# AI Workflow Optimizer

AI Workflow Optimizer is a command-line tool designed to automate and streamline AI model workflows. By defining tasks such as data preprocessing, model training, and evaluation in a YAML configuration file, developers can ensure consistent and efficient execution of their AI pipelines.

## Features

- Define workflows using a YAML configuration file
- Parallel task execution for improved efficiency
- Built-in logging for progress tracking and debugging

## Installation

```bash
pip install -r requirements.txt
```

## Usage

1. Create a YAML configuration file (e.g., `workflow.yaml`) with the following structure:

```yaml
tasks:
  - name: preprocess_data
    duration: 2
  - name: train_model
    duration: 5
  - name: evaluate_model
    duration: 3
```

2. Run the tool:

```bash
python ai_workflow_optimizer.py --config workflow.yaml
```

## Example Output

```plaintext
2023-01-01 12:00:00 - INFO - Starting task: preprocess_data
2023-01-01 12:00:02 - INFO - Completed task: preprocess_data
2023-01-01 12:00:02 - INFO - Starting task: train_model
2023-01-01 12:00:07 - INFO - Completed task: train_model
2023-01-01 12:00:07 - INFO - Starting task: evaluate_model
2023-01-01 12:00:10 - INFO - Completed task: evaluate_model
2023-01-01 12:00:10 - INFO - Workflow execution completed.
```

## Testing

Run the tests using pytest:

```bash
pytest test_ai_workflow_optimizer.py
```

## License

This project is licensed under the MIT License.