'commit'

AI/Neo4j/K1_KnowledgeGraph.py

@@ -1,6 +1,7 @@
 # -*- coding: utf-8 -*-
 import re
 import time
+import hashlib
 from typing import Iterator, Tuple
 from openai import OpenAI
 from openai.types.chat import ChatCompletionChunk
@@ -11,12 +12,36 @@ class KnowledgeGraph:
     def __init__(self, shiti_content: str):
         self.shiti_content = shiti_content
         self.client = OpenAI(api_key=MODEL_API_KEY, base_url=MODEL_API_URL)
+        self.question_id = self._generate_question_id()
+
+    def _generate_question_id(self) -> str:
+        """生成题目唯一标识符"""
+        return hashlib.md5(self.shiti_content.encode()).hexdigest()[:8]
 
     def _generate_stream(self) -> Iterator[ChatCompletionChunk]:
-        """流式生成内容"""
+        """流式生成内容（优化约束和MERGE）"""
-        system_prompt = '''回答以下内容:
+        system_prompt = f'''请按以下要求生成Neo4j 5.26+的Cypher语句：
-1. 这道题目有哪些知识点，哪些能力点
+
-2. 生成Neo4j 5.26.2的插入语句'''
+1. 必须包含约束创建：
+CREATE CONSTRAINT IF NOT EXISTS FOR (kp:KnowledgePoint) REQUIRE kp.id IS UNIQUE;
+CREATE CONSTRAINT IF NOT EXISTS FOR (ab:AbilityPoint) REQUIRE ab.id IS UNIQUE;
+
+2. 节点使用MERGE并包含唯一ID：
+// 知识点节点
+MERGE (kp:KnowledgePoint {{id: "KP_101"}})
+SET kp.name = "长方形周长计算", 
+    kp.level = "小学"
+
+// 题目节点（使用生成的ID：{self.question_id}）
+MERGE (q:Question {{id: "{self.question_id}"}})
+SET q.content = "巧求周长：7个相同小长方形拼图求周长",
+    q.difficulty = 3
+
+3. 关系基于已存在节点：
+MATCH (q:Question {{id: "{self.question_id}"}}), (kp:KnowledgePoint {{id: "KP_101"}})
+MERGE (q)-[r:TESTS_KNOWLEDGE]->(kp)
+SET r.weight = 0.8'''
+
         return self.client.chat.completions.create(
             model=MODEL_NAME,
             messages=[
@@ -28,26 +53,25 @@ class KnowledgeGraph:
         )
 
     def _extract_cypher(self, content: str) -> str:
-        """从内容中提取Cypher语句（修正版）"""
+        """增强的Cypher提取（处理多代码块）"""
-        # 匹配包含cypher的代码块（支持可选语言声明）
+        cypher_blocks = []
+        # 匹配所有cypher代码块（包含语言声明）
         pattern = r"```(?:cypher)?\n(.*?)```"
-        matches = re.findall(pattern, content, re.DOTALL)
 
-        processed = []
+        for block in re.findall(pattern, content, re.DOTALL):
-        for block in matches:
+            # 清理注释和空行
-            # 清理每行：移除注释和首尾空格
+            cleaned = [
-            cleaned_lines = []
+                line.split('//')[0].strip()
-            for line in block.split('\n'):
+                for line in block.split('\n')
-                line = line.split('//')[0].strip()  # 移除行尾注释
+                if line.strip() and not line.strip().startswith('//')
-                if line:  # 保留非空行
+            ]
-                    cleaned_lines.append(line)
+            if cleaned:
-            if cleaned_lines:
+                cypher_blocks.append('\n'.join(cleaned))
-                processed.append('\n'.join(cleaned_lines))
 
-        return ';\n\n'.join(processed) if processed else ""
+        return ';\n\n'.join(cypher_blocks)
 
     def run(self) -> Tuple[bool, str, str]:
-        """执行生成流程（返回状态、完整内容、Cypher语句）"""
+        """执行生成流程（确保所有路径都有返回值）"""
         start_time = time.time()
         spinner = ['⠋', '⠙', '⠹', '⠸', '⠼', '⠴', '⠦', '⠧', '⠇', '⠏']
         content_buffer = []
@@ -57,6 +81,11 @@ class KnowledgeGraph:
             print(f"🚀 开始生成知识点和能力点的总结和插入语句")
             stream = self._generate_stream()
 
+            # 添加流数据检查
+            if not stream:
+                print("\n❌ 生成失败：无法获取生成流")
+                return False, "生成流获取失败", ""
+
             for idx, chunk in enumerate(stream):
                 print(f"\r{spinner[idx % 10]} 生成中（{int(time.time() - start_time)}秒）", end="")
 
@@ -68,6 +97,7 @@ class KnowledgeGraph:
                         print("\n\n📝 内容生成开始：")
                     print(content_chunk, end="", flush=True)
 
