NCA-GENL Software Development Practice Question
A developer is building a document-summarization service on NVIDIA NIM for LLMs and wants to stream partial tokens to the client while the model is still generating. The NIM endpoint exposes an OpenAI-compatible /chat/completions route. Which request parameter should the developer set to receive incremental token deltas rather than one complete response body?
⚠ Common exam trap
The trap here is assuming that an Accept header or a parameter like n or logprobs changes response timing, when only the stream field actually enables incremental token delivery.
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
✓
Set "stream": true in the JSON request body and consume the server-sent event chunks.
Streaming on an OpenAI-compatible NIM chat completions endpoint is controlled by the stream boolean in the request body, which switches the transport to server-sent events carrying incremental delta objects. The other parameters alter candidate count, content negotiation, or scoring metadata, and none of them cause tokens to be emitted before generation completes.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set "logprobs": true and reconstruct partial text from the token log probabilities.
Why it's wrong here
Requesting log probabilities returns scoring metadata alongside the completed text, not partial output. The response is still delivered as one payload after the model finishes, so the developer would have per-token confidence values but no way to render tokens to the user before the whole summarization job completes.
- ✗
Set the SSE header "Accept: text/event-stream" on the request without changing the body.
Why it's wrong here
Negotiating a content type does not by itself switch the endpoint into streaming mode. The OpenAI-compatible chat completions route decides its response framing from the stream field in the JSON body, so a header alone yields a normal single JSON response and the client still receives nothing until generation completes.
- ✗
Set "n": 2 so the endpoint returns two candidate completions the client can merge.
Why it's wrong here
The n parameter controls how many independent completion candidates are generated and billed, not how a single completion is delivered. Requesting multiple candidates still returns one complete JSON body after generation finishes, so the client would wait for the full summary and receive duplicate outputs it must then reconcile.
- ✓
Set "stream": true in the JSON request body and consume the server-sent event chunks.
Why this is correct
The OpenAI-compatible chat completions schema used by NIM for LLMs accepts a boolean stream field. When it is true, the server returns text/event-stream data chunks containing incremental choices delta objects terminated by a data: [DONE] sentinel, which is exactly the incremental token delivery the summarization UI needs.
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Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official NVIDIA exam blueprint
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