# Z-Image Turbo Seamless Tiling Lora API

> Teksta-attēla modelis, kas izveido savienojamas tekstūras ar horizontālu, vertikālu vai divvirzienu flīzēšanu un līdz 3 LoRA

Ģenerē attēlus no teksta uzvednes, kas vienmērīgi atkārtojas malās un ir noderīgi tekstūrām un rakstiem. `tiling_mode` izvēlas both, horizontal vai vertical atkārtošanu, bet `tile_size` un `tile_stride` pielāgo flīzēšanu. Pieņem līdz 3 LoRA svarus laukā `loras`, var sākt ar `image_url` un neobligātu `mask_image_url` aizkrāsošanai, kā arī atgriež 1 līdz 4 attēlus vienā pieprasījumā png, jpeg vai webp formātā.

- Model id: `z-image/turbo/tiling/lora`
- Made by: Alibaba
- Category: Text to Image
- Output: image
- Price per megapixel of your output image: $0.025 / megapixel of output image (cheapest run $0.025 (25 API credits))
- Run: `POST https://api.doitong.com/v1/run/z-image/turbo/tiling/lora`
- Quote: `POST https://api.doitong.com/v1/quote/z-image/turbo/tiling/lora`
- Docs page: https://doitong.com/lv/developers/models/z-image/turbo/tiling/lora

## Pricing

Price: **$0.025 / megapixel of output image**. Price per megapixel of your output image: the input files are measured before the run (length, resolution, frame rate). The quote measures the same files and is exactly what the run charges.

The full example input below costs $0.025 = 25 API credits (1 MP output image × $0.025).

Prices are the upstream price in USD, paid from the API balance in API credits (1000 API credits = 1 USD). `POST https://api.doitong.com/v1/quote/z-image/turbo/tiling/lora` with the same JSON body returns the exact price for that input; the quote is exactly what a run charges. Invalid input is never charged and failed or canceled requests are refunded automatically.

## Input parameters

Send either the canonical name or the native field name (not both). Canonical names are the same across models.

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `prompt` |  | string | yes |  |  | Uzvedne, kas vada attēla ģenerēšanu. |
| `image_size` |  | object {width, height} \| enum (string) | no | `square_hd` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9`, `auto` | Ģenerētā attēla izmēri, kur 'auto' izvēlas 1024x1024, ja vien nav norādīts ievades attēls; tādā gadījumā tiek izmantoti tā izmēri. |
| `num_inference_steps` |  | integer | no | `8` | 1 – 8 | Veicamo secināšanas darbību skaits. |
| `seed` |  | integer \| null | no |  |  | Sēkla reproducējamiem attēliem: identiska uzvedne un sēkla rada identisku attēlu, ja modeļa versija nav mainīta. |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Ģenerēšanai pieprasītais attēlu skaits. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Drošības pārbaude, kas nedrošu attēlu vietā atgriež melnus attēlus. true iespējo pārbaudi; false to atspējo tikai autorizētiem kontiem, bet pieprasījumi bez autorizācijas tiek pārbaudīti neatkarīgi no iestatījuma. |
| `output_format` |  | enum (string) | no | `png` | `jpeg`, `png`, `webp` | Iegūtā attēla faila formāts. |
| `acceleration` |  | enum (string) | no | `regular` | `none`, `regular`, `high` | Apstrādei piemērotais paātrinājuma līmenis. |
| `enable_prompt_expansion` |  | boolean | no | `false` |  | Kontrolē, vai ir iespējota uzvednes paplašināšana. |
| `image_url` | `image` | string (image URL) \| null | no |  |  | Attēla URL, ko izmanto attēla pārveides ģenerēšanai vai attēla retušēšanai. mask_image_url norādīšana atlasa attēla retušēšanu; tā izlaišana atlasa attēla pārveides ģenerēšanu. |
| `mask_image_url` |  | string (image URL) \| null | no |  |  | Aizkrāsošanas maskas URL, kas iesniegts kopā ar obligāto image_url. Maska saglabā melnos apgabalus nemainītus un no jauna ģenerē baltos apgabalus. |
| `strength` |  | number | no | `0.6` | ≤ 1, > 0 | Pārveidošanas stiprums, kas piemērots tikai attēlam, kurš iesniegts, izmantojot image_url; citādi netiek izmantots. |
| `tile_size` |  | integer | no | `128` | 32 – 256 | Latentās telpas elementa izmērs, kur 64 atbilst 512px, 128 — 1024px, bet 256 — 2048px. Ģenerētā attēla izmēri automātiski ierobežo izmēru pa elementiem sadalītajās asīs; ielāpu veidošanai nepieciešama pāra vērtība, kas dalās ar 2. |
| `tile_stride` |  | integer | no | `64` | 16 – 128 | Latentās telpas elementa solis ar pikseļu ekvivalentiem 32 = 256px, 64 = 512px un 128 = 1024px. Derīgi ir tikai 2 daudzkārtņi; jebkura vērtība, kas pārsniedz pusi no efektīvā elementa izmēra, tiek automātiski samazināta līdz šai robežai. |
| `tiling_mode` |  | enum (string) | no | `both` | `both`, `horizontal`, `vertical` | Elementu sadalīšanas virziens: 'both' aptver visus virzienus, 'horizontal' — tikai no kreisās puses uz labo, bet 'vertical' — tikai no augšas uz leju. |
| `loras` |  | array of object {path, scale} | no | `[]` |  | Piemērojamie LoRA svari; ne vairāk kā 3 ieraksti. |
| `loras[].path` |  | string | yes |  |  | LoRA svaru atrašanās vieta, kas norādīta kā URL vai HuggingFace repozitorija ID owner/repo formātā. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | LoRA piemērojamais mērogošanas koeficients diapazonā no 0.0 līdz 4.0. |

