DSPy 3.4.1 raises AdapterParseError for an unparseable ReAct step, which is not the ValueError its loop
catches, so one malformed step discarded the whole hunt (7 of 60 hunts in the repeats). The step now ends
the loop like an invalid tool choice. Records carry loop_parse_failed beside parse_failed.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
The answer check counted only the rendered function text as shown, so 7 of
8 baseline suspicions citing lines the model had read with read_file were
marked unknown (baseline 1/12 against the pilot hunter's 6/12). Tools now
record the lines they return. A DSPy parse failure scores as zero findings
with a flag instead of a broken run. The per-run response cache now takes
effect through dspy.configure_cache.
Co-Authored-By: Claude Opus 5.5 <[email protected]>
hunter-learning-loop groups 1-3 (first increment). The feature table is the
contract: one row per touched function with diff, source, semantic and
taxonomy columns, provenance per producer, labels by the benchmark's rule.
Producers read the repository at head only (a planted advisory id and
commit text never reach a feature). The hunt program is a DSPy ReAct loop
over a signature whose inputs are the unmasked columns in a fixed order;
answers outside the closed family list or citing unseen lines score as
unknown. The runner writes records the benchmark scorer reads, resumable
by change, program id and mask, and refuses the held-out pilot unless the
run is a report run. Research extra [hunt] = dspy, pandas; the core
install is unchanged. 43 tests on a scripted model, no network.
Co-Authored-By: Claude Fable 5.1 <[email protected]>
