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

import asyncio
import os
import sys
from datetime import datetime

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

from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.audio.vad.vad_analyzer import VADParams
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.gemini_multimodal_live.gemini import GeminiMultimodalLiveLLMService
from pipecat.transports.services.daily import DailyParams, DailyTransport

load_dotenv(override=True)

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


async def fetch_weather_from_api(function_name, tool_call_id, args, llm, context, result_callback):
    temperature = 75 if args["format"] == "fahrenheit" else 24
    await result_callback(
        {
            "conditions": "nice",
            "temperature": temperature,
            "format": args["format"],
            "timestamp": datetime.now().strftime("%Y%m%d_%H%M%S"),
        }
    )


tools = [
    {
        "function_declarations": [
            {
                "name": "get_current_weather",
                "description": "Get the current weather",
                "parameters": {
                    "type": "object",
                    "properties": {
                        "location": {
                            "type": "string",
                            "description": "The city and state, e.g. San Francisco, CA",
                        },
                        "format": {
                            "type": "string",
                            "enum": ["celsius", "fahrenheit"],
                            "description": "The temperature unit to use. Infer this from the users location.",
                        },
                    },
                    "required": ["location", "format"],
                },
            },
        ]
    }
]

system_instruction = """
You are a helpful assistant who can answer questions and use tools.

You have a tool called "get_current_weather" that can be used to get the current weather. If the user asks
for the weather, call this function.
"""


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

        transport = DailyTransport(
            room_url,
            token,
            "Respond bot",
            DailyParams(
                audio_in_sample_rate=16000,
                audio_out_sample_rate=24000,
                audio_out_enabled=True,
                vad_enabled=True,
                vad_audio_passthrough=True,
                # set stop_secs to something roughly similar to the internal setting
                # of the Multimodal Live api, just to align events. This doesn't really
                # matter because we can only use the Multimodal Live API's phrase
                # endpointing, for now.
                vad_analyzer=SileroVADAnalyzer(params=VADParams(stop_secs=0.5)),
            ),
        )

        llm = GeminiMultimodalLiveLLMService(
            api_key=os.getenv("GOOGLE_API_KEY"),
            system_instruction=system_instruction,
            tools=tools,
        )

        llm.register_function("get_current_weather", fetch_weather_from_api)

        context = OpenAILLMContext(
            [{"role": "user", "content": "Say hello."}],
        )
        context_aggregator = llm.create_context_aggregator(context)

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

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

        @transport.event_handler("on_first_participant_joined")
        async def on_first_participant_joined(transport, participant):
            await task.queue_frames([context_aggregator.user().get_context_frame()])

        runner = PipelineRunner()

        await runner.run(task)


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