# Match a Reference > Restyle your room to match a reference photo — its palette, materials, and mood, in your space. ## Overview - **Endpoint**: `https://queue.modelrunner.run/hakankaan/match-reference` - **Wrapper ID**: `hakankaan/match-reference` - **Category**: image-to-image - **Kind**: wrapper inference - **Tags**: none ## 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/hakankaan/match-reference` 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=` (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/hakankaan/match-reference/requests//status", "response_url": "https://queue.modelrunner.run/hakankaan/match-reference/requests/", "cancel_url": "https://queue.modelrunner.run/hakankaan/match-reference/requests//cancel" } ``` 2. **Poll status** — `GET ` 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 `. Returns the finished request, including the generated `output`: ```json { "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 - **`prompt`** (`string`, _optional_): Optional extra guidance for the restyle, e.g. "keep my sofa" or "match the reference's wall color exactly". - **`file_url`** (`string`, _required_): External URL of the user's room photo. Its architecture, layout, camera angle, and through-window views are preserved. - **`creativity`** (`string`, _required_): How literally to chase the reference: precise adapts the look gently to the room, balanced restyles decisively, creative fully transforms toward the reference. - Default: `"balanced"` - Options: `"precise"`, `"balanced"`, `"creative"` - **`reference_url`** (`string`, _required_): External URL of the reference interior photo — the look to match. Only its style transfers (palette, materials, furniture character, lighting mood); its architecture, layout, and camera are ignored. - **`creativity_level`** (`number`, _optional_): Fine-grained creativity value used only when creativity is precise. - Default: `0.7` - Range: `0.5` to `1` ### 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/hakankaan/match-reference \ --header "Authorization: Key $MODEL_RUNNER_KEY" \ --header "Content-Type: application/json" \ --data '{ "file_url": "", "reference_url": "", "creativity": "balanced" }') STATUS_URL=$(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("hakankaan/match-reference", { input: { "file_url": "", "reference_url": "", "creativity": "balanced" } }); console.log(result.data); ``` ### Python ```python import asyncio import modelrunner_ai async def main(): response = await modelrunner_ai.submit_async( "hakankaan/match-reference", arguments={ "file_url": "", "reference_url": "", "creativity": "balanced" } ) result = await response.get() print(result["output"]) asyncio.run(main()) ``` ## Additional Resources - [Playground](https://modelrunner.ai/wrappers/hakankaan/match-reference) - [OpenAPI Schema](https://modelrunner.ai/wrappers/hakankaan/match-reference/openapi.json) - [LLM Instructions](https://modelrunner.ai/wrappers/hakankaan/match-reference/llms.txt)