File parameters (`image`, `mask_image_url`) take a public `https://` URL, a `data:` URI up to 10 MB, or the `file_url` of an upload from `POST /files`.

## Example input

Required parameters only:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

## Run it

Set `DOITONG_API_KEY` to a key from https://doitong.com/developers/dashboard#keys. `?wait=20` returns the finished request in the same call when it is ready within 20 seconds; otherwise poll `GET /requests/{id}` (it also accepts `?wait=`), or pass `webhook_url`.

### curl

```bash
# Run the model; wait up to 20 s for the finished result in the same call
curl -X POST "https://api.doitong.com/v1/run/z-image/turbo/tiling/lora?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }'

# Still "queued" or "running"? Poll with the id from the response:
curl "https://api.doitong.com/v1/requests/REQUEST_ID?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY"
```

### JavaScript

```javascript
const API = "https://api.doitong.com/v1";
const headers = {
  "Authorization": "Bearer " + process.env.DOITONG_API_KEY,
  "Content-Type": "application/json",
};

// Run the model; wait up to 20 s for the finished result in the same call
let res = await fetch(API + "/run/z-image/turbo/tiling/lora?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  }),
});
let request = await res.json();
if (!res.ok) throw new Error(request.error.code + ": " + request.error.message);

// Not finished yet: long-poll until it is
while (request.status === "queued" || request.status === "running") {
  res = await fetch(API + "/requests/" + request.id + "?wait=20", { headers });
  request = await res.json();
}
if (request.status !== "succeeded") throw new Error(JSON.stringify(request.error));
console.log(request.outputs.map((o) => o.url), request.cost.credits + " API credits ($" + request.cost.usd + ")");
```

### Python

```python
import os
import requests

API = "https://api.doitong.com/v1"
headers = {"Authorization": "Bearer " + os.environ["DOITONG_API_KEY"]}

payload = {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/z-image/turbo/tiling/lora", params={"wait": 20}, json=payload, headers=headers)
request = r.json()
if not r.ok:
    raise RuntimeError(request["error"]["code"] + ": " + request["error"]["message"])

# Not finished yet: long-poll until it is
while request["status"] in ("queued", "running"):
    request = requests.get(API + "/requests/" + request["id"], params={"wait": 20}, headers=headers).json()
if request["status"] != "succeeded":
    raise RuntimeError(request["error"])
print([o["url"] for o in request["outputs"]], request["cost"]["credits"], "API credits", "$" + request["cost"]["usd"])
```

### MCP

The MCP server at `https://api.doitong.com/v1/mcp` exposes the tools `search_models`, `get_model`, `quote`, `run`, `get_request`, `cancel_request`, `list_requests`, `create_upload` and `get_account`. A `run` call for this model:

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "run",
    "arguments": {
      "model_id": "z-image/turbo/tiling/lora",
      "input": {
        "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
      },
      "wait_seconds": 20
    }
  }
}
```

## Response

Every call returns a request object. `status` is one of `queued`, `running`, `succeeded`, `failed`, `canceled`. `outputs` lists the generated files with URLs on our storage (kept forever, or 7 days with `?storage=temporary`; `storage` says which); `output` is the model's own result object with the same URLs.

