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README.md
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llama3.1_local_rag.py
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requirements.txt
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README.md

💻 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
  1. Install the required dependencies:
pip install -r requirements.txt
  1. 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.