Kling 3.0 Pro Image to Video
Integrate
kling-video/v3/pro/image-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-video/v3/pro/image-to-video?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling-video/v3/pro/image-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": False,
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/kling-video/v3/pro/image-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-video/v3/pro/image-to-video",
"input": {
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}
}
Call the Kling 3.0 Pro Image to Video model (kling-video/v3/pro/image-to-video) through the Doitong API. Docs for agents: https://doitong.com/developers/models/kling-video/v3/pro/image-to-video.md
POST https://api.doitong.com/v1/run/kling-video/v3/pro/image-to-video?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}
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-video/v3/pro/image-to-video with the same body returns the exact price before the run.
This request: $0.56 560 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.
Examples
Build a request
Controls are generated from the model schema. The code and the price update as you change them.
/run/kling-video/v3/pro/image-to-video?wait=20
quote → $0.56
# 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-video/v3/pro/image-to-video?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling-video/v3/pro/image-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": False,
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/kling-video/v3/pro/image-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-video/v3/pro/image-to-video",
"input": {
"prompt": "The paper boat drifts forward with the current, raindrops ripple around it, neon reflections shimmer on the wet street, the camera follows at water level.",
"image": "https://content.doitong.com/dev-api/2026/10/21/req_rrqclmu39lveihzpwxufalbn/0-oGMt1xgBCGjIy2tBNDIKy_MSH2rhkY.png",
"duration": 5,
"generate_audio": false
},
"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
Made on Doitong
Public works made with Kling v3 by the Doitong community. Reuse a prompt in one click.
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About Kling 3.0 Pro Image to Video
Kling's flagship image-to-video model keeps the subject of the start image stable while adding natural motion, camera moves and, by default, matching sound and speech. Give it an end image to control where the shot lands, split one generation into several shots with per-shot prompts, or pin recurring characters and objects with reference elements. The frame shape follows the start image.
Parameters
Send either the canonical name or the native name, not both. Canonical names
promptoptional
multi_promptoptional
multi_prompt[].promptrequired
multi_prompt[].durationoptional
start_image_urlrequired
image
durationoptional
generate_audiooptional
end_image_urloptional
end_image
elementsoptional
elements[].frontal_image_urloptional
elements[].reference_image_urlsoptional
elements[].video_urloptional
elements[].voice_idoptional
shot_typeoptional
negative_promptoptional
cfg_scaleoptional
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-video/v3/pro/image-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": 560,
"usd": "0.56",
"charged": 560,
"refunded": 0
},
"input": {
"prompt": "The banana manager turns to the camera, smiles and waves while coworkers keep typing, gentle handheld camera",
"image": "https://content.doitong.com/images/gp/image_20260610003801_541d9719_316882.png",
"duration": 5
},
"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 v3 variants
More models: Image to Video
For AI agents: this page as Markdown is at https://doitong.com/developers/models/kling-video/v3/pro/image-to-video.md. All models and guides: https://doitong.com/developers/llms.txt