Stable Diffusion V3

ᠵᡠᠸᡝᠪᡠᠮᠪᡳ

ᠮᠣᡩᡝᠯ id stable-diffusion-v3-medium

# 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/stable-diffusion-v3-medium?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/stable-diffusion-v3-medium?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/stable-diffusion-v3-medium", 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/mnc/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": "stable-diffusion-v3-medium",
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }
}

Stable Diffusion V3 ᠮᠣᠳᡝᠯ (stable-diffusion-v3-medium) ᠪᡝ Doitong API ᠵᠠᠯᡳᠨᡩᡝ ᠠᠰᡠᠮᠪᡳ. ᠠᡤᡝᠨᡨᡳ ᡩᠠᡳᠯᠠᠨ: https://doitong.com/mnc/developers/models/stable-diffusion-v3-medium.md

POST https://api.doitong.ru/v1/run/stable-diffusion-v3-medium?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"
}

ᡝᡵᡝᠮᡝ ᠪᡠᠮᡝᠨᡳ ᠠᠨᠠᠮᡝ "queued" ᡳᠨᡠ "running" ᠪᡝ, GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 ᠪᡝ ᠠᠨᠠᠮᡝ "succeeded" ᠪᡝᠴᡳ ᠠᠰᡠᠮᠪᡳ; ᡶᡳᠯᡝ ᠪᡝ outputs[].url ᠪᡝᠴᡳ ᠣᠨᡩᠣᠮᡝ. POST https://api.doitong.ru/v1/quote/stable-diffusion-v3-medium ᠪᡝ ᡝᠮᡠ ᠪᡠᠶᡝᠮᡝ ᠪᡝ ᠠᠰᡠᠮᠪᡳᡩᡝ ᠵᠠᠯᡤᠠᠨ ᠪᡝ ᠶᠠᠪᡠᠮᠪᡳ ᠰᡳᠨᡳ ᠠᠮᡤᠠ ᠠᠰᡠᠮᠪᡳ ᠣᠯᡥᠣᠮᡝ.

ᡝᠨᡳ ᠵᠠᠯᡳᠨ: $0.035 35 API ᠺᠷᡝᡩᡳᠲ · ≈ ₽3.69 ᡝᡵᡝ ᠵᠠᠯᡳᠨᡩᡝ ᠠᠰᡠᠮᠪᡳ

API ᡩᠠᠮᡠᠨ ᡤᠠᠯᠠ

Stability AI ᡥᡡᠯᠠᠨ ᡩᡝ ᡤᠠᠳᠠᠨ #diffusion#style

Stable Diffusion 3 Medium ᠮᡝᠯᡝᠨ ᠣᠴᡳ ᠵᠣᠯᡤᡳᠨ ᠵᡳᠯᡤᠠᠨᡳ ᠵᠠᠰᠠᠮᠪᡳ᠂ ᠵᠠᠯᠠᠨᠠᠮᠪᡳᠨᡳ ᠮᡝᠯᡝᠨ ᠵᡠᠯᡝᡵᡳ 4 ᠵᠠᠯᠠᠨ

OpenAPI Markdown

Stability AI · ᡤᠠᠳᠠᠨ

ᡳᠨᡝ ᡝᠮᡠᠨᡳᠩᡤᡝ ᡝᡵᡝᠮᡝ ᡩᡝ

ᡝᡵᡝ ᠵᡠᠯᡝᠨ ᡩᡝ ᡤᡝᡪᡳᠯᡝᠨ ᠪᠠᠶᠠᠨᠠᠮᡝ ᠠᠮᡪᠠᠯᠠ ᡶᡳᠯᡝᠮᡝ ᠪᡝᠶᡝᠮᡝ᠃ API ᠵᡳᡵᡤᠠᡳ ᡤᠠᡳᡥᠠᡩᡝ ᡤᡝᡪᡳᠯᡝᠨ ᠵᠠᠯᠠᠨᠠᠮᡝ ᠪᡠᠶᡝᠮᡝ ᠮᡠᠰᡝᡳ ᠰᡠᠯᡠᠨᡩᡝ ᠪᠠᠶᠠᠨᠠᠮᡝ᠂ ᠝ᠮᡤᡳ ᠮᡠᠰᡝ ᠠᠶᠠᠨ 7 ᡥᠠᠨ ᠰᠠᡳᠨᠠᠮᡝ᠃

