概要
The framework centers on an embeddings database that combines sparse and dense vector indexes, graph networks and relational databases. This foundation can support search applications or provide knowledge context to LLM applications. Higher-level pipelines, workflows and agents add capabilities such as prompting, question answering, labeling, transcription, translation and summarization. Applications can run locally or use container orchestration for scaling.
主な機能
- Sparse and dense vector search with SQL integration
- Relational, graph and object-storage capabilities around an embeddings database
- Embedding generation for text, documents, audio, images and video
- Topic modeling, graph analysis and multimodal indexing
- Pipelines for LLM prompts, question answering, labeling, transcription, translation and summarization
- Workflows that connect pipelines and aggregate application logic
- Agents built on smolagents that can coordinate tools, workflows and other agents
- Retrieval-augmented generation and knowledge-graph workflows
- Web and Model Context Protocol APIs
- Bindings for JavaScript, Java, Rust and Go
- Local execution and container-orchestrated deployment options
要件、インストール、クイックスタート
使用方法
モデルの互換性とユースケース
Models can be loaded from a Hugging Face Hub path or a local directory, with defaults used when paths are omitted. The repository lists support for Hugging Face models, llama.cpp, and OpenAI, Claude and AWS Bedrock through LiteLLM in agent contexts. Recommended task models listed in the README include all-MiniLM-L6-v2 for embeddings, BLIP for image captions, DeBERTa v3 Zeroshot for zero-shot labels, Gemma 4 31B for LLM use, DistilBART for summarization, ESPnet JETS for text-to-speech, Whisper for transcription and the OPUS model series for translation.
ライセンスとリスクに関する注意事項
The repository metadata identifies the license as Apache-2.0, and the README describes txtai as open source under the Apache 2.0 license. Review the repository license and the separate licenses or usage terms of any models, datasets and external services selected for an application.
リリースとメンテナンス
The supplied README links to articles covering txtai 9.0, 8.0, 7.0, 6.0, 5.0 and 4.0, as well as the GitHub releases page. The current release version and release date are not stated in the repository metadata. Releases: https://github.com/neuml/txtai/releases