📖 The AI Tool Bible

Chainlit vs LangGraph

A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.

 
Chainlit
Agents
LangGraph
Agents
TaglineOpen-source Python framework for building production-grade conversational AI interfaces in minutes.Stateful, graph-based agent orchestration from LangChain.
CategoryAgentsAgents
PricingFree· Open-source (Apache 2.0); optional paid Literal AI observability tierFreemium· Free open-source; LangGraph Platform paid
ModelMulti-modelBYO (Claude / GPT / open)
Editorial score—8.8 / 10
Use cases
chatbot-uiagent-frontendrag-demosinternal-toolsllm-prototyping
stateful agentshuman-in-loopproduction
Pros
  • Production-ready chat UI from a few lines of Python
  • Native integrations with LangChain, LlamaIndex, OpenAI, Mistral
  • Built-in multi-step reasoning visualization and feedback capture
  • Enterprise auth and data persistence supported out of the box
  • Apache-licensed and fully self-hostable
  • Reliable, debuggable agent graphs
  • Built-in persistence + HITL
  • Production-grade
  • Tight LangSmith integration
Cons
  • UI is opinionated; deep theming requires a custom React frontend
  • Python-only on the backend
  • Smaller community than Streamlit/Gradio
  • Steeper learning curve than CrewAI
  • Verbose to set up
Websitedocs.chainlit.iowww.langchain.com
Pick Chainlit if
  • ✅ Production-ready chat UI from a few lines of Python
  • ✅ Native integrations with LangChain, LlamaIndex, OpenAI, Mistral
  • ✅ Built-in multi-step reasoning visualization and feedback capture
  • ✅ Enterprise auth and data persistence supported out of the box
Pick LangGraph if
  • ✅ Reliable, debuggable agent graphs
  • ✅ Built-in persistence + HITL
  • ✅ Production-grade
  • ✅ Tight LangSmith integration
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