From a08f65c960790f7363b89f1ec44745bf23c7e746 Mon Sep 17 00:00:00 2001 From: macbook-maxwell Date: Thu, 27 Nov 2025 22:38:55 +0800 Subject: [PATCH] update --- ...数学题目分析与验证（后端）.md | 184 ++++++++++++------ 1 file changed, 121 insertions(+), 63 deletions(-) rename 数学图谱后端接口定义.md => MathVerify Pro智能数学题目分析与验证（后端）.md (89%) diff --git a/数学图谱后端接口定义.md b/MathVerify Pro智能数学题目分析与验证（后端）.md similarity index 89% rename from 数学图谱后端接口定义.md rename to MathVerify Pro智能数学题目分析与验证（后端）.md index 6d8ffbf..0c00c5c 100644 --- a/数学图谱后端接口定义.md +++ b/MathVerify Pro智能数学题目分析与验证（后端）.md @@ -1,8 +1,30 @@ +# 应用简介 +MathVerify Pro智能数学题目分析与验证系统，是用于高中数学题目分析的工具，主要是通过把试卷切割成一小题一小题的题目，并通过AI分析题目所涉及的知识点和方法，再通过人工验证，一方面来确定AI的分析正确与否；另一方面，可以把这些数学题的正确的知识点方法存储起来，用于后期知识库、知识图谱的使用，以及AI Agent或数学模型的使用。 -## 外部接口 +MathVerify Pro智能数学题目分析与验证系统分为前端和后端两部分。 +前端又分为：试卷分析和题目验证两部分。参考前端代码和前端部分的README.md -> 外部接口，是后端应用程序请求的外部api，不是提供给前端直接使用的。后端请求了这些api以后还要进行处理后，再提供给前端使用。 +## 后端应用程序的工作流程： +### 试卷分析过程： +1. 从前端接收一张或多张试卷的图片（PNG或JPG）； +2. 保存到本地文件夹； +3. 逐张发送给`分割试卷API`，把整张试卷分割成一张张的题目图片（简称小题图片）； +4. 逐张发送每张小题图片到`ocr api`； +5. 把ocr的结果，发送到`题目分析api`； +6. 把小题图片（需转换为base64）、ocr结果的文本内容、题目分析api，存入数据库；暂时存到sqlite3中； +7. 每一小题存储完成后，就发送到前端，用于显示题目和分析结果； +8. 一张卷子完成以后，发送给前端一个单张卷子任务完成的通知； +9. 所有卷子都完成以后，发送给前端，所有任务完成的通知。 + +### 题目验证过程： +1. 前端从数据库中（通过接口）读取未验证的题目，每次10条； +2. 前端更新修改后的数据，并修改标记位为已验证。后端更新完成后，发送通知。 +3. + +## 涉及到的外部接口 + +> 外部接口，是后端应用程序请求的外部api，不是提供给前端直接使用的api。后端请求了这些api以后还要进行处理后，再提供给前端使用。 ### 1. 分割试卷API: @@ -400,7 +422,7 @@ https://ekt1.suzhou.edu.cn/autocut/files/20251125_082929_f1975f5c/question_003.j https://ekt1.suzhou.edu.cn/autocut/files/20251125_082929_f1975f5c/question_014.jpg ``` -question_id 也需要记录。其他字段忽略. +question_id 也需要记录。其他字段可忽略. 返回错误包括:只支持图片格式: { @@ -416,6 +438,8 @@ question_id 也需要记录。其他字段忽略. ### 2. ocr api： +注意：这是一个ai模型接口，可能会存在一些不可预知的错误，需要做好错误处理，比如，返回的内容 "content"字段中，有可能带上markdown标记，也有可能不带。模型有可能因超时或其他原因，返回错误。请合理处理错误。 + 输入：上面的切割试卷api所生成的url； 输出：markdown形式的带有数学公式的题目文本内容。 大模型api地址：https://ekt1.suzhou.edu.cn/llm/v1/chat/completions @@ -424,6 +448,7 @@ openai兼容格式 上传需要先把url解析成base64。模型不能直接识别url。 设定温度为0； 设定提示词是： + ``` 你是一名数学文字识别专家。你的任务是，将图片中的文字，严格转换为markdown格式的文字；如图中有数学公式，你必须使用$或者$$进行包裹，生成markdown可解析的latex格式的数学公式；你无需输出其他任何解释性文字，只需严格输出图片中的文字。 ``` @@ -506,9 +531,9 @@ openai兼容格式 ### 3. 题目分析api： - **请求方式:** POST - + - **请求URL**:` https://aimaster.apps.k8s.aiscenes.cn/dev-api/aimaster/scenario/open/api` - + `https://aimaster.apps.k8s.aiscenes.cn/`为域名 /dev-api/ 是测试环境, 目前只有测试环境 @@ -516,28 +541,28 @@ openai兼容格式 /aimaster/scenario/open/api 为固定后缀 - **request**: - + header参数说明: -| 字段名 | 类型 | 说明 | -| ------------- | ------ | ----------------------------------------------------------------- | -| Authorization | String | token登录获取,给固定值Bearer W/cbr9kftZmnpOqxAfiLvRVZx2+9Lf6X9I9FS+t0zK4= | -| | | | +| 