# mirelo-ai/sfx-1.6/inpaint-audio

> Mirelo SFX1.6 Inpaint Audio is a fast AI audio inpainting model that regenerates a selected segment of a short audio clip while preserving the audio outside that region. Ready-to-use REST inference API for sound effect repair, audio cleanup, segment regeneration, game audio, video production, cinematic sound design, and professional audio editing workflows with simple integration, no coldstarts, and affordable pricing.

## Overview

- **Endpoint**: `https://api.wavespeed.ai/api/v3/mirelo-ai/sfx-1.6/inpaint-audio`
- **Polling/result URL**: `https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result`
- **Model ID**: `mirelo-ai/sfx-1.6/inpaint-audio`
- **Category**: audio-to-audio

## API Information

This model can be used via our HTTP API or more conveniently via our client libraries.
The API is asynchronous: submit a prediction, then poll its result URL until it completes.

### Input Schema

The API accepts the following input parameters:

- **`audio`** (`string`, _required_):
  Source audio. Maximum duration is 10 seconds. Audio outside the selected segment is preserved.

- **`start_s`** (`number`, _required_):
  Start of the inpaint region in seconds. Must leave a 1 second left gap.
  - Default: `2`
  - Range: `1` to `9`

- **`end_s`** (`number`, _required_):
  End of the inpaint region in seconds. The segment span must be 1 to 8 seconds.
  - Default: `6`
  - Range: `2` to `10`

- **`prompt`** (`string`, _optional_):
  Optional text prompt guiding the regenerated segment.

- **`num_samples`** (`integer`, _optional_):
  Number of variations to generate.
  - Default: `1`
  - Range: `1` to `4`



**Required Parameters Example**:

```json
{
  "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
  "start_s": 2,
  "end_s": 6
}
```

**Full Example**:

```json
{
  "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
  "start_s": 2,
  "end_s": 6,
  "prompt": "A cinematic ocean wave at sunrise, highly detailed",
  "num_samples": 1
}
```

### Result Data Schema

The `data` object returned by the API has the following fields:

- **`created_at`** (`string (date-time)`, _optional_):
  ISO timestamp of when the request was created (e.g., "2023-04-01T12:34:56.789Z").

- **`id`** (`string`, _optional_):
  Unique identifier for the prediction, the ID of the prediction to get.

- **`model`** (`string`, _optional_):
  Model ID used for the prediction.

- **`outputs`** (`array of string | object`, _optional_):
  Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model.

- **`status`** (`string`, _optional_):
  Status of the task: created, processing, completed, or failed.

- **`urls`** (`object`, _optional_):
  Object containing related API endpoints.



**Example `data` Object**:

```json
{
  "created_at": "example",
  "id": "example",
  "model": "example",
  "outputs": [],
  "status": "example",
  "urls": {}
}
```

## Usage Examples

The examples use `jq` to read JSON. Set your API key first:

```bash
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
```

### 1. Submit a prediction

```bash
REQUEST_BODY=$(cat <<'JSON'
{
  "audio": "https://interactive-examples.mdn.mozilla.net/media/cc0-audio/t-rex-roar.mp3",
  "start_s": 2,
  "end_s": 6
}
JSON
)

SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
  --request POST \
  --url https://api.wavespeed.ai/api/v3/mirelo-ai/sfx-1.6/inpaint-audio \
  --header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
  --header "Content-Type: application/json" \
  --data "${REQUEST_BODY}")

printf '%s\n' "${SUBMIT_RESPONSE}" | jq .
```

The response contains the prediction ID in `data.id`.

### 2. Poll until complete and read `outputs`

```bash
PREDICTION_ID=$(printf '%s' "${SUBMIT_RESPONSE}" | jq -r '.data.id')
if [ -z "${PREDICTION_ID}" ] || [ "${PREDICTION_ID}" = "null" ]; then
  printf 'Submission response did not contain data.id\n' >&2
  exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"

while true; do
  RESPONSE=$(curl --silent --show-error --fail-with-body \
    --request GET \
    --url "${RESULT_URL}" \
    --header "Authorization: Bearer ${WAVESPEED_API_KEY}")

  RESULT=$(printf '%s' "${RESPONSE}" | jq -e '.data')
  STATUS=$(printf '%s' "${RESULT}" | jq -er '.status')
  case "${STATUS}" in
    completed)
      # Generated files are returned in the outputs array.
      printf '%s\n' "${RESULT}" | jq '.outputs'
      break
      ;;
    failed|cancelled|timeout|deleted)
      printf '%s\n' "${RESULT}" | jq '{status, error, code}'
      exit 1
      ;;
    *)
      sleep 2
      ;;
  esac
done
```

## Additional Resources

### Documentation

- [Model Playground](https://wavespeed.ai/models/mirelo-ai/sfx-1.6/inpaint-audio)
- [API Documentation](https://wavespeed.ai/docs/docs-api/mirelo-ai/mirelo-ai-sfx-1.6-inpaint-audio)