A progressive AI Agent building tutorial covering 18 steps to implement a lightweight OpenClaw (pickle-bot) from scratch, featuring tool calling, multi-agent collaboration, and production-grade capabilities.
A self-hostable AI research workspace for grounded chat, paper study, 206+ scientific skills, and 13-stage deep research execution.
A minimal, learning-oriented reimplementation of the OpenClaw core architecture, demonstrating system-level AI Agent design including dual-loop Agent Loop, EventStream, Session persistence, three-tier context management, and WebSocket RPC gateway.
A daily automated AI ecosystem aggregation and digest tool. Crawls 10+ data sources including GitHub, HN, ArXiv, and HuggingFace, generates bilingual (CN/EN) reports via LLM analysis, and distributes through GitHub Issues, Web UI, RSS, and MCP Server.
A local-first AI research assistant featuring multi-LLM support, 20+ research strategies, multi-search-engine integration, and automated quality scoring for 212K+ academic sources, producing citation-backed PDF/Markdown reports via CLI, Web UI, REST API, or MCP Server.
An interactive open-access textbook on Machine Learning Systems engineering from Harvard University, integrating the TinyTorch framework with hands-on edge deployment labs, covering the full spectrum from ML fundamentals to system optimization.
A curated collection of extracted system prompts from popular chatbots like ChatGPT, Claude, and Gemini, helping researchers understand the behavior boundaries of AI models。
A minimal Agentic RAG built with LangGraph — learn Retrieval-Augmented Generation Agents in minutes. Build a production-ready Agentic RAG system with LangGraph, conversation memory, and human-in-the-loop query clarification.
AI-Compass is a comprehensive open-source project that provides learning paths and practical guidelines for AI technologies, helping users from beginners to professionals build a complete AI knowledge system from fundamental theory to cutting-edge applications.
A curated collection of autonomous agents (LLM) research papers updated daily, providing the latest AI research findings for researchers and developers。
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