Files
chatgpt-on-wechat/agent/evolution/__init__.py
zhayujie ba777ed706 feat(evolution): add self-evolution subsystem
Add a self-evolution subsystem that reviews idle conversations in an
isolated agent and durably learns from them — patching/creating skills,
finishing unfinished tasks, and backfilling missed memory.

- Trigger: background idle scan, fires when a session is idle >= N min AND
  (>= N turns OR context usage > 80%). In-memory cursor reviews only new
  messages so a session never re-learns old content.
- Isolated review agent: same model, restricted toolset, hard write-guard
  confining edits to the workspace (built-in skills are protected).
- Safety: file-level backup before edits + evolution_undo tool; notify the
  user ONLY when a workspace file actually changed (no-nag rule); capped
  concurrency.
- Records to memory/evolution/<date>.md, surfaced in the memory UI's
  renamed "Self-Evolution" tab (merged with dream diaries).
- Hide internal [SCHEDULED]/[EVOLUTION]/backup_id markers from chat history
  display (also fixes scheduler marker leakage) while keeping them in stored
  content for undo.
- Flat config: self_evolution_enabled (default off until release),
  self_evolution_idle_minutes (15), self_evolution_min_turns (6).
- Tests: tests/test_evolution.py (stub + real model modes, 7 scenarios).
2026-06-07 18:55:33 +08:00

20 lines
614 B
Python

"""
Self-evolution subsystem for CowAgent.
Runs a lightweight, isolated review pass after a conversation goes idle to
decide whether anything is worth durably learning (memory / skill) or whether
an unfinished task can be pushed forward. Conservative by design: most
conversations should produce no change at all.
Public entry points:
from agent.evolution import get_evolution_config
from agent.evolution.trigger import start_evolution_trigger, note_user_turn
"""
from agent.evolution.config import EvolutionConfig, get_evolution_config
__all__ = [
"EvolutionConfig",
"get_evolution_config",
]