mnml.aiAPI

ArchDiffusion v4.2-lite

ArchDiffusion v4.2-lite is a lightweight, fast, and cost-effective AI rendering API for architectural visualization. It uses the Flux Klein model for quick image transformations with minimal parameters.

How it works: v4.2-lite takes your source image and prompt, processes it through the Flux Klein AI model, and returns a transformed architectural visualization. It's designed for speed and simplicity with minimal configuration.

v4.2-lite vs v4.2:

  • • Faster processing: Optimized for quick turnaround
  • • Lower cost: Only 1 credit per generation (vs 4 credits for v4.2)
  • • Simpler API: Fewer parameters to configure
  • • Expert types: Supports all 6 expert modes (exterior, interior, masterplan, landscape, plan, product)

Credit Cost: 1 credit per generation

Endpoint

HTTP Method
POST https://api.mnmlai.dev/v1/archDiffusion-v42-lite

Request

Send a POST request with multipart/form-data containing your source image and design parameters. The API processes images asynchronously, returning a request ID for status tracking.

Parameters

ParameterTypeDefaultDescription
imageRequiredFile-Source architectural image (JPEG, PNG, WebP). Max 15MB, min 1KB
promptRequiredString-Description of desired transformation (max 2000 characters)
expert_nameString"exterior"Expert mode: "exterior", "interior", "masterplan", "landscape", "plan", "product"
output_formatString"png"Output image format: "png", "jpeg", "webp"

Expert Types

exterior: Building exteriors
interior: Interior spaces
masterplan: Site plans & urban
landscape: Outdoor landscapes
plan: Floor plans
product: Product renders

Response

The API processes your request asynchronously and immediately returns a response containing a unique request ID. Use this ID with the Status Check endpoint to monitor processing progress and retrieve the final generated image.

Success Response (200 OK)

{
  "status": "success",
  "id": "vysqf2nr0drmc0ctqx5tkdse48",
  "prompt": "Modern building with glass facade",
  "expert_name": "exterior",
  "parameters": {
    "outputFormat": "png"
  },
  "credits": 99
}

Code Examples

1. Basic Exterior Rendering (cURL)

curl -X POST https://api.mnmlai.dev/v1/archDiffusion-v42-lite \
  -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 commercial building with glass facade" \
  -F "expert_name=exterior"

2. Interior Rendering

curl -X POST https://api.mnmlai.dev/v1/archDiffusion-v42-lite \
  -H "Accept: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: multipart/form-data" \
  -F "image=@/path/to/room.jpg" \
  -F "prompt=Luxury modern living room with natural lighting" \
  -F "expert_name=interior" \
  -F "output_format=jpeg"

3. Node.js Implementation

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 residential building with landscaping');
form.append('expert_name', 'exterior');
form.append('output_format', 'png');

const response = await axios.post(
  'https://api.mnmlai.dev/v1/archDiffusion-v42-lite',
  form,
  {
    headers: {
      'Accept': 'application/json',
      'Authorization': 'Bearer YOUR_API_KEY',
      ...form.getHeaders()
    }
  }
);

console.log('Request ID:', response.data.id);
console.log('Remaining credits:', response.data.credits);

4. Python Implementation

import requests

url = 'https://api.mnmlai.dev/v1/archDiffusion-v42-lite'

files = {
    'image': open('building.jpg', 'rb')
}

data = {
    'prompt': 'Modern office building with green terrace',
    'expert_name': 'exterior',
    'output_format': 'png'
}

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']}")
print(f"Remaining credits: {result['credits']}")

Checking Processing Status

Status Check Endpoint
GET https://api.mnmlai.dev/v1/status/{id}

Processing Time: Typically 15-30 seconds (faster than v4.2). Poll the status endpoint every 3-5 seconds until the status becomes "succeeded" or "failed".

Best Practices

Image Guidelines

  • Use high-quality source images (1024px or larger recommended)
  • Supported formats: JPEG, PNG, WebP
  • File size: 1KB - 15MB per image
  • Images are automatically resized to 1344px width

When to Use v4.2-lite vs v4.2

  • Use v4.2-lite: Quick iterations, prototyping, budget-conscious projects, simpler transformations
  • Use v4.2: Final presentations, detailed control over environmental parameters, reference images, complex styling

Prompt Tips

  • Be descriptive about materials, lighting, and atmosphere in your prompt
  • Include style references (e.g., "modern minimalist", "industrial loft")
  • Specify time of day or weather conditions in the prompt for desired effects

Error Handling

Common Error Responses

// 400 Bad Request - Missing image
{
  "status": "error",
  "code": "MISSING_IMAGE",
  "message": "Image file is required"
}

// 400 Bad Request - Missing prompt
{
  "status": "error",
  "code": "MISSING_PROMPT",
  "message": "Prompt is required"
}

// 400 Bad Request - Insufficient credits
{
  "status": "error",
  "code": "NO_CREDITS",
  "message": "You do not have enough credits to use this feature. This API requires 1 credit.",
  "details": { "credits": 0, "required": 1 }
}

// 400 Bad Request - Image too large
{
  "status": "error",
  "code": "IMAGE_TOO_LARGE",
  "message": "Image file is too large",
  "details": { "size": 20000000, "maxSize": 15728640 }
}

Next Steps

ArchDiffusion v4.2 (Full)ArchDiffusion v4.1Status Check