Health AI Consultant

A professional RAG-powered health consultation application using Flask, React, and Ollama.

Overview

Health AI Consultant is a modern web application that provides AI-powered health information and consultation services. It uses Retrieval-Augmented Generation (RAG) to ensure responses are grounded in reliable health information, preventing hallucinations and providing factual answers to health-related queries.

The application features a clean, professional user interface built with React and Tailwind CSS, and a robust backend powered by Flask and Ollama. All processing happens locally, ensuring privacy and data security.

Features

• AI-Powered Health Chat: Ask health-related questions and receive informative responses
• Document Upload: Add health documents to enhance the knowledge base
• Citation Support: View sources for information provided in responses
• Responsive Design: Works on desktop and mobile devices
• Local Processing: All data stays on your machine for privacy

Tech Stack

Backend

• Flask: Python web framework for the API
• Ollama: Local large language model inference
• ChromaDB: Vector database for document storage and retrieval
• LangChain: Framework for building LLM applications

Frontend

• React: JavaScript library for building the user interface
• Vite: Next-generation frontend tooling
• Tailwind CSS: Utility-first CSS framework
• React Router: Declarative routing for React

Getting Started

Prerequisites

• Python 3.9+
• Node.js 16+
• Ollama installed and running locally

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/health-ai-consultant.git
   cd health-ai-consultant
   

2. Set up the backend:

   # Install Python dependencies
   pip install -r requirements.txt
   

3. Set up the frontend:

   cd frontend
   npm install
   

4. Create a .env file in the root directory with the following content:

   OLLAMA_BASE_URL=http://localhost:11434
   FLASK_ENV=development
   DEBUG=True
   

Running the Application

1. Start the backend server:

   python app_flask.py
   

2. In a separate terminal, start the frontend development server:

   cd frontend
   npm run dev
   

3. Open your browser and navigate to http://localhost:3000

Usage

1. Chat Interface: Type your health-related questions in the chat input and press Enter or click the Send button
2. Document Upload: Navigate to the Upload section to add health documents to the knowledge base
3. View Sources: Click on citations in responses to see the source of information

Deployment

The application can be deployed using:

• Frontend: Vercel, Netlify, or GitHub Pages
• Backend: Railway, Render, or any platform supporting Python applications

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Built with Ollama for local AI inference
• Powered by LangChain and ChromaDB for RAG capabilities
• Designed with Tailwind CSS for a modern UI