📅 2025-05-04 — Session: Validated and Enhanced PromptFlow Pipelines
🕒 19:45–20:25
🏷️ Labels: Promptflow, Automation, Data Management, Python, JSON
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The primary goal of this session was to validate and enhance PromptFlow pipelines for semantic analysis of assistant chat logs, focusing on metadata tagging and automation.
Key Activities
- Validation of PromptFlow Pipeline: Conducted a validation process for a PromptFlow pipeline that semantically analyzes chat logs.
- Setup Guide Creation: Developed a comprehensive guide for setting up new semantic pipelines, including folder structure, YAML configurations, and run commands.
- Periodic Processing Automation: Transitioned from manual runs to a production-grade periodic processing loop using PromptFlow, with plans for centralized data aggregation.
- Daily Message Export Script: Implemented a Python script to extract daily subsets of messages and save them as JSONL files.
- Run Folder Automation: Planned a strategy to automate the identification of run folders for daily inputs in PromptFlow.
- Output Appending Method: Provided a method to append outputs to a
results.jsonlfile, ensuring PromptFlow’s normal operation. - Data Cleaning: Developed code to filter out null-structured JSON entries, ensuring meaningful data processing.
- Unicode Handling: Addressed JSON-escaped Unicode issues, providing solutions for handling accented characters.
Achievements
- Successfully validated and enhanced the PromptFlow pipelines.
- Created reusable guides and scripts to facilitate automation and data management.
Pending Tasks
- Further testing and refinement of the automated processing loop and run folder identification strategy.