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:
@@ -4,15 +4,12 @@
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import asyncio
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import os
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import sys
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from dataclasses import dataclass
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import aiohttp
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from dotenv import load_dotenv
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from loguru import logger
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from runner import configure
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from pipecat.frames.frames import (
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DataFrame,
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@@ -30,13 +27,12 @@ from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
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from pipecat.services.cartesia.tts import CartesiaHttpTTSService
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from pipecat.services.fal.image import FalImageGenService
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.transports.services.daily import DailyParams, DailyTransport
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from pipecat.transports.base_transport import TransportParams
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from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
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from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection
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load_dotenv(override=True)
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logger.remove(0)
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logger.add(sys.stderr, level="DEBUG")
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@dataclass
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class MonthFrame(DataFrame):
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@@ -67,22 +63,28 @@ class MonthPrepender(FrameProcessor):
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await self.push_frame(frame, direction)
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async def main():
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async def run_bot(webrtc_connection: SmallWebRTCConnection):
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"""Run the Calendar Month Narration bot using WebRTC transport.
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Args:
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webrtc_connection: The WebRTC connection to use
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room_name: Optional room name for display purposes
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"""
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logger.info(f"Starting bot")
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# Create a transport using the WebRTC connection
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transport = SmallWebRTCTransport(
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webrtc_connection=webrtc_connection,
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params=TransportParams(
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audio_out_enabled=True,
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camera_out_enabled=True,
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camera_out_width=1024,
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camera_out_height=1024,
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),
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)
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# Create an HTTP session for API calls
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async with aiohttp.ClientSession() as session:
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(room_url, _) = await configure(session)
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transport = DailyTransport(
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room_url,
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None,
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"Month Narration Bot",
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DailyParams(
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audio_out_enabled=True,
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camera_out_enabled=True,
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camera_out_width=1024,
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camera_out_height=1024,
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),
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)
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llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")
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tts = CartesiaHttpTTSService(
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@@ -144,14 +146,30 @@ async def main():
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frames.append(MonthFrame(month=month))
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frames.append(LLMMessagesFrame(messages))
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runner = PipelineRunner()
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task = PipelineTask(pipeline)
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await task.queue_frames(frames)
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# Set up transport event handlers
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@transport.event_handler("on_client_connected")
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async def on_client_connected(transport, client):
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logger.info(f"Client connected")
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# Start the month narration once connected
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await task.queue_frames(frames)
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@transport.event_handler("on_client_disconnected")
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async def on_client_disconnected(transport, client):
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logger.info(f"Client disconnected")
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@transport.event_handler("on_client_closed")
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async def on_client_closed(transport, client):
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logger.info(f"Client closed connection")
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await task.cancel()
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# Run the pipeline
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runner = PipelineRunner(handle_sigint=False)
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await runner.run(task)
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if __name__ == "__main__":
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asyncio.run(main())
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from run import main
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main()
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