AI Workflow Optimizer

What It Does

Installation

pip install -r requirements.txt

Usage

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.

Source Code

import argparse
import yaml
import logging
from concurrent.futures import ThreadPoolExecutor, as_completed
from pathlib import Path

def setup_logging():
    logging.basicConfig(
        level=logging.INFO,
        format='%(asctime)s - %(levelname)s - %(message)s',
        handlers=[logging.StreamHandler()]
    )

def load_workflow_config(config_path):
    try:
        with open(config_path, 'r') as file:
            return yaml.safe_load(file)
    except FileNotFoundError:
        logging.error(f"Configuration file not found: {config_path}")
        raise
    except yaml.YAMLError as e:
        logging.error(f"Error parsing YAML file: {e}")
        raise

def execute_task(task):
    try:
        logging.info(f"Starting task: {task['name']}")
        # Simulate task execution
        import time
        time.sleep(task.get('duration', 1))
        logging.info(f"Completed task: {task['name']}")
        return {"task": task['name'], "status": "success"}
    except Exception as e:
        logging.error(f"Task {task['name']} failed: {e}")
        return {"task": task['name'], "status": "failed", "error": str(e)}

def execute_workflow(config):
    tasks = config.get('tasks', [])
    if not tasks:
        logging.warning("No tasks found in the workflow configuration.")
        return

    results = []
    with ThreadPoolExecutor() as executor:
        future_to_task = {executor.submit(execute_task, task): task for task in tasks}
        for future in as_completed(future_to_task):
            result = future.result()
            results.append(result)

    logging.info("Workflow execution completed.")
    return results

def main():
    parser = argparse.ArgumentParser(description="AI Workflow Optimizer")
    parser.add_argument('--config', required=True, help="Path to the YAML workflow configuration file")
    args = parser.parse_args()

    setup_logging()

    try:
        config = load_workflow_config(args.config)
        execute_workflow(config)
    except Exception as e:
        logging.error(f"Workflow execution failed: {e}")

if __name__ == "__main__":
    main()