# Flux 2 Lora Gallery > Virtually furnishes an empty apartment ## Overview - **Endpoint**: `https://fal.run/fal-ai/flux-2-lora-gallery/apartment-staging` - **Model ID**: `fal-ai/flux-2-lora-gallery/apartment-staging` - **Category**: image-to-image - **Kind**: inference **Tags**: stylized, transform ## Pricing - **Price**: $0.021 per processed megapixels For more details, see [fal.ai pricing](https://fal.ai/pricing). ## API Information This model can be used via our HTTP API or more conveniently via our client libraries. See the input and output schema below, as well as the usage examples. ### Input Schema The API accepts the following input parameters: - **`image_urls`** (`list`, _required_): The URL of the empty room image to furnish. - Array of string - Examples: ["https://v3b.fal.media/files/b/tiger/58rkpMdBl7eqcxuZ8YRus.png"] - **`prompt`** (`string`, _required_): The prompt to generate a furnished room. Use 'furnish this room' for best results. - Examples: "Furnish this room with modern furniture and decor", "Furnish this empty apartment with cozy living room furniture", "Furnish this room with minimalist Scandinavian design" - **`image_size`** (`ImageSize | Enum`, _optional_): The size of the generated image. If not provided, the size of the input image will be used. - One of: ImageSize | Enum - **`guidance_scale`** (`float`, _optional_): The CFG (Classifier Free Guidance) scale. Controls how closely the model follows the prompt. Default value: `2.5` - Default: `2.5` - Range: `0` to `20` - **`num_inference_steps`** (`integer`, _optional_): The number of inference steps to perform. Default value: `40` - Default: `40` - Range: `4` to `50` - **`acceleration`** (`AccelerationEnum`, _optional_): Acceleration level for image generation. 'regular' balances speed and quality. Default value: `"regular"` - Default: `"regular"` - Options: `"none"`, `"regular"` - **`seed`** (`integer`, _optional_): Random seed for reproducibility. Same seed with same prompt will produce same result. - **`sync_mode`** (`boolean`, _optional_): If `True`, the media will be returned as a data URI and won't be saved in history. - Default: `false` - **`enable_safety_checker`** (`boolean`, _optional_): Whether to enable the safety checker for the generated image. Disabling it requires account authorization; unauthorized requests are always checked. Default value: `true` - Default: `true` - **`output_format`** (`OutputFormatEnum`, _optional_): The format of the output image Default value: `"png"` - Default: `"png"` - Options: `"png"`, `"jpeg"`, `"webp"` - **`num_images`** (`integer`, _optional_): Number of images to generate Default value: `1` - Default: `1` - Range: `1` to `4` - **`lora_scale`** (`float`, _optional_): The strength of the apartment staging effect. Default value: `1` - Default: `1` - Range: `0` to `2` **Required Parameters Example**: ```json { "image_urls": [ "https://v3b.fal.media/files/b/tiger/58rkpMdBl7eqcxuZ8YRus.png" ], "prompt": "Furnish this room with modern furniture and decor" } ``` **Full Example**: ```json { "image_urls": [ "https://v3b.fal.media/files/b/tiger/58rkpMdBl7eqcxuZ8YRus.png" ], "prompt": "Furnish this room with modern furniture and decor", "guidance_scale": 2.5, "num_inference_steps": 40, "acceleration": "regular", "enable_safety_checker": true, "output_format": "png", "num_images": 1, "lora_scale": 1 } ``` ### Output Schema The API returns the following output format: - **`images`** (`list`, _required_): The generated furnished room images - Array of Image - Examples: [{"url":"https://v3b.fal.media/files/b/panda/3J1ezJEhcDLwoC9P8imqj.png"}] - **`seed`** (`integer`, _required_): The seed used for generation - **`prompt`** (`string`, _required_): The prompt used for generation **Example Response**: ```json { "images": [ { "url": "https://v3b.fal.media/files/b/panda/3J1ezJEhcDLwoC9P8imqj.png" } ], "prompt": "" } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/flux-2-lora-gallery/apartment-staging \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "image_urls": [ "https://v3b.fal.media/files/b/tiger/58rkpMdBl7eqcxuZ8YRus.png" ], "prompt": "Furnish this room with modern furniture and decor" }' ``` ### Python Ensure you have the Python client installed: ```bash pip install fal-client ``` Then use the API client to make requests: ```python import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/flux-2-lora-gallery/apartment-staging", arguments={ "image_urls": ["https://v3b.fal.media/files/b/tiger/58rkpMdBl7eqcxuZ8YRus.png"], "prompt": "Furnish this room with modern furniture and decor" }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ### JavaScript Ensure you have the JavaScript client installed: ```bash npm install --save @fal-ai/client ``` Then use the API client to make requests: ```javascript import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/flux-2-lora-gallery/apartment-staging", { input: { image_urls: ["https://v3b.fal.media/files/b/tiger/58rkpMdBl7eqcxuZ8YRus.png"], prompt: "Furnish this room with modern furniture and decor" }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ## Additional Resources ### Documentation - [Model Playground](https://fal.ai/models/fal-ai/flux-2-lora-gallery/apartment-staging) - [API Documentation](https://fal.ai/models/fal-ai/flux-2-lora-gallery/apartment-staging/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/flux-2-lora-gallery/apartment-staging) ### fal.ai Platform - [Platform Documentation](https://fal.ai/docs/documentation) - [Python Client](https://fal.ai/docs/api-reference/client-libraries/python) - [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript) ### Other agent-readable surfaces This file covers one model. To find anything else: - [Platform overview](https://fal.ai/llms.txt): Entry points and representative endpoint IDs - [Documentation index](https://fal.ai/docs/llms.txt): Every documentation page - [Full documentation text](https://fal.ai/docs/llms-full.txt): The whole documentation inlined - Any other model: `https://fal.ai/models//llms.txt`