# PhotoMaker API

> Génération de portraits personnalisés à partir d’une archive de photos de référence, avec préréglages de style et img2img facultatif

Crée de nouvelles images d’une personne à partir d’une archive de type zip de ses photos (`image_archive_url`) et d’un `prompt` textuel obligatoire. Choisissez le pipeline de base `photomaker` ou `photomaker-style`, puis l’un des 11 styles comme Cinematic, Comic book ou Line art. Prend en charge 1 à 4 images par requête, 20 à 100 étapes d’inférence, un guidage de 1 à 10 et une image initiale facultative avec `initial_image_strength` entre 0 et 1.

- Model id: `photomaker`
- Made by: Tencent
- Category: Image Editing
- Output: image
- Estimated price per run: $0.022 / image (cheapest run $0.022 (22 API credits))
- Run: `POST https://api.doitong.com/v1/run/photomaker`
- Quote: `POST https://api.doitong.com/v1/quote/photomaker`
- Docs page: https://doitong.com/fr/developers/models/photomaker

## Pricing

Price: **$0.022 / 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 $0.022 = 22 API credits (1 image × 22 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/photomaker` 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 |
|---|---|---|---|---|---|---|
| `image_archive_url` |  | string | yes |  |  | Fournissez les images à utiliser dans une archive, en indiquant leur URL. |
| `prompt` |  | string | yes |  |  | Décrivez l’image que vous souhaitez générer avec le plus de détails possible pour obtenir les meilleurs résultats. |
| `base_pipeline` |  | enum (string) | no | `photomaker` | `photomaker`, `photomaker-style` | Pipeline de base utilisé pour la génération d’image. |
| `initial_image_url` |  | string (image URL) \| null | no |  |  | Image de départ facultative pour le traitement img2img. |
| `initial_image_strength` |  | number | no | `0.5` | 0 – 1 | Niveau de bruit de l’image latente, allant de l’absence de bruit ajouté à O jusqu’au maximum à 1. |
| `style` |  | enum (string) | no | `Photographic` | `(No style)`, `Cinematic`, `Disney Character`, `Digital Art`, `Photographic`, `Fantasy art`, `Neonpunk`, `Enhance`, `Comic book`, `Lowpoly`, `Line art` |  |
| `negative_prompt` |  | string | no | `` |  | Prompt négatif indiquant les détails d’image indésirables. Il peut exclure les couleurs, les objets, le décor ou des caractéristiques et qualités plus fines, comme une moustache, du flou ou une faible résolution. |
| `num_inference_steps` |  | integer | no | `50` | 20 – 100 | Contrôle le nombre d'étapes de génération effectuées par Stable Diffusion ; des étapes supplémentaires peuvent produire une image finale plus détaillée. |
| `style_strength` |  | integer | no | `20` | 15 – 50 |  |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Définissez le nombre d'images produites par une requête, en permettant un temps de génération plus long pour un lot plus important. |
| `guidance_scale` |  | number | no | `5` | 1 – 10 | Force d'adhérence au prompt pour la sélection d'image, exprimée comme CFG (Classifier Free Guidance). |
| `seed` |  | integer \| null | no |  |  | Graine permettant de reproduire des images dans Stable Diffusion. Une image peut être reproduite exactement à chaque exécution en conservant la version du modèle, le prompt et la graine inchangés. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Le filtrage peut être assoupli en définissant false, si l'appelant est autorisé. |

File parameters (`initial_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
{
  "image_archive_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "prompt": "A red fox trots through fresh snow at sunrise, soft golden light, shallow depth of field"
}
```

A fuller example:

```json
{
  "image_archive_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
  "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/photomaker?wait=20" \
  -H "Authorization: Bearer $DOITONG_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "image_archive_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/photomaker?wait=20", {
  method: "POST",
  headers,
  body: JSON.stringify({
    "image_archive_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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 = {
    "image_archive_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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/photomaker", 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": "photomaker",
      "input": {
        "image_archive_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
        "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": "photomaker",
  "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": 22,
    "usd": "0.022",
    "charged": 22,
    "refunded": 0
  },
  "input": {
    "image_archive_url": "https://content.doitong.com/images/showcase/v3/gen_fox_cartoon.jpg",
    "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
      }
    ],
    "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 |
|---|---|---|
| `images` | array of object {url, content_type, file_name, file_size, width, height} |  |
| `seed` | integer |  |

## Related models

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- [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/photomaker
- 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=photomaker
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/photomaker