Vibekstra 🔮

AI-powered single source shortest path using Claude AI.

The project name is an interesting tribute to the classic "Dijkstra" algorithm, emphasizing its essence based on "Vibe" (intuition) rather than deterministic computation.

✨ Features

• AI-Driven: Utilizes Claude's latest models to calculate the shortest path.
• Type-Safe: Uses Pydantic for robust input and output validation.
• Simple Interface: Provides a clean and intuitive function to solve the problem.
• Purely Experimental: This is a fun project. Do NOT use it in any production environment!

🚀 Installation

Once published to PyPI, you can install it using pip:

pip install vibekstra

💡 Usage

1. Set Your API Key

You need to set your Claude API key. It's best to set it as an environment variable.

export CLAUDE_API_KEY="sk-ant-api03-..."

2. Call the Function

Here is a complete, runnable example of how to use vibekstra.

from vibekstra import vibekstra

# 1. Define your graph
n = 4      # The number of vertices
s = 1      # The source vertex

# The list of edges: [start_vertex, end_vertex, weight]
edges = [
    [1, 2, 2],
    [2, 3, 2],
    [2, 4, 1],
    [1, 3, 5],
    [3, 4, 3],
    [1, 4, 4],
]

# 2. Let the AI calculate the shortest paths!
try:
    # Pass the arguments correctly, separated by commas
    distances = vibekstra(n=n, s=s, edges=edges)
    
    print(f"Shortest distances from source {s}: {distances}")
    # Expected output: Shortest distances from source 1: [0, 2, 4, 3]

except Exception as e:
    print(f"An error occurred: {e}")

🧪 Testing (For Developers)

If you have cloned the repository and want to run tests locally:

1. Install the project in editable mode with its dependencies
2. Run pytest from the root directory

# From the project root directory
pip install -e .
pytest

🛠️ Development Setup

# Clone the repository
git clone https://github.com/yourusername/vibekstra.git
cd vibekstra

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Install in development mode
pip install -e .

# Set your Claude API key
export CLAUDE_API_KEY="your-api-key-here"

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.

⚠️ Disclaimer

This project is highly experimental. Its results depend on an external AI service and may be inconsistent, inaccurate, or slow. Never use this in critical systems where reliability and performance are required.

🤝 Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📈 Roadmap

• Support for additional AI models
• Performance benchmarking against traditional algorithms
• Visualization of shortest paths
• Support for directed/undirected graphs
• Web API interface