# Fooocus API

> 文生图模型，支持风格预设、LoRA 合并、细化器选项和基于图像的控制模式

使用 Fooocus 及其默认风格栈根据提示词生成图像。选择 `performance` 模式（Speed、Quality、Extreme Speed、Lightning），设置 `sharpness` 和 `aspect_ratio`，并请求 1 到 4 张图像。最多可合并 5 个 LoRA，可选控制图像支持 ImagePrompt、PyraCanny、CPDS 或 FaceSwap 引导。输出格式为 png、jpeg 或 webp。

- Model id: `fooocus`
- Made by: Open model
- Category: Text to Image
- Output: image
- Estimated price per run: $0.444 / image (cheapest run $0.444 (444 API credits))
- Run: `POST https://api.doitong.com/v1/run/fooocus`
- Quote: `POST https://api.doitong.com/v1/quote/fooocus`
- Docs page: https://doitong.com/zh-CN/developers/models/fooocus

## Pricing

Price: **$0.444 / image**. Estimated from the typical cost of one run, per output (`num_images`). The quote is exactly what the run charges.

The full example input below costs $0.444 = 444 API credits (1 image × 444 API credits).

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/fooocus` 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 | no | `` |  | 描述要生成的图像；尽可能提供详细信息以获得最佳结果。 |
| `negative_prompt` |  | string | no | `` |  | 指定要排除的图像细节的负面提示词，包括颜色、对象、场景或更细致的特征。例如胡须、模糊或低分辨率。 |
| `styles` |  | array of enum (string) | no | `["Fooocus Enhance","Fooocus Sharp","Fooocus V2"]` |  | 生成期间应用的风格。 |
| `performance` |  | enum (string) | no | `Extreme Speed` | `Speed`, `Quality`, `Extreme Speed`, `Lightning` | 性能选项：Speed 或 Quality。 |
| `guidance_scale` |  | number | no | `4` | 1 – 30 | 图像选择的提示词遵循强度，以 CFG（Classifier Free Guidance）表示。 |
| `sharpness` |  | number | no | `2` | 0 – 30 | 输出图像的锐度设置。提高该值会使图像及其纹理更加锐利。 |
| `aspect_ratio` |  | string | no | `1024x1024` |  | 输出图像尺寸，可从预设中选择，或指定自定义宽度和高度。两个自定义尺寸都必须能被 8 整除。 |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | 每个请求生成的图像数量。 |
| `loras` |  | array of object {path, scale} | no | `[{"path":"https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0/resolve/main/sd_xl_offset_example-lora_1.0.safetensors","scale":0.1}]` |  | 合并用于最终图像生成的 LoRA，最多 5 个 LoRA。 |
| `loras[].path` |  | string | yes |  |  | LoRA 权重的位置，以 URL 或路径指定。 |
| `loras[].scale` |  | number | no | `0.1` | 0 – 1 | 合并到基础模型前应用于 LoRA 权重的倍数。 |
| `refiner_model` |  | enum (string) | no | `None` | `None`, `realisticVisionV60B1_v51VAE.safetensors` | 精修器选择：SDXL 或 SD 1.5。 |
| `refiner_switch` |  | number | no | `0.8` | 0 – 1 | 精修器切换值：真实感 SD1.5 模型使用 0.4，动漫 SD1.5 模型使用 0.667，XL-refiners 使用 0.8。在两个 SDXL 模型之间切换时可使用任意值。 |
| `output_format` |  | enum (string) | no | `jpeg` | `png`, `jpeg`, `webp` | 生成图像的文件格式。 |
| `seed` |  | integer \| null | no |  |  | 用于在 Stable Diffusion 中复现图像的种子。保持模型版本、提示词和种子不变，即可在每次运行中完全复现图像。 |
| `control_image_url` |  | string (image URL) \| null | no |  |  | 用于引导图像生成的参考图像。 |
| `control_type` |  | enum (string) | no | `PyraCanny` | `ImagePrompt`, `PyraCanny`, `CPDS`, `FaceSwap` | 图像控制方法。 |
| `control_image_weight` |  | number | no | `1` | 0 – 2 | 控制图像强度，用于确定输出与控制图像之间的相似程度。 |
| `control_image_stop_at` |  | number | no | `1` | 0 – 1 | 控制图像停止值，用于控制输出与控制图像的相似程度。 |
| `inpaint_image_url` |  | string (image URL) \| null | no |  |  | 修复过程中使用的参考图像。 |
| `mask_image_url` |  | string (image URL) \| null | no |  |  | 图像生成期间应用的蒙版图像。 |
| `mixing_image_prompt_and_inpaint` |  | boolean | no | `false` |  |  |
| `enable_safety_checker` |  | boolean | no | `true` |  | 安全检查开关：只有经过账户授权时，false 才会禁用检查。没有该授权的请求始终会进行检查，不安全图像会被替换为黑色图像。 |

File parameters (`control_image_url`, `inpaint_image_url`, `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
{}
```

A fuller example:

```json
{
  "prompt": ""
}
```

## 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/fooocus?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "prompt": ""
  }'

# 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/fooocus?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "prompt": ""
  }),
});
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": "",
}

# Run the model; wait up to 20 s for the finished result in the same call
r = requests.post(API + "/run/fooocus", 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": "fooocus",
      "input": {
        "prompt": ""
      },
      "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": "fooocus",
  "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": 444,
    "usd": "0.444",
    "charged": 444,
    "refunded": 0
  },
  "input": {
    "prompt": ""
  },
  "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": {},
    "has_nsfw_concepts": [
      false
    ]
  },
  "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} | 生成图像的文件信息。 |
| `timings` | object | 生成耗时。 |
| `has_nsfw_concepts` | array of boolean | 指示生成的图像中是否出现 NSFW 概念。 |

## Related models

- [Fooocus Image Prompt](https://doitong.com/developers/models/fooocus/image-prompt.md) (`fooocus/image-prompt`): $0.085 / image
- [Fooocus Inpainting](https://doitong.com/developers/models/fooocus/inpaint.md) (`fooocus/inpaint`): $0.055 / image
- [Fooocus Upscale or Vary](https://doitong.com/developers/models/fooocus/upscale-or-vary.md) (`fooocus/upscale-or-vary`): $0.007 / image
- [FLUX.1 \[dev\]](https://doitong.com/developers/models/flux/dev.md) (`flux/dev`): $0.025 / megapixel
- [FLUX.1 \[schnell\]](https://doitong.com/developers/models/flux/schnell.md) (`flux/schnell`): $0.003 / megapixel
- [FLUX.2 \[dev\]](https://doitong.com/developers/models/flux-2.md) (`flux-2`): $0.012 / megapixel
- [FLUX.2 \[pro\]](https://doitong.com/developers/models/flux-2-pro.md) (`flux-2-pro`): $0.015 / megapixel of output image
- [GPT Image 2.5 Text to Image](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/text-to-image.md) (`openai/gpt-image-2.5/flare/text-to-image`): from $0.008 / image

## Links

- HTML page: https://doitong.com/developers/models/fooocus
- 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=fooocus
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/fooocus