MunnaBh-AI: An AI Healthcare Chatbot for Diagnosis

Table of Contents

1. Introduction
2. Features
3. Architecture
4. Installation
5. Usage
6. Configuration
7. License
8. Contact

Introduction

MunnaBh-AI is an AI-driven healthcare chatbot designed to assist in diagnosing, treating, and providing medical information. This project leverages a custom-built Large Language Model (LLM) and integrates with various tools to offer a holistic healthcare solution.

Features

• Google OAuth Login for secure user authentication.
• Integration with Google Fit using NoCode API to gather health data.
• Support for uploading X-rays and MRI scans for analysis.
• Diagnosis, treatment recommendations, and medical information delivery.

Architecture

Briefly describe the architecture of MunnaBh-AI, including the main components and how they interact:

• Frontend: Developed using React.js
• Backend: Powered by FastAPI
• AI Model: Custom-built LLM using mistral AI with pincone vector database to create embeddings.
• Integration: Google OAuth, Google Fit API

Installation

Prerequisites

• Node.js
• Python (3.10)
• Google Fit app (Not mandatory)

Steps

1. Clone the repository:

   git clone https://github.com/reddy-j-harshith/MS-MUNNABH-AI
   cd MS-MUNNABH-AI

2. Install dependencies:

    npm install
    pip install -r backend\requirements.txt

3. Start the application:

• To start the server from backend

   uvicorn backend.main:app --reload

• To start the frontend from backend/frontend

   npm install

   npm start

Usage

1. Start the application.
2. Login using your Google Account.
3. Interact with the chatbot to input symptoms, upload medical images, and receive diagnoses and recommendations.

License

This project is licensed under the terms of the MIT License

Contributors

• Sri Jaitra Saketh Goparaju [email protected]
• Jeeru Harshith Reddy [email protected]