# Scenario Texture Upscale — API Reference

Model ID: `model_sc-upscale-flux-texture`

---

## Authentication

- **API_KEY** and **API_SECRET** are found in your [Scenario Project Settings](https://app.scenario.com/team&tab=api_keys) under API Keys.
- Set them as environment variables `SCENARIO_SDK_API_KEY` and `SCENARIO_SDK_API_SECRET` — both SDKs pick them up by default.
- For raw HTTP (cURL), use Basic Auth: `Authorization: Basic base64("<API_KEY>:<API_SECRET>")`.

### Install the SDK

- JavaScript / TypeScript: `npm install @scenario-labs/sdk`
- Python: `pip install scenario-sdk`

---

## Generate

**Endpoint:** `POST https://api.cloud.scenario.com/v1/generate/custom/model_sc-upscale-flux-texture`

### Parameters

| Parameter | Type | Required | Default | Description |
|-----------|------|----------|---------|-------------|
| `image` | assetId | yes | - | The texture image you want to upscale. |
| `upscaleFactor` | number | - | `2` | How much to enlarge the image. The model adds real new detail up to 4096x4096px (for example, a 2048x2048 image at 2x); beyond that size it enlarges without inventing new detail. |
| `preset` | string | - | `balanced` | A quick starting point that sets Structure Fidelity and Strength together. Precise stays closest to the original, Creative adds the most new detail, Balanced sits between. |
| `loras` | model[] | - | `` | Optional add-on style models (LoRAs) to apply while upscaling, by ID or URL. Add up to 10. |
| `lorasScale` | number[] | - | `` | How strongly each LoRA is applied, in the same order as the models above. |
| `prompt` | string | - | `` | Optional text describing the texture or the detail you want emphasized as it's enhanced. |
| `imagePrompt` | assetId[] | - | - | Optional images to guide the visual style of the result. Add up to 4. |
| `imagePromptStrength` | number | - | `0.6` | How closely the result follows your style images. Higher values match them more tightly. |
| `controlnetConditioningScale` | number | - | `0.4` | How closely the result preserves the original image's structure. Higher values stay truer to the original layout and shapes. |
| `strength` | number | - | `0.4` | How much new, imaginative detail the model adds. Higher values invent more; lower values stay faithful to the source. |
| `numInferenceSteps` | number | - | `28` | How many refinement passes the model makes. More can improve quality but take longer. |
| `detailsEnable` | boolean | - | `true` | Sharpens and enhances fine details in the result. On by default. |
| `baseModel` | string | - | `FLUX.1-dev` | The base model to use: Stylized (Flux Dev) for artistic or illustrated textures, Realism (Flux Krea Dev) for photographic ones. |
| `seed` | number | - | - | A number that makes results repeatable. Reusing the same seed and settings produces the same image; leave it empty for a random result each time. |

### Example Requests

**cURL**

```bash
curl -X POST "https://api.cloud.scenario.com/v1/generate/custom/model_sc-upscale-flux-texture" \
  -H "Authorization: Basic $(echo -n '<API_KEY>:<API_SECRET>' | base64)" \
  -H "Content-Type: application/json" \
  --data-binary @- <<'EOF'
{
  "image": "<asset_id>",
  "upscaleFactor": 2,
  "preset": "balanced",
  "lorasScale": [],
  "prompt": "",
  "imagePromptStrength": 0.6,
  "controlnetConditioningScale": 0.4,
  "strength": 0.4,
  "numInferenceSteps": 28,
  "detailsEnable": true,
  "baseModel": "FLUX.1-dev"
}
EOF
```

**Python**

```python
import os
from scenario_sdk import Scenario

client = Scenario(
    api_key=os.environ.get("SCENARIO_SDK_API_KEY"),
    api_secret=os.environ.get("SCENARIO_SDK_API_SECRET"),
)

body = {
    "image": "<asset_id>",
    "upscaleFactor": 2,
    "preset": "balanced",
    "lorasScale": [],
    "prompt": "",
    "imagePromptStrength": 0.6,
    "controlnetConditioningScale": 0.4,
    "strength": 0.4,
    "numInferenceSteps": 28,
    "detailsEnable": True,
    "baseModel": "FLUX.1-dev"
}

response = client.generate.run_model(
    model_id="model_sc-upscale-flux-texture",
    body=body,
)
print(response)
```

**JavaScript**

```javascript
import Scenario from "@scenario-labs/sdk";

const client = new Scenario({
  apiKey: process.env["SCENARIO_SDK_API_KEY"],
  apiSecret: process.env["SCENARIO_SDK_API_SECRET"],
});

const body = {
  "image": "<asset_id>",
  "upscaleFactor": 2,
  "preset": "balanced",
  "lorasScale": [],
  "prompt": "",
  "imagePromptStrength": 0.6,
  "controlnetConditioningScale": 0.4,
  "strength": 0.4,
  "numInferenceSteps": 28,
  "detailsEnable": true,
  "baseModel": "FLUX.1-dev"
};

const response = await client.generate.runModel("model_sc-upscale-flux-texture", { body });
console.info(response);
```

---

## Retrieve Results

After submitting a generation request, you receive a `jobId`. Poll the job until `job.status` is `"success"`. The generated asset IDs are in `job.metadata.assetIds`.

**Endpoint:** `GET https://api.cloud.scenario.com/v1/jobs/{jobId}`

### Example Requests

**cURL**

```bash
curl -X GET "https://api.cloud.scenario.com/v1/jobs/<JOB_ID>" \
  -H "Authorization: Basic $(echo -n '<API_KEY>:<API_SECRET>' | base64)"
```

**Python**

```python
job = client.jobs.retrieve(job_id="<JOB_ID>")
print(job.status)
print(job.metadata.asset_ids)
```

**JavaScript**

```javascript
// Option 1 — wait on the response from runModel using the SDK helper
const completed = await response.job.wait();
console.info(completed.status);
console.info(completed.metadata?.assetIds);

// Option 2 — retrieve a job by its ID
const job = await client.jobs.retrieve("<JOB_ID>");
console.info(job.status);
console.info(job.metadata?.assetIds);
```

**Example response:**

```json
{
  "job": {
    "jobId": "job_abc123",
    "status": "success",
    "metadata": {
      "assetIds": [
        "asset_abc123"
      ]
    }
  }
}
```

> **Important:** Generated asset URLs are **temporary** and expire after a short period. Download and store any images you wish to keep before the URL expires. More info: [Content Delivery Network (CDN)](https://docs.scenario.com/get-started/documentation/content-delivery-network-cdn).

---

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