— name: gemini-imagegen description: This skill should be used when generating and editing images using the Gemini API (Nano Banana Pro). It applies when creating images from text prompts, editing existing images, applying style transfers, generating logos with text, creating stickers, product mockups, or any image generation/manipulation task. Supports text-to-image, image editing, multi-turn refinement, and composition from multiple reference images. — # Gemini Image Generation (Nano Banana Pro) Generate and edit images using Google's Gemini API. The environment variable `GEMINI_API_KEY` must be set. ## Default Model | Model | Resolution | Best For | |——-|————|———-| | `gemini-3-pro-image-preview` | 1K-4K | All image generation (default) | **Note:** Always use this Pro model. Only use a different model if explicitly requested. ## Quick Reference ### Default Settings – **Model:** `gemini-3-pro-image-preview` – **Resolution:** 1K (default, options: 1K, 2K, 4K) – **Aspect Ratio:** 1:1 (default) ### Available Aspect Ratios `1:1`, `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9`, `21:9` ### Available Resolutions `1K` (default), `2K`, `4K` ## Core API Pattern “`python import os from google import genai from google.genai import types client = genai.Client(api_key=os.environ["GEMINI_API_KEY
d:T1273,#!/usr/bin/env python3 """ Compose multiple images into a new image using Gemini API. Usage: python compose_images.py "instruction" output.png image1.png [image2.png …] Examples: python compose_images.py "Create a group photo of these people" group.png person1.png person2.png python compose_images.py "Put the cat from the first image on the couch from the second" result.png cat.png couch.png python compose_images.py "Apply the art style from the first image to the scene in the second" styled.png style.png photo.png Note: Supports up to 14 reference images (Gemini 3 Pro only). Environment: GEMINI_API_KEY – Required API key """ import argparse import os import sys from PIL import Image from google import genai from google.genai import types def compose_images( instruction: str, output_path: str, image_paths: list[str], model: str = "gemini-3-pro-image-preview", aspect_ratio: str | None = None, image_size: str | None = None, ) -> str | None: """Compose multiple images based on instructions. Args: instruction: Text description of how to combine images output_path: Path to save the result image_paths: List of input image paths (up to 14) model: Gemini model to use (pro recommended) aspect_ratio: Output aspect ratio image_size: Output resolution Returns: Any text response from the model, or None """ api_key = os.environ.get("GEMINI_API_KEY") if not api_key: raise EnvironmentError("GEMINI_API_KEY environment variable not set") if len(image_paths) > 14: raise ValueError("Maximum 14 reference images supported") if len(image_paths) < 1: raise ValueError("At least one image is required") # Verify all images exist for path in image_paths: if not os.path.exists(path): raise FileNotFoundError(f"Image not found: {path}") client = genai.Client(api_key=api_key) # Load images images = [Image.open(path) for path in image_paths] # Build contents: instruction first, then images contents = [instruction] + images # Build config config_kwargs = {"response_modalities": ["TEXT", "IMAGE"]} image_config_kwargs = {} if aspect_ratio: image_config_kwargs["aspect_ratio"] = aspect_ratio if image_size: image_config_kwargs["image_size"] = image_size if image_config_kwargs: config_kwargs["image_config"] = types.ImageConfig(**image_config_kwargs) config = types.GenerateContentConfig(**config_kwargs) response = client.models.generate_content( model=model, contents=contents, config=config, ) text_response = None image_saved = False for part in response.parts: if part.text is not None: text_response = part.text elif part.inline_data is not None: image = part.as_image() image.save(output_path) image_saved = True if not image_saved: raise RuntimeError("No image was generated.") return text_response def main(): parser = argparse.ArgumentParser( description="Compose multiple images using Gemini API", formatter_class=argparse.RawDescriptionHelpFormatter, epilog=__doc__ ) parser.add_argument("instruction", help="Composition instruction") parser.add_argument("output", help="Output file path") parser.add_argument("images", nargs="+", help="Input images (up to 14)") parser.add_argument( "–model", "-m", default="gemini-3-pro-image-preview", choices=["gemini-2.5-flash-image", "gemini-3-pro-image-preview"], help="Model to use (pro recommended for composition)" ) parser.add_argument( "–aspect", "-a", choices=["1:1", "2:3", "3:2", "3:4", "4:3", "4:5", "5:4", "9:16", "16:9", "21:9"], help="Output aspect ratio" ) parser.add_argument( "–size", "-s", choices=["1K", "2K", "4K"], help="Output resolution" ) args = parser.parse_args() try: text = compose_images( instruction=args.instruction, output_path=args.output, image_paths=args.images, model=args.model, aspect_ratio=args.aspect, image_size=args.size, ) print(f"Composed image saved to: {args.output}") if text: print(f"Model response: {text}") except Exception as e: print(f"Error: {e}", file=sys.stderr) sys.exit(1) if __name__ == "__main__": main() 1e:T104d,#!/usr/bin/env python3 """ Edit existing images using Gemini API. Usage: python edit_image.py input.png "edit instruction" output.png [options] Examples: python edit_image.py photo.png "Add a rainbow in the sky" edited.png python edit_image.py room.jpg "Change the sofa to red leather" room_edited.jpg python edit_image.py portrait.png "Make it look like a Van Gogh painting" artistic