Guide for implementing Google Gemini API image generation - create high-quality images from text prompts using gemini-2.5-flash-image model. Use when generating images, creating visual content, or implementing text-to-image features. Supports text-to-image, image editing, multi-image composition, and iterative refinement.
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Updated Jan 15, 2026, 09:07 AM
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---
name: gemini-image-gen
description: Guide for implementing Google Gemini API image generation - create high-quality images from text prompts using gemini-2.5-flash-image model. Use when generating images, creating visual content, or implementing text-to-image features. Supports text-to-image, image editing, multi-image composition, and iterative refinement.
license: MIT
version: 1.0.0
allowed-tools:
- Bash
- Read
- Write
---
# Gemini Image Generation Skill
Generate high-quality images using Google's Gemini 2.5 Flash Image model with text prompts, image editing, and multi-image composition capabilities.
## When to Use This Skill
Use this skill when you need to:
- Generate images from text descriptions
- Edit existing images by adding/removing elements or changing styles
- Combine multiple source images into new compositions
- Iteratively refine images through conversational editing
- Create visual content for documentation, design, or creative projects
## Prerequisites
### API Key Setup
The skill automatically detects your `GEMINI_API_KEY` in this order:
1. **Process environment**: `export GEMINI_API_KEY="your-key"`
2. **Skill directory**: `.claude/skills/gemini-image-gen/.env`
3. **Project directory**: `./.env` (project root)
**Get your API key**: Visit [Google AI Studio](https://aistudio.google.com/apikey)
Create `.env` file with:
```bash
GEMINI_API_KEY=your_api_key_here
```
### Python Setup
Install required package:
```bash
pip install google-genai
```
## Quick Start
### Basic Text-to-Image Generation
```python
from google import genai
from google.genai import types
import os
# API key detection handled automatically by helper script
client = genai.Client(api_key=os.getenv('GEMINI_API_KEY'))
response = client.models.generate_content(
model='gemini-2.5-flash-image',
contents='A serene mountain landscape at sunset with snow-capped peaks',
config=types.GenerateContentConfig(
response_modalities=['image'],
aspect_ratio='16:9'
)
)
# Save to ./docs/assets/
for i, part in enumerate(response.candidates[0].content.parts):
if part.inline_data:
with open(f'./docs/assets/generated-{i}.png', 'wb') as f:
f.write(part.inline_data.data)
```
### Using the Helper Script
For convenience, use the provided helper script that handles API key detection and file saving:
```bash
# Generate single image
python .claude/skills/gemini-image-gen/scripts/generate.py \
"A futuristic city with flying cars" \
--aspect-ratio 16:9 \
--output ./docs/assets/city.png
# Generate with specific modalities
python .claude/skills/gemini-image-gen/scripts/generate.py \
"Modern architecture design" \
--response-modalities image text \
--aspect-ratio 1:1
```
## Key Features
### Aspect Ratios
| Ratio | Resolution | Use Case | Token Cost |
|-------|-----------|----------|------------|
| 1:1 | 1024×1024 | Social media, avatars | 1290 |
| 16:9 | 1344×768 | Landscapes, banners | 1290 |
| 9:16 | 768×1344 | Mobile, portraits | 1290 |
| 4:3 | 1152×896 | Traditional media | 1290 |
| 3:4 | 896×1152 | Vertical posters | 1290 |
### Response Modalities
- **`['image']`**: Generate only images
- **`['text']`**: Generate only text descriptions
- **`['image', 'text']`**: Generate both images and descriptions
### Image Editing
Provide existing image + text instructions to modify:
```python
import PIL.Image
img = PIL.Image.open('original.png')
response = client.models.generate_content(
model='gemini-2.5-flash-image',
contents=[
'Add a red balloon floating in the sky',
img
]
)
```
### Multi-Image Composition
Combine up to 3 source images (recommended):
```python
img1 = PIL.Image.open('background.png')
img2 = PIL.Image.open('foreground.png')
response = client.models.generate_content(
model='gemini-2.5-flash-image',
contents=[
'Combine these images into a cohesive scene',
img1,
img2
]
)
```
## Prompt Engineering Tips
**Structure effective prompts** with three elements:
1. **Subject**: What to generate ("a robot")
2. **Context**: Environmental setting ("in a futuristic city")
3. **Style**: Artistic treatment ("cyberpunk style, neon lighting")
**Example**: "A robot in a futuristic city, cyberpunk style with neon lighting and rain-slicked streets"
**Quality modifiers**:
- Add terms like "4K", "HDR", "high-quality", "professional photography"
- Specify camera settings: "35mm lens", "shallow depth of field", "golden hour lighting"
**Text in images**:
- Limit to 25 characters maximum
- Use up to 3 distinct phrases
- Specify font styles: "bold sans-serif title" or "handwritten script"
See `references/prompting-guide.md` for comprehensive prompt engineering strategies.
## Safety Settings
The model includes adjustable safety filters. Configure per-request:
```python
config = types.GenerateContentConfig(
response_modalities=['image'],
safety_settings=[
types.SafetySetting(
category=types.HarmCategory.HARM_CATEGORY_HATE_SPEECH,
threshold=types.HarmBlockThreshold.BLOCK_MEDIUM_AND_ABOVE
)
]
)
```
See `references/safety-settings.md` for detailed configuration options.
## Output Management
All generated images should be saved to `./docs/assets/` directory:
```bash
# Create directory if needed
mkdir -p ./docs/assets
```
The helper script automatically saves to this location with timestamped filenames.
## Model Specifications
**Model**: `gemini-2.5-flash-image`
- **Input tokens**: Up to 65,536
- **Output tokens**: Up to 32,768
- **Supported inputs**: Text and images
- **Supported outputs**: Text and images
- **Knowledge cutoff**: June 2025
- **Features**: Image generation, structured outputs, batch API, caching
## Limitations
- Maximum 3 input images recommended for best results
- Text rendering works best when generated separately first
- Does not support audio/video inputs
- Regional restrictions on child image uploads (EEA, CH, UK)
- Optimal language support: English, Spanish (Mexico), Japanese, Mandarin, Hindi
## Error Handling
Common issues and solutions:
**API key not found**:
```bash
# Check environment variables
echo $GEMINI_API_KEY
# Verify .env file exists
cat .claude/skills/gemini-image-gen/.env
# or
cat .env
```
**Safety filter blocking**:
- Review `response.prompt_feedback.block_reason`
- Adjust safety settings if appropriate for your use case
- Modify prompt to avoid triggering filters
**Token limit exceeded**:
- Reduce prompt length
- Use fewer input images
- Simplify image editing instructions
## Reference Documentation
For detailed information, see:
- `references/api-reference.md` - Complete API specifications
- `references/prompting-guide.md` - Advanced prompt engineering
- `references/safety-settings.md` - Safety configuration details
- `references/code-examples.md` - Additional implementation examples
## Resources
- [Official Documentation](https://ai.google.dev/gemini-api/docs/image-generation)
- [API Reference](https://ai.google.dev/api/generate-content)
- [Get API Key](https://aistudio.google.com/apikey)
- [Google AI Studio](https://aistudio.google.com) - Interactive testing