Kling 4.0 Reference to Video
Integrate
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.com/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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling/v4/reference-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.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/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/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": "kling/v4/reference-to-video",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Call the Kling 4.0 Reference to Video model (kling/v4/reference-to-video) through the Doitong API. Docs for agents: https://doitong.com/developers/models/kling/v4/reference-to-video.md
POST https://api.doitong.com/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"
}
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/kling/v4/reference-to-video with the same body returns the exact price before the run.
Files like the example: $1.175 1,175 API credits your files are measured before the run 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.
Made on Doitong
Public works made with Kling 4.0 by the Doitong community. Reuse a prompt in one click.
Video
**Duration: 4 seconds | Aspect ratio: 16:9 | Children's YouTube Intro | Video with Audio** Animate the provided image into a bright, magical, energetic, professional YouTube intro for a children's entertainment channel, with perfectly synchronized sound effects, cheerful music, and a cute child's...
Video
**Duration: 4 seconds | Aspect ratio: 16:9 | Children's YouTube Intro | Video with Audio** Animate the provided image into a bright, magical, energetic, professional YouTube intro for a children's entertainment channel, with perfectly synchronized sound effects, cheerful music, and a cute child's...
Video
**Duration: 4 seconds | Aspect ratio: 16:9 | Children's YouTube Intro | Video with Audio** Animate the provided image into a bright, magical, energetic, professional YouTube intro for a children's entertainment channel, with perfectly synchronized sound effects, cheerful music, and a cute child's...
Video
**Duration: 5 seconds | Aspect ratio: 16:9 | Children's YouTube Intro | Video with Audio** Animate the provided image into a bright, magical, energetic, professional YouTube intro for a children's entertainment channel, with perfectly synchronized sound effects, cheerful music, and a cute child's...
Video
Моя первая глобальная цель — 10.000 подписчиков. Я хочу расти вместе с вами, делать сериалы ещё круче, масштабнее и в итоге превратить это в полноценный проект, чтобы в дальнейшем монетизировать свой блог. Путь к первой десятке объявляю открытым. Идём со мной? Мне нужно такое видео в трёх кадрах...
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Video
Кролик открывает дверь девушке, девушка дает чаевые кролику и говорит « спасибо, мой ушастый друг», он закрывает за ней дверь и говорит «Пожалуйста, красотка» после того как она села в машину за руль, кролик немного отходит, девушка в дрифте уезжает, все в одной сцене. Съемка кинематографичная....
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Animate this image realistically. Make me look like I am working at the computer: my eyes should naturally look at the screen, my hands should move naturally as if typing on the keyboard, and occasionally use the mouse. Add subtle, realistic movements to my head and body. Keep my facial...
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«Шедевр» Духовка резко открывается. ПУФ! Облако пара исчезает — внутри стоит красивый золотистый пирог. Лиза радостно достаёт его и пробует кусочек. Лиза: «Я гений!» Пирог внезапно наклоняется и падает набок. ПЛЮХ! Лиза смотрит на него и невозмутимо говорит: Лиза: «Ну… почти.» Камера быстро...
Video
В видео показана короткая драматическая история примерно на 29 секунд: * 0–4 сек. Мужчина со слезами на глазах держит оружие и выглядит глубоко расстроенным. * 4–8 сек. Он направляет оружие на женщину в клетчатой рубашке. Женщина зомби стоит спокойно, между ними напряжённая атмосфера. * 8–12 сек....
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Video
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Video
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Video
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Build a request
Controls are generated from the model schema. The code and the price update as you change them.
/run/kling/v4/reference-to-video?wait=20
quote → $1.175
# 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/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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling/v4/reference-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.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/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
}
}
}
Run this request
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About Kling 4.0 Reference to Video
Creates video from a text `prompt` plus reference images, reference videos and character or object elements, which are cited in the prompt as @Image1, @Video1 or @Element1. Duration runs from 3 to 30 seconds (default 5), with output at 720p or 1080p and aspect ratios auto, 16:9, 9:16, 1:1 or 21:9. Use `multi_prompt` for per-shot prompts, in which case the total length is the sum of the shot durations. Limits are 10 images, 5 videos of 3-30s each, and 7 elements, of which up to 3 can carry a voice.
Parameters
Send either the canonical name or the native name, not both. Canonical names
promptoptional
multi_promptoptional
multi_prompt[].promptrequired
multi_prompt[].durationoptional
durationoptional
start_image_urloptional
image
image_urlsoptional
images
video_urlsoptional
videos
elementsoptional
elements[].frontal_image_urloptional
elements[].reference_image_urlsoptional
elements[].video_urloptional
elements[].voice_idoptional
resolutionoptional
aspect_ratiooptional
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": "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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Fields of output
- video
- object {url, content_type, file_name, file_size}Video produced by the model.
Other Kling 4.0 variants
More models: Reference to Video
For AI agents: this page as Markdown is at https://doitong.com/developers/models/kling/v4/reference-to-video.md. All models and guides: https://doitong.com/developers/llms.txt