AI Agent Frameworks
Build autonomous, multi-step AI agents with these leading frameworks and platforms.
LangGraph
LangGraph is a low-level orchestration framework from the LangChain team for building stateful, multi-step agent workflows. It provides fine-grained control over execution flow with persistent state, human-in-the-loop checkpoints, and cycle support — ideal for complex agents that need more than simple chain sequencing.
CrewAI
CrewAI is an open-source framework for orchestrating role-playing, autonomous AI agents that collaborate to complete complex tasks. You define agents with specific roles, goals, and tools, then combine them into crews that work together — ideal for building multi-agent systems for research, analysis, and automation.
DSPy
DSPy is a framework for programming language models rather than prompting them, by composing modular pipelines and automatically optimizing prompts and weights. Developed at Stanford, it replaces brittle prompt engineering with reproducible, testable programs that adapt across different models and tasks.
Dify LLM App Development Platform
Dify is an open-source LLM application development platform that combines visual workflow orchestration, a built-in RAG engine, and Agent capabilities. It lets developers and non-technical users quickly build, test, and deploy AI-powered apps with support for multiple model providers and seamless API integration.
Flowise
Flowise is an open-source, drag-and-drop tool for visually building LLM applications and agent workflows with little to no code. It supports chaining prompts, integrating vector stores, and connecting multiple LLM providers — making it accessible for non-developers to prototype and deploy AI-powered solutions quickly.
n8n
n8n is an open-source workflow automation platform with native AI nodes for building agents and connecting hundreds of apps and services. It can be self-hosted for full data control or used in the cloud, combining visual workflow building with the flexibility to write custom code when needed.
AutoGen
AutoGen is Microsoft's open-source framework for building multi-agent AI systems where agents converse with each other, use tools, and collaborate to solve complex tasks. It supports flexible conversation patterns and human-in-the-loop workflows, making it a research-backed choice for orchestrating agent teams.