LTX-2.3 22B · Extend Video · LoRA
整合
模型 id
ltx-2.3-22b/extend-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/extend-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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3-22b/extend-video/lora?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/extend-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/zh-TW/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/extend-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"
}
]
}
}
透過 Doitong API 呼叫 LTX-2.3 22B · Extend Video · LoRA 模型(ltx-2.3-22b/extend-video/lora)。代理程式文件:https://doitong.com/zh-TW/developers/models/ltx-2.3-22b/extend-video/lora.md
POST https://api.doitong.ru/v1/run/ltx-2.3-22b/extend-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"
}
]
}
如果回應狀態為 "queued" 或 "running",請輪詢 GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20,直到狀態變為 "succeeded";檔案位於 outputs[].url。使用相同主體傳送 POST https://api.doitong.ru/v1/quote/ltx-2.3-22b/extend-video/lora,可在執行前取得確切價格。
像範例一樣的檔案: $0.203 203 API 點數 · ≈ ₽21.78 您的檔案會在執行前計量 在此頁面執行
您的新 API 金鑰。 僅會在此時顯示,且已填入下方的程式碼與 API 金鑰欄位。請妥善保密:切勿將其放入在瀏覽器中執行的程式碼。
建立請求
控制項是根據模型結構描述生成的。變更設定時,程式碼和價格會同步更新。
POST
/run/ltx-2.3-22b/extend-video/lora?wait=20
報價 → $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/extend-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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/ltx-2.3-22b/extend-video/lora?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
"video": "https://content.doitong.com/video/showcase/v3/gen_fox_cartoon.mp4",
"loras": [
{
"path": "https://example.com/your-file.safetensors"
}
]
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + 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/extend-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/extend-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
}
}
}
關於 LTX-2.3 22B · Extend Video · LoRA
根據 `prompt` 延續 `video_url` 中的片段,並需要 `loras` 清單以套用自訂 LoRA。`num_frames` 範圍為 9 到 481,`end_image_url` 可定義最後一幀,`match_input_fps` 會保留來源影格率。支援音訊生成、攝影機 LoRA 和多種取樣設定。
參數
請傳送標準名稱或原生名稱其中之一,不要同時傳送兩者。 標準名稱
名稱類型
預設值允許值
說明
prompt必填
類型string
作為影片生成基礎的提示詞。
video_url必填
video
類型url · video
指向要延長之影片的 URL。
end_image_url選填
end_image
類型url · image
透過 URL 提供結束影格圖像,以定義延長影片的結尾。
num_frames選填
類型integer
預設值121
9 – 481
生成輸出的影格數。
video_size選填
類型object
預設值auto
autosquare_hdsquareportrait_4_3portrait_16_9landscape_4_3landscape_16_9
生成影片的尺寸。
generate_audio選填
類型boolean
預設值true
控制影片是否包含生成的音訊。
use_multiscale選填
類型boolean
預設值true
用於改善一致性與細節的多尺度生成切換。設為 True 時,較小的初步影片會引導第二次生成,其尺寸會達到或超過要求的尺寸。
match_input_fps選填
類型boolean
預設值true
輸出影格率覆寫;啟用時以來源影片的 FPS 取代預設目標 FPS。
fps選填
類型number
預設值24
1 – 60
輸出影片影格率,以每秒影格數表示。
num_inference_steps選填
類型integer
預設值40
8 – 50
執行的推論步驟數。
video_cfg_scale選填
類型number
預設值3
1 – 20
影片引導設定:提高此值可讓生成內容更一致、更聚焦。使用無分類器引導(CFG)。
video_stg_scale選填
類型number
預設值0
0 – 20
透過時空引導(STG)尺度控制影片的一致性與焦點;提高設定值可增強兩者。
video_rescaling_scale選填
類型number
預設值0.7
0 – 1
影片重新縮放調整,以比例平衡無分類器引導與時空引導。
video_modality_scale選填
類型number
預設值3
0 – 10
影片模態調整,以比例平衡影片與音訊的貢獻。
audio_cfg_scale選填
類型number
預設值7
1 – 20
音訊引導設定:提高此值可讓生成內容更一致、更聚焦。使用無分類器引導(CFG)。
audio_stg_scale選填
類型number
預設值0
0 – 20
透過時空引導(STG)尺度控制音訊的一致性與焦點;提高設定值可增強兩者。
