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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 critical crash bug + audit fixes
1. CRASH FIX: grader_hard.py line 213 — critical_caught was undefined (NameError). Now computed from _bugs_caught() before use. This would crash if any LLM approved a critical-severity PR. 2. README: Fixed stale references: - Language enum: 4 → 7 (rust, typescript, ruby added) - Test count: 19 → 21 - HF URL: openenv → ragavrida - Validation count: 15 → 17 3. inference.py: Added 3-attempt retry with exponential backoff for LLM API calls to handle transient failures. 4. env/models.py: Updated language comment to match validator. All verified: 21/21 tests, 17/17 validation, baseline runs.1a6681a -
Fix all 4 remaining issues for hackathon
1. comments=3 frozen: Server now rebuilds obs after add_comment (task_hard track comments, server updates state on each comment) 2. Heuristic > LLM: Fixed eval_live.py hard scoring to use decision-only rewards (not intermediate ack rewards) 3. 20 → 50 PR templates: Added 30 new PRs across 7 languages (python, java, go, js, typescript, rust, ruby), all 8 bug categories. Expanded PRFile language validator. 4. World model trained: Added train_world_model.py with - Pure Python MLP (no PyTorch/TF dependency) - 340 transitions, 100 epochs - Copy baseline 0.025, model 0.047 - Documents the research challenge for KW-WM7e55f05 -
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