简历炼金术 是一款基于 AI 的智能简历优化工具,帮助求职者打造更具竞争力的简历。通过 AI 分析、毒舌点评、STAR 法则润色和职位匹配等功能,让你的简历脱颖而出。
| 功能 | 描述 |
|---|---|
| 🔍 智能诊断 | 综合评分 + 六维雷达图,全面分析简历质量 |
| 🎯 毒舌点评 | 犀利幽默的 HR 视角点评,直击痛点 |
| ✍️ AI 润色 | 基于 STAR 法则的专业润色,支持流式输出实时显示 |
| 🎯 职位匹配 | JD 关键词对比,精准优化建议 |
| ⚡ 单句润色 | 快速优化单个句子,支持标准/数据/专家三种模式,流式响应 |
| 📄 简历导出 | 支持多种模板,一键导出 PDF |
| 📁 文件导入 | 支持导入 Markdown/TXT 文件,拖拽上传 |
技术类
- 💻 技术/程序员
- 🖥️ 运维/SRE
- 🛡️ 网络安全
- 🐛 测试工程师
产品与设计
- 📦 产品经理
- 🎨 UI/UX 设计师
业务与职能
- 📊 数据分析师
- 📢 市场/运营
- 💼 销售
- 👥 人力资源
- 🧮 会计/财务
- 前端: React 18 + TypeScript + Vite
- 样式: Tailwind CSS + shadcn/ui
- 动画: Framer Motion
- 后端: Supabase Edge Functions
- AI: 硅基流动 API (SiliconFlow)
- 数据库: Supabase PostgreSQL
# 克隆项目
git clone <your-repo-url>
cd resume-alchemy
# 安装依赖
npm install
# 启动开发服务器
npm run dev├── src/
│ ├── components/ # React 组件
│ │ ├── ui/ # shadcn/ui 基础组件
│ │ ├── resume-templates/ # 简历模板
│ │ ├── AnalysisResult.tsx
│ │ ├── PolishEditor.tsx
│ │ ├── JDMatcher.tsx
│ │ └── ...
│ ├── hooks/ # 自定义 Hooks
│ │ └── useResumeAI.ts # AI 功能 Hook
│ ├── lib/ # 工具函数
│ ├── pages/ # 页面组件
│ └── integrations/ # 第三方集成
├── supabase/
│ ├── functions/ # Edge Functions
│ │ └── resume-ai/ # AI 处理函数
│ └── config.toml # Supabase 配置
├── docs/
│ └── DEPLOYMENT.md # 自部署教程
└── public/ # 静态资源
项目使用 Supabase Secrets 管理敏感配置:
| 变量名 | 说明 |
|---|---|
SILICONFLOW_API_KEY |
硅基流动 API 密钥 |
SILICONFLOW_MODEL |
AI 模型名称 (如 Qwen/Qwen3-8B) |
- 选择行业 - 首页选择你的目标职业
- 上传简历 - 粘贴简历内容
- 查看分析 - AI 会给出评分、点评和改进建议
- 润色简历 - 使用 AI 润色功能优化内容
- 职位匹配 - 输入 JD 进行匹配度分析
- 导出简历 - 选择模板导出 PDF
- ✅ API 密钥存储在服务器端,前端不可见
- ✅ 基于 IP 的速率限制(每分钟 10 次)
- ✅ 模型名称服务器端配置,防止滥用
详细的自部署教程请查看 docs/DEPLOYMENT.md
Resume Alchemy is an AI-powered intelligent resume optimization tool that helps job seekers create more competitive resumes. With AI analysis, brutally honest reviews, STAR method polishing, and job matching features, make your resume stand out.
| Feature | Description |
|---|---|
| 🔍 Smart Diagnosis | Comprehensive scoring + 6-dimension radar chart |
| 🎯 Roast Review | Sharp and humorous HR perspective feedback |
| ✍️ AI Polish | Professional polishing based on STAR method with streaming output |
| 🎯 Job Matching | JD keyword comparison with optimization suggestions |
| ⚡ Quick Polish | Fast single sentence optimization with 3 modes, streaming response |
| 📄 Resume Export | Multiple templates, one-click PDF export |
| 📁 File Import | Support Markdown/TXT file import, drag & drop upload |
Tech
- 💻 Tech/Programmer
- 🖥️ DevOps/SRE
- 🛡️ Cyber Security
- 🐛 QA/Test Engineer
Product & Design
- 📦 Product Manager
- 🎨 UI/UX Designer
Business & Functional
- 📊 Data Analyst
- 📢 Marketing/Operations
- 💼 Sales
- 👥 Human Resources
- 🧮 Accountant/Finance
- Frontend: React 18 + TypeScript + Vite
- Styling: Tailwind CSS + shadcn/ui
- Animation: Framer Motion
- Backend: Supabase Edge Functions
- AI: SiliconFlow API
- Database: Supabase PostgreSQL
# Clone the project
git clone <your-repo-url>
cd resume-alchemy
# Install dependencies
npm install
# Start development server
npm run dev├── src/
│ ├── components/ # React components
│ │ ├── ui/ # shadcn/ui base components
│ │ ├── resume-templates/ # Resume templates
│ │ └── ...
│ ├── hooks/ # Custom Hooks
│ ├── lib/ # Utility functions
│ ├── pages/ # Page components
│ └── integrations/ # Third-party integrations
├── supabase/
│ ├── functions/ # Edge Functions
│ │ └── resume-ai/ # AI processing function
│ └── config.toml # Supabase config
├── docs/
│ └── DEPLOYMENT.md # Self-deployment guide
└── public/ # Static assets
The project uses Supabase Secrets for sensitive configurations:
| Variable | Description |
|---|---|
SILICONFLOW_API_KEY |
SiliconFlow API key |
SILICONFLOW_MODEL |
AI model name (e.g., Qwen/Qwen3-8B) |
- Select Industry - Choose your target profession
- Upload Resume - Paste your resume content
- View Analysis - AI provides scoring, reviews, and suggestions
- Polish Resume - Use AI to optimize content
- Job Matching - Input JD for matching analysis
- Export Resume - Choose template and export to PDF
- ✅ API keys stored server-side, invisible to frontend
- ✅ IP-based rate limiting (10 requests per minute)
- ✅ Model name configured server-side to prevent abuse
For detailed self-deployment instructions, see docs/DEPLOYMENT.md
MIT License
Contributions are welcome! Please feel free to submit a Pull Request.
For questions or suggestions, please open an issue.