#
# Copyright (c) 2024-2026, Daily
#
# SPDX-License-Identifier: BSD 2-Clause License
#

import asyncio
import os

from dotenv import load_dotenv
from loguru import logger

from pipecat.audio.vad.silero import SileroVADAnalyzer
from pipecat.evals.transport import EvalTransportParams
from pipecat.frames.frames import LLMRunFrame, ManuallySwitchServiceFrame
from pipecat.pipeline.llm_switcher import LLMSwitcher
from pipecat.pipeline.pipeline import Pipeline
from pipecat.pipeline.service_switcher import ServiceSwitcher
from pipecat.pipeline.worker import PipelineParams, PipelineWorker, ProcessorUnusablePolicy
from pipecat.processors.aggregators.llm_context import LLMContext
from pipecat.processors.aggregators.llm_response_universal import (
    LLMContextAggregatorPair,
    LLMUserAggregatorParams,
)
from pipecat.runner.types import RunnerArguments
from pipecat.runner.utils import create_transport
from pipecat.services.cartesia.stt import CartesiaSTTService
from pipecat.services.cartesia.tts import CartesiaTTSService
from pipecat.services.deepgram.stt import DeepgramSTTService
from pipecat.services.deepgram.tts import DeepgramTTSService
from pipecat.services.google.llm import GoogleLLMService
from pipecat.services.llm_service import FunctionCallParams
from pipecat.services.openai.llm import OpenAILLMService
from pipecat.transports.base_transport import BaseTransport, TransportParams
from pipecat.transports.daily.transport import DailyParams
from pipecat.transports.websocket.fastapi import FastAPIWebsocketParams
from pipecat.workers.runner import WorkerRunner

load_dotenv(override=True)


async def get_current_weather(params: FunctionCallParams, location: str, format: str):
    """Get the current weather.

    Args:
        location: The city and state, e.g. "San Francisco, CA".
        format: The temperature unit to use. Must be either "celsius" or "fahrenheit". Infer this from the user's location.
    """
    await params.result_callback({"conditions": "nice", "temperature": "75"})


async def get_restaurant_recommendation(params: FunctionCallParams, location: str):
    """
    Get a restaurant recommendation.

    Args:
        location (str): The city and state, e.g. "San Francisco, CA".
    """
    await params.result_callback({"name": "The Golden Dragon"})


# We use lambdas to defer transport parameter creation until the transport
# type is selected at runtime.
transport_params = {
    "eval": lambda: EvalTransportParams(
        audio_in_enabled=True,
        audio_out_enabled=True,
    ),
    "daily": lambda: DailyParams(
        audio_in_enabled=True,
        audio_out_enabled=True,
    ),
    "twilio": lambda: FastAPIWebsocketParams(
        audio_in_enabled=True,
        audio_out_enabled=True,
    ),
    "webrtc": lambda: TransportParams(
        audio_in_enabled=True,
        audio_out_enabled=True,
    ),
}


async def run_bot(transport: BaseTransport, runner_args: RunnerArguments):
    logger.info("Starting bot")

    stt_cartesia = CartesiaSTTService(api_key=os.environ["CARTESIA_API_KEY"])
    stt_deepgram = DeepgramSTTService(api_key=os.environ["DEEPGRAM_API_KEY"])
    # Uses ServiceSwitcherStrategyManual by default
    stt_switcher = ServiceSwitcher(services=[stt_cartesia, stt_deepgram])

    tts_cartesia = CartesiaTTSService(
        api_key=os.environ["CARTESIA_API_KEY"],
        settings=CartesiaTTSService.Settings(
            voice="86e30c1d-714b-4074-a1f2-1cb6b552fb49",
        ),
    )
    tts_deepgram = DeepgramTTSService(
        api_key=os.environ["DEEPGRAM_API_KEY"],
        settings=DeepgramTTSService.Settings(
            voice="aura-2-helena-en",
        ),
    )
    # Uses ServiceSwitcherStrategyManual by default
    tts_switcher = ServiceSwitcher(services=[tts_cartesia, tts_deepgram])

    system_prompt = "You are a helpful assistant in a voice conversation. Your responses will be spoken aloud, so avoid emojis, bullet points, or other formatting that can't be spoken. Respond to what the user said in a creative, helpful, and brief way."

    llm_openai = OpenAILLMService(
        api_key=os.environ["OPENAI_API_KEY"],
        settings=OpenAILLMService.Settings(system_instruction=system_prompt),
    )
    llm_google = GoogleLLMService(
        api_key=os.environ["GOOGLE_API_KEY"],
        settings=GoogleLLMService.Settings(system_instruction=system_prompt),
    )
    # Uses ServiceSwitcherStrategyManual by default
    llm_switcher = LLMSwitcher(llms=[llm_openai, llm_google])

    # Direct functions listed in the context are registered automatically on
    # every member LLM (active or not), so the tools keep working across
    # service switches.
    context = LLMContext(tools=[get_current_weather, get_restaurant_recommendation])
    user_aggregator, assistant_aggregator = LLMContextAggregatorPair(
        context,
        user_params=LLMUserAggregatorParams(vad_analyzer=SileroVADAnalyzer()),
    )

    pipeline = Pipeline(
        [
            transport.input(),  # Transport user input
            stt_switcher,
            user_aggregator,  # User responses
            llm_switcher,  # LLM
            tts_switcher,  # TTS
            transport.output(),  # Transport bot output
            assistant_aggregator,  # Assistant spoken responses
        ]
    )

    worker = PipelineWorker(
        pipeline,
        params=PipelineParams(
            enable_metrics=True,
            enable_usage_metrics=True,
        ),
        idle_timeout_secs=runner_args.pipeline_idle_timeout_secs,
        processor_unusable_policy=ProcessorUnusablePolicy.END,
    )

    runner = WorkerRunner(handle_sigint=runner_args.handle_sigint)

    await runner.add_workers(worker)

    @transport.event_handler("on_client_connected")
    async def on_client_connected(transport, client):
        logger.info("Client connected")
        # Kick off the conversation.
        context.add_message(
            {"role": "developer", "content": "Please introduce yourself to the user."}
        )
        await worker.queue_frames([LLMRunFrame()])
        await asyncio.sleep(15)
        print(f"Switching to {stt_deepgram}")
        await worker.queue_frames([ManuallySwitchServiceFrame(service=stt_deepgram)])
        await asyncio.sleep(15)
        print(f"Switching to {llm_google}")
        await worker.queue_frames([ManuallySwitchServiceFrame(service=llm_google)])
        await asyncio.sleep(15)
        print(f"Switching to {tts_deepgram}")
        await worker.queue_frames([ManuallySwitchServiceFrame(service=tts_deepgram)])

    @transport.event_handler("on_client_disconnected")
    async def on_client_disconnected(transport, client):
        logger.info("Client disconnected")
        await runner.cancel()

    await runner.run()


async def bot(runner_args: RunnerArguments):
    """Main bot entry point compatible with Pipecat Cloud."""
    transport = await create_transport(runner_args, transport_params)
    await run_bot(transport, runner_args)


if __name__ == "__main__":
    from pipecat.runner.run import main

    main()