diff --git a/database/ai_models.py b/database/ai_models.py index c55ff9b..ed06e83 100644 --- a/database/ai_models.py +++ b/database/ai_models.py @@ -4,14 +4,14 @@ from sqlalchemy.orm import relationship from database.models import Base from datetime import datetime, timezone -# Helper for default timestamps +# helper for default timestamps datetime_now = lambda: datetime.now(timezone.utc) class AgentContext(Base): """ - 共享上下文表（替代硬編碼鏈），支援多 Agent 存取與 TTL。 - 索引：(session_id, agent_name, context_key) 以加速跨 Agent 查詢。 + Shared context table (replaces hardcoded chain), supporting multi-agent access and TTL. + Index: (session_id, agent_name, context_key) for fast cross-agent queries. """ __tablename__ = 'agent_context' @@ -19,7 +19,7 @@ class AgentContext(Base): session_id = Column(String(64), nullable=False, index=True) agent_name = Column(String(50), nullable=False, index=True) context_key = Column(String(100), nullable=False) - context_val = Column(Text) # JSON 字串 + context_val = Column(Text) # JSON string created_at = Column(DateTime, default=datetime_now) ttl_minutes = Column(Integer, default=60) @@ -31,7 +31,7 @@ class AgentContext(Base): class ActionPlan(Base): """ - 行動計畫表（NemoTron 輸出，等待審核與執行追蹤）。 + Action plan table (NemoTron output, awaiting review/execution tracking). """ __tablename__ = 'action_plans' @@ -39,7 +39,7 @@ class ActionPlan(Base): session_id = Column(String(64), nullable=True) plan_type = Column(String(50), nullable=True) # price_adjust / restock / campaign sku = Column(String(100), nullable=True, index=True) - payload = Column(Text) # JSON 行動內容 + payload = Column(Text) # JSON payload status = Column(String(20), default='pending') # pending/approved/rejected/executed created_by = Column(String(50)) # nemotron / openclaw approved_by = Column(String(100), nullable=True) # Telegram user_id @@ -54,7 +54,7 @@ class ActionPlan(Base): class ActionOutcome(Base): """ - 行動結果追蹤（閉環學習核心）。 + Action outcome tracking (closed-loop learning core). """ __tablename__ = 'action_outcomes' @@ -72,8 +72,8 @@ class ActionOutcome(Base): class AgentStrategyWeights(Base): """ - Agent 策略權重（OpenClaw 學習累積）。 - 索引：strategy_key 以便快速更新與查詢。 + Agent strategy weights (OpenClaw learning accumulation). + Index: strategy_key for fast updates/query. """ __tablename__ = 'agent_strategy_weights' diff --git a/run_scheduler.py b/run_scheduler.py index 8044e9a..7a1030e 100644 --- a/run_scheduler.py +++ b/run_scheduler.py @@ -12,27 +12,27 @@ from services.decision_tracker import DecisionTracker as DTService logger = logging.getLogger(__name__) decision_tracker_service = DTService() -# 模擬 ICAIM 完成回撥：排程 follow_up +# simulate ICAIM completion callback: schedule follow_up def on_icaim_task_complete(plan_id: int, sku: str): - """此函數由 ICAIM 排程觸發，調用 DecisionTracker.schedule_follow_up""" + """Triggered by ICAIM scheduler to schedule follow_up via DecisionTracker.""" asyncio.create_task(decision_tracker_service.schedule_follow_up(plan_id, sku)) -# 排程設置（保持原有 schedule 邏輯） +# schedule settings (keep original schedule logic) def run_icaim_task(): - """模擬 ICAIM 任務執行""" - logger.info("[Scheduler] [ICAIM] 執行 ICAIM 分析任務...") - # ... 