Image Generation
Generate images using generate_media with mode="image". The system auto-selects the best backend based on available API keys.
Quick Start
# Simple text-to-image (auto-selects backend)
generate_media(prompt="A cat in space", mode="image")
# Specify backend and quality
generate_media(prompt="A logo for a coffee shop", mode="image",
backend_type="openai", quality="high")
# Batch generation (parallel)
generate_media(prompts=["sunset over ocean", "mountain landscape", "city at night"],
mode="image", max_concurrent=3)Backend Comparison
| Backend | Default Model | Strengths | API Key |
|---|---|---|---|
| Google (priority 1) | gemini-3.1-flash-image-preview (Nano Banana 2) | Fast, flexible sizes, image editing, multi-turn | GOOGLE_API_KEY or GEMINI_API_KEY |
| OpenAI (priority 2) | gpt-5.4 | High quality, transparent backgrounds, continuation via response ID | OPENAI_API_KEY |
| Grok (priority 3) | grok-imagine-image | 1k resolution, continuation via stored data URI | XAI_API_KEY |
| OpenRouter (priority 4) | google/gemini-3.1-flash-image-preview | Access to multiple models via single API | OPENROUTER_API_KEY |
Key Parameters
| Parameter | Description | Example |
|---|---|---|
prompt | Text description of the image | "A watercolor painting of mountains" |
backend_type | Force a specific backend | "google", "openai", "grok", "openrouter" |
model | Override default model | "gemini-3-pro-image-preview" for studio quality |
quality | Image quality (OpenAI) | "low", "medium", "high", "auto" |
size | Image dimensions | See backends reference |
aspect_ratio | Aspect ratio | "16:9", "1:1", "4:5" |
input_images | Source images for image-to-image editing | ["photo.jpg"] |
continue_from | Continuation ID for multi-turn editing | result["continuation_id"] |
Image-to-Image Editing
Transform existing images by providing input_images:
generate_media(
prompt="Make it look like a watercolor painting",
mode="image",
input_images=["photo.jpg"]
)Supported backends for image-to-image: Google (Gemini), OpenAI, Grok. The system auto-selects if your current backend doesn't support it.
Multi-Turn Editing (Continuation)
Iteratively refine images using continue_from:
# First generation
result = generate_media(prompt="A logo for a coffee shop", mode="image")
# Refine using the continuation ID
result2 = generate_media(
prompt="Make the text larger and add a cup icon",
mode="image",
continue_from=result["continuation_id"]
)Each backend uses a different continuation mechanism:
- OpenAI: Passes
previous_response_id(stateless) - Google Gemini: In-memory chat store (LRU, 50 items)
- Grok: In-memory data URI store (LRU, 50 items)
Continuation only works for single image generation (not batch).
Google: Gemini vs Imagen
Google supports two API paths. Gemini (Nano Banana 2) is the default and recommended for most use cases. Imagen is only needed for advanced reference-image editing features.
- Gemini models (
gemini-*):generate_content()— text-to-image, image editing viainput_images, multi-turn continuation - Imagen models (
imagen-*):generate_images()/edit_image()— text-to-image withnegative_prompt/seed/guidance_scale, plus style transfer, control editing, and subject consistency via reference images
For studio-quality precision and text rendering, use: model="gemini-3-pro-image-preview" (Pro-tier).
Need More Control?
- Per-backend sizes, quality options, and quirks: See references/backends.md
- Complete
extra_paramsreference: See references/extra_params.md - Advanced editing (inpainting, style transfer, control, subject): See references/editing.md