Name: FLUX Half Illustration API: Photo and Illustration Mix
Brand: magicapi
SKU: api-magicapi-half-photo-half-illustration-generator-davisbrown-flux-half-illustration
Availability: InStock
Author: API Market

Shashank Agarwal

# 🎨 Half-Photo Half-Illustration Image Generator API (davisbrown FLUX Half Illustration)

## Overview
FLUX Half Illustration is a LoRA style for the FLUX image model, published by davisbrown. Its developer describes it as creating half photo, half illustrated elements; start your prompt with "In the style of TOK" to trigger the style.

Send a text `prompt` and the model returns a list of image URLs (1 to 4 images, set by `num_outputs`). You can also pass an `image` for image-to-image, or an `image` plus a `mask` for inpainting.

## Features
- **Mixed photo and illustration style**: photographic subjects combined with drawn elements, triggered by "In the style of TOK".
- **Text to image, image to image and inpainting**: use `prompt` alone, add `image` (with `prompt_strength`), or add `image` and `mask`.
- **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 px).
- **Two base models**: `dev` (default, about 28 steps) or `schnell` (about 4 steps).
- **Up to 4 images per request** with `num_outputs`.
- **Output formats**: `webp` (default), `jpg` or `png`, with `output_quality` 0 to 100.
- **Style strength**: `lora_scale` (-1 to 3, default 1), plus an optional second LoRA with `extra_lora` and `extra_lora_scale`.
- **Speed mode**: `go_fast` runs an fp8-quantized model for faster results.

## Use Cases
1. **Editorial and poster art**: portraits and fashion shots surrounded by illustrated details.
2. **Social media visuals**: eye-catching mixed-media images in feed or story aspect ratios.
3. **Album, event and merch artwork**: photo subjects with hand-drawn flourishes.
4. **Restyling photos**: send an existing photo as `image` and add illustrated elements with the prompt.

## Visual Examples
### Example Input
Prompt: "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll"

Settings: `model` `dev`, `aspect_ratio` `3:2`, `num_outputs` `1`, `num_inference_steps` `28`, `guidance_scale` `3.5`, `lora_scale` `1`, `output_format` `webp`, `output_quality` `80`.

### Example Output
![FLUX Half Illustration output for the sunglasses portrait prompt, mixing a photo subject with illustrated elements](https://blog.api.market/wp-content/uploads/2026/10/flux-half-illustration-output-0zszec8t-api-market.webp)

## Input Parameters
| Field | Type | Required | Default | Allowed values | Description |
| --- | --- | --- | --- | --- | --- |
| `prompt` | string | Yes |  |  | Prompt for the generated image. Include the trigger phrase "In the style of TOK" to activate the trained style |
| `image` | string (URL) | No | none |  | Input image for image-to-image or inpainting mode. If provided, `aspect_ratio`, `width` and `height` are ignored |
| `mask` | string (URL) | No | none |  | Image mask 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 works if `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 works if `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` | Which model to run. `dev` performs best with around 28 inference steps; `schnell` only needs 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 | random |  | 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. 100 is best quality. Not relevant for `png` |
| `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 (currently fp8 quantized); disable to run in 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. Sane results between 0 and 1 for base inference. With `go_fast` a 1.5x multiplier is applied to this value |
| `extra_lora` | string | No | none |  | Extra LoRA weights to load: a Hugging Face URL (`huggingface.co/<owner>/<model-name>`), a CivitAI URL (`civitai.com/models/<id>[/<model-name>]`) or a direct `.safetensors` URL |
| `extra_lora_scale` | number | No | `1` | -1 to 3 | How strongly the extra LoRA is applied. Sane results between 0 and 1 for base inference. With `go_fast` a 1.5x multiplier is applied to this value |

