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# -*- coding: utf-8 -*-
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import hashlib
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import json
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import time
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from typing import Iterator, Dict
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from openai import OpenAI
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from openai.types.chat import ChatCompletionChunk
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from K2_Neo4jExecutor import *
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class KnowledgeGraph:
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def __init__(self, content: str):
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self.content = content
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self.question_id = self._generate_question_id()
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self.graph = self._init_graph_connection()
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self.existing_knowledge = self._fetch_existing_nodes("KnowledgePoint")
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self.existing_ability = self._fetch_existing_nodes("AbilityPoint")
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self.client = OpenAI(api_key=MODEL_API_KEY, base_url=MODEL_API_URL)
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def _validate_ids(self, line: str) -> bool:
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"""修正后的ID验证（严格匹配数据库格式）"""
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# 调整正则表达式匹配6位小写hex格式
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found_ids = {
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'kp': set(re.findall(r'(kp_[a-f0-9]{6})', line.lower())),
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'ab': set(re.findall(r'(ab_[a-f0-9]{6})', line.lower()))
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}
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# 直接检查小写形式
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valid_kp = all(kp in self.existing_knowledge for kp in found_ids['kp'])
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valid_ab = all(ab in self.existing_ability for ab in found_ids['ab'])
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return valid_kp and valid_ab
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def _init_graph_connection(self) -> Graph:
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"""初始化并测试数据库连接"""
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try:
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graph = Graph(NEO4J_URI, auth=NEO4J_AUTH)
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graph.run("RETURN 1").data()
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print("✅ Neo4j连接成功")
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return graph
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except Exception as e:
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raise ConnectionError(f"❌ 数据库连接失败: {str(e)}")
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def _validate_weight(self, line: str) -> bool:
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"""验证关系权重是否合法"""
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weight_match = re.search(r"weight\s*:\s*([0-9.]+)", line)
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if weight_match:
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try:
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weight = float(weight_match.group(1))
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return 0.0 <= weight <= 1.0
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except ValueError:
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return False
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return True # 没有weight属性时视为合法
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def _validate_cypher_structure(self, cypher: str) -> bool:
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"""验证WITH子句存在性"""
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has_merge = re.search(r'\bMERGE\s*\(q:Question\b', cypher, re.IGNORECASE)
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has_with = re.search(r'\bWITH\s+q\b', cypher, re.IGNORECASE)
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return not has_merge or (has_merge and has_with)
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def _generate_question_id(self) -> str:
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"""生成题目唯一标识符"""
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return hashlib.md5(self.content.encode()).hexdigest()[:8]
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def _fetch_existing_nodes(self, label: str) -> Dict[str, str]:
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"""从Neo4j获取已有节点"""
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try:
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cypher = f"MATCH (n:{label}) RETURN n.id as id, n.name as name"
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result = self.graph.run(cypher).data()
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return {item['id']: item['name'] for item in result}
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except Exception as e:
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print(f"❌ 节点查询失败: {str(e)}")
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return {}
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def _generate_stream(self) -> Iterator[ChatCompletionChunk]:
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"""生成限制性提示词（添加现有节点示例）"""
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# 在提示词中添加现有节点示例
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knowledge_samples = '\n'.join([f"KP_{k[3:]}: {v}" for k, v in list(self.existing_knowledge.items())[:5]])
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ability_samples = '\n'.join([f"AB_{a[3:]}: {v}" for a, v in list(self.existing_ability.items())[:5]])
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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：
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请严格使用以下已有节点ID（不要创建新ID）：
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现有知识点示例（KP_后接6位小写字母/数字）：
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{knowledge_samples}
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现有能力点示例（AB_后接6位小写字母/数字）：
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{ability_samples}
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生成格式要求：
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MERGE (q:Question {{id: "{self.question_id}"}})
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SET q.content = "..."
