txtai
Explore a versatile embeddings database tailored for semantic search and language model processes. It adeptly merges vector indexes, graph databases, and relational structures to facilitate vector search via SQL, topic modeling, and retrieval augmented generation (RAG). Serving as a potent knowledge source for large language models, it supports various data forms such as text, documents, audio, images, and video. Easily build and scale with Python or YAML, and access API bindings for JavaScript, Java, Rust, and Go. Operate efficiently on local systems or expand through container orchestration.