ᡤᡳᠰᡠᠨ ᠪᡠᠶᡝᠮᡝ

ᡝᠨᡝᠩᡤᡳ

ᡝᠷᡝ ᡩᠠᡳᠯᠠᠮᡝ

$0.035 / ᡤᠠᠳᠠᠨ

35 API ᠺᠷᡝᡩᡳᠲ / ᡤᠠᠳᠠᠨ · ≈ ₽3.69

ᡝᠨᡳ ᠵᠠᠯᡳᠨ: 1 ᠵᡳᠰᡠᠨ × $0.035 $0.035 35 API ᠺᠷᡝᡩᡳᠲ · ≈ ₽3.69

ᠵᠠᠯᠠᠨᠠᠮᡝ · $0.035

ᠮᠠᠩᡤᡳ ᠰᡠᠯᡠᠮᡝ ᡠᠯᠠᠮᡝ ᡝᠨᡝᠩᡤᡳ ᠠᠪᠠᠮᡝ᠈ ᡝᠷᡳᠨ ᠠᡴᡡ ᡤᡳᠰᡠᠨ ᡩᡝ ᠠᠮᡝᠪᡠᠮᡝ ᠠᡵᠠᠮᡝ

num_outputs ᠵᡠᠯᡝ 1

ᡝᠮᡠ ᠵᠠᠯᠠᠨ ᡤᠠᠯᠠᠮᡝ ᡝᠨᡝᠩᡤᡳ ᠠᠪᠠᠮᠪᡳ

ᠵᠠᠯᡤᠠᠨ ᠵᠠᠯᡳᠨ ᠳᠡ: POST /quote/{id}

ᡤᡳᠰᡠᠨ ᠪᡠᠶᡝᠮᡝ

ᠵᠠᡴᡠᠨᡳ ᠵᡠᠯᡝ ᡩᡝᡵᡤᡳ ᡩᡝᠪᡝᠰᡠᠮᡝ ᠵᡠᠯᡤᡝ ᠪᡠᠶᡝᠮᡝ᠈ ᡳᠨᡳ ᡤᡳᠰᡠᠨ ᠪᠠᡳ ᡝᠨᡝᠩᡤᡳ ᠠᠮᠪᡳ

prompt •ᡴᠠᠷᠠᡴᡡ

ᡤᠠᠳᠠᠨ ᠪᡠᠶᡝᠮᡝᠨᡳ ᡥᡡᠯᠠᠨ᠉

image_size ᠵᡠᠯᡝ square_hd

ᠪᡠᠶᡝᠮᡝ ᡤᠠᠳᠠᠨ ᡳ ᡤᡳᡵᠠᠨ.

num_outputs num_images ᠵᡠᠯᡝ 1

ᠪᡠᠶᡝᠮᡝ ᡩᡝ ᠵᡠᠴᡝᠨ ᡳ ᠵᡠᠰᡝ ᡳ ᡩᡠᠯᠠᠨ᠉

ᠵᡠᠯᡤᡝ ᠵᡝᡵᡤᡳ negative_prompt · num_inference_steps · guidance_scale · seed · prompt_expansion · enable_safety_checker

negative_prompt ᠵᡠᠯᡝ

ᡤᠠᠳᠠᠨ ᠪᡠᠶᠠᠮᡝ ᡩᡝ ᠠᡵᠠᠮᡝ ᠠᡴᡡ ᠪᡝ ᠵᠠᠯᠠᠨ ᠪᡠᠮᡝ᠉

num_inference_steps ᠵᡠᠯᡝ 28

ᠶᠠᠪᡠᠯᠠᡵᠠ ᡠᠯᡥᡳᠰᡠ ᠪᠣᡩᠣᡵᠣ ᠠᠯᡥᠠ ᡳ ᡨᠣᠨ.

guidance_scale ᠵᡠᠯᡝ 5

ᡥᡡᠯᠠᠨ ᡩᡝ ᠵᠠᡴᡠᠨ ᠵᡠᠯᡝᠮᡝ ᠤᠯᠠᡥᠠᠨ, CFG (Classifier Free Guidance) ᡩᡝ ᠵᡠᠯᡝᠮᡝ.

