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Quick Start Guide

This guide takes you from a blank canvas to a running workflow in about 5 minutes. You will build a workflow that receives a webhook, makes an HTTP request, and returns a response — then test it locally using the CLI.

Before You Begin

Make sure you have:

  • A Tensorify account at app.tensorify.io
  • Python 3.9+ installed
  • The CLI installed: curl -fsSL https://cli.tensorify.io/install | sh (Windows: irm https://cli.tensorify.io/install.ps1 | iex)

See Installation for detailed setup.

Step 1: Create a Workflow

Sign in to app.tensorify.io and complete the onboarding to create your workspace. Then from the dashboard:

  1. Click New Workflow
  2. Give it a name — for example, my-first-workflow
  3. Click Create

The canvas will open with an empty graph.

Step 2: Add a Webhook Trigger

Every workflow needs a trigger — the event that starts execution. Add a Webhook node:

  1. In the node palette on the left, find Webhook under Triggers
  2. Drag it onto the canvas
  3. Click the node to open its settings panel
  4. Leave the defaults as-is for now (method: POST, verification: none)

Step 3: Add an HTTP Request Node

Next, add an action. This node will call an external API when the webhook fires:

  1. Drag an HTTP Request node onto the canvas
  2. In its settings, set:
    • Method: GET
    • URL: https://httpbin.org/get
  3. Connect the payload output of the Webhook node to the body input of the HTTP Request node

Step 4: Configure & Authenticate the CLI

tensorify init
tensorify login

tensorify init creates the runner config. tensorify login opens your browser to sign in and links the CLI to your workspace.

On a VPS or headless server, use tensorify init --api-key tfk_your_key instead. Get the key from Settings → API Keys in the app. See Installation for details.

Step 5: Start the Runner

tensorify runner start

Expected output:

✓ Connected to Tensorify
✓ Runner registered
  Waiting for workflows from the app...

Leave this terminal running.

Canvas tests use test signals from the editor only. For production webhooks, deploy from the Deploy dialog — see Running Workflows and Deploying Workflows.

Step 6: Test from the Canvas

Back in the browser:

  1. Click the Test button in the top toolbar
  2. Select the HTTP Request node as the target
  3. Click Run to Selected

The workflow executes on your local machine up to the selected node.

Your terminal will show the execution log. In the editor, click the HTTP Request node to see its output — the JSON response from httpbin.

What You Built

Webhook Trigger → HTTP Request

When this workflow receives a POST request, it calls httpbin.org/get and records the response. You can now extend it by adding Transform, If, Code, or any other nodes.

Next Steps

  • Core Concepts — understand how nodes, edges, and data flow work
  • Deploying Workflows — put this workflow in production
  • Plugins — browse all available nodes
  • Guides — follow a complete real-world automation from start to finish
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