Image Generation

TokenLab supports text-to-image, image-to-image, and image editing through public image endpoints. Image models do not share one universal parameter set, so production clients should first choose the endpoint, then choose the model, then send only the fields supported by that model.

When To Use Each Endpoint

User workflow	Endpoint	Use when	Avoid when
Text-to-image	`POST /v1/images/generations`	The user starts from a prompt only	You need an official GPT Image edit flow
Image-to-image	`POST /v1/images/generations`	The model documents reference images through `operation: "image-to-image"` plus `image_url`, `image_urls`, or `reference_image_urls`	The model expects multipart edit input
Image edit	`POST /v1/images/edits`	You are editing an existing image with a supported edit model such as a GPT Image family model	You are using Nano Banana style image-to-image generation
Variation	`POST /v1/images/variations`	You maintain a legacy variation-compatible integration	You are building a new reference-image workflow
Status	`GET /v1/tasks/{id}`	A create response returns `task_id`, `status: "pending"`, or `poll_url`	The create response already contains final `data[]`

Always send model. Image endpoints intentionally do not rely on a historical implicit default model for production traffic.

Pick A Model

Start with model discovery, then inspect the selected model’s TokenLab model details:

curl "https://api.tokenlab.sh/v1/models?recommended_for=image" \
  -H "Authorization: Bearer sk-your-api-key"

For non-chat models, the list response may include GET /v1/models. Model detail pages may expose the fuller GET /v1/models/{model}. Use those fields to confirm:

The supported operation, such as text-to-image, image-to-image, or image-edit.
The request endpoint expected by the model.
Which shape to use for references, such as image_url, image_urls, reference_image_urls, multipart image, or JSON images[].
Whether the model accepts size, aspect_ratio, resolution, quality, background, output_format, or response_format.

Request Shape Rules

gpt-image-2 style requests use OpenAI-like size, quality, and edit fields. For generation and edits, background accepts auto or opaque; transparent is not supported. Leave optional fields out when you want the model or TokenLab to use automatic defaults.
Gemini and Nano Banana image families usually use aspect_ratio; only send resolution when the model details expose it.
Nano Banana image-to-image belongs on /v1/images/generations with operation: "image-to-image" and reference image URLs.
/v1/images/generations does not accept top-level images[] or file_id; those are edit-flow shapes.
Remote image references must be public http or https URLs. Do not send private network URLs, embedded credentials, URL fragments, or signed URLs that may expire before processing starts.

Text-To-Image Example

curl https://api.tokenlab.sh/v1/images/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-image-2",
    "prompt": "A clean product photo of a ceramic coffee cup on a walnut desk",
    "size": "1024x1024",
    "response_format": "url"
  }'

Reference-Image Example

curl https://api.tokenlab.sh/v1/images/generations \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "nano-banana",
    "operation": "image-to-image",
    "prompt": "Keep the product shape, change the background to a bright studio setup",
    "image_urls": ["https://example.com/input/product.png"],
    "aspect_ratio": "1:1"
  }'

Handling Results

Image responses can be synchronous or asynchronous:

Synchronous responses return final data[] with url or b64_json.
Async responses return id, task_id, status, and usually poll_url.
Prefer poll_url when it is present. If you need a fixed route, poll GET /v1/tasks/{id}.
Use synchronous requests when you specifically need b64_json; async image results are URL-oriented.

curl "https://api.tokenlab.sh/v1/tasks/$TASK_ID" \
  -H "Authorization: Bearer sk-your-api-key"

Persist the returned image URL, task ID, model, and your own user/job ID. Do not keep polling after a terminal status.

Production Checklist

Validate user inputs before calling TokenLab: prompt length, image count, URL reachability, and file type.
Set HTTP timeouts high enough for synchronous high-resolution requests. Use async mode where available for long work.
Store request_id, task_id, poll_url, model, endpoint, and sanitized request shape for support.
On client timeout, check whether a task was created before retrying the create request.
Reconcile cost with usage records and billing_transaction_id when present, not with provider task IDs.

Common Errors

Symptom	Likely cause	Fix
`400` with `param: "model"`	Missing explicit model	Query `/v1/models?recommended_for=image` and send `model`
Unsupported field	Field is not documented for that model	Remove the field or choose a model/endpoint that documents it
No `b64_json` on async result	Async image tasks return URL-oriented results	Use synchronous mode for base64 output
Reference image rejected	Wrong endpoint or private/expired URL	Match the model’s documented reference shape and use reachable URLs

API Reference

Topic	Reference
Create Image	Create Image
Edit Image	Edit Image
Create Image Variation	Create Image Variation
Get Image Status	Get Image Status
Get Task Status	Get Task Status

Getting Started

Core Guides

Media Guides

When To Use Each Endpoint

Pick A Model

Request Shape Rules

Text-To-Image Example

Reference-Image Example

Handling Results

Production Checklist

Common Errors

API Reference

​When To Use Each Endpoint

​Pick A Model

​Request Shape Rules

​Text-To-Image Example

​Reference-Image Example

​Handling Results

​Production Checklist

​Common Errors

​API Reference

When To Use Each Endpoint

Pick A Model

Request Shape Rules

Text-To-Image Example

Reference-Image Example

Handling Results

Production Checklist

Common Errors

API Reference