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Marius CiepluchandClaude Fable 5.1
d9d6335ab3
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]>
2 lines
81 B
Python
2 lines
81 B
Python
"""Repository annotations and offline contracts for hunter learning research."""
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