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

import asyncio
import os
import sys

import aiohttp
from dotenv import load_dotenv
from loguru import logger
from runner import configure

from pipecat.frames.frames import EndFrame, LLMMessagesFrame
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.processors.audio.audio_buffer_processor import AudioBufferProcessor
from pipecat.services.elevenlabs import ElevenLabsTTSService
from pipecat.services.openai import OpenAILLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport
from pipecat.vad.silero import SileroVADAnalyzer

load_dotenv(override=True)

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


async def main():
    async with aiohttp.ClientSession() as session:
        (room_url, token) = await configure(session)

        transport = DailyTransport(
            room_url,
            token,
            "Chatbot",
            DailyParams(
                audio_out_enabled=True,
                audio_in_enabled=True,
                camera_out_enabled=False,
                vad_enabled=True,
                vad_audio_passthrough=True,
                vad_analyzer=SileroVADAnalyzer(),
                transcription_enabled=True,
                #
                # Spanish
                #
                # transcription_settings=DailyTranscriptionSettings(
                #     language="es",
                #     tier="nova",
                #     model="2-general"
                # )
            ),
        )

        tts = ElevenLabsTTSService(
            api_key=os.getenv("ELEVENLABS_API_KEY"),
            #
            # English
            #
            voice_id="cgSgspJ2msm6clMCkdW9",
            aiohttp_session=session,
            #
            # Spanish
            #
            # model="eleven_multilingual_v2",
            # voice_id="gD1IexrzCvsXPHUuT0s3",
        )

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

        messages = [
            {
                "role": "system",
                #
                # English
                #
                "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 introducing yourself. Keep all your response to 12 words or fewer.",
                #
                # Spanish
                #
                # "content": "Eres Chatbot, un amigable y útil robot. Tu objetivo es demostrar tus capacidades de una manera breve. Tus respuestas se convertiran a audio así que nunca no debes incluir caracteres especiales. Contesta a lo que el usuario pregunte de una manera creativa, útil y breve. Empieza por presentarte a ti mismo.",
            },
        ]

        user_response = LLMUserResponseAggregator()
        assistant_response = LLMAssistantResponseAggregator()

        audiobuffer = AudioBufferProcessor()
        pipeline = Pipeline(
            [
                transport.input(),  # microphone
                user_response,
                llm,
                tts,
                transport.output(),
                audiobuffer,  # used to buffer the audio in the pipeline
                assistant_response,
            ]
        )

        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):
            print(f"Participant left: {participant}")
            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__":
    asyncio.run(main())