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ModelRunner

Layout Boost API

hakankaan/layout-boost

Rearrange a room's existing furniture — same pieces, only moved — to gain usable space and better flow.

Starts from $0.039 /run
2 model optionspublicpublished
OpenAPI

Wrapper Input

Input

External URL of the uploaded photo of a furnished room whose furniture should be rearranged.

How bold the rearrangement may be: precise = subtle nudges to the current layout, balanced = a moderate replan, creative = a complete replan. Never changes which furniture appears — only where it goes.

Min: 0.5 - Max: 1

Fine-grained rearrangement boldness used only when creativity is precise (0.5 = closest to the current layout, 1.0 = boldest precise replan).

Optional goals for the new layout, e.g. "make space for a desk near the window".

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Wrapper Output

Output

Fill in the input form and click submit to see the output
Logs (1 lines)

Pricing

Base ModelPricing ModeEffective Cost
nano-banana-2/editdefaultmegapixel tieredTiered pricing
nano-bananaper output0.039

Layout Boost API

Layout Boost is a image-to-image AI wrapper by hakankaan. On ModelRunner it runs through a REST API or via MCP from any AI assistant with pay-per-use pricing.

POST https://queue.modelrunner.run/hakankaan/layout-boost

cURL

# Submit a request to the queue. Input fields go at the top level of the
# body. The optional reserved "metadata" object holds your own flat string
# tags — stored on the request, never sent to the model; filter later with
# GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>.
curl -X POST https://queue.modelrunner.run/hakankaan/layout-boost \
  -H "Authorization: Key $MRUN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "file_url": "https://example.com/input.jpg",
    "creativity": "balanced",
    "metadata": {
      "project": "my-project"
    }
  }'
# → { "request_id": "...", "status_url": "...", "response_url": "..." }

# Poll status_url until "COMPLETED", then fetch the result
curl "https://queue.modelrunner.run/hakankaan/layout-boost/requests/$REQUEST_ID/status" \
  -H "Authorization: Key $MRUN_API_KEY"
curl "https://queue.modelrunner.run/hakankaan/layout-boost/requests/$REQUEST_ID" \
  -H "Authorization: Key $MRUN_API_KEY"

JavaScript

import { modelrunner } from "@modelrunner/client";

const result = await modelrunner.subscribe("hakankaan/layout-boost", {
  input: {
    "file_url": "https://example.com/input.jpg",
    "creativity": "balanced"
  },
});
console.log(result);

Python

import os
import requests

headers = {"Authorization": f"Key {os.environ['MRUN_API_KEY']}"}

submitted = requests.post(
    "https://queue.modelrunner.run/hakankaan/layout-boost",
    headers=headers,
    json={
      "file_url": "https://example.com/input.jpg",
      "creativity": "balanced"
    },
).json()

# Poll submitted["status_url"] until "COMPLETED", then:
result = requests.get(submitted["response_url"], headers=headers).json()

Input parameters

NameTypeRequiredDescription
file_urlstring (uri)yesExternal URL of the uploaded photo of a furnished room whose furniture should be rearranged.
creativityenumyesHow bold the rearrangement may be: precise = subtle nudges to the current layout, balanced = a moderate replan, creative = a complete replan. Never changes which furniture appears — only where it goes. Default: "balanced".
creativity_levelnumbernoFine-grained rearrangement boldness used only when creativity is precise (0.5 = closest to the current layout, 1.0 = boldest precise replan). Default: 0.7.
promptstringnoOptional goals for the new layout, e.g. "make space for a desk near the window".

Machine-readable: OpenAPI schema · llms.txt

Use Layout Boost from Claude & Cursor (MCP)

Point Claude Code, Claude Desktop, Cursor, or any MCP client at the ModelRunner MCP server and Layout Boost becomes a tool your assistant can call directly — it authorizes via OAuth (no API key in config) and runs this wrapper with the run_model tool using the endpoint hakankaan/layout-boost.

MCP client config (Claude Desktop, Cursor)

{
  "mcpServers": {
    "modelrunner": {
      "command": "npx",
      "args": ["-y", "mcp-remote", "https://mcp.modelrunner.run/mcp"]
    }
  }
}

Claude Code

claude mcp add --transport http modelrunner https://mcp.modelrunner.run/mcp

Then ask your assistant, for example: “Run hakankaan/layout-boost on ModelRunner to generate image”. MCP setup guide.

Wrapper Details

Model Details

**Rearrange a room's existing furniture — the exact same pieces, only moved — to gain usable space and better traffic flow.**

Layout Boost takes a photo of a furnished room and replans the furniture arrangement for better space usage, circulation, and function. It is a layout tool, not a restyling tool: the result must contain the exact same furniture inventory as the input — same pieces, same colors, same materials, same count — with nothing added, nothing removed, and nothing restyled. Architecture stays untouched: walls, windows, doors, flooring, ceiling, camera angle, the view through windows, and wall/floor finishes are all preserved exactly.

## Inputs

- `file_url` (required) — photo of a furnished room. The room should already contain the furniture you want rearranged; an empty room has nothing to move. - `creativity` (required) — how bold the rearrangement may be: - `precise` — subtle nudges: shift, slide, or rotate a few pieces while keeping the layout recognizable. - `balanced` — a moderate replan: several pieces relocate for clearly better space usage. - `creative` — a complete replan: any piece may move anywhere sensible. - `creativity_level` (0.5–1, default 0.7) — fine-grained rearrangement boldness, used only when `creativity` is `precise`. - `prompt` (optional) — the user's goals for the new layout, e.g. `make space for a desk near the window` or `open up a play area in the middle of the room`.

There are deliberately **no style, room-type, or color controls**: this wrapper must never restyle, recolor, or re-materialize anything. If you want a redesign rather than a rearrangement, use `roomix/room-redesign` instead.

## How to use

1. Upload the room photo and pass its URL as `file_url`. 2. Pick `creativity` for how far the layout may depart from the current one — start with `balanced`. 3. Optionally state a goal in `prompt`; the model prioritizes it while rearranging. 4. Runs are independent — one room photo per run. To explore layout options for the same room, run the **same original** `file_url` several times at different `creativity` settings and compare. Do not feed one run's output into the next run as its input: chaining compounds drift away from the original furniture inventory.