LTX 2.5 Pro Image to Video
इंटीग्रेट करें
lightricks/ltx-2.5/image-to-video/pro
# 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/lightricks/ltx-2.5/image-to-video/pro?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": false
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/lightricks/ltx-2.5/image-to-video/pro?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": false
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": False,
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/lightricks/ltx-2.5/image-to-video/pro", 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/hi/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": "lightricks/ltx-2.5/image-to-video/pro",
"input": {
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": false
}
}
LTX 2.5 Pro Image to Video मॉडल (lightricks/ltx-2.5/image-to-video/pro) को Doitong API के ज़रिए कॉल करें। एजेंट के लिए दस्तावेज़: https://doitong.com/hi/developers/models/lightricks/ltx-2.5/image-to-video/pro.md
POST https://api.doitong.ru/v1/run/lightricks/ltx-2.5/image-to-video/pro?wait=20
Authorization: Bearer $DOITONG_API_KEY
Content-Type: application/json
{
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": false
}
यदि रिस्पॉन्स स्टेटस "queued" या "running" है, तो GET https://api.doitong.ru/v1/requests/REQUEST_ID?wait=20 को तब तक पोल करें जब तक यह "succeeded" न हो जाए; फ़ाइलें outputs[].url में हैं। उसी बॉडी के साथ POST https://api.doitong.ru/v1/quote/lightricks/ltx-2.5/image-to-video/pro चलाने से रन से पहले सटीक कीमत मिलती है।
यह अनुरोध: $0.72 720 API क्रेडिट · ≈ ₽77.46 इसे इस पेज पर चलाएँ
आपकी नई API कुंजी। यह केवल अभी दिखाया गया है और कोड तथा नीचे दिए गए API कुंजी फ़ील्ड में पहले से मौजूद है। इसे गुप्त रखें: इसे कभी भी ब्राउज़र में चलने वाले कोड में न डालें।
उदाहरण
अनुरोध बनाएँ
कंट्रोल मॉडल स्कीमा से जनरेट होते हैं। इन्हें बदलने पर कोड और कीमत अपडेट होती है।
/run/lightricks/ltx-2.5/image-to-video/pro?wait=20
कोटेशन → $0.72
# 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/lightricks/ltx-2.5/image-to-video/pro?wait=20" \
-H "Authorization: Bearer $DOITONG_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": false
}'
# 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 $DOITONG_API_KEY"
const API = "https://api.doitong.ru/v1";
const headers = {
"Authorization": "Bearer " + process.env.DOITONG_API_KEY,
"Content-Type": "application/json",
};
// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/lightricks/ltx-2.5/image-to-video/pro?wait=20", {
method: "POST",
headers,
body: JSON.stringify({
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": false
}),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);
// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
import os
import requests
API = "https://api.doitong.ru/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}
payload = {
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": False,
}
# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/lightricks/ltx-2.5/image-to-video/pro", 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": "lightricks/ltx-2.5/image-to-video/pro",
"input": {
"image": "https://content.doitong.com/dev-api/2026/10/21/req_m47cpdni6njc4mezryvt9kg2/0-fUu2PV5voQYZjKUW9sc_1_qYL5cs4B.png",
"prompt": "The camera glides forward and slowly tilts up toward the peaks, icebergs drift gently, clouds move across the sky and the morning light grows brighter.",
"duration": 6,
"resolution": "720p",
"generate_audio": false
},
"wait_seconds": 20
}
}
}
यह अनुरोध चलाएँ
आपकी key इसी ब्राउज़र में रहती है: इसे केवल Doitong API को भेजा जाता है और केवल तभी (localStorage) में सेव किया जाता है जब आप Remember चुनते हैं। API कुंजी प्राप्त करें
LTX 2.5 Pro Image to Video के बारे में
LTX 2.5 Pro इमेज-टू-वीडियो आपके प्रथम फ़्रेम को एनिमेट करता है, अंतिम फ़्रेम पर समाप्त हो सकता है, जनरेट किया गया ऑडियो जोड़ता है और नामित कैमरा मूव (dolly, jib, static या focus shift) स्वीकार करता है। 6, 8 या 10 सेकंड या स्वचालित लंबाई, 720p या 1080p, 24, 25 या 50 fps।
पैरामीटर
कैनोनिकल नाम या नेटिव नाम में से कोई एक भेजें, दोनों नहीं। कैनोनिकल नाम
image_urlआवश्यक
image
end_image_urlवैकल्पिक
end_image
promptआवश्यक
durationवैकल्पिक
resolutionवैकल्पिक
aspect_ratioवैकल्पिक
fpsवैकल्पिक
generate_audioवैकल्पिक
camera_motionवैकल्पिक
फ़ाइल पैरामीटर में सार्वजनिक https:// URL, 10 MB तक का data: URI, या अपलोड का file_url लिया जाता है। फ़ाइलें
आउटपुट
{
"id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
"object": "request",
"model": "lightricks/ltx-2.5/image-to-video/pro",
"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": 720,
"usd": "0.72",
"charged": 720,
"refunded": 0
},
"input": {
"prompt": "Fireflies swirl around the fox as it slows down and looks back over its shoulder",
"image": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
"duration": 6,
"resolution": "720p",
"camera_motion": "static"
},
"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
}
},
"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"
}
}
आउटपुट के फ़ील्ड
- video
- object {url, content_type, file_name, file_size, width, height, fps, duration, num_frames}परिणामी वीडियो फ़ाइल।
अन्य LTX 2.5 वेरिएंट
और मॉडल: इमेज से वीडियो
AI एजेंट के लिए: इस पेज का Markdown यहाँ है https://doitong.com/hi/developers/models/lightricks/ltx-2.5/image-to-video/pro.md. सभी मॉडल और गाइड: https://doitong.com/developers/llms.txt