import discord
import logging
import os
from huggingface_hub import InferenceClient
import asyncio
import subprocess
from datasets import load_dataset

# 로깅 설정
logging.basicConfig(level=logging.DEBUG, format='%(asctime)s:%(levelname)s:%(name)s: %(message)s', handlers=[logging.StreamHandler()])

# 인텐트 설정
intents = discord.Intents.default()
intents.message_content = True
intents.messages = True
intents.guilds = True
intents.guild_messages = True

# 데이터셋 로드
data_files = ['train_0.csv', 'train_1.csv', 'train_2.csv', 'train_3.csv', 'train_4.csv', 'train_5.csv']
law_dataset = load_dataset('csv', data_files=data_files)

# 추론 API 클라이언트 설정
hf_client = InferenceClient("CohereForAI/c4ai-command-r-plus", token=os.getenv("HF_TOKEN"))

# 특정 채널 ID
SPECIFIC_CHANNEL_ID = int(os.getenv("DISCORD_CHANNEL_ID"))

# 대화 히스토리를 저장할 전역 변수
conversation_history = []

class MyClient(discord.Client):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.is_processing = False

    async def on_ready(self):
        logging.info(f'{self.user}로 로그인되었습니다!')
        subprocess.Popen(["python", "web.py"])
        logging.info("Web.py server has been started.")

    async def on_message(self, message):
        if message.author == self.user:
            return
        if not self.is_message_in_specific_channel(message):
            return
        if self.is_processing:
            return
        self.is_processing = True
        try:
            response = await self.generate_response(message)
            await message.channel.send(response)
        finally:
            self.is_processing = False

    def is_message_in_specific_channel(self, message):
        return message.channel.id == SPECIFIC_CHANNEL_ID or (
            isinstance(message.channel, discord.Thread) and message.channel.parent_id == SPECIFIC_CHANNEL_ID
        )

    async def generate_response(self, message):
        global conversation_history
        user_input = message.content
        user_mention = message.author.mention
        system_message = f"{user_mention}, DISCORD에서 사용자들의 질문에 답하는 어시스턴트입니다."
        answer = self.search_in_dataset(user_input, law_dataset)
        full_response_text = system_message + "\n\n" + answer

        if not full_response_text.strip():
            full_response_text = "죄송합니다, 정보를 제공할 수 없습니다."

        max_length = 2000
        if len(full_response_text) > max_length:
            for i in range(0, len(full_response_text), max_length):
                part_response = full_response_text[i:i+max_length]
                await message.channel.send(part_response)
        else:
            await message.channel.send(full_response_text)

        logging.debug(f'Full model response sent: {full_response_text}')
        conversation_history.append({"role": "assistant", "content": full_response_text})

    def search_in_dataset(self, query, dataset):
    # 사용자의 쿼리와 관련된 사건명을 찾아 사건번호를 반환합니다.
        response = []
        for record in dataset['train']:
        # 사건명 필드가 None이 아닐 때만 검사를 수행
            if record['사건명'] and query in record['사건명']:
                detail = f"사건번호: {record['사건번호']}"
                response.append(detail)

        return "\n".join(response) if response else "관련 법률 정보를 찾을 수 없습니다."
 

if __name__ == "__main__":
    discord_client = MyClient(intents=intents)
    discord_client.run(os.getenv('DISCORD_TOKEN'))