Debugged and Optimized PromptFlow Execution

📅 2025-04-30 — Session: Debugged and Optimized PromptFlow Execution

🕒 06:50–08:10
🏷️ Labels: Promptflow, Debugging, Logging, Optimization, Node Execution
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to debug and optimize the execution of various nodes in a PromptFlow setup, focusing on improving logging, output declaration, and pipeline functionality.

Key Activities

• Debugging Outputs: Explored methods for inspecting intermediate values in PromptFlow Python tools, moving beyond print() to more robust logging strategies.
• Managing Artifacts: Reviewed key files and folders generated after a PromptFlow run to guide debugging efforts.
• Flow Execution Summary: Analyzed successful flow execution, identified issues with truncated outputs, and recommended improvements in logging and JSON handling.
• Execution Log Analysis: Investigated execution logs of my_python_tool, suggesting updates to logging and error handling.
• Output Declaration Fixes: Addressed missing outputs in the filter_llm node by providing solutions for explicit output declarations.
• YAML Configuration Correction: Provided a correct outputs: section for a flow YAML to ensure accurate node output references.
• Node Execution and Optimization: Confirmed successful execution of filter_llm, filter_prompt, and match_prompt nodes, with recommendations for future debugging and prompt optimization.
• Review Process Enhancements: Redesigned review agent prompts for strategic evaluation, incorporating executive perspectives.

Achievements

• Successfully debugged and optimized multiple nodes within the PromptFlow, ensuring correct output declarations and improved logging.
• Enhanced review agent prompts for strategic decision-making.

Pending Tasks

• Further refine logging strategies to capture all necessary outputs in future runs.
• Continue optimizing prompt structures for better clarity and efficiency in the match_llm function.