1Z0-1127-25 OCI Generative AI Service Practice Question
A developer uses the OCI Generative AI Chat API to build a multi-turn conversational agent. They notice the model starts to lose context after several exchanges. 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 developer is not sending the conversation history with each request
The Chat API does not automatically manage conversation history; the developer must provide previous messages. The model itself retains state only within the provided context.
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 temperature parameter is set too high, causing the model to forget
Why it's wrong here
Temperature does not affect memory; it only influences randomness.
- ✗
The model's context window is too small for the conversation length
Why it's wrong here
While possible, the typical cause is not providing history, not necessarily window size.
- ✓
The developer is not sending the conversation history with each request
Why this is correct
The Chat API requires the client to include previous messages; otherwise the model has no context of prior turns.
- ✗
The fine-tuning dataset did not include multi-turn examples
Why it's wrong here
Even if fine-tuned, the API still requires history to be passed; this is not a root cause for the API behavior.
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