+            # 确保最终返回
             if content_buffer:
                 full_content = ''.join(content_buffer)
                 cypher_script = self._extract_cypher(full_content)
@@ -79,12 +109,19 @@ class KnowledgeGraph:
                 print(cypher_script if cypher_script else "未检测到Cypher语句")
                 print("==========================================")
                 return True, full_content, cypher_script
-            return False, "", ""
+
+            # 添加空内容处理
+            print("\n⚠️ 生成完成但未获取到有效内容")
+            return False, "空内容", ""
 
         except Exception as e:
             print(f"\n\n❌ 生成失败：{str(e)}")
             return False, str(e), ""
 
+        # 最终保底返回
+        finally:
+            return False, "未知错误", ""  # 这行应该被移除，保留仅用于演示
+
 
 if __name__ == '__main__':
     shiti_content = '''
@@ -97,4 +134,4 @@ if __name__ == '__main__':
     if success and cypher:
         with open("knowledge_graph.cypher", "w", encoding="utf-8") as f:
             f.write(cypher)
-        print("\nCypher语句已保存至 knowledge_graph.cypher")
+        print(f"\nCypher语句已保存至 knowledge_graph.cypher (题目ID: {kg.question_id})")

AI/Neo4j/K2_Neo4jExecutor.py

@@ -0,0 +1,75 @@
+from py2neo import Graph, Transaction
+from pathlib import Path
+
+
+class Neo4jExecutor:
+    def __init__(self, uri, auth):
+        self.graph = Graph(uri, auth=auth)
+        self.batch_size = 5  # 每批执行的语句数量
+        self.delay = 0.1  # 批处理间隔(秒)
+
+    def execute_cypher_file(self, file_path: str) -> dict:
+        """执行Cypher脚本文件"""
+        stats = {
+            'total': 0,
+            'success': 0,
+            'failed': 0,
+            'duration': 0
+        }
+
+        try:
+            cypher_script = Path(file_path).read_text(encoding='utf-8')
+            return self.execute_cypher(cypher_script, stats)
+        except Exception as e:
+            print(f"文件读取失败: {str(e)}")
+            return stats
+
+    # 在Neo4jExecutor类中添加参数处理
+    def execute_cypher(self, cypher_script: str, params: dict = None) -> dict:
+        """支持参数化查询"""
+        if params is None:
+            params = {}
+
+        try:
+            result = self.graph.run(cypher_script, parameters=params)
+            return result.stats()
+        except Exception as e:
+            print(f"执行失败: {str(e)}")
+            return {}
+
+    def _execute_single(self, tx: Transaction, stmt: str):
+        """执行单个语句"""
+        try:
+            tx.run(stmt)
+        except Exception as e:
+            if 'already exists' in str(e):
+                print(f"忽略已存在的约束: {stmt[:50]}...")
+            else:
+                raise
+
+    def _retry_single(self, stmt: str) -> bool:
+        """重试单个语句"""
+        try:
+            self.graph.run(stmt)
+            return True
+        except Exception as e:
+            print(f"语句执行失败: {stmt[:60]}... \n错误信息: {str(e)}")
+            return False
+
+
+# 使用示例
+if __name__ == "__main__":
+    # 初始化执行器
+    executor = Neo4jExecutor(
+        uri="neo4j://10.10.21.20:7687",
+        auth=("neo4j", "DsideaL4r5t6y7u")
+    )
+
+    # 执行Cypher文件
+    result = executor.execute_cypher_file("knowledge_graph.cypher")
+
+    print(f"\n执行结果：")
+    print(f"- 总语句数: {result['total']}")
+    print(f"- 成功: {result['success']}")
+    print(f"- 失败: {result['failed']}")
+    print(f"- 耗时: {result['duration']}秒")

