Connecting Google Gemini AI with Oracle APEX: My Hands-On Experience

Prathap Reddy — Wed, 19 Aug 2026 12:18:16 +0000

Recently, I started exploring the Generative AI capabilities available in Oracle APEX. As part of my learning, I wanted to see how easily I could connect an external AI model to APEX and test it in a real environment.

For this experiment, I chose Google Gemini and configured it through the Generative AI Services available in Oracle APEX.

The setup was quite straightforward, and I wanted to document the steps I followed and a few things I learned along the way.

Why I Tried This

I've been working with Oracle APEX and wanted to understand how AI can be brought into low-code application development.

Instead of building a separate application or writing a custom integration from scratch, APEX provides configuration options for connecting to generative AI services.

That made it a good opportunity for me to try the integration myself and understand what happens behind the scenes.

What I Used

For my setup, I used:

Oracle APEX

Google Gemini

Gemini API key

APEX Generative AI Services

APEX Workspace Administrator access

I also used my own APEX environment to test the configuration.

Configuring Gemini in Oracle APEX

I started by navigating to:

Workspace Utilities → Generative AI Services → Create/Edit

From there, I created a new Generative AI Service and selected Google Gemini as the AI provider.

I gave the configuration a meaningful name so that it would be easy to identify later.

Configuring the API Details

The next step was configuring the Gemini API details.

For the API endpoint, I used:

https://generativelanguage.googleapis.com/v1beta

I then provided the required model information and configured the credentials.

One thing I found useful here was that APEX provides the configuration directly from the UI, so I didn't have to write a separate REST integration just to establish the connection.

Adding the Gemini API Key

The next part was adding the Gemini API key.

I enabled the option to create credentials and entered the API key generated for my Gemini environment.

I also made sure that the API key had the required access for the Generative Language API.

For security reasons, I would recommend never publishing your actual API key in screenshots, blog posts, GitHub repositories, or other public places.

Enabling Gemini for APEX

After configuring the credentials, I looked at the APEX settings.

There are options such as:

Used by App Builder

Default for New Apps

For my testing, I enabled the appropriate option so that the configured AI service could be used by APEX App Builder.

This was one of the interesting parts of the setup because the integration is handled through the APEX configuration rather than requiring me to build the entire connection manually.

Testing the Connection

Before considering the configuration complete, I used the Test Connection option.

I think this is an important step because it immediately tells you whether the basic configuration is working.

If something goes wrong, I would first check:

API key

Model ID

Base URL

Endpoint URL

Credentials configuration

Network/connectivity

Whether the selected model is supported by the configured APEX integration

My Configuration Screen

This is the configuration screen from my APEX environment:

The screenshot shows the Gemini provider, API configuration, model information, credentials, and the App Builder settings.

What I Learned

The biggest takeaway for me was that connecting an AI service to APEX doesn't necessarily require a large amount of custom development.

The configuration is largely handled through the APEX interface, which makes it easier to experiment with generative AI capabilities while continuing to work within a low-code environment.

I also learned that small configuration details matter. The API key, model ID, endpoint, and credential settings all need to match the AI service being used.

Where This Could Be Useful

There are several areas where I think this type of integration could be useful in APEX applications:

Generating application content

Assisting developers during application development

Natural-language interactions

Generating SQL or application-related suggestions

AI-assisted application development

Building smarter business applications

The actual use case will depend on the application and the AI capabilities being enabled.

A Small Lesson From My Experiment

One thing I would recommend to anyone trying this for the first time is don't immediately start troubleshooting the entire application when something doesn't work.

Start with the connection itself.

Check the API key, model, endpoint, credentials, and then use Test Connection.

Once the basic connection works, move on to testing the AI features inside APEX.

That approach makes troubleshooting much easier.

Final Thoughts

This was a useful hands-on experiment for me because it helped me understand how Oracle APEX and Generative AI can work together.

I'm still exploring what can be built with this integration, but I think the combination of low-code development and AI has a lot of potential.

My next step is to move beyond the configuration and build an actual business use case with APEX and Gemini rather than just testing the connection.

Have you tried integrating Gemini, OpenAI, or another LLM with Oracle APEX? I'd be interested to hear about your experience and what you built.

OracleAPEX #GeminiAI #Oracle #GenerativeAI #LowCode #AI #AppDevelopment

Connecting Oracle APEX to Google Gemini AI: A Step-by-Step Guide

Prathap Reddy — Wed, 19 Aug 2026 11:47:00 +0000

Introduction

Oracle APEX has quietly made adding generative AI to low-code apps as simple as filling out a form. No middleware, no custom REST wrappers, no separate AI service to host. In this post, I'll walk through exactly how I connected Google Gemini to my APEX workspace using APEX's native Generative AI Services, and what it unlocks once it's set up.

Why this matters

Most teams assume "adding AI" means weeks of integration work and a dedicated ML engineer. Oracle APEX flips that: plugging in a foundation model is now a configuration task, not an engineering project. Once connected, AI capabilities like Builder AI, natural language search, and AI-assisted page generation work automatically — across every app in your workspace.

Prerequisites
An Oracle APEX workspace ( tested on 26.1)
A Google Gemini API key (Google AI Studio)
Workspace admin access to configure Generative AI Services
Step-by-step setup

Navigate to Generative AI Services
From Workspace Utilities → Generative AI Services → Create/Edit.
Set the AI Provider
Choose Google Gemini from the AI Provider dropdown, and give it a name (e.g. "Gemini API Key").
Configure the Base URL and Endpoint URL
Both point to Gemini's API:

https://generativelanguage.googleapis.com/v1beta

Add credentials
Toggle "Create Credentials" on, and paste in your Gemini API key. APEX stores this securely — you won't need to manage it in code anywhere.
Enable it for App Builder
Toggle Used by App Builder and, optionally, Default for New Apps, so every new app in the workspace automatically uses Gemini.
Test the connection
Click Test Connection to confirm APEX can reach Gemini before saving.

What this unlocks

Once configured, several AI-powered features become available immediately:

Builder AI — generate pages, forms, and reports from natural language descriptions
AI-assisted natural language search in Interactive Reports
AI-generated data models and content during app creation

**Model version compatibility

Not every Gemini model works out of the box with APEX's Generative AI Services. I found that Gemini Flash 3 and onward is what you need — earlier model versions either failed to respond correctly or weren't supported by APEX's integration layer. If you're setting this up and things aren't working, check your Model ID first before troubleshooting anything else.

API key scope
Make sure the API key you generate in Google AI Studio has access to the Generative Language API specifically — a key created for a different Google Cloud service won't authenticate correctly here.

Test Connection is your friend

Don't skip the Test Connection button before saving. It catches URL/endpoint mismatches and auth issues immediately, rather than surfacing as a vague error later inside Builder AI or natural language search.

Takeaway

Low-code and generative AI are converging faster than most people realize. If you're building on Oracle APEX and haven't tried wiring in a foundation model yet, it's a 10-minute setup that changes what your app builder can do.

Have you connected an LLM into APEX or another low-code platform? I'd love to hear what you built.

DEV Community: Prathap Reddy

Connecting Google Gemini AI with Oracle APEX: My Hands-On Experience

OracleAPEX #GeminiAI #Oracle #GenerativeAI #LowCode #AI #AppDevelopment

Connecting Oracle APEX to Google Gemini AI: A Step-by-Step Guide