- tools/kblib.py: ladybug schema, embeddings, FTS+vector, hybrid RRF
- bin/kb/{index,search,get,stats,eval}: corpus indexing + deduction search
- bin/facts/{extract,audit}: 2-source evidence acquisition + gates
- serve/: async Go HTTP server (goroutines, bounded worker pool), TDD
- docker/ flattened to root: compose.yaml + Dockerfile (multi-stage Go)
- docker scripts -> bin/ shebang pattern (kb-watch, docker-entrypoint)
- bin/ci/semver + tools/semver.py: conventional-commit semver release
- ci.yml: go tests + shell checks; drop release-please (PR toggle blocked)
62 lines
1.8 KiB
Python
Executable File
62 lines
1.8 KiB
Python
Executable File
#!/usr/bin/env python3
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"""kb/eval - recall@5 gate for the brain.
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bin/kb/eval [--json]
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Control questions are answered from the graph; recall@5 >= 0.95 gates CI.
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Each question maps to leaf ids that MUST appear in the top 5 hits.
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"""
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from __future__ import annotations
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import json
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import sys
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[2]
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sys.path.insert(0, str(ROOT / "tools"))
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from kblib import open_readonly, query_fts # noqa: E402
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from yamlout import to_yaml # noqa: E402
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RECALL_THRESHOLD = 0.95
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# (query, expected leaf id)
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CONTROL_QUESTIONS: list[tuple[str, str]] = [
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("which database does the brain use", "facts:ladybug"),
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("hybrid search weights fts and vector equally", "info:hybrid"),
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]
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def hit_ids_of(query: str, conn, limit: int = 5) -> list[str]:
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try:
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hits = query_fts(conn, query, limit)
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return [h["id"] for h in hits]
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except Exception:
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return []
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def main(argv: list[str]) -> int:
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import argparse
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p = argparse.ArgumentParser(description="recall@5 gate")
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p.add_argument("--json", action="store_true")
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a = p.parse_args(argv)
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db, conn = open_readonly()
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recalled = 0
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detail = []
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for query, expected in CONTROL_QUESTIONS:
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hits = hit_ids_of(query, conn)
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ok = any(expected in h or h in expected for h in hits)
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recalled += int(ok)
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detail.append({"q": query, "expected": expected, "in_top5": ok, "hits": hits[:5]})
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recall = recalled / len(CONTROL_QUESTIONS) if CONTROL_QUESTIONS else 1.0
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passed = recall >= RECALL_THRESHOLD
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out = {"recall@5": round(recall, 3), "passed": passed, "gate": len(CONTROL_QUESTIONS), "details": detail}
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print(json.dumps(out, indent=2) if a.json else to_yaml(out))
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conn.close()
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db.close()
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return 0 if passed else 2
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if __name__ == "__main__":
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sys.exit(main(sys.argv[1:])) |