'commit'

AI/A1_GenerateMarkdown.py

@@ -25,7 +25,7 @@ class MarkdownGenerator:
         self.course_name = course_name
         self.template_path = template_path or DEFAULT_TEMPLATE
         self.output_path = output_path or DEFAULT_OUTPUT_DIR / f"{course_name}.md"
-        self.client = OpenAI(api_key=API_KEY, base_url=MODEL_URL)  # 初始化OpenAI客户端
+        self.client = OpenAI(api_key=MODEL_API_KEY, base_url=MODEL_URL)  # 初始化OpenAI客户端
 
         self._validate_paths()
 
@@ -55,7 +55,7 @@ class MarkdownGenerator:
         )
 
         return self.client.chat.completions.create(
-            model=MODEL_R1,
+            model=MODEL_NAME,
             messages=[
                 {"role": "system", "content": system_prompt},
                 {"role": "user", "content": f"请生成《{self.course_name}》教学大纲"}

AI/B2_WavToText.py

@@ -1,13 +1,12 @@
 # -*- coding: utf-8 -*-
 import json
 import time
-from pathlib import Path
 from typing import Dict, Tuple
 
 from aliyunsdkcore.acs_exception.exceptions import ClientException, ServerException
 from aliyunsdkcore.client import AcsClient
 from aliyunsdkcore.request import CommonRequest
-
+from Config import *
 # 服务常量配置
 CONFIG = {
     "REGION_ID": "cn-shanghai",
@@ -169,8 +168,8 @@ def transcribe_audio_file(
 def ShiBie(audio_url, output_path):
     # 配置参数（应通过环境变量或配置文件获取）
     CREDENTIALS = {
-        "access_key_id": "LTAI5tE4tgpGcKWhbZg6C4bh",
+        "access_key_id": ALY_AK,
-        "access_key_secret": "oizcTOZ8izbGUouboC00RcmGE8vBQ1",
+        "access_key_secret": ALY_SK,
         "app_key": "OIpiw501l4o6MYEe",
         "audio_url":audio_url,
         "output_path": output_path

AI/B3_TextSummarize.py

@@ -1,5 +1,4 @@
 # -*- coding: utf-8 -*-
-from pathlib import Path
 from typing import Optional, Tuple, Iterator
 from openai import OpenAI, APIError, APITimeoutError
 import time
@@ -11,9 +10,9 @@ class ContentAnalyzer:
 
     def __init__(
             self,
-            api_key: str = API_KEY,
+            api_key: str = MODEL_API_KEY,
             base_url: str = MODEL_URL,
-            model: str = MODEL_R1,
+            model: str = MODEL_NAME,
             max_retries: int = 10,
             initial_timeout: int = 300
     ):

AI/C1_RecognizeHandwriting.py

@@ -8,6 +8,7 @@ from alibabacloud_ocr_api20210707 import models as ocr_api_20210707_models
 from alibabacloud_ocr_api20210707.client import Client as ocr_api20210707Client
 from alibabacloud_tea_openapi import models as open_api_models
 from alibabacloud_tea_util import models as util_models
+from Config import *
 
 
 class RecognizeHandwriting:
@@ -18,8 +19,8 @@ class RecognizeHandwriting:
     def create_client() -> ocr_api20210707Client:
         # 安全建议：建议将密钥移到环境变量中
         config = open_api_models.Config(
-            access_key_id=os.getenv('ALIYUN_ACCESS_KEY', 'LTAI5tE4tgpGcKWhbZg6C4bh'),
+            access_key_id=ALY_AK,
-            access_key_secret=os.getenv('ALIYUN_ACCESS_SECRET', 'oizcTOZ8izbGUouboC00RcmGE8vBQ1')
+            access_key_secret=ALY_SK
         )
         config.endpoint = f'ocr-api.cn-hangzhou.aliyuncs.com'
         return ocr_api20210707Client(config)

AI/C2_CheckZuoWen.py

@@ -8,7 +8,7 @@ from Config import *
 class EnglishEssayAnalyzer:
     def __init__(self):
         self.client = OpenAI(
-            api_key=API_KEY,
+            api_key=MODEL_API_KEY,
             base_url=MODEL_URL
         )
 
@@ -28,7 +28,7 @@ class EnglishEssayAnalyzer:
         """流式分析作文（新增关键方法）"""
         try:
             stream = self.client.chat.completions.create(
-                model=MODEL_R1,
+                model=MODEL_NAME,
                 messages=[{
                     "role": "user",
                     "content": self._build_prompt(essay)

AI/Config.py

@@ -1,17 +1,22 @@
 from pathlib import Path
 
-# 阿里云中用来调用deepseek r1的密钥
-API_KEY = "sk-01d13a39e09844038322108ecdbd1bbc"
-
 # 固定配置项
-MODEL_R1 = "deepseek-r1"
+# 阿里云中用来调用deepseek r1的密钥
-MODEL_V3 = "deepseek-v3"
+MODEL_API_KEY = "sk-01d13a39e09844038322108ecdbd1bbc"
+MODEL_NAME = "deepseek-r1"
+#MODEL_NAME='qwen-plus'
 MODEL_URL='https://dashscope.aliyuncs.com/compatible-mode/v1'
 
