OpenAI Vision and Feedly Integration

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Automate image-based content curation: Use OpenAI Vision to analyze Feedly articles and categorize them based on visual content. Latenode’s visual editor and affordable execution pricing make this complex task accessible. Customize further with JavaScript for unique filtering.

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OpenAI Vision

Feedly

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect OpenAI Vision and Feedly

Create a New Scenario to Connect OpenAI Vision and Feedly

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 OpenAI Vision, triggered by another scenario, or executed manually (for testing purposes). In most cases, OpenAI Vision or Feedly will be your first step. To do this, click "Choose an app," find OpenAI Vision or Feedly, and select the appropriate trigger to start the scenario.

Add the OpenAI Vision Node

Select the OpenAI Vision node from the app selection panel on the right.

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OpenAI Vision

Configure the OpenAI Vision

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

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Run node once

Add the Feedly Node

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

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Authenticate Feedly

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

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Configure the OpenAI Vision and Feedly 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 OpenAI Vision and Feedly 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 OpenAI Vision, Feedly, 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 OpenAI Vision and Feedly integration works as expected. Depending on your setup, data should flow between OpenAI Vision and Feedly (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect OpenAI Vision and Feedly

Feedly + OpenAI Vision + Slack: Whenever a new article appears in a Feedly feed, OpenAI Vision analyzes the featured image. The analysis results are then posted to a specified Slack channel.

Feedly + OpenAI Vision + Slack: Upon a new article in Feedly, extract image URL to OpenAI Vision for analysis. Then, post a summary and analysis of the article and image to a specified Slack channel.

OpenAI Vision and Feedly integration alternatives

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.

About Feedly

Aggregate and filter Feedly articles within Latenode to automate content-driven workflows. Track brand mentions, industry trends, or competitor activity, then instantly trigger actions like posting to social media, updating databases, or notifying teams—all based on custom rules and logic.

See how Latenode works

FAQ OpenAI Vision and Feedly

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

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

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

Can I automatically categorize Feedly articles based on image analysis?

Yes, you can! Latenode lets you analyze Feedly article images with OpenAI Vision, then tag or filter the article, automating content management & enhancing information discovery.

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

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

  • Identify objects in Feedly article images and tag the articles.
  • Summarize Feedly articles based on image and text content.
  • Filter Feedly articles based on detected image attributes.
  • Create custom alerts for specific image types in Feedly feeds.
  • Extract text from images within Feedly articles.

How does Latenode handle OpenAI Vision API key security?

Latenode securely stores your OpenAI Vision API keys using encrypted vaults. Keys are only accessible during workflow execution for enhanced security.

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

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

  • Rate limits of the OpenAI Vision API may affect processing speed.
  • Accuracy of image analysis depends on image quality.
  • Feedly API limits may restrict the number of articles processed.

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