115 lines
3.4 KiB
Python
115 lines
3.4 KiB
Python
#
|
||
# Copyright (c) 2024–2025, 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.pipeline.pipeline import Pipeline
|
||
from pipecat.pipeline.runner import PipelineRunner
|
||
from pipecat.pipeline.task import PipelineTask
|
||
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
|
||
from pipecat.services.cartesia.tts import CartesiaTTSService
|
||
from pipecat.services.deepgram.stt import DeepgramSTTService
|
||
from pipecat.services.openai.llm import OpenAILLMService
|
||
|
||
load_dotenv(override=True)
|
||
|
||
|
||
async def run_bot_logic(transport):
|
||
"""Main bot logic that works with any transport."""
|
||
logger.info(f"Starting bot")
|
||
|
||
stt = DeepgramSTTService(api_key=os.getenv("DEEPGRAM_API_KEY"))
|
||
|
||
tts = CartesiaTTSService(
|
||
api_key=os.getenv("CARTESIA_API_KEY"),
|
||
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
|
||
)
|
||
|
||
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))
|
||
|
||
messages = [
|
||
{
|
||
"role": "system",
|
||
"content": "You are a friendly AI assistant. Respond naturally and keep your answers conversational.",
|
||
},
|
||
]
|
||
|
||
context = OpenAILLMContext(messages)
|
||
context_aggregator = llm.create_context_aggregator(context)
|
||
|
||
pipeline = Pipeline(
|
||
[
|
||
transport.input(),
|
||
stt,
|
||
context_aggregator.user(),
|
||
llm,
|
||
tts,
|
||
transport.output(),
|
||
context_aggregator.assistant(),
|
||
]
|
||
)
|
||
|
||
task = PipelineTask(pipeline)
|
||
|
||
@transport.event_handler("on_client_connected")
|
||
async def on_client_connected(transport, client):
|
||
logger.info("Client connected")
|
||
messages.append({"role": "system", "content": "Say hello and briefly introduce yourself."})
|
||
await task.queue_frames([context_aggregator.user().get_context_frame()])
|
||
|
||
@transport.event_handler("on_client_disconnected")
|
||
async def on_client_disconnected(transport, client):
|
||
logger.info("Client disconnected")
|
||
await task.cancel()
|
||
|
||
runner = PipelineRunner(handle_sigint=False)
|
||
await runner.run(task)
|
||
|
||
|
||
async def bot(session_args):
|
||
"""Main bot entry point compatible with Pipecat Cloud."""
|
||
|
||
if hasattr(session_args, "room_url"):
|
||
# Daily session arguments (cloud or local)
|
||
from pipecat.transports.services.daily import DailyParams, DailyTransport
|
||
|
||
transport = DailyTransport(
|
||
session_args.room_url,
|
||
session_args.token,
|
||
"Pipecat Bot",
|
||
params=DailyParams(
|
||
audio_in_enabled=True,
|
||
audio_out_enabled=True,
|
||
vad_analyzer=SileroVADAnalyzer(),
|
||
),
|
||
)
|
||
|
||
elif hasattr(session_args, "webrtc_connection"):
|
||
# WebRTC session arguments (local only, created by server.py)
|
||
from pipecat.transports.base_transport import TransportParams
|
||
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
|
||
|
||
transport = SmallWebRTCTransport(
|
||
params=TransportParams(
|
||
audio_in_enabled=True,
|
||
audio_out_enabled=True,
|
||
vad_analyzer=SileroVADAnalyzer(),
|
||
),
|
||
webrtc_connection=session_args.webrtc_connection,
|
||
)
|
||
|
||
await run_bot_logic(transport)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
from pipecat.runner.cloud import main
|
||
|
||
main()
|