),
|
|
)
|
|
|
|
await asyncio.sleep(1)
|
|
await task.queue_frame(
|
|
UserStoppedSpeakingFrame(),
|
|
)
|
|
await asyncio.sleep(5)
|
|
await task.queue_frame(EndFrame())
|
|
|
|
# @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([LLMMessagesFrame(messages)])
|
|
|
|
await runner.run(task)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|