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

import asyncio
import os
import sys

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

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.processors.metrics.sentry import SentryMetrics
from pipecat.services.elevenlabs.tts import ElevenLabsTTSService
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():
    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,
                video_out_enabled=False,
                vad_analyzer=SileroVADAnalyzer(),
                transcription_enabled=True,
            ),
        )

        # Initialize Sentry
        sentry_sdk.init(
            dsn="your-project-dsn",
            traces_sample_rate=1.0,
        )

        tts = ElevenLabsTTSService(
            api_key=os.getenv("ELEVENLABS_API_KEY"),
            voice_id="cgSgspJ2msm6clMCkdW9",
            metrics=SentryMetrics(),
        )

        llm = OpenAILLMService(
            api_key=os.getenv("OPENAI_API_KEY"),
            metrics=SentryMetrics(),
        )

        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 introducing yourself.",
            },
        ]

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

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

        task = PipelineTask(
            pipeline,
            params=PipelineParams(allow_interruptions=True, enable_metrics=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([context_aggregator.user().get_context_frame()])

        @transport.event_handler("on_participant_left")
        async def on_participant_left(transport, participant, reason):
            print(f"Participant left: {participant}")
            await task.cancel()

        runner = PipelineRunner()

        await runner.run(task)


if __name__ == "__main__":
    asyncio.run(main())