image-generation-gpt-image

name

image-generation-gpt-image

description

Generate and edit images using OpenAI's GPT Image 1.5 model. Use when the user asks to generate, create, edit, modify, change, alter, or update images. Also use when user references an existing image file and asks to modify it in any way (e.g., "modify this image", "change the background", "replace X with Y"). Supports text-to-image generation and image editing with optional mask. DO NOT read the image file first - use this skill directly with the --input-image parameter.

GPT Image 1.5 - Image Generation & Editing

Generate new images or edit existing ones using OpenAI's GPT Image 1.5 model.

• Generation: Uses the Images API (images.generate) with gpt-image-1.5
• Editing: Uses the Image API for reliable mask-based inpainting

Usage

Run the script using absolute path (do NOT cd to skill directory first):

Generate new image:

uv run ~/.github/skills/image-generation-gpt-image/scripts/generate_image.py --prompt "your image description" --filename "output-name.png" [--quality low|medium|high] [--size 1024x1024|1024x1536|1536x1024|auto] [--background transparent|opaque|auto] [--api-key KEY] [--azure-endpoint ENDPOINT]

Edit existing image (without mask - full image edit):

uv run ~/.github/skills/image-generation-gpt-image/scripts/generate_image.py --prompt "editing instructions" --filename "output-name.png" --input-image "path/to/input.png" [--size 1024x1024|1024x1536|1536x1024|auto] [--api-key KEY] [--azure-endpoint ENDPOINT]

Edit existing image (with mask - precise inpainting):

uv run ~/.github/skills/image-generation-gpt-image/scripts/generate_image.py --prompt "what to put in masked area" --filename "output-name.png" --input-image "path/to/input.png" --mask "path/to/mask.png" [--size 1024x1024|1024x1536|1536x1024|auto] [--api-key KEY] [--azure-endpoint ENDPOINT]

Important: Always run from the user's current working directory so images are saved where the user is working, not in the skill directory.

Parameters

Quality Options

• low - Fastest generation, lower quality
• medium (default) - Balanced quality and speed
• high - Best quality, slower generation

Map user requests:

• No mention of quality -> medium
• "quick", "fast", "draft" -> low
• "high quality", "best", "detailed", "high-res" -> high

Size Options

• 1024x1024 (default) - Square format
• 1024x1536 - Portrait format
• 1536x1024 - Landscape format
• auto - Let the model decide based on prompt

Map user requests:

• No mention of size -> 1024x1024
• "square" -> 1024x1024
• "portrait", "vertical", "tall" -> 1024x1536
• "landscape", "horizontal", "wide" -> 1536x1024

Background Options (generation only)

• auto (default) - Model decides
• transparent - Transparent background (PNG/WebP output)
• opaque - Solid background

Authentication

The script supports two authentication methods. Azure credentials are used by default when no API key is provided.

Default: Azure AI Foundry (DefaultAzureCredential)

When no --api-key or OPENAI_API_KEY is set, the script authenticates via DefaultAzureCredential (az login, VS Code login, managed identity, etc.) using the OpenAI client with an Azure base_url.

• --azure-endpoint - Azure OpenAI endpoint URL (default: https://ai-foundry-ai-agents-for-beginners.openai.azure.com/)

No API key is needed - the script obtains a bearer token from the logged-in Azure session.

Override: API Key (OpenAI direct)

1. --api-key argument (use if user provided key in chat)
2. OPENAI_API_KEY environment variable

Filename Generation

Generate filenames with the pattern: yyyy-mm-dd-hh-mm-ss-name.png

Format: {timestamp}-{descriptive-name}.png

• Timestamp: Current date/time in format yyyy-mm-dd-hh-mm-ss (24-hour format)
• Name: Descriptive lowercase text with hyphens
• Keep the descriptive part concise (1-5 words typically)
• Use context from user's prompt or conversation
• If unclear, use random identifier (e.g., x9k2, a7b3)

Examples:

• Prompt "A serene Japanese garden" -> 2025-12-17-14-23-05-japanese-garden.png
• Prompt "sunset over mountains" -> 2025-12-17-15-30-12-sunset-mountains.png
• Prompt "create an image of a robot" -> 2025-12-17-16-45-33-robot.png
• Unclear context -> 2025-12-17-17-12-48-x9k2.png

Image Editing

Both editing modes use the Image API (images.edit endpoint) with gpt-image-1.5 for reliable results.

Without Mask (Full Image Edit)

When the user wants to modify an existing image without specifying exact regions:

1. Use --input-image parameter with the path to the image
2. The prompt should contain editing instructions (e.g., "make the sky more dramatic", "change to cartoon style")
3. A fully transparent mask is auto-generated, allowing the model to edit the entire image

With Mask (Precise Inpainting)

When the user wants to edit specific regions:

1. Use --input-image parameter with the path to the image
2. Use --mask parameter with a PNG mask file
3. The mask should have transparent areas (alpha=0) where edits should occur
4. The prompt describes what should appear in the masked region

Common editing tasks: add/remove elements, change style, adjust colors, replace backgrounds, etc.

Prompt Handling

For generation: Pass user's image description as-is to --prompt. Only rework if clearly insufficient.

For editing: Pass editing instructions in --prompt (e.g., "add a rainbow in the sky", "make it look like a watercolor painting")

Preserve user's creative intent in both cases.

Output

• Saves PNG to current directory (or specified path if filename includes directory)
• Script outputs the full path to the generated image
• Do not read the image back - just inform the user of the saved path

Examples

Generate new image:

uv run ~/.github/skills/image-generation-gpt-image/scripts/generate_image.py --prompt "A serene Japanese garden with cherry blossoms" --filename "2025-12-17-14-23-05-japanese-garden.png" --quality high --size 1536x1024

Generate with transparent background:

uv run ~/.github/skills/image-generation-gpt-image/scripts/generate_image.py --prompt "A cute cartoon cat mascot" --filename "2025-12-17-14-25-30-cat-mascot.png" --background transparent --quality high

Edit existing image (full image):

uv run ~/.github/skills/image-generation-gpt-image/scripts/generate_image.py --prompt "make the sky more dramatic with storm clouds" --filename "2025-12-17-14-27-00-dramatic-sky.png" --input-image "original-photo.jpg"

Edit with mask (inpainting):

uv run ~/.github/skills/image-generation-gpt-image/scripts/generate_image.py --prompt "a flamingo swimming" --filename "2025-12-17-14-30-00-lounge-flamingo.png" --input-image "lounge.png" --mask "mask.png"

Generate using Azure AI Foundry (no API key needed):

uv run ~/.github/skills/image-generation-gpt-image/scripts/generate_image.py --prompt "A futuristic cityscape" --filename "2025-12-17-14-35-00-cityscape.png" --azure-endpoint "https://my-resource.openai.azure.com/" --quality high