Implement backend logic for handling LLM data

[ckak912]

As part of integrating CodeBuddy with a LLM, we need to implement the backend logic to handle various data effectively. This issue has multiple tasks related to managing the data from the model on the backend.

Overview of main tasks

1. Created table in the database to store the data
2. Create endpoints to allow for API calls to the model, passing the relevant data from the model to generate and retrieve hint code for specific steps. WIP
3. Python handler to manage and update the LLM data efficiently.
4. Implement backend logic to handle the user response's, submissions, and feedback from the model.
5. Integrate statistics and analytics to monitor user performance and progress.

Acceptance Criteria

1. The selected step information is accurately extracted and properly stored on the backend.
2. The API calls to the model successfully generate and retrieve hint codes for specific steps, and the response data is correctly handled on the backend.
3. Exercise data is effectively managed and updated, ensuring consistency and integrity of information.
4. Backend functions for user responses, submissions, and feedback are seamlessly integrated, enabling smooth interaction with exercises.
5. Exercise statistics and analytics provide meaningful insights into user performance and progress.

Database and Migration Considerations This issue will require modifications to the database structure and migration files to accomdate new columns for the new data.

[ckak912]

Created table in the database to store the data