# PhotoMaker API

> Personalized na pagbuo ng portrait mula sa archive ng mga reference na larawan, na may estilo preset at opsyonal na img2img

Gumagawa ng mga bagong larawan ng isang tao mula sa zip-style archive ng mga larawan niya (`image_archive_url`) kasama ang kinakailangang teksto na `prompt`. Piliin ang `photomaker` o `photomaker-style` base pipeline, at pumili sa 11 estilo gaya ng Cinematic, Comic book o Line art. Sinusuportahan ang 1 hanggang 4 na larawan bawat kahilingan, 20 hanggang 100 inference hakbang, guidance mula 1 hanggang 10, at opsyonal na initial na larawan na may `initial_image_strength` sa pagitan ng 0 at 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/fil/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 |  |  | Magbigay ng mga larawang gagamitin sa archive, na tinutukoy ng URL nito. |
| `prompt` |  | string | yes |  |  | Ilarawan ang larawang gusto mong mabuo, gamit ang pinakamaraming posibleng detalye para sa pinakamagandang resulta. |
| `base_pipeline` |  | enum (string) | no | `photomaker` | `photomaker`, `photomaker-style` | Base pipeline na ginagamit para sa pagbuo ng larawan. |
| `initial_image_url` |  | string (image URL) \| null | no |  |  | Opsyonal na panimulang larawan para sa img2img processing. |
| `initial_image_strength` |  | number | no | `0.5` | 0 – 1 | Noise level ng latent larawan, mula sa walang idinagdag na noise sa O hanggang sa maximum sa 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 | `` |  | Negative prompt na tumutukoy sa hindi gustong detalye ng larawan. Maaari nitong alisin ang mga kulay, bagay, tanawin, o maliliit na feature at katangian gaya ng bigote, blur, o mababang resolution. |
| `num_inference_steps` |  | integer | no | `50` | 20 – 100 | Kinokontrol kung ilang pagbuo step ang ginagawa ng Stable Diffusion; maaaring magbigay ang karagdagang step ng mas detalyadong final na larawan. |
| `style_strength` |  | integer | no | `20` | 15 – 50 |  |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Itakda kung ilang larawan ang bubuuin ng isang kahilingan, na nagbibigay ng mas mahabang oras ng pagbuo para sa mas malaking batch. |
| `guidance_scale` |  | number | no | `5` | 1 – 10 | Lakas ng pagsunod sa prompt para sa pagpili ng larawan, na ipinapahayag bilang CFG (Classifier Free Guidance). |
| `seed` |  | integer \| null | no |  |  | Seed para muling makabuo ng mga larawan sa Stable Diffusion. Eksaktong mauulit ang isang larawan sa bawat run kung hindi babaguhin ang bersyon ng modelo, prompt, at seed. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Maaaring luwagan ang screening sa pamamagitan ng pagtatakda ng false, kung awtorisado ang tumatawag. |

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

- [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/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