737 lines
26 KiB
Python
737 lines
26 KiB
Python
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import re
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from openai import OpenAI
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from typing import List, Dict,Tuple
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import json
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import time
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import os
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from kg_build_v2.Prompt import Prompt_guzhang,Prompt_compose,Prompt_compose_tujie,Prompt_compose_mulu_tujie
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from kg_build_v2.extract_html import extract_repairproject_tables_html,extract_operation_tables_html,extract_tables,extract_guzhang_tables
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# from modelsAPI.model_api import OpenaiAPI
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def read_markdown_file(file_path):
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"""
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读取 Markdown 文件并返回其全部内容作为字符串。
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参数:
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file_path (str): Markdown 文件的路径（支持相对或绝对路径）
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返回:
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str 或 None: 成功时返回文件内容；出错时返回 None
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"""
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try:
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with open(file_path, 'r', encoding='utf-8') as f:
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content = f.read()
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return content
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except FileNotFoundError:
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print(f"错误：文件未找到 - {file_path}")
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except PermissionError:
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print(f"错误：没有权限读取文件 - {file_path}")
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except UnicodeDecodeError:
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print(f"错误：文件编码不是 UTF-8，无法读取 - {file_path}")
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except Exception as e:
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print(f"读取文件时发生未知错误: {e}")
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return None
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def openai_chat(query:str, model="Qwen3.5-35B-A3B"):
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"""调用OpenAI API"""
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try:
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client = OpenAI(
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api_key= "none",
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base_url= "http://192.168.0.46:59800/v1"
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)
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response = client.chat.completions.create(
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model=model,
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messages=[
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{"role": "user", "content": query},
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],
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temperature=0.1,
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stream=False,
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response_format = {"type": "json_object"},
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extra_body={"chat_template_kwargs": {"enable_thinking": False}}
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)
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return response.choices[0].message.content
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except Exception as e:
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print(f"调用OpenAI API时出错: {e}")
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return None
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def safe_json_loads(s: str):
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try:
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return json.loads(s)
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except json.JSONDecodeError as e:
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# 尝试修复常见问题
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s = s.replace("\\n", "\\\n").replace("\r", "\\r").replace("\t", "\\t")
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# 或者直接清理非法字符
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s = re.sub(r'[\x00-\x1f\x7f]', '', s) # 移除控制字符
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try:
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return json.loads(s)
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except:
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raise e
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#def openai_chat(query: str, model="Qwen3-32B"):
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# """调用OpenAI API"""
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# try:
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# client = OpenAI(
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# api_key="none",
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# base_url="http://192.168.0.46:59800/v1"
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# )
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# response = client.chat.completions.create(
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# model=model,
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# messages=[
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# {"role": "user", "content": query},
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# ],
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# temperature=0.1,
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# stream=False,
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# response_format={"type": "json_object"},
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# extra_body={"chat_template_kwargs": {"enable_thinking": False}}
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# )
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# return response.choices[0].message.content
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# except Exception as e:
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# print(f"调用OpenAI API时出错: {e}")
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# return None
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# def extract_guzhang_table_entity(chunks):
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# """
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# 提取故障类实体
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# """
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# all_results = []
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# all_entity_results = []
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# all_relation_results = []
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# # 确定起始索引
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# print("提取故障类实体和关系")
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# for idx, block in enumerate(chunks, 1):
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# # 跳过第一个表格
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# print(f"=== 故障类 Block {idx} ===")
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# print(block[:100]) # 只打印前500字符
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# print("\n" + "="*60 + "\n")
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# final_prompt = Prompt_guzhang.format(
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# text=block
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# )
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# raw_response = openai_chat(final_prompt)
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# if raw_response is None:
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# print(f" ⚠️ 第 {idx} 切片 API 调用失败")
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# continue
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# # 尝试解析 JSON
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# try:
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# cleaned = raw_response.strip()
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# if cleaned.startswith("```json"):
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# cleaned = cleaned[7:].lstrip()
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# if cleaned.endswith("```"):
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# cleaned = cleaned[:-3].rstrip()
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# json_result = safe_json_loads(cleaned)
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# entities = json_result.get("entities", [])
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# relationships = json_result.get("relationships", [])
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# for entity in entities:
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# # 确保 entity 有 "properties" 键，且其值为字典
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# if "properties" in entity and isinstance(entity["properties"], dict):
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# entity["properties"]["切片"] = block
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# # 打印美化版
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# all_entity_results += entities
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# all_relation_results += relationships
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# # all_results.append({
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# # "entities": entities, # 已添加切片属性的实体列表
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# # "relationships": relationships, # 关系列表
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# # })
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# # 打印美化版
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# except Exception as e:
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# print(f" ⚠️ 第 {idx} 切片 JSON 解析失败: {e}")
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# print(f" 原始响应: {repr(raw_response[:500])}")
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# json_result = None
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# continue
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# all_results.append({
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# "entities": all_entity_results, # 已添加切片属性的实体列表
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# "relationships": all_relation_results, # 关系列表
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# })
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# return all_results
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def extract_guzhang_table_entity(chunks):
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"""
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提取故障类实体和关系，将所有切片的结果合并为两个大列表
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返回: {
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"entities": [...],
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"relationships": [...]
