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Milele/nutrition-rag-app

sourceHugging Faceupdated 1y agoView on Hugging Face
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App README

🧠 Nutrition Disorder Specialist Chatbot

A Retrieval-Augmented Generation (RAG) based AI assistant designed to help clinicians, researchers, and health professionals quickly retrieve evidence-based insights on nutritional disorders from trusted medical literature.

🔍 Features

  • —Semantic Search: Ask natural language questions and get accurate, context-grounded answers.
  • —Structured Retrieval: Filter results based on metadata like source document and page number.
  • —Chroma Vector Store: Efficient retrieval using semantic chunks indexed from medical reference PDFs.
  • —Streamlit Interface: Easy-to-use, interactive frontend for real-time querying.
  • —Dockerized Deployment: Fully containerized and deployed via Hugging Face Docker Spaces.

📁 Project Structure

bash
├── app.py               # Streamlit frontend with LangChain pipeline
├── requirements.txt     # Python dependencies
├── Dockerfile           # Docker build instructions
├── nutritional_db/      # Chroma vector store containing indexed medical data
└── README.md            # Project description (this file)

🚀 How to Use

  1. 1.Visit the app at: https://huggingface.co/spaces/Milele/nutrition-rag-app
  2. 2.Ask questions like:
  3. 3."What are the symptoms of zinc deficiency?"
  4. 4."List the recommended daily allowances for trace minerals."
  5. 5.Get context-backed, citation-aware responses pulled from structured documents.

🛠️ Built With

👥 Authors

Developed by InnoviTech Solutions in partnership with the Global Nutrition Health Organization.

Developer: Grace Burns

Empowering nutritional care through intelligent retrieval and generative AI.