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Documentation Index

Fetch the complete documentation index at: https://docs.lyzr.ai/llms.txt

Use this file to discover all available pages before exploring further.

This quickstart walks you through building, running, and inspecting a minimal SuperFlow — a Trigger that hands input to an LLM and returns its response. You’ll do everything in the Studio UI; no code required, and no need to set up an agent first.

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What you’ll build

A two-node SuperFlow:
  1. A Trigger that accepts a message as input.
  2. An LLM node that calls a model with that message and returns the answer.
By the end you’ll know how to create a SuperFlow, add and connect nodes, configure them, run it, and inspect the output.

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Steps

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1. Open SuperFlow

In Agent Studio, open the SuperFlow section from the sidebar. You’ll land on the SuperFlow list page.

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2. Create a new SuperFlow

Click New SuperFlow in the top-right. A modal appears. You can:
  • Pick a template from the gallery, or
  • Click Start Blank to start with an empty canvas.
For this quickstart, choose Start Blank, give it a name (for example, Hello SuperFlow), and confirm.

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3. Get to know the canvas

The editor opens with an empty canvas. Take a moment to orient yourself:
  • The node palette is on the left. Search or scroll to find nodes; drag them onto the canvas, or click to add.
  • The canvas is in the middle. You can pan, zoom, and use the controls in the bottom-left.
  • The toolbar sits in the top-right with Undo, Redo, Auto-align, Save, History, Approvals, Copy as JSON, and Run buttons.
  • The save indicator shows Saved, Saving…, or Unsaved changes. SuperFlow auto-saves a few seconds after every edit.

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4. Add the Trigger

Every SuperFlow needs exactly one Trigger node — it’s the entry point. In the node palette on the left, search for Trigger and drag it onto the canvas. That’s it — no configuration needed for this quickstart. Whatever message you type in the Run panel later will flow straight to the LLM.

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5. Add an LLM node

Back in the node palette, search for LLM. Drag it onto the canvas to the right of the Trigger. The LLM node is a one-shot model call — pick a model, give it a system prompt and a query, get a response. There’s no agent to set up first, which makes it the fastest way to get something running.

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6. Connect the nodes

Drag from the Trigger’s output handle (the dot on its right edge) to the LLM node’s input handle (the dot on its left edge). A connecting edge appears. If either node shows an “unreachable” warning, double-check the connection — every node must trace back to the Trigger.

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7. Configure the LLM

Click the LLM node. In the right drawer:
  • Provider — pick a provider (for example, OpenAI).
  • Model — pick a model (for example, gpt-4o-mini).
  • System prompt — write a short instruction, for example: 
    You are a helpful assistant. Answer the user's question concisely in one or two sentences.
Leave the Query field empty. The LLM node automatically picks up the message coming from the Trigger — you don’t need to wire it in by hand. Leave Temperature and Max tokens at their defaults for now.
Want to wire the query explicitly (for example, when your trigger payload has multiple fields)? Use an expression like {{ $('Trigger').json.message }} in the Query field, or click the field reference picker to insert it for you. See Expressions & data flow for the full syntax.
Once you’re comfortable with the LLM node, try the AI Agent node next. It runs a fully-configured Lyzr agent (with its tools, knowledge bases, and memory) as a single step — the right choice when you want to reuse an agent you’ve already built.

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8. Run it

Click the Run button in the top-right of the toolbar (it looks like a play icon, tooltip Run SuperFlow). The execution panel slides in from the right. Type your message in the input area — for example, “What is SuperFlow in one sentence?” — and click Run. The message flows straight to the LLM node.

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9. Watch the run

As the SuperFlow runs:
  • Each node on the canvas shows a live status. Amber pulse = running, green check = completed, red = error.
  • Edges connecting active nodes animate while data flows.
  • The execution panel shows each node’s output as it completes. Click a node’s card to expand its JSON output.
When the run finishes, expand the LLM card to see the model’s response.

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10. Iterate

You now have a working SuperFlow. From here you can:
  • Add more nodes — try an If node to branch based on the LLM’s response, or an HTTP Request to send the answer somewhere.
  • Swap the LLM node for an AI Agent node when you want tool calls, knowledge-base lookups, or memory.
  • Open History in the toolbar to replay past runs and inspect their outputs.
  • Convert this run into a webhook or a scheduled trigger — see Triggers & schedules.

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What’s next