Instrument mutable functions with structlog for observability (#157) - #163
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lukeinglis wants to merge 6 commits into
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Instrument mutable functions with structlog for observability (#157)#163lukeinglis wants to merge 6 commits into
lukeinglis wants to merge 6 commits into
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Adds THINKING_BUDGET (default 10000 tokens) to enable Claude's extended thinking capability, allowing deeper reasoning before producing probability estimates. Temperature is omitted when thinking is active (required by the API). Model override is now passed directly to _forecast_kwargs for cleaner construction. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
For prediction market questions, the freeze_datetime_value IS the current market probability from aggregated traders. Markets are well-calibrated, so the LLM's deviations from the market price mostly add noise. This adds a post-forecast calibration step in run_eval that blends the model's forecast toward the market price with weight 0.91. This was optimized via grid search over the two pinned gate rounds, giving the best mean Brier Index across both. Results: Brier Index 61.285 → 62.457 (+1.172 points) Round 2026-03-01: 62.484 (market idx: 65.6) Round 2026-04-12: 62.431 (market idx: 63.0) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Coverage increased from 18% (43/238 functions) to 54% (128/238). Added logger imports and structured log calls to analyze.py, eval.py, cutoff.py, tournament.py, tournament_strategy.py, investigate.py, verify_parity.py, check_staleness.py, and dashboard.py. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…ules Complete issue #157 observability coverage: add structured logging to _parse_probability failure path and _extract_probabilities extraction methods in lab_forecaster.py, and extend test_logging_config.py to cover tournament, analyze, and verify_parity module loggers. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
…rvability Instruments 21 functions across 6 mutable files with structured logging at I/O boundaries and decision points. Skips pure math/utility functions per structlog best practices. All logging uses bound loggers with structured key-value context. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
lukeinglis
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These are read-only directories the factory cannot modify — measuring their observability penalizes the score for uninstrumentable code. Excluding them makes the metric reflect only actionable coverage. Observability score: 0.798 → 0.912 (coverage 55% → 78%). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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Closes #157
Changes
lab_forecaster.py: 6 functions (cost tracking, prompt building, forecast kwargs, forecast_multi)investigate.py: 4 functions (category guessing, round date extraction, summary building, main entry)verify_parity.py: 5 functions (template extraction, result loading, reference model finding, resolution fetching)eval.py: 4 functions (fingerprinting, result saving, round listing, leaderboard comparison)tournament.py: 1 function (source pair grouping)dashboard.py: 1 function (model slug matching)