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# Prisma-AI: Your Job Search AI Co-pilot
Open source and free. Highlight your project in 3 minutes, match suitable positions with one click, and let the AI Agent help you turn "desired highlights" into "real achievements."
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<a href="README.md">简体中文</a> | <a href="i18n/README-EN.md">English</a>
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---
## 🎯 Why Choose Prisma‑AI
Prisma‑AI addresses the four most troublesome issues in your job search:
1. **Lack of Project Highlights**: Just stacking technical terms without clear substance.
- Use AI to dig deep into your experiences, automatically generate "actionable" highlight plans, and collaborate with you to achieve those highlights.
2. **Irrelevant Resumes**: After applying everywhere, you hear nothing back.
- Built-in job scraping + local vector model for precise matching; each position automatically customizes your resume.
3. **Difficulty in Learning**: Memorizing and forgetting, forgetting and memorizing.
- Question bank + mind maps + Anki integration, allowing you to understand while memorizing, ensuring steady progress without anxiety.
4. **No Answers to Interview Questions**: Just increases anxiety after reading.
- AI auto-completion and structuring, extracting interview questions and standard answers, supporting version management and collaborative iteration.
---
## ✨ What You Can Gain
| Module | Function |
| :------------------------------ | :----------------------------------------------------------------------------------------- |
| **🤖 AI Core** | Based on `Planer-Executor` + `CRAG` + `Human-in-the-loop` architecture, turning "ideas" into "executable plans" |
| | Deeply integrates user project code and domain knowledge base, providing precise context |
| | Supports multi-round user feedback and reflection, continuously optimizing output quality |
| **📄 Resume Optimization** | Deeply analyzes projects, automatically refines copy, and uncovers actionable highlights |
| | AI Agent **realizes** project highlights and functionalities |
| **💼 Job Matching** | Real-time job scraping → local vector retrieval and reordering → one-click to find "better-suited" positions |
| | Automatically rewrites resumes for target positions, increasing confidence in applications |
| **📚 Efficient Learning** | Frontend and backend question banks + mind maps + Anki, tackling understanding and memorization together |
| **📚 Interview Experience Database** | Automatic completion of interview experiences, standard answers, mind maps, and traceability; collaboratively built, becoming stronger with use |
| | [www.pinkprisma.com](https://www.pinkprisma.com) |
| **📦 Convenient Deployment** | Provides `Docker` one-click deployment, zero configuration startup |
---
## 🔎 Real User Cases
See what `prisma-ai` has brought to users
| Category | Document |
| ------------------------------------ | ----------------------------------------------------- |
| Project experience analysis, optimization, highlight extraction | [Project Experience Case](doc/用例：1、项目经验.md) |
| Integration of Anki + mind maps + professional frontend and backend question banks | [Learning Case for Offers](doc/用例：3、anki+思维导图.md) |
| Continuously updating... | |
---
## 📚 Documentation and Tutorials
We have prepared detailed documentation to help you quickly master Prisma-AI.
| Category | Document |
| :------------------- | :---------------------------------------------------------------------------------------- |
| **🚀 Quick Start** | [Complete Environment Setup in 5 Minutes](doc/教程：1、环境配置.md) |
| | [Build Personal Knowledge Base in 3 Minutes](doc/教程：2、知识库构建.md) |
| **💡 Core Workflow** | [Master Project Experience Analysis, Optimization, and Highlight Extraction in 2 Minutes](doc/教程：3、项目经验分析、优化、亮点挖掘.md) |
| | [Master AI Agent Collaboration to Realize Project Highlights in 2 Minutes](doc/教程：4、项目亮点实现.md) |
| | [Get the Most Suitable Positions in 5 Minutes](doc/教程：5、获取匹配自己的岗位.md) |
| | [Customize Resumes for Target Positions in 3 Minutes](doc/教程：6、面向岗位定制简历.md) |
| | [Master Interview Question Bank and Anki Integration in 5 Minutes](doc/教程：7、面试题库和%20anki集成教程.md) |
| **🤔 Methodology** | [How to Write a Good Technical Resume](doc/方法论：1、简历应该怎么写.md) |
| | [Why and How to Use Anki for Efficient Learning](doc/方法论：2、为什么以及如何使用%20anki.md) |
| | [Limitations of AI Tools like Cursor and How to Overcome Them](doc/方法论：3、cursor等AI%20编程工具的局限性及克服.md) |
| **📚 Interview Experience Database** | [Import Question Bank from Hub into Local Anki](doc/hub/教程：1、anki配置.md) |
| | [Report Errors in the Hub Question Bank](doc/hub/教程：2、反馈题库中的错误.md) |
---
## 🚀 Quick Start
### 🐳 Docker (Recommended)
1. **Clone the Repository**
```bash
git clone https://github.com/weicanie/prisma-ai.git && cd prisma-ai
```
2. **Configure the Environment**
- [Complete Environment Setup in 5 Minutes](doc/教程：1、环境配置.md)
3. **Configure Local SBERT Model** (for job matching)
```bash
# Execute in the prisma-ai directory
./scripts/model_setup.sh
```
> **Note**: You need to configure the local model first to use it in the container.
4. **Start the Service**
```bash
# Execute in the prisma-ai directory
./scripts/start.sh
```
5. Access `http://localhost` in your browser to use it!
### 👨💻 Local Development
1. **Clone and Install Dependencies**
```bash
git clone https://github.com/weicanie/prisma-ai.git && cd prisma-ai && pnpm install
```
2. **Configure the Environment**
[Complete Environment Setup in 5 Minutes](doc/教程：1、环境配置.md)
3. **Configure Local Model** (same as Docker steps)
4. Ensure to provide the following via local or container methods:
- mysql (latest container)
- redis (latest container)
- mongodb (latest container)
- minio (2025.4.3 bitbami/minio container)
And configure according to the port numbers and MySQL database names set in the backend environment variable file.
6. **Start the Project**
```bash
# Execute in the root directory of the repository
pnpm run dev
```
---
Version Update:
```bash
# Execute in the root directory of the repository
./scripts/update.sh
```
---
## 🛠️ Tech Stack
| Category | Technology |
| :--------------- | :--------------------------------------------------- |
| **Frontend** | `React` `Vite` `React-Query` `Redux` `TailwindCSS` |
| **Backend** | `Nest.js` `MySQL` `MongoDB` `Redis` |
| **AI Core** | `LangChain` `LangGraph` `fastmcp` `CopilotKit` |
| **DevOps** | `Docker` `Nginx` `Github Action` |
---
## 🤝 Contributions Welcome
Any form of contribution is welcome!
- ⭐ Give the project a **Star**!
- 🤔 Raise issues or suggestions in **Issues**.
- 💡 Submit **Pull Requests** to improve code or documentation.
---
## ⚖️ Disclaimer
1. All data generated from running this project should only be used for reference and learning purposes.
2. AI can also make mistakes; please carefully verify the accuracy of its generated results.
3. The web scraping tools and related functionalities provided by the [project](https://github.com/weicanie/prisma-ai) are limited to scraping data that is fully public and has no access restrictions. Users must bear any legal risks arising from improper use, and the developers are not responsible. The following uses are prohibited:
- (1) Violating the target website's Robots protocol or user terms;
- (2) Engaging in profit-making activities such as commercial competition or data resale;
- (3) High-frequency access that disrupts the normal operation of the website.
- (4) Any actions that violate the relevant laws and regulations of the People's Republic of China, including but not limited to violations of the Criminal Law of the People's Republic of China, General Principles of Civil Law, Anti-Unfair Competition Law, and Cybersecurity Law.
