/FoodRAG

Primary LanguagePython

NutriChatBot

Welcome to the NutriChatBot repository! This ChatBot is designed to provide users with reliable nutritional information from a unique dual-perspective approach—both as a patient and a doctor. Our ChatBot utilizes advanced Retrieval Augmented Generation (RAG) techniques to fetch factual data from external sources, ensuring that users receive accurate and up-to-date information.

FoodRAG

Features

  • Dual Perspective Interaction: Engage with the ChatBot either as a patient seeking nutritional advice or a healthcare professional looking for detailed nutritional data.
  • Retrieval Augmented Generation: Leverages a sophisticated RAG system to enhance the response quality with verified external data.
  • Interactive Experience: Designed to be user-friendly, allowing for easy and effective interactions.

How It Works

The NutriChatBot uses a combination of natural language processing and retrieval techniques to provide information that is both precise and relevant. Here’s how it interacts with users:

  1. User Query: You start by asking a question related to nutrition.
  2. Data Retrieval: The ChatBot then retrieves information from its extensive database of nutritional data.
  3. Response Generation: Using the RAG system, the ChatBot formulates a response that not only answers your question but also provides additional context where necessary.

Getting Started

To start using the NutriChatBot, clone this repository and follow the instructions below:

Follow setup instructions in setup_env.txt

Execute following command.

streamlit run main.py