Praise: tasteful streaming-thinking-token handling in `_process_thinking_tokens`

backend/utils/llm_utils.py:15-55 is the kind of code I usually expect to be a mess, and isn't. The function correctly handles three independently tricky cases:

1. A single streaming token containing both <think> and </think> (the partition order on lines 26 and 40 is deliberate and necessary).
2. A provider that emits a closing </think> without an opening one (line 28-31 — clear token_join and emit "" to the callback so the UI can drop already-streamed reasoning).
3. Content split across multiple tokens where the tag boundary falls mid-stream.

Two things I appreciated:

• The function's return value is_thinking plus the explicit token_join: List[str] argument keeps state out of the function — the caller in call_llm_for_system_prompt (line 116) owns both. That makes it trivially unit-testable without mocking anything.
• The "treat everything accumulated so far as reasoning and clear it" branch comes with a callback nudge to the UI (callback("")). That's exactly the kind of correctness-for-the-user behaviour that tends to get dropped in the rush to ship streaming.

The accompanying check on line 124 (if not result and content_tokens_seen > 0: logger.warning(...)) is a nice operational touch — it gives you a single log line that explains "the user got an empty response because everything matched <think>…</think>", which is exactly the kind of diagnostic you want when investigating "the model returned nothing" tickets.

Filing because clean streaming-tag handling is rare and this one is worth pointing at as a reference for similar code elsewhere in the codebase.

Read backend/utils/llm_utils.py:15-55 and the call site in call_llm_for_system_prompt around line 116 to understand the existing streaming-token behavior. The issue requests no code or documentation change, so there is no defined completion condition beyond preserving this implementation as a reference.