image-generation
FeaturedGenerate images and iteratively edit saved image artifacts.
AI & Automation 46,287 stars
8196 forks Updated today MIT
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# 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
- 5 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
Integrates with
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