| name | image-gen |
| description | Create and edit images using OpenAI image generation API with GPT image models (gpt-image-1, gpt-image-1-mini, gpt-image-1.5 and later). Use when the user asks to generate an image from a text prompt, edit or modify an existing image, create illustrations, logos, icons, concept art, or any visual content using AI image generation. Also use when combining multiple source images into a new composition. |
| license | Complete terms in LICENSE.txt |
| metadata | {"author":"Yohan Lasorsa"} |
Image Generation & Editing
Generate and edit images via OpenAI-compatible REST APIs using the bundled Python CLI script. No external dependencies required (Python 3.8+ standard library only). Compatible with OpenAI, Azure OpenAI (v1 endpoint), and other OpenAI-compatible providers.
Quick Reference
Supported Models
| Model | Generation | Editing | Notes |
|---|
gpt-image-1 | ✓ | ✓ | Base GPT image model |
gpt-image-1-mini | ✓ | ✓ | Smaller, faster variant |
gpt-image-1.5 | ✓ | ✓ | Latest, most capable |
Key Parameters
| Parameter | Values | Default | Notes |
|---|
size | auto, 1024x1024, 1536x1024 (landscape), 1024x1536 (portrait) | auto | |
quality | auto, low, medium, high | auto | |
background | auto, transparent, opaque | auto | Transparent requires png or webp output |
output_format | png, jpeg, webp | png | |
output_compression | 0–100 | 100 | Only for jpeg/webp |
n | 1–10 | 1 | Number of images |
moderation | auto, low | auto | Generation only |
Usage
The script at scripts/image_gen.py is a zero-dependency Python CLI.
Authentication
Variables can be defined in a .env file in the working directory or any parent directory.
| Variable | Description | Default |
|---|
OPENAI_API_KEY | API key (required) | — |
OPENAI_BASE_URL | Base URL for custom endpoints (Azure OpenAI, etc.) | https://api.openai.com/v1 |
OPENAI_IMAGE_MODEL | Default model | gpt-image-1.5 |
All variables can also be passed as CLI flags (--api-key, --base-url, --model).
Generate an Image
python scripts/image_gen.py generate "A cat wearing a top hat" -o ./output
With full options:
python scripts/image_gen.py generate "A minimalist coffee shop logo" \
--size 1024x1024 \
--quality high \
--background transparent \
--output-format png \
-o ./output
Edit an Image
python scripts/image_gen.py edit "Add sunglasses to the person" \
-i photo.png -o ./output
Multiple input images (up to 16):
python scripts/image_gen.py edit "Create a gift basket with these items" \
-i item1.png -i item2.png -i item3.png -o ./output
With mask for inpainting:
python scripts/image_gen.py edit "Replace the background with a beach" \
-i photo.png --mask mask.png -o ./output
Important: Do not pass --model unless the user explicitly asks for a specific model. The default model is resolved from OPENAI_IMAGE_MODEL env var or falls back to gpt-image-1.5.
Prompt Guidelines
For best results with GPT image models:
- Be specific and descriptive: include subject, style, mood, colors, composition.
- Specify the art style: "photorealistic", "watercolor", "flat illustration", "3D render", etc.
- For logos/icons: request "transparent background" and set
--background transparent --output-format png.
- For edits: clearly describe what should change and what should remain.
- The maximum prompt length for GPT image models is 32,000 characters.
Output
-o accepts a file path or a directory:
- File path (e.g.
-o logo.png): saves directly to that path. With --n >1, appends _1, _2, etc. before the extension. Intermediate directories are created automatically.
- Directory (e.g.
-o ./out): saves as image_1.{ext}, image_2.{ext}, etc.
Existing files are never overwritten — a numeric suffix is appended automatically if the target already exists.
The script prints saved file path(s) to stdout (one per line) and any revised prompts to stderr.
Recipes
Before generating an images, always first generate a prompt using these copy/paste instructions for prompt recipes: references/sample-prompts.md.
An image genaration/editing workflow consists of 2 steps:
- Generate a prompt for the image generation/editing based on the user query using the sample prompts.
- Pass the generated prompt to the image generation/editing command to generate/edit the image.
