- A
PDFLoader
Why wrong: PDFLoader is for PDF documents.
- B
TextLoader
Why wrong: TextLoader is for plain text files, not CSV.
- C
TokenTextSplitter
TokenTextSplitter is a valid option but any text splitter works; the question asks for TWO components: a loader and a splitter.
- D
CSVLoader
CSVLoader reads CSV files and yields Document objects.
- E
TextSplitter
A text splitter divides the loaded documents into chunks.
Question 5 of 991
1Z0-1127 LangChain and AI Application Development Practice Question
This 1Z0-1127 practice question tests your understanding of langchain and ai application development. Read the scenario carefully and evaluate each option against the stated constraints before committing to an answer. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
A developer wants to load a CSV file containing customer feedback and split it into chunks for a RAG pipeline. Which TWO LangChain components should they use?
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
✓
TokenTextSplitter
Option C (TokenTextSplitter) is correct because it splits text into chunks based on token count, which is essential for RAG pipelines to ensure each chunk fits within the context window of an LLM. Option D (CSVLoader) is correct because it is specifically designed to load CSV files, making it the appropriate choice for ingesting the customer feedback data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
PDFLoader
Why it's wrong here
PDFLoader is for PDF documents.
- ✗
TextLoader
Why it's wrong here
TextLoader is for plain text files, not CSV.
- ✓
TokenTextSplitter
Why this is correct
TokenTextSplitter is a valid option but any text splitter works; the question asks for TWO components: a loader and a splitter.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
CSVLoader
Why this is correct
CSVLoader reads CSV files and yields Document objects.
Related concept
Read the scenario before looking for a memorised answer.
- ✓
TextSplitter
Why this is correct
A text splitter divides the loaded documents into chunks.
Related concept
Read the scenario before looking for a memorised answer.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Cisco often tests the distinction between abstract base classes (TextSplitter) and concrete implementations (TokenTextSplitter), leading candidates to select the generic option when a specific one is required.
Detailed technical explanation
How to think about this question
TokenTextSplitter uses a tokenizer (e.g., from tiktoken) to count tokens accurately, ensuring chunks respect the LLM's token limit (e.g., 4096 tokens for GPT-3.5). CSVLoader internally uses Python's csv module to parse rows and columns, then converts each row into a Document object with metadata, preserving field names for downstream retrieval. In a real-world RAG pipeline, combining CSVLoader with TokenTextSplitter allows chunking feedback entries by token count while maintaining the original row structure for accurate context retrieval.
KKey Concepts to Remember
- Read the scenario before looking for a memorised answer.
- Find the constraint that changes the correct option.
- Eliminate answers that are true in general but not in this case.
TExam Day Tips
- Watch for words such as best, first, most likely and least administrative effort.
- Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A practitioner preparing for the 1Z0-1127 exam encounters this exact type of scenario on the job. The correct answer here is not the most general option — it is the best answer for the specific constraint described. Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option. Real exam questions reward reading the full scenario before eliminating options, because the constraint defines which answer fits.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
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FAQ
Questions learners often ask
What does this 1Z0-1127 question test?
LangChain and AI Application Development — This question tests LangChain and AI Application Development — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: TokenTextSplitter — Option C (TokenTextSplitter) is correct because it splits text into chunks based on token count, which is essential for RAG pipelines to ensure each chunk fits within the context window of an LLM. Option D (CSVLoader) is correct because it is specifically designed to load CSV files, making it the appropriate choice for ingesting the customer feedback data.
What should I do if I get this 1Z0-1127 question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Last reviewed: Jul 4, 2026
This 1Z0-1127 practice question is part of Courseiva's free Oracle certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the 1Z0-1127 exam.
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