RAG

A lightweight, fast Python library for generating text, sparse and image embeddings using the ONNX runtime instead of PyTorch, with no GPU required.

• RAG
• Libraries

A retrieval-augmented-generation dialogue system for building a knowledge-base question-answering service from your own documents, with a vector-database-backed retrieval engine.

• RAG

A native macOS app for chatting with a local large language model that can answer using files, folders and websites on the Mac, entirely offline, with an optional bring-your-own-key mode.

• RAG
• Inference

A benchmark toolbox for evaluating text and multimodal embedding and retrieval models across languages, with an interactive leaderboard and a command-line runner.

• RAG
• AI evals

A document parsing and retrieval system that turns unstructured files into persistent, navigable memory for AI agents and retrieval-augmented generation.

• Agent memory
• RAG

A Python toolkit for reproducing and developing retrieval-augmented generation research, bundling 36 preprocessed benchmark datasets and 23 published RAG algorithms behind one customizable pipeline framework.

• RAG

An open-source, self-hostable platform that connects AI agents and assistants to a company's business systems, providing permission-aware search and cited answers over Slack, Google Drive, GitHub, Notion and more.

• RAG

A local-first command-line search tool that unifies ripgrep-style text search, BM25 and vector search behind one interface, usable directly from a terminal or by an AI agent.

• RAG
• CLI tools

A memory framework for LLMs, inspired by human long-term memory, that indexes documents as a knowledge graph so agents can retrieve across multiple hops and integrate new knowledge continually.

• Agent memory
• RAG

A production-oriented Java platform for building agentic retrieval-augmented generation applications, covering document ingestion, hybrid retrieval, intent understanding, session memory and MCP tool calling.

• Agent frameworks
• RAG

An open-source document intelligence API that performs layout analysis, OCR and semantic chunking to convert PDFs, presentations, Word documents and images into structured data for RAG and LLM pipelines.

• RAG

A hands-on notebook series that teaches Retrieval-Augmented Generation from an introductory setup through advanced techniques such as multi-querying, logical and semantic routing, and custom RAG pipeline construction.

• RAG
• Tutorials

A modular Agentic RAG tutorial and project template built with LangGraph, demonstrating hierarchical retrieval, conversation memory, query clarification and multi-agent orchestration for retrieval-augmented generation.

• RAG
• Tutorials

A compact, single-header similarity search and clustering engine for vectors and arbitrary objects, with bindings in eleven languages and support for user-defined distance metrics.

• RAG
• Databases

A LanceDB-backed long-term memory plugin for OpenClaw agents that auto-captures preferences, decisions, and project context, then recalls them with hybrid vector and keyword search.

• Agent memory
• RAG

A bio-inspired cognitive memory engine that scores retrieval by the strongest chain of reasoning connecting a query to an answer, instead of ranking by vector similarity or a static knowledge graph.

• Agent memory
• RAG

A command-line tool for semantic search over video footage: describe what you are looking for in text or an image, and it returns a trimmed clip from the matching moment.

• RAG

An open-source command-line tool that compiles raw documents into a structured, interlinked wiki-style knowledge base using large language models, with reasoning-based retrieval for long documents and no vector database required.

• Agent memory
• RAG

A single-package Retrieval-Augmented Generation platform, built on Langflow, Docling and OpenSearch, that lets users upload documents and query them through a chat interface with agentic, multi-agent workflows.

• RAG

A lightweight Python library for splitting text into chunks for retrieval-augmented generation pipelines, with more than thirty integrations and support for 56 languages.

• RAG

An AI-native database written in C++ that provides fast hybrid search across dense vectors, sparse vectors, tensors (multi-vector) and full text, for retrieval-augmented generation and similar applications.

• RAG
• Databases

A tool for interactively visualizing large embeddings and their metadata, letting a user cross-filter, search and explore data structure at scale.

• RAG
• Data engineering

A toolkit for deploying and serving open-source text-embedding and sequence-classification models, supporting popular families such as FlagEmbedding, GTE and E5.

• RAG
• Inference

A self-evolving 'librarian' agent that searches across multiple retrieval methods and opens source documents directly to answer questions grounded in a user's own files, superseding the original AutoRAG pipeline-optimization tool.

• RAG