## Pricing
- **Pay As You Go (PAYG) pricing**: you only pay for what you use.
- **Price**: $0.014 per API unit.
- **1 API unit = 1 successful request with up to 8 seconds of processing.** A longer job bills one more unit for each started block of 8 seconds (for example, 20 seconds of processing is 3 units, $0.042).
- Processing time grows with `num_outputs`, `num_inference_steps` and image size; `schnell` and `go_fast` are faster.
- **Example cost**: the example request (one image, 28 steps, `dev`) took 10.4 seconds of processing, which is 2 units, so $0.028.
- **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/half-photo-half-illustration-generator-davisbrown-flux-half-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/half-photo-half-illustration-generator-davisbrown-flux-half-illustration/predictions" \
  -H "Content-Type: application/json" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY" \
  -d '{
    "version": "687458266007b196a490e79a77bae4b123c1792900e1cb730a51344887ad9832",
    "input": {
      "model": "dev",
      "prompt": "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll",
      "lora_scale": 1,
      "num_outputs": 1,
      "aspect_ratio": "3:2",
      "output_format": "webp",
      "guidance_scale": 3.5,
      "output_quality": 80,
      "num_inference_steps": 28
    }
  }'
```

Response (201 Created):
```json
{
  "id": "0zszec8td9rmw0d1d8fa84p6nm",
  "version": "687458266007b196a490e79a77bae4b123c1792900e1cb730a51344887ad9832",
  "status": "starting",
  "created_at": "2026-10-23T18:55:20.427Z"
}
```

#### Check Prediction Status
```bash
curl -X GET "https://prod.api.market/api/v1/magicapi/half-photo-half-illustration-generator-davisbrown-flux-half-illustration/predictions/{id}" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY"
```

Response when the prediction has finished (200 OK):
```json
{
  "id": "0zszec8td9rmw0d1d8fa84p6nm",
  "status": "succeeded",
  "output": [
    "https://blog.api.market/wp-content/uploads/2026/10/flux-half-illustration-output-0zszec8t-api-market.webp"
  ],
  "error": null,
  "created_at": "2026-10-23T18:55:20.427Z",
  "started_at": "2026-10-23T18:55:21.427Z",
  "completed_at": "2026-10-23T18:55:41.427Z"
}
```

`output` is an array 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`, a `num_outputs` above 4 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/half-photo-half-illustration-generator-davisbrown-flux-half-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: "687458266007b196a490e79a77bae4b123c1792900e1cb730a51344887ad9832", 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": "dev",
  "prompt": "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "3:2",
  "output_format": "webp",
  "guidance_scale": 3.5,
  "output_quality": 80,
  "num_inference_steps": 28
}).then((urls) => console.log(urls));
```

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

API_KEY = "YOUR_API_MARKET_KEY"
BASE_URL = "https://prod.api.market/api/v1/magicapi/half-photo-half-illustration-generator-davisbrown-flux-half-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": "687458266007b196a490e79a77bae4b123c1792900e1cb730a51344887ad9832", "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": "dev",
    "prompt": "In the style of TOK, a photo editorial avant-garde dramatic action pose of a person wearing 90s round wacky sunglasses pulling glasses down looking forward, in Tokyo with large marble structures and bonsai trees at sunset with a vibrant illustrated jacket surrounded by illustrations of flowers, smoke, flames, ice cream, sparkles, rock and roll",
    "lora_scale": 1,
    "num_outputs": 1,
    "aspect_ratio": "3:2",
    "output_format": "webp",
    "guidance_scale": 3.5,
    "output_quality": 80,
    "num_inference_steps": 28
}))
```

## FAQ
- **Do I need the "TOK" trigger phrase?**
  - Yes, for the half-photo, half-illustration look. Start the prompt with "In the style of TOK"; without it the trained style is less likely to appear.
- **How many images does one request return?**
  - Between 1 and 4, set by `num_outputs` (default 1). Billing is by processing time, so more images take longer and can add units.
- **How do I make generation faster and cheaper?**
  - Use `model` `schnell` with about 4 `num_inference_steps`, turn on `go_fast`, or set `megapixels` to `0.25`. Shorter processing means fewer 8-second units.
- **Can I edit an existing photo?**
  - Yes. Pass it as `image` and lower `prompt_strength` to keep more of the original. Add a `mask` to repaint only part of it.
- **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, 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.


Create mixed-media images that combine photos and illustrations with the FLUX Half Illustration LoRA: text-to-image, image-to-image and inpainting.