The Book Recommendation App is an open-source project designed to provide personalized book recommendations to users based on their category, genre, and mood preferences. It uses a content-based filtering algorithm to enhance recommendation relevance.
- User-friendly web interface for inputting preferences.
- Utilizes the Google Books API for book data.
- Enhanced recommendations using content-based filtering.
- Detailed README and instruction for contribution.
- Python 3.9
To run this project locally, follow these instructions:
- Clone this repository:
git clone https://github.com/fury-05/Book-Recommendation-App.git
- Change to the project directory:
cd Book-Recommendation-App
- Install the required packages:
pip install -r requirements.txt
-
Set up the Google Books API key:
- Obtain a Google Books API key and add it to your environment or create a Replit Secrets variable named "google_api_key".
-
Set up the New York Times API key:
- Obtain a New York Times API key and add it to your environment or create a Replit Secrets variable named "nyt_api_key".
- Run the application:
python main.py
- Access the app in your web browser at
http://localhost:5000
.
We welcome contributions from the community to enhance and refine the Book Recommendation App. If you'd like to contribute, please follow these steps:
-
Fork this repository to your GitHub account.
-
Clone your forked repository:
git clone https://github.com/YourUsername/Book-Recommendation-App.git
- Create a new branch for your feature or bug fix:
git checkout -b feature/your-feature-name
- Make your changes and commit them:
git commit -m "Add your feature description"
- Push your changes to your GitHub repository:
git push origin feature/your-feature-name
-
Create a pull request (PR) from your GitHub repository to the main repository.
-
Await approval from the project maintainers to merge your PR.
This project is licensed under the MIT License - see the LICENSE file for details.
Version 1.1.0
Expanding Raw API Data View - For Developers For Trouble Shooting Or Demonstrating How We Fetch Data.
We appreciate your contributions to make the Book Recommendation App even better!