> ## Documentation Index
> Fetch the complete documentation index at: https://docs.archetypeai.app/llms.txt
> Use this file to discover all available pages before exploring further.

# Lens Customization

Lens customization is the simplest way to adapt Newton to your use case. It involves creating or modifying the parameters of a lens without having to provide any additional training data.

At a high level, a lens lets you configure two key components of a lens:

* Lens Parameters: such as the instruction and focus of the lens
* Lens Data Streams: such as what sensors should be connected to a lens and where the lens output should be streamed.

## What You Can Configure

### Instruction and Focus

The `instruction` and `focus` parameters in `lens_parameters` tell Newton what to look for and how to respond. These are analogous to system prompts in traditional LLMs, but are specifically designed for physical-world reasoning tasks.

```yaml theme={"system"}
lens_parameters:
  instruction: |
    You are an intelligent traffic monitoring system. Monitor the traffic feed 
    for the following activity or object.
    Output alerts in the format: [alert]{activity or object name}: {description}
  focus: All red pickup trucks driving east.
```

**Best practices for instructions:**

* Be specific about the output format you expect
* Provide context about the sensor placement or environment (e.g., "this camera is on 104th and main street looking west-to-east")
* Clearly define what constitutes an alert or event worth reporting

### Input and Output Streams

Configure how data flows into and out of the lens:

Each lens can be customized to read and write from dedicated data streams. For example, a developer can stream data from a CSV file or video file into a lens and then stream the results back to an external application via a Server Sent Events stream. Available stream types are documented in the [Streams](/core-concepts/streams/data-streams) section.

The example below demonstrates how a CSV file can be hooked up and streamed into a lens.

```yaml theme={"system"}
input_streams:
  - stream_type: csv_file_reader
    stream_config:
      file_id: data.csv
      window_size: 1024
      step_size: 1024
output_streams:
  - stream_type: server_sent_events_writer
```

Available stream types are documented in the [Streams](/core-concepts/streams/data-streams) section.

### Lens-Specific Parameters

Different lenses expose different configuration options. Common parameters include:

| Parameter         | Description                                    | Example |
| ----------------- | ---------------------------------------------- | ------- |
| `buffer_size`     | Number of samples to buffer before processing  | `1024`  |
| `window_size`     | Size of the sliding window for analysis        | `1024`  |
| `step_size`       | How far to advance the window between analyses | `512`   |
| `normalize_input` | Whether to normalize input data                | `true`  |

Refer to the documentation for your specific lens to see all available parameters.

## When to Use Lens Customization

Lens customization is appropriate when:

* You're getting started and want to quickly test different configurations.
* You want to change what Newton focuses on for your specific use case, such as real-time safety alerts in a factory.
* Your use case or sensor data does not require extensive customization.

## Next Steps

If lens customization alone isn't achieving the results you need, consider adding [N-Shot Examples](/core-concepts/customization/n-shot-examples) to guide Newton's behavior with labeled examples.