Enhanced Logging and Executor Refactoring for PromptFlow

📅 2025-04-21 — Session: Enhanced Logging and Executor Refactoring for PromptFlow

🕒 00:50–01:20
🏷️ Labels: Logging, Promptflow, Python, Flowpower, Executor, Debugging
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The session aimed to enhance the logging capabilities of PromptFlow and refactor executor scripts within the Flowpower framework to improve debugging, testing, and developer experience.

Key Activities

• Maximal Logging Strategy for PromptFlow: Developed a comprehensive strategy for detailed logging in PromptFlow, including logging inputs, outputs, and errors at each step of a YAML flow.
• Trace Logger Implementation in Python: Created a Python trace logger script to handle logging setup, error tracking, and JSON dumping functionalities.
• Creation of flowpower.utils.trace_logger: Successfully implemented the flowpower.utils.trace_logger with robust logging features for error tracking and live log monitoring.
• Enhancing PromptFlow with Flowpower Features: Conducted a quality assessment and recommended improvements by integrating Flowpower’s logging features into PromptFlow.
• Refactored runner.py for Flowpower Executors: Refactored the runner.py script to enhance its modularity and logging capabilities for Flowpower executors.
• Overview of executor.py Functionality: Provided a detailed overview and cleaned version of executor.py, focusing on its orchestration functions for executing flows and nodes.

Achievements

• Developed and implemented a detailed logging strategy for PromptFlow.
• Successfully created and integrated a trace logger in Python for enhanced error tracking.
• Refactored key executor scripts to improve their structure and logging capabilities.

Pending Tasks

• Further integration of Flowpower logging features into other components of PromptFlow.
• Continued monitoring and testing of the new logging implementations to ensure reliability and performance.