# IP Adapter Face ID API

> Menghasilkan gambar yang mencocokkan wajah dari satu foto atau zip foto, pada basis SD 1.5 atau SDXL

Mempersonalisasi generasi berdasarkan wajah yang diberikan sebagai `face_image_url`, atau sebagai zip beberapa wajah melalui `face_images_data_url` yang embedding-nya dirata-ratakan. `model_type` memilih antara varian SD 1.5 dan SDXL, dan checkpoint dasar dapat diubah dengan parameter repo. `width` dan `height` berada dalam rentang 512 hingga 1024, dan `num_inference_steps` hingga 200.

- Model id: `ip-adapter-face-id`
- Made by: Tencent
- Category: Image Editing
- Output: image
- Estimated price per run: $0.015 / image (cheapest run $0.06 (60 API credits))
- Run: `POST https://api.doitong.com/v1/run/ip-adapter-face-id`
- Quote: `POST https://api.doitong.com/v1/quote/ip-adapter-face-id`
- Docs page: https://doitong.com/id/developers/models/ip-adapter-face-id

## Pricing

Price: **$0.015 / image**. Estimated from the typical cost of one run, per output (`num_samples`). The quote is exactly what the run charges.

The full example input below costs $0.06 = 60 API credits (4 images × 15 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/ip-adapter-face-id` 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

| Parameter | Canonical name | Type | Required | Default | Allowed values / range | Description |
|---|---|---|---|---|---|---|
| `model_type` |  | enum (string) | no | `1_5-v1` | `1_5-v1`, `1_5-v1-plus`, `1_5-v2-plus`, `SDXL-v1`, `SDXL-v2-plus`, `1_5-auraface-v1` | Pemilihan model, dengan 1_5 sebagai bawaan sekaligus pilihan yang direkomendasikan untuk sebagian besar penggunaan. |
| `prompt` |  | string | yes |  |  | Jelaskan gambar yang ingin dibuat sedetail mungkin untuk memperoleh hasil terbaik. |
| `face_image_url` |  | string (image URL) \| null | no |  |  | Gambar referensi pencocokan wajah, diskalakan dan dipangkas menjadi 640x640 setiap kali dimensinya berbeda dari ukuran tersebut. |
| `face_images_data_url` |  | string \| null | no |  |  | URL arsip zip gambar wajah, digunakan untuk membuat ID wajah yang lebih akurat dengan merata-ratakan embedding dari gambar yang diarsipkan. |
| `negative_prompt` |  | string | no | `blurry, low resolution, bad, ugly, low quality, pixelated, interpolated, compression artifacts, noisey, grainy` |  | Negative prompt yang menentukan detail gambar yang tidak diinginkan. Prompt ini dapat mengecualikan warna, objek, pemandangan, atau fitur dan kualitas yang lebih halus, seperti kumis, buram, atau resolusi rendah. |
| `seed` |  | integer \| null | no |  |  | Seed untuk mereproduksi gambar dalam Stable Diffusion. Gambar dapat direproduksi secara persis pada setiap proses dengan mempertahankan versi model, prompt, dan seed. |
| `guidance_scale` |  | number | no | `7.5` | 0 – 16 | Kekuatan kepatuhan terhadap prompt untuk pemilihan gambar, dinyatakan sebagai CFG (Classifier Free Guidance). |
| `num_inference_steps` |  | integer | no | `50` | 1 – 200 | Jumlah langkah inferensi pembuatan gambar, dengan kualitas gambar yang lebih baik pada jumlah lebih besar tetapi waktu pembuatan lebih lama. |
| `num_samples` |  | integer | no | `4` | 1 – 4 | Jumlah sampel untuk ID wajah, dengan bawaan 4. Meningkatkan jumlah ini memperbaiki kualitas gambar, tetapi memperpanjang waktu pembuatan. |
| `width` |  | integer | no | `512` | 512 – 1,024 | Lebar gambar yang dihasilkan. |
| `height` |  | integer | no | `512` | 512 – 1,024 | Tinggi gambar yang dihasilkan. |
| `face_id_det_size` |  | integer | no | `640` | 64 – 640 | Atur ukuran model deteksi wajah, kurangi jika model tidak dapat menemukan wajah dalam gambar Anda. Pengaturan yang lebih besar memberikan deteksi yang lebih akurat, tetapi berjalan lebih lambat dan lebih mungkin sama sekali tidak menemukan wajah. |
| `base_1_5_model_repo` |  | string | no | `SG161222/Realistic_Vision_V4.0_noVAE` |  | URL model Base 1.5; bawaannya `SG161222/Realistic_Vision_V4.0_noVAE`. |
| `base_sdxl_model_repo` |  | string | no | `SG161222/RealVisXL_V3.0` |  | URL model Base SDXL; bawaannya `SG161222/RealVisXL_V3.0`. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Penyaringan dapat dilonggarkan dengan menetapkan false, jika pemanggil berwenang. |

File parameters (`face_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/ip-adapter-face-id?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/ip-adapter-face-id?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/ip-adapter-face-id", 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": "ip-adapter-face-id",
      "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": "ip-adapter-face-id",
  "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": 60,
    "usd": "0.06",
    "charged": 60,
    "refunded": 0
  },
  "input": {
    "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
  },
  "output": {
    "image": {
      "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
    },
    "seed": 42
  },
  "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 |
|---|---|---|
| `image` | object {url, content_type, file_name, file_size, width, height} | Informasi file untuk gambar yang dihasilkan. |
| `seed` | integer | Seed pembuatan gambar, termasuk nilai yang dipilih secara acak jika input tidak menyertakan seed; jika tidak, nilai yang diberikan akan diulang. |

## Related models

- [FLUX.1 Kontext \[pro\]](https://doitong.com/developers/models/flux-pro/kontext.md) (`flux-pro/kontext`): $0.04 / image
- [GPT Image 2.5 Edit](https://doitong.com/developers/models/openai/gpt-image-2.5/flare/edit.md) (`openai/gpt-image-2.5/flare/edit`): from $0.12 / image
- [Nano Banana 2 Edit](https://doitong.com/developers/models/nano-banana-2/edit.md) (`nano-banana-2/edit`): from $0.06 / image
- [Nano Banana Pro Edit](https://doitong.com/developers/models/nano-banana-pro/edit.md) (`nano-banana-pro/edit`): from $0.15 / image
- [Qwen Image 3 Edit](https://doitong.com/developers/models/alibaba/qwen-image-3/edit.md) (`alibaba/qwen-image-3/edit`): from $0.04 / image
- [Seedream 5.0 Pro Edit](https://doitong.com/developers/models/bytedance/seedream/v5/pro/edit.md) (`bytedance/seedream/v5/pro/edit`): from $0.0675 / run of output image
- [Hunyuan Image · v3 · Instruct · Edit](https://doitong.com/developers/models/hunyuan-image/v3/instruct/edit.md) (`hunyuan-image/v3/instruct/edit`): $0.174 / image
- [Hunyuan World](https://doitong.com/developers/models/hunyuan_world.md) (`hunyuan_world`): $0.15 / image

## Links

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