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Use assets when a product, person, or scene needs to appear in more than one request. An asset record holds metadata; its linked source images provide the visual references.

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Find a library avatar and preset

Set include_public=true to include shared library assets. Set paginated=true for an object response with pagination:
Repeat with type=preset for scenes. Choose an asset by its alias and preview, then keep its id. When page_info.has_next_page is true, send page_info.next_cursor as the next cursor, keeping the same filters.
Without paginated=true, GET /assets returns a bare array. It also defaults to type=model when you omit the type. Do not parse both modes as the same response shape.

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Save a product

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Create the asset record

Keep the returned id as OUTFIT_ASSET_ID.

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Upload the references to that asset

Repeat with the back and useful detail photos of the same product and colorway. Alternatively, link an already-uploaded image with POST /images/{id}/asset and {"asset_id":"OUTFIT_ASSET_ID"}. Read back your references with GET /assets/{id}/images?for_training=true. Omit the for_training filter to read the asset’s wider image collection. Public preset source photos may not be accessible even when you can use the preset for generation.

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Use the saved references

Substitute the IDs returned by your own requests:
Send this body to POST /images/generate. It returns an array of jobs. Change the outfit asset for another product while keeping the same avatar, preset, and settings for a consistent series.

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Create your own avatar or preset

Create an asset with type=model for an avatar or type=preset for a visual setup. Give it a useful alias and characteristics. Upload its reference photos to /assets/{id}/images with type=training. For a preset, use a class such as human_studio, human_location, ghost_mannequin, flat_lay, or product_packshot. You can analyze one to three uploaded images to obtain a suggested name, class, and prompt before saving the asset. A display_image URL is only a thumbnail. You must also upload or link source images for the asset to act as a visual reference. Reference-based image models such as Nano Banana 2 can use these saved references without a separate model-training request.