Kling 4.0 Reference to Video
ᠵᡠᠸᡝᠪᡠᠮᠪᡳ
kling/v4/reference-to-video
# 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/kling/v4/reference-to-video?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling/v4/reference-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/kling/v4/reference-to-video", 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": "kling/v4/reference-to-video",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Kling 4.0 Reference to Video ᠮᠣᠳᡝᠯ (kling/v4/reference-to-video) ᠪᡝ Doitong API ᠵᠠᠯᡳᠨᡩᡝ ᠠᠰᡠᠮᠪᡳ. ᠠᡤᡝᠨᡨᡳ ᡩᠠᡳᠯᠠᠨ: https://doitong.com/mnc/developers/models/kling/v4/reference-to-video.md
POST https://api.doitong.ru/v1/run/kling/v4/reference-to-video?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/kling/v4/reference-to-video ᠪᡝ ᡝᠮᡠ ᠪᡠᠶᡝᠮᡝ ᠪᡝ ᠠᠰᡠᠮᠪᡳᡩᡝ ᠵᠠᠯᡤᠠᠨ ᠪᡝ ᠶᠠᠪᡠᠮᠪᡳ ᠰᡳᠨᡳ ᠠᠮᡤᠠ ᠠᠰᡠᠮᠪᡳ ᠣᠯᡥᠣᠮᡝ.
ᠵᠠᠨᡳ ᡥᠠᠯᠠᠮᠠ ᡥᡡᠯᠠᠨᡳ ᡶᡳᠯᡝ: $1.175 1,175 API ᠺᠷᡝᡩᡳᠲ · ≈ ₽122.95 ᠰᡳᠨᡳ ᡶᡳᠯᡝ ᠵᠠᠯᡤᠠᠨ ᠠᠰᡠᠮᠪᡳᠨᡳ ᠠᠯᡳᠮᠪᡳ ᡝᡵᡝ ᠵᠠᠯᡳᠨᡩᡝ ᠠᠰᡠᠮᠪᡳ
ᠰᡳᠨᡳ ᠵᠠᠮᡠᠰᡳᠨ API ᠵᡳᡵᡤᠠ. ᡝᠯᡝ ᡝᠨᡩᡝ ᡳᠯᡤᠠᠮᠪᡳ ᡝᡵᡝ ᠮᡠᠨᡩᡝ ᡴᠣᡩᡝ ᡩᠠᠮᡠ ᠮᡝᠨᡩᡝᡵᡝ ᠪᠠᡩᡝᠯᡝᠨ ᠠᠮᡪᡳ ᡳᠨᡠ API ᠵᡳᡵᡤᠠ ᡩᡝᠪᡨᡝᡵᡝ ᡩᡝ ᠠᡴᡠ᠉ ᡳᠨᡠ ᡝᡵᡝᠩᡤᡝ ᠠᠮᠪᠠᠨ ᠮᡠᠨᡩᡝ ᠪᡝ ᠠᠰᡠᡵᠠᠮᠪᡳ: ᠮᡠᡵᡝ ᡩᠠᠮᡠ ᠪᡠᠶᡝᡵᡝ ᠪᠠᡩᡝᠯᡝᠨ ᡩᡝ ᠰᡳᠨᡩᡝᠮᡝ ᠠᠪᡠᠮᡝ ᠰᠠᠮᡪᡳ᠉
Doitong ᡩᡝ ᠪᡠᠶᡝᠮᡝ
Doitong ᡤᡝᠮᡠᠨᡳ Kling 4.0 ᡩᡝ ᠵᠠᠯᠠᠨ ᠪᡠᠶᡝᠮᡝ᠈ ᡳᠨᡳ ᡤᡳᠰᡠᠨ ᡝᠮᡠ ᡤᡳᠯᠠᠨ ᡩᡝ ᡩᠠᡵᠠᠮᡝ
ᠰᡠᠨᡤᠠ
Оживи исходное изображение. Полностью сохрани внешность девушки, лицо, причёску, одежду, интерьер, цвета, композицию и русский текст. Девушка смотрит прямо на зрителя, естественно улыбается, моргает, слегка наклоняется вперёд и показывает пальцем на зрителя. Она естественно произносит по-русски:...
