Build and run agents you can see, understand and trust.

Demystify AI agents by building them yourself. Local LLMs, no black boxes, real understanding of function calling, memory, and ReAct patterns.

LLM-powered Agent Runtime with Dynamic DAG Planning & Concurrent Execution

fullstack chat agent with authentication, request credits and payments built in

The minimal AI agent engine

The Karpathy treatment for OpenClaw - stripped to ε. 515 lines of Python, 6 files, one dependency.

A complete LangGraph multi-agent system demo using SQL tools, Tavily search, MCP Toolbox, and OpenRouter models — with reproducible notebooks and a full supervisor-led agent workflow.

Thoth - Personal AI Sovereignty. A local-first AI assistant with 23 integrated tools, a personal knowledge graph, voice, vision, shell, browser automation, scheduled tasks, health tracking, and messaging channels. Run locally via Ollama or add opt-in cloud models. Your data stays on your machine.

🤖 Advanced AI agent system combining ReAct reasoning and Plan-Execute strategies with unified memory, reflection patterns, and browser automation tools. Built with LangGraph, LangChain, and Google Gemini.

Lightweight Python SDK for LLMs with unified API across 9 providers. Built-in ReAct & Plan-Execute agents, streaming, native tool calling, context injection, structured outputs, and observability.

An AI-powered investment analysis tool 📈 that leverages simple ReAct AI agent flow framework and financial analysis techniques to provide comprehensive portfolio insights. This intelligent agent helps investors make data-driven decisions by offering deep portfolio risk assessment, stock profiling, and personalized recommendations.

A simple ReAct agent that has access to LlamaIndex docs and to the internet to provide you with insights on LlamaIndex itself.

Ship customer-facing AI with isolation, spend controls, and provenance.

JS bindings for Cross-Language MCP Orchestrator, think of LangChain + Vercel AI kit but for MCP

A practice repository implementing examples from the official LangChain documentation

Innovative AI agent implementations using LangGraph—featuring ReAct, RAG (Corrective, Self, Agentic), chatbots, microagents, and more, with multi-AI agent systems on the horizon! 🤖🚀

基于大模型 (LLM) ，智能体(Agent)与 RAG 技术的智能口岸物流助手。通过 Agent 自动调度查询工具与检索法规知识库，为港口用户提供通关异常诊断与决策支持。

React AI Agent with Long-Term Memory and Tool calling

Unified Tokio agent runtime — orchestration, memory, knowledge graph, and ReAct loop in one crate

The Financial Analysis Crew is a Streamlit app that simplifies financial stock analysis. With the power of LLM-driven agents, users can seamlessly gather and analyze stock market data to generate comprehensive financial insights. Perfect for investors, analysts, and anyone interested in making data-driven financial decisions.