Wan v2.2 5B · Text to Video
Intégrer
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/fr/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"
}
}
Appelez le modèle Wan v2.2 5B · Text to Video (wan/v2.2-5b/text-to-video) via la Doitong API. Documentation pour les agents : https://doitong.com/fr/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"
}
Si le statut de la réponse est "queued" ou "running", interrogez GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 jusqu’à ce qu’il soit "succeeded" ; les fichiers se trouvent dans outputs[].url. POST https://api.doitong.ru/v1/quote/wan/v2.2-5b/text-to-video avec le même corps renvoie le prix exact avant l’exécution.
Cette requête: 0,15 $ 150 crédits API · ≈ 16,14 ₽ L’exécuter sur cette page
Votre nouvelle clé API. Elle n’est affichée que maintenant et figure déjà dans le code et dans le champ de clé API ci-dessous. Gardez-la secrète : ne l’intégrez jamais dans du code exécuté dans un navigateur.
Créé sur Doitong
Créations publiques réalisées avec Wan v22 par la communauté Doitong. Réutilisez un prompt en un clic.
Vidéo
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...
Vidéo
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...
Créer une requête
Les contrôles sont générés à partir du schéma du modèle. Le code et le prix se mettent à jour lorsque vous les modifiez.
/run/wan/v2.2-5b/text-to-video?wait=20
devis → 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
}
}
}
Exécuter cette requête
Votre clé reste dans ce navigateur : elle est envoyée uniquement à la Doitong API et enregistrée dans localStorage uniquement si vous cochez Mémoriser. Obtenir une clé API
À propos de Wan v2.2 5B · Text to Video
Crée un clip vidéo à partir d’un `prompt` textuel. La longueur est définie par `num_frames` (17 à 161) et `frames_per_second` (4 à 60), avec une `resolution` de 580p ou 720p et les formats 16:9, 9:16 ou 1:1. L’interpolation film ou rife peut être activée, et la qualité de sortie ainsi que le mode d’écriture sont configurables. Il s’agit de la variante à guidage standard avec jusqu’à 50 étapes d’inférence.
Paramètres
promptrequis
negative_promptfacultatif
num_framesfacultatif
frames_per_secondfacultatif
seedfacultatif
resolutionfacultatif
aspect_ratiofacultatif
num_inference_stepsfacultatif
enable_safety_checkerfacultatif
enable_output_safety_checkerfacultatif
enable_prompt_expansionfacultatif
guidance_scalefacultatif
shiftfacultatif
interpolator_modelfacultatif
num_interpolated_framesfacultatif
adjust_fps_for_interpolationfacultatif
video_qualityfacultatif
video_write_modefacultatif
Sortie
{
"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 de sortie
- video
- object {url, content_type, file_name, file_size}Fichier vidéo produit par la génération.
- prompt
- stringPrompt textuel utilisé pour générer la vidéo.
- seed
- integerValeur du seed appliquée pendant la génération.
Autres variantes Wan v22
Plus de modèles : Texte vers vidéo
Pour les agents IA : cette page au format Markdown est disponible à https://doitong.com/fr/developers/models/wan/v2.2-5b/text-to-video.md. Tous les modèles et guides : https://doitong.com/developers/llms.txt