Verify each finding against the current code and only fix it if needed.

Inline comments:
In `@tensorrt_llm/serve/openai_protocol.py`:
- Around line 510-511: Change the ChatCompletionLogProbsContent.top_logprobs
field to use a non-nullable list with a default factory so it always serializes
as [] instead of null; specifically, replace the
Optional[List[ChatCompletionLogProb]] = None declaration in class
ChatCompletionLogProbsContent with a List[ChatCompletionLogProb] defaulting to
Field(default_factory=list) (matching the pattern used by CompletionLogProbs) so
model_dump without exclude_none produces an empty list.

In `@tests/integration/defs/disaggregated/test_disaggregated.py`:
- Around line 2241-2255: The test can silently pass when there are no comparable
logprob entries; after obtaining ns_logprobs and st_logprobs (and before the
for-loop that skips i==0 and None entries) add an explicit check that there is
at least one comparable entry: compute comparable_count = sum(1 for i,(n,s) in
enumerate(zip(ns_logprobs,st_logprobs)) if i != 0 and n is not None and s is not
None) and assert comparable_count > 0 with a clear message including api_type,
ns_logprobs and st_logprobs; keep the existing np.isclose comparisons unchanged
but rely on this new assertion to fail when both paths return no comparable
logprobs.
- Around line 2181-2189: This test uses the "llama31_8b_ucx" config but doesn't
set the UCX env vars; before calling setup_disagg_cluster, update the
environment passed (llm_venv._new_env) to include TRTLLM_USE_UCX_KVCACHE="1" and
an appropriate UCX_TLS (e.g., "tcp,self,sm") so the UCX code path is exercised;
either mutate a copy of llm_venv._new_env or create a new env dict and pass that
into setup_disagg_cluster (refer to config_file, llama31_8b_ucx, and the
setup_disagg_cluster call to locate where to change).

---

Nitpick comments:
In `@tests/integration/defs/disaggregated/test_disaggregated.py`:
- Around line 2257-2293: Enforce that the returned top_logprobs match the
requested bound and include the sampled token: after building top_lp_payload
(which sets "top_logprobs": 3) and retrieving lp_obj/content/top_lps, assert
len(top_lps) >= top_lp_payload["top_logprobs"] (or hardcode 3) and also assert
the sampled token from the content item (e.g., item.get("token") or
item.get("text") — whichever field holds the generated token in this response
shape) appears among the top_lps tokens using a membership check like
any(tl["token"] == sampled_token for tl in top_lps); use the existing variables
top_lp_payload, lp_obj, content, item, top_lps and tl to locate and implement
the checks.