Name: Flux GHIBSKY API: Anime Sky Illustration Generator
Brand: magicapi
SKU: api-magicapi-anime-sky-illustration-generator-aleksa-codes-flux-ghibsky-illustration
Availability: InStock
Author: API Market

Shashank Agarwal

# 🌌 Anime Sky Illustration Generator API (aleksa-codes Flux GHIBSKY)

## Overview
Flux GHIBSKY Illustration is a LoRA (a small style add-on) for the FLUX image model, published by aleksa-codes. Its developer describes it as creating serene landscapes with vibrant, surreal skies and detailed, Ghibli-inspired elements, in the atmospheric style of Makoto Shinkai's films. Include the trigger phrase `GHIBSKY style` in the prompt to apply it.

Send a text `prompt` to generate images, or add an `image` (and optionally a `mask`) for image-to-image or inpainting. Each request returns a list of 1 to 4 image URLs, set by `num_outputs`.

## Features
- **Trigger phrase**: start the prompt with `GHIBSKY style` to activate the illustration style.
- **Two base models**: `model` `dev` (default, best at around 28 steps) or `schnell` (needs only 4 steps).
- **Image-to-image and inpainting**: pass `image`, plus an optional `mask`, and control how much changes with `prompt_strength`.
- **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).
- **Style strength**: `lora_scale` (-1 to 3) sets how strongly the GHIBSKY LoRA is applied; `extra_lora` adds a second LoRA with its own `extra_lora_scale`.
- **Output control**: 1 to 4 images per request, `webp` (default), `jpg` or `png`, about 1 or 0.25 megapixels.
- **Speed mode**: `go_fast` runs an fp8 quantized model for faster predictions.

## Use Cases
1. **Wallpapers and backgrounds**: phone (`9:16`) and desktop (`16:9`) scenes with dramatic skies.
2. **Story and game art**: establishing shots and landscapes in a consistent illustrated style.
3. **Turning photos into illustrations**: send a photo as `image` with a `GHIBSKY style` prompt.
4. **Social media and book covers**: atmospheric illustrations in the aspect ratio of each placement.

## Visual Examples
### Example Input
Prompt: "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights" with the `dev` model, `lora_scale` 1, 28 steps, one `9:16` JPG image at quality 100:

```json
{
  "model": "dev",
  "prompt": "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "9:16",
  "output_format": "jpg",
  "guidance_scale": 3.5,
  "output_quality": 100,
  "num_inference_steps": 28
}
```

### Example Output
![Flux GHIBSKY output: an illustrated cat on a windowsill looking out at a starry night sky and distant city lights](https://blog.api.market/wp-content/uploads/2026/10/flux-ghibsky-illustration-output-zvx5t9n4-api-market.jpg)

