neuml/txtai

一体化人工智能框架

TXTAI 是一个用于语义搜索、大型语言模型编排和语言模型工作流程的一体化人工智能框架。

txtai的关键组成部分是嵌入数据库，它是向量索引（稀疏索引和密集索引）、图网络和关系数据库的联合体。

这一基础使向量搜索成为可能，和/或作为大型语言模型（LLM）应用的强大知识来源。

构建自主代理、检索增强生成（RAG）流程、多模型工作流程等。

txtai 功能总结：

• 🔎 带SQL的向量搜索、对象存储、主题建模、图分析和多模态索引
• 📄 为文本、文档、音频、图像和视频创建嵌入
• 💡 由语言模型驱动的管道，运行LLM提示、问答、标签、转录、翻译、摘要等功能
• ↪️️ 连接管道并聚合业务逻辑的工作流程。txtai流程可以是简单的微服务或多模型工作流。
• 🤖 智能连接嵌入、管道、工作流及其他代理，自主解决复杂问题的代理

All-in-one AI framework

txtai is an all-in-one AI framework for semantic search, LLM orchestration and language model workflows.

The key component of txtai is an embeddings database, which is a union of vector indexes (sparse and dense), graph networks and relational databases.

This foundation enables vector search and/or serves as a powerful knowledge source for large language model (LLM) applications.

Build autonomous agents, retrieval augmented generation (RAG) processes, multi-model workflows and more.

Summary of txtai features:

• 🔎 Vector search with SQL, object storage, topic modeling, graph analysis and multimodal indexing
• 📄 Create embeddings for text, documents, audio, images and video
• 💡 Pipelines powered by language models that run LLM prompts, question-answering, labeling, transcription, translation, summarization and more
• ↪️️ Workflows to join pipelines together and aggregate business logic. txtai processes can be simple microservices or multi-model workflows.
• 🤖 Agents that intelligently connect embeddings, pipelines, workflows and other agents together to autonomously solve complex problems
• ⚙️ Web and Model Context Protocol (MCP) APIs. Bindings available for JavaScript, Java, Rust and Go.
• 🔋 Batteries included with defaults to get up and running fast