Description

Create the foundational structure for the FastAPI-based API portion of the knowledge graph similarity detection project. The structure should follow common industry standards for backend APIs, prioritize separation of concerns, and be designed for scalability, allowing easy addition of new endpoints. The organization will promote maintainability and adherence to best practices across all modules.

User Stories

As an Architect, I want a standardized project structure for the API, so we can maintain consistency across teams and projects.
As an Architect, I want the API structure to follow industry best practices, ensuring code readability, modularity, and ease of future maintenance.

Details

Objective: Set up an organized directory structure in the repository that facilitates modularity, easy-to-follow code practices, and seamless collaboration.
Requirements:
- [x] Create a repository on GitHub or similar version control platform.
- [ ] Add a README.md with a brief project overview, setup instructions, and a directory structure outline.
- [ ] Define the following folders and files, maintaining separation of concerns:

Required Directory and File Structure

Based on:

[!NOTE] This is only a proposal, can be modify to fit with project requirements

project_root/
├── app/                          # Main FastAPI application directory
│   ├── main.py                   # Application entry point
│   ├── config.py                 # Configuration settings and environment variables
│   ├── api/                      # API routes, endpoints, and dependencies
│   │   ├── routers/              # Individual route files organized by entity
│   │   │   └── similarity.py     # Endpoint for similarity detection
│   ├── models/                   # Model loader and neural network logic
│   ├── services/                 # Core services (e.g., similarity detection, rate limiting)
│   ├── db/                       # Database setup, connection, and management
│   ├── schemas/                  # Pydantic schemas for input/output validation
│   └── utils/                    # Utility functions, including custom logging
├── tests/                        # Tests for the application
│   ├── unit/                     # Unit tests for individual components
│   ├── integration/              # Integration tests for API endpoints
├── .env.example                  # Example environment variables for developers
├── requirements.txt              # Dependencies required for running the project
└── README.md                     # Overview and instructions for setting up the project

Examples and Notes

README.md: Include setup instructions, dependency installation steps, and a brief project description.
requirements.txt: Initial dependencies may include:
```
fastapi
uvicorn
pydantic
redis
sqlalchemy
```

Edge Cases

API Key Management: Ensure no sensitive information is stored in .env.example.
Module Expandability: The structure should allow for easy addition of new modules, such as additional routers files for new endpoints.
Platform Compatibility: Ensure file naming consistency, especially for case-sensitive systems.

GabrielEValenzuela / chatML

Define and implement API folder schema #4