
Text to Image
Create AI images from text prompts
Prompt-driven video editing via Alibaba Wan 2.7 API with multi-image reference support. Stable for high-concurrency tasks at an affordable rate. Built for free testing and stable API workflows.
// Step 1: Submit generation request
const response = await fetch('https://api.flaq.ai/api/v1/video/task', {
method: 'POST',
headers: {
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
body: JSON.stringify({
model_name: 'wan-2.7-video-edit',
prompt: 'Replace the sky with warm sunset colors, keep subjects natural',
negative_prompt: 'artifacts, flicker',
seed: 42,
video_url: 'https://example.com/source-video.mp4',
images: [
'https://example.com/ref-a.jpg',
'https://example.com/ref-b.jpg'
],
audio_setting: 'auto'
})
});
const { data } = await response.json();
const taskId = data.task_id;
// Step 2: Poll for results
const taskId = data.task_id;
const pollResult = async (taskId) => {
const res = await fetch(`https://api.flaq.ai/api/v1/video/${taskId}`, {
headers: { 'Authorization': 'Bearer YOUR_API_KEY' }
});
return res.json();
};
while (true) {
const pollResultData = await pollResult(taskId);
const status = pollResultData.data.task_status;
if (status === 'succeed') {
console.log(pollResultData.data.task_result.videos[0].url);
break;
}
if (status === 'failed') {
console.error(pollResultData.data.task_status_msg);
break;
}
await new Promise(resolve => setTimeout(resolve, 10000));
}
import requests
response = requests.post(
'https://api.flaq.ai/api/v1/video/task',
headers={
'Content-Type': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
},
json={
'model_name': 'wan-2.7-video-edit',
'prompt': 'Replace the sky with warm sunset colors, keep subjects natural',
'negative_prompt': 'artifacts, flicker',
'seed': 42,
'video_url': 'https://example.com/source-video.mp4',
'images': [
'https://example.com/ref-a.jpg',
'https://example.com/ref-b.jpg',
],
'audio_setting': 'auto',
}
)
result = response.json()
task_id = result['data']['task_id']
# Step 2: Poll for results
task_id = response.json()['data']['task_id']
poll_url = f"https://api.flaq.ai/api/v1/video/{task_id}"
while True:
poll_result = requests.get(poll_url, headers={'Authorization': 'Bearer YOUR_API_KEY'}).json()
status = poll_result['data']['task_status']
if status == 'succeed':
print(poll_result['data']['task_result']['videos'][0]['url'])
break
if status == 'failed':
print(poll_result['data']['task_status_msg'])
break
time.sleep(10)
curl -X POST https://api.flaq.ai/api/v1/video/task \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model_name": "wan-2.7-video-edit",
"prompt": "Replace the sky with warm sunset colors, keep subjects natural",
"negative_prompt": "artifacts, flicker",
"seed": 42,
"video_url": "https://example.com/source-video.mp4",
"images": [
"https://example.com/ref-a.jpg",
"https://example.com/ref-b.jpg"
],
"audio_setting": "auto"
}'
# Step 2: Poll for results
# Replace {task_id} with the task_id returned from the submit response
curl -X GET "https://api.flaq.ai/api/v1/video/{task_id}" \
-H "Authorization: Bearer YOUR_API_KEY"
| Parameters | Price | Original Price | Discount |
|---|
Alibaba Wan 2.7 Video Edit API delivers production-grade AI video editing for developers and creative teams. This advanced video editing API integration enables you to make local or global edits to existing videos using natural language text prompts, at 720p and 1080p resolutions across 2–10 second durations. Built on Alibaba's 14B-parameter Wan 2.7 architecture with more than 5x faster inference than previous versions, the Wan 2.7 model combines precise text-guided editing with optional audio preservation, while the API provides stable integration for professional video post-production workflows on Flaq AI.
Note Please ensure your input videos and editing prompts comply with platform content guidelines. If an error occurs, review your content for restricted material, adjust it, and try again.
Wan 2.7 Video Edit vs. Wan 2.7 Text-to-Video Wan 2.7 Text-to-Video generates new videos from text descriptions. Wan 2.7 Video Edit API works with existing video content, enabling precise local and global modifications through text prompts—making it the preferred choice for post-production workflows, content refinement, and iterative video editing without full regeneration.
Wan 2.7 Video Edit vs. Runway Gen-3 Inpainting Runway Gen-3 Inpainting offers region-based video editing with creative controls. Wan 2.7 Video Edit API distinguishes itself with 14B-parameter architecture, both local and global editing capabilities, optional audio preservation, 1080p output, and more than 5x faster inference—delivering more comprehensive text-guided video editing for professional workflows.
Wan 2.7 Video Edit vs. Pika Effects Pika Effects provides stylized video transformations with a user-friendly interface. Wan 2.7 Video Edit API offers programmatic access, both local and global editing through natural language, optional audio preservation, and 1080p resolution—making it superior for developers requiring scalable, precise video editing.
Wan 2.7 Video Edit vs. Kling Video Editing Kling offers video editing with strong human motion preservation. Wan 2.7 Video Edit API counters with broader editing scope (local and global), optional audio preservation, 1080p output, flexible aspect ratio support (5 formats), and Alibaba's advanced spatiotemporal modeling—making it versatile for diverse editing scenarios.
Wan 2.7 Video Edit vs. Seedance V2.0 Text-to-Video Seedance V2.0 generates new videos from text prompts, while Wan 2.7 Video Edit API focuses on modifying existing video content through text-guided edits—preserving original footage while applying targeted or global changes, making it the right choice when working with existing video assets rather than generating from scratch.
Explore several AI creation tools for quick image and video workflows in your browser, then scale successful ideas with Flaq AI's production-ready model APIs. Flaq AI provides a unified API layer for all models, making it easy to use and scale your workflows.

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