ᠰᡠᠨᡤᠠ
Оживи исходное изображение, полностью сохрани внешность девушки и дизайн розового персонажа, их лица, цвета, интерьер, композицию и существующий русский текст. Розовый персонаж оживает, смотрит на зрителя, радостно улыбается, моргает, слегка подпрыгивает и машет рукой. Он произносит по-русски:...
ᠰᡠᠨᡤᠠ
Make A warm, emotional 25 second video cinematic scene of a 4 years of boy with dark brown hair and big eyes having a difficult moment—crying, reaching toward their mother, and showing frustration. The mother initially looks concerned,she listens him then gently kneels down, makes eye contact,...
ᠰᡠᠨᡤᠠ
Ты эксперт в медиа продвижении в социальных сетях --- Название рилс: "Ошибка №1 После Развода: Почему ты тормозишь себя?" Хук (Первые 3-5 секунд): * Визуал: Крупный план вашего лица, выражающего легкое недоумение или задумчивость. Затем резкий переход к черно-белой картинке или затемнению. *...
ᠰᡠᠨᡤᠠ
🎬 Фильм «Мамы больше нет» Общий стиль для всех сцен: Фотореалистичный современный российский художественный фильм. Настоящие люди, реальные человеческие лица, натуральная кожа, естественная мимика и движения. Реальная квартира, естественный дневной и вечерний свет, кинематографическая камера,...
ᠰᡠᠨᡤᠠ
Use the uploaded image as the exact identity and appearance reference. Create a short hyperrealistic video where the woman keeps exactly the same face, identity, facial features, proportions, skin tone, hairstyle, bouquet, white shirt, pink balloons, candles “24”, and background. The motion must...
ᠰᡠᠨᡤᠠ
Медленное плавное приближение камеры к гигантскому флакону духов в миниатюрном ночном городе. Две маленькие машины спокойно проезжают по дороге перед основанием флакона. Вдали едва заметно движется лёгкая дымка. Огни города мягко отражаются на мокром асфальте. Флакон стоит неподвижно. Его форма,...
ᠰᡠᠨᡤᠠ
Девушка всилит дома смотрит интернете ищет салон красоты ,находит салон,приходит в салон наш с кудрявыми волосами ,другой мастер кератиновое выпрямление волос ,и она смотрит на свои волосы в зеркало и очень счастлива и благодарит мастера Анастасию Render entirely in "Claymation" style — match its...
ᠰᡠᠨᡤᠠ
Animate this baby very gently and naturally. She is lying on her tummy and happily playing with the colorful toy in front of her. She smiles warmly, softly blinks, makes tiny hand and finger movements toward the toy, slightly wiggles her body, and shows subtle natural breathing. The toy can move...
ᠰᡠᠨᡤᠠ
The toddler slowly lowers his raised hand and gently pats his own bottom, then continues rhythmically patting his bottom many times, slowly and softly, his palm touches only his own body, his hand stays close to his body, like a mother soothing a baby, in a sweet cute baby voice he quietly coos...
ᠰᡠᠨᡤᠠ
Дверь кофейни резко открывается. Внутрь заходит эффектная рыжеволосая девушка в чёрной кожаной куртке, шлем под мышкой. На улице у входа виден её мощный мотоцикл. Она уверенно подходит к стойке. Бариста — симпатичный парень-ботан в очках, с растрёпанными волосами, — поднимает глаза от кофемашины....
ᠰᡠᠨᡤᠠ
A cinematic 3D Pixar-style animation. The same young firefighter gently polishes his silver helmet marked with the number 5. He blinks naturally, smiles slightly, and turns his eyes toward the flashing red alarm light. Red emergency lights pulse and reflect on his helmet and face. Subtle hand...
ᠰᡠᠨᡤᠠ
Cinematic 3D Pixar-style animation. The same young firefighter from the previous shot suddenly hears the emergency alarm. His expression changes from calm to determined. He quickly turns his head toward the flashing red alarm light, grabs his silver firefighter helmet marked with the number 5,...
ᠰᡠᠨᡤᠠ
Ultra-realistic 4K ASMR video, vertical 9:16. A whole fresh brown coconut with a realistic hairy shell sits on a beautiful dark wooden cutting board. Cinematic macro close-up, soft studio lighting, luxurious satisfying aesthetic. A hand slowly approaches holding a sharp stainless steel knife. The...
