import asyncio
import os
import sys
import argparse

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.frames.frames import LLMMessagesFrame, EndFrame
from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
from pipecat.services.openai import OpenAILLMService
from pipecat.services.elevenlabs import ElevenLabsTTSService
from pipecat.transports.services.daily import DailyParams, DailyTransport

from loguru import logger

from dotenv import load_dotenv

load_dotenv(override=True)

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

daily_api_key = os.getenv("DAILY_API_KEY", "")
daily_api_url = os.getenv("DAILY_API_URL", "https://api.daily.co/v1")


async def main(room_url: str, token: str):
    transport = DailyTransport(
        room_url,
        token,
        "Chatbot",
        DailyParams(
            api_url=daily_api_url,
            api_key=daily_api_key,
            audio_in_enabled=True,
            audio_out_enabled=True,
            camera_out_enabled=False,
            vad_enabled=True,
            vad_analyzer=SileroVADAnalyzer(),
            transcription_enabled=True,
        ),
    )

    tts = ElevenLabsTTSService(
        api_key=os.getenv("ELEVENLABS_API_KEY", ""),
        voice_id=os.getenv("ELEVENLABS_VOICE_ID", ""),
    )

    llm = OpenAILLMService(api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o")

    messages = [
        {
            "role": "system",
            "content": "You are Chatbot, a friendly, helpful robot. Your output will be converted to audio so don't include special characters other than '!' or '?' in your answers. Respond to what the user said in a creative and helpful way, but keep your responses brief. Start by saying hello.",
        },
    ]

    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, PipelineParams(allow_interruptions=True))

    @transport.event_handler("on_first_participant_joined")
    async def on_first_participant_joined(transport, participant):
        await transport.capture_participant_transcription(participant["id"])
        await task.queue_frames([LLMMessagesFrame(messages)])

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

    @transport.event_handler("on_call_state_updated")
    async def on_call_state_updated(transport, state):
        if state == "left":
            await task.queue_frame(EndFrame())

    runner = PipelineRunner()

    await runner.run(task)


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Pipecat Bot")
    parser.add_argument("-u", type=str, help="Room URL")
    parser.add_argument("-t", type=str, help="Token")
    config = parser.parse_args()

    asyncio.run(main(config.u, config.t))