Wan · v2.2 A14b · Text to Video · Turbo
Integrere
wan/v2.2-a14b/text-to-video/turbo
# 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/wan/v2.2-a14b/text-to-video/turbo?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/wan/v2.2-a14b/text-to-video/turbo?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/wan/v2.2-a14b/text-to-video/turbo", 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/se/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": "wan/v2.2-a14b/text-to-video/turbo",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Riŋge Wan · v2.2 A14b · Text to Video · Turbo-modeallii (wan/v2.2-a14b/text-to-video/turbo) Doitong API bokte. Dokumentašuvdna ageanttaide: https://doitong.com/se/developers/models/wan/v2.2-a14b/text-to-video/turbo.md
POST https://api.doitong.ru/v1/run/wan/v2.2-a14b/text-to-video/turbo?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"
}
Jus vástádusa status lea "queued" dahje "running", jeara GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 dassážii go dat lea "succeeded"; fiillat leat outputs[].url:s. POST https://api.doitong.ru/v1/quote/wan/v2.2-a14b/text-to-video/turbo seamma boduin máksá dárkilis haddái ovdal vuodjámis.
Dát ohcamuš: 0,10 $ 100 API-kreditta · ≈ 10,75 ₽ Vuodje dán siiddu alde
Du ođđa API-čoavdda. Dat čájehuvvo dušše dál ja lea juo koden ja API-čoavdda giettis dás vuolábealde. Bisso dan čihkosis: ale goassige bidde dan kodaide mat vuđđojuvvojit fierpmádatrávnnji.
Ráhkaduvvon Doitongis
Doitong-bargosearvvi almmolaš barggut, ráhkaduvvon Wan v22 Turbo bokte. Geavat fas jearaldaga ovtta deaddilemiin.
Video
Создай 30-секундный обучающий музыкальный ролик для детей 3–5 лет. Тема: транспорт. Яркая 2D-анимация, весёлый водитель в кепке, крупные машины, пастельные цвета. 0:00–0:10 приветствие под музыку; 0:10–0:30 песенка: "Машина едет би-би, би-би", "Поезд едет ту-ту, ту-ту". Бодрая детская музыка...
Video
Создай 30-секундный обучающий музыкальный ролик для детей 3–5 лет. Тема: транспорт. Яркая 2D-анимация, тот же весёлый водитель в кепке, самолёт. 0:00–0:15 песенка: "Самолёт летит вж-ж-ж, вж-ж-ж"; 0:15–0:25 интерактивная пауза: водитель спрашивает "Как гудит машина?", пауза; 0:25–0:30 финальный...
Video
# PROMPT: Animated Mother’s Day greeting card **Format:** vertical video 9:16 **Duration:** 12–15 seconds **Style:** high‑quality Pixar‑inspired 3D animation, cinematic, warm, emotional, charming animated movie aesthetic. ### The main character is a child Use the attached image as the only and...
Ráhkat jearaldaga
Kontrollat ráhkaduvvojit modealla skeama vuođul. Koda ja haddi ođasmahttojuvvojit go rievddadat daid.
/run/wan/v2.2-a14b/text-to-video/turbo?wait=20
haddemearrádus → 0,10 $
# 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/wan/v2.2-a14b/text-to-video/turbo?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/wan/v2.2-a14b/text-to-video/turbo?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/wan/v2.2-a14b/text-to-video/turbo", 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": "wan/v2.2-a14b/text-to-video/turbo",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Geavat dán ohcamuša
Du key báhcá dán fierpmádatlogan: dat sáddejuvvo dušše Doitong API:ii ja vurkejuvvo (localStorage) dušše jos válljet Remember. Viečča API-keya
Dát lea Wan · v2.2 A14b · Text to Video · Turbo birra
Geahpideapmi teaksta-video-loahppačuokkis, mii vuostáiváldá `prompt`, `resolution` 480p, 580p dahje 720p, ja `aspect_ratio` 16:9, 9:16 dahje 1:1. Rámma-lohku, bagadallan ja lávkeheivehusat eai leat olámuttus. Sáhtát ain bidjat `seed`, `acceleration`, video-kvalitehta ja čállinmode, ja doalahit prompt-viiddideami.
Parametterat
promptgáibiduvvo
seedeaktodáhtolaš
resolutioneaktodáhtolaš
aspect_ratioeaktodáhtolaš
enable_safety_checkereaktodáhtolaš
enable_output_safety_checkereaktodáhtolaš
enable_prompt_expansioneaktodáhtolaš
accelerationeaktodáhtolaš
video_qualityeaktodáhtolaš
video_write_modeeaktodáhtolaš
Boađus
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "wan/v2.2-a14b/text-to-video/turbo",
"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": 100,
"usd": "0.10",
"charged": 100,
"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
},
"prompt": "A medium shot establishes a modern, minimalist office setting: clean lines, muted grey walls, and polished wood surfaces. The focus shifts to a close-up on a woman in sharp, navy blue business attire. Her crisp white blouse contrasts with the deep blue of her tailored suit jacket. The subtle texture of the fabric is visible—a fine weave with a slight sheen. Her expression is serious, yet engaging, as she speaks to someone unseen just beyond the frame. Close-up on her eyes, showing the intensity of her gaze and the fine lines around them that hint at experience and focus. Her lips are slightly parted, as if mid-sentence. The light catches the subtle highlights in her auburn hair, meticulously styled. Note the slight catch of light on the silver band of her watch. High resolution 4k",
"seed": 42
},
"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"
}
}
Outputa giettit
- video
- object {url, content_type, file_name, file_size}Ráhkadeami bokte buvttaduvvon videofiila.
- prompt
- stringTeakstabivdda geavahuvvon videoráhkadeapmái.
- seed
- integerRáhkadeamis geavahuvvon sádjiárvu.
Eará Wan v22 Turbo-variánttat
Eanet modeallat: Teakstas video
AI-agenttaide: dán siidu Markdowna lea dáppe https://doitong.com/se/developers/models/wan/v2.2-a14b/text-to-video/turbo.md. Buot modeallat ja ráđit: https://doitong.com/developers/llms.txt