# Adaptive Memory Optimizer

## Overview
The Adaptive Memory Optimizer is a Python-based CLI tool designed to benchmark the memory usage of an AI agent and dynamically suggest or apply optimizations. The tool supports three optimization strategies: pruning, compression, and partitioning. It helps developers reduce resource consumption and improve scalability without sacrificing performance.

## Features
- Monitors memory usage of an AI agent script.
- Supports three optimization strategies:
  - **Pruning**: Reduces the dataset by keeping every other sample.
  - **Compression**: Averages memory usage over intervals.
  - **Partitioning**: Splits memory data into chunks.
- Generates reports in CSV or JSON format.

## Requirements
- Python 3.7+
- Required Python packages:
  - `psutil`
  - `pandas`

Install the required packages using pip:
```bash
pip install psutil pandas
```

## Usage
Run the tool from the command line with the following options:

```bash
python adaptive_memory_optimizer.py --agent <path_to_agent_script> --strategy <strategy> [--output <output_format>] [--interval <interval>]
```

### Arguments
- `--agent`: Path to the Python script of the AI agent to monitor.
- `--strategy`: Optimization strategy to apply. Choices are:
  - `pruning`
  - `compression`
  - `partitioning`
- `--output`: (Optional) Output format for the report. Choices are:
  - `csv`
  - `json`
- `--interval`: (Optional) Interval in seconds for memory usage sampling. Default is `1` second.

### Example
```bash
python adaptive_memory_optimizer.py --agent my_agent.py --strategy pruning --output json --interval 2
```

This command monitors the memory usage of `my_agent.py`, applies the pruning strategy, and saves the report in JSON format.

## Testing
The tool includes a test suite written with `pytest`. To run the tests, install `pytest` and execute:

```bash
pip install pytest
pytest test_adaptive_memory_optimizer.py
```

The tests include:
- Unit tests for each optimization strategy.
- Integration test for the main `adaptive_memory_optimizer` function with mocked dependencies.

## License
This project is licensed under the MIT License.