Build LangChain Applications using Vertex AI: laboratório com desafio avaliações

SHIVANK U. · Revisado há about 1 year

YERRAM A. · Revisado há about 1 year

Maurizio . · Revisado há about 1 year

He H. · Revisado há about 1 year

Alan J. · Revisado há about 1 year

Salman A. · Revisado há about 1 year

Vikas S. · Revisado há about 1 year

Michal R. · Revisado há about 1 year

S Narendra D. · Revisado há about 1 year

PADMA M. · Revisado há about 1 year

Ashish W. · Revisado há about 1 year

Muhammad H. · Revisado há about 1 year

Lakshit J. · Revisado há about 1 year

Working by marcodelmart.com

Marco Flavio D. · Revisado há about 1 year

Thanks

El H. · Revisado há about 1 year

jupyter labs keep locking up and it took almost to the end of the timer to get this to finish

Joey G. · Revisado há about 1 year

Seakingretsu G. · Revisado há about 1 year

Raghu D. · Revisado há about 1 year

Task 2 Sose not work with; text_splitter = INSERT_CLASSNAME(chunk_size=10000, chunk_overlap=1000) docs = text_splitter.INSERT_METHOD_NAME(documents) print(f"# of documents = {len(docs)}") instead need to use text_splitter = RecursiveCharacterTextSplitter(chunk_size=10000, chunk_overlap=1000) # Assuming 'documents' contains Document objects, extract the text content text_contents = [doc.page_content for doc in documents if hasattr(doc, 'page_content')] # Split each document's text into smaller chunks docs = [] for text in text_contents: split_docs = text_splitter.create_documents([text]) # Split each document separately docs.extend(split_docs) print(f"# of documents = {len(docs)}")

Yoha G. · Revisado há about 1 year

Carlos G. · Revisado há about 1 year

Malvika V. · Revisado há about 1 year

Sameer D. · Revisado há about 1 year

vaibhav s. · Revisado há about 1 year

Saish B. · Revisado há about 1 year

Jacek S. · Revisado há about 1 year