OpenHands/OpenHands
OpenHands is an AI-powered platform that automates software development tasks, enabling developers to code less and produce more by modifying code, running commands, browsing the web, and integrating APIs efficiently.
The project "Awesome-Self-Evolving-Agents" is a comprehensive survey and curated collection focused on the emerging paradigm of self-evolving AI agents. It bridges foundational AI models and lifelong agentic systems, providing a detailed taxonomy and conceptual framework for the evolution and optimization of AI agents. The repository categorizes approaches into three major directions: single-agent optimization, multi-agent optimization, and domain-specific optimization, illustrating the development of these methods from 2023 to 2025. It includes a rich set of references to state-of-the-art research papers and open-source frameworks that contribute to the field, such as EvoAgentX, an automated framework for evolving agentic workflows, and MASLab, a unified codebase for multi-agent systems based on large language models (LLMs). The survey covers various optimization techniques for AI agents, particularly focusing on large language model (LLM) behavior optimization through both training-based and test-time methods. Training-based approaches include supervised fine-tuning and reinforcement learning strategies, highlighting recent advances like ToRA, STaR, MAS-GPT, and several reinforcement learning frameworks that enable self-rewarding and self-play mechanisms. Test-time optimization methods involve feedback-based and search-based techniques to improve agent performance dynamically during deployment. The project also provides visual aids such as a taxonomy tree and a conceptual framework diagram to help understand the evolution paths and optimization strategies of AI agents. It encourages community contributions and stars, indicating an active and growing interest in this research area. Overall, this repository serves as a valuable resource for researchers and practitioners interested in the development, training, and deployment of self-evolving AI agents, offering a structured overview of current methodologies, tools, and future directions in the field.
https://github.com/EvoAgentX/Awesome-Self-Evolving-Agents
OpenHands is an AI-powered platform that automates software development tasks, enabling developers to code less and produce more by modifying code, running commands, browsing the web, and integrating APIs efficiently.
Strix is an open-source AI-driven security testing platform that autonomously finds, validates, and helps fix application vulnerabilities through dynamic and collaborative AI agents.
Goose is an open-source, native AI agent available as a desktop app, CLI, and API, designed for diverse tasks like code, research, writing, and automation, supporting over 15 LLM providers.
Shannon is an autonomous AI pentester for web applications and APIs, analyzing source code, identifying attack vectors, and executing real exploits to prove vulnerabilities.
A comprehensive collection of 44 specialized AI subagents for Claude Code that enhance development workflows with domain-specific expertise across software development, infrastructure, security, data, and business domains.
AgentScope is a transparent, modular, and customizable framework for building LLM-empowered multi-agent applications with real-time control and asynchronous execution.
OfficeCLI is an open-source command-line interface and API enabling AI agents to read, edit, and automate Word, Excel, and PowerPoint files without needing Office suite installations.
Deep Agents is an open-source agent harness built on LangChain and LangGraph that enables AI agents to plan, execute, and delegate complex long-horizon tasks using customizable tools, subagents, and human-in-the-loop workflows.