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黄海 5 months ago
parent b05f7f18d7
commit e898ee003e
3 changed files with 149 additions and 62 deletions
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2
AI/Neo4j/Backup/K3_Start.py
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@ -36,7 +36,7 @@ if __name__ == '__main__':
executor.execute_cypher_text(init_script)
# 分段读入题目
question_blocks = split_questions('../ShiTi.md')
question_blocks = split_questions('ShiTi.md')
# 验证分割结果
for i, block in enumerate(question_blocks, 1):

0
AI/Neo4j/ShiTi.md → AI/Neo4j/Backup/ShiTi.md
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209
AI/Neo4j/InputShiTi.py
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@ -36,8 +36,8 @@ class KnowledgeGraph:
1. 只使用以下存在的知识点（格式：ID:名称）：
{", ".join([f"{k}:{v}" for k, v in zip(example_ids, example_names)])}...
共{len(self.knowledge_points)}个可用知识点
2. 按此格式生成Cypher：
2. 题目可能包含多个知识点，让仔细检查。
3. 按此格式生成Cypher：
MERGE (q:Question {{id: "{self.question_id}"}})
SET q.content = "题目内容"
WITH q
@ -45,66 +45,149 @@ MATCH (kp:KnowledgePoint {{id: "知识点ID"}})
MERGE (q)-[:TESTS_KNOWLEDGE]->(kp)"""
def _clean_cypher(self, code: str) -> str:
"""完整清洗逻辑"""
"""完整Cypher清洗逻辑（增强版）"""
safe = []
cypher_block = re.findall(r"```(?:cypher)?\n(.*?)```", code, re.DOTALL)
if not cypher_block:
return ""
content_keywords = {
'行程问题': ['相遇', '相向而行', '追及', '速度', '路程'],
'几何问题': ['面积', '体积', '周长', '三角形', '长方体'],
'分数运算': ['分数', '百分比', '%', '分之']
}
try:
# 提取代码块
cypher_block = re.findall(r"```(?:cypher)?\n(.*?)```", code, re.DOTALL)
if not cypher_block:
print("未检测到Cypher代码块")
return ""
# 预处理配置
valid_ids_upper = [k.upper() for k in self.knowledge_points.keys()]
detected_types = []
raw_lines = cypher_block[0].split('\n')
has_question = False
# === 第一步：基础清洗 ===
for line in raw_lines:
# 清理注释和空白
clean_line = line.split('//')[0].strip()
if not clean_line:
continue
# 阻止CREATE操作
if 'CREATE' in clean_line.upper():
print(f"阻止CREATE操作: {clean_line}")
continue
# 强制Question节点在最前面
if 'MERGE (q:Question' in clean_line:
has_question = True
safe.insert(0, clean_line)
continue
safe.append(clean_line)
# === 第二步：检测题目类型 ===
for pattern, keys in content_keywords.items():
if any(k in self.content for k in keys):
detected_types.append(pattern)
print(f"检测到题目类型: {pattern}")
# 预处理：获取所有知识点的规范大写形式
valid_ids_upper = [k.upper() for k in self.knowledge_points.keys()]
has_question = False
for line in cypher_block[0].split('\n'):
# 清理注释和空白
line = line.split('//')[0].strip()
if not line:
continue
# 阻止CREATE操作
if 'CREATE' in line.upper():
continue
# 强制Question节点在最前面
if 'MERGE (q:Question' in line:
has_question = True
safe.insert(0, line)
continue
# 处理知识点匹配
if 'MATCH (kp:KnowledgePoint' in line:
# 提取并验证ID
kp_id_match = re.search(r"id: ['\"](.*?)['\"]", line)
if kp_id_match:
original_id = kp_id_match.group(1)
# === 第三步：处理知识点ID ===
knowledge_lines = []
for line in safe.copy():
if 'MATCH (kp:KnowledgePoint' in line:
# 安全提取ID
match = re.search(r"id: ['\"](.*?)['\"]", line)
if not match:
print(f"无效的MATCH语句: {line}")
safe.remove(line)
continue
original_id = match.group(1)
upper_id = original_id.upper()
# 验证存在性（不区分大小写）
# 验证ID存在性
if upper_id not in valid_ids_upper:
