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txtai

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📌 Summary:
txtai 是一個提供多模態索引、主題建模和語言模型流程等功能的語義搜尋、LLM 管理和多模態索引的全能型向量索引庫。它可以獨立運作,也可以作為大型語言模型(LLM)提示的強大知識來源。txtai 的特點包括向量搜尋、語義搜尋、主題建模、圖分析、多模態索引等。txtai 支援各種數據類型,如文本、文件、音訊、圖片和影片。可以使用 Python 或 YAML 建立,透過 JavaScript、Java、Rust 或 Go 等語言進行 API 整合。可以本地運行,也可以使用容器編排來進行擴展。

🎯 Key Points:
- txtai 是一個全能型的向量索引庫,支援多種數據類型,如文本、文件、音訊、圖片和影片。
- txtai 支援語義搜尋、主題建模、圖分析、多模態索引等功能。
- txtai 可以獨立運作,也可以作為 LLM 提示的強大知識來源。
- txtai 提供各種管道和工作流程,以連接管道並結合業務邏輯。
- txtai 可以使用 Python 或 YAML 建立,並支援多種 API 語言,如 JavaScript、Java、Rust 和 Go。
- txtai 是基於 Python 3.8+ 開發的,採用 Hugging Face Transformers、Sentence Transformers 和 FastAPI 等技術。

🔖 Keywords:
#文本向量索引
#多模態索引
#語義搜尋
#主題建模
#圖分析
#LLM 管理
#KGE
neuml.github.iotxtaitxtai is an all-in-one open-source embeddings database for semantic search, LLM orchestration and language model workflows

Of course I know RDF2vec ;-)
However, Heiko Paulheim's RDF2vec website has grown nicely and has become a rather valuable resource for this embedding method, including implementations, models and services, variations and extensions, as well as more than 150 references in scientific papers!
RDF2vec website: rdf2vec.org/
original paper: madoc.bib.uni-mannheim.de/4130
Petar Ristoski's PhD thesis (with RDF2vec): ub-madoc.bib.uni-mannheim.de/4

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