LTX-2.3 22B · Text to Video
Integreiddio
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/cy/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"
}
}
Galwch y model LTX-2.3 22B · Text to Video (ltx-2.3-22b/text-to-video) drwy Doitong API. Dogfennaeth ar gyfer asiantau: https://doitong.com/cy/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"
}
Os yw statws yr ymateb yn "queued" neu "running", holwch GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 nes ei fod yn "succeeded"; mae'r ffeiliau yn outputs[].url. Mae POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/text-to-video gyda'r un corff yn dychwelyd yr union bris cyn y rhediad.
Ffeiliau fel yr enghraifft: $0.18 180 o gredydau API · ≈ ₽19.36 caiff eich ffeiliau eu mesur cyn y rhediad Ei redeg ar y dudalen hon
Eich allwedd API newydd. Dim ond nawr y caiff ei ddangos ac mae eisoes yn y cod ac ym maes allwedd API isod. Cadwch ef yn gyfrinachol: peidiwch byth â’i roi mewn cod sy’n rhedeg mewn porwr.
Mae eich canlyniad cyntaf yn mynd yma
Adeiladwch gais isod a'i redeg gyda'ch allwedd API. Mae allbynnau'n cael eu copïo i'n storio, wedi'u cadw am byth neu am 7 diwrnod am ddim.
Adeiladu cais
Cynhyrchir rheolyddion o sgema'r model. Mae'r cod a'r pris yn diweddaru wrth i chi eu newid.
/run/ltx-2.3-22b/text-to-video?wait=20
dyfynbris → $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
}
}
}
Rhedeg y cais hwn
Mae'ch allwedd yn aros yn y porwr hwn: caiff ei hanfon at Doitong API yn unig a'i chadw (localStorage) dim ond os ticiwch Cofio. Cael allwedd API
Ynglŷn â LTX-2.3 22B · Text to Video
Yn cynhyrchu clip o `prompt`. Mae `video_size` yn cynnig rhagosodiadau sgwâr, portread a thirwedd, mae `num_frames` yn amrywio o 9 i 481, ac `fps` yn 1 i 60. Mae `generate_audio` yn ychwanegu sain. Gellir tiwnio samplu gyda `num_inference_steps` (8 i 50), graddfeydd arweiniad, `camera_lora` a graddfeydd distill LoRA ar gyfer pob rediad.
Paramedrau
promptgofynnol
num_framesdewisol
video_sizedewisol
generate_audiodewisol
use_multiscaledewisol
fpsdewisol
num_inference_stepsdewisol
video_cfg_scaledewisol
video_stg_scaledewisol
video_rescaling_scaledewisol
video_modality_scaledewisol
audio_cfg_scaledewisol
audio_stg_scaledewisol
audio_rescaling_scaledewisol
audio_modality_scaledewisol
gradient_estimation_gammadewisol
use_restart_samplingdewisol
schedulerdewisol
accelerationdewisol
camera_loradewisol
camera_lora_scaledewisol
negative_promptdewisol
seeddewisol
enable_prompt_expansiondewisol
enable_safety_checkerdewisol
video_output_typedewisol
video_qualitydewisol
video_write_modedewisol
distill_lora_first_pass_scaledewisol
distill_lora_second_pass_scaledewisol
Allbwn
{
"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"
}
}
Meysydd yr allbwn
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}Fideo a gynhyrchwyd gan y model.
- seed
- integerGwerth had a ddefnyddir i gychwyn cynhyrchu rhifau ar hap.
- prompt
- stringAnogiad a ddefnyddir i arwain cynhyrchu.
Amrywiadau LTX 2.3 22b eraill
Mwy o fodelau: Testun i Fideo
Ar gyfer asiantau AI: mae'r dudalen hon fel Markdown ar gael yn https://doitong.com/cy/developers/models/ltx-2.3-22b/text-to-video.md. Pob model a chanllaw: https://doitong.com/developers/llms.txt