#
# Copyright (c) 2024–2025, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#

import asyncio
import os
import sys

from dotenv import load_dotenv
from loguru import logger

from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport

load_dotenv(override=True)

logger.remove(0)
logger.add(sys.stderr, level="DEBUG")


async def main(room_url: str, token: str):
    transport = DailyTransport(
        room_url,
        token,
        "bot",
        DailyParams(
            audio_out_enabled=True,
            transcription_enabled=True,
            vad_enabled=True,
            vad_analyzer=SileroVADAnalyzer(),
        ),
    )

    tts = CartesiaTTSService(
        api_key=os.getenv("CARTESIA_API_KEY", ""), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121"
    )

    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"))

    messages = [
        {
            "role": "system",
            "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
        },
    ]

    context = OpenAILLMContext(messages)
    context_aggregator = llm.create_context_aggregator(context)

    pipeline = Pipeline(
        [
            transport.input(),
            context_aggregator.user(),
            llm,
            tts,
            transport.output(),
            context_aggregator.assistant(),
        ]
    )

    task = PipelineTask(
        pipeline,
        params=PipelineParams(
            allow_interruptions=True,
            enable_metrics=True,
            enable_usage_metrics=True,
            report_only_initial_ttfb=True,
        ),
    )

    @transport.event_handler("on_first_participant_joined")
    async def on_first_participant_joined(transport, participant):
        await transport.capture_participant_transcription(participant["id"])
        messages.append({"role": "system", "content": "Please introduce yourself to the user."})
        await task.queue_frames([context_aggregator.user().get_context_frame()])

    @transport.event_handler("on_participant_left")
    async def on_participant_left(transport, participant, reason):
        await task.cancel()

    runner = PipelineRunner()

    await runner.run(task)


def _voice_bot_process(room_url: str, token: str):
    asyncio.run(main(room_url, token))