#
# Copyright (c) 2026, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#

"""Main transport task — run on Machine A.

Handles audio I/O (STT, TTS) and bridges frames to the bus. The LLM
worker tasks run as separate processes (possibly on different
machines) and connect to the same Redis-backed `TaskBus`.

Usage::

    python main.py --redis-url redis://localhost:6379

Requirements:

- DEEPGRAM_API_KEY
- CARTESIA_API_KEY
"""

import argparse
import os

from dotenv import load_dotenv
from loguru import logger
from redis.asyncio import Redis

from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.bus import BusBridgeProcessor
from pipecat.bus.network.redis import RedisBus
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
    LLMContextAggregatorPair,
    LLMUserAggregatorParams,
)
from pipecat.registry.types import TaskReadyData
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.tasks.llm import LLMTaskActivationArgs
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams

load_dotenv(override=True)

MAIN_NAME = "acme"

transport_params = {
    "daily": lambda: DailyParams(
        audio_in_enabled=True,
        audio_out_enabled=True,
    ),
    "webrtc": lambda: TransportParams(
        audio_in_enabled=True,
        audio_out_enabled=True,
    ),
}


async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
    redis = Redis.from_url(runner_args.cli_args.redis_url)
    bus = RedisBus(redis=redis, channel=runner_args.cli_args.channel)
    runner = PipelineRunner(bus=bus, handle_sigint=runner_args.handle_sigint)

    stt = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
    tts = CartesiaTTSService(
        api_key=os.environ["CARTESIA_API_KEY"],
        settings=CartesiaTTSService.Settings(
            voice="9626c31c-bec5-4cca-baa8-f8ba9e84c8bc",  # Jacqueline
        ),
    )

    context = LLMContext()
    aggregators = LLMContextAggregatorPair(
        context,
        user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
    )

    bridge = BusBridgeProcessor(
        bus=runner.bus,
        task_name=MAIN_NAME,
        name=f"{MAIN_NAME}::BusBridge",
    )

    pipeline = Pipeline(
        [
            transport.input(),
            stt,
            aggregators.user(),
            bridge,
            tts,
            transport.output(),
            aggregators.assistant(),
        ]
    )

    task = PipelineTask(
        pipeline,
        name=MAIN_NAME,
        params=PipelineParams(
            enable_metrics=True,
            enable_usage_metrics=True,
        ),
        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
    )

    # The remote LLM workers may take a moment to register on the bus.
    # We only activate ``greeter`` once *both* the client is connected
    # and the worker has been observed via the registry.
    state = {"client_connected": False, "greeter_ready": False}

    async def maybe_activate():
        if not (state["client_connected"] and state["greeter_ready"]):
            return
        await task.activate_task(
            "greeter",
            args=LLMTaskActivationArgs(
                messages=[
                    {
                        "role": "developer",
                        "content": (
                            "Welcome the user to Acme Corp, mention the available "
                            "products and ask how you can help."
                        ),
                    },
                ],
            ),
        )

    async def on_greeter_ready(_data: TaskReadyData) -> None:
        state["greeter_ready"] = True
        await maybe_activate()

    await runner.registry.watch("greeter", on_greeter_ready)

    @transport.event_handler("on_client_connected")
    async def on_client_connected(transport, client):
        logger.info("Client connected")
        state["client_connected"] = True
        await maybe_activate()

    @transport.event_handler("on_client_disconnected")
    async def on_client_disconnected(transport, client):
        logger.info("Client disconnected")
        await task.cancel()

    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

    parser = argparse.ArgumentParser(description="Main transport task (Redis bus)")
    parser.add_argument("--redis-url", default="redis://localhost:6379", help="Redis URL")
    parser.add_argument("--channel", default="pipecat:acme", help="Redis pub/sub channel")

    main(parser)