OpenAI's video generation model supporting text-to-video and image-to-video at 720p resolution with durations up to 20 seconds
Sora 2 API Async video generation
Integrate Sora 2 via Lumenfall’s OpenAI-compatible API to generate high-fidelity videos up to 20 seconds long with 720p resolution.
Base URL
https://api.lumenfall.ai/v1
Model
sora-2
Code Examples
Text to Video
/v1/videos/generations# Step 1: Submit video generation request
VIDEO_ID=$(curl -s -X POST \
https://api.lumenfall.ai/v1/videos \
-H "Authorization: Bearer $LUMENFALL_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "sora-2",
"prompt": "",
"size": "1024x1024"
}' | jq -r '.id')
echo "Video ID: $VIDEO_ID"
# Step 2: Poll for completion
while true; do
RESULT=$(curl -s \
https://api.lumenfall.ai/v1/videos/$VIDEO_ID \
-H "Authorization: Bearer $LUMENFALL_API_KEY")
STATUS=$(echo $RESULT | jq -r '.status')
echo "Status: $STATUS"
if [ "$STATUS" = "completed" ]; then
echo $RESULT | jq -r '.output.url'
break
elif [ "$STATUS" = "failed" ]; then
echo $RESULT | jq -r '.error.message'
break
fi
sleep 5
done
const BASE_URL = 'https://api.lumenfall.ai/v1';
const API_KEY = 'YOUR_API_KEY';
// Step 1: Submit video generation request
const submitRes = await fetch(`${BASE_URL}/videos`, {
method: 'POST',
headers: {
'Authorization': `Bearer ${API_KEY}`,
'Content-Type': 'application/json'
},
body: JSON.stringify({
model: 'sora-2',
prompt: '',
size: '1024x1024'
})
});
const { id: videoId } = await submitRes.json();
console.log('Video ID:', videoId);
// Step 2: Poll for completion
while (true) {
const pollRes = await fetch(`${BASE_URL}/videos/${videoId}`, {
headers: { 'Authorization': `Bearer ${API_KEY}` }
});
const result = await pollRes.json();
if (result.status === 'completed') {
console.log('Video URL:', result.output.url);
break;
} else if (result.status === 'failed') {
console.error('Error:', result.error.message);
break;
}
await new Promise(r => setTimeout(r, 5000));
}
import requests
import time
BASE_URL = "https://api.lumenfall.ai/v1"
API_KEY = "YOUR_API_KEY"
HEADERS = {
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
}
# Step 1: Submit video generation request
response = requests.post(
f"{BASE_URL}/videos",
headers=HEADERS,
json={
"model": "sora-2",
"prompt": "",
"size": "1024x1024"
}
)
video_id = response.json()["id"]
print(f"Video ID: {video_id}")
# Step 2: Poll for completion
while True:
result = requests.get(
f"{BASE_URL}/videos/{video_id}",
headers=HEADERS
).json()
if result["status"] == "completed":
print(f"Video URL: {result['output']['url']}")
break
elif result["status"] == "failed":
print(f"Error: {result['error']['message']}")
break
time.sleep(5)
Image to Video
/v1/videos/generationsParameter Normalization
How we handle parameters across different providers
Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:
| Behavior | What happens | Example |
|---|---|---|
passthrough |
Sent as-is to the provider | style, quality |
renamed |
Same value, mapped to the field name the provider expects | prompt |
converted |
Transformed to the provider's native format | size |
emulated |
Works even if the provider has no concept of it | n, response_format |
Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.