# -*- coding: utf-8 -*- import hashlib import json import time from typing import Iterator, Dict from openai import OpenAI from openai.types.chat import ChatCompletionChunk from K2_Neo4jExecutor import * class KnowledgeGraph: def __init__(self, content: str): self.content = content self.question_id = self._generate_question_id() self.graph = self._init_graph_connection() self.existing_knowledge = self._fetch_existing_nodes("KnowledgePoint") self.existing_ability = self._fetch_existing_nodes("AbilityPoint") self.client = OpenAI(api_key=MODEL_API_KEY, base_url=MODEL_API_URL) def _validate_ids(self, line: str) -> bool: """强化ID验证(严格过滤非法节点)""" # 调整正则表达式严格匹配格式 found_ids = { 'kp': set(re.findall(r'\b(kp_[a-f0-9]{6})\b', line.lower())), 'ab': set(re.findall(r'\b(ab_[a-f0-9]{6})\b', line.lower())) } # 严格检查存在性(空集合视为有效) valid_kp = not found_ids['kp'] or all(kp in self.existing_knowledge for kp in found_ids['kp']) valid_ab = not found_ids['ab'] or all(ab in self.existing_ability for ab in found_ids['ab']) return valid_kp and valid_ab def _init_graph_connection(self) -> Graph: """初始化并测试数据库连接""" try: graph = Graph(NEO4J_URI, auth=NEO4J_AUTH) graph.run("RETURN 1").data() print("✅ Neo4j连接成功") return graph except Exception as e: raise ConnectionError(f"❌ 数据库连接失败: {str(e)}") def _validate_weight(self, line: str) -> bool: """验证关系权重是否合法""" weight_match = re.search(r"weight\s*:\s*([0-9.]+)", line) if weight_match: try: weight = float(weight_match.group(1)) return 0.0 <= weight <= 1.0 except ValueError: return False return True # 没有weight属性时视为合法 def _validate_cypher_structure(self, cypher: str) -> bool: """验证WITH子句存在性""" has_merge = re.search(r'\bMERGE\s*\(q:Question\b', cypher, re.IGNORECASE) has_with = re.search(r'\bWITH\s+q\b', cypher, re.IGNORECASE) return not has_merge or (has_merge and has_with) def _generate_question_id(self) -> str: """生成题目唯一标识符""" return hashlib.md5(self.content.encode()).hexdigest()[:8] def _fetch_existing_nodes(self, label: str) -> Dict[str, str]: """从Neo4j获取已有节点""" try: cypher = f"MATCH (n:{label}) RETURN n.id as id, n.name as name" result = self.graph.run(cypher).data() return {item['id']: item['name'] for item in result} except Exception as e: print(f"❌ 节点查询失败: {str(e)}") return {} def _generate_stream(self) -> Iterator[ChatCompletionChunk]: """强化提示词限制""" # 生成现有ID列表的提示 existing_kp_ids = '\n'.join([f"- {k}" for k in list(self.existing_knowledge.keys())[:5]]) existing_ab_ids = '\n'.join([f"- {k}" for k in list(self.existing_ability.keys())[:5]]) system_prompt = f''' 将题目中涉及到的小学数学知识点、能力点进行总结,并且按照以下格式生成在neo4j-community-5.26.2上的语句: 重要限制条件(违反将导致执行失败): 1. 禁止创建新节点(只能使用以下现有ID) 2. 现有知识点ID列表: {existing_kp_ids} ... 3. 现有能力点ID列表: {existing_ab_ids} ... 4. 必须使用MATCH定位已有节点后才能建立关系 生成格式示例(注意WITH子句): MERGE (q:Question {{id: "{self.question_id}"}}) SET q.content = "题目内容", q.name = "前10字符" WITH q MATCH (kp1:KnowledgePoint {{id: "kp_3f5g6h"}}) WHERE kp1 IS NOT NULL MERGE (q)-[:TESTS_KNOWLEDGE]->(kp1) ''' return self.client.chat.completions.create( model=MODEL_NAME, messages=[ {"role": "system", "content": system_prompt}, {"role": "user", "content": self.content} ], stream=True, timeout=300 ) def _format_node_list(self, nodes: Dict[str, str]) -> str: """格式化节点列表""" if not nodes: return " (无相关节点)" sample = [] for i, (k, v) in enumerate(nodes.items()): if i >= 5: sample.append(f" ...(共{len(nodes)}个,仅显示前5个)") break sample.append(f" - {k}: {v}") return '\n'.join(sample) def _extract_cypher(self, content: str) -> str: """安全提取Cypher""" safe_blocks = [] for block in re.findall(r"```(?:cypher)?\n(.*?)```", content, re.DOTALL): cleaned = self._sanitize_cypher(block) if cleaned: safe_blocks.append(cleaned) return ';\n\n'.join(safe_blocks) if safe_blocks else "" def _sanitize_cypher(self, cypher: str) -> str: # 新增过滤条件:禁止MERGE非Question节点 if re.search(r'\bMERGE\s*\((?!q:Question)', cypher, re.IGNORECASE): print("⚠️ 检测到非法MERGE语句,已过滤") return "" # 新增过滤条件:验证所有MATCH的节点是否带ID for line in cypher.split('\n'): if 'MATCH' in line and not re.search(r'\{id:\s*".+?"\}', line): print(f"⚠️ 检测到无ID的MATCH语句: {line[:50]}") return "" def run(self) -> Tuple[bool, str, str]: """执行安全生成流程(修正返回三元组)""" if not self.existing_knowledge or not self.existing_ability: print("❌ 知识库或能力点为空,请检查数据库") return False, "节点数据为空", "" # 保持三元组格式 start_time = time.time() spinner = ['⠋', '⠙', '⠹', '⠸', '⠼', '⠴', '⠦', '⠧', '⠇', '⠏'] content_buffer = [] try: print(f"🚀 开始生成(知识点:{len(self.existing_knowledge)}个,能力点:{len(self.existing_ability)}个)") stream = self._generate_stream() for idx, chunk in enumerate(stream): print(f"\r{spinner[idx % 10]} 生成中({int(time.time() - start_time)}秒)", end="") if chunk.choices and chunk.choices[0].delta.content: content_chunk = chunk.choices[0].delta.content content_buffer.append(content_chunk) if len(content_buffer) == 1: print("\n\n📝 内容生成开始:") print(content_chunk, end="", flush=True) if content_buffer: full_content = ''.join(content_buffer) cypher_script = self._extract_cypher(full_content) # 新增提取步骤 print(f"\n\n✅ 生成完成!耗时 {int(time.time() - start_time)}秒") return True, full_content, cypher_script # 返回三元组 print("\n⚠️ 生成完成但未获取到有效内容") return False, "空内容", "" # 修正为三元组 except Exception as e: error_msg = str(e) if not isinstance(e, dict) else json.dumps(e) print(f"\n\n❌ 生成失败:{error_msg}") return False, error_msg, "" # 保持三元组格式