Files
pipecat/examples/video-processing/video-processing-gstreamer-videotestsrc.py
Mark Backman d3021b4590 Rename example files to prepend parent folder name, preventing package shadowing
Example files like openai.py shadow installed packages when Python adds the
script directory to sys.path. Prepend the parent folder name to each example
file (e.g. openai.py -> function-calling-openai.py). Also split
thinking-and-mcp/ into separate mcp/ and thinking/ directories.
2026-03-31 22:06:01 -04:00

77 lines
2.1 KiB
Python

#
# Copyright (c) 2024-2026, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
from dotenv import load_dotenv
from loguru import logger
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.processors.gstreamer.pipeline_source import GStreamerPipelineSource
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
load_dotenv(override=True)
# We use lambdas to defer transport parameter creation until the transport
# type is selected at runtime.
transport_params = {
"daily": lambda: DailyParams(
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
"webrtc": lambda: TransportParams(
video_out_enabled=True,
video_out_is_live=True,
video_out_width=1280,
video_out_height=720,
),
}
async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
logger.info(f"Starting bot with video test source")
gst = GStreamerPipelineSource(
pipeline='videotestsrc ! capsfilter caps="video/x-raw,width=1280,height=720,framerate=30/1"',
out_params=GStreamerPipelineSource.OutputParams(
video_width=1280, video_height=720, clock_sync=False
),
)
pipeline = Pipeline(
[
gst, # GStreamer test source
transport.output(), # Transport bot output
]
)
task = PipelineTask(
pipeline,
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
)
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
await runner.run(task)
async def bot(runner_args: RunnerArguments):
"""Main bot entry point compatible with Pipecat Cloud."""
transport = await create_transport(runner_args, transport_params)
await run_bot(transport, runner_args)
if __name__ == "__main__":
from pipecat.runner.run import main
main()