LTX 2.3 22B
Integrera
ltx-2.3-22b/reference-video-to-video/lora
# 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-2.3-22b/reference-video-to-video/lora?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",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3-22b/reference-video-to-video/lora?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors",
},
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ltx-2.3-22b/reference-video-to-video/lora", 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.ru/v1/mcp \
--header "Authorization: Bearer $DOITONG_API_KEY"
# 2. Your agent calls the "run" tool with:
{
"model_id": "ltx-2.3-22b/reference-video-to-video/lora",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}
}
Anropa modellen LTX 2.3 22B (ltx-2.3-22b/reference-video-to-video/lora) via Doitong API. Dokumentation för agenter: https://doitong.com/sv/developers/models/ltx-2.3-22b/reference-video-to-video/lora.md
POST https://api.doitong.ru/v1/run/ltx-2.3-22b/reference-video-to-video/lora?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",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}
Om svarsstatusen är "queued" eller "running" ska du polla GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 tills den är "succeeded"; filerna finns i outputs[].url. POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/reference-video-to-video/lora med samma body returnerar det exakta priset före körningen.
Filer som exemplet: 0,51 $ 510 API-krediter · ≈ 54,73 ₽ dina filer mäts innan körningen 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.
Ditt första resultat visas här
Skapa en begäran nedan och kör den med din API-nyckel. Utdata kopieras till vår lagring och sparas för alltid eller 7 dagar kostnadsfritt.
Skapa en begäran
Kontrollerna genereras från modellschemat. Koden och priset uppdateras när du ändrar dem.
/run/ltx-2.3-22b/reference-video-to-video/lora?wait=20
pris → 0,51 $
# 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-2.3-22b/reference-video-to-video/lora?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",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3-22b/reference-video-to-video/lora?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors",
},
],
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ltx-2.3-22b/reference-video-to-video/lora", 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-2.3-22b/reference-video-to-video/lora",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
},
"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 LTX 2.3 22B
Använder en referens-`video_url` och en `prompt` samt en obligatorisk lista `loras` med anpassade LoRAs. Valfri `audio_url` ersätter ljudspåret, och `image_url` och `end_image_url` anger första och sista bildruta. Längden följer referensvideon när `match_video_length` är aktiverat, annars används `num_frames` (9 till 481).
Parametrar
Skicka antingen det kanoniska namnet eller det inbyggda namnet, inte båda. Kanoniska namn
promptobligatoriskt
video_urlobligatoriskt
video
audio_urlvalfritt
audio
image_urlvalfritt
image
end_image_urlvalfritt
end_image
match_video_lengthvalfritt
num_framesvalfritt
video_sizevalfritt
generate_audiovalfritt
use_multiscalevalfritt
match_input_fpsvalfritt
fpsvalfritt
num_inference_stepsvalfritt
video_cfg_scalevalfritt
video_stg_scalevalfritt
video_rescaling_scalevalfritt
video_modality_scalevalfritt
audio_cfg_scalevalfritt
audio_stg_scalevalfritt
audio_rescaling_scalevalfritt
audio_modality_scalevalfritt
gradient_estimation_gammavalfritt
use_restart_samplingvalfritt
schedulervalfritt
accelerationvalfritt
camera_loravalfritt
camera_lora_scalevalfritt
negative_promptvalfritt
seedvalfritt
enable_prompt_expansionvalfritt
enable_safety_checkervalfritt
video_output_typevalfritt
video_qualityvalfritt
video_write_modevalfritt
lorasobligatoriskt
loras[].pathobligatoriskt
loras[].weight_namevalfritt
loras[].scalevalfritt
distill_lora_first_pass_scalevalfritt
distill_lora_second_pass_scalevalfritt
video_strengthvalfritt
audio_strengthvalfritt
preprocessorvalfritt
ic_lora_typevalfritt
Filparametrar tar emot en offentlig https://-URL, en data:-URI på upp till 10 MB eller file_url från en uppladdning. Filer
Resultat
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "ltx-2.3-22b/reference-video-to-video/lora",
"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": 510,
"usd": "0.51",
"charged": 510,
"refunded": 0
},
"input": {
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
],
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"video_url": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4"
},
"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,
"prompt": "black-and-white video, a cowboy walks through a dusty town, film grain"
},
"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"
}
}
Resultatets fält
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}Video som produceras av modellen.
- seed
- integerSeed-värde som används för att initiera genereringen av slumptal.
- prompt
- stringPrompt som används för att vägleda genereringen.
Andra LTX 2.3 22b-varianter
Fler modeller: Video till video
För AI-agenter: den här sidan som Markdown finns på https://doitong.com/sv/developers/models/ltx-2.3-22b/reference-video-to-video/lora.md. Alla modeller och guider: https://doitong.com/developers/llms.txt