Fibo · Structured Prompt
整合
模型 id
bria/fibo/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.ru/v1/run/bria/fibo/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.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bria/fibo/generate/structured_prompt?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/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/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/zh-TW/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "bria/fibo/generate/structured_prompt",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
透過 Doitong API 呼叫 Fibo · Structured Prompt 模型(bria/fibo/generate/structured_prompt)。代理程式文件:https://doitong.com/zh-TW/developers/models/bria/fibo/generate/structured_prompt.md
POST https://api.doitong.ru/v1/run/bria/fibo/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"
}
如果回應狀態為 "queued" 或 "running",請輪詢 GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20,直到狀態變為 "succeeded";檔案位於 outputs[].url。使用相同主體傳送 POST https://api.doitong.ru/v1/quote/bria/fibo/generate/structured_prompt,可在執行前取得確切價格。
此請求: $0.01 10 API 點數 · ≈ ₽1.08 在此頁面執行
您的新 API 金鑰。 僅會在此時顯示,且已填入下方的程式碼與 API 金鑰欄位。請妥善保密:切勿將其放入在瀏覽器中執行的程式碼。
建立請求
控制項是根據模型結構描述生成的。變更設定時,程式碼和價格會同步更新。
POST
/run/bria/fibo/generate/structured_prompt?wait=20
報價 → $0.01
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.ru/v1/run/bria/fibo/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.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/bria/fibo/generate/structured_prompt?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/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/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/generate/structured_prompt",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
關於 Fibo · Structured Prompt
類語言模型的端點,回傳影像的結構化提示,而非影像本身。輸入為 `prompt`、現有的 `structured_prompt` 或參考 `image_url`,以及 `seed`。JSON 輸出包含美學、光線、物件、攝影特徵、簡短描述、風格媒材及要渲染的文字等欄位。
參數
請傳送標準名稱或原生名稱其中之一,不要同時傳送兩者。 標準名稱
名稱類型
預設值允許值
說明
prompt選填
類型string | null
用於生成圖像的提示詞。
structured_prompt選填
類型object
用於圖像生成的結構化提示詞。
structured_prompt.short_description選填
類型string | null
預期輸出圖像的簡短描述。
structured_prompt.objects選填
類型object[]
預設值[]
以清單指定生成圖像的內容,記錄每個物件的屬性及其與其他圖示物件的關係。
structured_prompt.objects[].description選填
類型string | null
預期輸出物件的描述。
structured_prompt.objects[].location選填
類型string | null
物件在圖像中的位置。
structured_prompt.objects[].relationship必填
類型string
物件與圖像中其他物件的關係。
structured_prompt.objects[].relative_size選填
類型string | null
物件相對於圖像的大小。
structured_prompt.objects[].shape_and_color選填
類型string | null
物件的形狀與色彩。
structured_prompt.objects[].texture選填
類型string | null
物件的材質。
structured_prompt.objects[].appearance_details選填
類型string | null
描述物件外觀的詳細資訊。
structured_prompt.objects[].number_of_objects選填
類型integer | null
圖像中的物件數量。
structured_prompt.objects[].pose選填
類型string | null
圖示物件的姿勢。
structured_prompt.objects[].expression選填
類型string | null
圖示物件呈現的表情。
structured_prompt.objects[].clothing選填
類型string | null
圖示物件穿著的服裝。
structured_prompt.objects[].action選填
類型string | null
圖示物件執行的動作。
structured_prompt.objects[].gender選填
類型string | null
圖示物件的性別。
structured_prompt.objects[].skin_tone_and_texture選填
類型string | null
圖示物件的皮膚質感與色調。
structured_prompt.objects[].orientation選填
類型string | null
圖示物件的方向。
