image-generation

Solid

Generate images and iteratively edit saved image artifacts.

AI & Automation 44,101 stars 7803 forks Updated today MIT

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Skill Content

# Image Generation Use the `generate_image` tool when the user asks you to create, render, draw, design, generate, or edit an image. If the `generate_image` tool is not available in the current tool list, tell the user that image generation is not enabled for this nanobot instance. ## When To Use - Text-to-image: call `generate_image` with a concrete `prompt`. - Image editing: pass the saved artifact path or user image path in `reference_images`. - Iterative edits in the same conversation: prefer the most recent generated image artifact if the user says things like "make it brighter", "change the background", or "try another version". - Ambiguous edits: ask a short clarifying question if multiple recent images could be the target. - After generating images, call the `message` tool with the artifact paths in the `media` parameter to deliver them to the user. ## Prompt Rules Write prompts with enough detail for image models: - Subject and scene. - Composition and camera or layout. - Style, mood, lighting, and color palette. - Text that must appear in the image, quoted exactly. - Constraints such as "keep the same character", "preserve the logo", or "do not change the background". ## Artifact Rules The tool stores generated images as persistent artifacts under nanobot's media directory and returns structured metadata: - `id`: generated image id, such as `img_ab12cd34ef56`. - `path`: local file path for internal follow-up edits. - `mime`: image MIME type. - `prompt`, `m...

Details

Author
HKUDS
Repository
HKUDS/nanobot
Created
4 months ago
Last Updated
today
Language
Python
License
MIT

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