Wan 2.7 Reference to Video
Integriruj
wan/v2.7/reference-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/v2.7/reference-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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/wan/v2.7/reference-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/v2.7/reference-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/rom/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/v2.7/reference-to-video",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Kall o Wan 2.7 Reference to Video modelo (wan/v2.7/reference-to-video) vas o Doitong API. Dokumentacia vaš agentura: https://doitong.com/rom/developers/models/wan/v2.7/reference-to-video.md
POST https://api.doitong.com/v1/run/wan/v2.7/reference-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"
}
Te o response status si "queued" vaj "running", ker polling GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20 dži kaj te avel "succeeded"; e fajlo si andro outputs[].url. POST https://api.doitong.com/v1/quote/wan/v2.7/reference-to-video sa jekhe body-esa del o precizno molipen angl-o phiripen.
Fajlo sar o misalo: $0.50 500 API krediti tire fajlo si merime angl-o phiripen Phir les kate
Tiro nevo API klidin. Dikhavel pes akana numa thaj si angleder ando kodo thaj ando API klidin kotor tele. Garav les: na thovel les ande kodo savo keren andre jekh browser.
Kerdo pe Doitong
Publikane khera kerde Wan27-sa e Doitong komunitetostar. Pheripen jekh prompto ande jekh klik.
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
Реалистичная бытовая сцена в советской одесской квартире зимним вечером. Женщина находится на кухне, мужчина — в комнате и прихожей. Атмосфера обычной советской семьи перед приходом гостей. Голоса: все персонажи говорят по-русски с естественным, выразительным одесским говором. Характерная...
Ker jekh mangipen
O kontrolura kerde si katar e schemaske. O kodo thaj e cena menjinen sar tu len menjines.
/run/wan/v2.7/reference-to-video?wait=20
hesab → $0.50
# 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/v2.7/reference-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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/wan/v2.7/reference-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/v2.7/reference-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/v2.7/reference-to-video",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Phandel kava mangipen
Tiro kluč ačhel kadale browsereste: bičhalel pes numa ko Doitong API thaj šuvav pes (localStorage) numa te tiknes Remember. Le jekh API ključ
Palal Wan 2.7 Reference to Video
Kerel video katar jek manglo teksto prompto plus referenca kipa (`reference_image_urls`) thaj referenca video (`reference_video_urls`) save anen karakterosko vaj objektosko dikhipe. But referenci šaj te aven jekhthane vaš scene but-subjektenca. Alosar maškar panče proporci, 720p vaj 1080p, thaj 2 dži 10 sekunda. Setis `multi_shots` true te phares o rezultato ande but shotura umesto jekh kontinualno take.
Parametra
Bičhalav vaj e kanonikano nav vaj e native nav, na duj. Kanonikane nava
prompttrubul
reference_image_urlsopcionalno
images
reference_video_urlsopcionalno
negative_promptopcionalno
aspect_ratioopcionalno
resolutionopcionalno
durationopcionalno
multi_shotsopcionalno
seedopcionalno
enable_safety_checkeropcionalno
Fajloske parametra lel jekh publikano https:// URL, jekh data: URI dži 10 MB, vaj e file_url uploadoski. Fajlura
Rezultato
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "wan/v2.7/reference-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": 500,
"usd": "0.50",
"charged": 500,
"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,
"width": 1024,
"height": 768,
"fps": 1.0,
"duration": 5,
"num_frames": 1
},
"seed": 42,
"actual_prompt": "string"
},
"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"
}
}
Outputoske fieldura
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}Video-fajlo kerdino generiripeça.
- seed
- integerSeed-valoro aplikovano ko generiripe.
- actual_prompt
- string | nullPrompto čačes labardo kana promptosko pheripe palem sas aktivime.
Aver variantura e Wan27
Bute modeli: Referenca ko Video
AI agentenge: kadija rig sar Markdown si kate https://doitong.com/rom/developers/models/wan/v2.7/reference-to-video.md. Sa e modelura thaj e gidura: https://doitong.com/developers/llms.txt