Guides
CrewAI vs AutoGen: Which Multi-Agent Framework
CrewAI structures agents around fixed roles and a defined process; AutoGen is built around open-ended agent conversation — here’s the real difference
What Is Smolagents? Hugging Face’s Agent Library
A minimal, code-first agent library from Hugging Face — how it differs from heavier frameworks like LangChain, and when its simplicity is the point
Python AI Agent Frameworks Compared
How LangGraph, CrewAI, AutoGen, and smolagents actually differ, and which one fits a new multi-agent Python project
Resources
LangChain
The most widely used Python framework for building LLM-powered applications, with 700+ integrations and tools for agents, RAG, and chains
LangGraph
Framework for building stateful, multi-step AI agent workflows as graphs — ideal for complex reasoning and tool-use pipelines
Pydantic AI
Type-safe Python framework for building production AI agents, built by the Pydantic team with structured outputs and dependency injection
smolagents
Hugging Face’s lightweight agent library — minimal, readable code for building tool-using LLM agents with support for any model via the Transformers ecosystem