Llama3.1 Local RAG

💻 Local Lllama-3.1 with RAG

Streamlit app that allows you to chat with any webpage using local Llama-3.1 and Retrieval Augmented Generation (RAG). This app runs entirely on your computer, making it 100% free and without the need for an internet connection.

Features

• Input a webpage URL
• Ask questions about the content of the webpage
• Get accurate answers using RAG and the Llama-3.1 model running locally on your computer

How to get Started?

1. Clone the GitHub repository

git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
cd awesome-llm-apps/rag_tutorials/llama3.1_local_rag

2. Install the required dependencies:

pip install -r requirements.txt

3. Run the Streamlit App

streamlit run llama3.1_local_rag.py

How it Works?

• The app loads the webpage data using WebBaseLoader and splits it into chunks using RecursiveCharacterTextSplitter.
• It creates Ollama embeddings and a vector store using Chroma.
• The app sets up a RAG (Retrieval-Augmented Generation) chain, which retrieves relevant documents based on the user's question.
• The Llama-3.1 model is called to generate an answer using the retrieved context.
• The app displays the answer to the user's question.