claude
2684095e2f
Co-authored-by: claude <claude@jpaul.io> Co-committed-by: claude <claude@jpaul.io>
99 lines
3.7 KiB
Python
99 lines
3.7 KiB
Python
"""Assistive AI reviewer — local simulation of a PR-reviewer bot.
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This stands in for a forge-native reviewer (an app/bot triggered when a PR opens, running on a
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runner from Module 19) without needing any hosted account. It does the two deterministic halves of
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the job and leaves the one judgment call — what actually happens to the PR — to you.
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python reviewer.py prompt # assemble the prompt: rubric + diff. Paste to your AI.
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python reviewer.py apply ai-review.sample.json # ingest the AI's JSON, render it, gate it
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The point of this module: the agent produces comments and a recommendation. It never approves,
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never requests-changes-as-a-gate, never merges. The `apply` step ends at a HUMAN DECISION, every
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time. Stdlib only — no pip install.
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"""
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import argparse
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import json
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import sys
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from pathlib import Path
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HERE = Path(__file__).parent
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PROMPT_HEADER = """\
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You are an assistive code reviewer. Follow the rubric below exactly, then review the diff that
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follows it. Return ONLY the JSON object the rubric specifies — no prose before or after.
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================ REVIEW RUBRIC ================
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{rubric}
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================ DIFF UNDER REVIEW ============
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{diff}
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"""
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def cmd_prompt(args: argparse.Namespace) -> int:
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rubric = Path(args.rubric).read_text()
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diff = Path(args.patch).read_text()
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print(PROMPT_HEADER.format(rubric=rubric, diff=diff))
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return 0
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def cmd_apply(args: argparse.Namespace) -> int:
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try:
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review = json.loads(Path(args.response).read_text())
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except (json.JSONDecodeError, FileNotFoundError) as exc:
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print(f"error: could not read a JSON review from {args.response}: {exc}")
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return 1
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summary = review.get("summary", "(no summary)")
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recommendation = review.get("recommendation", "comment")
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comments = review.get("comments", [])
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print("=" * 70)
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print("AI REVIEWER — first pass (advisory only)")
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print("=" * 70)
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print(f"\nSummary: {summary}\n")
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if not comments:
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print("No line comments.\n")
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order = {"blocker": 0, "suggestion": 1, "nit": 2}
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for c in sorted(comments, key=lambda c: order.get(c.get("severity", "nit"), 9)):
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sev = c.get("severity", "nit").upper()
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loc = f"{c.get('file', '?')}:{c.get('line', '?')}"
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print(f" [{sev:10}] {loc}")
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print(f" {c.get('comment', '')}\n")
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print("-" * 70)
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print(f"Agent's recommendation: {recommendation}")
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print("-" * 70)
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print(
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"\nThis is the human decision gate. The agent did NOT merge, approve, or block.\n"
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"It only commented. You decide what happens next:\n"
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" - merge you read the comments, you disagree or they're addressed\n"
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" - request changes you agree; push the fix on the branch and re-run\n"
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" - dismiss the agent is wrong or noisy; ignore and move on\n"
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"\nNothing in this repo changes until you act. That's the whole point of Module 24.\n"
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)
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return 0
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def main(argv: list[str]) -> int:
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parser = argparse.ArgumentParser(description=__doc__)
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sub = parser.add_subparsers(dest="cmd", required=True)
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p = sub.add_parser("prompt", help="assemble the review prompt to paste to your AI")
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p.add_argument("--rubric", default=str(HERE / "review-rubric.md"))
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p.add_argument("--patch", default=str(HERE / "feature.patch"))
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p.set_defaults(func=cmd_prompt)
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a = sub.add_parser("apply", help="ingest the AI's JSON review and render the decision gate")
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a.add_argument("response", help="path to the JSON the AI returned")
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a.set_defaults(func=cmd_apply)
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args = parser.parse_args(argv)
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return args.func(args)
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if __name__ == "__main__":
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raise SystemExit(main(sys.argv[1:]))
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