fastapi-vss A RESTful API for vector similarity search. It uses the Python web framework FastAPI.
This accelerates machine learning workflows using vector similarity search with classification models. This does not require a custom trained model, but it is more effective with a fine-tuned model.
- 🔍 Vector similarity search using fast Redis; you can search for similar images based on vector embeddings with a simple API call. Redis is an in-memory data structure store that supports fast vector search.
- 📊 Supports foundational models like CLIP, and fine-tuned models for specific tasks.
- Support batch processing for efficient querying of multiple images. Default batch size is 32; you can adjust it with the
BATCH_SIZEenvironment variable. - Supports top-n search, where you can specify how many similar predictions to return, e.g.
top_n=5to return the top 5 similar predictions, where a prediction includes a score and the database id of the closest match. - 📦 Docker container for easy deployment
- 📜 OpenAPI documentation for easy integration
