Name: AI Interior Design – Generate Room Renders | $0.05/call | API.market
Brand: magicapi
SKU: api-magicapi-realistic-interior-design-generator
Availability: InStock
Author: API Market

Shashank Agarwal

# 🏠 Realistic Interior Design Generator API (adirik/interior-design)

## Overview
The Realistic Interior Design Generator API allows you to transform an existing room photo or blank canvas into a photo-realistic interior design based on a descriptive text prompt. By providing both an input image and a text description, you can generate highly detailed and visually appealing interior renderings—perfect for architects, interior designers, real estate professionals, or anyone needing rapid design inspiration.

This API processes requests asynchronously, meaning you first create a prediction, then poll for its status until the design is complete. The resulting image can reflect the exact style, furniture, and decorative elements you specify in your prompt.

![Example original bedroom photo](https://blog.api.market/wp-content/uploads/2026/04/realistic-interior.jpg)

## Features
- Transforms existing room images into stylish, photorealistic designs.
- Leverages advanced text-to-image prompting for total creative freedom.
- Customizable parameters for controlling prompt strength, guidance scale, seed, and more.
- Supports high-resolution outputs for professional applications.
- Async prediction flow for efficient job handling.

## Use Cases
1. Home Renovation Planning: Visualize how a current space would look with new color schemes, furniture, or decorative themes.  
2. Real Estate Staging: Generate staged interior images without the need for physical furnishings.  
3. Interior Design Proposals: Quickly experiment with different design concepts to present to clients.  
4. Content Creation: Produce unique interiors for marketing materials or creative storytelling.  
5. Inspiration Boards: Rapidly prototype ideas for personal or professional design boards.

## Visual Examples
Below are sample images showcasing how the API transforms an input room photo into a new design based on your text prompt.

### Input Image
![Input room photo for transformation](https://blog.api.market/wp-content/uploads/2026/04/realistic-interior.jpg)

### Output Image
![Resulting interior design](https://blog.api.market/wp-content/uploads/2026/04/output-realistic-interior.png)

In the above example:  
• The text prompt describes a bohemian bedroom with a canopy bed, macramé wall hanging, eclectic dresser, and potted plants.  
• The resulting image reflects these design elements with a visually realistic style.

## Pricing
• Each processed image costs 1 API unit.  
• GET requests to check prediction status (GET /api/v1/magicapi/realistic-interior-design-generator/predictions/{id}) are free and do not count against your usage.  
• Various pricing tiers are available depending on usage volume.

## API Documentation

### Base URL
All requests to this API should use the following base URL:
```
https://prod.api.market/api/v1/magicapi/realistic-interior-design-generator
```

Make sure to append the specific endpoint path to this base URL as documented below.

### Authentication
Include your API key in every request using the custom header:
```
x-magicapi-key: YOUR_API_MARKET_KEY
```
Replace YOUR_API_MARKET_KEY with your actual API credential.

### Asynchronous Processing
This API performs inference asynchronously. The general workflow is:

1. Send a POST request to /predictions to create a new prediction.  
2. Receive a prediction ID in the response.  
3. Poll GET /predictions/{id} using the prediction ID to check the current status.  
4. Continue polling until the status is "succeeded" or "failed."  
5. Once the status is "succeeded," the output image URL is returned.  
6. If the status is "failed," an error message is provided.

Recommended polling interval: 1 second  
Maximum timeout: 600 seconds (10 minutes)  

### Endpoints

#### Create a Prediction
• Method: POST  
• Endpoint: /predictions  
• Description: Submit a new prediction job for interior design generation. Provide your desired input image URL, text prompt, and any optional parameters.

Example request:
```bash
curl -X POST "https://prod.api.market/api/v1/magicapi/realistic-interior-design-generator/predictions" \
  -H "Content-Type: application/json" \
  -H "x-magicapi-key: YOUR_API_MARKET_KEY" \
  -d '{
    "input": {
      "image": "https://example.com/image.jpg",
      "prompt": "A chic modern living room with gray sectional sofa and gold accents"
    }
  }'
```

Example response (201 Created):
```json
{
  "id": "ufawqhfynnddngldkgtslldrkq",
  "version": "76604baddc85b1b4616e1c6475eca080da339c8875bd4996705440484a6eac38",
  "status": "starting",
  "created_at": "2025-04-23T20:02:03.733Z"
}
```
• Use the returned "id" to poll for status or retrieve results.  

