76 lines
2.0 KiB
Python
76 lines
2.0 KiB
Python
#
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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 argparse
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from dotenv import load_dotenv
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from loguru import logger
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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.processors.gstreamer.pipeline_source import GStreamerPipelineSource
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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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# Parse command line arguments
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# This will be used to pass the input video file to the bot
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# You can run the bot with a command like:
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# python 18-gstreamer-filesrc.py -i path/to/video.mp4
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def parse_arguments():
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parser = argparse.ArgumentParser(description="Daily AI SDK Bot Sample")
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parser.add_argument("-i", "--input", type=str, required=True, help="Input video file")
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return parser.parse_args()
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args = parse_arguments()
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async def run_bot(webrtc_connection: SmallWebRTCConnection):
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logger.info(f"Starting bot with video input: {args.input}")
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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_in_enabled=True,
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camera_out_enabled=True,
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camera_out_is_live=True,
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camera_out_width=1280,
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camera_out_height=720,
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),
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)
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gst = GStreamerPipelineSource(
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pipeline=f"filesrc location={args.input}",
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out_params=GStreamerPipelineSource.OutputParams(
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video_width=1280,
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video_height=720,
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),
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)
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pipeline = Pipeline(
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[
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gst, # GStreamer file source
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transport.output(), # Transport bot output
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]
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)
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task = PipelineTask(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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from run import main
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main()
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