LTX-2.3 22B Video to Video Trainer
Integracija
ltx23-v2v-trainer
# 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/ltx23-v2v-trainer?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"training_data_url": "https://example.com/your-file.zip"
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx23-v2v-trainer?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"training_data_url": "https://example.com/your-file.zip"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"training_data_url": "https://example.com/your-file.zip",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ltx23-v2v-trainer", 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/sl/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": "ltx23-v2v-trainer",
"input": {
"training_data_url": "https://example.com/your-file.zip"
}
}
Pokličite model LTX-2.3 22B Video to Video Trainer (ltx23-v2v-trainer) prek Doitong API. Dokumentacija za agente: https://doitong.com/sl/developers/models/ltx23-v2v-trainer.md
POST https://api.doitong.com/v1/run/ltx23-v2v-trainer?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"training_data_url": "https://example.com/your-file.zip"
}
Če je stanje odgovora "queued" ali "running", pošiljajte poizvedbe GET https://api.doitong.com/v1/requests/REQUEST_ID?wait=20, dokler ni "succeeded"; datoteke so v outputs[].url. POST https://api.doitong.com/v1/quote/ltx23-v2v-trainer z enakim telesom vrne natančno ceno pred zagonom.
Ta zahteva: 27,00 $ 27.000 API kreditov Zaženi na tej strani
Vaš novi ključ API. Prikazan je samo zdaj in je že v kodi ter v spodnjem polju ključa API. Hranite ga kot skrivnost: nikoli ga ne vključite v kodo, ki se izvaja v brskalniku.
Tukaj bo vaš prvi rezultat
Spodaj sestavite zahtevo in jo zaženite s svojim ključem API. Izhodi se kopirajo v našo shrambo, kjer se hranijo za vedno ali 7 dni brezplačno.
Ustvari zahtevo
Kontrolniki se ustvarijo iz sheme modela. Koda in cena se posodobita, ko ju spreminjate.
/run/ltx23-v2v-trainer?wait=20
cena → 27,00 $
# 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/ltx23-v2v-trainer?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"training_data_url": "https://example.com/your-file.zip"
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.com/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx23-v2v-trainer?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"training_data_url": "https://example.com/your-file.zip"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"training_data_url": "https://example.com/your-file.zip",
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/ltx23-v2v-trainer", 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": "ltx23-v2v-trainer",
"input": {
"training_data_url": "https://example.com/your-file.zip"
},
"wait_seconds": 20
}
}
}
Zaženi to zahtevo
Vaš ključ ostane v tem brskalniku: pošlje se samo v Doitong API in shrani v localStorage samo, če označite možnost Zapomni si. Pridobi ključ API
O modelu LTX-2.3 22B Video to Video Trainer
Uči LoRA na modelu LTX-2.3 22B za transformacijo videa z uporabo arhiva zip videov ali slik (mp4, mov, avi, mkv, png, jpg, jpeg); priporočenih je vsaj približno 10 datotek. `number_of_steps` sega od 1 do 20000 (privzeto 2000), `frame_rate` pa je privzeto 25. `first_frame_conditioning_p` je privzeto 0.1. Validacija sprejme največ 2 poziva z referenčnimi videi.
Parametri
training_data_urlobvezno
rankneobvezno
number_of_stepsneobvezno
learning_rateneobvezno
number_of_framesneobvezno
frame_rateneobvezno
resolutionneobvezno
aspect_rationeobvezno
trigger_phraseneobvezno
auto_scale_inputneobvezno
split_input_into_scenesneobvezno
split_input_duration_thresholdneobvezno
debug_datasetneobvezno
first_frame_conditioning_pneobvezno
validationneobvezno
validation[].promptobvezno
validation[].reference_video_urlobvezno
validation_negative_promptneobvezno
validation_number_of_framesneobvezno
validation_frame_rateneobvezno
validation_resolutionneobvezno
validation_aspect_rationeobvezno
stg_scaleneobvezno
Izhod
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "ltx23-v2v-trainer",
"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": 27000,
"usd": "27.00",
"charged": 27000,
"refunded": 0
},
"input": {
"training_data_url": "https://example.com/your-file.zip"
},
"output": {
"video": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200
},
"lora_file": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200
},
"config_file": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200
},
"debug_dataset": {
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_name": "0-output.jpeg",
"file_size": 1843200
}
},
"outputs": [
{
"type": "file",
"url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
"content_type": "image/jpeg",
"file_size": 1843200,
"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"
}
}
Polja izhoda
- video
- object {url, content_type, file_name, file_size} | nullURL vseh razpoložljivih validacijskih videov, prikazanih ob njihovih referenčnih videih.
- lora_file
- object {url, content_type, file_name, file_size}URL datoteke uteži naučenega IC-LoRA v obliki .safetensors.
- config_file
- object {url, content_type, file_name, file_size}Konfiguracija za nastavitev končne točke sklepanja.
- debug_dataset
- object {url, content_type, file_name, file_size} | nullArhiv za odpravljanje napak, na voljo samo za vhode, ki omogočajo `debug_dataset`; njegova vsebina učnih podatkov je predobdelana in vključuje videe v dekodirani obliki.
Več modelov: Učenje
Za agente AI: ta stran je v obliki Markdown na voljo na https://doitong.com/sl/developers/models/ltx23-v2v-trainer.md. Vsi modeli in vodniki: https://doitong.com/developers/llms.txt