How to connect Google Vertex AI and Code
Create a New Scenario to Connect Google Vertex AI and Code
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 Code will be your first step. To do this, click "Choose an app," find Google Vertex AI or Code, 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.

Google Vertex AI
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.
Add the Code Node
Next, click the plus (+) icon on the Google Vertex AI node, select Code from the list of available apps, and choose the action you need from the list of nodes within Code.

Google Vertex AI
⚙
Code
Authenticate Code
Now, click the Code node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Code settings. Authentication allows you to use Code through Latenode.
Configure the Google Vertex AI and Code 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 Vertex AI and Code 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
⚙
Code
Trigger on Webhook
⚙
Google Vertex AI
⚙
⚙
Iterator
⚙
Webhook response
Save and Activate the Scenario
After configuring Google Vertex AI, Code, 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 Code integration works as expected. Depending on your setup, data should flow between Google Vertex AI and Code (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 Code
Google Sheets + Google Vertex AI + Code: New customer feedback added to a Google Sheet triggers sentiment analysis by Vertex AI. The sentiment score is then processed using JavaScript code, and the result is logged back into the same Google Sheet.
Code + Google Vertex AI + Slack: Code identifies critical server errors and extracts relevant logs. These logs are sent to Vertex AI for analysis using Gemini. Finally, an alert with the analysis result is sent to the on-call team in Slack.
Google Vertex AI and Code 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.
Similar apps
Related categories
About Code
Need custom logic within your Latenode workflows? Code lets you add JavaScript snippets and NPM modules directly into your automation flows. Transform data, handle complex calculations, and connect to unsupported APIs. Latenode makes it easy to manage code alongside no-code steps, ensuring scalability and maintainability.
Related categories
See how Latenode works
FAQ Google Vertex AI and Code
How can I connect my Google Vertex AI account to Code using Latenode?
To connect your Google Vertex AI account to Code 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 Code accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate code generation using Vertex AI's models?
Yes, you can! Latenode allows you to trigger code scripts based on AI-generated content. This unlocks automated testing, debugging, and complex logic, streamlining development workflows.
What types of tasks can I perform by integrating Google Vertex AI with Code?
Integrating Google Vertex AI with Code allows you to perform various tasks, including:
- Automatically generate code snippets based on Vertex AI prompts.
- Trigger code execution based on sentiment analysis from Vertex AI.
- Use Vertex AI to validate and improve code generated by scripts.
- Generate documentation from code and enhance it with AI insights.
- Automate testing of Vertex AI models using dynamically generated code.
How does Latenode simplify Vertex AI interaction within custom code?
Latenode streamlines integration by handling authentication and data transfer, letting you focus on code logic and AI model interaction.
Are there any limitations to the Google Vertex AI and Code integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Complex data transformations may require custom JavaScript code.
- Large data transfers can impact workflow execution time.
- Real-time code execution monitoring is subject to resource availability.