audio_rescaling_scale選填
類型number
預設值0.7
0 – 1
音訊重新縮放調整,以比例平衡無分類器引導與時空引導。
audio_modality_scale選填
類型number
預設值3
0 – 10
音訊模態調整,以比例平衡影片與音訊的貢獻。
gradient_estimation_gamma選填
類型number
預設值2
0 – 10
去噪梯度估算設定:0 會關閉估算;其他值指定 gamma。
use_restart_sampling選填
類型boolean
預設值false
重新開始採樣切換,可提升影片品質:啟用後會在每個去噪步驟加入少量雜訊。
scheduler選填
類型enum
預設值ltx2
ltx2linear_quadraticbeta
排程器選擇。
acceleration選填
類型enum
預設值regular
noneregularhighfull
套用至處理的加速等級。
camera_lora選填
類型enum
預設值none
dolly_indolly_outdolly_leftdolly_rightjib_upjib_downstaticnone
攝影機 LoRA 選擇,比單獨使用攝影機動作提示詞更精確地控制生成影片中的移動。
camera_lora_scale選填
類型number
預設值1
0 – 1
攝影機 LoRA 強度,比單獨使用攝影機動作提示詞更精確地控制生成影片中的移動。
negative_prompt選填
類型string
預設值news broadcast, 3d animation, computer graphics, pc game, console game, video game, cartoon, childish, watermark, logo, text, on screen text, subtitles, titles, signature, slowmo, static
影片生成期間使用的負面提示詞。
seed選填
類型integer | null
初始化亂數生成的種子值。
enable_prompt_expansion選填
類型boolean
預設值true
控制是否啟用提示詞擴展。
enable_safety_checker選填
類型boolean
預設值true
控制是否啟用安全性檢查。
video_output_type選填
類型enum
預設值X264 (.mp4)
X264 (.mp4)VP9 (.webm)PRORES4444 (.mov)GIF (.gif)
結果影片的輸出類型。
video_quality選填
類型enum
預設值high
lowmediumhighmaximum
結果影片的品質等級。
video_write_mode選填
類型enum
預設值balanced
fastbalancedsmall
結果影片的寫入模式。
loras必填
類型object[]
生成用的 LoRA 選擇。
loras[].path必填
類型string
LoRA 權重位置,以 URL 或 owner/repo 格式的 HuggingFace 儲存庫 ID 提供。
loras[].weight_name選填
類型string | null
用於在 HuggingFace 儲存庫的多個權重中選取權重的 LoRA 權重名稱;只有包含多個權重的儲存庫需要此項。除非 `path` 指向 HuggingFace 儲存庫,否則此設定不會生效。
loras[].scale選填
類型number
預設值1
0 – 4
套用於 LoRA 的縮放係數,範圍為 0.0 至 4.0。
distill_lora_first_pass_scale選填
類型number
預設值0.2
0 – 1
控制第一輪蒸餾 LoRA 縮放,設為 0 可關閉。
distill_lora_second_pass_scale選填
類型number
預設值0.5
0 – 1
控制第一輪之後每一輪的蒸餾 LoRA 縮放。
extend_direction選填
類型enum
預設值forward
forwardbackward
要延長的影片側:選擇 'backward' 在開頭前加入內容,或選擇 'forward' 在結尾後加入內容。
num_context_frames選填
類型integer
預設值25
0 – 121
延長影片時用於提供上下文的影格數。
video_strength選填
類型number
預設值1
0 – 1
此條件強度控制修改影片內容的自由度:設定值越小,模型可調整的空間越大。
audio_strength選填
類型number
預設值1
0 – 1
此條件強度控制修改音訊內容的自由度:設定值越小,模型可調整的空間越大。
end_image_strength選填
類型number
預設值1
0 – 1
控制結束圖像對生成影片的影響程度。
必填
標準名稱,也可使用
檔案參數接受公開的 https:// URL、最大 10 MB 的 data: URI,或上傳檔案的 file_url。 檔案
輸出
GET /requests/req_8k2m4q7x1z9c3v5b6n0p2r4t
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "ltx-2.3-22b/extend-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",
"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": "A woman stands still amid a busy neon-lit street at night. The camera slowly dollies in toward her face as people blur past, their motion emphasizing her calm presence. City lights flicker and reflections shift across her denim jacket."
},
"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"
}
}
您的檔案,由您選擇每個 outputs[].url 都是儲存空間中的副本:可永久保留(按 GB-月計費),或免費保留 7 天;可透過帳戶設定或 ?storage= 設定。
所有模型使用相同結構圖片、影片和音訊皆包含 type、url、content_type、width、height 和 duration。output 是模型自己的結果物件。
輸出欄位
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}模型產生的影片。
- seed
- integer用於初始化亂數生成的種子值。
- prompt
- string用於引導生成的提示詞。
其他 LTX 2.3 22b 變體
更多模型:影片轉影片
給 AI 代理程式:此頁面的 Markdown 位於 https://doitong.com/zh-TW/developers/models/ltx-2.3-22b/extend-video/lora.md. 所有模型與指南: https://doitong.com/developers/llms.txt