Keywords AI
Compare LangGraph and OpenAI Agents SDK side by side. Both are tools in the Agent Frameworks category.
| Category | Agent Frameworks | Agent Frameworks |
| Website | langchain.com | github.com |
Key criteria to evaluate when comparing Agent Frameworks solutions:
LangGraph is LangChain's graph-based orchestration framework for building stateful, multi-step AI agents. It models agent workflows as directed graphs with nodes and edges, enabling complex control flow patterns like branching, looping, and human-in-the-loop interactions. LangGraph supports persistent state, streaming, and deployment via LangGraph Cloud.
The OpenAI Agents SDK is a lightweight Python framework for building multi-agent workflows with built-in tracing and guardrails. It provides primitives for defining agents with instructions and tools, orchestrating handoffs between agents, and implementing input/output guardrails for safety.
Developer frameworks and SDKs for building autonomous AI agents with tool use, planning, multi-step reasoning, and orchestration capabilities.
Browse all Agent Frameworks tools →An agent framework provides the building blocks for creating AI agents that can autonomously plan, use tools, and complete multi-step tasks. Instead of building tool use, memory, and orchestration from scratch, you get pre-built components that handle the common patterns.
For simple single-tool agents, raw API calls work fine. Frameworks become valuable when you need multi-step planning, tool orchestration, error recovery, memory, or multi-agent coordination. They save significant development time for complex agent architectures.
LangChain and LlamaIndex are the most mature with the largest ecosystems. CrewAI is best for multi-agent workflows. Vercel AI SDK is ideal for TypeScript/Next.js applications. Evaluate based on your language preference, use case complexity, and integration needs.