seed

Stable Diffusion ᡩᡝ ᡤᠠᠳᠠᠨ ᠪᡝ ᡩᠠᡥᡳᠮᡝ ᠠᡵᠠᡵᠠ ᡨᠠᡵᡳ᠈ ᠮᠣᠳᡝᠯ ᡳ ᡥᠠᠯᠠᠨ᠂ ᡥᡡᠯᠠᠨ᠂ ᡨᠠᡵᡳ ᠪᡝ ᡥᠠᠯᠠᡵᠠᡴᡡ ᠣᠪᡠᠴᡳ᠂ ᠠᠨᠠᠮᡝ ᡶᡠᠯᡠᡥᡝ ᡳᠵᡳᡧᡡᠨ ᡤᠠᠳᠠᠨ ᠪᡝ ᡩᠠᡥᡳᠮᡝ ᠠᡵᠠᠮᡝ ᠮᡠᡨᡝᠮᠪᡳ᠈

POST /run/stable-diffusion-v3-medium?wait=20 ᠵᠠᠯᡳᠨ → $0.035

# 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/stable-diffusion-v3-medium?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/stable-diffusion-v3-medium?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/stable-diffusion-v3-medium", 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": "stable-diffusion-v3-medium",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "wait_seconds": 20
    }
  }
}

ᡝᠨᡳ ᠵᠠᠯᡳᠨ ᠪᡝ ᠵᠠᠯᠠᠨᠠᠮᡝ

API ᠵᠠᠯᠠᠨ

ᡳᠨᡝ ᠵᠠᠯᠠᠨ ᡝᡵᡝ ᠪᡠᡵᡝᠪᡝᡵᡳ ᡩᡝ ᠪᡳᠮᡝ᠈ Doitong API ᡩᡝ ᠵᡝᠯᡤᡳ ᡩᠠᡵᠠᠮᡝ᠈ Remember ᠵᡠᠯᡝᠮᡝ ᡤᡳᠯᠠᠮᡝ localStorage ᡩᡝ ᠰᡠᠯᡝᠮᡝ ᠪᡳᠮᡝ ᡝᡵᡤᡝᠨ ᡩᡝ ᡳᠨᡠ ᠠᡶᡠᠯᠠᠮᠪᡳ API ᠵᠠᠯᠠᠨ ᠠᠪᠠᠮᡝ

Stable Diffusion V3 ᡠᡵᡝᠮᡝ

ᠮᡠᠰᡝᠨᡳ ᠵᠠᠰᠠᠮᠪᡳᠨᡳ ᠮᡝᠯᡝᠨ ᠪᡝᠯᡤᡝ ᠵᡠᠯᡤᡝᠯᡝᠨᡳ `prompt` ᡳ ᠠᠯᡳᠨ ᠠᠪᡠᠯᠠᠮᠪᡳ᠃ `negative_prompt`᠂ `prompt_expansion` ᠪᠠᡳ 6 ᠵᡠᠯᡤᡝᠯᡝᠨᡳ `image_size` ᠣᠴᡳ ᠰᡳᠨᡝᠮᡝ ᠪᠠᠶᠠᠨᠠᠮᠪᡳ᠂ square_hd ᠣᠴᡳ ᠵᠠᠯᠠᠨᠠᠮᠪᡳᠨᡳ ᠪᠠᠶᠠᠨᠠᠮᠪᡳ᠃ ᠠᠯᡳᠨ 1 ᠣᠴᡳ 50 ᠪᡝᠶᡝᠨᡝᠮᠪᡳ᠂ ᠵᠠᠯᠠᠨᠠᠮᠪᡳᠨᡳ 28᠂ `guidance_scale` 0 ᠣᠴᡳ 20 ᠪᡝᠶᡝᠨᡝᠮᠪᡳ᠃ `num_images` 1 ᠣᠴᡳ 4 ᠪᡝ ᠠᠪᡠᠯᠠᠮᠪᡳ᠃

