AI image generation | Simplified Developer Docs

Generate images from a text prompt or use existing workspace assets as visual references. Model capabilities, accepted settings, and pricing vary, so discover the model before submitting a job.

1. Choose a model and capability

simplified ai-image:models
simplified ai-image:models --capability prompt
simplified ai-image:models --model-id "MODEL_ID" --capability prompt

Replace MODEL_ID with an ID from the catalog. The model detail describes its fields and any available pricing metadata. Check the supported aspect ratios and required inputs rather than assuming every model accepts the same settings.

Capability	Input
`prompt`	A text description.
`reference_image`	A prompt and a reference asset UUID.
`multiple_images`	A prompt and multiple reference asset UUIDs, on a model that supports them.

2. Generate a first image

simplified ai-image:generate \
  --model "MODEL_ID" --capability prompt \
  --prompt "Studio photograph of a ceramic mug on warm linen, soft window light, no text." \
  --aspect-ratio 1:1 --count 1 --wait

Choose values supported by the selected model. --wait keeps the command running until the job completes or the client reaches its waiting limit. A successful wait returns an array of image results containing asset identifiers and URLs. Generation can consume workspace credits; use a single image while refining a prompt.

3. Use a reference image

Upload your reference, wait until it is ready, and copy its asset UUID. Then discover a reference-capable model and submit:

simplified ai-image:models --capability reference_image
simplified ai-image:generate \
  --model "REFERENCE_MODEL_ID" --capability reference_image \
  --reference-images "ASSET_UUID" \
  --prompt "Keep the product recognizable and place it on a clean studio backdrop." \
  --count 1 --wait

Use comma-separated UUIDs for multiple_images. These inputs are asset IDs, not file paths or public image URLs.

4. Refine supported settings

The CLI exposes --negative-prompt, --seed, and comma-separated style slugs through --properties, in addition to aspect ratio and count. Their effect depends on the model. A seed can help compare variations on models that support it; it is not a guarantee of identical output across providers or model updates.

5. Track a longer job

Omit --wait when you want to submit now and check later:

simplified ai-image:generate --model "MODEL_ID" \
  --prompt "A ceramic mug on a warm neutral background." --count 1

Save the response, especially art_variation_id, then poll:

simplified ai-image:status --id "ART_VARIATION_ID"

Image generation uses job_status values such as DONE and FAILED. With --wait, the CLI polls every three seconds for up to 180 seconds. A client timeout does not prove that the remote job failed; check the existing variation before submitting another job.

6. Put the image to work

Review the result, then use its URL in a social draft or an image-editing command. Keep the asset ID when you need to retrieve a fresh URL or use the image as a later generation reference.