Atomic Agents

Description

Atomic Agents (BrainBlend AI, MIT) is 'designed around the concept of atomicity to be an extremely lightweight and modular framework for building Agentic AI pipelines and applications.' Components are 'LEGO blocks': each AtomicAgent or BaseTool is single-purpose, reusable, and predictable, with explicit Pydantic input and output schemas. The framework is built on Instructor for provider portability (OpenAI, Anthropic, Groq, Ollama, Mistral, Cohere, Gemini), exposes ChatHistory and BaseDynamicContextProvider for runtime context injection, and ships an Atomic Forge CLI with 13+ pre-built tools. v2.0 renamed BaseAgent to AtomicAgent and added run_stream() / run_async_stream().

Solution

Single-agent IPO (Input → Process → Output) cycle. An AtomicAgent owns a Pydantic input schema, system prompt, ChatHistory, output schema, and an Instructor-backed LLM client. Each run() call validates the input, assembles prompt + history + dynamic context, calls the model under structured-output mode via Instructor, validates the output, and returns it. Tools are separate BaseTool blocks with their own schemas; chaining is purely by matching one block's output schema to the next's input schema — there is no built-in supervisor or orchestrator runtime.

Primary use cases

• schema-driven single-agent pipelines
• multi-step chains where components align by Pydantic schema
• provider-portable agents via Instructor
• custom tools registered through Atomic Forge CLI