Video ExtendAlibaba

ai/wan-2.2-spicy/video-extend-lora

alibaba/wan-2.2-spicy/video-extend-lora

alibaba/wan-2.2-spicy/video-extend-lora. 이미지, 동영상, 얼굴 바꾸기 모델 API를 살펴보세요. 모델을 시험한 뒤 하나의 통합 REST API로 연결할 수 있습니다.

관련 모델

ai/wan-2.2-spicy/video-extend-lora 관련 모델 1

전체 매개변수, 출력 스키마 및 실시간 요금

AI 모델 API 마켓하나의 플랫폼, 모든 기능가장 인기이용약관이미지, 동영상, 얼굴 바꾸기 모델 API를 살펴보세요. 모델을 시험한 뒤 하나의 통합 REST API로 연결할 수 있습니다.
prompt *Prompttextarea—≤ 5000 chars
video *Videovideo_upload—video/*
resolutionResolutionselect480p480p | 720p
durationDurationselect55 | 8
lorasLorasarray<object>—0–3 items
↳path *Pathtext—≤ 500 chars
↳scaleScaleslider10 ~ 4 · step 0.1
high_noise_lorasHigh Noise Lorasarray<object>—0–3 items
↳path *Pathtext—≤ 500 chars
↳scaleScaleslider10 ~ 4 · step 0.1
low_noise_lorasLow Noise Lorasarray<object>—0–3 items
↳path *Pathtext—≤ 500 chars
↳scaleScaleslider10 ~ 4 · step 0.1
seedSeednumber——

전체 매개변수, 출력 스키마 및 실시간 요금

자세히 보기하나의 플랫폼, 모든 기능이미지, 동영상, 얼굴 바꾸기 모델 API를 살펴보세요. 모델을 시험한 뒤 하나의 통합 REST API로 연결할 수 있습니다.
videosarray<string>

API

이미지, 동영상, 얼굴 바꾸기 모델 API를 살펴보세요. 모델을 시험한 뒤 하나의 통합 REST API로 연결할 수 있습니다.

cURL
# 1) Submit — returns { "task_uuid": "..." }
curl -X POST "https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.2-spicy/video-extend-lora" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "input": {
    "prompt": "Continue the camera movement and subject action naturally while preserving the original visual style, lighting, and scene continuity.",
    "video": "https://assets-public.namifusion.com/marketplace/videos/2026-04-14/88d6efad3763.mp4",
    "resolution": "480p",
    "duration": 5
  }
}'

# 2) Poll until status is "completed", then read the output URLs
curl "https://www.namifusion.com/api/v1/marketplace/run/tasks/TASK_UUID" \
  -H "Authorization: Bearer YOUR_API_KEY"
Python
import time, requests

API_KEY = "YOUR_API_KEY"
HEADERS = {"Authorization": f"Bearer {API_KEY}"}

# 1) Submit
resp = requests.post(
    "https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.2-spicy/video-extend-lora",
    headers=HEADERS,
    json={
        "input": {
            "prompt": "Continue the camera movement and subject action naturally while preserving the original visual style, lighting, and scene continuity.",
            "video": "https://assets-public.namifusion.com/marketplace/videos/2026-04-14/88d6efad3763.mp4",
            "resolution": "480p",
            "duration": 5
        }
    },
)
resp.raise_for_status()  # 401/402/429/5xx stop here instead of polling a bad task
task = resp.json()

# 2) Poll until a terminal state (completed / failed / cancelled).
#    This model is allowed up to 300s server-side.
deadline = time.time() + 360
while task.get("status") not in ("completed", "failed", "cancelled"):
    if time.time() > deadline:
        raise TimeoutError(f"still {task.get('status')} — keep the task_uuid and poll later")
    time.sleep(3)
    poll = requests.get(f"https://www.namifusion.com/api/v1/marketplace/run/tasks/{task['task_uuid']}", headers=HEADERS)
    poll.raise_for_status()
    task = poll.json()

print(task["status"], task.get("output"))
JavaScript
const API_KEY = "YOUR_API_KEY";
const HEADERS = { Authorization: `Bearer ${API_KEY}` };