ᠰᡠᠨᡤᠠ
VISUAL CORRECTION. This replaces the previous request entirely. Subject: a compact studio room A reference supplies identity ONLY. Keep the recognizable subject and visual style, but implement the requested changes to size, parts, pose, setting and composition. The actual result MUST visibly...
ᠰᡠᠨᡤᠠ
VISUAL CORRECTION. This replaces the previous request entirely. Subject: why leaves have veins A reference supplies identity ONLY. Keep the recognizable subject and visual style, but implement the requested changes to size, parts, pose, setting and composition. The actual result MUST visibly...
ᡤᡳᠰᡠᠨ ᠪᡠᠶᡝᠮᡝ
ᠵᠠᡴᡠᠨᡳ ᠵᡠᠯᡝ ᡩᡝᡵᡤᡳ ᡩᡝᠪᡝᠰᡠᠮᡝ ᠵᡠᠯᡤᡝ ᠪᡠᠶᡝᠮᡝ᠈ ᡳᠨᡳ ᡤᡳᠰᡠᠨ ᠪᠠᡳ ᡝᠨᡝᠩᡤᡳ ᠠᠮᠪᡳ
/run/kling/v4/reference-to-video?wait=20
ᠵᠠᠯᡳᠨ → $1.175
# 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/kling/v4/reference-to-video?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling/v4/reference-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/kling/v4/reference-to-video", 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": "kling/v4/reference-to-video",
"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
ᡳᠨᡝ ᠵᠠᠯᠠᠨ ᡝᡵᡝ ᠪᡠᡵᡝᠪᡝᡵᡳ ᡩᡝ ᠪᡳᠮᡝ᠈ Doitong API ᡩᡝ ᠵᡝᠯᡤᡳ ᡩᠠᡵᠠᠮᡝ᠈ Remember ᠵᡠᠯᡝᠮᡝ ᡤᡳᠯᠠᠮᡝ localStorage ᡩᡝ ᠰᡠᠯᡝᠮᡝ ᠪᡳᠮᡝ API ᠵᠠᠯᠠᠨ ᠠᠪᠠᠮᡝ
Kling 4.0 Reference to Video ᡠᡵᡝᠮᡝ
ᠪᡳᡵᡝᠩᡤᡝ ᡤᡳᠰᡠᠨᡳ `prompt` ᠪᡝ ᠠᠮᠪᠠᠰᡠᠨ ᠵᡳᡵᡤᠠᠨᡳ᠂ ᠠᡳᠯᡳᡤᠠᠨ ᠸᡳᡩᡳᠣᠣᠨ ᠪᠠ ᠨᡳᠶᠠᠯᠮᠠ ᠵᠠᡴᡳ ᠸᡝᠵᡳᠨ ᡝᠯᡝᠮᡝᠨᡨᡳ ᡳᠯᡤᠠᠮᡝ ᠸᡳᡩᡳᠣ ᠪᡝ ᠪᠣᠯᡤᠣᠮᡝ᠂ ᡳᠨᡠ ᡤᡳᠰᡠᠨᡩᡝ @Image1, @Video1 ᠶᠠᠪᡠᠯᠠᠮᡝ ᡝᠯᡝᠮᡝᠨᡨᡳ ᠰᡝᡵᡝᠩᡤᡝ ᠰᡳᠨᡩᠠᠮᡝ᠂ ᠠᡳᠯᠠᠨ 3 ᡳ ᡩᠣ 30 ᠰᡝᡴᡠᠨᡩᡝ ᠣᠴᡳᠨᠠᠮᡝ (ᡤᡳᠰᡠᠨ 5)᠂ ᠪᡝᠶᡝ ᠠᡳᠯᠠᠨ 720p ᠶᠠᠪᡠᠯᠠᠮᡝ ᡠᠮᡝ 1080p ᠵᡠᠯᡤᠠᠨ ᠪᠠ auto, 16:9, 9:16, 1:1 ᠶᠠᠪᡠᠯᠠᠮᡝ ᡠᠮᡝ 21:9. `multi_prompt` ᠪᡝ ᠵᠠᠯᡠ ᠵᠠᡴᡠ ᡤᡳᠰᡠᠨᡩᡝ ᠠᠮᠪᠠᠰᡠᠨ ᠵᠠᠪᡠᠮᡝ ᠵᡠᠰᡳᠨᡩᡝ ᠸᡝᠰᡳᠮᡝ᠂ ᡳᠨᡠ ᠠᠮᠪᠠᠰᡠᠨ ᠵᠠᠯᡠᠮᡝ ᠵᠠᡴᡠ ᠰᡝᡴᡠᠨᡳ ᡤᡝᠮᡠ ᡠᠯᡥᠠᠮᡝ. ᠵᡳᠯᡤᠠᠨ 10 ᠵᡳᡵᡤᠠᠨ᠂ ᠵᡳᠯᡤᠠᠨ 5 ᠸᡳᡩᡳᠣ 3-30s ᠪᠠ 7 ᡝᠯᡝᠮᡝᠨᡨᡳ ᠣᠴᡳᠨᠠᠮᡝ᠂ ᡳᠨᡳ 3 ᠪᡝ ᠠᠮᠠᠯᠠ ᠵᠠᡴᡳ ᠠᠮᠠᠯᠠᠮᡝ ᠠᠮᠪᠠᠰᡠᠨ.
