Your AI-powered coding mentor for problem-solving & algorithm optimization
- 🎯 Basic Approach: Generate brute-force solutions with clear explanations
- ⚡ Sub-Optimal Solutions: Improve efficiency step by step
- 🏆 Optimal Solutions: Find the most efficient algorithms
- 🔍 Code Verification: Test and validate solutions automatically
- 📚 Notes Generation: Transform code into comprehensive study notes
- 🎨 Interactive UI: Beautiful Streamlit interface with progress tracking
# Clone the repository
git clone https://github.com/ankush0511/AlgoMentor.git
cd AlgoMentor
# Install dependencies
pip install -r requirements.txt
# Set up environment variables
cp .env.example .env
# Add your API keys to .env fileCreate a .env file with:
GROQ_API_KEY=your_groq_api_key
GOOGLE_API_KEY=your_google_api_key
streamlit run main.pyAlgoMentor/
├── 📁 src/ # Source code
│ ├── 📁 agents/ # AI agents for different optimization levels
│ ├── 📁 models/ # Pydantic data models
│ ├── 📁 utils/ # Utility functions
│ ├── 📁 ui/ # User interface components
│ └── 📁 core/ # Core application logic
├── 📁 config/ # Configuration files
├── 📁 tests/ # Test files
├── 📁 docs/ # Documentation
├── 📁 assets/ # Static assets
├── 📄 main.py # Application entry point
├── 📄 requirements.txt # Python dependencies
├── 📄 .env.example # Environment variables template
└── 📄 README.md # Project documentation
- Enter Problem: Paste your DSA problem or use example problems
- Basic Approach: Get brute-force solution with explanation
- Sub-Optimal: Improve the solution step by step
- Optimal: Achieve the most efficient algorithm
- Notes: Generate comprehensive study notes from your code
- Fork the repository
- Create a feature branch
- Make your changes
- Add tests if applicable
- Submit a pull request
- Download the Docker image at
ankush0511/algomentor
This project is licensed under the MIT License.