// 1) Submit
const resp = await fetch("https://www.namifusion.com/api/v1/marketplace/run/alibaba/wan-2.2-spicy/video-extend-lora", {
  method: "POST",
  headers: { ...HEADERS, "Content-Type": "application/json" },
  body: JSON.stringify({
    "input": {
      "prompt": "Continue the camera movement and subject action naturally while preserving the original visual style, lighting, and scene continuity.",
      "video": "https://assets-public.namifusion.com/marketplace/videos/2026-04-14/88d6efad3763.mp4",
      "resolution": "480p",
      "duration": 5
    }
  }),
});
if (!resp.ok) throw new Error(`submit failed: ${resp.status} ${await resp.text()}`);
let task = await resp.json();

// 2) Poll until a terminal state (completed / failed / cancelled).
//    This model is allowed up to 300s server-side.
const deadline = Date.now() + 360 * 1000;
while (!["completed", "failed", "cancelled"].includes(task.status)) {
  if (Date.now() > deadline) throw new Error(`still ${task.status} — keep the task_uuid and poll later`);
  await new Promise((r) => setTimeout(r, 3000));
  const poll = await fetch(`https://www.namifusion.com/api/v1/marketplace/run/tasks/${task.task_uuid}`, { headers: HEADERS });
  if (!poll.ok) throw new Error(`poll failed: ${poll.status}`);
  task = await poll.json();
}

console.log(task.status, task.output);

API 문서

ai/wan-2.2-spicy/video-extend-lora

Extend short clips into longer, smoother videos with flexible LoRA-based style control.

ai/wan-2.2-spicy/video-extend-lora is an image-to-video model designed for video continuation and clip extension workflows. It helps turn existing footage into longer sequences with smoother motion, while supporting custom LoRA weights for more precise control over style, character consistency, and visual details. With no cold starts and cost-efficient inference, it is well suited for production-oriented creative pipelines.

🚀 Key Features

  • Video extension workflow: Continue from an input video to generate longer sequences that feel more complete and narrative-ready.
  • Smooth animation: Optimized for temporal continuity and motion coherence to produce more natural-looking extended clips.
  • Custom LoRA support: Apply up to 3 LoRAs, including separate high-noise and low-noise LoRA configurations, for flexible visual control.
  • No cold start: Delivers more predictable responsiveness for real-time or high-throughput production use cases.
  • Flexible output options: Supports 480p and 720p output, with 5-second and 8-second durations for balancing quality, speed, and cost.
  • Reproducible generation: Seed control makes it easier to test variations, compare outputs, and maintain consistency across runs.

🛠️ Technical Specifications

ItemDetails
Model architectureVideo extension / continuation model with LoRA support
Task typeImage-to-video
InputPrompt, input video, LoRA configurations
Output FormatVideo
Resolution480p, 720p
Duration5s, 8s
FpsNot publicly specified
LoRA supportUp to 3 LoRAs; up to 3 high-noise LoRAs; up to 3 low-noise LoRAs
SeedSupported; -1 uses a random seed
LatencyOptimized for fast inference with no cold starts
Best suited forClip extension, stylized continuation, character-consistent video generation

Sample prompts:

  • Continue the scene with the character walking forward through a neon-lit city street, smooth camera motion, cinematic lighting
  • Preserve the subject's appearance from the source video and extend with a natural turn, realistic cloth motion, and coherent body movement
  • Extend the existing product clip into a polished commercial-style video, slow push-in camera motion, clean background, premium advertising look

💰 Pricing

ItemPrice
Base Price$0.2

💡 Best Use Cases

  • Short-form content extension: Expand existing clips into longer social videos, teasers, or narrative sequences.
  • E-commerce and advertising: Turn product footage into richer promotional videos without reshooting new material.
  • Style and character consistency: Use LoRAs to maintain a consistent visual identity across extended scenes.
  • Previsualization and concept development: Quickly extend shots for storyboard animation, pacing tests, and creative validation.

🔗 Related Models

  • WAN 2.2 Spicy series: A strong fit for users prioritizing motion quality, clip continuation, and customizable LoRA-driven control.
  • video-extend-lora variants: Particularly useful for workflows centered on extending footage while preserving style and subject continuity.