Features
Open-source Python framework for building agents
Model-driven orchestration; no rigid workflows
Built-in web search and web browsing tools
Code execution: local, Docker, E2B sandbox
MCP client for model-context protocol integration
Document input and output handling
Skills system for modular domain-specific instructions
Flexible tool execution via generic Tool class
Context management with automatic conversation summarization
Multi-provider LLM support (OpenAI-compatible, LiteLLM, custom)
Multimodal support: images, video, audio
Session-based execution with lifecycle management
Built-in logging and file output handling
OpenResponses client for OpenAI Responses API
Sub-agents capability and caching support
GLM-5.2 open-source flagship model with 1M context
GLM-5V-Turbo multimodal coding model
GLM-5-Turbo agent-optimized base model
AutoGLM autonomous planning and execution agent (50+ steps)
GLM-PC computer-operating agent via screen input
AutoClaw 1-minute PC agent deployment
MaaS high-performance model API services
Model fine-tuning for language and multimodal models
AI search tool with multi-engine integration
General translation with context recognition
GLM PPT/Poster one-click presentation generation
CogAgent-9B open-source GLM-PC base model
End-side deployment with Intel partnership
CodeGeeX smart coding assistant for AIPC
