intelliHR-AI

Project Overview

intelliHR-AI is an AI-powered platform designed to enhance HR processes through automation, analytics, and intelligent decision-making. The project is structured for scalability and maintainability, following best practices in Python application development.

Project Structure

intelliHR-AI/
├── agents/         # AI agents and related logic
├── app/            # Main application code
│   ├── main.py     # Application entry point
│   ├── models/     # Data models
│   ├── routes/     # API routes
│   ├── services/   # Business logic/services
│   └── utils/      # Utility functions
├── config/         # Configuration files
├── tests/          # Unit and integration tests
├── requirements.txt# Python dependencies
├── env_example     # Example environment variables
├── README.md       # Project documentation

Getting Started

Prerequisites

• Python 3.8+
• pip (Python package manager)

Setup

1. Clone the repository:

   git clone <repo-url>
   cd intelliHR-AI

2. Create a virtual environment:

   python3 -m venv venv
   
   # On Windows PowerShell
   .\venv\Scripts\Activate.ps1
   
   # On Windows CMD
   .\venv\Scripts\activate.bat
   
   # On Unix or MacOS
   source venv/bin/activate

3. Install dependencies:

   pip install -r requirements.txt

4. Configure environment variables:

   • Copy env_example to .env and update values as needed.

Running the Application (FastAPI)

The server uses FastAPI for the backend. To run the development server, use uvicorn:

# Run on default port 8000
uvicorn app.main:app --reload
# Run on a custom port (e.g., 8080)
uvicorn app.main:app --reload --port 8080

This will start the FastAPI server with auto-reload enabled for development. By default, the server will be available at http://127.0.0.1:8000 or your chosen port (e.g., http://127.0.0.1:8080).

API Documentation

• Swagger UI: http://127.0.0.1:8000/docs
• ReDoc: http://127.0.0.1:8000/redoc

Running Tests

pytest -v

Running with Docker (Environment-specific)

Build the Docker image for a specific environment (dev, stage, prod):

# Development
docker build -t intellihr-ai-dev --build-arg ENVIRONMENT=dev .

# Staging
docker build -t intellihr-ai-stage --build-arg ENVIRONMENT=stage .

# Production
docker build -t intellihr-ai-prod --build-arg ENVIRONMENT=prod .

Run the container for the chosen environment:

# Development
docker run -p 9090:2001 intellihr-ai-dev

# Staging
docker run -p 9090:2001 intellihr-ai-stage

# Production
docker run -p 9090:2001 intellihr-ai-prod

Notes

• Ensure Python 3.8+ is installed.
• For any missing dependencies, add them to requirements.txt and re-run the install step.
• For development, use the --reload flag with Uvicorn for auto-reload.

Contributing

1. Fork the repository
2. Create a new branch (git checkout -b feature/your-feature)
3. Commit your changes
4. Push to the branch (git push origin feature/your-feature)
5. Open a pull request

License

This project is licensed under the MIT License.