## Input Parameters
| Field | Type | Required | Default | Allowed values | Description |
| --- | --- | --- | --- | --- | --- |
| `prompt` | string | Yes |  |  | Prompt for the generated image. Include the trigger word phrase `GHIBSKY style` to apply the GHIBSKY illustration 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. If custom is selected, width and height are used and the model 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. Not compatible 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. Not compatible with go_fast. |
| `prompt_strength` | number | No | `0.8` | 0 to 1 | Prompt strength when using image-to-image. 1.0 discards all information in the input image. |
| `model` | string | No | `dev` | `dev`, `schnell` | Which base model to run. dev works best with around 28 inference steps; schnell needs only 4 steps. |
| `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 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 quality, 0 is lowest quality. Not relevant for .png outputs |
| `disable_safety_checker` | boolean | No | `false` |  | Disable the safety checker for generated images. |
| `go_fast` | boolean | No | `false` |  | Run faster predictions with a speed-optimized (fp8 quantized) model; disable to run in the original bf16 |
| `megapixels` | string | No | `1` | `1`, `0.25` | Approximate number of megapixels for generated image |
| `lora_scale` | number | No | `1` | -1 to 3 | How strongly the main LoRA is applied. Results are usually good between 0 and 1. With go_fast, a 1.5x multiplier is applied to this value. |
| `extra_lora` | string | No | none |  | Optional second LoRA to combine with the main one, given as a Hugging Face or CivitAI model link or a direct URL to a .safetensors file. |
| `extra_lora_scale` | number | No | `1` | -1 to 3 | How strongly the extra LoRA is applied. Results are usually good between 0 and 1. 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**: $0.017 per API unit.
- **1 API unit = 1 request with up to 10 seconds of processing time.** A request that finishes within 10 seconds costs one unit ($0.017).
- A request that runs longer bills one more unit for each started block of 10 seconds: more than 10 and up to 20 seconds is 2 units ($0.034), up to 30 seconds is 3 units ($0.051), and so on.
- **Example cost**: the example request took 14.1 seconds of processing, which is 2 units = **$0.034**.
- More images (`num_outputs`), more steps or `custom` sizes take longer and can use more units. `model` `schnell` with 4 steps or `go_fast` usually finishes faster.
- **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/anime-sky-illustration-generator-aleksa-codes-flux-ghibsky-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/anime-sky-illustration-generator-aleksa-codes-flux-ghibsky-illustration/predictions" \
  -H "Content-Type: application/json" \
  -H "x-api-market-key: YOUR_API_MARKET_KEY" \
  -d '{
    "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0",
    "input": {
      "model": "dev",
      "prompt": "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights",
      "lora_scale": 1,
      "num_outputs": 1,
      "aspect_ratio": "9:16",
      "output_format": "jpg",
      "guidance_scale": 3.5,
      "output_quality": 100,
      "num_inference_steps": 28
    }
  }'
```

Response (201 Created):
```json
{
  "id": "zvx5t9n4msrmt0d1d0rs2k7e58",
  "version": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0",
  "status": "starting",
  "created_at": "2026-10-23T09:57:26.620Z"
}
```

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

Response when the prediction has finished (200 OK):
```json
{
  "id": "zvx5t9n4msrmt0d1d0rs2k7e58",
  "status": "succeeded",
  "output": [
    "https://blog.api.market/wp-content/uploads/2026/10/flux-ghibsky-illustration-output-zvx5t9n4-api-market.jpg"
  ],
  "error": null,
  "created_at": "2026-10-23T09:57:26.620Z",
  "started_at": "2026-10-23T09:57:27.120Z",
  "completed_at": "2026-10-23T09:57:40.761Z"
}
```

`output` is a list of image URLs, one per image (`num_outputs`, 1 to 4).

### 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
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/anime-sky-illustration-generator-aleksa-codes-flux-ghibsky-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: "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", 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": "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights",
  "lora_scale": 1,
  "num_outputs": 1,
  "aspect_ratio": "9:16",
  "output_format": "jpg",
  "guidance_scale": 3.5,
  "output_quality": 100,
  "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/anime-sky-illustration-generator-aleksa-codes-flux-ghibsky-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": "a9f94946fa0377091ac0bcfe61b0d62ad9a85224e4b421b677d4747914b908c0", "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({
    "model": "dev",
    "prompt": "GHIBSKY style, a cat on a windowsill gazing out at a starry night sky and distant city lights",
    "lora_scale": 1,
    "num_outputs": 1,
    "aspect_ratio": "9:16",
    "output_format": "jpg",
    "guidance_scale": 3.5,
    "output_quality": 100,
    "num_inference_steps": 28
})
print(output)
```

## FAQ
- **Do I need the trigger phrase?**
  - Include `GHIBSKY style` in the prompt to apply the illustration style. Without it the LoRA has less effect on the image.
- **How many images does one request return?**
  - 1 by default, up to 4 with `num_outputs`. The output is always a list of URLs.
- **Can I turn a photo into an illustration?**
  - Yes. Pass it as `image` and set `prompt_strength` (default 0.8; 1.0 ignores the input image). Add a `mask` to change only part of it.
- **How do I choose an exact size?**
  - Set `aspect_ratio` to `custom` and pass `width` and `height` (256 to 1440, rounded to a multiple of 16). Custom sizes do not work with `go_fast`.
- **What did the example request cost?**
  - 2 API units, $0.034, because it took 14.1 seconds of processing.
- **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 dreamy anime sky and landscape illustrations with the Flux GHIBSKY LoRA from a text prompt, or restyle your own image. Pay per request.