# Hidream I1 Full API

> HiDream-I1 Full text-to-image na may guidance scale at suporta sa LoRA, 50 default na hakbang

Ang full-hakbang na bersyon ng HiDream-I1 para sa text-to-image. Default nito ang 50 inference hakbang at nagdaragdag ng `guidance_scale` mula 0 hanggang 20 (default 5) at listahan ng `loras` para sa paglalapat ng LoRA. Tumatanggap din ito ng negative prompt, `seed`, preset o custom na `image_size`, at 1 hanggang 4 na larawan bawat kahilingan, sa jpeg o png.

- Model id: `hidream-i1-full`
- Made by: HiDream
- Category: Text to Image
- Output: image
- Price: $0.05 / megapixel (cheapest run $0.05 (50 API credits))
- Run: `POST https://api.doitong.com/v1/run/hidream-i1-full`
- Quote: `POST https://api.doitong.com/v1/quote/hidream-i1-full`
- Docs page: https://doitong.com/fil/developers/models/hidream-i1-full

## Pricing

Price: **$0.05 / megapixel**. Billed per megapixel of output (width × height of every image). Each image is rounded up to a whole megapixel.

The full example input below costs $0.05 = 50 API credits (1 MP × 50 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/hidream-i1-full` 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 |  |  | Prompt na gumagabay sa pagbuo ng larawan. |
| `negative_prompt` |  | string | no | `` |  | Negative prompt na tumutukoy sa mga detalyeng dapat alisin sa larawan, kabilang ang mga kulay, bagay, tanawin, o maliliit na feature. Kabilang sa mga halimbawa ang bigote, blur, o mababang resolution. |
| `image_size` |  | object {width, height} \| enum (string) | no | `{"height":1024,"width":1024}` | `square_hd`, `square`, `portrait_4_3`, `portrait_16_9`, `landscape_4_3`, `landscape_16_9` | Mga dimension ng nabuong larawan. |
| `num_inference_steps` |  | integer | no | `50` | 1 – 50 | Bilang ng inference step na isasagawa. |
| `seed` |  | integer \| null | no |  |  | Seed para sa nauulit na mga larawan: ang magkaparehong prompt at seed ay gumagawa ng magkaparehong larawan kapag hindi nagbago ang bersyon ng modelo. |
| `guidance_scale` |  | number | no | `5` | 0 – 20 | Lakas ng pagsunod sa prompt para sa pagpili ng larawan, na ipinapahayag bilang CFG (Classifier Free Guidance). |
| `num_images` | `num_outputs` | integer | no | `1` | 1 – 4 | Bilang ng larawang hinihingi para sa pagbuo. |
| `enable_safety_checker` |  | boolean | no | `true` |  | Safety checking na nagbabalik ng mga itim na larawan kapalit ng mga larawang na-flag na unsafe. Pinapagana ng true ang checking; dini-disable ito ng false para lamang sa mga awtorisadong account, habang sinusuri pa rin ang mga kahilingang walang authorization. |
| `output_format` |  | enum (string) | no | `jpeg` | `jpeg`, `png` | File format ng resultang larawan. |
| `loras` |  | array of object {path, weight_name, scale} \| null | no | `[]` |  | Tumukoy ng path at scale para sa bawat LoRA na nais mong ilapat sa modelo. Ibigay ang mga ito bilang listahan, at maaaring magsama ng weight name para sa bawat entry. |
| `loras[].path` |  | string | yes |  |  | Lokasyon ng LoRA weights, na tinutukoy bilang URL o path. |
| `loras[].weight_name` |  | string \| null | no |  |  | LoRA weight name, kinakailangan lamang kapag may higit sa 1 safetensors file ang isang Hugging Face repository. Ginagamit lamang ang pangalang ito kapag tumutukoy ang `path` sa naturang repository. |
| `loras[].scale` |  | number | no | `1` | 0 – 4 | Multiplier na inilalapat sa LoRA weight bago ito i-merge sa base modelo. |

## 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/hidream-i1-full?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/hidream-i1-full?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/hidream-i1-full", 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": "hidream-i1-full",
      "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": "hidream-i1-full",
  "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": 50,
    "usd": "0.05",
    "charged": 50,
    "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",
        "width": 1024,
        "height": 768,
        "content_type": "image/jpeg"
      }
    ],
    "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, width, height, content_type} | Impormasyon ng file para sa mga nabuong larawan. |
| `timings` | object |  |
| `seed` | integer | Seed para sa pagbuo ng larawan, kasama ang random na napiling value kung walang seed sa input; kung hindi, inuulit nito ang ibinigay na value. |
| `has_nsfw_concepts` | array of boolean | Nagsasaad kung may mga konseptong NSFW sa nabuong mga larawan. |
| `prompt` | string | Prompt na ginagamit sa pagbuo ng larawan. |

## Related models

- [Hidream I1 Full · Image to Image](https://doitong.com/developers/models/hidream-i1-full/image-to-image.md) (`hidream-i1-full/image-to-image`): $0.10 / 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
- [Ideogram V4.5](https://doitong.com/developers/models/ideogram/v4.5.md) (`ideogram/v4.5`): from $0.03 / image
- [Nano Banana 2](https://doitong.com/developers/models/nano-banana-2.md) (`nano-banana-2`): from $0.06 / image

## Links

- HTML page: https://doitong.com/developers/models/hidream-i1-full
- 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=hidream-i1-full
- Errors: https://doitong.com/developers/docs/errors
- Model details as JSON: https://api.doitong.com/v1/models/hidream-i1-full