Name: tudortotolici Newspaper Illustration Image Generator API
Brand: magicapi
SKU: api-magicapi-cartoon-newspaper-illustrations-tudortotolici-newspaper-illustration
Availability: InStock
Author: API Market

Shashank Agarwal

# 📰 Newspaper Illustration Image Generator API (tudortotolici Newspaper Illustration)

## Overview
Newspaper Illustration is a style LoRA for image generation. Its developer describes it as specializing in black-and-white, cartoon-style drawings reminiscent of classic newspaper illustrations.

Write a `prompt` that starts with the trigger word `TOKNWSILL`, as in the example, to activate the trained style. The model runs on a `dev` (default, about 28 steps) or `schnell` (about 4 steps) base model, supports image-to-image and inpainting through `image` and `mask`, and returns a list of 1 to 4 image URLs (`num_outputs`).

## Features
- **Newspaper illustration style**: black-and-white, cartoon-style drawings, activated with the trigger word `TOKNWSILL` in the prompt.
- **Two base models**: `model` `dev` (default) works best with around 28 inference steps; `schnell` needs only 4.
- **Aspect ratios**: `1:1` (default), `16:9`, `21:9`, `3:2`, `2:3`, `4:5`, `5:4`, `3:4`, `4:3`, `9:16`, `9:21`, or `custom` with `width` and `height` (256 to 1440).
- **Image-to-image and inpainting**: pass `image` (and `mask` for inpainting); `prompt_strength` (default 0.8) sets how much of the input image is replaced.
- **Up to 4 images per request** with `num_outputs`, in WebP (default), JPG or PNG.
- **Extra LoRA**: load a second LoRA with `extra_lora` and set its strength with `extra_lora_scale`.
- **Speed mode**: `go_fast` runs an fp8-quantized model for faster predictions.

## Use Cases
1. **Editorial illustrations**: drawings for articles, newsletters and blog posts.
2. **Comic-style visuals**: single-panel cartoon scenes for social posts and presentations.
3. **Restyling sketches or photos**: turn an input image into a newspaper-style drawing with image-to-image.

## Visual Examples
### Example Input
Prompt: "TOKNWSILL, Create a black-and-white cartoon-style drawing of people shopping at a busy farmers market, with fruit stalls, wicker baskets and a street musician playing a guitar."

Settings: `model` `schnell`, `aspect_ratio` `21:9`, `num_outputs` 1, `num_inference_steps` 28, `guidance_scale` 3.5, `lora_scale` 1, `extra_lora_scale` 0.8, `output_format` `webp`, `output_quality` 100.

### Example Output
![Black-and-white newspaper-style cartoon of people shopping at a busy farmers market with fruit stalls and a street musician](https://blog.api.market/wp-content/uploads/2026/10/newspaper_illustration-output-0atk3ps0-api-market.webp)

## Input Parameters
| Field | Type | Required | Default | Allowed values | Description |
| --- | --- | --- | --- | --- | --- |
| `prompt` | string | Yes |  |  | Prompt for the generated image. Include the trigger word `TOKNWSILL` to activate the trained style. |
| `image` | string (URL) | No | none |  | Input image URL for image-to-image or inpainting mode. If provided, `aspect_ratio`, `width` and `height` are ignored. |
| `mask` | string (URL) | No | none |  | Image mask URL for inpainting mode. If provided, `aspect_ratio`, `width` and `height` are ignored. |
| `aspect_ratio` | string | No | `1:1` | `1:1`, `16:9`, `21:9`, `3:2`, `2:3`, `4:5`, `5:4`, `3:4`, `4:3`, `9:16`, `9:21`, `custom` | Aspect ratio for the generated image. `custom` uses `width` and `height` and runs in bf16 mode. |
| `height` | integer | No | none | 256 to 1440 | Height of the generated image. Only used when `aspect_ratio` is `custom`. Rounded to the nearest multiple of 16. Incompatible with `go_fast`. |
| `width` | integer | No | none | 256 to 1440 | Width of the generated image. Only used when `aspect_ratio` is `custom`. Rounded to the nearest multiple of 16. Incompatible with `go_fast`. |
| `prompt_strength` | number | No | `0.8` | 0 to 1 | Prompt strength when using image-to-image. 1.0 fully replaces the information in the input image. |
| `model` | string | No | `dev` | `dev`, `schnell` | Base model to run. `dev` performs best with around 28 inference steps; `schnell` needs only 4. |
| `num_outputs` | integer | No | `1` | 1 to 4 | Number of images to generate |
| `num_inference_steps` | integer | No | `28` | 1 to 50 | Number of denoising steps. More steps can give more detailed images but take longer. |
| `guidance_scale` | number | No | `3` | 0 to 10 | Guidance scale for the diffusion process. Lower values can give more realistic images. Good values to try are 2, 2.5, 3 and 3.5. |
| `seed` | integer | No | none |  | Random seed. Set it for reproducible generation. |
| `output_format` | string | No | `webp` | `webp`, `jpg`, `png` | Format of the output images |
| `output_quality` | integer | No | `80` | 0 to 100 | Quality when saving the output images, from 0 to 100 (100 is best). Not used for PNG output. |
| `disable_safety_checker` | boolean | No | `false` |  | Disable the safety checker for generated images |
| `go_fast` | boolean | No | `false` |  | Run faster predictions with a model optimized for speed (fp8 quantized); set to `false` to run in the original bf16 |
| `megapixels` | string | No | `1` | `1`, `0.25` | Approximate number of megapixels for the generated image |
| `lora_scale` | number | No | `1` | -1 to 3 | How strongly the main LoRA is applied. Results are usually best between 0 and 1; with `go_fast` the value is multiplied by 1.5. |
| `extra_lora` | string | No | none |  | Additional LoRA weights to load: a Hugging Face model, a CivitAI model or a .safetensors file URL |
| `extra_lora_scale` | number | No | `1` | -1 to 3 | How strongly the extra LoRA is applied. Results are usually best between 0 and 1; with `go_fast` the value is multiplied by 1.5. |

