LTX-2.3 22B · Text to Video · LoRA
Integrasikan
ltx-2.3-22b/text-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/text-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",
"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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3-22b/text-to-video/lora?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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",
"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/text-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/ms/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/text-to-video/lora",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}
}
Panggil model LTX-2.3 22B · Text to Video · LoRA (ltx-2.3-22b/text-to-video/lora) melalui Doitong API. Dokumentasi untuk ejen: https://doitong.com/ms/developers/models/ltx-2.3-22b/text-to-video/lora.md
POST https://api.doitong.ru/v1/run/ltx-2.3-22b/text-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",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}
Jika status respons ialah "queued" atau "running", tinjau GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 sehingga statusnya menjadi "succeeded"; fail berada dalam outputs[].url. POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/text-to-video/lora dengan badan yang sama mengembalikan harga tepat sebelum dijalankan.
Fail seperti contoh: $0.203 203 kredit API · ≈ ₽21.84 fail anda diukur sebelum dijalankan Jalankan pada halaman ini
Kunci API baharu anda. Ia hanya dipaparkan sekarang dan sudah dimasukkan dalam kod serta medan kunci API di bawah. Simpan secara rahsia: jangan sekali-kali letakkannya dalam kod yang berjalan dalam pelayar.
Hasil pertama anda akan muncul di sini
Bina permintaan di bawah dan jalankannya dengan kunci API anda. Output disalin ke storan kami, disimpan selama-lamanya atau 7 hari secara percuma.
Bina permintaan
Kawalan dijana daripada skema model. Kod dan harga dikemas kini apabila anda mengubahnya.
/run/ltx-2.3-22b/text-to-video/lora?wait=20
sebut harga → $0.203
# 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/text-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",
"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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3-22b/text-to-video/lora?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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",
"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/text-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/text-to-video/lora",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
},
"wait_seconds": 20
}
}
}
Jalankan permintaan ini
Kunci anda kekal dalam pelayar ini: ia hanya dihantar kepada Doitong API dan disimpan (localStorage) hanya jika anda menanda Ingat. Dapatkan kunci API
Tentang LTX-2.3 22B · Text to Video · LoRA
Menerima `prompt` dan senarai `loras` LoRA tersuai yang diperlukan. `video_size` menawarkan pratetap segi empat sama, potret dan landskap, `num_frames` ialah 9 hingga 481 dan `fps` 1 hingga 60. Penjanaan audio, LoRA kamera dan skala distill LoRA laluan pertama turut tersedia.
Parameter
promptdiperlukan
num_framespilihan
video_sizepilihan
generate_audiopilihan
use_multiscalepilihan
fpspilihan
num_inference_stepspilihan
video_cfg_scalepilihan
video_stg_scalepilihan
video_rescaling_scalepilihan
video_modality_scalepilihan
audio_cfg_scalepilihan
audio_stg_scalepilihan
audio_rescaling_scalepilihan
audio_modality_scalepilihan
gradient_estimation_gammapilihan
use_restart_samplingpilihan
schedulerpilihan
accelerationpilihan
camera_lorapilihan
camera_lora_scalepilihan
negative_promptpilihan
seedpilihan
enable_prompt_expansionpilihan
enable_safety_checkerpilihan
video_output_typepilihan
video_qualitypilihan
video_write_modepilihan
lorasdiperlukan
loras[].pathdiperlukan
loras[].weight_namepilihan
loras[].scalepilihan
distill_lora_first_pass_scalepilihan
distill_lora_second_pass_scalepilihan
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "ltx-2.3-22b/text-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": 203,
"usd": "0.203",
"charged": 203,
"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"
},
"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": "A cowboy walking through a dusty town at high noon, camera following from behind, cinematic depth, realistic lighting, western mood, 4K 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"
}
}
Medan output
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}Video yang dihasilkan oleh model.
- seed
- integerNilai seed yang digunakan untuk memulakan penjanaan nombor rawak.
- prompt
- stringPrompt yang digunakan untuk membimbing penjanaan.
Varian LTX 2.3 22b lain
Lebih banyak model: Teks ke Video
Untuk ejen AI: halaman ini dalam Markdown tersedia di https://doitong.com/ms/developers/models/ltx-2.3-22b/text-to-video/lora.md. Semua model dan panduan: https://doitong.com/developers/llms.txt