Files
SkillOpt/skillopt/sleep/state.py
T
Yifan Yang 4e7add899d feat(sleep): nightly offline self-evolution engine + Claude Code plugin
Add skillopt/sleep — a deployment-time companion to SkillOpt that gives a
local Claude agent a nightly "sleep cycle":

  harvest ~/.claude transcripts -> mine recurring tasks -> replay offline
    -> consolidate (reflect -> bounded edit -> held-out GATE) -> stage -> adopt

Synthesizes SkillOpt (validation-gated bounded text optimization, reusing
skillopt.evaluation.gate verbatim), Claude Dreams (offline consolidation;
input never mutated; review-then-adopt), and the agent-sleep paper
(short-term experience -> long-term competence).

Engine (skillopt/sleep/, import-light, py>=3.10):
  - harvest.py   read-only parse of session JSONL + history.jsonl
  - mine.py      sessions -> TaskRecords (heuristic miner + LLM hook)
  - backend.py   MockBackend (deterministic, no API) + AnthropicBackend
  - replay.py    offline re-run -> (hard, soft) scores
  - consolidate.py  one SkillOpt epoch behind a held-out gate
  - memory.py    protected-region edits to SKILL.md / CLAUDE.md
  - staging.py   stage proposals; adopt with backup (Dreams safety contract)
  - cycle.py + __main__.py  orchestrator + CLI (run/dry-run/status/adopt/harvest)

Plugin (skillopt-sleep-plugin/): plugin.json, /sleep command, skillopt-sleep
skill, SessionEnd hook, bundled runner + cron generator.

Validation (deterministic, no API): persona experiment proves held-out lift
(researcher 0.33->1.0, programmer 0.32->1.0) AND that the gate rejects an
injected harmful edit. 13 stdlib-unittest tests pass, incl. full cycle +
adopt-with-backup and parsing of real on-disk transcripts.

Co-Authored-By: Claude Opus 4 <noreply@anthropic.com>
2026-06-08 14:31:51 +00:00

84 lines
2.9 KiB
Python

"""SkillOpt-Sleep — persistent cross-night state.
state.json lives in ~/.skillopt-sleep and is the "long-term" store that
turns nightly episodes into durable competence (the Agent-Sleep paper's
short-term -> long-term transfer). It records:
- night counter
- last harvest timestamp per project (so each night only sees new data)
- cross-night "slow/meta" memory (lessons that persisted across nights)
- per-night history (scores, accept/reject) for trend reporting
"""
from __future__ import annotations
import json
import os
from typing import Any, Dict, List, Optional
def _now_iso(clock: Optional[float] = None) -> str:
# caller passes a timestamp; we avoid importing time at module import
import time as _t
return _t.strftime("%Y-%m-%dT%H:%M:%S", _t.localtime(clock if clock is not None else _t.time()))
DEFAULT_STATE: Dict[str, Any] = {
"version": 1,
"night": 0,
"last_harvest": {}, # project -> iso timestamp of last harvested record
"slow_memory": "", # cross-night consolidated lessons (meta-skill analogue)
"history": [], # list of per-night summaries
}
class SleepState:
def __init__(self, path: str, data: Optional[Dict[str, Any]] = None) -> None:
self.path = path
self.data = data if data is not None else dict(DEFAULT_STATE)
# io ---------------------------------------------------------------------
@classmethod
def load(cls, path: str) -> "SleepState":
if os.path.exists(path):
try:
with open(path) as f:
data = json.load(f)
merged = dict(DEFAULT_STATE)
merged.update(data if isinstance(data, dict) else {})
return cls(path, merged)
except Exception:
pass
return cls(path, dict(DEFAULT_STATE))
def save(self) -> None:
os.makedirs(os.path.dirname(self.path), exist_ok=True)
tmp = self.path + ".tmp"
with open(tmp, "w") as f:
json.dump(self.data, f, ensure_ascii=False, indent=2)
os.replace(tmp, self.path)
# accessors --------------------------------------------------------------
@property
def night(self) -> int:
return int(self.data.get("night", 0))
def last_harvest_for(self, project: str) -> Optional[str]:
return self.data.get("last_harvest", {}).get(project)
def set_last_harvest(self, project: str, iso_ts: str) -> None:
self.data.setdefault("last_harvest", {})[project] = iso_ts
@property
def slow_memory(self) -> str:
return str(self.data.get("slow_memory", ""))
def set_slow_memory(self, content: str) -> None:
self.data["slow_memory"] = content
def begin_night(self, clock: Optional[float] = None) -> int:
self.data["night"] = self.night + 1
return self.night
def record_night(self, summary: Dict[str, Any]) -> None:
self.data.setdefault("history", []).append(summary)