中文 | English
🚀 An Apple-style AI-powered technical interview platform to help you improve your coding skills effortlessly
- 🎯 Realistic Interview Experience: Simulates real interview environments with coding challenges and technical questions
- 🍎 Beautiful Apple-Style UI: Elegant, modern, and intuitive interface inspired by Apple's design language
- 🤖 AI-Powered Feedback: Get detailed professional feedback and improvement suggestions powered by OpenAI
- 👨💻 Powerful Code Editor: Supports multiple programming languages, syntax highlighting, customizable themes and font sizes
- 🌐 Multi-Language Support: Practice in English or Chinese
- 📊 Smart Learning: System tracks your mistakes and prioritizes areas you need to strengthen
- 🔄 Flexible Filtering: Quickly skip irrelevant questions with the "Regenerate Question" feature
- 📝 History Tracking: Review past performance and identify areas for improvement
- 💾 Auto-Save: Never lose your progress with automatic saving of answers
- Next.js 15 - Latest React framework
- Tailwind CSS - Utility-first CSS framework
- shadcn/ui - Beautiful UI component library
- OpenAI API - AI-powered question generation and answer evaluation
- Monaco Editor - Same editor used in VS Code
# Clone repository
git clone https://github.com/peanut996/random-interview-platform.git
cd random-interview-platform
# Install dependencies
pnpm install
# Start development server
pnpm run dev
Application will run at http://localhost:3000
In the app's settings menu, configure:
- OpenAI API endpoint (typically
https://api.openai.com/v1
) - Choose model (recommended:
gpt-4o
) - Enter your OpenAI API key
Through the settings panel, you can:
- Select question type: coding problems or conceptual questions
- Customize technical categories: add specific technology areas you want to practice
- Set difficulty level: from easy to hard
- Configure editor: choose theme, font size, and programming language
- Configure OpenAI parameters: endpoint, model, and API key
Through the built-in contribution feature, you can easily add new questions to the platform:
- Text Contribution: Directly paste text content containing interview questions
- URL Contribution: Provide a link to a webpage containing interview questions
- Edit & Confirm: After parsing, you can edit question details including title, type, difficulty and categories
- Automatic Processing: The system will automatically create a Pull Request to help merge your questions into the database
Contributed questions will help all platform users improve their skills.
Built-in Monaco editor (same as VS Code) supporting 12 popular programming languages, multiple editor themes, and real-time code preview.
Enjoy an excellent user experience on any device - desktop, tablet, or mobile.
Get comprehensive scoring and detailed feedback after submitting answers, including suggestions for code correctness, efficiency, and readability.
If you have any questions or suggestions, feel free to:
- Submit a GitHub Issue