# 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=project_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(":")`. ### 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 | - | Image to upscale | | `upscaleFactor` | number | - | `2` | Upscale factor | | `preset` | string | - | `balanced` | Select a preset to apply a set of parameters | | `loras` | model[] | - | `` | List of one or more LoRA model IDs or URLs. | | `lorasScale` | number[] | - | `` | Scales for the LoRA weights | | `prompt` | string | - | `` | Prompt | | `imagePrompt` | assetId[] | - | - | Upload up to 4 images to guide the style of the output. | | `imagePromptStrength` | number | - | `0.6` | Higher fidelity keeps the enhanced image's style closely aligned with the style images | | `controlnetConditioningScale` | number | - | `0.4` | Higher values better preserve the structure of the input image. | | `strength` | number | - | `0.4` | Higher values introduce more imaginative elements to the output image. | | `numInferenceSteps` | number | - | `28` | The number of steps for the generation | | `detailsEnable` | boolean | - | `true` | Enhances fine details in the output image. | | `baseModel` | string | - | `FLUX.1-dev` | Use FLUX.1-dev for stylized images, and FLUX.1-Krea-dev for realistic images. | | `seed` | number | - | - | Seed used for reproduction | ### 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 ':' | base64)" \ -H "Content-Type: application/json" \ --data-binary @- <<'EOF' { "image": "", "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": "", "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": "", "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/" \ -H "Authorization: Basic $(echo -n ':' | base64)" ``` **Python** ```python job = client.jobs.retrieve(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(""); 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). --- *Generated by [Scenario](https://app.scenario.com)*