📅 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.