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}
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"""
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all_entities = []
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all_relationships = []
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print("提取故障类实体和关系")
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for idx, block in enumerate(chunks, 1):
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print(f"=== 故障类 Block {idx} ===")
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print(block[:100])
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print("\n" + "="*60 + "\n")
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final_prompt = Prompt_guzhang.format(text=block)
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raw_response =openai_chat(final_prompt)
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if raw_response is None:
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print(f" ⚠️ 第 {idx} 切片 API 调用失败")
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continue
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try:
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cleaned = raw_response.strip()
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if cleaned.startswith("```json"):
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cleaned = cleaned[7:].lstrip()
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if cleaned.endswith("```"):
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cleaned = cleaned[:-3].rstrip()
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json_result = safe_json_loads(cleaned)
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if json_result is None:
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print(f" ⚠️ 第 {idx} 切片 JSON 解析失败: 解析返回 None")
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continue
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entities = json_result.get("entities", [])
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relationships = json_result.get("relationships", [])
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# 为每个实体添加来源切片信息
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for entity in entities:
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if "properties" in entity and isinstance(entity["properties"], dict):
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entity["properties"]["切片"] = block
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# 拼接到总列表
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all_entities.extend(entities)
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all_relationships.extend(relationships)
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print(f" ✅ 第 {idx} 切片解析成功: {len(entities)} 个实体, {len(relationships)} 个关系")
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except Exception as e:
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print(f" ⚠️ 第 {idx} 切片 JSON 解析失败: {e}")
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print(f" 原始响应: {repr(raw_response[:500])}")
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continue
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# 最终结果：返回一个字典，包含拼接后的两个列表
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result = {
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"entities": all_entities,
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"relationships": all_relationships
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}
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return result
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# def extract_compose_table_entity(chunks):
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# """
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# 提取组成表的设备、零部件实体以及关系
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# """
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# print("提取故障类实体和关系")
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# all_results = []
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# all_entity_results = []
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# all_relation_results = []
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# # 确定起始索引
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# for idx, block in enumerate(chunks, 1):
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# # 跳过第一个表格
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# print(f"=== 组成表 Block {idx} ===")
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# print(block[:100]) # 只打印前500字符
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# print("\n" + "="*60 + "\n")
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# final_prompt = Prompt_compose.format(
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# text=block
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# )
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# raw_response = openai_chat(final_prompt)
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# if raw_response is None:
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# print(f" ⚠️ 第 {idx} 切片 API 调用失败")
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# continue
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# # 尝试解析 JSON
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# try:
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# cleaned = raw_response.strip()
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# if cleaned.startswith("```json"):
