make_image

Generate or edit images from a prompt and optional reference images.

POST /api/v1/tools/make_image/run

Generates images from a text prompt. With reference_images attached it edits/composes from them (put a product on a model, restyle a photo, keep a face consistent); without references it generates purely from text.

Routing

The default model: "auto" routes by whether references are attached:

• With reference_images → nano-banana-2 (reference-driven editing/composition).
• Without → gpt-image-2 (text-to-image).

You can pin model explicitly, with one hard rule: nano-banana-2 requires at least one reference image — it is an edit model and a ref-less request to it is rejected with a 400.

Arguments

Argument	Type	Required	Default	Description
prompt	string	yes	—	What to generate, or the edit to apply to the references.
reference_images	array of strings (URLs)	no	—	Up to 14 publicly fetchable image URLs. Attaching any requires owns_references: true.
owns_references	boolean	with refs	—	Likeness-consent attestation, identical to make_video: required true when references are attached, otherwise 400 with no debit; persisted on the run with a timestamp as an audit trail.
model	string	no	"auto"	One of auto, nano-banana-2, gpt-image-2.
aspect_ratio	string	no	"9:16"	One of 1:1, 16:9, 9:16, 4:3, 3:4, 3:2, 2:3, 21:9.
resolution	string	no	"1k"	One of 1k, 2k, 4k. Higher resolutions cost more — see pricing.
count	number	no	1	Number of images to generate, 1–4 — all are variations of the same prompt. For distinct scenes or outfits, submit one run per prompt. Cost is per image.
enhance_prompt	boolean	no	false	Rewrite a rough prompt via a prompt-writing model before generation (+3 credits); both prompts are stored and searchable. Same semantics as make_video.
influencer	string	no	—	Slug of a saved influencer. The server attaches its portrait + character sheet as references and prepends its appearance description to your prompt, keeping the same character across generations. An unknown slug → 400, no debit.

Example — text-to-image

curl -X POST https://getagenthook.com/api/v1/tools/make_image/run \
  -H "Authorization: Bearer $AGENTHOOK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Product shot of a matte-black water bottle on a concrete plinth, soft studio light, pale lime accent backdrop",
    "aspect_ratio": "1:1",
    "count": 2
  }'

Example — reference-driven edit

curl -X POST https://getagenthook.com/api/v1/tools/make_image/run \
  -H "Authorization: Bearer $AGENTHOOK_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "Put the person from image 1 in a denim jacket, golden-hour street background",
    "reference_images": ["https://example.com/my-face.jpg"],
    "owns_references": true,
    "resolution": "2k"
  }'

Response

202 with run_id and credits_charged; poll GET /api/v1/runs/{run_id}. On completed, output is an array of durable image URLs — one per count. On failed, credits are refunded instantly.