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ba777ed706
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).
59 lines
2.3 KiB
Python
59 lines
2.3 KiB
Python
"""Evolution undo tool.
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Lets the main chat agent roll back a previous self-evolution when the user asks
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("undo the last learning"). The rollback itself is a deterministic FILE RESTORE
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from the snapshot taken before the evolution — the model only supplies the
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backup_id it reads from the [EVOLUTION] record in the conversation. No LLM-driven
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re-editing is involved, so a restore can never make things worse.
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"""
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from agent.tools.base_tool import BaseTool, ToolResult
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class EvolutionUndoTool(BaseTool):
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"""Restore memory/skill files to the state before a self-evolution."""
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name: str = "evolution_undo"
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description: str = (
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"Undo a previous self-evolution (self-learning) by restoring the "
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"memory/skill files to their state before that learning. Use this when "
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"the user asks to undo / revert / roll back the last self-learning. "
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"Find the backup_id in the most recent [EVOLUTION] record in the "
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"conversation and pass it here."
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)
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params: dict = {
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"type": "object",
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"properties": {
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"backup_id": {
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"type": "string",
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"description": (
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"The backup_id from the [EVOLUTION] record to restore "
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"(e.g. '20260607-155551-850')."
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),
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}
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},
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"required": ["backup_id"],
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}
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def execute(self, args: dict):
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backup_id = (args.get("backup_id") or "").strip()
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if not backup_id:
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return ToolResult.fail("Error: backup_id is required")
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try:
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from agent.memory.config import get_default_memory_config
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from agent.evolution.backup import restore_backup
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workspace_dir = get_default_memory_config().get_workspace()
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ok = restore_backup(workspace_dir, backup_id)
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if ok:
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return ToolResult.success(
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f"Restored memory/skills to the state before evolution "
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f"{backup_id}. The previous self-learning has been undone."
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)
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return ToolResult.fail(
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f"Could not find or restore backup {backup_id}. It may have "
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f"expired or already been rolled back."
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)
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except Exception as e:
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return ToolResult.fail(f"Error during undo: {e}")
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