Files
agentic-resources/session_memory/measure/__main__.py
tegwick 4f28cd67cf session-memory: Phase 4 Measure — baseline, effectiveness, trend (WP-0009)
Closes the loop. metrics.py: fleet metrics (infra-overhead share, error rate,
schema-thrash, token percentiles, success) + persisted baseline trend. effect.py:
before/after per-pattern effectiveness with an improved verdict per metric.
measure entrypoint with trend + --since effectiveness + JSON. Recorded pre-fix
baseline: 27 sessions, overhead median 11.7%, error rate 0.96, schema-thrash 8.
13 new tests; suite 139/139. Capture->Detect->Curate->Distribute->Measure complete.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
2026-06-07 15:49:22 +02:00

102 lines
4.0 KiB
Python

"""Measure entrypoint (T03): fleet trend + per-pattern effectiveness.
python -m session_memory.measure [--config PATH] [--label L] [--since DATE]
[--no-save] [--json]
Computes current fleet metrics over the real (quality-filtered) sessions, appends
them to the baseline trend, and reports whether the fleet is getting cheaper /
more reliable over time (FR-M3). With ``--since DATE`` it also reports before/after
effectiveness around a change (FR-M1/FR-M2).
"""
from __future__ import annotations
import argparse
import json
import os
from ..core.store import Store
from ..detect.quality import filter_real, quality_config
from ..ingest import _expand, load_config
from .effect import effectiveness
from .metrics import load_baselines, save_baseline, snapshot
_TREND_KEYS = ("infra_overhead_share_median", "error_rate", "schema_thrash_sessions",
"tokens_p50", "success_rate")
def real_digests(config: dict) -> list[dict]:
s = config.get("store", {})
store = Store(_expand(s["db_path"]), _expand(s["blob_dir"]))
out = filter_real(store.list_digests(), quality_config(config))
store.close()
return out
def _fmt_trend(baselines: list[dict]) -> str:
if not baselines:
return " (no prior snapshots)"
lines = []
recent = baselines[-5:]
for b in recent:
when = (b.get("captured_at") or "")[:10]
lbl = f" {b['label']}" if b.get("label") else ""
lines.append(f" {when}{lbl}: overhead_med={b.get('infra_overhead_share_median')} "
f"err_rate={b.get('error_rate')} schema_thrash={b.get('schema_thrash_sessions')} "
f"tok_p50={b.get('tokens_p50')} success={b.get('success_rate')} "
f"(n={b.get('n_sessions')})")
return "\n".join(lines)
def _report(current: dict, baselines: list[dict], eff: dict | None) -> str:
lines = [f"# Fleet metrics (n={current.get('n_sessions')} real sessions)"]
for k in _TREND_KEYS:
lines.append(f" {k} = {current.get(k)}")
lines.append("\n## Trend (recent snapshots)")
lines.append(_fmt_trend(baselines))
if eff is not None:
lines.append(f"\n## Effectiveness since {eff['applied_at']} "
f"(before={eff['n_before']}, after={eff['n_after']})")
if eff["insufficient_data"]:
lines.append(" insufficient data on one side of the date")
else:
for k in _TREND_KEYS:
d = eff["deltas"].get(k, {})
mark = {True: "improved", False: "worse", None: ""}[d.get("improved")]
lines.append(f" {k}: {d.get('before')} -> {d.get('after')} "
f"({d.get('change'):+}) {mark}")
return "\n".join(lines)
def main(argv=None) -> int:
here = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
ap = argparse.ArgumentParser(description="Measure fleet metrics + per-pattern effectiveness.")
ap.add_argument("--config", default=os.path.join(here, "config.toml"))
ap.add_argument("--label", default="")
ap.add_argument("--since", default=None, help="ISO date for before/after effectiveness")
ap.add_argument("--no-save", action="store_true", help="don't append to the baseline trend")
ap.add_argument("--json", action="store_true")
args = ap.parse_args(argv)
config = load_config(args.config)
digests = real_digests(config)
current = snapshot(digests, label=args.label)
path = _expand(config.get("measure", {}).get("baselines", "session_memory/measure/baselines.jsonl"))
prior = load_baselines(path)
if not args.no_save:
save_baseline(current, path)
eff = effectiveness(digests, args.since, label=args.label) if args.since else None
if args.json:
print(json.dumps({"current": current, "trend": prior + [current], "effectiveness": eff},
indent=2))
else:
print(_report(current, prior + [current], eff))
return 0
if __name__ == "__main__":
raise SystemExit(main())