This repository contains a simple application that uses the Word2Vec model to recommend similar ingredients based on the user's selection. The application provides a user-friendly interface where you can select up to 6 ingredients, and it will display a list of recommended ingredients that are similar to the selected ones.
The application utilizes the Gensim library to load a pre-trained Word2Vec model that has learned to represent words (in this case, ingredients) in a high-dimensional vector space. The model captures semantic relationships between words, allowing it to find ingredients that are similar in meaning or context.
Check out the live demo of the Ingredient Recommender application here.
To run this application, you need to have Python and the required libraries installed. You can install the necessary dependencies using the following command:
pip install gensim gradio- Clone this repository to your local machine:
git clone https://github.com/egecandrsn/ingredient-recommender.git- Navigate to the project directory:
cd ingredient-recommender- Run the application:
python app.py-
A web interface will open in your default web browser. You can select ingredients from the dropdown menus. Choose up to 6 ingredients, and the application will display a list of recommended ingredients based on your selection.
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Experiment with different ingredient combinations to explore various recommendations.
Contributions are welcome! If you find any issues or want to add new features, feel free to create a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.
Feel free to modify and expand upon this README as needed to provide more information about your project, its purpose, and how users can use or contribute to it.