Langflow puts a canvas on top of LangChain. Drag components, connect them, watch it run, then export the whole thing as Python when you want to take it further.
Reach for it when
- You want to prototype a chain visually
- You are already using LangChain underneath
- You want to hand a flow to someone non technical
Look elsewhere when
- You are comfortable writing the chain directly
- You need fine control the canvas does not expose
What the lessons will cover
- 01Install and setup
- 02The canvas
- 03Components
- 04Building a RAG flow
- 05Agents and tools
- 06Custom components
- 07Exporting to code
- 08Deploying a flow
Others in visual and no code
n8nWire an AI workflow on a canvas.
FlowiseOpen source drag and drop for LLM apps.
DifyBuild, deploy and watch agents from a browser.Common questions
Is Langflow free to use?
Langflow is open source and free to run yourself. You still pay whichever model provider you point it at, and this tutorial is free with no signup.
Do I need to know Python to use Langflow?
No. Langflow is built around a visual canvas, so you can get a working flow without writing code.
When should I not use Langflow?
You are comfortable writing the chain directly. You need fine control the canvas does not expose.
Lessons for Langflow are being written. Meanwhile the LangGraph tutorial covers the same ground: state, tools, loops, memory and human approval. Most of it carries straight over.
Start the LangGraph tutorial →