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# cleaned = cleaned[7:].lstrip()
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# if cleaned.endswith("```"):
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# cleaned = cleaned[:-3].rstrip()
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# json_result = safe_json_loads(cleaned)
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# entities = json_result.get("entities", [])
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# relationships = json_result.get("relationships", [])
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# for entity in entities:
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# # 确保 entity 有 "properties" 键，且其值为字典
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# if "properties" in entity and isinstance(entity["properties"], dict):
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# entity["properties"]["切片"] = block
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# all_entity_results += entities
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# all_relation_results += relationships
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# # 打印美化版
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# print(json.dumps(json_result, ensure_ascii=False, indent=2))
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# # all_results.append({
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# # "entities": entities, # 已添加切片属性的实体列表
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# # "relationships": relationships, # 关系列表
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# # })
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# except Exception as e:
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# print(f" ⚠️ 第 {idx} 切片 JSON 解析失败: {e}")
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# print(f" 原始响应: {repr(raw_response[:500])}")
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# json_result = None
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# continue
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# all_results.append({
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# "entities": all_entity_results, # 已添加切片属性的实体列表
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# "relationships": all_relation_results, # 关系列表
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# })
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# return all_results
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def extract_compose_table_entity(chunks):
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"""
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提取组成表的设备、零部件实体以及关系
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"""
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print("提取组成表实体和关系")
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# 建议：将 all_results 改为复数形式以符合习惯
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all_entities = []
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all_relationships = []
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# 确定起始索引
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for idx, block in enumerate(chunks, 1):
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# 跳过第一个表格（如果需要的话，逻辑保持不变）
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print(f"=== 组成表 Block {idx} ===")
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print(block[:100]) # 只打印前100字符预览
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print("\n" + "="*60 + "\n")
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final_prompt = Prompt_compose.format(text=block)
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raw_response =openai_chat(final_prompt)
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if raw_response is None:
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print(f" ⚠️ 第 {idx} 切片 API 调用失败")
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continue
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# 尝试解析 JSON
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try:
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cleaned = raw_response.strip()
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if cleaned.startswith("```json"):
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cleaned = cleaned[7:].lstrip()
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if cleaned.endswith("```"):
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cleaned = cleaned[:-3].rstrip()
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json_result = safe_json_loads(cleaned)
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# === 核心修改点：处理实体并添加切片信息 ===
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entities = json_result.get("entities", [])
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relationships = json_result.get("relationships", [])
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# 为当前切片的实体添加属性
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for entity in entities:
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if "properties" in entity and isinstance(entity["properties"], dict):
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entity["properties"]["切片"] = block
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# 构建当前块的结果对象
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# current_result = {
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# "entities": entities,
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# "relationships": relationships,