## Pricing
- **Pay As You Go (PAYG) pricing**: you only pay for what you use.
- **Price**: $0.013 per API unit.
- **1 API unit = 1 request with up to 7 seconds of processing.** A request that runs longer is billed one more unit for each started 7-second block (for example, more than 7 and up to 14 seconds of processing is 2 units, $0.026).
- More images (`num_outputs` up to 4), more inference steps and the `dev` model take longer to process and can cross into a second unit.
- **Example cost**: the example request (one image with the `schnell` model) took 6.7 seconds of processing, which fits in one 7-second block: 1 API unit, $0.013.
- **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/cartoon-newspaper-illustrations-tudortotolici-newspaper-illustration`

### 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/cartoon-newspaper-illustrations-tudortotolici-newspaper-illustration/predictions" \
  -H "Content-Type: application/json" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY" \
  -d '{
    "version": "1797002c268b308bb2650476b8515b4410afabf5fb7c1cdb47584f5eae6bfd97",
    "input": {
      "model": "schnell",
      "prompt": "TOKNWSILL, Create a black-and-white cartoon-style drawing of people shopping at a busy farmers market, with fruit stalls, wicker baskets and a street musician playing a guitar.",
      "lora_scale": 1,
      "num_outputs": 1,
      "aspect_ratio": "21:9",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 100,
      "extra_lora_scale": 0.8,
      "num_inference_steps": 28
    }
  }'
```

Response (201 Created):
```json
{
  "id": "0atk3ps0f5rmy0d1f1t9sjp9rr",
  "version": "1797002c268b308bb2650476b8515b4410afabf5fb7c1cdb47584f5eae6bfd97",
  "status": "starting",
  "created_at": "2026-10-26T13:43:59.121Z"
}
```

#### Check Prediction Status
```bash
curl -X GET "https://prod.api.market/api/v1/magicapi/cartoon-newspaper-illustrations-tudortotolici-newspaper-illustration/predictions/{id}" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY"
```

Response when the prediction has finished (200 OK):
```json
{
  "id": "0atk3ps0f5rmy0d1f1t9sjp9rr",
  "status": "succeeded",
  "output": [
    "https://blog.api.market/wp-content/uploads/2026/10/newspaper_illustration-output-0atk3ps0-api-market.webp"
  ],
  "error": null,
  "created_at": "2026-10-26T13:43:59.121Z",
  "started_at": "2026-10-26T13:43:59.161Z",
  "completed_at": "2026-10-26T13:44:05.822Z"
}
```

`output` is a list of image URLs, one per generated image (`num_outputs`).

### 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 a `num_outputs` above 4.
- **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
Requests are rate limited to keep usage fair. If you receive a 429 response, wait and retry with exponential backoff.

## 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/cartoon-newspaper-illustrations-tudortotolici-newspaper-illustration";

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: "1797002c268b308bb2650476b8515b4410afabf5fb7c1cdb47584f5eae6bfd97", 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({
  "model": "schnell",
  "prompt": "TOKNWSILL, Create a black-and-white cartoon-style drawing of people shopping at a busy farmers market, with fruit stalls, wicker baskets and a street musician playing a guitar.",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "21:9",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 100,
  "extra_lora_scale": 0.8,
  "num_inference_steps": 28
}).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/cartoon-newspaper-illustrations-tudortotolici-newspaper-illustration"


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": "1797002c268b308bb2650476b8515b4410afabf5fb7c1cdb47584f5eae6bfd97", "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")


print(create_and_wait_for_prediction({
    "model": "schnell",
    "prompt": "TOKNWSILL, Create a black-and-white cartoon-style drawing of people shopping at a busy farmers market, with fruit stalls, wicker baskets and a street musician playing a guitar.",
    "lora_scale": 1,
    "num_outputs": 1,
    "aspect_ratio": "21:9",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 100,
    "extra_lora_scale": 0.8,
    "num_inference_steps": 28
}))
```

## FAQ
- **Do I need the trigger word?**
  - Include `TOKNWSILL` in the prompt, as in the example. The model was trained with it, and it makes the newspaper illustration style more likely to appear.
- **How many images does one request return?**
  - 1 to 4, set with `num_outputs` (default 1). They come back as a list of URLs.
- **Should I use `dev` or `schnell`?**
  - `dev` (default) performs best with around 28 inference steps. `schnell` only needs about 4 steps, so lower `num_inference_steps` when you use it.
- **Can I restyle my own image?**
  - Yes. Pass it as `image` and describe the scene in `prompt`. `prompt_strength` (default 0.8) controls how much of the input is replaced; add a `mask` to repaint only part of it.
- **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`.
- **What if my prediction fails?**
  - Failed predictions are not billed. Read the `error` field, adjust the input and try again.

## 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@magicapi.com.


Generate black-and-white cartoon drawings in a classic newspaper illustration style from text or an image. $0.013 per request, pay as you go.