# LLM Burnout Tracker

## Description
The LLM Burnout Tracker is a CLI tool designed to analyze user interaction logs with large language models (LLMs). It detects patterns of excessive usage, such as prolonged sessions or high-frequency queries, which may indicate user fatigue or burnout. The tool provides actionable insights and recommendations to mitigate fatigue and improve user well-being.

## Features
- Analyze user interaction logs for signs of fatigue.
- Generate burnout risk scores based on engagement metrics.
- Provide actionable recommendations to mitigate user fatigue.
- Visualize user engagement patterns.

## Installation
1. Clone the repository:
   ```bash
   git clone https://github.com/your-repo/llm_burnout_tracker.git
   cd llm_burnout_tracker
   ```
2. Install the required dependencies:
   ```bash
   pip install -r requirements.txt
   ```

## Usage
### Command-Line Interface
```bash
python llm_burnout_tracker.py --input user_logs.csv --output burnout_report.txt --visual engagement_plot.png
```

### Arguments
- `--input`: Path to the input CSV or JSON file containing user interaction logs.
- `--output`: Path to save the burnout report.
- `--visual` (optional): Path to save the visualization of user engagement.

### Example
```bash
python llm_burnout_tracker.py --input user_logs.csv --output burnout_report.txt --visual engagement_plot.png
```

## Input Format
The input file must be a CSV or JSON file with the following columns:
- `timestamp`: The timestamp of each interaction (e.g., `2023-01-01 10:00:00`).
- `query`: The content or identifier of the query.

## Output
- A JSON-formatted burnout report containing the risk score, analysis, and recommendations.
- An optional visualization of user engagement metrics saved as an image file.

## Testing
Run the tests using `pytest`:
```bash
pytest test_llm_burnout_tracker.py
```

## License
MIT License