📅 2025-05-18 — Session: Debugged and Enhanced LLM Function Calls

🕒 05:45–06:25
🏷️ Labels: LLM, Debugging, Openai, Function_Call, Python
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to debug and enhance the function calling capabilities within the OpenAI API, focusing on improving reliability and error handling.

Key Activities

  • Debugged issues with LLM’s function calling logic, ensuring correct triggering and error handling.
  • Addressed common problems in OpenAI API function calls, focusing on prompt formatting and execution clarity.
  • Enhanced Python logging for robust debugging of API calls, including detailed input/output logging.
  • Analyzed and improved the parsed_message function, addressing issues with long prompts.
  • Reflected on structural and semantic differences in prompt engineering, and identified challenges in schema completion by LLMs.
  • Diagnosed issues in LLM processing, suggesting improvements in prompt tokens and logging practices.
  • Provided comprehensive Python code for enhanced observability in LLM call debugging.

Achievements

  • Improved debugging techniques for OpenAI function calls.
  • Developed enhanced logging and error handling strategies.

Pending Tasks

  • Implement suggested improvements in prompt engineering and logging practices.
  • Further testing of the enhanced debugging strategies in different scenarios.