Wrap selector and env.step in run_episode with heuristic fallback and concise step-error logging. Out-of-data customer/service/runbook ids now retry safely instead of crashing the run.
Made-with: Cursor
Harden checkpoint sanitizer against all sandbox/sim edge cases.
Validate per-action literals, anchor service_name and runbook_id to env-provided values, default missing required strings, and wrap selector and sanitizer in try/except so evaluation never crashes on malformed checkpoint output.
Made-with: Cursor
Finalize checkpoint-first evaluation and sandbox submission workflow.
Default compare runs now use trained checkpoints with explicit heuristic fallback, add no-Docker sandbox launch for HF Spaces, and align notebook/docs/runbook around mentor-ready stage curves and submission checks.
Made-with: Cursor
Improve checkpoint policy quality and environment robustness.
Run trained checkpoint evaluation in a clean subprocess to avoid Unsloth patch conflicts, and sanitize checkpoint actions so invalid outputs fall back to trained_heuristic only when required.
Made-with: Cursor
audit pass: hackathon-ready polish and truthful reporting
Surface policy_used and episodes_per_difficulty in EvaluationReport so artifacts unambiguously distinguish checkpoint vs heuristic-fallback runs. Replace hardcoded behavior_examples in train.py with real behavior_diffs derived from actual baseline/trained metrics. Rewrite README around the theme 3.1 judging criteria with a TL;DR, criterion mapping, and realistic time estimates. Split training notebook into quick (5a) and full (5b) modes, use unbuffered logs, and inspect policy_used in the results cell. Harden .gitignore against ephemeral venv dirs.
Made-with: Cursor
Polish judge-facing docs and add checkpoint evaluation.
Add honest results/reproduce sections and judge quick-start in README, ship checkpoint-based evaluation policy and compare flag in evaluate.py, wire trained adapter eval into train.py with graceful fallback, refresh blog/video/pitch narratives, and update notebook with clean install plus checkpoint compare and two-seed reproducibility cells.
Made-with: Cursor
Harden training signal and clean generated artifacts.
Improve GRPO robustness with tolerant JSON parsing, action-keyed reward shaping, parse-rate diagnostics, and shorter completion defaults; add raw reward reporting/plotting in evaluation for transparent baseline behavior; and remove redundant generated result snapshots.
Made-with: Cursor
Harden hackathon readiness and surface reproducible evidence.
Align manifest and API docs with full environment lifecycle, improve training reproducibility and reward shaping, clarify heuristic-vs-trained evaluation semantics, and add tracked evaluation artifacts/checklist items for safer judging and reruns.
Made-with: Cursor
updated EICC v2 environment, APIs, and training pipeline
Adds the enterprise incident command center world model, expanded action/observation space, deterministic incident grading, production-hardening API updates, and complete training/evaluation artifacts for submission readiness.
Made-with: Cursor
