📅 2024-09-16 — Session: Refactored Data Processing and Schema Management
🕒 22:00–23:55
🏷️ Labels: Data_Processing, Schema_Management, Python, Nosql, AI
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The primary objective of this session was to improve data processing workflows and schema management in various contexts, including NoSQL data handling and Python programming.
Key Activities
- Repairing Bedroom Walls with Enduido: Outlined a guide for using wall filler to repair bedroom walls, covering preparation to painting.
- Optimizing NoSQL Data Processing Workflow: Developed a workflow to enhance efficiency by avoiding reprocessing of previously handled resolutions.
- Fixing Schema Key Interpretation in JSON Parsing: Resolved issues with schema key interpretation in JSON parsing, ensuring correct handling as lists.
- Refinement of Schema Key Handling in Python Code: Improved Python functions for schema key processing, using
ast.literal_evaljudiciously. - Analysis of NoSQL Schema for Resolution 172/2024: Analyzed and recommended improvements for a NoSQL schema.
- Enhancements for Data Extraction: Planned improvements for data extraction processes focusing on financial data and committee mentions.
- Preventing Model Hallucination in Schema-Based Data Extraction: Outlined strategies to prevent AI model hallucinations by enforcing schema adherence.
- Reinforcing Schema Enforcement in OpenAI Function Calls: Structured approach to ensure schema enforcement in OpenAI API calls.
- Enhancing Schema Extraction Logic: Modified the
extract_parametersfunction to preserve nested fields in schema extraction.
Achievements
- Established a more efficient NoSQL data processing workflow.
- Improved schema key handling in JSON and Python scripts.
- Developed strategies to prevent AI model hallucinations in data extraction.
Pending Tasks
- Further testing and validation of the enhanced data processing workflows and schema management strategies.
- Implementation of recommended improvements in NoSQL schemas.