LTX-2.3 22B · Text to Video
Integrasikan
ltx-2.3-22b/text-to-video
# 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?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3-22b/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/ltx-2.3-22b/text-to-video", 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/id/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",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
}
Panggil model LTX-2.3 22B · Text to Video (ltx-2.3-22b/text-to-video) melalui Doitong API. Dokumentasi untuk agen: https://doitong.com/id/developers/models/ltx-2.3-22b/text-to-video.md
POST https://api.doitong.ru/v1/run/ltx-2.3-22b/text-to-video?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"
}
Jika status respons adalah "queued" atau "running", lakukan polling GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 hingga statusnya menjadi "succeeded"; file terdapat di outputs[].url. POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/text-to-video dengan body yang sama mengembalikan harga pasti sebelum dijalankan.
File seperti contoh: $0,18 180 kredit API · ≈ ₽19,36 file Anda diukur sebelum dijalankan Jalankan di halaman ini
Kunci API baru Anda. Ini hanya ditampilkan sekarang dan sudah dimasukkan ke dalam kode serta kolom kunci API di bawah. Simpan secara rahasia: jangan pernah menaruhnya di kode yang berjalan di browser.
Hasil pertama Anda akan muncul di sini
Buat permintaan di bawah ini dan jalankan dengan kunci API Anda. Output disalin ke penyimpanan kami, disimpan selamanya atau 7 hari gratis.
Buat permintaan
Kontrol dibuat dari skema model. Kode dan harga diperbarui saat Anda mengubahnya.
/run/ltx-2.3-22b/text-to-video?wait=20
estimasi harga → $0,18
# 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?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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3-22b/text-to-video?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/ltx-2.3-22b/text-to-video", 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",
"input": {
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
},
"wait_seconds": 20
}
}
}
Jalankan permintaan ini
Key Anda tetap berada di browser ini: key hanya dikirim ke Doitong API dan disimpan (localStorage) hanya jika Anda mencentang Ingat. Dapatkan kunci API
Tentang LTX-2.3 22B · Text to Video
Menghasilkan klip dari `prompt`. `video_size` menyediakan prasetel persegi, potret, dan lanskap, `num_frames` berkisar dari 9 hingga 481, dan `fps` dari 1 hingga 60. `generate_audio` menambahkan suara. Sampling dapat disesuaikan dengan `num_inference_steps` (8 hingga 50), skala panduan, `camera_lora`, dan skala LoRA distill untuk setiap pass.
Parameter
promptwajib
num_framesopsional
video_sizeopsional
generate_audioopsional
use_multiscaleopsional
fpsopsional
num_inference_stepsopsional
video_cfg_scaleopsional
video_stg_scaleopsional
video_rescaling_scaleopsional
video_modality_scaleopsional
audio_cfg_scaleopsional
audio_stg_scaleopsional
audio_rescaling_scaleopsional
audio_modality_scaleopsional
gradient_estimation_gammaopsional
use_restart_samplingopsional
scheduleropsional
accelerationopsional
camera_loraopsional
camera_lora_scaleopsional
negative_promptopsional
seedopsional
enable_prompt_expansionopsional
enable_safety_checkeropsional
video_output_typeopsional
video_qualityopsional
video_write_modeopsional
distill_lora_first_pass_scaleopsional
distill_lora_second_pass_scaleopsional
Output
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "ltx-2.3-22b/text-to-video",
"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": 180,
"usd": "0.18",
"charged": 180,
"refunded": 0
},
"input": {
"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"
}
}
Field output
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}Video yang dihasilkan model.
- seed
- integerNilai seed yang digunakan untuk menginisialisasi pembuatan angka acak.
- prompt
- stringPrompt yang digunakan untuk memandu pembuatan.
Varian LTX 2.3 22b lainnya
Model lainnya: Teks ke Video
Untuk agen AI: halaman ini dalam Markdown tersedia di https://doitong.com/id/developers/models/ltx-2.3-22b/text-to-video.md. Semua model dan panduan: https://doitong.com/developers/llms.txt