Kling 3.0 Pro Text to Video
Integrate
kling-video/v3/pro/text-to-video
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://vit.doitong.com/api/v1/run/kling-video/v3/pro/text-to-video?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://vit.doitong.com/api/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://vit.doitong.com/api/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling-video/v3/pro/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://vit.doitong.com/api/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": False,
"aspect_ratio": "16:9",
}
# 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/text-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://vit.doitong.com/api/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "kling-video/v3/pro/text-to-video",
"input": {
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
}
}
Call the Kling 3.0 Pro Text to Video model (kling-video/v3/pro/text-to-video) through the Doitong API. Docs for agents: https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md
POST https://vit.doitong.com/api/v1/run/kling-video/v3/pro/text-to-video?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
}
If the response status is "queued" or "running", poll GET https://vit.doitong.com/api/v1/requests/REQUEST_ID?wait=20 until it is "succeeded"; the files are in outputs[].url. POST https://vit.doitong.com/api/v1/quote/kling-video/v3/pro/text-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
PromptA paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.
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/text-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://vit.doitong.com/api/v1/run/kling-video/v3/pro/text-to-video?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
}'
# Still "queued" or "running"? Poll with the id from the response:
curl "https://vit.doitong.com/api/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://vit.doitong.com/api/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling-video/v3/pro/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://vit.doitong.com/api/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": False,
"aspect_ratio": "16:9",
}
# 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/text-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/text-to-video",
"input": {
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
},
"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
About Kling 3.0 Pro Text to Video
Kling's flagship text-to-video model renders smooth, physically plausible motion and film-like lighting, and by default generates matching sound and speech. Split one clip into several shots with per-shot prompts, or let the model plan the cuts itself. 16:9, 9:16 or 1:1, any length from 3 to 15 seconds, with a negative prompt and a guidance scale.
Parameters
promptoptional
durationoptional
multi_promptoptional
multi_prompt[].promptrequired
multi_prompt[].durationoptional
generate_audiooptional
shot_typeoptional
aspect_ratiooptional
negative_promptoptional
cfg_scaleoptional
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "kling-video/v3/pro/text-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": "Close-up of fireflies dancing in a dark forest at twilight, soft glowing particles, slow dolly forward",
"duration": 5,
"aspect_ratio": "16:9"
},
"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://vit.doitong.com/api/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://vit.doitong.com/api/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: Text to Video
For AI agents: this page as Markdown is at https://doitong.com/developers/models/kling-video/v3/pro/text-to-video.md. All models and guides: https://doitong.com/developers/llms.txt