gemini-imagegen

To generate images from text prompts using the Gemini API, you provide a descriptive text prompt to the Python script, which then calls the Gemini AI to transform your textual input into a visual output. You can configure the aspect ratio and image size for the generated result.

Yes, you can edit existing images and perform multi-turn refinement by providing natural language instructions alongside your reference images. The Gemini API processes these instructions to modify the visual output iteratively within your design or marketing workflow.

Multi-reference composition works by combining multiple reference images into a single new visual using the Gemini API. You provide several source images, and the Python script processes them together to create a unified composition based on your text prompt.

Yes, a valid GEMINI_API_KEY is required for authentication when running these Python scripts for AI image generation. The script enforces this API key check before communicating with the google-genai client to output text and image modalities.

You need the google-genai library and the Pillow package installed in your Python environment to run these multi-reference image editing scripts. These dependencies handle the API communication and the processing of the generated image outputs.

Text-to-image generation with the Gemini API requires Python dependencies like google-genai and Pillow, and relies on a valid GEMINI_API_KEY for authentication. Outputs are constrained by the configurable aspect ratios and image sizes supported by the API.