# Paint the Walls

> Repaint every wall in a room photo — a designer color and finish, with the furniture, trim, and lighting untouched.

## Overview

- **Endpoint**: `https://queue.modelrunner.run/roomix/wall-paint`
- **Wrapper ID**: `roomix/wall-paint`
- **Category**: image-to-image
- **Kind**: wrapper inference
- **Tags**: interior, walls, paint, color, room

## Pricing

- **Estimated Price**: $0.08766667 average per output

## Request Lifecycle

This wrapper runs on the ModelRunner **asynchronous queue API** — a single POST does not return the output. Every call requires an `Authorization: Key $MODEL_RUNNER_KEY` header. Run three steps:

1. **Submit** — `POST https://queue.modelrunner.run/roomix/wall-paint` with a JSON body holding the input fields at the top level. The body may also include a reserved top-level `metadata` object — a flat string map (max 16 keys, key ≤64 / value ≤512 chars) stored on the request for your own tagging. It is never sent to the wrapper; filter your request history with `GET https://queue.modelrunner.run/requests?metadata=<url-encoded JSON>` (exact key=value matches, AND-ed). The response carries request handles only (no output yet):

```json
{
  "status": "IN_QUEUE",
  "request_id": "<21-char id>",
  "status_url": "https://queue.modelrunner.run/roomix/wall-paint/requests/<request_id>/status",
  "response_url": "https://queue.modelrunner.run/roomix/wall-paint/requests/<request_id>",
  "cancel_url": "https://queue.modelrunner.run/roomix/wall-paint/requests/<request_id>/cancel"
}
```

2. **Poll status** — `GET <status_url>` until `status` is `COMPLETED`. Possible values are `IN_QUEUE`, `IN_PROGRESS`, `COMPLETED`, `FAILED`, `CANCELLED`. A `FAILED` request responds with HTTP 400 and an `error` field.

3. **Read result** — `GET <response_url>`. Returns the finished request, including the generated `output`:

```json
{ "id": "<request_id>", "status": "COMPLETED", "output": ..., "input": ... }
```

The JavaScript and Python SDKs below perform steps 2–3 for you. In any language without an SDK (Swift, Go, Kotlin, etc.) you must implement the polling loop and the final result fetch yourself — see the cURL example for the full flow.

### Input Schema

- **`color`** (`string`, _optional_):
  Curated designer paint color for every wall. Deliberately spread across the spectrum so no two choices read alike — for a shade between them, send 'custom_color' instead. 'auto' lets the wrapper pick a shade that flatters the room's existing furniture, flooring, and daylight.
  - Default: `"auto"`
  - Options: `"auto"`, `"crisp-white"`, `"cream"`, `"greige"`, `"charcoal-gray"`, `"espresso-brown"`, `"blush-pink"`, `"clay-terracotta"`, `"mustard-ochre"`, `"burgundy"`, `"sage-green"`, `"olive-green"`, `"forest-green"`, `"teal"`, `"sky-blue"`, `"denim-blue"`, `"deep-navy"`, `"dusty-lavender"`

- **`finish`** (`string`, _optional_):
  Sheen and surface character of the paint. 'auto' leaves the finish to the model.
  - Default: `"auto"`
  - Options: `"auto"`, `"matte"`, `"eggshell"`, `"satin"`, `"limewash"`, `"venetian-plaster"`

- **`prompt`** (`string`, _optional_):
  Optional exceptions and notes, e.g. 'leave the brick chimney breast bare' or 'paint only the wall behind the bed'. Honored above the default of painting every wall the same color.

- **`file_url`** (`string`, _required_):
  External URL of the uploaded photo of the room whose walls should be repainted.

- **`custom_color`** (`string`, _optional_):
  Exact color to paint the walls, as a hex value like '#3A5F4B' or a plain description like 'deep forest green'. When set it overrides 'color'.

### Output Schema

_No `Output` schema properties are available._

## Usage Examples

### cURL

The queue API is asynchronous: submit the request, poll `status_url` until it is `COMPLETED`, then read the result from `response_url`. Requires `jq`.

```bash
# 1. Submit the request (returns request handles, not the output)
SUBMIT=$(curl --silent --request POST \
  --url https://queue.modelrunner.run/roomix/wall-paint \
  --header "Authorization: Key $MODEL_RUNNER_KEY" \
  --header "Content-Type: application/json" \
  --data '{
  "file_url": ""
}')

STATUS_URL=$(echo "$SUBMIT" | jq -r '.status_url')
RESPONSE_URL=$(echo "$SUBMIT" | jq -r '.response_url')

# 2. Poll until the request leaves the queue / in-progress state
while true; do
  STATUS=$(curl --silent --url "$STATUS_URL" \
    --header "Authorization: Key $MODEL_RUNNER_KEY" | jq -r '.status')
  echo "Status: $STATUS"
  case "$STATUS" in
    COMPLETED) break ;;
    FAILED|CANCELLED) echo "Request $STATUS"; exit 1 ;;
  esac
  sleep 1
done

# 3. Read the finished request, including the generated output
curl --silent --url "$RESPONSE_URL" \
  --header "Authorization: Key $MODEL_RUNNER_KEY"
```

### JavaScript

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

const result = await modelrunner.subscribe("roomix/wall-paint", {
  input: {
  "file_url": ""
}
});

console.log(result.data);
```

### Python

```python
import asyncio
import modelrunner_ai

async def main():
    response = await modelrunner_ai.submit_async(
        "roomix/wall-paint",
        arguments={
  "file_url": ""
}
    )
    result = await response.get()
    print(result["output"])

asyncio.run(main())
```

## Additional Resources

- [Playground](https://modelrunner.ai/wrappers/roomix/wall-paint)
- [OpenAPI Schema](https://modelrunner.ai/wrappers/roomix/wall-paint/openapi.json)
- [LLM Instructions](https://modelrunner.ai/wrappers/roomix/wall-paint/llms.txt)