OpenAI Vision and Lark Integration

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Automate image-based approvals by connecting OpenAI Vision to Lark. Latenode's visual editor and affordable execution-based pricing make it easy to build custom workflows that extract data from images and send results to Lark for review. Scale as needed.

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OpenAI Vision

Lark

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect OpenAI Vision and Lark

Create a New Scenario to Connect OpenAI Vision and Lark

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 Lark will be your first step. To do this, click "Choose an app," find OpenAI Vision or Lark, 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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Connect OpenAI Vision

Sign In

Run node once

Add the Lark Node

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

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Authenticate Lark

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

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Configure the OpenAI Vision and Lark 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 Lark 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, Lark, 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 Lark integration works as expected. Depending on your setup, data should flow between OpenAI Vision and Lark (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 Lark

Lark + OpenAI Vision + Google Drive: When a new message containing an image is sent in a Lark group chat, the image is analyzed by OpenAI Vision (not available in the provided actions). The extracted text and the original image are then saved to a designated folder in Google Drive.

Lark + OpenAI Vision + Jira: When a user reports a bug in Lark with an image, the message triggers image analysis by OpenAI Vision (not available in the provided actions). A Jira ticket is then created, and the image is added as an attachment to the issue.

OpenAI Vision and Lark 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 Lark

Use Lark within Latenode to centralize team comms & automate notifications based on workflow triggers. Aggregate messages, streamline approvals, and post updates to specific channels. Benefit from Latenode's visual editor and logic tools for advanced routing that keeps everyone informed and aligned.

See how Latenode works

FAQ OpenAI Vision and Lark

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

To connect your OpenAI Vision account to Lark 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 Lark accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automatically analyze images and send summaries to Lark?

Yes, you can! Latenode's visual editor simplifies building complex workflows. Automatically analyze images with OpenAI Vision and instantly send summaries to Lark channels for team collaboration.

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

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

  • Detecting objects in images and sending notifications via Lark.
  • Extracting text from images and posting it to Lark channels.
  • Analyzing image sentiment and sharing results in Lark.
  • Moderating image content and alerting teams through Lark.
  • Creating image-based surveys and collecting responses in Lark.

How does Latenode handle OpenAI Vision's rate limits for image analysis?

Latenode includes built-in rate limiting and error handling. You can also use JavaScript blocks to implement custom retry logic, ensuring robust performance.

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

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

  • Complex image analysis workflows might require significant processing time.
  • Accuracy of image analysis depends on the quality of the image.
  • Lark's API has its own rate limits that may affect high-volume workflows.

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