import re
from openai import OpenAI
from typing import List, Dict
import json
import time
import os
from  kg_build_v2.extract_html import extract_repairproject_tables_html,extract_operation_tables_html,extract_tables
from  kg_build_v2.Prompt import prompt_extract_repair_node_rela
from modelsAPI.model_api import OpenaiAPI

def read_markdown_file(file_path):
    """
    读取 Markdown 文件并返回其全部内容作为字符串。

    参数:
        file_path (str): Markdown 文件的路径（支持相对或绝对路径）

    返回:
        str 或 None: 成功时返回文件内容；出错时返回 None
    """
    try:
        with open(file_path, 'r', encoding='utf-8') as f:
            content = f.read()
        return content
    except FileNotFoundError:
        print(f"错误：文件未找到 - {file_path}")
    except PermissionError:
        print(f"错误：没有权限读取文件 - {file_path}")
    except UnicodeDecodeError:
        print(f"错误：文件编码不是 UTF-8，无法读取 - {file_path}")
    except Exception as e:
        print(f"读取文件时发生未知错误: {e}")
    return None


def safe_json_loads(s: str):
    try:
        return json.loads(s)
    except json.JSONDecodeError as e:
        # 尝试修复常见问题
        s = s.replace("\\n", "\\\n").replace("\r", "\\r").replace("\t", "\\t")
        # 或者直接清理非法字符
        s = re.sub(r'[\x00-\x1f\x7f]', '', s)  # 移除控制字符
        try:
            return json.loads(s)
        except:
            raise e

def extract_wxindextable(chunks, skip_first=True):
    """
    批量处理一个文档的多个切片（chunks），每个切片调用大模型结构化，并返回全部结果。
    
    :param chunks: List[str] - 同一文档的多个文本切片
    :param skip_first: bool - 是否跳过第一个表格块（默认True）
    :return: List[Dict] - 结构化结果列表
    """
    all_results = []
    
    # 确定起始索引
    start_idx = 1 if skip_first else 0

    for idx, block in enumerate(chunks, 1):
        # 跳过第一个表格
        if skip_first and idx == 1:
            print(f"=== 跳过第 {idx} 个表格块（首个表格） ===\n")
            continue
            
        print(f"=== 维修项目 Block {idx} ===")
        print(block[:100])  # 只打印前500字符
        print("\n" + "="*60 + "\n")

        final_prompt = prompt_extract_repair_node_rela.format(text=block)
        
        raw_response =  OpenaiAPI.openai_chat(final_prompt,timeout=180)
        
        if raw_response is None:
            print(f"  ⚠️ 第 {idx} 切片 API 调用失败")
            continue
        
        
        # 尝试解析 JSON
        try:
            cleaned = raw_response.strip()
            if cleaned.startswith("```json"):
                cleaned = cleaned[7:].lstrip()
            if cleaned.endswith("```"):
                cleaned = cleaned[:-3].rstrip()
            
            json_result = safe_json_loads(cleaned)
            if "properties" in json_result:
                json_result["properties"]["切片"] = block  # 添加原始文本块
            else:
                print(f"  ⚠️ 第 {idx} 切片的 JSON 中缺少 'properties' 字段，跳过添加切片")
            # 打印美化版
            all_results.append(json_result)
            
        except Exception as e:
            print(f"  ⚠️ 第 {idx} 切片 JSON 解析失败: {e}")
            print(f"  原始响应: {repr(raw_response[:500])}")
            json_result = None
            continue      
    
    return all_results

# def openai_chat(query: str, model="Qwen3-32B"):
#     """调用OpenAI API"""
#     try:
#         client = OpenAI(
#             api_key="none",
#             base_url="http://192.168.0.46:59800/v1"
#         )

#         response = client.chat.completions.create(
#             model=model,
#             messages=[
#                 {"role": "user", "content": query},
#             ],
#             temperature=0.1,
#             stream=False,
#             response_format={"type": "json_object"},
#             extra_body={"chat_template_kwargs": {"enable_thinking": False}}
#         )
#         return response.choices[0].message.content
#     except Exception as e:
#         print(f"调用OpenAI API时出错: {e}")
#         return None



def get_repair_node_rela(mdcontent):
    print("开始提取维修项目表实体和关系")
    chunks, cleaned_content = extract_repairproject_tables_html(mdcontent)
    print(f"找到 {len(chunks)} 个维修表格块")
    if len(chunks) > 0:
        result = extract_wxindextable(chunks=chunks)
        return result
    else:
        return []



# if __name__ == "__main__":
#     input_directory = "F:\zklnlp\HJ\hj_kg_code\kgrag\extract_html_json\测试wx手册_shenghna_output11_full_content.md"
    
#     # 调用目录处理函数
#     mdcontent = read_markdown_file(input_directory)
    
#     if mdcontent is None:
#         print("无法读取文件，程序退出")
#         exit(1)
    
#     result = get_repair_node_rela(mdcontent=mdcontent)
#     print(len(result))