1Z0-1127-25 LangChain and AI Application Development Practice Question
An AI developer is building a document Q&A application using LangChain and OCI Generative AI. They need to split large PDF documents into smaller chunks before embedding. Which text splitter should they use to ensure splits respect sentence boundaries while also controlling chunk size?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
RecursiveCharacterTextSplitter
RecursiveCharacterTextSplitter splits text recursively by separators (like \n\n, \n, period) to keep semantically related text together and respects sentence-like boundaries. TokenTextSplitter splits by tokens without regard for sentence boundaries. PDFLoader and WebBaseLoader are document loaders, not splitters.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
RecursiveCharacterTextSplitter
Why this is correct
This splitter recursively splits text by a list of separators, keeping paragraphs and sentences intact while controlling chunk size.
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WebBaseLoader
Why it's wrong here
WebBaseLoader loads content from URLs; it is not a text splitter.
- ✗
PDFLoader
Why it's wrong here
PDFLoader is a document loader, not a text splitter; it loads PDF content into documents.
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TokenTextSplitter
Why it's wrong here
TokenTextSplitter splits by token count, which may cut in the middle of sentences.
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