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_operation_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_entity_relation(chunks, skip_first=False):
    """
    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 = []
    all_entities = []
    all_relationships = []
    # 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"=== 操作项目 Block {idx} ===")
        print(block[:100])  # 只打印前500字符
        print("\n" + "="*60 + "\n")

        final_prompt = prompt_extract_operation_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)
            entities = json_result.get("entities", [])
            relationships = json_result.get("relationships", [])
            for entity in entities:
                # 确保 entity 有 "properties" 键，且其值为字典
                if "properties" in entity and isinstance(entity["properties"], dict):
                    entity["properties"]["切片"] = block
            # 打印美化版
            all_entities.extend(entities)
            all_relationships.extend(relationships)
            # 将当前结果追加到总列表
            # all_results.append({
            #     "entities": entities,          # 已添加切片属性的实体列表
            #     "relationships": relationships,  # 关系列表
            #     })

            
        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 = []
            continue
    result = {
        "entities": all_entities,
        "relationships": all_relationships
    }  
    
    return result





def get_operation_node_rela(mdcontent):
    print("开始提取操作项目表实体和关系")
    chunks_repair, cleaned_content = extract_repairproject_tables_html(mdcontent)
    chunks_operation, cleaned_content_operation = extract_operation_tables_html(cleaned_content)

    
    if len(chunks_operation) > 0:
        print(f"找到 {len(chunks_operation)} 个操作项目表格块")
        result = extract_entity_relation(chunks=chunks_operation)
        return result
    else:
        return []



# if __name__ == "__main__":
#     input_directory = r"F:\zklnlp\HJ\hj_kg_code\kgrag\table_extract\files\操作使用手册_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)
    
#     res = get_operation_node_rela(mdcontent=mdcontent)
#     print(len(res))