#### Get Prediction Status
• Method: GET  
• Endpoint: /predictions/{id}  
• Description: Retrieve the status and output of an existing prediction.

Example request:
```bash
curl -X GET "https://prod.api.market/api/v1/magicapi/realistic-interior-design-generator/predictions/ufawqhfynnddngldkgtslldrkq" \
  -H "x-magicapi-key: YOUR_API_MARKET_KEY"
```

Example response when succeeded (200 OK):
```json
{
  "id": "ufawqhfynnddngldkgtslldrkq",
  "status": "succeeded",
  "output": "https://somecdn.com/output_image.jpg",
  "created_at": "2023-01-01T12:00:00.000Z",
  "started_at": "2023-01-01T12:00:05.000Z",
  "completed_at": "2023-01-01T12:01:00.000Z"
}
```

## Status Codes
- 200 OK: Request succeeded—data fetched or operation completed.  
- 201 Created: Prediction job successfully submitted.  
- 400 Bad Request: Input validation failed—check if your parameters are correct.  
- 401 Unauthorized: API key missing or invalid.  
- 403 Forbidden: The API key is valid, but the request is disallowed.  
- 404 Not Found: The specified resource or endpoint does not exist.  
- 429 Too Many Requests: Rate limit reached. Wait or upgrade your plan before retrying.  
- 500 Internal Server Error: Server encountered an error—try again later or contact support.  
- 503 Service Unavailable: Service is temporarily down or undergoing maintenance.

## Rate Limits
The API enforces rate limits to ensure everyone has fair access. If you exceed the limit, you may receive a 429 Too Many Requests error. Implement exponential backoff in your application to handle these situations gracefully.

## Error Handling
When the API encounters an error, it returns a JSON response with details. For example:
```json
{
  "error": {
    "code": "invalid_parameter",
    "message": "The parameter 'image' is required",
    "status": 400
  }
}
```
To handle errors:
- Check the status code to determine the type of issue (e.g., 400 for invalid parameters).
- Review the error.message field to understand which parameter or request aspect needs correcting.
- Implement retries for transient errors, but do not retry on validation failures without fixing the input.

## Implementation Guide

### Example Code (JavaScript)
Below is a sample illustrating how to create a prediction and poll until completion.

```javascript
const apiKey = "YOUR_API_MARKET_KEY";
const baseUrl = "https://prod.api.market/api/v1/magicapi/realistic-interior-design-generator";

async function createAndWaitForPrediction(inputData) {
  try {
    // 1. Create the prediction
    const response = await fetch(`${baseUrl}/predictions`, {
      method: "POST",
      headers: {
        "Content-Type": "application/json",
        "x-magicapi-key": apiKey
      },
      body: JSON.stringify({ input: inputData })
    });

    if (!response.ok) {
      throw new Error(`API error: ${response.status} ${response.statusText}`);
    }

    const prediction = await response.json();
    const predictionId = prediction.id;

    // 2. Poll for results with a timeout
    return await pollForResults(predictionId);
  } catch (error) {
    console.error("Error:", error);
    throw error;
  }
}

function delay(ms) {
  return new Promise(resolve => setTimeout(resolve, ms));
}

async function pollForResults(predictionId) {
  const MAX_TIMEOUT = 600000; // 600 seconds (10 minutes)
  const POLL_INTERVAL = 1000; // 1 second

  const startTime = Date.now();

  while (Date.now() - startTime < MAX_TIMEOUT) {
    const response = await fetch(`${baseUrl}/predictions/${predictionId}`, {
      headers: { "x-magicapi-key": apiKey }
    });

    if (!response.ok) {
      throw new Error(`API error: ${response.status} ${response.statusText}`);
    }

    const prediction = await response.json();

    if (prediction.status === "succeeded") {
      return prediction.output;
    }

    if (prediction.status === "failed") {
      throw new Error(`Prediction failed: ${prediction.error || "Unknown error"}`);
    }

    await delay(POLL_INTERVAL);
  }

  throw new Error("Prediction timed out after 10 minutes");
}

// Example usage:
createAndWaitForPrediction({
  image: "https://example.com/my_room.jpg",
  prompt: "A minimalist Scandinavian living room with light wood floors and soft gray accents"
})
  .then(outputUrl => {
    console.log("Design image available at:", outputUrl);
  })
  .catch(err => {
    console.error("Prediction error:", err.message);
  });
```