print(f"忽略无效知识点ID: {original_id}")
safe.remove(line)
continue
# 替换为数据库实际存储的大写ID
line = line.replace(original_id, upper_id)
# 替换为正确的大写ID
new_line = line.replace(original_id, upper_id)
safe[safe.index(line)] = new_line
knowledge_lines.append(new_line)
# === 第四步：自动补充知识点 ===
for dtype in detected_types:
# 安全获取已关联知识点ID
extracted_ids = []
for line in knowledge_lines:
try:
match = re.search(r"id: ['\"](.*?)['\"]", line)
if match:
kp_id = match.group(1).upper()
extracted_ids.append(kp_id)
except AttributeError:
continue
# 获取对应的知识点名称（确保为字符串）
type_exists = any(
dtype in str(self.knowledge_points.get(kp_id, ''))
for kp_id in extracted_ids
)
if not type_exists:
# 查找匹配的知识点（添加空值过滤）
candidates = [
(k, v) for k, v in self.knowledge_points.items()
if v and dtype in str(v) # 确保v是字符串
and k.upper() in valid_ids_upper
]
# 自动补全WITH语句
if has_question and 'MERGE (q)-[:TESTS_KNOWLEDGE]' in line:
if not any('WITH q' in l for l in safe):
safe.append("WITH q")
# 按名称匹配度排序
candidates.sort(key=lambda x: (
dtype in x[1], # 优先完全匹配
-len(x[1]) # 次优先名称长度短的
), reverse=True)
safe.append(line)
if candidates:
target_id, target_name = candidates[0]
print(f"补充知识点: {target_id} - {target_name}")
safe.extend([
"WITH q",
f"MATCH (kp:KnowledgePoint {{id: \"{target_id.upper()}\"}})",
"MERGE (q)-[:TESTS_KNOWLEDGE]->(kp)"
])
else:
print(f"未找到匹配的{dtype}知识点")
# 确保Question节点后紧跟WITH
if has_question:
# 在MERGE (q:Question)之后插入WITH
for i, line in enumerate(safe):
if 'MERGE (q:Question' in line:
if i + 1 >= len(safe) or not safe[i + 1].startswith('WITH'):
safe.insert(i + 1, "WITH q")
break
# === 第五步：语法修正 ===
# 确保Question节点后紧跟WITH
if has_question:
for i, line in enumerate(safe):
if 'MERGE (q:Question' in line:
# 检查下一条是否是WITH
if i + 1 >= len(safe) or not safe[i + 1].startswith('WITH'):
safe.insert(i + 1, "WITH q")
break
# 最终过滤空行
return '\n'.join([line for line in safe if line])
# 移除重复的WITH语句
final_safe = []
prev_was_with = False
for line in safe:
if line.startswith('WITH'):
if not prev_was_with:
final_safe.append(line)
prev_was_with = True
else:
final_safe.append(line)
prev_was_with = False
return '\n'.join(final_safe)
except Exception as e:
print(f"清洗Cypher时发生错误: {str(e)}")
return ""
def run(self) -> str:
"""执行知识点关联流程"""
@ -158,6 +241,7 @@ MERGE (q)-[:TESTS_KNOWLEDGE]->(kp)"""
if __name__ == '__main__':
test_case = """【时间问题】甲乙两车从相距240公里的两地同时出发相向而行，甲车时速60公里，乙车时速40公里，几小时后相遇？"""
kg = KnowledgeGraph(test_case)
#print("原始知识点库：", kg.knowledge_points) # 查看加载的知识点
cypher = kg.run()
if cypher:
# 插入数据
@ -167,14 +251,17 @@ if __name__ == '__main__':
else:
print("未生成有效Cypher")
# # 临时诊断
# print("当前知识库中是否存在该ID：",
# 'f0333b305f7246b5a06d03d4e3ff55a9' in kg.knowledge_points)
#
# # 直接查询数据库
# test_cypher = '''
# MATCH (kp:KnowledgePoint)
# WHERE kp.id = 'f0333b305f7246b5a06d03d4e3ff55a9'
# RETURN kp.id, kp.name
# '''
# print("直接查询结果：", kg.graph.run(test_cypher).data())
'''
# 基本可视化查询
MATCH path=(q:Question {id: "07ece550"})-[:TESTS_KNOWLEDGE]->(kp)
RETURN path
# 带样式的可视化
MATCH (q:Question {id: "07ece550"})-[:TESTS_KNOWLEDGE]->(kp)
RETURN q, kp
// 在浏览器中点击左侧样式图标，设置：
// - Question节点颜色：橙色
// - KnowledgePoint节点颜色：蓝色
// - 关系线宽：3px
'''

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