- Added ServerManager class to manage the FastAPI server lifecycle.
- Included methods to start, check status, and join the server thread.

feat: Create training manager for scheduled model training

- Introduced TrainingManager class to handle scheduled model training tasks.
- Implemented cron-based scheduling for training every hour.
- Added methods to start, stop, and check the status of the training manager.

feat: Develop webhook queue management for async processing

- Created WebhookQueue class for managing webhook tasks in a thread-safe manner.
- Implemented worker threads to process tasks asynchronously.
- Added methods for enqueueing tasks, stopping workers, and retrieving statistics.

feat: Establish main entry point for GitOps Bot application

- Created main.py as the entry point for the FastAPI application.
- Initialized the Application class and started the server.

chore: Add nodemon configuration for development

- Included nodemon.json to watch for changes and restart the application automatically.

chore: Update requirements.txt with necessary dependencies

- Added required packages for FastAPI, async processing, and machine learning functionalities.

feat: Set up server initialization and middleware

- Created server/__init__.py to initialize the FastAPI app.
- Implemented logging middleware for request processing time.
- Added webhook authentication middleware to verify GitLab tokens.

feat: Define API routes for policies and health checks

- Created API routes for retrieving policies and checking server health status.

feat: Implement webhook routes for handling GitLab events

- Developed routes to handle push, merge request, issue, and note events.
- Integrated webhook queue for processing events asynchronously.

test: Add comprehensive tests for model prediction and training

- Implemented test scripts for model prediction and training functionalities.
- Included logging and validation for test results and performance metrics.