Refactored and Modularized Ingestion Pipeline

📅 2025-11-19 — Session: Refactored and Modularized Ingestion Pipeline

🕒 23:05–23:45
🏷️ Labels: Refactoring, Modularization, Ingestion Pipeline, Metadata, Python
📂 Project: Dev

Session Goal

The session aimed to refactor and modularize the ingestion pipeline and related components for improved clarity and efficiency in data processing.

Key Activities

• Developed a patch plan for implementing paper-level metadata extraction and JSON saving, introducing a new function parse_paper and a script persist_to_store.py.
• Integrated paper-level metadata storage by updating the pipeline to save metadata after parsing TEI files.
• Refactored the filesystem layer to separate concerns and centralize shared logic, detailing responsibilities for chunks_fs.py and papers_fs.py.
• Restructured file handling and metadata management in the paper processing system, with a clear integration plan.
• Redistributed code into separate modules for chunk files and paper metadata, introducing a new ingestion orchestrator.
• Analyzed and refactored ingestion pipeline functions to improve clarity and modularity.
• Streamlined the ingest_pipeline.py script for architectural clarity and efficient data handling.
• Provided a restructuring plan for chroma_helpers.py to enhance clarity and separation of concerns.

Achievements

• Completed the refactoring and modularization of the ingestion pipeline and related scripts, enhancing the overall architecture and efficiency of the data processing system.

Pending Tasks

• Further development steps for the ingest_pipeline.py script to ensure full integration with the new modular structure.