Configured and Debugged PromptFlow Automation

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📅 2025-05-04 — Session: Configured and Debugged PromptFlow Automation

🕒 18:45–19:25
🏷️ Labels: Promptflow, YAML, Python, Error Handling, Automation
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary objective of this session was to configure and debug various aspects of the PromptFlow automation framework, ensuring seamless integration and execution of AI-driven tasks.

Key Activities

  • Exported a Pandas DataFrame to JSONL format for compatibility with PromptFlow.
  • Developed a minimal PromptFlow DAG for chat screening, detailing YAML configuration.
  • Refined the identity block for a PromptFlow assistant to align with project goals.
  • Resolved ModuleNotFoundError by ensuring the correct virtual environment setup for PromptFlow.
  • Installed necessary Python dependencies, including slugify, to address dependency errors.
  • Addressed errors in the filter_prompt node within PromptFlow, providing solutions for error handling.
  • Finalized and updated the YAML configuration files (run.yaml and run.yml) for GPT execution, ensuring data mapping accuracy.
  • Performed a consistency check between YAML and JSON files to rectify type mismatches.
  • Resolved installation issues related to promptflow.tools.
  • Evaluated AI agent performance in structuring and interpreting assistant messages.

Achievements

  • Successfully configured and debugged PromptFlow automation tasks.
  • Ensured compatibility and correctness of YAML configurations and data files.
  • Improved error handling and dependency management within the PromptFlow environment.

Pending Tasks

  • Further validation of the updated configurations with real-world data inputs to ensure robustness.
  • Continuous monitoring of AI agent performance for potential improvements.

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