Wan v2.2 5B · Text to Video
Integrar
wan/v2.2-5b/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/wan/v2.2-5b/text-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.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/wan/v2.2-5b/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.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/v2.2-5b/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/rm/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/v2.2-5b/text-to-video",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Cloma il model Wan v2.2 5B · Text to Video (wan/v2.2-5b/text-to-video) tras la Doitong API. Documentaziun per agents: https://doitong.com/rm/developers/models/wan/v2.2-5b/text-to-video.md
POST https://api.doitong.ru/v1/run/wan/v2.2-5b/text-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"
}
Sche il status da la resposta è "queued" u "running", fa polling GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 fin ch'el è "succeeded"; las datotecas èn en outputs[].url. POST https://api.doitong.ru/v1/quote/wan/v2.2-5b/text-to-video cun il medem body returna il pretsch exact avant l'execuziun.
Questa dumonda: $0,15 150 credits API · ≈ ₽16,14 Lantschar sin questa pagina
Tia nova clav API. Quest vegn mussada mo ussa ed è gia en il code ed en il champ da la clav API sutvart. Mantegna ella secreta: na la metta mai en code che vegn exequì en in navigatur.
Fatg sin Doitong
Ovras publicas fatgas cun Wan v22 da la communitad Doitong. Reutilisescha in prompt cun in clic.
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...
Construir ina dumonda
Ils controls vegnan generads dal schema dal model. Il code e il pretsch s'actualiseschan durant che ti als midas.
/run/wan/v2.2-5b/text-to-video?wait=20
calculaziun → $0,15
# 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/v2.2-5b/text-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.ru/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/wan/v2.2-5b/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.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/v2.2-5b/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": "wan/v2.2-5b/text-to-video",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Executar questa dumonda
Tia clav resta en quest browser: ella vegn tramessa mo al Doitong API e memorisada (localStorage) mo sch'ella scheccas Tiar a memoria. Obtegnair ina clav API
Davart Wan v2.2 5B · Text to Video
Createscha in clip video a partir d’in `prompt` textual. La lunghezza vegn definida da `num_frames` (17 a 161) e `frames_per_second` (4 a 60), cun `resolution` da 580p u 720p ed aspect ratios 16:9, 9:16 u 1:1. L’interpolaziun da frames cun film u rife po vegnir activada; la qualitad d’output ed il modus da scriver la datoteca èn adattabels. Questa è la varianta cun guidance standard e fin a 50 pass d’inferenza.
Parameters
promptobligatori
negative_promptopziunal
num_framesopziunal
frames_per_secondopziunal
seedopziunal
resolutionopziunal
aspect_ratioopziunal
num_inference_stepsopziunal
enable_safety_checkeropziunal
enable_output_safety_checkeropziunal
enable_prompt_expansionopziunal
guidance_scaleopziunal
shiftopziunal
interpolator_modelopziunal
num_interpolated_framesopziunal
adjust_fps_for_interpolationopziunal
video_qualityopziunal
video_write_modeopziunal
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "wan/v2.2-5b/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": 150,
"usd": "0.15",
"charged": 150,
"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"
}
}
Champs da l'output
- video
- object {url, content_type, file_name, file_size}Datoteca video producida da la generaziun.
- prompt
- stringPrompt da text utilisà per generar il video.
- seed
- integerValur da seed applitgada durant la generaziun.
Autras variantes Wan v22
Dapli models: Text a video
Per agents AI: questa pagina sco Markdown è disponibla sut https://doitong.com/rm/developers/models/wan/v2.2-5b/text-to-video.md. Tut ils models e las guidas: https://doitong.com/developers/llms.txt