from fastapi import FastAPI, HTTPException, BackgroundTasks
from qa_Ask import QAService, match_query, store_data
from pydantic import BaseModel
from collections import deque
import requests
import os
import time
import uuid
import json
import shutil
import yaml
import logging


app = FastAPI()

import sys

# 配置日志记录到文件和终端
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler('log/app.log'),
        logging.StreamHandler(sys.stdout)  # 这里添加控制台处理程序
    ]
)
logger = logging.getLogger(__name__)

class QuestionRequest(BaseModel):
    question: str
    ScoreThreshold: float


class QuestionResponse(BaseModel):
    code: int
    msg: str
    data: list


class QuestionItem(BaseModel):
    questionCode: str
    questionList: list[str]


with open('config/config.yaml', 'r') as config_file:
    config_data = yaml.safe_load(config_file)

knowledge_base_file = config_data['knowledge_base_file']
api_url = config_data['api']['url']
path = config_data['output_file_path']
max_knowledge_bases = config_data['max_knowledge_bases']


def load_knowledge_bases():
    """加载知识库名称列表"""
    if os.path.exists(knowledge_base_file):
        with open(knowledge_base_file, "r") as file:
            return file.read().splitlines()
    else:
        return []


def save_knowledge_bases(names):
    """保存知识库名称列表到文件"""
    with open(knowledge_base_file, "w") as file:
        file.write("\n".join(names))


def update_kb(kb_name, qa_service, path, max_knowledge_bases):
    """更新知识库"""
    store_data(qa_service, path)

    if len(recent_knowledge_bases) == max_knowledge_bases:
        folder_to_delete = recent_knowledge_bases.popleft()
        shutil.rmtree(f"knowledge_base/{folder_to_delete}")

    recent_knowledge_bases.append(kb_name)
    save_knowledge_bases(recent_knowledge_bases)

    os.remove(path)
    logger.info(f"Knowledge base updated: {kb_name}\n"
                f"Please wait while the database is being updated···")


def fetch_and_write_data(api_url, path):
    """从API获取数据并写入文件"""
    try:
        response = requests.get(api_url)
        response_data = response.json()

        if response.status_code == 200 and response_data["code"] == 200:
            question_items = response_data["data"]

            with open(path, "w", encoding="utf-8") as file:
                json.dump(question_items, file, ensure_ascii=False, indent=2)

            return True
        else:
            logger.error(f"Failed to fetch data from API. Status code: {response.status_code}, Response data: {response_data}")
            return False
    except Exception as e:
        logger.error(f"Error fetching data from API: {e}")
        return False


@app.post("/updateDatabase")
async def save_to_json(question_items: list[QuestionItem], background_tasks: BackgroundTasks):
    """接收问题数据并异步保存为JSON文件，触发后台更新任务"""
    try:
        json_data = json.dumps([item.dict() for item in question_items], ensure_ascii=False, indent=2)
        path = "output.json"

        with open(path, "w", encoding="utf-8") as file:
            file.write(json_data)

        kb_name = str(uuid.uuid4())

        device = None
        qa_service = QAService(kb_name, device)

        background_tasks.add_task(
            update_kb, kb_name, qa_service, path, max_knowledge_bases
        )

        return {"status": "success", "message": "Please wait while the database is being updated···"}

    except Exception as e:
        logger.error(f"Error saving data to file or scheduling knowledge base update task: {e}")
        # raise HTTPException(status_code=500, detail=f"Internal Server Error: {str(e)}")
        return {"status": "error", "message": "update task error···"}

@app.post("/matchQuestion")
def match_question(request: QuestionRequest):
    """匹配问题的端点"""
    try:
        logger.info(f"match_question:Request: {request}")
        start_time = time.time()
        query = request.question

        newest = recent_knowledge_bases[-1]

        top_k = 3

        device = None
        qa_service = QAService(newest, device)

        result = match_query(qa_service, query, top_k, request.ScoreThreshold)

        response = QuestionResponse(code=200, msg="success", data=[result])
        stop_time = time.time()
        duration = stop_time - start_time

        logger.info(f"match_question:Matched question in {duration} seconds. "
                    f"Response: {result}")
        return response

    except Exception as e:
        logger.error(f"Error matching question: {e}")
        return QuestionResponse(code=500, msg="success", data=[])

recent_knowledge_bases = deque(load_knowledge_bases(), maxlen=max_knowledge_bases)

if fetch_and_write_data(api_url, path):
    kb_name = str(uuid.uuid4())
    device = None
    qa_service = QAService(kb_name, device)
    update_kb(kb_name, qa_service, path, max_knowledge_bases)

if __name__ == "__main__":
    import uvicorn

    uvicorn.run(app, host="0.0.0.0", port=8000)