Wan-2.1 Pro Text-to-Video
Integrera
wan-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.com/v1/run/wan-pro/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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/wan-pro/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/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-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/sv/developers/docs/mcp)
claude mcp add --transport http doitong-models https://api.doitong.com/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "wan-pro/text-to-video",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Anropa modellen Wan-2.1 Pro Text-to-Video (wan-pro/text-to-video) via Doitong API. Dokumentation för agenter: https://doitong.com/sv/developers/models/wan-pro/text-to-video.md
POST https://api.doitong.com/v1/run/wan-pro/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"
}
Om svarsstatusen är "queued" eller "running" ska du polla GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 tills den är "succeeded"; filerna finns i outputs[].url. POST https://api.doitong.com/v1/quote/wan-pro/text-to-video med samma body returnerar det exakta priset före körningen.
Den här begäran: ≈0,80 $ 800 API-krediter Kör den på den här sidan
Din nya API-nyckel. Den visas bara nu och finns redan i koden och i API-nyckelfältet nedan. Håll den hemlig: lägg aldrig in den i kod som körs i en webbläsare.
Skapat på Doitong
Offentliga verk skapade med Wan 2.1 av Doitong-communityt. Återanvänd en prompt med ett klick.
Video
Create a highly realistic UGC-style smartphone video inside a modern commercial airplane during a daytime flight. Natural cabin lighting, subtle handheld camera movement, authentic airplane ambience, realistic passengers and natural acting. The video must feel like a real spontaneous phone...
Video
**SORA 2 PROMPT — 20 seconds, vertical 9:16** Create a highly realistic UGC-style smartphone video inside a modern commercial airplane during a daytime flight. Natural cabin lighting, subtle handheld camera movement, authentic airplane ambience, realistic passengers and natural acting. The video...
Video
Create a realistic cinematic 20-second video, filmed like a high-budget modern commercial with natural acting, realistic lighting and believable facial expressions. All dialogue is spoken naturally in French. **SCENE 1 — EXPENSIVE RESTAURANT, EVENING — 0–5 sec** A young man in his late 20s is...
Video
Create a realistic cinematic UGC-style commercial video, exactly 30 seconds long. The entire scene takes place inside a modern passenger airplane during a daytime flight. Natural smartphone-like cinematography, realistic airplane cabin, authentic passengers, natural lighting, realistic skin...
Video
TITLE: Santa's Secret Christmas Selfie with Dasha 🎄 VIDEO FORMAT: 15–20 seconds, vertical 9:16, cinematic Christmas short film, high-quality realistic 3D animation. REFERENCE IMAGE — DASHA_001 Use the uploaded image as the exact character reference for Dasha. Preserve her recognizable face,...
Skapa en begäran
Kontrollerna genereras från modellschemat. Koden och priset uppdateras när du ändrar dem.
/run/wan-pro/text-to-video?wait=20
pris → 0,80 $
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/wan-pro/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.com/v1/requests/REQUEST_ID?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/wan-pro/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/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-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": "wan-pro/text-to-video",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Kör den här begäran
Din nyckel stannar i den här webbläsaren: den skickas endast till Doitong API och sparas endast i localStorage om du markerar Kom ihåg. Hämta en API-nyckel
Om Wan-2.1 Pro Text-to-Video
Genererar video enbart från en textbaserad `prompt`. Utdata är en videofil. Indata är avsiktligt minimala: `seed` för reproducerbara resultat och en växel för säkerhetskontrollen. Den har ingen bildindata och inga val för upplösning eller längd.
Parametrar
promptobligatoriskt
seedvalfritt
enable_safety_checkervalfritt
Resultat
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "wan-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": 800,
"usd": "0.80",
"charged": 800,
"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
}
},
"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.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Resultatets fält
- video
- object {url, content_type, file_name, file_size}Video som produceras av modellen.
Andra Wan 2.1-varianter
Fler modeller: Text till video
För AI-agenter: den här sidan som Markdown finns på https://doitong.com/sv/developers/models/wan-pro/text-to-video.md. Alla modeller och guider: https://doitong.com/developers/llms.txt