This project is a comprehensive, interactive, and intuitive recipe finder that leverages a combination of cutting-edge technologies to provide users with personalized access to a database of over 100,000 recipes from 50+ cuisines. Find the best recipes for you and eat healthy food from around the world!
Todo:
- Webscraping
- MongoDB Database
- Web Application infrastructure and landing page
- Search function for website
- Account creation and recipe saving
- LLM finetuned
- LLM APIs setup
- Frontend for LLm interaction built
The motivation behind this project is two-fold:
- Full-stack Programming Practice: This project provided a great opportunity to delve into full-stack development, and get hands-on experience working with databases, APIs, front-end, and back-end technologies.
- Building a NoSQL Database: The project allowed the exploration and implementation of a NoSQL database (MongoDB) and utilizing it through REST APIs.
- Development of a Language Model for Custom Data: Leveraged a large language model to build a "ChatGPT" trained on our MongoDB database that users can interface with
- Implement a Full MERN Stack: This project is a practical application of the MERN (MongoDB, Express, React, Node.js) stack. It allowed the learning and practicing of Javascript, HTML, CSS basics.
- Practicing Project Management Skills: The project also offered a chance to develop PM skills such as planning, coordinating and executing a tech project.
Intricate UI design with complete user interaction functionality. Some of the key features include:
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The backend is a MERN stack which includes MongoDB as the database, Express server to handle API requests, and React for front-end interfacing.
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It also includes Python-based machine learning models put up as APIs for advanced features.
This project includes a detailed search function that provides the user with numerous recipes based on their search criteria.
- Search criteria: -- Dish: Pasta -- Ingredients: Chicken; spinach; tomato
- Results:
