1Z0-1127-25 LangChain and AI Application Development Practice Question
An application uses LangChain's ConversationalRetrievalChain with memory. Users report that the chatbot occasionally repeats information from earlier in the conversation even when the new question is unrelated. What is the most likely cause?
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 retriever is returning irrelevant documents from the conversation history
The chain retrieves documents based on the conversation history plus the current question; if the retriever returns irrelevant chunks from past context, the LLM may repeat old information.
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 memory type is set to ConversationSummaryMemory
Why it's wrong here
SummaryMemory compresses history, it doesn't cause repetition directly.
- ✗
The chunk_size is too small, causing loss of context
Why it's wrong here
Small chunks may lack context but don't cause repetition of old info.
- ✓
The retriever is returning irrelevant documents from the conversation history
Why this is correct
ConversationalRetrievalChain uses the chat history to formulate a new query; if the retrieval is broad, old topics may resurface.
- ✗
The LLM temperature is set too high
Why it's wrong here
High temperature increases randomness, not repetition of old info.
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