ᠵᠠᡴᡠᠨ

ᠵᠠᡴᡠᠨᡳ ᡤᡳᠰᡠᠨ ᠵᡝᠯᡤᡳ ᠠᠪᠠᠮᠪᡳ᠈ ᠨᡝᠮᡝ ᠮᡠᠰᡝ ᡠᠯᠠᠮᠪᡳ ᠵᠠᡴᡠᠨᡳ ᡤᡳᠰᡠᠨ

ᠵᡝᡵᡤᡳᡠᠯᠠᠮᡝ ᠵᠠᠯᠠᠨᡳ ᠵᡠᠯᡝᠠᠪᠠᠮᡝ ᠵᠠᠪᡠᠨ ᠵᠠᠯᠠᠨᡳ ᡤᡳᠰᡠᠨ

promptᡴᠠᠷᠠᡴᡡ

ᡠᠯᠠᠮᡝstring

ᡤᠠᠳᠠᠨ ᠪᡠᠶᡝᠮᡝᠨᡳ ᡥᡡᠯᠠᠨ᠉

negative_promptᠵᡠᠯᡝ

ᡠᠯᠠᠮᡝstring

ᠵᠠᠯᠠᠨᡳ ᠵᡠᠯᡝ

ᡤᠠᠳᠠᠨ ᠪᡠᠶᠠᠮᡝ ᡩᡝ ᠠᡵᠠᠮᡝ ᠠᡴᡡ ᠪᡝ ᠵᠠᠯᠠᠨ ᠪᡠᠮᡝ᠉

prompt_expansionᠵᡠᠯᡝ

ᡠᠯᠠᠮᡝboolean

ᠵᠠᠯᠠᠨᡳ ᠵᡠᠯᡝfalse

ᡥᡡᠯᠠᠨ ᠵᠠᠯᠠᠨ ᠪᡝ ᡝᠮᡤᡳᠯᡝᠨ ᡩᠠᠯᠠᠨ ᡤᠠᠯᠠᠨ ᠪᠠᡳᡵᠠᠨᠠ.

image_sizeᠵᡠᠯᡝ

ᡠᠯᠠᠮᡝobject

ᠵᠠᠯᠠᠨᡳ ᠵᡠᠯᡝsquare_hd

square_hdsquareportrait_4_3portrait_16_9landscape_4_3landscape_16_9

ᠪᡠᠶᡝᠮᡝ ᡤᠠᠳᠠᠨ ᡳ ᡤᡳᡵᠠᠨ.

num_inference_stepsᠵᡠᠯᡝ

ᡠᠯᠠᠮᡝinteger

ᠵᠠᠯᠠᠨᡳ ᠵᡠᠯᡝ28

1 – 50

ᠶᠠᠪᡠᠯᠠᡵᠠ ᡠᠯᡥᡳᠰᡠ ᠪᠣᡩᠣᡵᠣ ᠠᠯᡥᠠ ᡳ ᡨᠣᠨ.

seedᠵᡠᠯᡝ

ᡠᠯᠠᠮᡝinteger | null

guidance_scaleᠵᡠᠯᡝ

ᡠᠯᠠᠮᡝnumber

ᠵᠠᠯᠠᠨᡳ ᠵᡠᠯᡝ5

0 – 20

ᡥᡡᠯᠠᠨ ᡩᡝ ᠵᠠᡴᡠᠨ ᠵᡠᠯᡝᠮᡝ ᠤᠯᠠᡥᠠᠨ, CFG (Classifier Free Guidance) ᡩᡝ ᠵᡠᠯᡝᠮᡝ.

num_imagesᠵᡠᠯᡝ num_outputs

ᡠᠯᠠᠮᡝinteger

ᠵᠠᠯᠠᠨᡳ ᠵᡠᠯᡝ1

1 – 4

ᠪᡠᠶᡝᠮᡝ ᡩᡝ ᠵᡠᠴᡝᠨ ᡳ ᠵᡠᠰᡝ ᡳ ᡩᡠᠯᠠᠨ᠉

enable_safety_checkerᠵᡠᠯᡝ

ᡠᠯᠠᠮᡝboolean

ᠵᠠᠯᠠᠨᡳ ᠵᡠᠯᡝtrue

ᠠᠮᡤᠠᠨᡳ ᠵᠠᠯᡳᠨᠠᠮᠪᡳ; ᠠᠮᡤᠠᠨ ᠪᡝ ᡠᠵᡠᠯᠠᠮᡝ ᡤᠠᠳᠠᠨ ᠪᡝ ᡴᠠᡵᠠ ᠪᡠᠶᡝᠮᡝᠮᠪᡳ᠉ true ᠪᡝ ᡠᠵᡠᠯᠠᠮᡝᠨᡳ ᡩᠠᠯᡳᠨ; false ᠪᡝ ᡩᠠᠯᡳᠨ ᠠᡴᡠᠯᠠᠮᠪᡳ᠂ ᠵᡠᠯᡝ ᠵᡠᠯᡝᠨᡳ ᠪᡝ ᠠᡴᡠᠯᠠᠮᠪᡳ᠉

