Atomic Agents
Atomic Agents is a lightweight and modular framework designed for building Agentic AI pipelines and applications. It emphasizes atomicity, allowing developers to create powerful applications without sacrificing maintainability or developer experience. The framework is built on top of Instructor and utilizes Pydantic for data validation and serialization, enabling clear input and output schemas.
Key Features:
- Modularity: Combine small, reusable components to build AI applications.
- Predictability: Define clear input and output schemas for consistent behavior.
- Extensibility: Easily swap out components or integrate new ones without disrupting the entire system.
- Control: Fine-tune each part of the system individually, from system prompts to tool integrations.
Benefits:
- Developer-Friendly: Leverage familiar Python practices for AI development.
- Dynamic Context: Use Context Providers to inject additional information into agents at runtime.
- Chaining Agents: Align input and output schemas to easily chain agents and tools together.
Highlights:
- Supports various AI models and tools, including OpenAI, Ollama, and Groq.
- Comprehensive documentation and examples to help developers get started quickly.
- Active community contributions and support for ongoing development.