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# }
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all_entities.extend(entities)
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all_relationships.extend(relationships)
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# 添加到总结果列表
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# 打印美化版
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# print(json.dumps(json_result, ensure_ascii=False, indent=2))
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except Exception as e:
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print(f" ⚠️ 第 {idx} 切片 JSON 解析失败: {e}")
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print(f" 原始响应: {repr(raw_response[:500])}")
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continue
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result = {
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"entities": all_entities,
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"relationships": all_relationships
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}
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# 返回按切片分组的结果列表
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return result
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# def compose_table_tujie_entity(chunks):
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# """
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# 提取图解目录中设备、零部件类实体以及相关关系
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# """
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# all_results = []
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# all_entity_results = []
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# all_relation_results = []
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# # 确定起始索引
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# for idx, block in enumerate(chunks, 1):
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# # 跳过第一个表格
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# print(f"=== 图解目录 Block {idx} ===")
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# print(block[:100]) # 只打印前500字符
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# print("\n" + "="*60 + "\n")
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# final_prompt = Prompt_compose_tujie.format(
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# text=block
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# )
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# raw_response = openai_chat(final_prompt)
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# if raw_response is None:
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# print(f" ⚠️ 第 {idx} 切片 API 调用失败")
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# continue
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# # 尝试解析 JSON
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# try:
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# cleaned = raw_response.strip()
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# if cleaned.startswith("```json"):
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# cleaned = cleaned[7:].lstrip()
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# if cleaned.endswith("```"):
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# cleaned = cleaned[:-3].rstrip()
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# json_result = safe_json_loads(cleaned)
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# entities = json_result.get("entities", [])
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# relationships = json_result.get("relationships", [])
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# for entity in entities:
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# # 确保 entity 有 "properties" 键，且其值为字典
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# if "properties" in entity and isinstance(entity["properties"], dict):
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# entity["properties"]["切片"] = block
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# # 打印美化版
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# all_entity_results += entities
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# all_relation_results += relationships
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# print(json.dumps(json_result, ensure_ascii=False, indent=2))
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# # all_results.append({
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# # "entities": entities, # 已添加切片属性的实体列表
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# # "relationships": relationships, # 关系列表
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# # })
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# # 打印美化版
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# print(json.dumps(json_result, ensure_ascii=False, indent=2))
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# success = True
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# except Exception as e:
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# print(f" ⚠️ 第 {idx} 切片 JSON 解析失败: {e}")
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# print(f" 原始响应: {repr(raw_response[:500])}")
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# success = False
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# json_result = None
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# continue
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# all_results.append({
