# Food Recipes Rating System Based on Sentiment Analysis

## Table of Contents

- [Introduction](#introduction)

- [Features](#features)

- [Tech Stack](#tech-stack)

- [Installation](#installation)

- [Usage](#usage)

- [Project Structure](#project-structure)

- [Contributing](#contributing)

- [License](#license)

## Introduction

This project is a Food Recipes Rating System that utilizes sentiment analysis to rate reviews. Reviews are analyzed using an LSTM model to determine their sentiment, which then translates into a numerical rating from 1 to 5. The system is built using Django for the backend, and it incorporates NLTK and Scikit-learn for natural language processing and machine learning.

## Features

- User authentication using GitHub OAuth

- Recipe posting with detailed descriptions and images

- Review submission with sentiment-based rating (1 to 5)

- Sentiment analysis using a custom LSTM model

- Email notifications through Google API

## Tech Stack

- **Backend:** Django

- **Natural Language Processing:** NLTK, Scikit-learn

- **Machine Learning Model:** LSTM (Long Short-Term Memory)

- **Authentication:** GitHub OAuth

- **Email Service:** Google API

- **Database:** SQLite (default Django setup)

## Installation

1. **Clone the repository:**

```bash

git clone https://github.com/yourusername/food-recipes-rating-system.git

cd food-recipes-rating-system

```

2. **Create a virtual environment and activate it:**

```bash

python3 -m venv venv

source venv/bin/activate # On Windows, use `venv\Scripts\activate`

```

3. **Install the dependencies:**

```bash

pip install -r requirements.txt

```

4. **Apply the migrations:**

```bash

python manage.py migrate

```

5. **Run the development server:**

```bash

python manage.py runserver

```

## Usage

1. **Navigate to the homepage:**

Open your web browser and go to `http://127.0.0.1:8000/`.

2. **Sign in using GitHub:**

Use GitHub OAuth to authenticate and access the platform.

3. **Post a recipe:**

Create a new recipe by filling out the form with the required details.

4. **Submit a review:**

Leave a review for any recipe. The sentiment of your review will be analyzed, and a rating from 1 to 5 will be assigned based on the sentiment score.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.