```json
{
  "id": "req_8k2m4q7x1z9c3v5b6n0p2r4t",
  "object": "request",
  "model": "z-image/turbo/tiling/lora",
  "status": "succeeded",
  "created_at": "2026-10-20T12:00:00Z",
  "started_at": "2026-10-20T12:00:02Z",
  "completed_at": "2026-10-20T12:00:09Z",
  "queue_position": null,
  "cost": {
    "credits": 25,
    "usd": "0.025",
    "charged": 25,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "images": [
      {
        "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
        "content_type": "image/jpeg",
        "file_name": "0-output.jpeg",
        "file_size": 1843200,
        "width": 1024,
        "height": 768
      }
    ],
    "timings": {},
    "seed": 42,
    "has_nsfw_concepts": [
      false
    ],
    "prompt": "string"
  },
  "outputs": [
    {
      "type": "image",
      "url": "https://content.doitong.com/dev-api/2026/10/20/req_8k2m4q7x1z9c3v5b6n0p2r4t/0-output.jpeg",
      "content_type": "image/jpeg",
      "file_size": 1843200,
      "width": 1024,
      "height": 768,
      "stored": true
    }
  ],
  "error": null,
  "metrics": {
    "inference_seconds": 6.8
  },
  "urls": {
    "self": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t",
    "cancel": "https://api.doitong.com/v1/requests/req_8k2m4q7x1z9c3v5b6n0p2r4t/cancel"
  }
}
```

### Output fields (`output`)

| Field | Type | Description |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} | Ģenerēto attēlu failu informācija. |
| `timings` | object | Ģenerēšanas procesa laika informācija. |
| `seed` | integer | Attēla ģenerēšanas sēkla, tostarp nejauši izvēlētā vērtība, ja ievadē sēkla nebija norādīta; pretējā gadījumā atkārto norādīto vērtību. |
| `has_nsfw_concepts` | array of boolean | Norāda, vai ģenerētajos attēlos parādās NSFW koncepcijas. |
| `prompt` | string | Attēla ģenerēšanas laikā izmantotā uzvedne. |

## Related models

- [Z Image Base](https://doitong.com/developers/models/z-image/base.md) (`z-image/base`): $0.01 / megapixel
- [Z Image Base Lora](https://doitong.com/developers/models/z-image/base/lora.md) (`z-image/base/lora`): $0.012 / megapixel
- [Z Image Turbo](https://doitong.com/developers/models/z-image/turbo.md) (`z-image/turbo`): $0.005 / megapixel
- [Z Image Turbo Lora](https://doitong.com/developers/models/z-image/turbo/lora.md) (`z-image/turbo/lora`): $0.0085 / megapixel
- [Z-Image Turbo Seamless Tiling](https://doitong.com/developers/models/z-image/turbo/tiling.md) (`z-image/turbo/tiling`): $0.02 / megapixel of output image
- [Z Image Turbo Controlnet](https://doitong.com/developers/models/z-image/turbo/controlnet.md) (`z-image/turbo/controlnet`): $0.013 / image
- [Z Image Turbo Controlnet Lora](https://doitong.com/developers/models/z-image/turbo/controlnet/lora.md) (`z-image/turbo/controlnet/lora`): $0.04 / image
- [Z Image Turbo Image To Image](https://doitong.com/developers/models/z-image/turbo/image-to-image.md) (`z-image/turbo/image-to-image`): $0.015 / image

## Links

- HTML page: https://doitong.com/developers/models/z-image/turbo/tiling/lora
- All models and guides for AI agents: https://doitong.com/developers/llms.txt
- OpenAPI 3.1 with this model's typed request body: https://doitong.com/developers/openapi.json?model=z-image/turbo/tiling/lora
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/z-image/turbo/tiling/lora