WDBX is a powerful vector database and embedding management system designed specifically for AI applications. It provides efficient storage, indexing, and retrieval of high-dimensional vector embeddings.
- Fast similarity search with configurable indexing
- Support for various embedding models
- Storage and retrieval of vector embeddings with metadata
- Customizable vector database with pluggable backends
- Comprehensive UI dashboard for visualization and management
- Visualization tools for vector embeddings
- Plugin system for extensibility
# Basic installation
pip install wdbx
# Install with UI components
pip install wdbx[ui]from wdbx import VectorDB
# Create a new vector database
db = VectorDB(dimension=1536)
# Add vectors with metadata
db.add_vector([0.1, 0.2, ...], metadata={"text": "Example text"})
# Find similar vectors
results
8C12
= db.find_similar([0.1, 0.2, ...], top_k=5)WDBX includes a full-featured UI dashboard built with Streamlit that provides visualization and management capabilities for your vector database.
You can launch the UI with:
# Using the CLI (if installed with UI components)
wdbx-ui
# Or directly with Streamlit
streamlit run /path/to/wdbx/ui/streamlit_app.pyThe UI dashboard provides:
- Modular Architecture - Easily extensible with new pages and features
- Vector Visualization - Visualize your vectors in 2D or 3D space using dimensionality reduction
- Similarity Search Interface - Interactive search for similar vectors
- Database Statistics - View and monitor your database metrics
- Theme Customization - Multiple themes including light, dark, and specialized options
- Advanced Settings - Toggle advanced features for power users
The WDBX UI can be easily deployed to Streamlit Cloud for sharing with your team or showcasing your vector database.
- Use the deployment helper script to prepare your files:
python -m wdbx.ui.deployment.deploy_to_cloud --target ./deploy-
Push the generated files to a GitHub repository
-
Connect the repository to Streamlit Cloud and specify
streamlit_app.pyas the main file
For detailed deployment instructions, see UI Deployment Guide.
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License - see the LICENSE file for details.