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WITH q
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MATCH (kp:KnowledgePoint {{id: "KP_xxxxxx"}}) // 必须使用已有KP_ID
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MERGE (q)-[:TESTS_KNOWLEDGE]->(kp)
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WITH q
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MATCH (ab:AbilityPoint {{id: "AB_xxxxxx"}}) // 必须使用已有AB_ID
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MERGE (q)-[:REQUIRES_ABILITY]->(ab)
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'''
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return self.client.chat.completions.create(
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model=MODEL_NAME,
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messages=[
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{"role": "system", "content": system_prompt},
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{"role": "user", "content": self.content}
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],
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stream=True,
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timeout=300
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)
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def _format_node_list(self, nodes: Dict[str, str]) -> str:
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"""格式化节点列表"""
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if not nodes:
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return " （无相关节点）"
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sample = []
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for i, (k, v) in enumerate(nodes.items()):
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if i >= 5:
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sample.append(f" ...（共{len(nodes)}个，仅显示前5个）")
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break
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sample.append(f" - {k}: {v}")
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return '\n'.join(sample)
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def _extract_cypher(self, content: str) -> str:
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"""安全提取Cypher"""
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safe_blocks = []
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for block in re.findall(r"```(?:cypher)?\n(.*?)```", content, re.DOTALL):
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cleaned = self._sanitize_cypher(block)
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if cleaned:
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safe_blocks.append(cleaned)
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return ';\n\n'.join(safe_blocks) if safe_blocks else ""
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def _sanitize_cypher(self, cypher: str) -> str:
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valid_lines = []
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for line_num, line in enumerate(cypher.split('\n'), 1):
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# 添加调试输出
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print(f"正在处理第{line_num}行: {line[:50]}...")
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# 允许SET子句中的内容
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if line.strip().startswith("SET"):
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valid_lines.append(line)
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continue
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# 记录过滤原因
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filter_reason = []
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if re.search(r'\bCREATE\b', line, re.IGNORECASE):
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filter_reason.append("包含CREATE语句")
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if not self._validate_ids(line):
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filter_reason.append("存在无效ID")
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if not self._validate_weight(line):
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filter_reason.append("权重值非法")
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if filter_reason:
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print(f"第{line_num}行被过滤: {line[:50]}... | 原因: {', '.join(filter_reason)}")
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continue
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valid_lines.append(line)
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return '\n'.join(valid_lines)
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def run(self) -> Tuple[bool, str, str]:
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"""执行安全生成流程"""
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if not self.existing_knowledge or not self.existing_ability:
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print("❌ 知识库或能力点为空，请检查数据库")
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return False, "节点数据为空", ""
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start_time = time.time()
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spinner = ['⠋', '⠙', '⠹', '⠸', '⠼', '⠴', '⠦', '⠧', '⠇', '⠏']
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content_buffer = []
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try:
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print(f"🚀 开始生成（知识点：{len(self.existing_knowledge)}个，能力点：{len(self.existing_ability)}个）")
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stream = self._generate_stream()
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for idx, chunk in enumerate(stream):
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print(f"\r{spinner[idx % 10]} 生成中（{int(time.time() - start_time)}秒）", end="")
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if chunk.choices and chunk.choices[0].delta.content:
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content_chunk = chunk.choices[0].delta.content
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content_buffer.append(content_chunk)
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if len(content_buffer) == 1:
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print("\n\n📝 内容生成开始：")
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print(content_chunk, end="", flush=True)
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if content_buffer:
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full_content = ''.join(content_buffer)
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print(f"\n\n✅ 生成完成！耗时 {int(time.time() - start_time)}秒")
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return True, full_content
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print("\n⚠️ 生成完成但未获取到有效内容")
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return False, "空内容"
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# 修改run方法中的异常处理
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except Exception as e:
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# 修正后的代码
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error_msg = str(e) if not isinstance(e, dict) else json.dumps(e)
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print(f"\n\n❌ 生成失败：{error_msg}")
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return False, error_msg, ""
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