AI-Powered Notes Application

This project is an AI-powered note application that meets all the specified task requirements:

Features

1. Authentication with JWT: Secure user authentication.
2. CRUD Operations for Notes: Create, read, update, and delete notes.
3. Note History: View historical versions of notes.
4. Summarization: Summarize notes using the OpenAI API.
5. Analytical Endpoints: Calculate various statistics such as:
   • Total word count across all notes.
   • Average note length.
   • Most common words or phrases.
   • Top 3 longest and shortest notes.
6. Testing: Unit and integration tests with 80% coverage.

Implementation

• Authentication: Implemented using JWT for secure access.
• Database & Models:
  • Two main models: User and Note, linked via a foreign key.
  • Versioning is handled with SQLAlchemy-Continuum to track note history.
• Performance:
  • Pagination is implemented in endpoints (e.g., retrieving all notes and note history) to reduce database load.
• AI Integration:
  • Utilizes an asynchronous OpenAI client since the API is completely asynchronous.
  • Uses an async SQLAlchemy driver for database communications.
• Analytics:
  • Provides a separate asynchronous endpoint for data analysis.
  • Uses synchronous utilities with Pandas and NLTK to calculate statistics and clean stop words.
• Testing:
  • Testing is performed using an SQLite environment with asynchronous tests ensuring 80% coverage.

How to Run

1. Environment Setup:
   • Configuration details are provided in the .env file. Ensure you set your OPENAI_API_KEY.
2. Development:
   • Build and run the application using Docker Compose:

     docker-compose --build

3. Testing:
   • Run tests with (docker-compose must be run as well):

     pytest -v -s