Fibo Lite · Structured Prompt
Integrate
bria/fibo-lite/generate/structured_prompt
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/bria/fibo-lite/generate/structured_prompt?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bria/fibo-lite/generate/structured_prompt?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bria/fibo-lite/generate/structured_prompt", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
# 1. Connect once (Claude Code; Cursor, VS Code, Claude Desktop: https://doitong.com/en-US/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "bria/fibo-lite/generate/structured_prompt",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Call the Fibo Lite · Structured Prompt model (bria/fibo-lite/generate/structured_prompt) through the Doitong API. Docs for agents: https://doitong.com/en-US/developers/models/bria/fibo-lite/generate/structured_prompt.md
POST https://api.doitong.com/v1/run/bria/fibo-lite/generate/structured_prompt?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
If the response status is "queued" or "running", poll GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 until it is "succeeded"; the files are in outputs[].url. POST https://api.doitong.com/v1/quote/bria/fibo-lite/generate/structured_prompt with the same body returns the exact price before the run.
This request: $0.008 8 API credits Run it on this page
Your new API key. It is shown only now and is already in the code and in the API key field below. Keep it secret: never put it in code that runs in a browser.
Your first result goes here
Build a request below and run it with your API key. Outputs are copied to our storage, kept forever or 7 days for free.
Build a request
Controls are generated from the model schema. The code and the price update as you change them.
/run/bria/fibo-lite/generate/structured_prompt?wait=20
quote → $0.008
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/bria/fibo-lite/generate/structured_prompt?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bria/fibo-lite/generate/structured_prompt?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bria/fibo-lite/generate/structured_prompt", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])
# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
{
"jsonrpc": "2.0",
"id": 1,
"method": "tools/call",
"params": {
"name": "run",
"arguments": {
"model_id": "bria/fibo-lite/generate/structured_prompt",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Run this request
Your key stays in this browser: it is sent only to the Doitong API and saved (localStorage) only if you tick Remember. Get an API key
About Fibo Lite · Structured Prompt
Returns a structured description for use with Fibo Lite instead of an image. Inputs are `prompt`, an existing `structured_prompt` or an `image_url`, plus `seed`. The JSON output covers aesthetics, artistic style, background setting, lighting, objects, photographic characteristics, subject emotions and text renders.
Parameters
Send either the canonical name or the native name, not both. Canonical names
promptoptional
structured_promptoptional
structured_prompt.short_descriptionrequired
structured_prompt.objectsrequired
structured_prompt.objects[].descriptionrequired
structured_prompt.objects[].locationrequired
structured_prompt.objects[].relationshiprequired
structured_prompt.objects[].relative_sizeoptional
structured_prompt.objects[].shape_and_coloroptional
structured_prompt.objects[].textureoptional
structured_prompt.objects[].appearance_detailsoptional
structured_prompt.objects[].number_of_objectsoptional
structured_prompt.objects[].poseoptional
structured_prompt.objects[].expressionoptional
structured_prompt.objects[].clothingoptional
structured_prompt.objects[].actionoptional
structured_prompt.objects[].genderoptional
structured_prompt.objects[].skin_tone_and_textureoptional
structured_prompt.objects[].orientationoptional
structured_prompt.background_settingrequired
structured_prompt.lightingrequired
structured_prompt.lighting.conditionsrequired
structured_prompt.lighting.directionrequired
structured_prompt.lighting.shadowsoptional
structured_prompt.aestheticsrequired
structured_prompt.aesthetics.compositionrequired
structured_prompt.aesthetics.color_schemerequired
structured_prompt.aesthetics.mood_atmosphererequired
structured_prompt.aesthetics.aesthetic_scorerequired
structured_prompt.aesthetics.preference_scorerequired
structured_prompt.photographic_characteristicsoptional
structured_prompt.photographic_characteristics.depth_of_fieldrequired
structured_prompt.photographic_characteristics.focusrequired
structured_prompt.photographic_characteristics.camera_anglerequired
structured_prompt.photographic_characteristics.lens_focal_lengthrequired
structured_prompt.style_mediumoptional
structured_prompt.text_renderoptional
structured_prompt.text_render[].textrequired
structured_prompt.text_render[].locationrequired
structured_prompt.text_render[].sizerequired
structured_prompt.text_render[].colorrequired
structured_prompt.text_render[].fontrequired
structured_prompt.text_render[].appearance_detailsoptional
structured_prompt.contextrequired
structured_prompt.artistic_stylerequired
structured_prompt.subject_emotionsoptional
image_urloptional
image
seedoptional
File parameters take a public https:// URL, a data: URI up to 10 MB, or the file_url of an upload. Files
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "bria/fibo-lite/generate/structured_prompt",
"status": "succeeded",
"created_at": "2026-10-20T12:00:00Z",
"started_at": "2026-10-20T12:00:02Z",
"completed_at": "2026-10-20T12:00:09Z",
"queue_position": null,
"cost": {
"credits": 8,
"usd": "0.008",
"charged": 8,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"short_description": "string",
"objects": [
{
"description": "string",
"location": "string",
"relationship": "string",
"relative_size": "string",
"shape_and_color": "string",
"texture": "string",
"appearance_details": "string",
"number_of_objects": 1,
"pose": "string",
"expression": "string",
"clothing": "string",
"action": "string",
"gender": "string",
"skin_tone_and_texture": "string",
"orientation": "string"
}
],
"background_setting": "string",
"lighting": {
"conditions": "string",
"direction": "string",
"shadows": "string"
},
"aesthetics": {
"composition": "string",
"color_scheme": "string",
"mood_atmosphere": "string",
"aesthetic_score": "string",
"preference_score": "string"
},
"photographic_characteristics": {
"depth_of_field": "string",
"focus": "string",
"camera_angle": "string",
"lens_focal_length": "string"
},
"style_medium": "string",
"text_render": [
{
"text": "string",
"location": "string",
"size": "string",
"color": "string",
"font": "string",
"appearance_details": "string"
}
],
"context": "string",
"artistic_style": "string",
"subject_emotions": "string"
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"stored": true
}
],
"error": null,
"metrics": {
"inference_seconds": 6.8
},
"urls": {
"self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Fields of output
- short_description
- stringBrief overview of what the image contains, limited to 200 words.
- objects
- array of object {description, location, relationship, relative_size, shape_and_color, texture, appearance_details, number_of_objects, pose, expression, clothing, action, gender, skin_tone_and_texture, orientation}List of notable objects in the foreground or midground.
- background_setting
- stringDescription of the scene as a whole: where it takes place, its surroundings or backdrop, and any background features worth noting.
- lighting
- object {conditions, direction, shadows}Information describing the lighting.
- aesthetics
- object {composition, color_scheme, mood_atmosphere, aesthetic_score, preference_score}Information describing the image's aesthetics.
- photographic_characteristics
- object {depth_of_field, focus, camera_angle, lens_focal_length} | nullInformation describing the photographic qualities.
- style_medium
- string | nullArtistic medium or style used.
- text_render
- array of object {text, location, size, color, font, appearance_details} | nullList of text elements rendered within the image.
- context
- stringAdditional context to aid interpretation of the image.
- artistic_style
- stringSpecific artistic traits, expressed in at most 3 words.
- subject_emotions
- string | nullExplicit description of the subjects' visible expressions or emotions.
Other Fibo Lite variants
More models: LLM
For AI agents: this page as Markdown is at https://doitong.com/en-US/developers/models/bria/fibo-lite/generate/structured_prompt.md. All models and guides: https://doitong.com/developers/llms.txt