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ScriptsMar 31, 2026·2 min de lecture

txtai — All-in-One Embeddings Database

txtai is an all-in-one embeddings database for semantic search, LLM orchestration, and language model workflows. 10.4K+ GitHub stars. Vector search + SQL + RAG pipelines. Apache 2.0.

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Introduction

txtai is an all-in-one embeddings database combining semantic search, LLM orchestration, and language model workflows in a single library. With 10,400+ GitHub stars and Apache 2.0 license, txtai provides vector search with SQL support, RAG pipelines, extractive QA, labeling, transcription, translation, summarization, and workflow automation. It supports local and cloud LLMs, and can be deployed as an API server. txtai is designed to be the simplest way to build semantic search and AI-powered applications.

Best for: Developers who want semantic search + LLM pipelines in one lightweight library Works with: Claude Code, OpenAI Codex, Cursor, Gemini CLI, Windsurf Features: Vector search, SQL, RAG, QA, translation, summarization

Key Features

  • Embeddings database: Vector search with SQL query support
  • RAG pipelines: Retrieval-augmented generation out of the box
  • LLM orchestration: Chain multiple AI models in workflows
  • Extractive QA: Answer questions from documents
  • Translation + summarization: Built-in NLP pipelines
  • API server: Deploy as a REST API with one command
  • Local + cloud: Works with local models and cloud providers

FAQ

Q: What is txtai? A: txtai is an all-in-one embeddings database with 10.4K+ stars for semantic search, RAG, and LLM workflows. Vector search + SQL + NLP pipelines in one library. Apache 2.0.

Q: How do I install txtai? A: Run pip install txtai. Create an Embeddings() instance, index() your data, and search() semantically.

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Source et remerciements

Created by NeuML. Licensed under Apache 2.0. neuml/txtai — 10,400+ GitHub stars

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