Allergies Helper Assistant

The Allergies Helper Assistant is a web application designed to help users identify potential respiratory issues based on their symptoms. It dynamically interacts with users, retrieves relevant medical knowledge, and generates AI-powered responses to provide guidance.

---

Features

• Interactive User Interface:

  • Chat-like interface where users can input their symptoms.
  • Dynamic follow-up questions to gather detailed information.

• Backend with Flask:

  • Tracks conversation history for each user.
  • Integrates with a structured knowledge base to retrieve relevant contexts.
  • Generates responses using the OpenAI API.

• AI-Powered Responses:

  • Leverages the OpenAI API to provide contextual and detailed medical guidance.
  • Dynamically generates follow-up questions and possible diagnoses.

• Knowledge Base Integration:

  • Extracts data from medical documents (PDFs, DOCX).
  • Provides up-to-date resources for symptom analysis and response generation.

• Multilingual Support:

  • Responds in the user's preferred language (e.g., English, Romanian).

• Frontend (React):

  • Clean and responsive UI for smooth interaction.
  • Displays scrollable responses for detailed outputs.

Requirements

• Frontend:

  • React.js
  • Axios for API communication.

• Backend:

  • Flask
  • Flask-CORS for cross-origin resource sharing.
  • OpenAI API for AI-powered responses.
  • Sentence Transformers for knowledge base search.

• Knowledge Base:

  • Extracts and processes medical data from PDFs and DOCX files.

Installation and Setup

Prerequisites

• Node.js
• Python 3.8 or later
• pip (Python package manager)

Clone the Repository

git clone https://github.com/raulradulescu/RAG-IP-application.git
cd RAG-IP-application

Backend Setup

1. Create a virtual environment and activate it:

   python -m venv venv
   source venv/bin/activate   # On Windows: venv\Scripts\activate

2. Install dependencies:

   pip install -r requirements.txt

3. Set your OpenAI API key as an environment variable:

   export GLHF_API_KEY=<your_openai_api_key>
   # On Windows:
   set GLHF_API_KEY=<your_openai_api_key>

4. Run the Flask backend:

   python app.py

Frontend Setup

1. Navigate to the rag-webapp directory:

   cd rag-webapp

2. Install dependencies:

   npm install

3. Start the React development server:

   npm start

Usage

1. Open the frontend in your browser (http://localhost:3000).
2. Enter your symptoms into the input field.
3. View the AI-generated responses and follow-up questions.
4. Get a possible diagnosis and guidance based on your symptoms.