# Marlin Find

> Marlin is a 2B video VLM tuned for the two questions developers actually want to ask of their videos: what is happening, and when?


## Overview

- **Endpoint**: `https://fal.run/fal-ai/marlin/find`
- **Model ID**: `fal-ai/marlin/find`
- **Category**: vision
- **Kind**: inference
**Tags**: utility, editing



## Pricing

- **Price**: $0.015 per 1000 tokens

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:


- **`video_url`** (`string`, _required_):
  URL of the video to search through.
  - Examples: "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4"

- **`prompt`** (`string`, _required_):
  Natural-language description of the event or scene to find in the video.
  - Examples: "when is pizza dropped?"

- **`do_sample`** (`boolean`, _optional_):
  If true, sample with temperature/top_p; if false, use greedy decoding.
  - Default: `false`

- **`temperature`** (`float`, _optional_):
  Sampling temperature. Only used when do_sample is true. Default value: `1`
  - Default: `1`
  - Range: `0` to `2`

- **`top_p`** (`float`, _optional_):
  Nucleus sampling threshold. Only used when do_sample is true. Default value: `1`
  - Default: `1`



**Required Parameters Example**:

```json
{
  "video_url": "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4",
  "prompt": "when is pizza dropped?"
}
```

**Full Example**:

```json
{
  "video_url": "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4",
  "prompt": "when is pizza dropped?",
  "temperature": 1,
  "top_p": 1
}
```


### Output Schema

The API returns the following output format:

- **`span`** (`EventSegment`, _optional_):
  Detected (start, end) span in seconds, or null if the model could not locate the event.

- **`text`** (`string`, _required_):
  Raw post-thinking model output (e.g. "From 14.3 to 18.2.").

- **`format_ok`** (`boolean`, _required_):
  True iff the output matched the trained "From X to Y." format.



**Example Response**:

```json
{
  "text": ""
}
```


## Usage Examples

### cURL

```bash
curl --request POST \
  --url https://fal.run/fal-ai/marlin/find \
  --header "Authorization: Key $FAL_KEY" \
  --header "Content-Type: application/json" \
  --data '{
     "video_url": "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4",
     "prompt": "when is pizza dropped?"
   }'
```

### 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/marlin/find",
    arguments={
        "video_url": "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4",
        "prompt": "when is pizza dropped?"
    },
    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/marlin/find", {
  input: {
    video_url: "https://v3b.fal.media/files/b/0a913346/ZbEaRKcU1dMNYkHl9g1Zz_T4QEyOJ3R3WzuQS9.mp4",
    prompt: "when is pizza dropped?"
  },
  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/marlin/find)
- [API Documentation](https://fal.ai/models/fal-ai/marlin/find/api)
- [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/marlin/find)

### fal.ai Platform

- [Platform Documentation](https://docs.fal.ai)
- [Python Client](https://docs.fal.ai/clients/python)
- [JavaScript Client](https://docs.fal.ai/clients/javascript)