AgentsFree
LangGraph
LangGraph is the serious engineer's choice when an agent needs real state management, branching, retries, human-in-the-loop steps, and durable execution across long-running tasks. It's a Python (and now TypeScript) framework where you define agents as graphs of nodes — each node a function, each edge a transition — with explicit state passed through. Pair it with LangSmith for tracing and the LangGraph Platform for hosting. This is where you go after n8n stops being expressive enough.
What it's good for
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Multi-agent systems where specialised agents hand off tasks to each other
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Long-running agent jobs that need to pause for human approval and resume
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Production AI features where retries, error handling, and observability matter
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Custom RAG pipelines with conditional retrieval, reranking, and multi-step reasoning
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Agentic backends behind SaaS products where uptime and traceability are required
How to use it
Define your agent as a StateGraph in Python or TypeScript — typed state, explicit nodes for tool calls or LLM steps, conditional edges. Run locally during development with full tracing in LangSmith. For production, deploy to LangGraph Platform (hosted) or run the open-source server on your own infrastructure. Add Human-in-the-loop nodes wherever an agent decision warrants a real reviewer. The framework is open-source and free; LangSmith and the hosted Platform charge by usage.
MaxtDesign · AI Studios
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