gemini-imagegen

Text-to-image generation with the Gemini API requires setting the GEMINI_API_KEY environment variable. You can then create original images from detailed prompts using the google-genai and Pillow libraries for processing.

Image editing with the Gemini API supports modifying existing images through natural language instructions. You can iteratively refine images in a multi-turn conversation, adjusting details like lighting or adding elements such as flying vehicles.

Image composition combines multiple reference images into a single output using the Gemini API. By providing several input images, the API processes and merges them according to your prompt to generate the final composite result.

Yes, AI image generation with Gemini requires the GEMINI_API_KEY environment variable. You must configure this key in your environment alongside the google-genai and Pillow dependencies to authenticate and execute API requests.

Iteratively refining AI-generated images is best done through multi-turn conversations with the Gemini API. This allows you to provide sequential natural language instructions to adjust elements like tone, lighting, and composition step by step.

Text-to-image generation with Gemini relies on the google-genai and Pillow libraries, meaning outputs are constrained by API capabilities and local image processing limits. Complex edits may require multiple conversational turns to achieve the desired result.