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Running RAG Example Notebooks

About the Notebooks

The notebooks show how to use the langchain-nvidia-ai-endpoints and llama-index-embeddings-nvidia Python packages. These packages provide the basics for developing a RAG application and performing inference either from NVIDIA API Catalog endpoints or a local deployment of NVIDIA microservices.

Prerequisites

Running the Notebooks

  1. Export your NVIDIA API key as an environment variable:

    export NVIDIA_API_KEY="nvapi-<...>"

  2. Create a virtual environment:

    python3 -m venv .venv
source .venv/bin/activate

  3. Install JupyterLab in the virtual environment:

    pip3 install jupyterlab

  4. Start the JupyterLab server:

    jupyter lab --allow-root --ip=0.0.0.0 --NotebookApp.token='' --port=8889

  5. Open a web browser and access http://localhost:8889/lab.

    Browse to the RAG/notebooks directory to open an execute the cells of the notebooks.