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

Add the Google Cloud Text-To-Speech Node
Select the Google Cloud Text-To-Speech node from the app selection panel on the right.


Google Cloud Text-To-Speech

Configure the Google Cloud Text-To-Speech
Click on the Google Cloud Text-To-Speech node to configure it. You can modify the Google Cloud Text-To-Speech 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 Text-To-Speech 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.
Configure the Google Cloud Text-To-Speech 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 Text-To-Speech 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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OpenAI Vision
Trigger on Webhook
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Webhook response

Save and Activate the Scenario
After configuring Google Cloud Text-To-Speech, 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 Text-To-Speech and OpenAI Vision integration works as expected. Depending on your setup, data should flow between Google Cloud Text-To-Speech 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 Text-To-Speech and OpenAI Vision
Slack + OpenAI Vision + Google Cloud Text-To-Speech: When a new file is added to a Slack channel, analyze the image with OpenAI Vision, convert the description to audio using Google Cloud Text-To-Speech, and send the audio file to the same Slack channel.
Discord bot + OpenAI Vision + Google Cloud Text-To-Speech: When a new message with an image is posted to a Discord channel, analyze the image with OpenAI Vision, convert the description to audio using Google Cloud Text-To-Speech, and then post the audio file in the same Discord channel using a Discord bot.
Google Cloud Text-To-Speech and OpenAI Vision integration alternatives

About Google Cloud Text-To-Speech
Use Google Cloud Text-To-Speech in Latenode to automate voice notifications, generate audio content from text, and create dynamic IVR systems. Integrate it into any workflow with a drag-and-drop interface. No code is required, and it's fully customizable with JavaScript for complex text manipulations. Automate voice tasks efficiently without vendor lock-in.
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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 Cloud Text-To-Speech and OpenAI Vision
How can I connect my Google Cloud Text-To-Speech account to OpenAI Vision using Latenode?
To connect your Google Cloud Text-To-Speech account to OpenAI Vision on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google Cloud Text-To-Speech and click on "Connect".
- Authenticate your Google Cloud Text-To-Speech and OpenAI Vision accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I narrate image descriptions using AI?
Yes, you can! Latenode lets you trigger Google Cloud Text-To-Speech using OpenAI Vision's image analysis for automated, accessible content. Automate at scale with no code and JavaScript tools.
What types of tasks can I perform by integrating Google Cloud Text-To-Speech with OpenAI Vision?
Integrating Google Cloud Text-To-Speech with OpenAI Vision allows you to perform various tasks, including:
- Create audio descriptions of images for visually impaired users.
- Generate spoken summaries of visual content for social media.
- Automate the creation of narrated slideshows from image datasets.
- Produce educational content with image recognition and voiceover.
- Develop accessibility features for image-based applications.
How do I manage Google Cloud Text-To-Speech voices in Latenode?
Latenode allows you to select and customize Google Cloud Text-To-Speech voices directly within your workflows, using a simple visual interface or code.
Are there any limitations to the Google Cloud Text-To-Speech and OpenAI Vision integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- API usage limits of Google Cloud Text-To-Speech and OpenAI Vision apply.
- Complex image analysis may increase workflow execution time.
- Audio quality is dependent on Google Cloud Text-To-Speech's capabilities.