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# "entities": all_entity_results, # 已添加切片属性的实体列表
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# "relationships": all_relation_results, # 关系列表
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# })
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# return all_results
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def compose_table_tujie_entity(chunks):
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"""
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提取图解目录中设备、零部件类实体以及相关关系
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"""
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all_entities = []
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all_relationships = []
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for idx, block in enumerate(chunks, 1):
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print(f"=== 图解目录 Block {idx} ===")
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print(block[:100]) # 只打印前100字符预览
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print("\n" + "="*60 + "\n")
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final_prompt = Prompt_compose_tujie.format(text=block)
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raw_response = openai_chat(final_prompt)
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if raw_response is None:
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print(f" ⚠️ 第 {idx} 切片 API 调用失败")
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continue
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# 尝试解析 JSON
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try:
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# 清理响应中的 Markdown 代码块标记
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cleaned = raw_response.strip()
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if cleaned.startswith("```json"):
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cleaned = cleaned[7:].lstrip()
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if cleaned.endswith("```"):
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cleaned = cleaned[:-3].rstrip()
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json_result = safe_json_loads(cleaned)
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# 提取实体和关系
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entities = json_result.get("entities", [])
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relationships = json_result.get("relationships", [])
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# 为当前切片的实体添加“切片”属性
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for entity in entities:
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if "properties" in entity and isinstance(entity["properties"], dict):
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entity["properties"]["切片"] = block
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# 构建当前切片的结果对象
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all_entities.extend(entities)
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all_relationships.extend(relationships)
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# 将当前结果追加到总列表
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# 打印美化版（打印 current_result 而不是原始的 json_result，确保包含修改）
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# print(json.dumps(json_result, ensure_ascii=False, indent=2))
|
||
|
||
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])}")
|
||
continue
|
||
result = {
|
||
"entities": all_entities,
|
||
"relationships": all_relationships
|
||
}
|
||
return result
|
||
|
||
def extract_compose_table_mulu_tujie(chunks):
|
||
"""
|
||
提取图解目录中设备属性信息
|
||
"""
|
||
all_results = []
|
||
|
||
# 确定起始索引
|
||
|
||
for idx, block in enumerate(chunks, 1):
|
||
# 跳过第一个表格
|
||
|
||
print(f"=== Repair Block {idx} ===")
|
||
print(block[:100]) # 只打印前500字符
|
||
print("\n" + "="*60 + "\n")
|
||
|
||
final_prompt = Prompt_compose_mulu_tujie.format(
|
||
text=block
|
||
)
|
||
|
||
|
||
raw_response = openai_chat(final_prompt)
|
||
|
||
if raw_response is None:
|
||
print(f" ⚠️ 第 {idx} 切片 API 调用失败")
|
||
continue
|
||
|
||
|
||
|
||
all_results.append({
|
||
"chunk_index": idx,
|
||
"structured_result": raw_response,
|
||
"success": "success"
|
||
})
|
||
|
||
return all_results
|
||
|
||
# def get_nromal_node_rela(mdcontent):
|
||
# print("开始提取常规表格实体和关系")
|
||
|
||
# # 提取各类表格
|
||
# chunks_repair, cleaned_content = extract_repairproject_tables_html(mdcontent)
|
||
# chunks_operation, cleaned_content_operation = extract_operation_tables_html(cleaned_content)
|
||
# slices, contexts, cleaned_content_normal = extract_tables(cleaned_content_operation)
|
||
|
||
# # 分类表格
|
||
# compose_table = []
|
||
# compose_table_tujie = []
|
||
# compose_table_mulu_tujie = []
|
||
# guzhang_table = []
|
||
|
||
# for ins in contexts:
|
||
# if '组成部分' in ins and '功能描述' in ins and '数量' in ins:
|
||
# compose_table.append(ins)
|
||
# elif '组成编码' in ins and '名称' in ins and '是否为关重件' in ins and '是否为寿命件' in ins:
|
||
# compose_table_tujie.append(ins)
|
||
# elif '组成编码' in ins and '名称' in ins and '数量' in ins and '重量' in ins:
|
||
# compose_table_mulu_tujie.append(ins)
|
||
# elif '故障现象' in ins and '故障原因' in ins and '维修项目' in ins:
|
||
# guzhang_table.append(ins)
|
||
|
||
# # 初始化结果
|
||
# all_entities = []
|
||
# all_relationships = []
|
||
|
||
# # 提取并合并故障表
|
||
# if guzhang_table:
|
||
# result = extract_guzhang_table_entity(guzhang_table)
|
||
# all_entities.extend(result.get('entities', []))
|
