LTX 2.3 Video Fast · Image to Video
Integrer
ltx-2.3/image-to-video/fast
# 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/ltx-2.3/image-to-video/fast?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3/image-to-video/fast?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"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/ltx-2.3/image-to-video/fast", 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": "ltx-2.3/image-to-video/fast",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Kald LTX 2.3 Video Fast · Image to Video-modellen (ltx-2.3/image-to-video/fast) via Doitong API. Dokumentation til agenter: https://doitong.com/da/developers/models/ltx-2.3/image-to-video/fast.md
POST https://api.doitong.ru/v1/run/ltx-2.3/image-to-video/fast?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"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/ltx-2.3/image-to-video/fast med samme body returnerer den nøjagtige pris før kørslen.
Denne anmodning: 0,36 $ 360 API-kreditter · ≈ 38,73 ₽ 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/ltx-2.3/image-to-video/fast?wait=20
pris → 0,36 $
# 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/ltx-2.3/image-to-video/fast?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3/image-to-video/fast?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"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/ltx-2.3/image-to-video/fast", 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": "ltx-2.3/image-to-video/fast",
"input": {
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"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 LTX 2.3 Video Fast · Image to Video
Animerer et billede med en påkrævet prompt og en valgfri `end_image_url` til en overgang. `duration` kan være 6 til 20 sekunder i trin på to, men varigheder over 10 sekunder kræver 25 fps og 1080p. `resolution` omfatter 1080p, 1440p og 2160p, og fps kan være 24, 25, 48 eller 50. Der kan genereres lyd.
Parametre
Send enten det kanoniske navn eller det oprindelige navn, ikke begge. Kanoniske navne
image_urlpåkrævet
image
end_image_urlvalgfri
end_image
promptpåkrævet
durationvalgfri
resolutionvalgfri
aspect_ratiovalgfri
fpsvalgfri
generate_audiovalgfri
enable_safety_checkervalgfri
Filparametre accepterer en offentlig https://-URL, en data:-URI på op til 10 MB eller file_url fra en upload. Filer
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "ltx-2.3/image-to-video/fast",
"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": 360,
"usd": "0.36",
"charged": 360,
"refunded": 0
},
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"image_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg"
},
"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
}
},
"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
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}Resulterende videofil.
Andre LTX 2.3-varianter
Flere modeller: Billede til video
Til AI-agenter: Denne side som Markdown findes på https://doitong.com/da/developers/models/ltx-2.3/image-to-video/fast.md. Alle modeller og vejledninger: https://doitong.com/developers/llms.txt