claude
389ac2e460
Apply the no-ai-slop standard (now binding in AGENTS.md): the em-dash character is banned outright (restructured, not blind-replaced), plus the banned word/phrase list (delve, leverage, robust, seamless, truly, unlock, etc.). 0 em-dashes remain in modules + capstone; the only "robust" left is the planted M10 ai-change.patch trap. Module H1 titles use a colon separator. All deliberate teaching devices preserved; labs compile/parse (py/sh/yaml/json); no junk. AGENTS.md updated with the hard no-slop rules. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01TfzV5QvtPDz8LJS3Pu5VLT
79 lines
2.8 KiB
Python
79 lines
2.8 KiB
Python
"""Run the eval set against one candidate and print a scorecard.
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Usage:
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python run_eval.py candidates/current_model
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python run_eval.py candidates/swapped_model
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python run_eval.py candidates/current_model --threshold 0.9
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A "candidate" is a directory containing a tasks.py that an agent produced. The
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runner imports that tasks.py, runs every case in eval_set.py against it, prints
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a pass/fail line per case, and reports an aggregate score.
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The exit code is the guardrail: 0 if the score meets the threshold, 1 if it
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doesn't. That single integer is what lets an eval gate a model swap, a prompt
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change, or an unattended agent in CI (Module 14) instead of a human eyeballing
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output. "Below threshold" should block exactly like a failing test does.
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"""
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import argparse
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import importlib.util
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import sys
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from pathlib import Path
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from eval_set import CASES
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def load_candidate(candidate_dir: Path):
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"""Import the tasks.py living in candidate_dir as an isolated module."""
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tasks_py = candidate_dir / "tasks.py"
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if not tasks_py.exists():
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sys.exit(f"no tasks.py in {candidate_dir}")
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spec = importlib.util.spec_from_file_location("candidate_tasks", tasks_py)
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module = importlib.util.module_from_spec(spec)
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spec.loader.exec_module(module)
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return module
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def run_case(candidate, items, expected):
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"""Build the input state with the candidate's own classes, then grade."""
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tlist = candidate.TaskList()
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for title, done in items:
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tlist.tasks.append(candidate.Task(title=title, done=done))
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try:
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actual = tlist.pending_count()
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except Exception as exc: # a crash is a failed case, not a crashed harness
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return False, f"raised {type(exc).__name__}: {exc}"
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return actual == expected, f"expected {expected}, got {actual}"
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def main(argv):
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parser = argparse.ArgumentParser()
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parser.add_argument("candidate", help="path to a candidate dir with tasks.py")
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parser.add_argument("--threshold", type=float, default=1.0,
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help="minimum passing fraction to exit 0 (default 1.0)")
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args = parser.parse_args(argv)
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candidate_dir = Path(args.candidate)
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candidate = load_candidate(candidate_dir)
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passed = 0
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print(f"\neval set: {len(CASES)} cases candidate: {candidate_dir}\n")
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for name, items, expected in CASES:
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ok, detail = run_case(candidate, items, expected)
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mark = "PASS" if ok else "FAIL"
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print(f" [{mark}] {name:<40} ({detail})")
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passed += ok
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score = passed / len(CASES)
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print(f"\nscore: {passed}/{len(CASES)} = {score:.0%} threshold: {args.threshold:.0%}")
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if score < args.threshold:
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print("RESULT: below threshold; this change is NOT safe to ship.\n")
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return 1
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print("RESULT: at or above threshold; safe by this eval.\n")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main(sys.argv[1:]))
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