This is an example for a very basic RAG architecture using semantic search (kNN), keyword search (BM25) and reranking with RFF. We dont use any vector database, but loads all embeddings into memory.

The KNN class is defined in the code, and it has two methods: fit(), which trains the classifier on the data, and predict(), which forecasts the class of a new instance. The mean and standard ...