Audience
Developers interested in a similarity search library
About Faiss
Faiss is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning.
Faiss is written in C++ with complete wrappers for Python. Some of the most useful algorithms are implemented on the GPU. It is developed by Facebook AI Research.
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Provides the OpenAPI v3 specification to generate a client library in almost any programming language. Alternatively utilise ready-made client for Python or other programming languages with additional functionality.
Implement a unique custom modification of the HNSW algorithm for Approximate Nearest Neighbor Search. Search with a State-of-the-Art speed and apply search filters without compromising on results.
Support additional payload associated with vectors. Not only stores payload but also allows filter results based on payload values.
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Pricing
Starting Price:
Free
Pricing Details:
Open source
Free Version:
Free Version available.
Integrations
Company Information
Meta
Founded: 2004
United States
faiss.ai/
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