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rag_tutorials/llama3.1_local_rag/README.md

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+## 💻 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
+
+```bash
+git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
+```
+2. Install the required dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+3. Run the Streamlit App
+```bash
+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.
+