AI Agent Skills

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

The most accurate document search and store for building AI apps

AI Agent that handles engineering tasks end-to-end: integrates with developers’ tools, plans, executes, and iterates until it achieves a successful result.

A modular Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes.

A native macOS app that allows users to chat with a local LLM that can respond with information from files, folders and websites on your Mac without installing any other…

Turn your PC, Mac, or Linux box into an AI server. LLM inference, chat UI, voice, agents, workflows, RAG, and image generation.

🔥 Comprehensive survey on Context Engineering: from prompt engineering to production-grade AI systems. hundreds of papers, frameworks, and implementation guides for LLM…

🚀 EvoAgentX: Building a Self-Evolving Ecosystem of AI Agents

Fast, Accurate, Lightweight Python library to make State of the Art Embedding

AI Search & RAG Without Moving Your Data. Get instant answers from your company's knowledge across 100+ apps while keeping data secure. Deploy in minutes, not months.

A streamlined and customizable framework for efficient large model (LLM, VLM, AIGC) evaluation and performance benchmarking.

What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers?

Multi-agent systems, memory, planning, reasoning loops

Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.

The AI-native state store for agents. MySQL-compatible, embedded or server, hybrid vector + full-text search, COW sandboxes (FORK/MERGE).

A curated collection of practical AI projects implementing OCR systems, RAG, AI agents, and other AI use cases.