### Example Code (Python)
```python
import requests
import time

API_KEY = "YOUR_API_MARKET_KEY"
BASE_URL = "https://prod.api.market/api/v1/magicapi/realistic-interior-design-generator"

def create_and_wait_for_prediction(input_data):
    headers = {
        "Content-Type": "application/json",
        "x-magicapi-key": API_KEY
    }

    # 1. Create the prediction
    response = requests.post(
        f"{BASE_URL}/predictions",
        headers=headers,
        json={"input": input_data}
    )

    if response.status_code != 201 and response.status_code != 200:
        raise Exception(f"API error: {response.status_code} {response.text}")

    prediction = response.json()
    prediction_id = prediction["id"]

    # 2. Poll for results with a timeout
    return poll_for_results(prediction_id)

def poll_for_results(prediction_id):
    MAX_TIMEOUT = 600  # 10 minutes
    POLL_INTERVAL = 1  # 1 second

    start_time = time.time()

    while time.time() - start_time < MAX_TIMEOUT:
        response = requests.get(
            f"{BASE_URL}/predictions/{prediction_id}",
            headers={"x-magicapi-key": API_KEY}
        )

        if response.status_code != 200:
            raise Exception(f"API error: {response.status_code} {response.text}")

        prediction = response.json()
        status = prediction["status"]

        if status == "succeeded":
            return prediction["output"]
        if status == "failed":
            error_msg = prediction.get("error", "Unknown error")
            raise Exception(f"Prediction failed: {error_msg}")

        time.sleep(POLL_INTERVAL)

    raise Exception("Prediction timed out after 10 minutes")

# Example usage:
if __name__ == "__main__":
    try:
        result_url = create_and_wait_for_prediction({
            "image": "https://example.com/room.jpg",
            "prompt": "A cozy industrial loft living room with exposed brick walls and vintage leather furniture"
        })
        print("Design generated at:", result_url)
    except Exception as e:
        print("Error:", str(e))
```

### Example cURL Commands
```bash
# Step 1: Create a prediction
curl -X POST "https://prod.api.market/api/v1/magicapi/realistic-interior-design-generator/predictions" \
  -H "Content-Type: application/json" \
  -H "x-magicapi-key: YOUR_API_MARKET_KEY" \
  -d '{
    "input": {
      "image": "https://example.com/image.jpg",
      "prompt": "Modern farmhouse style kitchen with white cabinetry and reclaimed wood shelves"
    }
  }'

# Suppose the response is:
# {
#   "id": "abcd1234",
#   "status": "starting"
# }

# Step 2: Poll until 'status' is 'succeeded' or 'failed'
curl -X GET "https://prod.api.market/api/v1/magicapi/realistic-interior-design-generator/predictions/abcd1234" \
  -H "x-magicapi-key: YOUR_API_MARKET_KEY"
```

### Performance Optimization
- Provide concise prompts and images at a reasonable resolution to reduce processing time.  
- Use guidance_scale and prompt_strength parameters judiciously for faster results.  
- Cache results locally if you frequently request similar prompts.

## FAQ
1. Can I generate an entirely new room from just text?  
   – Yes. Provide a blank or simple placeholder image along with your text prompt describing the desired room.  
2. How long do predictions typically take?  
   – Processing time ranges from a few seconds to a couple of minutes, depending on complexity and server load.  
3. Can I adjust the output resolution?  
   – Currently, the resolution is implicitly set by the model. High-resolution outputs are supported but may increase inference time.  
4. Do I pay for status-check (GET) requests?  
   – No. Only image generation requests (POST) consume API units.

## Contact Us
If you have any questions or need assistance, you can reach out to us through the embedded chat on the bottom right corner of the page or send an email to hello[at]api.market.

Create photorealistic interior designs from text and images. Ideal for virtual staging. From $0.05/call. Try it free on API.market.