import asyncio
import aiohttp
import os
import sys
import argparse

from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.runner import PipelineRunner
from pipecat.pipeline.task import PipelineParams, PipelineTask
from pipecat.processors.aggregators.llm_response import LLMAssistantResponseAggregator, LLMUserResponseAggregator
from pipecat.frames.frames import (
    LLMMessagesFrame,
    EndFrame
)
from pipecat.services.elevenlabs import ElevenLabsTTSService
from pipecat.services.openai import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport, DailyDialinSettings
from pipecat.vad.silero import SileroVADAnalyzer
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, callId: str, callDomain: str):
    async with aiohttp.ClientSession() as session:
        # diallin_settings are only needed if Daily's SIP URI is used
        # If you are handling this via Twilio, Telnyx, set this to None
        # and handle call-forwarding when on_dialin_ready fires.
        diallin_settings = DailyDialinSettings(
            call_id=callId,
            call_domain=callDomain
        )

        transport = DailyTransport(
            room_url,
            token,
            "Chatbot",
            DailyParams(
                api_url=daily_api_url,
                api_key=daily_api_key,
                dialin_settings=diallin_settings,
                audio_in_enabled=True,
                audio_out_enabled=True,
                camera_out_enabled=False,
                vad_enabled=True,
                vad_analyzer=SileroVADAnalyzer(),
                transcription_enabled=True,
            )
        )

        tts = ElevenLabsTTSService(
            aiohttp_session=session,
            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 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, but keep your responses brief. Start by saying 'Oh, hello! Who dares dial me at this hour?!'.",
            },
        ]

        tma_in = LLMUserResponseAggregator(messages)
        tma_out = LLMAssistantResponseAggregator(messages)

        pipeline = Pipeline([
            transport.input(),
            tma_in,
            llm,
            tts,
            transport.output(),
            tma_out,
        ])

        task = PipelineTask(pipeline, PipelineParams(allow_interruptions=True))

        @transport.event_handler("on_first_participant_joined")
        async def on_first_participant_joined(transport, participant):
            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())

        runner = PipelineRunner()

        await runner.run(task)


if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Pipecat Simple ChatBot")
    parser.add_argument("-u", type=str, help="Room URL")
    parser.add_argument("-t", type=str, help="Token")
    parser.add_argument("-i", type=str, help="Call ID")
    parser.add_argument("-d", type=str, help="Call Domain")
    config = parser.parse_args()

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