RAG

A command-line tool that converts documentation sites, GitHub repositories, PDFs, videos, notebooks and other sources into structured knowledge packages for AI skills, RAG pipelines and coding assistants.

• RAG
• CLI tools

An open-source library and MCP server that turns PDFs, Word documents, HTML, images and other unstructured files into clean, structured data ready for language models, vector databases and other downstream processing.

• MCP servers
• RAG

A Rust vector index with Python bindings, built on Google Research's TurboQuant quantizer, that fits large embedding corpora in a fraction of the memory float32 storage needs.

• RAG
• Databases

A private AI platform for building agents, assistants and enterprise search, with an agent builder, document analysis across many file formats, deep research tools and API connectivity to external tools.

• Agent frameworks
• RAG

A Python framework for computing, using and training embedding and reranking models, including sentence embeddings, cross-encoder reranking, sparse embeddings and ColBERT-style multi-vector retrieval, for semantic search and similarity tasks.

• RAG
• Models

A Rust library, with Node.js, Python and WebAssembly bindings, that converts Word, PowerPoint, Excel, RTF, EPUB, CSV and PDF files into clean Markdown for LLMs.

• RAG

An open-source platform for building enterprise-grade AI agents, combining a RAG pipeline, an agentic workflow engine and MCP tool use, aimed at uses such as customer service and internal knowledge bases.

• Agent frameworks
• RAG

An all-in-one multimodal retrieval-augmented generation framework, built on LightRAG, for querying documents that mix text, images, tables and equations through a single interface.

• RAG

An open-source, customizable RAG chat interface for asking questions over your own documents, aimed at both end users and developers who want to build their own retrieval pipeline.

• RAG

A fast, typo-tolerant open-source search engine, positioned as an alternative to Algolia and Elasticsearch, with support for geosearch and semantic search.

• RAG
• Databases

An open-source Python framework for orchestrating LLM applications, with modular pipelines and agent workflows that give explicit control over retrieval, routing, memory and generation.

• Agent frameworks
• RAG

An open-source PDF parser that extracts Markdown, JSON with bounding boxes, and HTML from PDFs for AI and RAG pipelines, and automates PDF accessibility tagging.

• RAG

A community-maintained collection of more than 42 runnable notebooks, each demonstrating a specific technique for building retrieval-augmented generation systems, from foundational to advanced.

• RAG
• Tutorials

An autonomous research agent that searches the web and local documents to produce detailed, cited reports on a given topic, using planner and execution agents with any LLM provider.

• Agent frameworks
• RAG

An AI agent building platform with out-of-the-box data processing and model-calling capabilities, letting users assemble complex question-answering applications through a visual workflow editor.

• Agent frameworks
• RAG

An open-source, LLM-powered knowledge platform that turns a team's documents into a queryable retrieval-augmented system, a multi-step reasoning agent, and a self-maintaining wiki, all sharing the same knowledge bases.

• RAG

A memory and context engine for AI applications that extracts facts from conversations, maintains user profiles, and combines retrieval-augmented generation with memory in a single API.

• Agent memory
• RAG

An open-source AI platform that indexes more than 50 workplace applications to give LLMs and AI agents context about a team's own knowledge, alongside chat, deep research and custom agents.

• RAG

A retrieval-augmented generation engine that replaces a vector index with a tree structure of a document, letting an LLM reason its way to the relevant section the way a person would.

• RAG

A Microsoft research project and data pipeline that extracts structured, graph-based context from unstructured text using LLMs, to help a language model reason over private data.

• RAG

A self-hosted AI answering engine that searches the web and cites its sources, combining local models through Ollama or cloud providers with a bundled private web search backend.

• RAG

A self-hostable personal AI application that chats with any local or hosted language model, answers questions from the web or a user's own documents, and can run scheduled research automations.

• RAG
• Inference

A Python library that uses large language models to pull structured information out of unstructured text, mapping every extracted value back to its exact location in the source for verification.

• RAG

A Python library that adds retrieval-augmented generation to an application: ingest files such as PDF, text or Markdown, then ask questions over them using any supported LLM and vector store.

• RAG