eDNA Backend API

This repository contains the backend API for the eDNA classification project. It uses FastAPI to serve a PyTorch deep learning model that predicts the phylum of an organism based on a raw DNA sequence.

Getting Started

Follow these instructions to get a local copy of the project up and running for development and testing.

Prerequisites

Make sure you have Python 3.8+ installed on your system.

Installation

1. Clone the repository:

   git clone https://github.com/ssrithwik007/eDNA-backend.git
   cd eDNA-backend

2. Create and activate a virtual environment:

   # Create the virtual environment
   python -m venv venv
   
   # Activate it:
   # On Windows (PowerShell)
   .\venv\Scripts\activate
   
   # On macOS / Linux
   source venv/bin/activate

3. Install the required packages: This command reads the requirements.txt file and installs all the necessary libraries for the project.

   pip install -r requirements.txt

Running the Application

Once the installation is complete, you can run the API server.

From the project's root directory (backend), run the following command to start the Uvicorn server:

uvicorn app.main:app --reload

The --reload flag makes the server restart automatically when you make changes to the code.

The API will now be running and available at http://127.0.0.1:8000. 🚀

API Usage

You can interact with the API in two primary ways:

1. Interactive Docs (Recommended): Navigate to http://127.0.0.1:8000/docs in your browser to see the automatically generated Swagger UI documentation. You can test the endpoints directly from this page.

2. Using curl: You can send a POST request to the /predict endpoint from your terminal.

   curl -X 'POST' \
     'http://127.0.0.1:8000/predict' \
     -H 'accept: application/json' \
     -H 'Content-Type: application/json' \
     -d '{
     "sequence": "GTCGATCGGCTAGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCATGCTAGCTAGCA"
   }'