Updating foundation examples to use SmallWebRTCTransport and pipecat-ai-small-webrtc-prebuilt (#1534)

Co-authored-by: Filipi Fuchter <filipi@daily.co>
This commit is contained in:
Mark Backman
2025-04-11 19:44:16 -04:00
committed by GitHub
parent 8186219879
commit f6accbd510
120 changed files with 7989 additions and 7179 deletions

View File

@@ -4,14 +4,10 @@
# 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.frames.frames import EndFrame, LLMMessagesFrame
from pipecat.pipeline.pipeline import Pipeline
@@ -19,46 +15,51 @@ from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
load_dotenv(override=True)
logger.remove(0)
logger.add(sys.stderr, level="DEBUG")
async def run_bot(webrtc_connection: SmallWebRTCConnection):
logger.info(f"Starting bot")
async def main():
async with aiohttp.ClientSession() as session:
(room_url, _) = await configure(session)
# Create a transport using the WebRTC connection
transport = SmallWebRTCTransport(
webrtc_connection=webrtc_connection,
params=TransportParams(
audio_out_enabled=True,
),
)
transport = DailyTransport(
room_url, None, "Say One Thing From an LLM", DailyParams(audio_out_enabled=True)
)
tts = CartesiaTTSService(
api_key=os.getenv("CARTESIA_API_KEY"),
voice_id="71a7ad14-091c-4e8e-a314-022ece01c121", # British Reading Lady
)
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"), model="gpt-4o")
llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
messages = [
{
"role": "system",
"content": "You are an LLM in a WebRTC session, and this is a 'hello world' demo. Say hello to the world.",
}
]
messages = [
{
"role": "system",
"content": "You are an LLM in a WebRTC session, and this is a 'hello world' demo. Say hello to the world.",
}
]
task = PipelineTask(Pipeline([llm, tts, transport.output()]))
runner = PipelineRunner()
# Register an event handler so we can play the audio when the client joins
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
await task.queue_frames([LLMMessagesFrame(messages), EndFrame()])
task = PipelineTask(Pipeline([llm, tts, transport.output()]))
runner = PipelineRunner(handle_sigint=False)
@transport.event_handler("on_first_participant_joined")
async def on_first_participant_joined(transport, participant):
await task.queue_frames([LLMMessagesFrame(messages), EndFrame()])
await runner.run(task)
await runner.run(task)
if __name__ == "__main__":
asyncio.run(main())
from run import main
main()