structured_prompt.background_setting選填
類型string | null
生成圖像的背景設定。
structured_prompt.lighting選填
類型object
生成圖像的光線。
structured_prompt.lighting.conditions選填
類型string | null
生成圖像的光線條件。
structured_prompt.lighting.direction選填
類型string | null
生成圖像的光線方向。
structured_prompt.lighting.shadows選填
類型string | null
生成圖像中要呈現的陰影。
structured_prompt.aesthetics選填
類型object
生成圖像的美學特質。
structured_prompt.aesthetics.composition選填
類型string | null
生成圖像的構圖。
structured_prompt.aesthetics.color_scheme選填
類型string | null
生成圖像的色彩配置。
structured_prompt.aesthetics.mood_atmosphere選填
類型string | null
生成圖像的情緒與氛圍。
structured_prompt.aesthetics.aesthetic_score選填
類型string | null
正在生成之圖像的美學評分。
structured_prompt.aesthetics.preference_score選填
類型string | null
正在生成之圖像的偏好評分。
structured_prompt.photographic_characteristics選填
類型object
生成圖像的攝影特性。
structured_prompt.photographic_characteristics.depth_of_field選填
類型string | null
生成圖像的景深。
structured_prompt.photographic_characteristics.focus選填
類型string | null
生成圖像的焦點。
structured_prompt.photographic_characteristics.camera_angle選填
類型string | null
生成圖像的相機角度。
structured_prompt.photographic_characteristics.lens_focal_length選填
類型string | null
生成圖像的鏡頭設定,以焦距表示。
structured_prompt.style_medium選填
類型string | null
生成圖像的藝術媒材。
structured_prompt.text_render選填
類型any[]
預設值[]
要包含在圖像中的文字項目清單。
structured_prompt.context選填
類型string | null
生成圖像的情境。
structured_prompt.artistic_style選填
類型string | null
生成圖像的藝術風格。
structured_prompt.trigger_word選填
類型string | null
structured_prompt.sub_trigger_word選填
類型string | null
structured_prompt.art_direction選填
類型string | null
structured_prompt.action_description選填
類型string | null
structured_prompt.actor_prefix選填
類型string | null
image_url選填
image
類型url · image
以檔案或 URL 提供的參考圖像。
seed選填
類型integer
預設值5555
控制隨機性以產生可重現結果的種子。
必填
標準名稱,也可使用
檔案參數接受公開的 https:// URL、最大 10 MB 的 data: URI,或上傳檔案的 file_url。 檔案
輸出
GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "bria/fibo/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": 10,
"usd": "0.01",
"charged": 10,
"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": [],
"context": "string",
"artistic_style": "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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
您的檔案,由您選擇每個 outputs[].url 都是儲存空間中的副本:可永久保留(按 GB-月計費),或免費保留 7 天;可透過帳戶設定或 ?storage= 設定。
所有模型使用相同結構圖片、影片和音訊皆包含 type、url、content_type、width、height 和 duration。output 是模型自己的結果物件。
輸出欄位
- short_description
- string | null預期輸出圖像的簡短描述。
- 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} | null以清單指定生成圖像的內容,記錄每個物件的屬性及其與其他圖示物件的關係。
- background_setting
- string | null生成圖像的背景設定。
- lighting
- object {conditions, direction, shadows} | null生成圖像的光線。
- aesthetics
- object {composition, color_scheme, mood_atmosphere, aesthetic_score, preference_score} | null生成圖像的美學特質。
- photographic_characteristics
- object {depth_of_field, focus, camera_angle, lens_focal_length} | null生成圖像的攝影特性。
- style_medium
- string | null生成圖像的藝術媒材。
- text_render
- array of any | null要包含在圖像中的文字項目清單。
- context
- string | null生成圖像的情境。
- artistic_style
- string | null生成圖像的藝術風格。
其他 Bria Fibo 變體
更多模型:LLM
給 AI 代理程式:此頁面的 Markdown 位於 https://doitong.com/zh-TW/developers/models/bria/fibo/generate/structured_prompt.md. 所有模型與指南: https://doitong.com/developers/llms.txt