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

Add the Google Cloud Storage Node
Select the Google Cloud Storage node from the app selection panel on the right.


Google Cloud Storage

Configure the Google Cloud Storage
Click on the Google Cloud Storage node to configure it. You can modify the Google Cloud Storage URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the OpenAI Vision Node
Next, click the plus (+) icon on the Google Cloud Storage node, select OpenAI Vision from the list of available apps, and choose the action you need from the list of nodes within OpenAI Vision.


Google Cloud Storage
⚙
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.
Configure the Google Cloud Storage 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.
Set Up the Google Cloud Storage 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.

JavaScript
⚙
AI Anthropic Claude 3
⚙
OpenAI Vision
Trigger on Webhook
⚙

Google Cloud Storage
⚙
⚙
Iterator
⚙
Webhook response

Save and Activate the Scenario
After configuring Google Cloud Storage, 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 Cloud Storage and OpenAI Vision integration works as expected. Depending on your setup, data should flow between Google Cloud Storage 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 Cloud Storage and OpenAI Vision
Google Cloud Storage + OpenAI Vision + Slack: When a new file is uploaded to a Google Cloud Storage bucket, OpenAI Vision analyzes the image for policy violations. If a violation is detected, a notification is sent to a designated Slack channel.
Google Cloud Storage + OpenAI Vision + Google Sheets: This automation extracts text from images stored in a Google Cloud Storage bucket using OpenAI Vision. The extracted text is then logged into a Google Sheet, with each image's text populating a new row.
Google Cloud Storage and OpenAI Vision integration alternatives

About Google Cloud Storage
Use Google Cloud Storage in Latenode for automated file management. Upload, download, and manage files in your workflows. Automate backups, data archiving, or image processing. Connect GCS to other apps for seamless data transfer and triggering events. Latenode's visual editor simplifies complex file-based automations.
Similar apps
Related categories
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.
Similar apps
Related categories
See how Latenode works
FAQ Google Cloud Storage and OpenAI Vision
How can I connect my Google Cloud Storage account to OpenAI Vision using Latenode?
To connect your Google Cloud Storage account to OpenAI Vision on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Storage and click on "Connect".
- Authenticate your Google Cloud Storage and OpenAI Vision accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automatically tag images in Google Cloud Storage using OpenAI Vision?
Yes, you can! Latenode's visual editor simplifies connecting Google Cloud Storage to OpenAI Vision, automating image analysis and tagging to improve content discoverability.
What types of tasks can I perform by integrating Google Cloud Storage with OpenAI Vision?
Integrating Google Cloud Storage with OpenAI Vision allows you to perform various tasks, including:
- Automatically labeling images stored in Google Cloud Storage buckets.
- Extracting text from images and storing the results in a database.
- Detecting objects in images and generating reports.
- Moderating content by identifying inappropriate images.
- Creating searchable image libraries using AI-generated tags.
Can I process very large files from Google Cloud Storage on Latenode?
Yes, Latenode efficiently handles large files by streaming data between Google Cloud Storage and OpenAI Vision, minimizing memory usage for processing.
Are there any limitations to the Google Cloud Storage and OpenAI Vision integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- OpenAI Vision’s rate limits apply; high-volume processing may require optimization.
- Large image files may take longer to process depending on network speeds.
- Complex custom logic may require JavaScript nodes for advanced manipulation.