Uses RAG to scan a collection of crypto whitepapers (~1100) to answer questions about the inner workings of cryptocurrencies.

use rag.ipynb to preprocess the text, generate the embeddings and do inference.

the model returns the response and the relaxant passages it uses for context

change the topic to ask about different collections of text