AI Agent Skills

Build and query a private RAG knowledge base from your documents. Ingests documents, indexes them with embeddings, and answers questions grounded in retrieved c

Memory layer for AI Agents. Replace complex RAG pipelines with a serverless, single-file memory layer. Give your agents instant retrieval and long-term memory.

📑 PageIndex: Document Index for Vectorless, Reasoning-based RAG

🌌 A complete search engine and RAG pipeline in your browser, server or edge network with support for full-text, vector, and hybrid search in less than 2kb.

Deeplake is AI Data Runtime for Agents. It provides serverless postgres with a multimodal datalake, enabling scalable retrieval and training.

The AI search platform

Open-source framework for building AI-powered apps in JavaScript, Go, and Python, built and used in production by Google

Awesome-GraphRAG: A curated list of resources (surveys, papers, benchmarks, and opensource projects) on graph-based retrieval-augmented generation.

[EMNLP2025] "LightRAG: Simple and Fast Retrieval-Augmented Generation"

Neo4j graph construction from unstructured data using LLMs

This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.

Data framework for building RAG and knowledge workflows around agent tasks.

Open-source LLM knowledge platform: turn raw documents into a queryable RAG, an autonomous reasoning agent, and a self-maintaining Wiki.

One delightful Ruby framework for every major AI provider. Build AI agents, chatbots, RAG apps, and multimodal workflows in beautiful, expressive code.

Synthadoc: An open-source LLM knowledge compilation engine that turns raw documents into structured, local-first wikis. A transparent, human-readable alternative to trad…

Full-stack AI app generator — FastAPI + Next.js with AI Agents, RAG, streaming, auth, and 20+ integrations out of the box.