text: embeddings,    url,    prefer_grpc=True,    collection_name="my_documents",    force_recreate=True,)Similarity searchâ€‹The simplest scenario for using Qdrant vector store is to perform a similarity search. Under the hood, our query will be encoded with the embedding_function and used to find similar documents in Qdrant collection.query = "What did the president say about Ketanji Brown Jackson"found_docs = qdrant.similarity_search(query)print(found_docs[0].page_content)    Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Voting Rights Act. And while youâ€™re at it, pass the Disclose Act so Americans can know who is funding our elections.         Tonight, Iâ€™d like to honor someone who has dedicated his life to serve this country: Justice Stephen Breyerâ€”an Army veteran, Constitutional scholar, and retiring Justice of the United States Supreme Court. Justice Breyer, thank you for your service.         One of the most serious constitutional responsibilities a President has is nominating someone to serve on the United States Supreme Court.         And I did that 4 days ago, when I nominated Circuit Court of Appeals Judge Ketanji Brown Jackson. One of our nationâ€™s top legal minds, who will continue Justice Breyerâ€™s legacy of excellence.Similarity search with scoreâ€‹Sometimes we might want to perform the search, but also obtain a relevancy score to know how good is a particular result.