RAG_LLM_QnA_Assistant

Demo of Q&A Assistant base on RAG and LLM

/RAG_LLM_WithROCm$ tree -L 1
.
├── data //PDF files for RAG indexing
├── demo //RAG chatbot demo with Steamlit GUI
├── labs //RAG labs
├── README.md
├── resources //for markdown
└── Run_Ollama_with_AMD_iGPU780M-QuickStart.md

Quick Start

1. Setup ROCm environment and run LLM with iGPU

Refer to Run_Ollama_with_AMD_iGPU780M-QuickStart.md setup the ROCm and Ollama to run the LLM

2. Try RAG in Labs

Here are many jupyterlab files to help you setup the RAG pipeline with Ollama+LlamaIndex.

NOTE: You should add PDF file in ./data for RAG indexing

3. Try RAG Chatbot Demo

A RAG Chatbot Demo with GUI base on streamlit base on the example in Labs.

NOTE: You should add PDF file in ./demo/data for RAG indexing

Demo Show