- A
The conversation history accumulates in the prompt, causing the model to focus on past messages
Full history in the prompt can cause the model to rephrase or repeat past content.
- B
The chunk_size in the text splitter is too large
Why wrong: Chunk size affects retrieval quality, not conversation repetition.
- C
The LLM's max_tokens parameter is set too low
Why wrong: A low max_tokens truncates responses but does not directly cause repetition.
- D
The retriever's similarity search returns irrelevant chunks
Why wrong: Irrelevant chunks would cause off-topic answers, not repetition of earlier information.
Question 524 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 team is using LangChain's ConversationalRetrievalChain with ConversationBufferMemory to build a chatbot. After a few turns, the chatbot starts repeating information from earlier messages. What is the MOST likely cause?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue:
"most likely"Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
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
✓
The conversation history accumulates in the prompt, causing the model to focus on past messages
ConversationBufferMemory stores the entire conversation history, and each new query appends that history to the prompt. As history grows, the LLM may receive redundant context, causing repetition. Using ConversationSummaryMemory or limiting history length can mitigate this.
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.
- ✓
The conversation history accumulates in the prompt, causing the model to focus on past messages
Why this is correct
Full history in the prompt can cause the model to rephrase or repeat past content.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
- ✗
The chunk_size in the text splitter is too large
Why it's wrong here
Chunk size affects retrieval quality, not conversation repetition.
- ✗
The LLM's max_tokens parameter is set too low
Why it's wrong here
A low max_tokens truncates responses but does not directly cause repetition.
- ✗
The retriever's similarity search returns irrelevant chunks
Why it's wrong here
Irrelevant chunks would cause off-topic answers, not repetition of earlier information.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Many certification questions include familiar terms but test a specific constraint. Read the exact wording before choosing an answer that is generally true but wrong for this case.
Detailed technical explanation
How to think about this question
This question should be treated as a scenario, not a definition check. Identify the problem, the constraint and the best action. Then compare each option against those facts.
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.
- Use explanations to understand the rule behind the answer.
TExam Day Tips
- Underline the problem statement mentally.
- 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 1Z0-1127 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
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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: The conversation history accumulates in the prompt, causing the model to focus on past messages — ConversationBufferMemory stores the entire conversation history, and each new query appends that history to the prompt. As history grows, the LLM may receive redundant context, causing repetition. Using ConversationSummaryMemory or limiting history length can mitigate this.
What should I do if I get this 1Z0-1127 question wrong?
Identify which 1Z0-1127 exam domain this question belongs to, then review the specific concept being tested. Practise related questions in that domain and focus on understanding why each wrong answer is tempting — not just why the correct answer is right.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
About these practice questions
Courseiva creates original exam-style practice questions with explanations and wrong-answer analysis. It does not publish real exam questions, exam dumps, or protected exam content. Learn why practice questions differ from exam dumps →
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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