Two structural fixes for the SLM classifier's 100% failure rate:
(1) Pass ResponseFormat=json_object + Temperature=0 + TopP=1 +
MaxTokens=128 in the classifier Request. The provider type already
supports these but callSLM was leaving them unset, which meant ollama
(and any other backend) ran with default sampling and free-form text
output. format=json mode in particular makes ollama emit only valid
JSON at decoding time — eliminates the majority of parse failures.
(2) Harden extractJSON to strip common thinking-block tags before
hunting for the brace. Seen in the wild: <think>…</think> (Qwen3
distillations) and <Thought Process>…</Thought Process> (tiny3.5).
Defensive list also covers <reasoning>, <thoughts>. Unterminated
thinking blocks fall back to brace-search so we still have a shot.
Table-driven tests cover all variants plus the no-tag and
fenced-json paths to confirm no regression.
Even with format=json on a capable provider, the extractor is the
safety net for backends that don't enforce format strictly — same
defence-in-depth shape as the existing fence stripping.
Doesn't fix the deeper architecture question (encoder + bandit
preferred over decoder-SLM as classifier — see plan doc landing in
the same PR); fixes the immediate bug.
vikingowl
c0c2e4bff5