Files
chatgpt-on-wechat/agent/evolution/trigger.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

134 lines
5.0 KiB
Python

"""Idle-based evolution trigger.
A single background thread periodically scans live agent sessions and runs an
evolution pass for any session that is idle for >= idle_minutes AND has enough
accumulated signal, where "enough signal" is EITHER:
- >= min_turns user turns since the last evolution, OR
- the live context has grown past _CONTEXT_RATIO of the agent's token budget
(mirrors how OpenClacky / Claude Code consolidate under context pressure).
Turn counting is per user turn (not per message), measured from the last
evolution (or session start). After a pass runs, the baseline resets so a long
session can evolve multiple times without re-judging old content.
Per-session evolution state is stored on the agent instance via lightweight
attributes set by AgentBridge.agent_reply (see _note_user_turn).
"""
from __future__ import annotations
import threading
import time
from common.log import logger
from agent.evolution.config import get_evolution_config
from agent.evolution.executor import run_evolution_for_session
_SCAN_INTERVAL_SECONDS = 60
# Context-pressure trigger: evolve once the live context exceeds this fraction
# of the agent's token budget, even if min_turns hasn't been reached. Kept as a
# module constant (not user config) for now. Fallback budget matches
# agent_initializer / config.py (agent_max_context_tokens default = 50000).
_CONTEXT_RATIO = 0.8
_FALLBACK_CONTEXT_BUDGET = 50000
def _context_pressure_reached(agent) -> bool:
"""True if the agent's live context exceeds _CONTEXT_RATIO of its budget.
Uses the agent's own (estimated) token accounting so behavior matches the
existing context-trimming path. Best-effort: any error -> False.
"""
try:
with agent.messages_lock:
messages = list(agent.messages)
if not messages:
return False
est = sum(agent._estimate_message_tokens(m) for m in messages)
budget = getattr(agent, "max_context_tokens", None) or _FALLBACK_CONTEXT_BUDGET
return est / budget > _CONTEXT_RATIO
except Exception:
return False
def note_user_turn(agent, channel_type: str = "", receiver: str = "") -> None:
"""Record activity for a session's agent. Called once per real user turn.
Maintains, on the agent instance:
_evo_last_active : epoch seconds of the last user turn
_evo_turns : user turns since the last evolution
_evo_channel_type : originating channel (for later notify)
_evo_receiver : push target for notify
"""
try:
agent._evo_last_active = time.time()
agent._evo_turns = int(getattr(agent, "_evo_turns", 0)) + 1
if channel_type:
agent._evo_channel_type = channel_type
if receiver:
agent._evo_receiver = receiver
except Exception:
pass
def start_evolution_trigger(agent_bridge) -> None:
"""Start the idle-scan thread once per process (idempotent)."""
if getattr(agent_bridge, "_evolution_trigger_started", False):
return
agent_bridge._evolution_trigger_started = True
t = threading.Thread(
target=_scan_loop, args=(agent_bridge,), daemon=True, name="evolution-trigger"
)
t.start()
logger.info("[Evolution] Idle trigger started")
def _scan_loop(agent_bridge) -> None:
while True:
try:
time.sleep(_SCAN_INTERVAL_SECONDS)
cfg = get_evolution_config()
if not cfg.enabled:
continue
_scan_once(agent_bridge, cfg)
except Exception as e:
logger.warning(f"[Evolution] Scan loop error: {e}")
time.sleep(_SCAN_INTERVAL_SECONDS)
def _scan_once(agent_bridge, cfg) -> None:
now = time.time()
# Snapshot to avoid holding the dict while running long evolutions.
sessions = list(getattr(agent_bridge, "agents", {}).items())
for session_id, agent in sessions:
try:
last_active = getattr(agent, "_evo_last_active", 0)
turns = int(getattr(agent, "_evo_turns", 0))
# Enough signal = enough turns OR enough context pressure.
enough_signal = turns >= cfg.min_turns or _context_pressure_reached(agent)
if not enough_signal:
continue
idle = now - last_active if last_active > 0 else -1
if last_active <= 0 or idle < cfg.idle_seconds:
continue
channel_type = getattr(agent, "_evo_channel_type", "") or ""
receiver = getattr(agent, "_evo_receiver", "") or ""
# Reset baseline BEFORE running so a long pass / new messages during
# it don't double-trigger; turns accrue fresh from here.
agent._evo_turns = 0
run_evolution_for_session(
agent_bridge,
session_id=session_id,
channel_type=channel_type,
receiver=receiver,
idle_minutes=(now - last_active) / 60 if last_active > 0 else 0.0,
)
except Exception as e:
logger.warning(f"[Evolution] Failed to evaluate session={session_id}: {e}")