txtai 7.3 released: Adds new RAG Web Apps and streaming LLM/RAG support
The txtai 7.3.0 release introduces an open-source embeddings database for semantic search and language model workflows. It supports various data types, pipelines for tasks like summarization, and can be built with Python or YAML.
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The txtai 7.3.0 release offers an all-in-one open-source embeddings database for semantic search, LLM orchestration, and language model workflows. It includes features like vector search with SQL, object storage, and multimodal indexing. txtai supports creating embeddings for various data types like text, documents, audio, images, and video. It offers pipelines powered by language models for tasks such as question-answering, summarization, and translation. Workflows can be created to join pipelines and aggregate business logic. txtai can be built with Python or YAML, with API bindings available for other languages. It supports running locally or scaling out with container orchestration. The tool is built with Python 3.8+, Hugging Face Transformers, Sentence Transformers, and FastAPI, and is open-source under the Apache 2.0 license. Interested users can join the txtai.cloud preview for easy and secure hosted applications. Various use cases like semantic search, semantic graphs, LLM orchestration, and language model workflows are covered, with over 50 example notebooks available for reference.
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