字段名 | 类型 | 说明 | +| ------------- | ------ | ------------------------------------------------------------ | +| Authorization | String | token登录获取,给固定值Bearer wo54FKODEaPi9ip3NbjbE0/2YtIom1oyQXvlvqsLEpc= | +| | | | 样例: -Authorization:Bearer W/cbr9kftZmnpOqxAfiLvRVZx2+9Lf6X9I9FS+t0zK4= +Authorization:Bearer wo54FKODEaPi9ip3NbjbE0/2YtIom1oyQXvlvqsLEpc= body参数说明: -|字段名|类型|说明| -|---|---|---| -|chatId|String|对话主键,uuid自己生成,同一个id表示一次对话| -|scenarioInfoId|String|场景中心主键| -|latestMessageContent|String|用户最后一次提问| -|params|Object|应用的自定义参数,| - +| 字段名 | 类型 | 说明 | +| -------------------- | ------ | ------------------------------------------ | +| chatId | String | 对话主键,uuid自己生成,同一个id表示一次对话 | +| scenarioInfoId | String | 场景中心主键 | +| latestMessageContent | String | 用户最后一次提问 | +| params | Object | 应用的自定义参数, | + 样例: ```json { @@ -555,159 +580,192 @@ body参数说明: "scenarioInfoId": "e6e822e47fa24ca380f8d2d09eb114a7" } - ``` + ``` + - - **response** - + 1. **流式传输**：采用`data:` 前缀+JSON对象的分块传输格式 - + 样例: - ​ + ``` data: {"id":"AI Master","choices":[{"delta":{"content":null,"function_call":null,"refusal":null,"role":null,"tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1741340356,"model":"ai-master","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":null,"usage":null,"step":null,"agent_step":"Agent Start","agent_id":"d9bdca85-6dce-4dc9-833a-9b3c15a4603b","agent_name":"企业办事指南","function":null} - ​ + data: {"id":"chatcmpl-B8PGrW9oyk1P3EiKUHwffLhIxpVg6","choices":[{"delta":{"content":"","function_call":null,"refusal":null,"role":"assistant","tool_calls":null},"finish_reason":null,"index":0,"logprobs":null}],"created":1741343465,"model":"gpt-4o-2024-11-20","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":"fp_b705f0c291","usage":null,"step":"AI Start","agent_step":"Agent Starting","agent_id":"d9bdca85-6dce-4dc9-833a-9b3c15a4603b","agent_name":"企业办事指南","function":null} - 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​ + data: {"id":"01957028d0affb338184706545d352a0","choices":[{"delta":{"content":null,"function_call":null,"refusal":null,"role":"assistant","tool_calls":null,"reasoning_content":"迁"},"finish_reason":null,"index":0,"logprobs":null,"content_filter_results":{"hate":{"filtered":false},"self_harm":{"filtered":false},"sexual":{"filtered":false},"violence":{"filtered":false}}}],"created":1741343478,"model":"Pro/deepseek-ai/DeepSeek-R1","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":"","usage":{"completion_tokens":10,"prompt_tokens":13819,"total_tokens":13829,"completion_tokens_details":null,"prompt_tokens_details":null},"step":"AI Start","agent_step":"Agent Starting","agent_id":"2a9ae314-164c-4771-b250-8043416a12c3","agent_name":"企业变更助手","function":null} - ​ + data: {"id":"01957028d0affb338184706545d352a0","choices":[{"delta":{"content":null,"function_call":null,"refusal":null,"role":"assistant","tool_calls":null,"reasoning_content":"址所需"},"finish_reason":null,"index":0,"logprobs":null,"content_filter_results":{"hate":{"filtered":false},"self_harm":{"filtered":false},"sexual":{"filtered":false},"violence":{"filtered":false}}}],"created":1741343478,"model":"Pro/deepseek-ai/DeepSeek-R1","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":"","usage":{"completion_tokens":12,"prompt_tokens":13819,"total_tokens":13831,"completion_tokens_details":null,"prompt_tokens_details":null},"step":"AI Start","agent_step":"Agent Starting","agent_id":"2a9ae314-164c-4771-b250-8043416a12c3","agent_name":"企业变更助手","function":null} - ​ + data: {"id":"01957028d0affb338184706545d352a0","choices":[{"delta":{"content":null,"function_call":null,"refusal":null,"role":"assistant","tool_calls":null,"reasoning_content":"材料"},"finish_reason":null,"index":0,"logprobs":null,"content_filter_results":{"hate":{"filtered":false},"self_harm":{"filtered":false},"sexual":{"filtered":false},"violence":{"filtered":false}}}],"created":1741343478,"model":"Pro/deepseek-ai/DeepSeek-R1","object":"chat.completion.chunk","service_tier":null,"system_fingerprint":"","usage":{"completion_tokens":13,"prompt_tokens":13819,"total_tokens":13832,"completion_tokens_details":null,"prompt_tokens_details":null},"step":"AI Start","agent_step":"Agent Starting","agent_id":"2a9ae314-164c-4771-b250-8043416a12c3","agent_name":"企业变更助手","function":null} - ​ + data: [DONE] ``` - ​ + + +你需要把流式的response 合并。 + +返回的格式是： + +{ + "input_problem_summary": "简要概括题目（不超过20字）", + "analysis": { + "knowledges": [ + "题目所涉及到的知识点1", + "题目所涉及到的知识点2" + ], + "methods": [ + "题目所涉及到的解题方法1", + "题目所涉及到的解题方法2" + ] + } +} + +输出example： +```json +{ + "input_problem_summary": "已知对数函数含参单调性求参数范围", + "analysis": { + "knowledges": [ + "导数及其应用 - 导数在研究函数中的应用 - 利用导数研究函数的单调性", + "基本初等函数 - 对数函数 - 对数函数的导数" + ], + "methods": [ + "转化与化归思想", + "分离参数法", + "不等式恒成立问题求解" + ] + } +} +``` +注意：虽然prompt已经严格要求输出的内容是json格式，但是有可能AI会增加前面或后面的一些解释，也有可能加入markdown的json代码头，或者直接以`{}`开头，或者以引号开头。你需要预处理这些内容， 以使存储的和给到前端的数据是正确的json格式。 +## 存储 -## 后端处理 - -### 存储 - -使用sqlite3 ，直接存储；（知识点、方法，使用sqlite3 的JSON 存储，示例：存入时存为 ["apple", "banana", "cherry"]，ORM 映射为 List/Array） - -存储切割后的照片base64、原始照片的sessionId、切割后照片的questionId、题目的markdown格式文本（ocr后）、题目的知识点json、题目的方法json，是否verified， updated 知识点（如有）；updated 方法（如有），以及其他必要字段； +使用sqlite3 ，直接存储；（知识点、方法，使用sqlite3 的JSON 存储，示例：存入时存为 ["apple", "banana", "cherry"]，ORM 映射为 List/Array） +存储切割后的照片base64、原始照片的sessionId、切割后照片的questionId、题目的markdown格式文本（ocr后）、题目的知识点json、题目的方法json，是否verified， updated 知识点（如有）；updated 方法（如有），以及其他必要字段； \ No newline at end of file