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XERJ is the new way for AI to search data. Its autoindex capability activates agents to know your data without the token waste of grep (1974 tool). One command indexes code, docs, logs and PDFs for search, RAG, security audits and agent memory, using 40x fewer tokens than grep.

> 🎉 TradingAgents officially released! We have received numerous inquiries about the work, and we would like to express our thanks for the enthusiasm in our community. > > So we decided to fully open-source the framework.

《深入理解 AI Agent：设计原理与工程实践》（李博杰 著）开源主仓库：全书正文、编译版 PDF 与按章配套代码

> The main TierSense repository: use the three modules independently or combine them for your application. Find project navigation, integration guidance, and the centralized authors' statements here.

📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程

A curated, battle-tested AI-coding toolkit: Claude Code plugins, subagent orchestration, quality gates, and ready-to-copy prompts, extracted from real production use.

Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.

100+ AI Agents, Agent Skills and RAG Apps - Free and Open Source.

免费大模型API，支持免费调用GPT、DeepSeek等主流模型，免费额度10000点，每日刷新！另付费价格最低官方1-2折！

In English: AIHOT (aihot.news) is an AI news site that collects from many sources, lets a language model filter and score every item twice, writes Chinese headlines and summaries, clusters reports of the same story into one event, ranks events by how many independent sources…

Once production starts, the work is split across several AI agents. Different parts of the video are made at the same time, and every shot is handed to a different agent to check. If something's wrong it goes back to be fixed, so it's not a one-shot generate-and-done.

Companion materials for our survey of how execution experience becomes persistent harness state under a fixed base model. The survey covers update mechanisms, evolutionary search, continual PAC learning, evaluation, applications, and societal impact.

Ultra-lightweight, open-source, self-hosted personal AI agent framework in Python with WebUI, tools, memory, MCP, multi-agent workflows, automation, and chat apps

Open-source, self-hosted alternative to OpenAI Dots, Grok Bot. Built to be undetectable by anti-bot systems.

md on disk. md). That benchmark used the earlier default transcript-catchup behavior.

Token-scale scientific discovery engine — autonomous hypothesis generation, experiment execution, and knowledge graph synthesis

🤗 smolagents: a barebones library for agents that think in code.

📄 Our paper is on arXiv — come read it! AutoResearchClaw: Self-Reinforcing Autonomous Research with Human-AI Collaboration

AI联网搜索、文件解析及网页内容抓取等智能体核心能力提供商： 安思派开放平台(Anspire Open)是面向智能体时代的领先的基础设施提供商。我们为开发者提供构建强大智能体所需的核心能力栈，现已上线AI联网搜索【多版本，极具竞争力的价格】、文件解析【限免】及网页内容抓取【限免】、云端浏览器自动化（Anspire Browser Agent）【内测】、多轮改写等服务，持续为智能体连接并操作复杂的数字世界提供坚实基础。可无缝集成至Dify、Coze、元器等主流智能体平台。通过透明点数计费体系与模块化设计，为企业提供高效、低成本的定制化支持，加速智能化升级…

3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses!

Autonomous penetration testing using a swarm of AI agents. Orchestrates recon, classification, exploitation, and reporting specialists with ReAct reasoning — supports bug bounty, continuous monitoring, and CTF modes. Built with Go and 7+ native security tools.

An open-source, code-first Python toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.

The Harness of Harnesses • built for RSI: a trusted, persistent, self-evolving multi-agent ecosystem for all-domain collaboration.

Open-source, self-hosted AI penetration testing framework: maps your attack surface into a graph, autonomously exploits it from a Kali sandbox with human approval gates, and opens PRs that fix what it finds.

Framework · Domains · Results · Quick Start · Citation · 简体中文

Research and development (R&D) is crucial for the enhancement of industrial productivity, especially in the AI era, where the core aspects of R&D are mainly focused on data and models.

OpenChart is not built to monetize software, but to explore a future where humans and agents manage assets together. If you believe in this future and want to join forces, we want to talk to you.

Webcmd learns the navigational context of websites as agents use them, then turns that knowledge into local memory for faster, cheaper, more reliable browser automation.

Pocket Flow: 100-line LLM framework. Let Agents build Agents!

autoharness is a self-learning skill layer for Claude Code.