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LiveGraph

Move your Langflow flows to LiveGraph

Langflow already thinks in nodes and edges — the move is shorter than it looks, and the canvas on the other side stays live while a run executes.

How the move works

There's no Langflow file importer — our importer covers Flowise exports only, and we'd rather say that than half-convert your flow. The honest path is generate, not import:

  • Export the flow from Langflow — it downloads as JSON, and a flow file is just the nodes, edges, and component config you already see on its canvas.
  • Paste it into the describe box when you create a graph here — or describe the flow in words if the JSON is unwieldy.
  • Review the generated graph. It lands as an ordinary editable LiveGraph graph — rename nodes, tighten prompts, rewire edges, then run it.

What a flow maps to

LangflowLiveGraph
Agent component + toolsWorker node — role, prompt, and model per node, with its tools scoped per node
Prompt / Model componentsThe node's prompt and model picker — any provider per node, keys stay yours
Conditional / routing componentsexplicit edges, or auto edges where a router picks the next specialist
Chat Input / Output + PlaygroundRuns start from chat, the canvas, schedules, or webhooks — not a hosted chat surface
Tool and MCP componentsPer-node MCP servers with an exact-name tool allowlist, http_request, or file access
Vector store / RAG componentsNo built-in vector store — wire retrieval in through an MCP server or HTTP endpoint you control

What carries over

  • The flow shape. Which component feeds which — that's already a graph, so it regenerates faithfully from the export.
  • Prompts. Every instruction and system message inside your components moves into node prompts verbatim.
  • Model choices. Each node picks its own provider and model — Anthropic, Google, Groq, OpenRouter, or an OpenAI-compatible endpoint.

What doesn't move

  • Credentials and API keys. Provider keys and tool connections in Langflow stay there — each node's tools are re-entered here, encrypted at rest and scoped to that node.
  • Custom Python components. Component code doesn't execute on the canvas — rewire the same capability as an MCP server or HTTP endpoint the node can call.
  • Vector store connections. The store and its embeddings config don't port; retrieval goes through a tool the node calls.
  • The Playground. LiveGraph orchestrates agents against your systems — it doesn't host an embedded chat surface for end users.

Why move

In Langflow you test a flow in the Playground and read the log when it finishes — the canvas is a build surface, not a live one. On LiveGraph the run executes on the same canvas you built: you watch each hop as it happens, a run parks at an approval gate until a person says yes, and dragging an edge mid-run steers the run you're watching instead of restarting it. Generated graphs and hand-built ones get the same treatment — nothing lands in a black box.

Start

Create an account, paste your simplest flow's export into the describe box, and run it once — or watch the live demo first: a real multi-agent graph running in your browser, no signup.

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