import asyncio
import os
import sys

import aiohttp
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.services.openrouter import OpenRouterLLMService
from pipecat.services.azure import AzureTTSService
from pipecat.transports.services.daily import DailyParams, DailyTransport

load_dotenv(override=True)

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


async def get_weather(function_name, tool_call_id, arguments, llm, context, result_callback):
    location = arguments["location"]
    await result_callback(f"The weather in {location} is currently 72 degrees and sunny.")


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

        transport = DailyTransport(
            room_url,
            token,
            "Respond bot",
            DailyParams(
                audio_out_enabled=True,
                transcription_enabled=True,
                vad_enabled=True,
                vad_analyzer=SileroVADAnalyzer(),
            ),
        )

        tts = AzureTTSService(
            api_key=os.getenv("AZURE_API_KEY"),
            region="eastus",
            voice="en-US-JennyNeural",
            params=AzureTTSService.InputParams(language="en-US", rate="1.1", style="cheerful"),
        )

        llm = OpenRouterLLMService(
            api_key=os.getenv("OPENROUTER_API_KEY"), model="openai/chatgpt-4o-latest"
        )
        llm.register_function("get_weather", get_weather)

        tools = [
            {
                "name": "get_weather",
                "description": "Get the current weather in a given location",
                "input_schema": {
                    "type": "object",
                    "properties": {
                        "location": {
                            "type": "string",
                            "description": "The city and state, e.g. San Francisco, CA",
                        }
                    },
                    "required": ["location"],
                },
            }
        ]

        messages = [
            {
                "role": "system",
                "content": "You are a helpful assistant and whenever you asked about weather trigger get_weather function.",
            },
            {"role": "user", "content": "Say 'hello' to start the conversation."},
        ]

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

        pipeline = Pipeline(
            [
                transport.input(),  # Transport user input
                context_aggregator.user(),  # User spoken responses
                llm,  # LLM
                tts,  # TTS
                transport.output(),  # Transport bot output
                context_aggregator.assistant(),  # Assistant spoken responses and tool context
            ]
        )

        task = PipelineTask(pipeline, 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"])
            # Kick off the conversation.
            await task.queue_frames([context_aggregator.user().get_context_frame()])

        runner = PipelineRunner()

        await runner.run(task)


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