A case study on how to simply create a search system with txtai, Qdrant and pretrained language models. The cool thing about the semantic search is that none of the words used in a query has to be used in any document in our dataset, as the model is already capable of capturing synonyms. This is a huge advantage over conventional search algorithms like BM25.
