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Quickstart

This walks you through the typical generation flow end-to-end: authenticate, pick a model, estimate cost, generate, and retrieve results.

Signing up and creating a token are both self-serve and free — see self-serve access if you don’t have a workspace yet.

  1. Log in to app.layer.ai
  2. Go to Settings > Personal Access Tokens
  3. Click Create Token, name it, and copy the value

Export it for the examples below:

Terminal window
export LAYER_TOKEN="your-pat-token"
export WORKSPACE_ID="your-workspace-id"

List the base models available in your workspace and choose one that fits your use case:

Terminal window
curl https://api.app.layer.ai/api/v2/workspaces/$WORKSPACE_ID/base-models \
-H "Authorization: Bearer $LAYER_TOKEN"

Note the base_model_id of the base model you want to use. See Models & capabilities for filtering options.

Check how many Creative Units the generation will consume:

Terminal window
curl -X POST https://api.app.layer.ai/api/v2/workspaces/$WORKSPACE_ID/inferences/estimate \
-H "Authorization: Bearer $LAYER_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"base_model_id": "BASE_MODEL_ID",
"prompt": "A medieval castle on a hilltop at sunset, game concept art",
"width": 1024,
"height": 1024
}'
Terminal window
curl -X POST https://api.app.layer.ai/api/v2/workspaces/$WORKSPACE_ID/inferences \
-H "Authorization: Bearer $LAYER_TOKEN" \
-H "Content-Type: application/json" \
-d '{
"base_model_id": "BASE_MODEL_ID",
"prompt": "A medieval castle on a hilltop at sunset, game concept art",
"width": 1024,
"height": 1024
}'

This returns immediately with an inference_id and status: "in_progress".

Terminal window
curl https://api.app.layer.ai/api/v2/workspaces/$WORKSPACE_ID/inferences/INFERENCE_ID \
-H "Authorization: Bearer $LAYER_TOKEN"

When status is complete, the response includes URLs to your generated assets.

  • Browse the API reference for full endpoint details and parameter documentation
  • Attach reference sets to guide generation with your own art style
  • Use workflows to run multi-step pipelines