📅 2025-02-06 — Session: Developed Modular Processing Pipeline

🕒 22:15–23:25
🏷️ Labels: Modular Design, Document Processing, Ai Engineering, Chunk Enrichment, Python
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

The goal of this session was to design and implement a modular processing pipeline for document handling, focusing on text extraction and metadata management.

Key Activities

  • Outlined the architecture of a modular processing pipeline with components for file processing, text chunking, and notebook-based execution.
  • Designed a framework for chunk enrichment tasks using AI techniques like summarization and sentiment analysis.
  • Established best practices and design patterns for AI engineering in chunk querying and metadata extraction.
  • Developed a modular chunk processing system with components like ChunkManager, ChunkProcessor, and ChunkEnricher.
  • Implemented one-liner tests for ChunkManager methods to ensure functionality.
  • Managed temporary test files in Python to improve testing processes.
  • Fixed dynamic text passing in ChunkEnricher to ensure proper OpenAI API integration.

Achievements

  • Successfully designed a comprehensive modular processing pipeline architecture.
  • Implemented robust testing procedures for the ChunkManager class.
  • Enhanced the ChunkEnricher class for better API integration.

Pending Tasks

  • Further testing and validation of the entire pipeline.
  • Optimization of AI workflows for chunk enrichment.