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Commit History
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fix: clamp all scores strictly to (0, 1) — no 0.0 or 1.0
- graders: episode_score returns 0.01 for empty, clamps to [0.01, 0.99] - env/base: terminal_step and invalid action use 0.01 not 0.0/-0.1 - validate: updated local check to match strict (0,1) requirementfdc7ded
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fix: clamp all task scores to strict (0,1) range — never exactly 0.0 or 1.0
- All graders now clamp reward values to [0.01, 0.99] - inference.py score computation clamps to [0.01, 0.99] - Fixes validator rejection: 'task scores must be strictly between 0 and 1'226ad10
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Fix 4 critical grader bugs
Problem 1 — Medium grader penalties too aggressive: - Critical position: -0.30 → -0.15 - Security position: -0.20 → -0.10 - tau=0.0 (mediocre) now scores ~0.25 instead of 0.0 - Heuristic medium: 0.41 → 0.47 Problem 2 — Hard grader comment spam exploit: - Agent was looping add_comment×3 → request_changes for guaranteed points - Added consecutive_comments tracking with decaying ack reward - Reward: 0.05 → 0.03 → 0.01 for consecutive comments without decision - Counter resets on approve/request_changes Problem 3 — Frozen observation state (comments=3 on every step): - After add_comment, observation now rebuilds from task state - comment_count properly increments in returned state - info dict now includes comments_so_far and consecutive_comments Problem 4 — Difficulty now monotonic: Easy (0.80) > Medium (0.47) > Hard (0.37) ✅e130396 -
Improve grader quality + research framing
- Hard grader tightened: LINE_TOLERANCE 5→3, specificity requires 2+ keywords, coverage counts per-bug-line instead of binary, depth penalty for shallow reviews - Hard heuristic baseline dropped from 0.69 → 0.37 (proper difficulty progression) - Implemented coverage_bonus (+0.15 at episode end for thorough reviews) - Added research framing to README intro (first RL benchmark for knowledge work) - Updated baseline scores to match tightened grader470008d -
CodeReviewEnv v1.0 — OpenEnv-compliant submission
- 3 tasks (easy/medium/hard) with deterministic graders - Spec-compliant inference.py with [START]/[STEP]/[END] per-task logs - Root-level baseline.py (heuristic, no API key needed) - Fixed reward double-counting bug in _apply_reward_shaping - 17/17 validation checks, 21/21 tests passing - Docker-ready on port 7860 for HF Spacesdbf5e96