Updating foundation examples to use SmallWebRTCTransport and pipecat-ai-small-webrtc-prebuilt (#1534)
Co-authored-by: Filipi Fuchter <filipi@daily.co>
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59
examples/foundational/01-say-one-thing-rime.py
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59
examples/foundational/01-say-one-thing-rime.py
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#
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# Copyright (c) 2024–2025, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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import os
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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 pipecat.frames.frames import EndFrame, TTSSpeakFrame
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from pipecat.pipeline.pipeline import Pipeline
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.pipeline.task import PipelineTask
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from pipecat.services.rime.tts import RimeHttpTTSService
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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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async def run_bot(webrtc_connection: SmallWebRTCConnection):
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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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),
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)
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# Create an HTTP session
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async with aiohttp.ClientSession() as session:
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tts = RimeHttpTTSService(
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api_key=os.getenv("RIME_API_KEY", ""),
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voice_id="rex",
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aiohttp_session=session,
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)
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task = PipelineTask(Pipeline([tts, transport.output()]))
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# Register an event handler so we can play the audio when the client joins
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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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await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
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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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from run import main
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main()
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