The project involves:

API Development: Flask-based API (api.py) for accessing and serving document data stored in an SQLite database (documents.db).
Database Setup: Initialization and population script (setup_db.py) for creating the database schema and seeding initial data using SQLAlchemy.
Text Analysis: Utilizes spaCy for natural language processing tasks such as entity extraction and clustering.
Visualization: Matplotlib and Seaborn are used for visualizing data extracted from documents.

Key Files:

api.py: Flask API endpoints for document retrieval and serving.
setup_db.py: Script to initialize and populate the SQLite database.
text_analysis.py: Handles text preprocessing, entity extraction, and clustering.
visualizations.py: Generates visualizations using Matplotlib and Seaborn.

Git Ignore:

Ignores documents.db to avoid tracking SQLite database files.
Ignores pycache directory to exclude Python bytecode caches.

Dependencies:

Flask
SQLAlchemy
spaCy
Matplotlib
Seaborn