text: To use this, we added the add_files() method (and from_files()). Let's see this in action. We pick two PDF documents to upload: The "I have a dream" speech by Dr. KingChurchill's "We Shall Fight on the Beaches" speechimport tempfileimport urllib.requesturls = [    [        "https://www.gilderlehrman.org/sites/default/files/inline-pdfs/king.dreamspeech.excerpts.pdf",        "I-have-a-dream",    ],    [        "https://www.parkwayschools.net/cms/lib/MO01931486/Centricity/Domain/1578/Churchill_Beaches_Speech.pdf",        "we shall fight on the beaches",    ],]files_list = []for url, _ in urls:    name = tempfile.NamedTemporaryFile().name    urllib.request.urlretrieve(url, name)    files_list.append(name)docsearch: Vectara = Vectara.from_files(    files=files_list,    embedding=FakeEmbeddings(size=768),    metadatas=[{"url": url, "speech": title} for url, title in urls],)Similarity searchâ€‹The simplest scenario for using Vectara is to perform a similarity search. query = "What did the president say about Ketanji Brown Jackson"found_docs = vectara.similarity_search(    query, n_sentence_context=0, filter="doc.speech = 'state-of-the-union'")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