Add remote-proxy-assistant example
Demonstrates the WebSocket proxy tasks: a local `main.py` voice bot uses `WebSocketProxyClientTask` to forward bus messages (including `BusFrameMessage`s) to a remote `assistant.py` FastAPI server. Each incoming connection spawns a `WebSocketProxyServerTask` plus an `LLMTask` assistant on a per-session `PipelineRunner`.
This commit is contained in:
Aleix Conchillo Flaqué
118
examples/multi-task/remote-proxy-assistant/assistant.py
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118
examples/multi-task/remote-proxy-assistant/assistant.py
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#
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# Copyright (c) 2026, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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"""Remote assistant LLM server.
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Runs a FastAPI server that accepts WebSocket connections from a
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``main.py``-style client. Each connection spins up a
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`WebSocketProxyServerTask` bridging the socket to a local
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`PipelineRunner` and an `LLMTask` that handles the conversation.
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Usage::
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python assistant.py
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python assistant.py --port 9000
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Requirements:
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- OPENAI_API_KEY
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"""
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import argparse
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import os
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import uvicorn
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from dotenv import load_dotenv
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from fastapi import FastAPI, WebSocket
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from loguru import logger
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from pipecat.bus import BusFrameMessage
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from pipecat.pipeline.runner import PipelineRunner
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from pipecat.services.llm_service import FunctionCallParams
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from pipecat.services.openai.llm import OpenAILLMService
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from pipecat.tasks.llm import LLMTask, tool
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from pipecat.tasks.proxy.websocket import WebSocketProxyServerTask
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load_dotenv(override=True)
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app = FastAPI()
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class AcmeAssistant(LLMTask):
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"""Handles greetings, product questions, and conversation end."""
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def __init__(self):
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"""Initialize the AcmeAssistant LLM task."""
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llm = OpenAILLMService(
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api_key=os.environ["OPENAI_API_KEY"],
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settings=OpenAILLMService.Settings(
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system_instruction=(
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"You are a friendly assistant for Acme Corp. You know about three "
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"products: Acme Rocket Boots (jet-powered boots, $299, run up to "
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"60 mph), Acme Invisible Paint (makes anything invisible for 24 hours, "
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"$49 per can), and Acme Tornado Kit (portable tornado generator, $199, "
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"batteries included). Greet the user, help them with product questions, "
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"and call end_conversation when the user says goodbye. "
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"Keep responses brief, this is a voice conversation."
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),
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),
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)
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super().__init__("assistant", llm=llm, bridged=())
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@tool
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async def end_conversation(self, params: FunctionCallParams, reason: str):
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"""End the conversation when the user says goodbye.
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Args:
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reason (str): Why the conversation is ending.
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"""
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logger.info(f"Task '{self.name}': ending conversation ({reason})")
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await self.end(
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reason=reason,
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messages=[{"role": "developer", "content": reason}],
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result_callback=params.result_callback,
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)
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@app.websocket("/ws")
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async def websocket_endpoint(websocket: WebSocket):
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"""Handle a WebSocket connection from the main bot's proxy."""
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await websocket.accept()
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runner = PipelineRunner(handle_sigint=False)
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proxy = WebSocketProxyServerTask(
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"gateway",
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websocket=websocket,
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task_name="assistant",
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remote_task_name="acme",
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forward_messages=(BusFrameMessage,),
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)
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@proxy.event_handler("on_client_connected")
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async def on_client_connected(proxy, client):
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logger.info("WebSocket client connected")
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@proxy.event_handler("on_client_disconnected")
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async def on_client_disconnected(proxy, client):
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logger.info("WebSocket client disconnected")
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await runner.cancel()
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assistant = AcmeAssistant()
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await runner.spawn(proxy)
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logger.info("Assistant server ready, waiting for activation")
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await runner.run(assistant)
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logger.info("Assistant server session ended")
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Remote assistant LLM server")
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parser.add_argument("--host", default="0.0.0.0", help="Host to bind to")
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parser.add_argument("--port", type=int, default=8765, help="Port to listen on")
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args = parser.parse_args()
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uvicorn.run(app, host=args.host, port=args.port)
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169
examples/multi-task/remote-proxy-assistant/main.py
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169
examples/multi-task/remote-proxy-assistant/main.py
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#
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# Copyright (c) 2026, Daily
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#
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# SPDX-License-Identifier: BSD 2-Clause License
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#
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"""Main transport task with a WebSocket proxy to a remote LLM server.
