Building an Image Generation Service with Django

Welcome to the third lesson of our course on building an image generation service with Django! In our previous lessons, we created the PromptManager to format user inputs into detailed prompts and the ImageManager to handle storing and processing generated images. Now, we're ready to build the core component that brings everything together: the ImageGeneratorService.

The ImageGeneratorService is the central piece of our application that will:

1. Connect to Google's Gemini API to generate images
2. Use our PromptManager to format user inputs into effective prompts
3. Store generated images using our ImageManager
4. Provide access to all previously generated images

This service acts as the bridge between our application's components and the external AI service that actually creates the images. By encapsulating all the image generation logic in a dedicated service class, we maintain a clean separation of concerns in our application architecture.

In this lesson, we'll implement this service step by step, from setting up the API client to handling responses and errors. By the end, you'll have a fully functional image generation service that you can later integrate into a Django web application.

Before we can generate images, we need to set up a client to communicate with Google's Gemini API. The Gemini API provides access to Google's powerful image generation models, allowing us to create high-quality images from text prompts.

First, we need to install the Google Generative AI library. In a typical development environment, you would run:

pip install google-generativeai

In a Django project, it's best practice to store your API keys in environment variables. You can set these in your settings.py file or use a .env file with a library like django-environ.

Now, let's create our ImageGeneratorService class and set up the client in the constructor. We'll create a new file called image_generator_service.py in the myapp/services directory:

import os
from google import genai
from google.genai import types
from myapp.models import ImageManager, PromptManager

class ImageGeneratorService:
    def __init__(self):
        self.image_manager = ImageManager()
        self.gemini_client = genai.Client(api_key=os.environ.get("GEMINI_API_KEY"))

In this constructor, we're doing two important things:

1. Creating an instance of our ImageManager class to handle storing and retrieving images
2. Initializing the Gemini client with an API key from environment variables

The genai.Client is the main interface for interacting with Google's Generative AI services. We'll use this client to access the gemini-3.1-flash-image model, which specializes in generating images from text descriptions.