Lumoz Vision
Multimodal scene inspection, visual Q&A, OCR, and diffusion prompt reverse-engineering.
Parameters
Configure parameters and run inference.
Ready for Execution
Configure parameters on the left and click Run Microservice to generate output.
Processing Microservice...
Spawning browser worker & capturing full render...
{}
Execution Failed
Failed to connect to worker.
Invoke this microservice programmatically from your backend application. Authenticate by passing your Lumoz API key in the Authorization: Bearer YOUR_API_KEY header.
curl -X POST https://lumozai.com/api/v1/services/run \
-H "Authorization: Bearer YOUR_LUMOZ_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"service_id": "lumoz-vision",
"url": "https://lumozai.com",
"w": 1920,
"h": 1080
}'
import requests
url = "https://lumozai.com/api/v1/services/run"
headers = {
"Authorization": "Bearer YOUR_LUMOZ_API_KEY",
"Content-Type": "application/json"
}
payload = {
"service_id": "lumoz-vision",
"url": "https://lumozai.com",
"w": 1920,
"h": 1080
}
response = requests.post(url, json=payload, headers=headers)
data = response.json()
print("Output:", data.get("output"))
print("Execution time:", data.get("execution_time"))
const response = await fetch("https://lumozai.com/api/v1/services/run", {
method: "POST",
headers: {
"Authorization": "Bearer YOUR_LUMOZ_API_KEY",
"Content-Type": "application/json"
},
body: JSON.stringify({
service_id: "lumoz-vision",
url: "https://lumozai.com",
w: 1920,
h: 1080
})
});
const data = await response.json();
console.log("Output URL:", data.output);
Parameters Schema
| Field | Type | Required | Default | Description |
|---|---|---|---|---|
media |
string | Yes | - |
Public image or video URL |
prompt |
string | No | - |
Visual query or analysis instructions |
max_new_tokens |
integer | No | 512 |
- |