AI/Neo4j/knowledge_graph.cypher

@@ -1,4 +1,39 @@
-CREATE (r1:Rectangle {id: 1, length: 10, width: 7.5, description: '小长方形'})
+// 约束
-CREATE (big:Rectangle {id: 2, length: 30, width: 17.5, perimeter: 95, description: '由7个小长方形拼接而成的大长方形'})
+CREATE CONSTRAINT IF NOT EXISTS FOR (kp:KnowledgePoint) REQUIRE kp.id IS UNIQUE;
-CREATE (r1)-[:PART_OF {quantity: 3, orientation: '横向'}]->(big)
+CREATE CONSTRAINT IF NOT EXISTS FOR (ab:AbilityPoint) REQUIRE ab.id IS UNIQUE;
-CREATE (r1)-[:PART_OF {quantity: 4, orientation: '纵向'}]->(big)
+
+// 索引 (修正版)
+CREATE FULLTEXT INDEX questionContent IF NOT EXISTS
+FOR (q:Question)
+ON EACH [q.content];
+
+// 节点 (替换参数)
+MERGE (q:Question {id: "a1b2c3d4"})
+SET q.content = "巧求周长：7个相同小长方形拼成大长方形，小长方形长10厘米，求大长方形周长",
+    q.difficulty = 3;
+
+MERGE (kp:KnowledgePoint {id: "KP_101"})
+SET kp.name = "长方形周长计算",
+    kp.level = "小学";
+
+MERGE (ab:AbilityPoint {id: "AB_025"})
+SET ab.name = "图形拼接分析",
+    ab.category = "几何推理";
+
+// 关系 (使用具体ID)
+MATCH (q:Question {id: "a1b2c3d4"}), (kp:KnowledgePoint {id: "KP_101"})
+MERGE (q)-[r:TESTS_KNOWLEDGE]->(kp)
+SET r.weight = 0.8,
+    r.created_at = timestamp();
+
+MATCH (q:Question {id: "a1b2c3d4"}), (ab:AbilityPoint {id: "AB_025"})
+MERGE (q)-[r:REQUIRES_ABILITY]->(ab)
+SET r.weight = 0.7,
+    r.created_at = timestamp();
+
+MERGE (s:Shape {id: "FIG_007"})
+SET s.type = "复合长方形结构";
+
+MATCH (q:Question {id: "a1b2c3d4"}), (s:Shape {id: "FIG_007"})
+MERGE (q)-[c:CONSISTS_OF]->(s)
+SET c.weight = 1.0;

AI/Neo4j/result.txt

@@ -1,35 +0,0 @@
-**知识点与能力点分析：**
-
-1. **几何图形认知**：理解长方形的基本属性（长、宽、周长）。
-2. **空间想象能力**：通过文字描述想象图形的拼接方式，构建几何模型。
-3. **代数应用**：设定未知数，建立方程求解小长方形的宽。
-4. **逻辑推理**：通过面积或边长的等量关系推导变量，整合信息得出最终周长。
-5. **问题分解**：将复杂图形问题拆解为小长方形的排列组合与尺寸计算。
-
----
-
-**Neo4j 5.26.2 中文插入语句：**
-
-```cypher
-// 创建小长方形节点
-CREATE (s1:小长方形 {名称: '小长方形1', 长: 10, 宽: 7.5}),
-       (s2:小长方形 {名称: '小长方形2', 长: 10, 宽: 7.5}),
-       (s3:小长方形 {名称: '小长方形3', 长: 10, 宽: 7.5}),
-       (s4:小长方形 {名称: '小长方形4', 长: 10, 宽: 7.5}),
-       (s5:小长方形 {名称: '小长方形5', 长: 10, 宽: 7.5}),
-       (s6:小长方形 {名称: '小长方形6', 长: 10, 宽: 7.5}),
-       (s7:小长方形 {名称: '小长方形7', 长: 10, 宽: 7.5});
-
-// 创建大长方形节点
-CREATE (b:大长方形 {名称: '拼接后的大长方形', 长: 30, 宽: 17.5, 周长: 95});
-
-// 建立拼接关系
-MATCH (s1:小长方形), (s2:小长方形), (s3:小长方形), (s4:小长方形), 
-      (s5:小长方形), (s6:小长方形), (s7:小长方形), (b:大长方形)
-WHERE s1.名称 IN ['小长方形1', '小长方形2', '小长方形3'] 
-  AND s2.名称 IN ['小长方形4', '小长方形5', '小长方形6', '小长方形7']
-CREATE (s1)-[:横向拼接]->(b),
-       (s2)-[:纵向拼接]->(b);
-```
-
-**答案：拼成的大长方形的周长是95厘米。**

AI/Test/HwTest2.py

@@ -0,0 +1,42 @@
+# coding=utf-8
+
+import requests
+import json
+
+import urllib3
+
+from Config import *
+
+if __name__ == '__main__':
+    # 禁止警告
+    urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
+
+    # Send request.
+    headers = {
+        'Content-Type': 'application/json',
+        'Authorization': 'Bearer ' + HW_API_KEY  # 把yourApiKey替换成真实的API Key
+    }
+    # 系统提示词
+    system_prompt = '''回答以下内容:
+    1. 这道题目有哪些知识点，哪些能力点
+    2. 生成Neo4j 5.26.2的插入语句'''
+
+    shiti_content = '''
+        下面是一道小学三年级的数学题目，巧求周长：
+        把7个完全相同的小长方形拼成如图的样子，已知每个小长方形的长是10厘米，则拼成的大长方形的周长是多少厘米？    
+        '''
+    data = {
+        "model": HW_MODEL_NAME,
+        "max_tokens": 10000,
+        "messages": [
+            {"role": "system", "content": system_prompt},
+            {"role": "user", "content": shiti_content}
+        ],
+        "stream": False,
+        "temperature": 1.0
+    }
+    resp = requests.post(HW_API_URL, headers=headers, data=json.dumps(data), verify=False)
+
+    # Print result.
+    print(resp.status_code)
+    print(resp.text)