Reviewed and Debugged Evaluator Classes for OpenAI API

📅 2024-02-19 — Session: Reviewed and Debugged Evaluator Classes for OpenAI API

🕒 19:15–20:20
🏷️ Labels: Python, Openai, Debugging, Evaluator, Logging, API
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to review and debug the Evaluator classes used with the OpenAI API, focusing on ensuring proper functionality, extensibility, and error handling.

Key Activities

• Conducted a detailed code review of the Evaluator classes, identifying necessary corrections and improvements.
• Debugged an API error in the Evaluator40 class related to a null value in the ‘content’ field, providing a step-by-step troubleshooting guide.
• Reviewed the implementation of exercise_content in Evaluator35 and Evaluator40 classes, suggesting logging and verification steps to diagnose content handling issues.
• Proposed improvements in data diagnosis and management by implementing checks and logs in the construct_prompt function and evaluate calls.
• Addressed conceptual and technical issues in the Evaluator35 class, recommending making the Evaluator class an abstract base class for better structure and validation.
• Enhanced debugging techniques in Python by adding logging statements to track execution flow and capture errors.
• Resolved code inconsistency in handling exercise_id and filename in the get_exercise_content function.

Achievements

• Improved code structure and error handling in the Evaluator classes.
• Enhanced debugging capabilities with systematic logging and verification.

Pending Tasks

• Further testing of the Evaluator classes after implementing suggested changes to ensure robustness and reliability.