Gemini AI Integrations with Bit Flows – Automate Google AI Tasks

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In this guide, we’ll walk you through the Gemini integrations using Bit Flows. While we’ll use Bit Form as the trigger in this example, you can choose any trigger that suits your needs. Once the setup is complete, data from each form submission will be automatically sent to Gemini for processing or generating a response.

This beginner-friendly tutorial takes you through each step, making it simple to build your first AI-powered automation using Bit Flows and Gemini.

Authorization of Gemini Integrations

To set Gemini as an action in Bit Flows, first open your Bit Flows Dashboard, then either create a new flow or open an existing one. In the Flow Builder, click the plus (+) icon to add an action. From the list of available apps, search for and select Gemini.

After selecting your preferred action, the next step is to choose an event. For example, in this case, we’ve selected the “Ask Gemini” event.

After selecting the action event, a new pop-up will appear. Here, you need to connect your Gemini account. If you’ve already connected to Gemini before and want to use the same account, simply select it from the “Select Connection” dropdown. If not, click on “Add Connection” to create a new one.

When you click the Add Connection button, you’ll be asked to enter a name for your connection and provide your token in to Value field.

To get your Gemini API Token, follow these steps:

• Go to Google AI Studio
• Click on “Get API Key” in the top-right corner
• Click “Create API Key”
• Choose your existing project
• Click “Create API Key in existing project”
• Once the key is generated, copy it
• Paste the copied key into the Value field in Bit Flows

After entering your token, click on Connect. Once connected successfully, a popup will appear where you can configure the integration settings and map the fields.

Model: Select the Gemini model you want to use for this integration.

Message: Enter the message you want to send to Gemini. You can also map available form fields to include dynamic content in the message. Additionally, you can use Flow, Math, String, and System functions to enhance your message logic.
Learn more about Field Mapping.

Advance Feature

If you want to use advanced features, first enable the “Show Advanced Features” option.

Max Token: Specify the maximum number of tokens Gemini can use in its response. The default value is 1024. This controls the length of the output—higher values allow longer responses, while lower values keep them shorter.

Temperature: Controls the randomness of the output. Values can range from [0.0,1.0], inclusive. A value closer to 1.0 will produce responses that are more varied and creative, while a value closer to 0.0 will typically result in more straightforward responses from the model.

Top-p Sampling Value: This setting defines the maximum cumulative probability of tokens to consider when generating a response.
Enter a value between 0.0 and 1.0—lower values make the output more focused and deterministic, while higher values allow for more diverse and creative responses.

Top-k Sampling Value: This setting controls the maximum number of tokens Gemini will consider when generating a response.
Enter a value between 1 and 100—lower values make the output more focused and consistent, while higher values allow for more variety and randomness in the response.

Stop Sequence: A set of character sequences that tells Gemini when to stop generating output. If specified, the response will automatically end at the first occurrence of any stop sequence. This helps control where and how the output should finish.

Once you’ve finished these settings, you can either click the “Test Run” button to check if the integration is working correctly or simply close the popup to complete the setup.

You also have the option to test the full flow. You can either click “Listen Response” and then run the trigger event (e.g., submit the form), or use existing data to test the integration and make sure everything works correctly.

After completing all the steps, click the “Logs” icon at the top-right corner of the Flow Builder to view your integration logs. Logs help you verify if the trigger and action worked correctly and make it easier to spot and fix any issues.

That’s it! You’ve successfully set up an automation in Bit Flows to connect your trigger with Gemini. Now, whenever the trigger event occurs, a message will be sent to Gemini, and you’ll receive a dynamic AI-generated response based on your configuration. This completes your Gemini integrations with Bit Flows, enabling smart, automated workflows powered by AI.

If you need more help or want to explore more integrations, feel free to check out our User Guide.

Check out our easy-to-follow tutorials!

• How to Integrate Gemini AI with Bit Flows