import ray
from ray.util.queue import Queue
from dotenv import load_dotenv
from local_speaker_service import LocalSpeakerService
from text_to_speech_service import TextToSpeechService
from chat_service import ChatService
import asyncio
# from ray.actor import ActorHandle
from ffmpeg_converter_actor import FFMpegConverterActor
from agent_response import AgentResponse


@ray.remote
class PromptToLLMActor:
    def __init__(self, input_queue:Queue, output_queue:Queue):
        load_dotenv()
        self.input_queue = input_queue
        self.output_queue = output_queue
        self.chat_service = ChatService()
        self.cancel_event = None

    async def run(self):
        while True:
            prompt = await self.input_queue.get_async()
            self.cancel_event = asyncio.Event()
            agent_response = AgentResponse(prompt)
            async for sentence_response in self.chat_service.get_responses_as_sentances_async(agent_response, self.cancel_event):
                if self.chat_service.ignore_sentence(sentence_response['llm_sentence']):
                    continue
                print(f"{sentence_response['llm_sentence']} id: {agent_response['llm_sentence_id']} from prompt: {agent_response['prompt']}")
                sentence_response = sentence_response.make_copy()
                await self.output_queue.put_async(sentence_response)
                
    async def cancel(self):
        if self.cancel_event:
            self.cancel_event.set()
        while not self.input_queue.empty():
            await self.input_queue.get_async()
        while not self.output_queue.empty():
            await self.output_queue.get_async()

@ray.remote
class LLMSentanceToSpeechActor:
    def __init__(self, input_queue, output_queue, voice_id):
        load_dotenv()
        self.input_queue = input_queue
        self.output_queue = output_queue
        self.tts_service = TextToSpeechService(voice_id=voice_id)
        self.cancel_event = None

    async def run(self):
        while True:
            sentence_response = await self.input_queue.get_async()
            self.cancel_event = asyncio.Event()
            async for chunk_response in self.tts_service.get_speech_chunks_async(sentence_response, self.cancel_event):
                chunk_response = chunk_response.make_copy()
                await self.output_queue.put_async(chunk_response)

    async def cancel(self):
        if self.cancel_event:
            self.cancel_event.set()
        while not self.input_queue.empty():
            await self.input_queue.get_async()
        while not self.output_queue.empty():
            await self.output_queue.get_async()


# legacy code for playing from local speaker
# @ray.remote
# class SpeechToSpeakerActor:
#     def __init__(self, input_queue, voice_id):
#         load_dotenv()
#         self.input_queue = input_queue
#         self.speaker_service = LocalSpeakerService()

#     async def run(self):
#         while True:
#             audio_chunk = await self.input_queue.get_async()
#             # print (f"Got audio chunk {len(audio_chunk)}")
#             self.speaker_service.add_audio_stream([audio_chunk])
            
#     async def cancel(self):
#         while not self.input_queue.empty():
#             await self.input_queue.get_async()            

@ray.remote
class SpeechToConverterActor:
    def __init__(self, input_queue:Queue, ffmpeg_converter_actor:FFMpegConverterActor):
        load_dotenv()
        self.input_queue = input_queue
        self.ffmpeg_converter_actor = ffmpeg_converter_actor

    async def run(self):
        await self.ffmpeg_converter_actor.start_process.remote()
        self.ffmpeg_converter_actor.run.remote()
        while True:
            chunk_response = await self.input_queue.get_async()
            audio_chunk = chunk_response['tts_raw_chunk']
            await self.ffmpeg_converter_actor.push_chunk.remote(audio_chunk)
            
    async def cancel(self):
        while not self.input_queue.empty():
            await self.input_queue.get_async()


@ray.remote
class RespondToPromptActor:
    def __init__(self, out_audio_queue):
        voice_id="2OviOUQc1JsQRQgNkVBj"
        self.prompt_queue = Queue(maxsize=100)
        self.llm_sentence_queue = Queue(maxsize=100)
        self.speech_chunk_queue = Queue(maxsize=100)

        self.ffmpeg_converter_actor = FFMpegConverterActor.remote(out_audio_queue)
        
        self.prompt_to_llm = PromptToLLMActor.remote(self.prompt_queue, self.llm_sentence_queue)
        self.llm_sentence_to_speech = LLMSentanceToSpeechActor.remote(self.llm_sentence_queue, self.speech_chunk_queue, voice_id)
        # self.speech_output = SpeechToSpeakerActor.remote(self.speech_chunk_queue, voice_id)
        self.speech_output = SpeechToConverterActor.remote(self.speech_chunk_queue, self.ffmpeg_converter_actor)

        # Start the pipeline components.
        self.prompt_to_llm.run.remote()
        self.llm_sentence_to_speech.run.remote()
        self.speech_output.run.remote()
            
    async def enqueue_prompt(self, prompt):
        print("flush anything queued")
        prompt_to_llm_future = self.prompt_to_llm.cancel.remote()
        llm_sentence_to_speech_future = self.llm_sentence_to_speech.cancel.remote()
        speech_output_future = self.speech_output.cancel.remote()
        ffmpeg_converter_future = self.ffmpeg_converter_actor.flush_output_queue.remote()
        await asyncio.gather(
            prompt_to_llm_future,
            llm_sentence_to_speech_future,
            speech_output_future,
            ffmpeg_converter_future,
        )
        await self.prompt_queue.put_async(prompt)
        print("Enqueued prompt")