Backend Application README

About Project

This is the backend application for the ATS platform. It is built using FastAPI and includes features for processing and analyzing data using Google's Generative AI models and PDFPlumber for extracting text from PDF files.

Steps to Install for Windows, Linux, Mac

1. Set up a virtual environment:

   python -m venv venv
   source venv/bin/activate # On Linux/Mac
   venv\Scripts\activate # On Windows

2. Install dependencies:

   pip install -r requirements.txt

3. Set the GOOGLE_API_KEY environment variable: Create a .env file in the backend directory and add your Google API key.

   GOOGLE_API_KEY=YOUR_GOOGLE_API_KEY

4. Run the application:

   uvicorn main:app --port=8000 --host=0.0.0.0

   The application will start on http://127.0.0.1:8000 by default.

Running Locally

To run the application locally, you need to start the backend server using Uvicorn. The main application file is backend/main.py.

Changing the Host and Port

• Host: The default host is 0.0.0.0, which means the application will listen on all available network interfaces. You can change this in the uvicorn.run command in backend/main.py (line 19).
• Port: The default port is 8000. You can change this in the uvicorn.run command in backend/main.py (line 19).

For example, to run the application on localhost and port 5000, you would modify the command in backend/main.py as follows:

# backend/main.py
# ... (rest of the code)

if __name__ == "__main__":
    uvicorn.run("main:app", host="127.0.0.1", port=5000, reload=True)

CORS Configuration

The Cross-Origin Resource Sharing (CORS) configuration is set in backend/main.py (lines 12-19). If you need to allow requests from different origins (e.g., a different port or domain where your frontend is running), you can modify the origins list:

# backend/main.py
origins = [
    "http://localhost:3000",
    "localhost:3000",
    "Your_Backend_Deployed_Link"
]

Deployment Process on GCP

The backend is deployed on Google Cloud Platform (GCP) using Cloud Run. The Dockerfile is used to build the container image, which is then deployed to Cloud Run.

Deployed Links

Frontend: https://heroic-ats-frontend.vercel.app/

Follow for more:

Linkedin: https://www.linkedin.com/in/wankhede-gaurav/ Portfolio: https://gaurav-wankhede.vercel.app/ Instagram: https://www.instagram.com/_gaurav_wankhede_/