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fc1c8ea770
The runtime media-attachment mechanism was broken for streaming channels (e.g. WebSocket): the _streamed flag caused _send_once to skip the final OutboundMessage that carried generated media, so images were never delivered. Rather than adding complex coordination between streaming and media delivery, delegate image delivery to the LLM: after generate_image returns artifact paths, the next_step prompt now instructs the LLM to call the message tool with the paths in the media parameter. This works uniformly across all channels, streaming or not. Remove generated_media from TurnContext, _assemble_outbound, and _state_save. Update prompts in identity.md, SKILL.md, message tool description, and artifacts.py to reflect the new flow.
67 lines
2.9 KiB
Markdown
67 lines
2.9 KiB
Markdown
---
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name: image-generation
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description: Generate images and iteratively edit saved image artifacts.
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---
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# Image Generation
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Use the `generate_image` tool when the user asks you to create, render, draw, design, generate, or edit an image.
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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.
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## When To Use
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- Text-to-image: call `generate_image` with a concrete `prompt`.
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- Image editing: pass the saved artifact path or user image path in `reference_images`.
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- 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".
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- Ambiguous edits: ask a short clarifying question if multiple recent images could be the target.
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- After generating images, call the `message` tool with the artifact paths in the `media` parameter to deliver them to the user.
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## Prompt Rules
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Write prompts with enough detail for image models:
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- Subject and scene.
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- Composition and camera or layout.
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- Style, mood, lighting, and color palette.
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- Text that must appear in the image, quoted exactly.
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- Constraints such as "keep the same character", "preserve the logo", or "do not change the background".
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## Artifact Rules
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The tool stores generated images as persistent artifacts under nanobot's media directory and returns structured metadata:
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- `id`: generated image id, such as `img_ab12cd34ef56`.
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- `path`: local file path for internal follow-up edits.
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- `mime`: image MIME type.
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- `prompt`, `model`, and `source_images`: provenance for follow-up edits.
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In normal user-facing replies, do not expose local filesystem paths. Keep the reply natural, for example "Done, I generated it." You may include the short image `id` when it helps the user refer to a specific image, but keep raw `path` internal unless the user explicitly asks for debug details or a local artifact reference. Never paste base64.
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For follow-up edits, pass the prior artifact `path` to `reference_images`. If the user provides a new uploaded image, use that path as the reference instead.
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Do not include internal replay markers such as `[Message Time: ...]`, `[image: /local/path]`, `generate_image(...)`, or `message(...)` in user-facing replies.
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## Examples
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Generate a new image:
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```text
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generate_image(
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prompt="A minimal app icon for nanobot: friendly robot head, rounded square, soft blue and white palette, clean vector style, no text",
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aspect_ratio="1:1",
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image_size="1K"
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)
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```
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Edit the latest generated artifact:
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```text
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generate_image(
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prompt="Use the reference image. Keep the same robot and composition, but change the palette to warm orange and add a subtle sunrise background.",
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reference_images=["/home/user/.nanobot/media/generated/2026-05-08/img_ab12cd34ef56.png"],
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aspect_ratio="1:1",
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image_size="1K"
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)
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```
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