Linear and OpenAI Vision Integration

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Automatically create Linear tickets from images analyzed by OpenAI Vision. Latenode's visual editor simplifies the setup while its affordability lets you process large volumes of images.

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Linear

OpenAI Vision

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Linear and OpenAI Vision

Create a New Scenario to Connect Linear and OpenAI Vision

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Linear, triggered by another scenario, or executed manually (for testing purposes). In most cases, Linear or OpenAI Vision will be your first step. To do this, click "Choose an app," find Linear or OpenAI Vision, and select the appropriate trigger to start the scenario.

Add the Linear Node

Select the Linear node from the app selection panel on the right.

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Linear

Configure the Linear

Click on the Linear node to configure it. You can modify the Linear URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Linear

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Run node once

Add the OpenAI Vision Node

Next, click the plus (+) icon on the Linear node, select OpenAI Vision from the list of available apps, and choose the action you need from the list of nodes within OpenAI Vision.

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OpenAI Vision

Authenticate OpenAI Vision

Now, click the OpenAI Vision node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your OpenAI Vision settings. Authentication allows you to use OpenAI Vision through Latenode.

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Linear

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OpenAI Vision

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Connect OpenAI Vision

Sign In

Run node once

Configure the Linear and OpenAI Vision Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Run node once

Set Up the Linear and OpenAI Vision Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Linear, OpenAI Vision, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Linear and OpenAI Vision integration works as expected. Depending on your setup, data should flow between Linear and OpenAI Vision (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Linear and OpenAI Vision

Linear + Slack: When a new issue is created in Linear, especially if an image is attached (though image analysis is not directly possible with the available actions), a notification is sent to a specified Slack channel to alert the relevant teams.

Google Sheets + Linear: When a new row is added to a Google Sheet (e.g., with receipt data), a new issue is created in Linear to track the expense. The issue description would need to be populated with data extracted externally, as direct image processing isn't supported here.

Linear and OpenAI Vision integration alternatives

About Linear

Connect Linear to Latenode for automated issue tracking. Streamline bug reporting from various sources. Automatically create Linear issues from form submissions or customer support tickets. Update issue statuses based on events in other systems like Git or CI/CD pipelines, all within a scalable, low-code workflow.

About OpenAI Vision

Use OpenAI Vision in Latenode to automate image analysis tasks. Detect objects, read text, or classify images directly within your workflows. Integrate visual data with databases or trigger alerts based on image content. Latenode's visual editor and flexible integrations make it easy to add AI vision to any process. Scale automations without per-step pricing.

See how Latenode works

FAQ Linear and OpenAI Vision

How can I connect my Linear account to OpenAI Vision using Latenode?

To connect your Linear account to OpenAI Vision on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Linear and click on "Connect".
  • Authenticate your Linear and OpenAI Vision accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automatically create Linear tickets from image analysis?

Yes, you can! Latenode allows creating automated workflows that analyze images via OpenAI Vision and instantly generate Linear tickets, streamlining issue tracking.

What types of tasks can I perform by integrating Linear with OpenAI Vision?

Integrating Linear with OpenAI Vision allows you to perform various tasks, including:

  • Automatically creating Linear tickets from images of UI bugs.
  • Adding detailed image-based context to existing Linear issues.
  • Categorizing new Linear issues based on image content analysis.
  • Triggering Linear updates based on changes detected in images.
  • Generating visual summaries of Linear project progress.

How does Latenode handle Linear API rate limits for large teams?

Latenode offers robust error handling and queue management to optimize Linear API calls, preventing rate limit issues and ensuring reliable automation.

Are there any limitations to the Linear and OpenAI Vision integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • OpenAI Vision processing times depend on image complexity and API load.
  • Very large image files may require pre-processing before analysis.
  • Complex workflow logic requires familiarity with Latenode's interface.

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