||
# all_relationships.extend(result.get('relationships', []))
|
||
# print("输出故障类实体和关系")
|
||
# print(len(result['entities']))
|
||
# print(len(result['relationships']))
|
||
|
||
# # 提取并合并普通组成表
|
||
# if compose_table:
|
||
# result = extract_compose_table_entity(compose_table)
|
||
# all_entities.extend(result.get('entities', []))
|
||
# all_relationships.extend(result.get('relationships', []))
|
||
# print("输出组成表类实体和关系")
|
||
# print(len(result['entities']))
|
||
# print(len(result['relationships']))
|
||
|
||
# # 提取并合并图解组成表
|
||
# if compose_table_tujie:
|
||
# result = compose_table_tujie_entity(compose_table_tujie)
|
||
# all_entities.extend(result.get('entities', []))
|
||
# all_relationships.extend(result.get('relationships', []))
|
||
# print("输出图解组成表类实体和关系")
|
||
# print(len(result['entities']))
|
||
# print(len(result['relationships']))
|
||
# print(11111111111111111111)
|
||
# print(result)
|
||
|
||
# print(f"常规提取完成：共提取 {len(all_entities)} 个实体，{len(all_relationships)} 个关系")
|
||
|
||
# # 构造返回结果
|
||
# result = [{
|
||
# "entities": all_entities,
|
||
# "relationships": all_relationships,
|
||
# }]
|
||
|
||
# return result, cleaned_content_normal
|
||
def get_nromal_node_rela(mdcontent):
|
||
print("开始提取常规表格实体和关系")
|
||
|
||
# 初始化最终返回的清洗后内容
|
||
cleaned_content_normal = mdcontent
|
||
|
||
try:
|
||
# 提取各类表格
|
||
chunks_repair, cleaned_content = extract_repairproject_tables_html(mdcontent)
|
||
chunks_operation, cleaned_content_operation = extract_operation_tables_html(cleaned_content)
|
||
slices, contexts, cleaned_content_normal = extract_tables(cleaned_content_operation)
|
||
guzhangtable = extract_guzhang_tables(mdcontent)
|
||
# 分类表格
|
||
compose_table = []
|
||
compose_table_tujie = []
|
||
compose_table_mulu_tujie = []
|
||
guzhang_table = []
|
||
|
||
|
||
for ins in contexts:
|
||
if '组成部分' in ins and '功能描述' in ins and '数量' in ins:
|
||
compose_table.append(ins)
|
||
elif '组成编码' in ins and '名称' in ins and '是否为关重件' in ins and '是否为寿命件' in ins:
|
||
compose_table_tujie.append(ins)
|
||
elif '组成编码' in ins and '名称' in ins and '数量' in ins and '重量' in ins:
|
||
compose_table_mulu_tujie.append(ins)
|
||
elif '故障现象' in ins and '故障原因' in ins and '维修项目' in ins:
|
||
guzhang_table.append(ins)
|
||
|
||
except Exception as e:
|
||
print(f"预处理表格分类时发生错误: {e}")
|
||
# 如果预处理出错，初始化的 contexts 为空，后续不会提取数据
|
||
contexts = []
|
||
|
||
# 初始化结果
|
||
all_entities = []
|
||
all_relationships = []
|
||
|
||
if guzhangtable:
|
||
try:
|
||
result = extract_guzhang_table_entity(guzhangtable)
|
||
# 确保 result 是字典且包含键
|
||
if isinstance(result, dict):
|
||
entities = result.get('entities', [])
|
||
relationships = result.get('relationships', [])
|
||
if entities or relationships: # 确保有数据
|
||
all_entities.extend(entities)
|
||
all_relationships.extend(relationships)
|
||
print(all_entities)
|
||
print(all_relationships)
|
||
print("输出故障类实体和关系")
|
||
print(len(entities), len(relationships))
|
||
else:
|
||
print("警告: extract_guzhang_table_entity 返回值不是字典")
|
||
except Exception as e:
|
||
print(f"提取故障表时发生错误: {e}")
|
||
|
||
# --- 提取并合并故障表 (带容错) ---
|
||
if guzhang_table:
|
||
try:
|
||
result = extract_guzhang_table_entity(guzhang_table)
|
||
# 确保 result 是字典且包含键
|
||
if isinstance(result, dict):
|
||
entities = result.get('entities', [])
|
||
relationships = result.get('relationships', [])
|
||
if entities or relationships: # 确保有数据
|
||
all_entities.extend(entities)
|
||
all_relationships.extend(relationships)
|
||
print("输出故障类实体和关系")
|
||
print(len(entities), len(relationships))
|
||
else:
|
||
print("警告: extract_guzhang_table_entity 返回值不是字典")
|
||
except Exception as e:
|
||
print(f"提取故障表时发生错误: {e}")
|
||
|
||
|
||
# --- 提取并合并普通组成表 (带容错) ---
|
||
if compose_table:
|
||
try:
|
||
result = extract_compose_table_entity(compose_table)
|
||
if isinstance(result, dict):
|
||
entities = result.get('entities', [])
|
||
relationships = result.get('relationships', [])
|
||
if entities or relationships:
|
||
all_entities.extend(entities)
|
||
all_relationships.extend(relationships)
|
||
print("输出组成表类实体和关系")
|
||
print(len(entities), len(relationships))
|
||
else:
|
||
print("警告: extract_compose_table_entity 返回值不是字典")
|
||
except Exception as e:
|
||
print(f"提取普通组成表时发生错误: {e}")
|
||
|
||
# --- 提取并合并图解组成表 (带容错) ---
|
||
if compose_table_tujie:
|
||
try:
|
||
result = compose_table_tujie_entity(compose_table_tujie)
|
||
if isinstance(result, dict):
|
||
entities = result.get('entities', [])
|
||
relationships = result.get('relationships', [])
|
||
if entities or relationships:
|
||
all_entities.extend(entities)
|
||
all_relationships.extend(relationships)
|
||
print("输出图解组成表类实体和关系")
|
||
print(len(entities), len(relationships))
|
||
|
||
else:
|
||
print("警告: compose_table_tujie_entity 返回值不是字典")
|
||
except Exception as e:
|
||
print(f"提取图解组成表时发生错误: {e}")
|
||
|
||
print(f"常规提取完成：共提取 {len(all_entities)} 个实体，{len(all_relationships)} 个关系")
|
||
|
||
# 构造返回结果 (保持原有格式 [{...}])
|
||
result = [{
|
||
"entities": all_entities,
|
||
"relationships": all_relationships,
|
||
}]
|
||
|
||
return result, cleaned_content_normal
|
||
|
||
|
||
# if __name__ == "__main__":
|
||
# input_directory = "F:\zklnlp\HJ\hj_kg_code\kgrag\extract_html_json\测试LXJwx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)
|
||
|
||
# tables, cleaned_content = get_nromal_node_rela(mdcontent=mdcontent)
|
||
# for ins in tables:
|
||
# print(ins)
|
||
# print(11111111111111111111)
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|
||
|