d3021b4590
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.
133 lines
3.9 KiB
Python
133 lines
3.9 KiB
Python
#
|
|
# Copyright (c) 2024-2026, Daily
|
|
#
|
|
# SPDX-License-Identifier: BSD 2-Clause License
|
|
#
|
|
|
|
import asyncio
|
|
import tkinter as tk
|
|
|
|
from dotenv import load_dotenv
|
|
from loguru import logger
|
|
|
|
from pipecat.frames.frames import (
|
|
Frame,
|
|
InputAudioRawFrame,
|
|
InputImageRawFrame,
|
|
OutputAudioRawFrame,
|
|
OutputImageRawFrame,
|
|
)
|
|
from pipecat.pipeline.pipeline import Pipeline
|
|
from pipecat.pipeline.runner import PipelineRunner
|
|
from pipecat.pipeline.task import PipelineParams, PipelineTask
|
|
from pipecat.processors.frame_processor import FrameDirection, FrameProcessor
|
|
from pipecat.runner.types import RunnerArguments
|
|
from pipecat.runner.utils import create_transport, maybe_capture_participant_camera
|
|
from pipecat.transports.base_transport import BaseTransport, TransportParams
|
|
from pipecat.transports.daily.transport import DailyParams
|
|
from pipecat.transports.local.tk import TkLocalTransport, TkTransportParams
|
|
|
|
load_dotenv(override=True)
|
|
|
|
|
|
class MirrorProcessor(FrameProcessor):
|
|
async def process_frame(self, frame: Frame, direction: FrameDirection):
|
|
await super().process_frame(frame, direction)
|
|
|
|
if isinstance(frame, InputAudioRawFrame):
|
|
await self.push_frame(
|
|
OutputAudioRawFrame(
|
|
audio=frame.audio,
|
|
sample_rate=frame.sample_rate,
|
|
num_channels=frame.num_channels,
|
|
)
|
|
)
|
|
elif isinstance(frame, InputImageRawFrame):
|
|
await self.push_frame(
|
|
OutputImageRawFrame(image=frame.image, size=frame.size, format=frame.format)
|
|
)
|
|
else:
|
|
await self.push_frame(frame, direction)
|
|
|
|
|
|
# We use lambdas to defer transport parameter creation until the transport
|
|
# type is selected at runtime.
|
|
transport_params = {
|
|
"daily": lambda: DailyParams(
|
|
audio_in_enabled=True,
|
|
audio_out_enabled=True,
|
|
video_in_enabled=True,
|
|
video_out_enabled=True,
|
|
video_out_is_live=True,
|
|
video_out_width=1280,
|
|
video_out_height=720,
|
|
),
|
|
"webrtc": lambda: TransportParams(
|
|
audio_in_enabled=True,
|
|
audio_out_enabled=True,
|
|
video_in_enabled=True,
|
|
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")
|
|
|
|
tk_root = tk.Tk()
|
|
tk_root.title("Local Mirror")
|
|
|
|
tk_transport = TkLocalTransport(
|
|
tk_root,
|
|
TkTransportParams(
|
|
audio_out_enabled=True,
|
|
video_out_enabled=True,
|
|
video_out_is_live=True,
|
|
video_out_width=1280,
|
|
video_out_height=720,
|
|
),
|
|
)
|
|
|
|
pipeline = Pipeline([transport.input(), MirrorProcessor(), tk_transport.output()])
|
|
|
|
task = PipelineTask(
|
|
pipeline,
|
|
params=PipelineParams(),
|
|
idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
|
|
)
|
|
|
|
async def run_tk():
|
|
while not task.has_finished():
|
|
tk_root.update()
|
|
tk_root.update_idletasks()
|
|
await asyncio.sleep(0.1)
|
|
|
|
@transport.event_handler("on_client_connected")
|
|
async def on_client_connected(transport, client):
|
|
logger.info(f"Client connected")
|
|
await maybe_capture_participant_camera(transport, client, framerate=30)
|
|
|
|
@transport.event_handler("on_client_disconnected")
|
|
async def on_client_disconnected(transport, client):
|
|
logger.info(f"Client disconnected")
|
|
await task.cancel()
|
|
|
|
runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
|
|
|
|
await asyncio.gather(runner.run(task), run_tk())
|
|
|
|
|
|
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()
|