TermsAI是一个基于AI技术的知识图谱生成工具,只需输入学习主题和概念数量,即可自动生成结构化的知识图谱。该工具帮助用户快速梳理特定领域的关键概念及其之间的关系,是学习新知识、备课教学和研究工作的得力助手。

演示地址:https://termsai.shuaifox.com/

• 智能图谱生成:输入主题和所需概念数量,AI自动生成相关概念及其关系
• 可视化呈现:通过交互式网络图直观展示概念之间的关联
• 概念数量调整:灵活设置5-20个概念的生成量
• 图谱保存:一键下载生成的知识图谱为图片
• 图谱搜索:通过图谱ID查找之前生成的图谱
• 反馈优化:提供满意度反馈,不满意可重新生成
• 概念扩展:支持向已有图谱添加新概念

• 后端:Python、Flask
• 前端:HTML、CSS、JavaScript
• 可视化:vis-network.js
• 数据存储:SQLAlchemy
• AI生成:基于先进的AI大语言模型

• Python 3.7+
• 所需Python包:Flask, SQLAlchemy等

1. 克隆仓库到本地

git clone https://github.com/raphaelxiao/termsai.git
cd termsai

2. 安装依赖

pip install -r requirements.txt

3. 设置

• 在.env文件填写大模型API KEY
• 在configs/client.py设置模型(目前是设置了OPENAI的GPT-4o/4o-mini、SilconFlow的DeepSeek-V3/Qwen2.5-72B-Instruct以及阿里云百炼的deepseek-v3)
• 在configs/model_configs.py选择模型

4. 启动应用

python app.py

5. 访问应用 浏览器打开 http://localhost:5000 即可使用

termsai/
├── app.py # 主应用入口和API
├── utils.py # 工具函数
├── database.py # 数据库管理
├── models.py # 数据模型
├── templates/ # HTML模板
│ └── index.html # 主页面
└── static/ # 静态资源
 ├── css/ # 样式文件
 ├── js/ # JavaScript文件
 └── images/ # 图片资源

移动端

PC端

• 应用内容由AI生成,仅供参考
• 对于复杂主题,生成过程可能需要几分钟时间
• 建议使用现代浏览器以获得最佳体验

• 支持多语言知识图谱生成
• 添加图谱比较功能
• 优化生成速度和质量
• 增加用户自定义样式

MIT

欢迎贡献代码,提出建议或报告问题!

TermsAI is an AI-powered knowledge graph generation tool that automatically creates structured knowledge graphs by simply inputting a learning topic and the desired number of concepts. This tool helps users quickly organize key concepts and their relationships in a specific field, making it an excellent assistant for learning new topics, preparing lessons, and conducting research.

Demo: https://termsai.shuaifox.com/

• Intelligent Graph Generation: Input a topic and the number of concepts needed, and the AI will automatically generate related concepts and their relationships.
• Visualization: Interactive network diagrams intuitively display the relationships between concepts.
• Concept Quantity Adjustment: Flexibly set the number of concepts to generate (5-20).
• Graph Saving: Download the generated knowledge graph as an image with one click.
• Graph Search: Find previously generated graphs using a graph ID.
• Feedback Optimization: Provide satisfaction feedback, and regenerate if unsatisfied.
• Concept Expansion: Support adding new concepts to existing graphs.

• Backend: Python, Flask
• Frontend: HTML, CSS, JavaScript
• Visualization: vis-network.js
• Data Storage: SQLAlchemy
• AI Generation: Based on advanced large language models

• Python 3.7+
• Required Python packages: Flask, SQLAlchemy, etc.

1. Clone the repository to your local machine.

git clone https://github.com/your-username/termsai.git
cd termsai

2. Install dependencies.

pip install -r requirements.txt

3. Start the application.

python app.py

4. Access the application. Open your browser and visit http://localhost:5000 to use the tool.

termsai/
├── app.py # Main application entry and API
├── utils.py # Utility functions
├── database.py # Database management
├── models.py # Data models
├── templates/ # HTML templates
│ └── index.html # Main page
└── static/ # Static resources
 ├── css/ # Style files
 ├── js/ # JavaScript files
 └── images/ # Image resources

Mobile-view

PC-view

• The content generated by the application is for reference only.
• For complex topics, the generation process may take a few minutes.
• It is recommended to use modern browsers for the best experience.

• Support multi-language knowledge graph generation.
• Add graph comparison functionality.
• Optimize generation speed and quality.
• Allow user-defined styles.

MIT

Contributions are welcome! Feel free to contribute code, suggest ideas, or report issues!