LongCat Video · Text to Video · 480p
Integrer
longcat-video/text-to-video/480p
# 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/longcat-video/text-to-video/480p?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/longcat-video/text-to-video/480p?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/longcat-video/text-to-video/480p", 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/da/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": "longcat-video/text-to-video/480p",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Kald LongCat Video · Text to Video · 480p-modellen (longcat-video/text-to-video/480p) via Doitong API. Dokumentation til agenter: https://doitong.com/da/developers/models/longcat-video/text-to-video/480p.md
POST https://api.doitong.ru/v1/run/longcat-video/text-to-video/480p?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"
}
Hvis svarstatus er "queued" eller "running", skal du forespørge GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 igen, indtil den er "succeeded"; filerne findes i outputs[].url. POST https://api.doitong.ru/v1/quote/longcat-video/text-to-video/480p med samme body returnerer den nøjagtige pris før kørslen.
Filer som eksemplet: 0,27 $ 270 API-kreditter · ≈ 29,05 ₽ dine filer måles før kørslen Kør den på denne side
Din nye API-nøgle. Den vises kun nu og findes allerede i koden og i feltet til API-nøglen nedenfor. Hold den hemmelig: Anbring den aldrig i kode, der kører i en browser.
Dit første resultat kommer her
Opret en anmodning nedenfor, og kør den med din API-nøgle. Output kopieres til vores lagring, gemt for altid eller 7 dage gratis.
Opret en anmodning
Kontrollerne genereres fra modellens skema. Koden og prisen opdateres, når du ændrer dem.
/run/longcat-video/text-to-video/480p?wait=20
pris → 0,27 $
# 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/longcat-video/text-to-video/480p?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/longcat-video/text-to-video/480p?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/longcat-video/text-to-video/480p", 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": "longcat-video/text-to-video/480p",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Kør denne anmodning
Din nøgle forbliver i denne browser: Den sendes kun til Doitong API og gemmes kun i localStorage, hvis du markerer Husk. Hent en API-nøgle
Om LongCat Video · Text to Video · 480p
Genererer en video udelukkende fra en tekst-`prompt`. `aspect_ratio` kan være 16:9, 9:16 eller 1:1, og `num_frames` spænder fra 17 til 961 (standard 162) ved 1 til 60 `fps`. Den tilbyder `num_inference_steps` (8 til 50), `guidance_scale` (1 til 10) og en negativ prompt. Resultatet kan være MP4, WebM, ProRes MOV eller GIF.
Parametre
promptpåkrævet
negative_promptvalgfri
num_framesvalgfri
num_inference_stepsvalgfri
guidance_scalevalgfri
aspect_ratiovalgfri
fpsvalgfri
seedvalgfri
enable_prompt_expansionvalgfri
enable_safety_checkervalgfri
video_output_typevalgfri
video_qualityvalgfri
video_write_modevalgfri
accelerationvalgfri
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "longcat-video/text-to-video/480p",
"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": 270,
"usd": "0.27",
"charged": 270,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"output": {
"prompt": "realistic filming style, a person wearing a dark helmet, a deep-colored jacket, blue jeans, and bright yellow shoes rides a skateboard along a winding mountain road. The skateboarder starts in a standing position, then gradually lowers into a crouch, extending one hand to touch the road surface while maintaining a low center of gravity to navigate a sharp curve. After completing the turn, the skateboarder rises back to a standing position and continues gliding forward. The background features lush green hills flanking both sides of the road, with distant snow-capped mountain peaks rising against a clear, bright blue sky. The camera follows closely from behind, smoothly tracking the skateboarder’s movements and capturing the dynamic scenery along the route. The scene is shot in natural daylight, highlighting the vivid outdoor environment and the skateboarder’s fluid actions.",
"seed": 42,
"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.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
"cancel": "https://api.doitong.ru/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
}
}
Outputfelter
- prompt
- stringPrompten, der blev brugt til at generere outputtet.
- seed
- integerSeed-værdi anvendt under generering.
- video
- object {url, content_type, file_name, file_size}Videofil produceret ved generering.
Andre LongCat Video-varianter
Flere modeller: Tekst til video
Til AI-agenter: Denne side som Markdown findes på https://doitong.com/da/developers/models/longcat-video/text-to-video/480p.md. Alle modeller og vejledninger: https://doitong.com/developers/llms.txt