Open-AutoGLM

AppAgent is an LLM-based multimodal agent framework designed to operate smartphone apps like a human, supporting touch interaction and autonomous exploration.

Fully-automated and zero-code LLM agent framework that enables users to build and deploy custom AI agents through natural language without writing code.

Adala is an autonomous data labeling agent framework that uses AI agents to automate data annotation, classification, and quality checks, significantly improving data processing efficiency.

ART (Agent Reinforcement Trainer) trains multi-step agents for real-world tasks using GRPO reinforcement learning, enabling on-the-job training for models like Qwen, Llama, and more.