Interior AI
Generate stunning interior architectural designs with AI. Transform building images into photorealistic interior renderings.
Endpoint
HTTP Method
POST https://api.mnmlai.dev/v1/interiorRequest
Send a POST request with multipart/form-data containing your building image and design specifications.
Required Parameters
| Parameter | Type | Description |
|---|---|---|
image | File | The building interior image to redesign (multipart/form-data) |
prompt | String | Description of the desired interior design |
Optional Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
imageType | String | "3dmass" | Type of input image: "3dmass" | "sketch" | "photo" |
scenario | String | "creative" | Design approach: "creative" | "precise" |
geometry_input | Number | 75 | Geometry preservation level (0-100) |
styles | String | "realistic" | Rendering style: "realistic" | "artistic" |
renderspeed | String | "best" | Processing speed vs quality: "fast" | "best" |
Response
The Interior AI endpoint processes your building image asynchronously. You'll receive a request ID that you can use to check the status and retrieve the generated design.
Success Response (200 OK)
{
"status": "success",
"id": "b09ssvpzzhrj00cmzt1bykjzp1",
"prompt": "Modern interior design with glass facade"
}Examples
Basic Example
curl -X POST https://api.mnmlai.dev/v1/interior \
-H "Accept: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F "image=@/path/to/building.jpg" \
-F "prompt=Modern interior design with glass facade"Advanced Example with All Parameters
curl -X POST https://api.mnmlai.dev/v1/interior \
-H "Accept: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: multipart/form-data" \
-F "image=@/path/to/building.jpg" \
-F "prompt=Modern interior design with glass facade" \
-F "imageType=3dmass" \
-F "scenario=creative" \
-F "geometry_input=75" \
-F "styles=realistic" \
-F "renderspeed=best"Node.js Example
const FormData = require('form-data');
const fs = require('fs');
const axios = require('axios');
const form = new FormData();
form.append('image', fs.createReadStream('building.jpg'));
form.append('prompt', 'Modern interior design with glass facade');
form.append('imageType', '3dmass');
form.append('scenario', 'creative');
form.append('geometry_input', '75');
form.append('styles', 'realistic');
form.append('renderspeed', 'best');
const response = await axios.post(
'https://api.mnmlai.dev/v1/interior',
form,
{
headers: {
'Accept': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY',
...form.getHeaders()
}
}
);
console.log('Request ID:', response.data.id);Python Example
import requests
url = 'https://api.mnmlai.dev/v1/interior'
files = {
'image': open('building.jpg', 'rb')
}
data = {
'prompt': 'Modern interior design with glass facade',
'imageType': '3dmass',
'scenario': 'creative',
'geometry_input': '75',
'styles': 'realistic',
'renderspeed': 'best'
}
headers = {
'Accept': 'application/json',
'Authorization': 'Bearer YOUR_API_KEY'
}
response = requests.post(url, headers=headers, files=files, data=data)
result = response.json()
print(f"Request ID: {result['id']}")Processing Status
After submitting your request, use the Status Check endpoint with the returned ID to monitor processing progress:
Status Check Endpoint
GET https://api.mnmlai.dev/v1/status/{id}Error Handling
For detailed information on error responses, status codes, and best practices for handling errors, see our comprehensive API Errors documentation.
Interior AI Specific Errors
// 400 Bad Request - Missing required parameters
{
"error": "Missing required field: image"
}
// 413 Payload Too Large - File size exceeded
{
"error": "File size exceeds maximum limit of 10MB"
}