README.md

Aroma College Chatbot

A Retrieval-Augmented Generation (RAG) chatbot for answering questions about Aroma College using locally hosted Ollama models.

Prerequisites

1. Ollama must be installed and running on your machine
2. Python 3.8+ with pip and virtual environment

Setup

1. Create and activate the virtual environment:

   python -m venv .venv
   .venv\Scripts\activate  # On Windows
   source .venv/bin/activate  # On macOS/Linux
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Download Ollama model (in a separate terminal):

   ollama pull llama2     # For LLM completion
   

   Note: For embeddings, we're using the all-MiniLM-L6-v2 model from the sentence-transformers library.

Usage

1. Add college data

Place your college documents (PDF, DOCX, TXT, CSV) in the docs directory.

2. Ingest the data

Process and index the documents:

python main.py ingest --data-dir=./docs

3. Run the chatbot

You can use the chatbot in two ways:

• Web Interface: Start the Streamlit app

  python main.py web
  

  Then open your browser at http://localhost:8501

• Command Line: Ask questions directly from the terminal

  python main.py chat --question="What are the admission requirements for Aroma College?"
  

Project Structure

• main.py: Entry point for the application
• requirements.txt: Project dependencies
• data/: Directory for storing vector database
• docs/: Directory for college documents
• src/: Source code
  • ingestion/: Document loading and processing
  • database/: Vector database components
  • rag/: Retrieval and question answering
  • ui/: Streamlit web interface