ᡴᠠᠷᠠᡴᡡ ᠵᠠᡴᡠᠨᡳ ᡤᡳᠰᡠᠨ᠈ ᠮᡠᠰᡝ ᡝᠮᡠ ᠠᠪᠠᠮᠪᡳ

ᠪᡠᠶᡝᠮᡝ

GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t

{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "stable-diffusion-v3-medium",
  "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": 35,
    "usd": "0.035",
    "charged": 35,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "width": 1024,
        "height": 768,
        "content_type": "image/jpeg"
      }
    ],
    "timings": {},
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ],
    "prompt": "string",
    "num_images": 1
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "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"
  }
}

ᡤᡝᠯᡝᠮᡝ ᡥᡡᠯᡤᡠᠨᡳ ᡳᠨᡠᡝᠯᡝᡥᡝ outputs[].url ᠰᡠᠯᡠᠨ ᡩᡝ ᠰᡳᡵᡝ ᡶᡳᠯᡝ᠈ ᠝ᠮᡤᡳ ᠮᡠᠰᡝ ᠠᠪᠠᠯᡳ ᠵᡝᠮᡤᡳᠨ GB-ᠪᡳᠶᠠ ᠵᡝᠮᡤᡳᠨ ᠪᡝ ᡝᠮᡠᠯᡝᠮᡝ ᠠᠪᠠᠯᡳ 7 ᡥᠠᠨ ᠰᡳᠯᡤᠠᠨ ᡩᡝ᠈ ᠰᡳᠨᡳ ᠪᠠᠯᠠᠨᠰᡳ ᠵᡠᠶᡝᡵᡝᠨ ᠠᠪᠠᠯᡳ ?storage= ᡩᡝ ᡝᠵᡝᠨ ᡥᠠᠯᠠᠮᡝ᠉

ᡝᠮᡠ ᡤᡳᠰᡠᠨ ᡝᠮᡠ ᠮᠣᡩᡝᠯ ᡩᡝtype, url, content_type, width, height ᠮᠠᠩᡤᡳ duration᠈ ᠵᠠᠯᠠᠨ᠈ ᠪᡠᠵᡠᠮᠪᡳ ᠮᠠᠩᡤᡳ ᠵᡝᡵᡤᡳ ᡩᡝᠨᡳ᠈ output ᠮᠣᡩᡝᠯᡳᠨᡳ ᡝᠮᡠ ᠵᠠᠯᠠᠨ

ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᡳᠰᡠᠨ

images: array of object {url, width, height, content_type}ᠪᡠᠶᡝᠮᡝ ᡤᠠᠳᠠᠨᡳ ᡶᡳᠯᡝ ᡩᠠᠮᡠ.
timings: object
seed: integerᠪᡠᠶᡝᠮᡝᠨᡳ ᠰᡝᠨᡩᡝᠨᡳ ᠵᠠᠯᡳᠨ; ᡳᠨᡠ ᠪᡳᠰᡳᡵᡝᠨ ᠪᡝ ᠵᠠᠯᡳᠨᠠᠮᠪᡳ᠉
has_nsfw_concepts: array of booleanᠪᡠᠶᡝᠮᡝᠨᡳ ᠤᠯᡥᠠᠨ ᠤᠨᠠᠰᡳᠨ ᠩᡝᠮᡝ ᠪᡳ ᠰᡝᠮᡝ ᠵᠠᠯᡳᠨᠠᠮᠪᡳ᠉
prompt: stringᠪᡠᠶᡝᠮᡝᠨᡳ ᡥᡡᠯᠠᠨ᠉
num_images: integerᠪᡠᠶᡝᠮᡝ ᡤᠠᠳᠠᠨ ᡳ ᠵᠠᠯᠠᠨ.