ᠵᠠᡴᡠᠨ
ᠵᠠᡴᡠᠨᡳ ᡤᡳᠰᡠᠨ ᠵᡝᠯᡤᡳ ᠠᠪᠠᠮᠪᡳ᠈ ᠨᡝᠮᡝ ᠮᡠᠰᡝ ᡠᠯᠠᠮᠪᡳ ᠵᠠᡴᡠᠨᡳ ᡤᡳᠰᡠᠨ
promptᠵᡠᠯᡝ
multi_promptᠵᡠᠯᡝ
multi_prompt[].promptᡴᠠᠷᠠᡴᡡ
multi_prompt[].durationᠵᡠᠯᡝ
durationᠵᡠᠯᡝ
start_image_urlᠵᡠᠯᡝ
image
image_urlsᠵᡠᠯᡝ
images
video_urlsᠵᡠᠯᡝ
videos
elementsᠵᡠᠯᡝ
elements[].frontal_image_urlᠵᡠᠯᡝ
elements[].reference_image_urlsᠵᡠᠯᡝ
elements[].video_urlᠵᡠᠯᡝ
elements[].voice_idᠵᡠᠯᡝ
resolutionᠵᡠᠯᡝ
aspect_ratioᠵᡠᠯᡝ
ᠪᡠᠮᠪᡳᠯᡝᠰᡝ ᡝᠮᡠ ᡤᡝᠮᡠᠨᡳ https:// URL᠈ 10 MB ᡩᡝ ᡩᡝᠷᡤᡳ data: URI ᠵᡝᡵᡤᡳ ᡝᠮᡝ᠈ ᡳᠨᡝ ᠪᡠᠮᠪᡳᠯᡝᠰᡝᠨᡳ file_url ᠠᠪᠠᠮᠪᡳ ᠪᡠᠮᠪᡳ
ᠪᡠᠶᡝᠮᡝ
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "kling/v4/reference-to-video",
"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": 1175,
"usd": "1.175",
"charged": 1175,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"video": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_name": "0-output.mp4",
"file_size": 1843200
}
},
"outputs": [
{
"type": "video",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.mp4",
"content_type": "video/mp4",
"file_size": 1843200,
"width": 1280,
"height": 720,
"duration": 5,
"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"
}
}
ᠪᡠᠶᡝᠮᡝᠨᡳ ᡤᡳᠰᡠᠨ
- video
- object {url, content_type, file_name, file_size}ᠮᠣᠳᡝᠯ ᠪᡠᠶᡝᡥᠠᠨ ᠰᡠᠨᡤᠠ.
ᡝᠯᡤᡳ Kling 4.0 ᡠᠯᡤᡳᠨ
ᡝᠯᡤᡳ ᡩᠠᠯᡳᠨ: ᡩᠠᠯᡳᠨ ᡩᡝ ᠰᡠᠨᡤᠠ
AI ᠠᡤᡝᠨᡨᡳ ᡠᠴᡠᠷᡳ᠈ ᡝᡵᡝ ᡩᡝᠪᡝᡵᡳ Markdown ᠰᡳᠨᡩᠠᡵᡳ https://doitong.com/mnc/developers/models/kling/v4/reference-to-video.md. ᡝᡵᡝ ᠮᠣᡩᡝᠯ ᠵᠠᡴᡠᠨ ᠰᡠᠯᡠᠮᡝ https://doitong.com/developers/llms.txt