Add distributed-handoff examples (redis and pgmq)
Two transports of the same shape: a main task that hosts the
voice pipeline plus a network-backed `TaskBus` (`RedisBus` or
`PgmqBus`), and a standalone `llm.py` worker process for the
greeter / support LLM. Workers connect to the same bus channel,
register on the shared `TaskRegistry`, and the main task waits
on `runner.registry.watch("greeter", ...)` before sending the
welcome activation so it doesn't fire before the worker is up.
This commit is contained in:
Aleix Conchillo Flaqué
183
examples/multi-task/distributed-handoff/pgmq-handoff/llm.py
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183
examples/multi-task/distributed-handoff/pgmq-handoff/llm.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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"""LLM worker task — run on Machine B (or locally alongside ``main.py``).
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A standalone process that runs one LLM task (greeter or support)
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attached to the same PGMQ-backed `TaskBus` as the main task.
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Multiple instances can run on different machines as long as they
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share a Postgres database with the PGMQ extension enabled.
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Usage::
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python llm.py greeter --database-url postgresql://...
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python llm.py support --database-url postgresql://...
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Requirements:
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- OPENAI_API_KEY
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- DATABASE_URL (or ``--database-url``)
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"""
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import argparse
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import asyncio
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import os
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from urllib.parse import unquote, urlparse
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from dotenv import load_dotenv
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from loguru import logger
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from pgmq.async_queue import PGMQueue
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from pipecat.bus.network.pgmq import PgmqBus
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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, LLMTaskActivationArgs, tool
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load_dotenv(override=True)
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WORKER_CONFIG = {
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"greeter": {
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"system_instruction": (
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"You are a friendly greeter for Acme Corp. The available products "
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"are: the Acme Rocket Boots, the Acme Invisible Paint, and the Acme "
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"Tornado Kit. Ask which one they'd like to learn more about. "
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"When the user picks a product or asks a question about one, "
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"immediately call the transfer_to_agent tool with agent 'support'. "
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"Do not answer product questions yourself. If the user says goodbye, "
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"call the end_conversation tool. Do not mention transferring — just do it "
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"seamlessly. Keep responses brief — this is a voice conversation."
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),
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"watch": ["support"],
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},
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"support": {
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"system_instruction": (
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"You are a support agent for Acme Corp. You know about three "
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"products: Acme Rocket Boots (jet-powered boots, $299, run up "
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"to 60 mph), Acme Invisible Paint (makes anything invisible for "
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"24 hours, $49 per can), and Acme Tornado Kit (portable tornado "
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"generator, $199, batteries included). Answer the user's questions "
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"about these products. If the user wants to browse other products "
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"or start over, call the transfer_to_agent tool with agent "
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"'greeter'. If the user says goodbye, call the end_conversation "
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"tool. Do not mention transferring — just do it seamlessly. "
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"Keep responses brief — this is a voice conversation."
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),
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"watch": ["greeter"],
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},
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}
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def pgmq_from_url(database_url: str, *, pool_size: int = 4) -> PGMQueue:
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"""Build a `PGMQueue` from a Postgres DSN string."""
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parsed = urlparse(database_url)
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if parsed.scheme not in ("postgres", "postgresql"):
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raise ValueError(f"Unsupported scheme '{parsed.scheme}' for database URL")
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return PGMQueue(
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host=parsed.hostname or "localhost",
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port=str(parsed.port or 5432),
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database=(parsed.path or "/postgres").lstrip("/") or "postgres",
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username=unquote(parsed.username or "postgres"),
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password=unquote(parsed.password or ""),
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pool_size=pool_size,
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)
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class AcmeLLMTask(LLMTask):
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"""LLM task for Acme Corp with transfer and end tools."""
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def __init__(self, name: str, *, system_instruction: str, watch: list[str]):
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"""Initialize the AcmeLLMTask.
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Args:
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name: Unique task name (``"greeter"`` or ``"support"``).
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system_instruction: System prompt for this LLM role.
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watch: Sibling task names this task will watch via the
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registry so it knows when they become available for
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handoff.
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"""
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llm = OpenAILLMService(
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name=f"{name}::OpenAILLMService",
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api_key=os.environ["OPENAI_API_KEY"],
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settings=OpenAILLMService.Settings(system_instruction=system_instruction),
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)
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super().__init__(name, llm=llm, bridged=())
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self._watch = watch
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async def start(self) -> None:
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"""Register watches for sibling tasks once ready."""
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await super().start()
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for task_name in self._watch:
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await self.watch_task(task_name)
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@tool(cancel_on_interruption=False)
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async def transfer_to_agent(self, params: FunctionCallParams, agent: str, reason: str):
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"""Transfer the user to another agent.
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Args:
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agent (str): The agent to transfer to (e.g. 'greeter', 'support').
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reason (str): Why the user is being transferred.
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"""
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logger.info(f"Task '{self.name}': transferring to '{agent}' ({reason})")
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await self.handoff_to(
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agent,
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activation_args=LLMTaskActivationArgs(
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messages=[{"role": "developer", "content": reason}]
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),
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result_callback=params.result_callback,
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)
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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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async def main_async() -> None:
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parser = argparse.ArgumentParser(description="LLM worker task (greeter or support)")
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parser.add_argument("worker", choices=list(WORKER_CONFIG), help="Which worker to run")
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parser.add_argument(
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"--database-url",
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default=os.getenv("DATABASE_URL"),
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help="PostgreSQL DSN (or set DATABASE_URL env var)",
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)
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parser.add_argument(
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"--channel",
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default=os.getenv("PGMQ_CHANNEL", "pipecat_acme"),
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help="PGMQ channel prefix",
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)
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args = parser.parse_args()
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if not args.database_url:
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parser.error("--database-url is required (or set DATABASE_URL env var)")
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pgmq = pgmq_from_url(args.database_url)
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await pgmq.init()
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bus = PgmqBus(pgmq=pgmq, channel=args.channel)
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config = WORKER_CONFIG[args.worker]
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worker = AcmeLLMTask(
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args.worker,
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system_instruction=config["system_instruction"],
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watch=config["watch"],
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)
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runner = PipelineRunner(bus=bus, handle_sigint=True)
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logger.info(f"Starting {args.worker} worker, waiting for activation...")
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await runner.run(worker)
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if __name__ == "__main__":
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asyncio.run(main_async())
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