BeeAI Framework
lastmod 2025-04-17created 2025-04-171 edits
A framework for multi-agent development
About
- Designed for building production-grade multi-agent systems in Python or TypeScript
- Various agent structures and workflows can be freely defined, making it suitable for developing complex collaborative AI systems
Flexible agent architecture
- Supports everything from simple single agents to complex multi-agent structures
- Built-in examples:
- Get started quickly with ReActAgent
- Complex scenarios can be composed with the Workflow feature
Integration with various models and tools
- Integrates easily with major model providers:Ollama, Groq, OpenAI, watsonx.ai, etc.
- Use LangChain-based tools, or build your own custom tools
- Model Context Protocol (MCP) support makes server integration easy
- Focus on system scalability and flexibility
Production-ready features
- Optimizes token usage through memory strategies
- Agent state can be serialized/deserialized for saving and restoring
- Structured output generation, code execution (sandboxed execution planned)
- When problems occur:
- Trace the agent's entire workflow through the emitter system
- Supports detailed event-based monitoring and analysis
- Collects diagnostic data through logging and telemetry
- Reliable error handling with a clear exception system
Development roadmap
- Make Python and TypeScript features identical
- Build a standalone documentation site
- watsonx.ai deployment integration
- Provide workflows for various multi-agent architectures
- Add built-in agents (OTTB)
- Native tool calling based on LLM providers planned