RAG 'n' ROLL Assistant

A smart Retrieval-Augmented Generation (RAG) application using:

• Cortex Search for document retrieval
• Mistral LLM on Snowflake Cortex for response generation
• Streamlit Community Cloud for the front-end interface

Features

• Retrieve relevant documents using Cortex Search
• Generate context-aware answers with Mistral LLM
• Interactive and user-friendly web app built with Streamlit

How It Works

1. Enter a query in the Streamlit interface.
2. Cortex Search retrieves the top relevant documents.
3. Mistral LLM processes the retrieved documents and generates a response.
4. The app displays both the retrieved documents and the generated response.

Prerequisites

• Python 3.x installed
• API access for Cortex Search and Mistral LLM on Snowflake Cortex
• A dataset indexed in Cortex Search
• Required Python packages: streamlit, requests, snowflake-snowpark-python

Installation

Clone this repository:

• git clone https://github.com/sahasraa/RAG-n-ROLL-Assistant.git
• cd rag-n-roll-assistant