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Retrieval-Augmented Generation (RAG)

A short, guided Google Colab walkthrough for trying retrieval-augmented generation using NVIDIA's NIM cloud API, which offers free large language model inference on a T4 GPU runtime.

Retrieval-Augmented Generation (RAG)

This project is a brief, step-by-step guide rather than a packaged application: it walks a reader through registering for NVIDIA's NIM APIs, browsing or searching the available hosted models, viewing a chosen model's sample code, and generating an API key for it. The reader then opens the accompanying Colab notebook, switches its runtime to a T4 GPU, and pastes the API key into the first cell to run large language model inference against the selected NVIDIA-hosted model.

The material frames this as a way to experience retrieval-augmented generation in a few minutes using free, cloud-hosted inference rather than local hardware, though the captured instructions themselves mainly cover obtaining API access and running the Colab notebook rather than detailing the retrieval or indexing steps of the pipeline.

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