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
Role-based agent assignment (PM, architect, engineer, QA)
Structured output generation (requirements, design, code)
Data Interpreter for data analysis tasks
SELA module for self-evolving agents
Multi-agent collaboration and workflow orchestration
Meta-programming support for custom agent behaviors
Modular and extensible architecture
Built-in demo projects and case studies
MIT License fully open-source
Flow orchestration for complex agent pipelines
Integration with GitHub Actions and CI/CD
Community-driven with GitHub and Discord
