Google Vertex AI and OpenAI Vision Integration

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Enrich Google Vertex AI insights by routing images through OpenAI Vision’s advanced analysis. Latenode’s visual editor makes it easier to combine AI models and customize workflows with JavaScript, all at an affordable cost.

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Google Vertex AI

OpenAI Vision

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Vertex AI and OpenAI Vision

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

Add the Google Vertex AI Node

Select the Google Vertex AI node from the app selection panel on the right.

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Configure the Google Vertex AI

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

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Add the OpenAI Vision Node

Next, click the plus (+) icon on the Google Vertex AI 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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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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Configure the Google Vertex AI 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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Set Up the Google Vertex AI 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 Google Vertex AI, 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 Google Vertex AI and OpenAI Vision integration works as expected. Depending on your setup, data should flow between Google Vertex AI 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 Google Vertex AI and OpenAI Vision

Google Vertex AI + OpenAI Vision + Google Sheets: This workflow analyzes images with Google Vertex AI, extracts relevant data using OpenAI Vision (assuming a relevant action exists, but it does not, so it skips this), and logs the analysis results in a Google Sheet for reporting purposes.

Slack + Google Vertex AI + Slack: When a new file is uploaded to a Slack channel, the file is analyzed by Google Vertex AI (specifically Gemini), and the analysis result is sent as a message to the same Slack channel.

Google Vertex AI and OpenAI Vision integration alternatives

About Google Vertex AI

Use Vertex AI in Latenode to build AI-powered automation. Quickly integrate machine learning models for tasks like sentiment analysis or image recognition. Automate data enrichment or content moderation workflows without complex coding. Latenode’s visual editor makes it easier to chain AI tasks and scale them reliably, paying only for the execution time of each flow.

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.

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FAQ Google Vertex AI and OpenAI Vision

How can I connect my Google Vertex AI account to OpenAI Vision using Latenode?

To connect your Google Vertex AI account to OpenAI Vision on Latenode, follow these steps:

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

Can I analyze images and refine prompts based on content?

Yes, you can! Latenode allows you to visually connect OpenAI Vision to Google Vertex AI for dynamic prompt refinement, enhancing accuracy using no-code blocks and JS functions.

What types of tasks can I perform by integrating Google Vertex AI with OpenAI Vision?

Integrating Google Vertex AI with OpenAI Vision allows you to perform various tasks, including:

  • Automatically tagging product images based on visual content and context.
  • Generating detailed descriptions from images using multi-stage AI processing.
  • Classifying images and routing them to appropriate Google Vertex AI models.
  • Detecting objects in images and then using that data to create targeted prompts.
  • Building an AI-powered content moderation system with visual analysis.

How do I manage costs when using Google Vertex AI on Latenode?

Latenode provides detailed logging and usage statistics, empowering you to monitor and optimize your Google Vertex AI consumption effectively, preventing budget overruns.

Are there any limitations to the Google Vertex AI and OpenAI Vision integration on Latenode?

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

  • Complex workflows may require advanced JavaScript knowledge for optimal performance.
  • The processing speed depends on the API limits of both Google Vertex AI and OpenAI Vision.
  • Some advanced Google Vertex AI features might not have direct no-code equivalents.

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