A Python Library for Using PostgreSQL as a Vector Database in AI Applications

The Timescale Vector Python client library is a new library that enables easy storage, indexing, and querying of vector embeddings in PostgreSQL, making it simple to build AI applications with PostgreSQL as a vector database. The library provides optimized schema for vectors and metadata, performant batch ingestion of vectors, creation of indexes on vectors, similarity search and hybrid vector search, time-based vector search, Retrieval Augmented Generation (RAG) with time-based context retrieval, and more. It is designed to work seamlessly with Python developers, allowing them to easily integrate Timescale Vector's best-in-class similarity search and hybrid search performance into their generative AI applications. The library also provides a 90-day free trial for new customers and special early access pricing for existing Timescale customers.

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