Strapi CMS Plugin - Generate Content using Gen AI

An AI Strapi Plugin (@genai/gemini-content-generator) to generate content using Gen AI in Strapi

Introduction

The @genai/gemini-content-generator is a Strapi plugin designed to automate and enhance content creation using Google Gemini AI. This blog details the technical implementation, architecture, and publishing workflow of the plugin.

Strapi Plugin: https://github.com/suryakand/gemeni-content-generator-plugin

Example Strapi Project: There is an example GitHub Strapi project strapi-genai-plugin-example to showcase the use of plugin. Clone the repository and dollow the steps in the example project to see the plugin demo.

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Project Structure

The plugin follows the standard Strapi plugin architecture:

• admin/ — React-based UI for Strapi admin panel integration
• server/ — Node.js backend logic for Strapi plugin API and services
• dist/ — Compiled output for publishing

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Key Features

• Content Generation: Uses Google Gemini AI to generate and suggest content for Strapi collections.
• Admin UI: Seamless integration with Strapi admin panel for easy content generation and management.
• Configurable: API keys and settings are managed via environment variables for security and flexibility.

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Implementation Details

1. Google Gemini AI Integration

The plugin leverages the @google/generative-ai npm package to interact with Gemini AI APIs. The backend service in server/ handles API requests, authentication, and error handling.

// Example: server/services/gemini.js
const { GoogleGenerativeAI } = require('@google/generative-ai');

const gemini = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);

module.exports = {
  async generateContent(prompt) {
    return await gemini.generate({ prompt });
  },
};

2. Strapi Admin Panel Extension

The admin/ directory contains React components that extend the Strapi admin UI. These components provide buttons and forms for triggering content generation and displaying results.

• Uses Strapi Design System for consistent UI
• Handles async requests to the backend service

3. Plugin Configuration

Configuration is managed via environment variables and Strapi's plugin settings. Sensitive data like API keys are never committed to the repo, thanks to .env and .dockerignore rules.

GEMINI_API_KEY=your-google-gemini-api-key

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Publishing & CI/CD

The project includes a GitHub Actions workflow for automated publishing:

• On every push to main, the workflow:
  • Bumps the version
  • Tags the release
  • Publishes to npm
  • Creates a GitHub release

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Using the plugin

Installation

npm install @genai-cms/gemini-content-generator

Enable Plugin

Add the plugin to your config/plugins.js or config/plugins.ts:

module.exports = {
    'gemeni-content-generator': {
        enabled: true
    },
};

Creating a Gemini API Key

1. Visit the Google AI Studio and sign in with your Google account.
2. Click on "Create API key" and follow the prompts.
3. Copy the generated API key.
4. Add the API key to your .env file as shown below:

 GEMINI_API_KEY=<YOUR GEMENI API KEY>

Usage

After the plugin installation and configuration, you can access the Text AI field under CUSTOM fields tab. You can use this field to generate content for your collection types using the Google Gemini AI service. Below screenshot shows the custom Text AI.

For more details, refer to the plugin documentation or the Strapi marketplace page.

Example Strapi Project

There is an example GitHub Strapi project strapi-genai-plugin-example to showcase the use of plugin. Clone the repository and dollow the steps in the example project to see the plugin demo.

Sample Screen

Create new collection type in Strapi

Add fields (custom and regular) to the collection

Create new entry in newly created collection

Use the custom "Text AI" field to generate content using a prompt

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Conclusion

The @genai/gemini-content-generator plugin brings the power of Google Gemini AI to Strapi, making content creation faster and smarter. With a robust architecture, clean admin UI, and automated publishing, it's ready for production use and open-source collaboration.

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