Name: Beenga Image 1 API: Indian Context Image Generator
Brand: magicapi
SKU: api-magicapi-contemporary-indian-image-generation-beenga-beenga-image-1
Availability: InStock
Author: API Market

Shashank Agarwal

# 🪷 Indian Context Image Generator and Editor API (Beenga Image 1)

## Overview
Beenga Image 1 is an image model from Beenga for contemporary Indian subjects and settings. Its developer describes it as following negations in prompts, using present-day rather than ceremonial defaults, and rendering complexion as specified.

Send a text `prompt` to generate an image from scratch, or add source `images` and write the prompt as an instruction to edit them. Each request returns a list of image URLs; the example returned one image.

## Features
- **Text to image**: write the prompt plainly. With `beenga_prompt_layer` on (the default), Beenga applies its Indian-context prompt adherence to your wording.
- **Editing and references**: pass up to 5 image URLs in `images`. The prompt then works as an instruction, such as `change the sari to green` or `put her on a rooftop at night`. More than one image helps keep the same subject across a scene.
- **Aspect ratios**: `1:1` (default), `16:9`, `9:16`, `4:3`, `3:4`, `3:2`, `2:3`. For a standing full-length person its developer suggests `3:4` or `9:16`. When editing, the source image's dimensions are kept and `aspect_ratio` is ignored.
- **Curl enhance**: `curl_enhance` sharpens salon-curl geometry with a curl adapter. It is off by default because it also nudges unspecified hair toward curly.
- **Tuned for speed**: the distilled model is tuned for 4 `num_inference_steps`. `guidance_scale` has no effect on this checkpoint and is kept for compatibility.
- **Output format**: `png` (default), `jpg` or `webp`.
- **Seed**: set `seed` for reproducible output; leave it out for a random result.

## Use Cases
1. **Editorial and wedding imagery**: bridal, festive and everyday scenes with Indian clothing, hair and settings.
2. **Marketing for Indian audiences**: ads and social posts showing people in present-day Indian settings.
3. **Garment and scene edits**: change a garment's colour or move a subject to a new location with one instruction.
4. **Consistent characters**: pass several images of one person to keep them consistent across scenes.

## Visual Examples
### Example Input
Prompt: "bride in ivory lehenga, long thick braided hair decorated with flowers, luxury wedding venue, glowing skin, editorial photography"

No source images were sent, so the model generated the image from scratch. The request set every other field to its default value.

```json
{
  "prompt": "bride in ivory lehenga, long thick braided hair decorated with flowers, luxury wedding venue, glowing skin, editorial photography",
  "aspect_ratio": "1:1",
  "curl_enhance": false,
  "output_format": "png",
  "guidance_scale": 3.5,
  "beenga_prompt_layer": true,
  "num_inference_steps": 4
}
```

### Example Output
![Beenga Image 1 output: a bride in an ivory lehenga with a long braid decorated with flowers at a wedding venue](https://blog.api.market/wp-content/uploads/2026/10/beenga-image-1-output-yzq1jd9b-api-market-1.jpg)

## Input Parameters
| Field | Type | Required | Default | Allowed values | Description |
| --- | --- | --- | --- | --- | --- |
| `prompt` | string | Yes |  |  | What to generate, or what to change if you supply images. Write it plainly; Beenga handles the phrasing. |
| `images` | array of strings (URLs) | No | `[]` |  | Source image URLs to edit or reference. Leave empty to generate from scratch. With images, the prompt is an instruction, such as 'change the sari to green' or 'put her on a rooftop at night'. Pass more than one to hold a subject across a scene. Max 5. |
| `aspect_ratio` | string | No | `1:1` | `1:1`, `16:9`, `9:16`, `4:3`, `3:4`, `3:2`, `2:3` | Output shape. For a standing full-length person prefer 3:4 or 9:16; a square frame compresses the figure and hands and hair suffer for it. Ignored when editing; the source image's dimensions are kept. |
| `num_inference_steps` | integer | No | `4` | 1 to 50 | Denoising steps. The distilled model is tuned for 4. |
| `guidance_scale` | number | No | `3.5` | 0 to 10 | No effect on this checkpoint; the distilled model ignores guidance. Kept for API compatibility. |
| `seed` | integer | No | none |  | Fix for reproducible output. Leave blank for random. |
| `curl_enhance` | boolean | No | `false` |  | Sharpen salon-curl geometry using Beenga's curl adapter. Off by default: it also nudges unspecified hair toward curly. |
| `beenga_prompt_layer` | boolean | No | `true` |  | Apply Beenga's Indian-context prompt adherence. Turn off to see the raw model's behaviour. |
| `output_format` | string | No | `png` | `png`, `jpg`, `webp` | Image format |

