Kling 3.0 Pro Text to Video
Integra
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://api.doitong.ru/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://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling-video/v3/pro/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/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/it/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-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"
}
}
Chiama il modello Kling 3.0 Pro Text to Video (kling-video/v3/pro/text-to-video) tramite Doitong API. Documentazione per gli agenti: https://doitong.com/it/developers/models/kling-video/v3/pro/text-to-video.md
POST https://api.doitong.ru/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"
}
Se lo stato della risposta è "queued" o "running", interroga GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 finché non diventa "succeeded"; i file si trovano in outputs[].url. POST https://api.doitong.ru/v1/quote/kling-video/v3/pro/text-to-video con lo stesso body restituisce il prezzo esatto prima dell'esecuzione.
Questa richiesta: 0,56 $ 560 crediti API · ≈ 59,68 ₽ Esegui in questa pagina
La tua nuova chiave API. Viene mostrata solo ora ed è già presente nel codice e nel campo della chiave API qui sotto. Mantienila segreta: non inserirla mai nel codice eseguito in un browser.
Esempi
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.
Crea una richiesta
I controlli vengono generati dallo schema del modello. Il codice e il prezzo si aggiornano mentre li modifichi.
/run/kling-video/v3/pro/text-to-video?wait=20
preventivo → 0,56 $
# 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-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://api.doitong.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/kling-video/v3/pro/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A paper boat drifts down a rain-filled street gutter at dusk. The camera follows at water level as raindrops ripple around it and neon reflections shimmer on the wet asphalt, then the boat tips over a small cascade into a puddle. Realistic water physics, shallow depth of field, cinematic.",
"duration": 5,
"generate_audio": false,
"aspect_ratio": "16:9"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/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
}
}
}
Esegui questa richiesta
La tua chiave rimane in questo browser: viene inviata solo al Doitong API e salvata in localStorage solo se selezioni Ricorda. Ottieni una chiave API
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Informazioni su Kling 3.0 Pro Text to Video
Il modello text-to-video di punta di Kling renderizza movimenti fluidi e fisicamente plausibili e un'illuminazione cinematografica, e genera per impostazione predefinita suono e parlato sincronizzati. Dividi una clip in diverse inquadrature con prompt per inquadratura, oppure lascia che sia il modello a pianificare i tagli. 16:9, 9:16 o 1:1, con qualsiasi durata da 3 a 15 secondi, con un prompt negativo e una scala di guidance.
Parametri
promptfacoltativo
durationfacoltativo
multi_promptfacoltativo
multi_prompt[].promptobbligatorio
multi_prompt[].durationfacoltativo
generate_audiofacoltativo
shot_typefacoltativo
aspect_ratiofacoltativo
negative_promptfacoltativo
cfg_scalefacoltativo
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://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Campi dell'output
- video
- object {url, content_type, file_name, file_size}Video prodotto dal modello.
Altre varianti di Kling v3
Altri modelli: Da testo a video
Per gli agenti AI: questa pagina in Markdown è disponibile all'indirizzo https://doitong.com/it/developers/models/kling-video/v3/pro/text-to-video.md. Tutti i modelli e le guide: https://doitong.com/developers/llms.txt