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

# 현재 작업 디렉토리 출력
print("Current Working Directory:", os.getcwd())

# 데이터셋 파일 이름
data_files = ['train_0.csv', 'train_1.csv', 'train_2.csv', 'train_3.csv', 'train_4.csv', 'train_5.csv']

# 현재 작업 디렉토리에 모든 파일이 있는지 확인
missing_files = [file for file in data_files if not os.path.exists(file)]
if missing_files:
    print(f"Missing files: {missing_files}")
    # 필요한 경우 작업 디렉토리 변경
    os.chdir('/home/user/app')
    print("Changed directory to:", os.getcwd())
else:
    print("All files are present in the current directory.")

# 데이터셋 로드
law_dataset = load_dataset('csv', data_files=data_files)
print("Dataset loaded successfully.")

# 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

# 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 generate_response(message)
            if response.strip() == "":
                response = "죄송합니다, 제공할 수 있는 정보가 없습니다."
            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(message):
    global conversation_history
    user_input = message.content
    user_mention = message.author.mention
    system_message = f"{user_mention}, DISCORD에서 사용자들의 질문에 답하는 어시스턴트입니다."
    
    # 데이터 검색 및 응답 준비
    answer = search_in_dataset(user_input, law_dataset)
    if not answer:
        answer = "관련 법률 정보를 찾을 수 없습니다."
    
    full_response_text = system_message + "\n\n" + answer
    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(query, dataset):
    for record in dataset['train']:
        if query in record['사건명']:
            return record['사건번호']
    return "관련 법률 정보를 찾을 수 없습니다."

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