## Pricing
- **Pay As You Go (PAYG) pricing**: you only pay for what you use.
- **Price**: $0.0071 per API unit.
- **1 API unit = 1 request with up to 6 seconds of processing.** A longer request uses one more unit per started 6-second block (for example, 7 seconds of processing uses 2 units, $0.0142).
- **Example cost**: the example took 2.33 seconds of processing, which is 1 unit, $0.0071.
- **Failed or cancelled predictions are not billed.**
- **GET requests to check prediction status** are free and don't count toward API unit usage.
- **No monthly subscription fee.**

## API Documentation

### Base URL
All API requests go to: `https://prod.api.market/api/v1/magicapi/contemporary-indian-image-generation-beenga-beenga-image-1`

### Authentication
Send your api.market API key in the `x-api-market-key` header:
```
x-api-market-key: YOUR_API_MARKET_KEY
```

### Asynchronous Processing
**IMPORTANT**: This API is asynchronous. The flow is:
1. Send a POST request to `/predictions`. A successful request returns **201 Created** with a prediction `id` and a `status` of `starting` or `processing`.
2. Poll GET `/predictions/{id}` with that ID.
3. Keep polling while `status` is `starting` or `processing`.
4. Stop when `status` is `succeeded` (read `output`), `failed` or `canceled` (read `error`).

A polling interval of 1 second and an overall timeout of 600 seconds (10 minutes) work well.

### Endpoints

#### Create a Prediction
```bash
curl -X POST "https://prod.api.market/api/v1/magicapi/contemporary-indian-image-generation-beenga-beenga-image-1/predictions" \
  -H "Content-Type: application/json" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY" \
  -d '{
    "version": "a89289ee966c0f0d2273b3bf932297ad8eae5f2748e706783ef64fe8edd7f304",
    "input": {
      "prompt": "bride in ivory lehenga, long thick braided hair decorated with flowers, luxury wedding venue, glowing skin, editorial photography",
      "aspect_ratio": "1:1",
      "curl_enhance": false,
      "output_format": "png",
      "guidance_scale": 3.5,
      "beenga_prompt_layer": true,
      "num_inference_steps": 4
    }
  }'
```

Response (201 Created):
```json
{
  "id": "yzq1jd9b99rmr0d1ccj87979nm",
  "version": "a89289ee966c0f0d2273b3bf932297ad8eae5f2748e706783ef64fe8edd7f304",
  "status": "starting",
  "created_at": "2026-10-22T10:24:37.331Z"
}
```

#### Check Prediction Status
```bash
curl -X GET "https://prod.api.market/api/v1/magicapi/contemporary-indian-image-generation-beenga-beenga-image-1/predictions/{id}" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY"
```

Response when the prediction has finished (200 OK):
```json
{
  "id": "yzq1jd9b99rmr0d1ccj87979nm",
  "status": "succeeded",
  "output": [
    "https://blog.api.market/wp-content/uploads/2026/10/beenga-image-1-output-yzq1jd9b-api-market-1.jpg"
  ],
  "error": null,
  "created_at": "2026-10-22T10:24:37.331Z",
  "started_at": "2026-10-22T10:27:35.301Z",
  "completed_at": "2026-10-22T10:27:38.632Z"
}
```

`output` is a list of image URLs. The example returned one image.

### Status Codes
- **201 Created**: prediction created (POST `/predictions`). This is the normal success response.
- **200 OK**: prediction details returned (GET `/predictions/{id}`).
- **400 Bad Request**: invalid input, for example a missing `prompt` or an `aspect_ratio` that is not in the list.
- **401 Unauthorized**: missing or invalid API key.
- **404 Not Found**: no prediction with that ID.
- **429 Too Many Requests**: rate limit exceeded.
- **500 Internal Server Error** or **503 Service Unavailable**: temporary server problem; retry later.

## Rate Limits
All plans allow 10 requests per second. Requests above that return `429 Too Many Requests`; back off before retrying and honour any `Retry-After` header. Polling a prediction with GET is free but still counts toward the per-second limit, so poll every 1 to 5 seconds rather than in a tight loop.

## Error Handling
- Check the HTTP status code of every request and read the response body for the error message.
- A prediction can also end with `status` set to `failed`; the `error` field then explains why. Failed predictions are not billed.
- Retry 429, 500 and 503 responses with exponential backoff. Fix the input before retrying a 400.

