Fibo Edit [Structured Instruction]
Integrate
bria/fibo-edit/edit/structured_instruction
# 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-edit/edit/structured_instruction?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bria/fibo-edit/edit/structured_instruction?wait=20", {
method: "POST",
headers,
body: JSON.stringify({}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bria/fibo-edit/edit/structured_instruction", 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/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-edit/edit/structured_instruction",
"input": {}
}
Call the Fibo Edit [Structured Instruction] model (bria/fibo-edit/edit/structured_instruction) through the Doitong API. Docs for agents: https://doitong.com/developers/models/bria/fibo-edit/edit/structured_instruction.md
POST https://api.doitong.com/v1/run/bria/fibo-edit/edit/structured_instruction?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{}
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-edit/edit/structured_instruction with the same body returns the exact price before the run.
This request: $0.01 10 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-edit/edit/structured_instruction?wait=20
quote → $0.01
# 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-edit/edit/structured_instruction?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bria/fibo-edit/edit/structured_instruction?wait=20", {
method: "POST",
headers,
body: JSON.stringify({}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/bria/fibo-edit/edit/structured_instruction", 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-edit/edit/structured_instruction",
"input": {},
"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 Edit [Structured Instruction]
Generates only the structured instruction for an edit, not a picture. Inputs are an optional `image_url`, `mask_url`, `instruction` and `seed`. The JSON output covers fields such as objects, lighting, aesthetics, background setting, photographic characteristics and text to render.
Parameters
Send either the canonical name or the native name, not both. Canonical names
image_urloptional
image
mask_urloptional
mask
instructionoptional
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-edit/edit/structured_instruction",
"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": 10,
"usd": "0.01",
"charged": 10,
"refunded": 0
},
"input": {},
"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",
"preference_score": "string",
"aesthetic_score": "string"
},
"photographic_characteristics": {
"depth_of_field": "string",
"focus": "string",
"camera_angle": "string",
"lens_focal_length": "string"
},
"style_medium": "string",
"text_render": [],
"context": "string",
"artistic_style": "string",
"edit_instruction": "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
- string | nullBrief description of the intended output image.
- 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} | nullSpecify the generated image's contents as a list, recording each object's attributes and its relationships with the other depicted objects.
- background_setting
- string | nullBackground setting for the generated image.
- lighting
- object {conditions, direction, shadows} | nullLighting for the generated image.
- aesthetics
- object {composition, color_scheme, mood_atmosphere, preference_score, aesthetic_score} | nullAesthetic qualities for the generated image.
- photographic_characteristics
- object {depth_of_field, focus, camera_angle, lens_focal_length} | nullPhotographic properties for the generated image.
- style_medium
- string | nullStylistic medium for the generated image.
- text_render
- array of any | nullList of text entries to include in the image.
- context
- string | nullContext for the generated image.
- artistic_style
- string | nullArtistic style for the generated image.
- edit_instruction
- string | nullInstruction describing how to edit the image.
Other Fibo Edit variants
More models: LLM
For AI agents: this page as Markdown is at https://doitong.com/developers/models/bria/fibo-edit/edit/structured_instruction.md. All models and guides: https://doitong.com/developers/llms.txt