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License: MIT License

HTML 22.44% Python 77.56%
ai data-science flask ml mlalgotithms personal-assistant recipes recommender-system stramlit voice

recipe-recommendation-system's Introduction

Personalized Recipe Recommendation System

Welcome to the Personalized Recipe Recommendation System! This project suggests recipes based on ingredients you have at home, dietary preferences, and past cooking history. It also integrates a virtual kitchen assistant to make your cooking experience seamless and interactive.

Features

  • Personalized Recipe Suggestions: Get recipe recommendations based on the ingredients you have.
  • Dietary Preferences: Filter recipes according to dietary restrictions or preferences.
  • Past Cooking History: Enhance recommendations based on your previous cooking activities.
  • Virtual Kitchen Assistant: Interact with a virtual assistant for cooking instructions, ingredient substitutions, and more.
  • Web Application: User-friendly interface for easy interaction and recipe browsing.

Dataset

We used the Food.com Recipes and Reviews and Recipes and Interactions datasets from Kaggle for our recipe data.

Installation

  1. Clone the repository

    git clone https://github.com/Raufjatoi/Recipe-Recommendation-System.git
    cd Recipe-Recommendation-System
  2. Create and activate a virtual environment

    python3 -m venv env
    source env/bin/activate
  3. Install the required dependencies

    pip install -r requirements.txt
  4. Download the datasets and place them in the data folder

  5. Run the application

    python app.py

Usage

  1. Launch the Web Application

    • Open your web browser and go to http://127.0.0.1:5000.
  2. Enter Your Ingredients

    • In the input field, enter the ingredients you have at home, separated by commas.
  3. Get Recommendations

    • Click the "Get Recommendations" button to view personalized recipe suggestions.
  4. Interact with the Virtual Kitchen Assistant

    • Use the virtual assistant to get step-by-step cooking instructions, ingredient substitutions, and more.

File Structure

recipe-recommendation-system/

├── data/ # Folder containing the recipe datasets

├── templates/ # HTML templates for the web application
│ └── index.html # Home page of the web application

├── app.py # Main application file

├── preprocess.py # Script for data preprocessing

├── recommender.py # Script for the recommendation system

├── assistant.py # Script for the virtual kitchen assistant

├── requirements.txt # List of required Python packages

└── README.md # Project documentation

Contributing

We welcome contributions to enhance this project! Here’s how you can contribute:

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

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

  • Kaggle for providing the datasets
  • The open-source community for their invaluable tools and resources

Contact

If you have any questions or feedback, please reach out to us at [[email protected]].

Happy Cooking! 🍳🥗🍲

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