Validated and Enhanced PromptFlow Pipelines

• Day: 2025-05-04
• Time: 19:45 to 20:20
• Project: Dev
• Workspace: WP 2: Operational
• Status: Completed
• Priority: MEDIUM
• Assignee: Matías Nehuen Iglesias
• Tags: Promptflow, Automation, Python, JSON, Data Management

Description

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.jsonl and 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.

Evidence

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• event_ids: []