+# 华为云
+HW_API_KEY='2R7vrjfIZO1chcfk4V3zDscx2Ms4I4kdoY7XSFnxa8Z2RNfAztg8qrXXKkwJGZWvMtS4qnN782WmaY4xZfMhyg'
+HW_API_URL= url = "https://infer-modelarts-cn-southwest-2.modelarts-infer.com/v1/infers/952e4f88-ef93-4398-ae8d-af37f63f0d8e/v1/chat/completions"
+HW_MODEL_NAME='DeepSeek-R1'
+
+# 阿里云的配置信息
+ALY_AK='LTAI5tE4tgpGcKWhbZg6C4bh'
+ALY_SK='oizcTOZ8izbGUouboC00RcmGE8vBQ1'
+
 # 正确路径拼接方式
 mdWorkingPath = Path(__file__).parent / 'md-file' / 'readme'
 DEFAULT_TEMPLATE = mdWorkingPath / 'default.md'  # 使用 / 运算符
 DEFAULT_OUTPUT_DIR = mdWorkingPath / 'output'   # 使用 / 运算符
-
-# print(f"模板路径：{DEFAULT_TEMPLATE}")
-# print(f"输出目录：{DEFAULT_OUTPUT_DIR}")

AI/Neo4j/KnowledgeGraph.py

@@ -1,35 +1,57 @@
 # -*- coding: utf-8 -*-
+import re
 import time
 from typing import Iterator, Tuple
 from openai import OpenAI
 from openai.types.chat import ChatCompletionChunk
-from Config import API_KEY, MODEL_R1, MODEL_URL
+from Config import *
 
 
 class KnowledgeGraph:
-    def __init__(self, content: str):
+    def __init__(self, shiti_content: str):
-        self.content = content
+        self.shiti_content = shiti_content
-        self.client = OpenAI(api_key=API_KEY, base_url=MODEL_URL)
+        self.client = OpenAI(api_key=HW_API_KEY, base_url=HW_API_URL)
 
     def _generate_stream(self) -> Iterator[ChatCompletionChunk]:
+        """流式生成内容"""
         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'''
         return self.client.chat.completions.create(
-            model=MODEL_R1,
+            model=MODEL_NAME,
             messages=[
                 {"role": "system", "content": system_prompt},
-                {"role": "user", "content": self.content}
+                {"role": "user", "content": self.shiti_content}
             ],
             stream=True,
             timeout=300
         )
 
-    def run(self) -> Tuple[bool, str]:
+    def _extract_cypher(self, content: str) -> str:
-        """执行生成流程（返回状态和完整内容）"""
+        """从内容中提取Cypher语句（修正版）"""
+        # 匹配包含cypher的代码块（支持可选语言声明）
+        pattern = r"```(?:cypher)?\n(.*?)```"
+        matches = re.findall(pattern, content, re.DOTALL)
+
+        processed = []
+        for block in matches:
+            # 清理每行：移除注释和首尾空格
+            cleaned_lines = []
+            for line in block.split('\n'):
+                line = line.split('//')[0].strip()  # 移除行尾注释
+                if line:  # 保留非空行
+                    cleaned_lines.append(line)
+            if cleaned_lines:
+                processed.append('\n'.join(cleaned_lines))
+
+        return ';\n\n'.join(processed) if processed else ""
+
+    def run(self) -> Tuple[bool, str, str]:
+        """执行生成流程（返回状态、完整内容、Cypher语句）"""
         start_time = time.time()
         spinner = ['⠋', '⠙', '⠹', '⠸', '⠼', '⠴', '⠦', '⠧', '⠇', '⠏']
         content_buffer = []
+        cypher_script = ""
 
         try:
             print(f"🚀 开始生成知识点和能力点的总结和插入语句")
@@ -48,16 +70,20 @@ class KnowledgeGraph:
 
             if content_buffer:
                 full_content = ''.join(content_buffer)
+                cypher_script = self._extract_cypher(full_content)
+
                 print(f"\n\n✅ 生成成功！耗时 {int(time.time() - start_time)}秒")
                 print("\n================ 完整结果 ================")
                 print(full_content)
-                print("========================================")
+                print("\n================ Cypher语句 ===============")
-                return True, full_content
+                print(cypher_script if cypher_script else "未检测到Cypher语句")
-            return False, ""
+                print("==========================================")
+                return True, full_content, cypher_script
+            return False, "", ""
 
         except Exception as e:
             print(f"\n\n❌ 生成失败：{str(e)}")
-            return False, str(e)
+            return False, str(e), ""
 
 
 if __name__ == '__main__':
@@ -66,9 +92,9 @@ if __name__ == '__main__':
     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？    
     '''
     kg = KnowledgeGraph(shiti_content)
-    success, result = kg.run()  # 获取返回结果
+    success, result, cypher = kg.run()
 
-    # 如果需要进一步处理结果
+    if success and cypher:
-    if success:
+        with open("knowledge_graph.cypher", "w", encoding="utf-8") as f:
-        with open("result.txt", "w", encoding="utf-8") as f:
+            f.write(cypher)
-            f.write(result)
+        print("\nCypher语句已保存至 knowledge_graph.cypher")

AI/Neo4j/knowledge_graph.cypher

@@ -0,0 +1,4 @@
+CREATE (r1:Rectangle {id: 1, length: 10, width: 7.5, description: '小长方形'})
+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 (r1)-[:PART_OF {quantity: 3, orientation: '横向'}]->(big)
+CREATE (r1)-[:PART_OF {quantity: 4, orientation: '纵向'}]->(big)

AI/Neo4j/result.txt

@@ -0,0 +1,35 @@
+**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/HwTest.py

@@ -0,0 +1,32 @@
+# 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
+    }
+    data = {
+        "model": HW_MODEL_NAME,
+        "max_tokens": 20,
+        "messages": [
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": "你好"}
+        ],
+        "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)