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A research agent system deeply rooted in your Zotero library.

An agentic company research tool powered by LangGraph and Tavily that conducts deep diligence on companies using a multi-agent framework. It leverages Google's Gemini 2.5 Flash and OpenAI's GPT-5.1 on the backend for inference.

A production-oriented multi-agent orchestration framework.

A curated list of autonomous improvement loops, research agents, and autoresearch-style systems inspired by Karpathy's autoresearch.

[Survey] A Comprehensive Survey of Self-Evolving AI Agents: A New Paradigm Bridging Foundation Models and Lifelong Agentic Systems

A repo lists papers related to LLM based agent

Comprehensive resources on Generative AI, including a detailed roadmap, projects, use cases, interview preparation, and coding preparation.

✨ Fully autonomous AI Agent that can perform complicated tasks and projects using terminal, browser, and editor.

CodeMachine is an open-source tool that orchestrates AI coding agents into repeatable, long-running workflows. ⚡️

SRE Agent - CNCF Sandbox Project

A trilingual (繁中 / English / 简中) learning roadmap for agentic AI: from LLM basics to multi-agent systems, with 240+ curated resources and hands-on examples. 中文 AI agent 學習地圖。

AI 朝廷搭建完整教程 - 从零基础到进阶

Visible multi-agent CLI workspace for mixing Codex, Claude, Gemini, Kimi, Qwen, Cursor, Copilot, Pi, OpenCode, and other AI coding agents

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

Neo.mjs is a self-evolving software organism: a professional end-to-end AI engineering team whose cross-model swarm inhabits live apps via Neural Link, Active Hybrid GraphRAG, DreamService, and self-healing loops.

II-Agent: a new open-source framework to build and deploy intelligent agents

总结Prompt&LLM论文，开源数据&模型，AIGC应用

A curated list of Generative AI tools, works, models, and references

A Comprehensive Benchmark to Evaluate LLMs as Agents (ICLR'24)

[NeurIPS 2025] Open-source Multi-agent Poster Generation from Papers

👾 Open source implementation of the ChatGPT Code Interpreter

Harness LLMs with Multi-Agent Programming

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

Your agent in your terminal, equipped with local tools: writes code, uses the terminal, browses the web. Make your own persistent autonomous agent on top!