# Google GenAI

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See the changelog of this Action type [here](/actions/google-genai.md).
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Note that this Action is only available in certain Tenants. [Get in touch with us](/support/support.md) if you don't see it and want to access it.
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## Overview <a href="#overview" id="overview"></a>

The **Google GenAI** Action allows users to enrich their data using Google Gemini AI models.

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In order to configure this action, you must first link it to a Listener. Go to [Building a Pipeline ](/the-workspace/pipelines/building-a-pipeline.md)to learn how this works.
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## Ports

These are the input and output ports of this Action:

<details>

<summary>Input ports</summary>

* **Default port** - All the events to be processed by this Action enter through this port.

</details>

<details>

<summary>Output ports</summary>

* **Default port** - Events are sent through this port if no error occurs while processing them.
* **Error port** - Events are sent through this port if an error occurs while processing them.

</details>

## Configuration

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Find **Google GenAI** in the **Actions** tab (under the **AI** group) and drag it onto the canvas.
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To open the configuration, click the Action in the canvas and select **Configuration**.
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Enter the required parameters:

<table><thead><tr><th width="231">Parameter</th><th>Description</th><th data-hidden></th></tr></thead><tbody><tr><td><strong>Location</strong><mark style="color:red;"><strong>*</strong></mark></td><td>Enter the Google Cloud location for Vertex AI (e.g., <code>us-central1</code>).</td><td></td></tr><tr><td><strong>Model</strong><mark style="color:red;"><strong>*</strong></mark></td><td>Choose the Vertex AI model version to use from the menu.</td><td></td></tr><tr><td><strong>System Instructions</strong><mark style="color:red;"><strong>*</strong></mark></td><td>Enter the required system instructions.</td><td></td></tr><tr><td><strong>Prompt Field</strong><mark style="color:red;"><strong>*</strong></mark></td><td>Enter the prompt you want to send to the model.</td><td></td></tr><tr><td><strong>Temperature</strong></td><td>Adjusts randomness of outputs: greater than <code>1</code> is random, <code>0</code> is deterministic, and <code>0.75</code> is a good starting value. Default value is <code>0.7</code></td><td></td></tr><tr><td><strong>MaxLength</strong></td><td>Maximum number of tokens to generate. A word is generally 2-3 tokens. The default value is 128 (min 1, max 8892).</td><td></td></tr><tr><td><strong>Output Format</strong><mark style="color:red;"><strong>*</strong></mark></td><td>Choose the required output format.</td><td></td></tr><tr><td><strong>JSON credentials</strong><mark style="color:red;"><strong>*</strong></mark></td><td>choose the required JSON credentials.</td><td></td></tr><tr><td><strong>Output Field</strong><mark style="color:red;"><strong>*</strong></mark></td><td>Give a name to the output field that will return the evaluation.</td><td></td></tr></tbody></table>
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Click **Save** to complete.
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---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.onum.com/the-workspace/pipelines/actions/ai/google-genai.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.