llama3.1_local_rag

- 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.