Simple RAG System

🩺 Acupuncture Clinical Advisor - Retrieval-Augmented Generation (RAG)

📌 Overview

🏗️ Project Structure

├── main.py                 # Streamlit-based user interface
├── rag_notebook.ipynb      # Notebook for processing PDFs and creating FAISS index
├── requirements.txt        # Dependencies for the project
├── faiss_index/            # FAISS vector store directory
├── Acupuncture_PDFs/       # Directory containing clinical guideline PDFs
└── README.md               # Project documentation

🚀 Features

📥 Installation

1️⃣ Clone the Repository

git clone https://github.com/yourusername/acupuncture-rag.git
cd acupuncture-rag

2️⃣ Create a Virtual Environment

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

3️⃣ Install Dependencies

pip install -r requirements.txt

🔑 API Key Configuration

GROQ_API_KEY=your_api_key_here

📚 Preparing the Knowledge Base

1️⃣ Process Clinical Guidelines (PDFs)

python rag_notebook.py

2️⃣ Start the Streamlit Application

streamlit run main.py

📌 Usage

🛠️ Technologies Used

📝 License

🤝 Contributing

📧 Contact