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Google Workspace CLI — one command-line tool for Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin, and more. Dynamically built from Google Discovery Service. Includes AI agent skills.
An open-source, code-first Go toolkit for building, evaluating, and deploying sophisticated AI agents with flexibility and control.
Deep Agents is an agent harness built on langchain and langgraph. Deep Agents are equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - making them well-equipped…
【代码随想录知识星球】项目分享-自动化测试框架
An open-source SuperAgent harness that researches, codes, and creates. With the help of sandboxes, memories, tools, skills and subagents, it handles different levels of tasks that could take minute…
AI edge infrastructure for macOS. Run local or cloud models, share tools across apps via MCP, and power AI workflows with a native, always-on runtime.
Access to Anthropic's safety-first language model APIs via Go
📚 《从零开始构建智能体》——从零开始的智能体原理与实践教程
Tiny, Fast, and Deployable anywhere — automate the mundane, unleash your creativity
DATAGEN: AI-driven multi-agent research assistant automating hypothesis generation, data analysis, and report writing.
GenAI Agent Framework, the Pydantic way
[Book-2021] Practical MLOps O'Reilly Book
A community collection of OpenClaw use cases for making life easier.
Go implementation of the Ethereum protocol
A lightweight alternative to OpenClaw that runs in containers for security. Connects to WhatsApp, Telegram, Slack, Discord, Gmail and other messaging apps,, has memory, scheduled jobs, and runs dir…
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
Public repo for DeepLearning.AI MLEP Specialization
The 500 AI Agents Projects is a curated collection of AI agent use cases across various industries. It showcases practical applications and provides links to open-source projects for implementation…
Agent Reinforcement Trainer: train multi-step agents for real-world tasks using GRPO. Give your agents on-the-job training. Reinforcement learning for Qwen2.5, Qwen3, Llama, and more!
Code and implementations for the ACL 2025 paper "AgentGym: Evolving Large Language Model-based Agents across Diverse Environments" by Zhiheng Xi et al.
The absolute trainer to light up AI agents.
Agent-R1: Training Powerful LLM Agents with End-to-End Reinforcement Learning
Search-R1: An Efficient, Scalable RL Training Framework for Reasoning & Search Engine Calling interleaved LLM based on veRL