Modso RAG (Retrieval-Augmented Generation System)

A modular Python-based Retrieval-Augmented Generation (RAG) system designed for document retrieval and context-aware LLM text generation.

Project Structure

• app.py: Main application entry point (typically a Streamlit or Gradio UI).
• download_and_setup.py: Automated script for downloading necessary datasets, assets, or models.
• llm_service.py: Integration layer for communicating with Large Language Models.
• retriever.py: Logic for searching and fetching relevant context chunks from the vector store.
• vector_store.py: Manages vector embeddings, database creation, and similarity searches.
• requirements.txt: Project Python dependencies.

Requirements

Install dependencies using pip:

pip install -r requirements.txt

Running the Application

To start the app:

python app.py