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Healin - Medical Assistant

Healin is a futuristic, intelligent medical chatbot powered by Google Gemini and Pinecone vector embeddings. It uses a robust internal RAG (Retrieval-Augmented Generation) pipeline to fetch domain-specific medical knowledge to ensure accurate and context-aware responses.

Features

  • Cyberpunk UI: A beautifully stylized hacker-aesthetic chat interface.
  • RAG Architecture: Uses Pinecone for rapid document retrieval alongside Hugging Face embeddings.
  • Powered by Gemini: Fully integrated with the Google gemini-1.5-flash generative AI framework for instantaneous intelligence.

🚀 Beginner's Quick Start Guide

Follow these step-by-step instructions to run the application completely offline on your own machine.

1. Prerequisites

Make sure you have Python 3.10+ installed on your computer.

2. Prepare the Virtual Environment

Open your terminal (PowerShell or Command Prompt) and navigate into the project folder. Create and activate an isolated Python environment so your global packages don't conflict:

Create the environment: powershell python -m venv venv2

Activate the environment: powershell .\venv2\Scripts\activate (You should see (venv2) appear at the start of your terminal line).

3. Install Dependencies

With your environment active, install all required packages: powershell pip install -r requirements.txt

4. Configure Environment Variables

Create a file named literally .env inside the main project folder. Add your API keys inside this file: ini PINECONE_API_KEY="your_pinecone_key" HUGGINGFACEHUB_API_TOKEN="your_huggingface_token_for_embeddings" GOOGLE_API_KEY="your_google_gemini_api_key"

5. Initialize the Vector Store (First time only!)

If this is your first time setting up the project and Pinecone requires the medical documents, run the index script to build your vector database: powershell python store_index.py

6. Start the Application

Boot up the main Flask backend: powershell python app.py

7. Start Chatting

Open your favorite web browser (Chrome, Edge, Safari) and navigate to: 👉 http://127.0.0.1:8080

Note: All old boilerplate AWS, Docker, and deployment legacy artifacts have been cleanly removed to focus strictly on an optimized, fast offline RAG implementation.

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