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Handles audio I/O (STT, TTS) and bridges frames to the bus. A
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`WebSocketProxyClientTask` forwards bus messages to a remote LLM
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server (see ``assistant.py``) over WebSocket.
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Usage::
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python main.py --remote-url ws://localhost:8765/ws
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Requirements:
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- DEEPGRAM_API_KEY
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- CARTESIA_API_KEY
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"""
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import argparse
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import os
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from dotenv import load_dotenv
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from loguru import logger
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from pipecat.audio.vad.silero import SileroVADAnalyzer
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from pipecat.bus import BusBridgeProcessor, BusFrameMessage
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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 PipelineParams, PipelineTask
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from pipecat.processors.aggregators.llm_context import LLMContext
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from pipecat.processors.aggregators.llm_response_universal import (
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LLMContextAggregatorPair,
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LLMUserAggregatorParams,
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)
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from pipecat.registry.types import TaskReadyData
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from pipecat.runner.types import RunnerArguments
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from pipecat.runner.utils import create_transport
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from pipecat.services.cartesia.tts import CartesiaTTSService
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from pipecat.services.deepgram.stt import DeepgramSTTService
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from pipecat.tasks.llm import LLMTaskActivationArgs
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from pipecat.tasks.proxy.websocket import WebSocketProxyClientTask
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from pipecat.transports.base_transport import BaseTransport, TransportParams
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from pipecat.transports.daily.transport import DailyParams
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load_dotenv(override=True)
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MAIN_NAME = "acme"
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transport_params = {
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"daily": lambda: DailyParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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"webrtc": lambda: TransportParams(
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audio_in_enabled=True,
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audio_out_enabled=True,
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),
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}
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async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
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runner = PipelineRunner(handle_sigint=runner_args.handle_sigint)
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stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
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tts = CartesiaTTSService(
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api_key=os.environ["CARTESIA_API_KEY"],
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settings=CartesiaTTSService.Settings(
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voice="9626c31c-bec5-4cca-baa8-f8ba9e84c8bc", # Jacqueline
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),
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)
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context = LLMContext()
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aggregators = LLMContextAggregatorPair(
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context,
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user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
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)
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bridge = BusBridgeProcessor(
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bus=runner.bus,
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task_name=MAIN_NAME,
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name=f"{MAIN_NAME}::BusBridge",
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)
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pipeline = Pipeline(
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[
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transport.input(),
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stt,
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aggregators.user(),
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bridge,
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tts,
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transport.output(),
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aggregators.assistant(),
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]
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)
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task = PipelineTask(
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pipeline,
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name=MAIN_NAME,
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params=PipelineParams(
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enable_metrics=True,
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enable_usage_metrics=True,
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),
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idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
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)
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# Forward bus frame messages over the WebSocket so the remote
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# assistant sees user-side context and can ship back its replies.
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proxy = WebSocketProxyClientTask(
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"proxy",
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url=runner_args.cli_args.remote_url,
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local_task_name=MAIN_NAME,
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remote_task_name="assistant",
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forward_messages=(BusFrameMessage,),
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)
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await runner.spawn(proxy)
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async def on_assistant_ready(_data: TaskReadyData) -> None:
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logger.info("Remote assistant ready, activating")
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await task.activate_task(
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"assistant",
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args=LLMTaskActivationArgs(
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messages=[
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{
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"role": "developer",
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"content": (
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"Welcome the user to Acme Corp, mention the available "
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"products and ask how you can help."
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),
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},
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],
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),
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)
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await runner.registry.watch("assistant", on_assistant_ready)
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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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logger.info("Client connected, activating proxy")
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await task.activate_task("proxy")
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@transport.event_handler("on_client_disconnected")
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async def on_client_disconnected(transport, client):
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logger.info("Client disconnected")
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await task.cancel()
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await runner.run(task)
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async def bot(runner_args: RunnerArguments):
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"""Main bot entry point compatible with Pipecat Cloud."""
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transport = await create_transport(runner_args, transport_params)
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await run_bot(transport, runner_args)
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if __name__ == "__main__":
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from pipecat.runner.run import main
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parser = argparse.ArgumentParser(description="Main transport task with WebSocket proxy")
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parser.add_argument(
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"--remote-url",
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default="ws://localhost:8765/ws",
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help="WebSocket URL of the remote LLM server",
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)
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main(parser)
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