Txtai is an all-in-one embeddings database designed for semantic search, language model orchestration, and various language model workflows. It functions as a powerful knowledge source for large language models, offering features like vector search with SQL, topic modeling, and graph analysis. Txtai supports the creation of embeddings for various data types, including text, documents, audio, images, and video. With its versatile pipelines driven by language models, txtai can perform tasks such as question-answering, labeling, transcription, translation, and summarization.
The platform allows the building of workflows to combine different processes and business logic, offering the flexibility of simple microservices or more complex multi-model workflows. Txtai can be implemented using Python or YAML, with API bindings available for JavaScript, Java, Rust, and Go. It can be deployed locally or scaled out using container orchestration for efficient and scalable operations.
