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

import argparse
import os

from dotenv import load_dotenv
from loguru import logger

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.cartesia.tts import CartesiaTTSService
from pipecat.services.gemini_multimodal_live.gemini import (
    GeminiMultimodalLiveLLMService,
    GeminiMultimodalModalities,
    InputParams,
)
from pipecat.transports.base_transport import TransportParams
from pipecat.transports.network.small_webrtc import SmallWebRTCTransport
from pipecat.transports.network.webrtc_connection import SmallWebRTCConnection

load_dotenv(override=True)


SYSTEM_INSTRUCTION = f"""
"You are Gemini 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. Keep your responses brief. One or two sentences at most.
"""


async def run_bot(webrtc_connection: SmallWebRTCConnection, _: argparse.Namespace):
    logger.info(f"Starting bot")

    # Initialize the SmallWebRTCTransport with the connection
    transport = SmallWebRTCTransport(
        webrtc_connection=webrtc_connection,
        params=TransportParams(
            audio_in_enabled=True,
            audio_out_enabled=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"),
        transcribe_user_audio=True,
        system_instruction=SYSTEM_INSTRUCTION,
        tools=[{"google_search": {}}, {"code_execution": {}}],
        params=InputParams(modalities=GeminiMultimodalModalities.TEXT),
    )

    # Optionally, you can set the response modalities via a function
    # llm.set_model_modalities(
    #     GeminiMultimodalModalities.TEXT
    # )

    tts = CartesiaTTSService(
        api_key=os.getenv("CARTESIA_API_KEY"), voice_id="71a7ad14-091c-4e8e-a314-022ece01c121"
    )

    messages = [
        {
            "role": "user",
            "content": 'Start by saying "Hello, I\'m Gemini".',
        },
    ]

    # Set up conversation context and management
    # The context_aggregator will automatically collect conversation context
    context = OpenAILLMContext(messages)
    context_aggregator = llm.create_context_aggregator(context)

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

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

    @transport.event_handler("on_client_connected")
    async def on_client_connected(transport, client):
        logger.info(f"Client connected")
        # Kick off the conversation.
        await task.queue_frames([context_aggregator.user().get_context_frame()])

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

    @transport.event_handler("on_client_closed")
    async def on_client_closed(transport, client):
        logger.info(f"Client closed connection")
        await task.cancel()

    runner = PipelineRunner(handle_sigint=False)

    await runner.run(task)


if __name__ == "__main__":
    from run import main

    main()