## Implementation Guide
### Example Code

#### JavaScript
```javascript
const apiKey = "YOUR_API_MARKET_KEY";
const baseUrl = "https://prod.api.market/api/v1/magicapi/contemporary-indian-image-generation-beenga-beenga-image-1";

async function createAndWaitForPrediction(input) {
  const response = await fetch(`${baseUrl}/predictions`, {
    method: "POST",
    headers: {
      "Content-Type": "application/json",
      "x-api-market-key": apiKey
    },
    body: JSON.stringify({ version: "a89289ee966c0f0d2273b3bf932297ad8eae5f2748e706783ef64fe8edd7f304", input })
  });

  if (response.status !== 201) {
    throw new Error(`API error: ${response.status} ${await response.text()}`);
  }

  const prediction = await response.json();
  return pollForResults(prediction.id);
}

const delay = (ms) => new Promise((resolve) => setTimeout(resolve, ms));

async function pollForResults(predictionId) {
  const maxTimeout = 600000;
  const pollInterval = 1000;
  const startTime = Date.now();

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

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

    const prediction = await response.json();

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

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

    await delay(pollInterval);
  }

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

createAndWaitForPrediction({
  "prompt": "bride in ivory lehenga, long thick braided hair decorated with flowers, luxury wedding venue, glowing skin, editorial photography",
  "aspect_ratio": "1:1",
  "curl_enhance": false,
  "output_format": "png",
  "guidance_scale": 3.5,
  "beenga_prompt_layer": true,
  "num_inference_steps": 4
}).then((output) => console.log(output));
```

#### Python
```python
import time
import requests

API_KEY = "YOUR_API_MARKET_KEY"
BASE_URL = "https://prod.api.market/api/v1/magicapi/contemporary-indian-image-generation-beenga-beenga-image-1"


def create_and_wait_for_prediction(input_data):
    headers = {"Content-Type": "application/json", "x-api-market-key": API_KEY}
    response = requests.post(
        f"{BASE_URL}/predictions",
        headers=headers,
        json={"version": "a89289ee966c0f0d2273b3bf932297ad8eae5f2748e706783ef64fe8edd7f304", "input": input_data},
    )

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

    return poll_for_results(response.json()["id"])


def poll_for_results(prediction_id):
    max_timeout = 600
    poll_interval = 1
    headers = {"x-api-market-key": API_KEY}
    start_time = time.time()

    while time.time() - start_time < max_timeout:
        response = requests.get(f"{BASE_URL}/predictions/{prediction_id}", headers=headers)

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

        prediction = response.json()

        if prediction["status"] == "succeeded":
            return prediction["output"]

        if prediction["status"] in ("failed", "canceled"):
            raise Exception(f"Prediction {prediction['status']}: {prediction.get('error') or 'Unknown error'}")

        time.sleep(poll_interval)

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


output = create_and_wait_for_prediction({
    "prompt": "bride in ivory lehenga, long thick braided hair decorated with flowers, luxury wedding venue, glowing skin, editorial photography",
    "aspect_ratio": "1:1",
    "curl_enhance": False,
    "output_format": "png",
    "guidance_scale": 3.5,
    "beenga_prompt_layer": True,
    "num_inference_steps": 4
})
print(output)
```

## FAQ
- **How do I edit an existing image?**
  - Put its URL in `images` and describe the change in `prompt`, for example `change the sari to green`. The source image's dimensions are kept, so `aspect_ratio` is ignored.
- **What does `beenga_prompt_layer` do?**
  - It applies Beenga's Indian-context prompt adherence and is on by default. Set it to `false` to see the raw model's behaviour.
- **Should I change `guidance_scale` or `num_inference_steps`?**
  - `guidance_scale` has no effect on this checkpoint. The model is tuned for 4 steps; you can go up to 50, but more steps take longer and requests over 6 seconds of processing use more units.
- **Why did hair come out curly when I did not ask for it?**
  - Check `curl_enhance`. When it is `true` it nudges unspecified hair toward curly. It is `false` by default.
- **How many source images can I send?**
  - Up to 5 in `images`, according to the field description.
- **Is the 201 response from POST an error?**
  - No. 201 Created means the prediction was accepted. Use the returned `id` to poll GET `/predictions/{id}` until `status` is `succeeded`, `failed` or `canceled`.

## Contact Us
If you have any questions, reach out to us through the chat on the bottom right of the page. You can also email our support team at hello@magicapi.com.


Generate and edit images with contemporary Indian context using Beenga Image 1, with settings for aspect ratio, curl detail and output format.