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pipecat/examples/foundational/01c-fastpitch.py
2025-05-29 10:43:12 -07:00

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#
# Copyright (c) 20242025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#
import argparse
import os
from dotenv import load_dotenv
from loguru import logger
from pipecat.frames.frames import EndFrame, TTSSpeakFrame
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineTask
from pipecat.services.riva.tts import FastPitchTTSService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.network.fastapi_websocket import FastAPIWebsocketParams
from pipecat.transports.services.daily import DailyParams
load_dotenv(override=True)
# We store functions so objects (e.g. SileroVADAnalyzer) don't get
# instantiated. The function will be called when the desired transport gets
# selected.
transport_params = {
"daily": lambda: DailyParams(audio_out_enabled=True),
"twilio": lambda: FastAPIWebsocketParams(audio_out_enabled=True),
"webrtc": lambda: TransportParams(audio_out_enabled=True),
}
async def run_example(transport: BaseTransport, _: argparse.Namespace, handle_sigint: bool):
logger.info(f"Starting bot")
tts = FastPitchTTSService(api_key=os.getenv("NVIDIA_API_KEY"))
task = PipelineTask(Pipeline([tts, transport.output()]))
# Register an event handler so we can play the audio when the client joins
@transport.event_handler("on_client_connected")
async def on_client_connected(transport, client):
await task.queue_frames([TTSSpeakFrame(f"Hello there!"), EndFrame()])
runner = PipelineRunner(handle_sigint=handle_sigint)
await runner.run(task)
if __name__ == "__main__":
from pipecat.examples.run import main
main(run_example, transport_params=transport_params)