📅 2025-05-04 — Session: Validated and Enhanced PromptFlow Pipelines
🕒 19:45–20:20
🏷️ Labels: Promptflow, Automation, Python, JSON, Data Management
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to validate and enhance the PromptFlow pipeline for semantic analysis of assistant chat logs, focusing on metadata tagging and automation.
Key Activities
- Validation: Reviewed the PromptFlow pipeline setup for semantic analysis, ensuring metadata tagging for reuse and automation.
- Setup Guide Creation: Developed a comprehensive guide for setting up new PromptFlow pipelines, detailing folder structures, required files, YAML configurations, and run commands.
- Automation Transition: Outlined a transition plan from manual runs to a production-grade periodic processing loop, including data aggregation strategies.
- Script Development: Created a Python script for daily message export, processing DataFrames into JSONL files.
- Run Folder Automation: Planned automation for identifying run folders linked to daily input files, with Python implementation for logging.
- Output Management: Implemented methods to append outputs to
results.jsonland filter null-structured JSON entries.
Achievements
- Successfully validated the PromptFlow pipeline and created reusable guides and scripts for future use.
- Established a clear plan for automating periodic processing and data management tasks.
Pending Tasks
- Further testing and refinement of the automated run folder identification and periodic processing loop.
- Continuous improvement of data cleaning strategies for JSON and JSONL formats.