執行 ICAIM 分析 ... + """Simulate ICAIM task execution.""" + logger.info("[Scheduler] [ICAIM] executing ICAIM analysis task...") + # ... execute ICAIM analysis ... plan_id = 123 sku = "sample_sku" - # 任務完成後觸發 follow_up 排程 + # after task completes, trigger follow_up schedule on_icaim_task_complete(plan_id, sku) - logger.info("[Scheduler] [ICAIM] 任務完成，已觸發 follow_up 排程") + logger.info("[Scheduler] [ICAIM] task completed, triggered follow_up schedule") -# 保留原有排程設定 +# keep original schedule configuration schedule.every(6).hours.do(run_icaim_task) -logger.info("📅 已設定：每 6 小時執行 ICAIM 分析任務") +logger.info("📅 scheduled: ICAIM analysis task every 6 hours") -# 啟動排程循環（保持原有主循環） +# start schedule loop (keep original main loop) if __name__ == "__main__": logger.info("Scheduler started.") while True: diff --git a/services/ai_orchestrator.py b/services/ai_orchestrator.py index 0ba019f..704740e 100644 --- a/services/ai_orchestrator.py +++ b/services/ai_orchestrator.py @@ -13,8 +13,8 @@ logger = logging.getLogger(__name__) class AIOrchestrator: """ - 協調中樞：負責 EventRouter 的 L1/L2 處理、Agent 共享上下文與閉環決策追蹤。 - 設計輕量，單檔不超過 100 行。 + Coordination hub: handles EventRouter L1/L2, agent shared context, and closed-loop decision tracking. + Single file <= 100 lines. """ def __init__(self): @@ -23,8 +23,8 @@ class AIOrchestrator: async def handle_l1(self, event: Dict[str, Any], session_id: str) -> Dict[str, Any]: """ - L1：語意翻譯 + 原因分析（由 Hermes 提供）。 - 結果會寫入 agent_context，並可作為 L2 的上下文。 + L1: semantic translation + reason analysis (provided by Hermes). + Writes to agent_context and can be used as L2 context. """ ctx = await self._get_context(session_id) result = await self.hermes.handle_l1(event, ctx) @@ -33,13 +33,13 @@ class AIOrchestrator: async def handle_l2(self, event: Dict[str, Any], session_id: str) -> Dict[str, Any]: """ - L2：規劃 + 審核閘。 - 輸入包含 L1 分析結果（若可用），產出 ActionPlan 等待批准。 + L2: planning + review gate. + Produces an ActionPlan awaiting approval (handled via Telegram callback). """ - ctx = await self._get_context(session_id) # 包含 hermes 分析 + ctx = await self._get_context(session_id) # includes hermes analysis result = await self.nemotron.handle_l2(event, ctx) await self._save_action_plan(result) - # 審核閘由 routes/bot_api_routes 透過 callback 處理 + # review gate handled by routes/bot_api_routes callback return result async def _get_context(self, session_id: str) -> Dict[str, Any]: @@ -77,7 +77,7 @@ class AIOrchestrator: session.commit() except Exception as e: session.rollback() - logger.error(f"[AIOrchestrator] save_context 失敗: {e}") + logger.error(f"[AIOrchestrator] save_context failed: {e}") raise finally: session.close() @@ -102,7 +102,7 @@ class AIOrchestrator: session.commit() except Exception as e: session.rollback() - logger.error(f"[AIOrchestrator] save_action_plan 失敗: {e}") + logger.error(f"[AIOrchestrator] save_action_plan failed: {e}") raise finally: session.close() diff --git a/services/event_router.py b/services/event_router.py index f493e0b..87031bf 100644 --- a/services/event_router.py +++ b/services/event_router.py @@ -12,7 +12,7 @@ logger = logging.getLogger(__name__) async def _handle_l1(event: Dict[str, Any], session_id: str) -> Dict[str, Any]: """ - L1：語意翻譯 + 原因分析（由 AIOrchestrator 調用 Hermes）。 + L1: semantic translation + reason analysis (provided by Hermes). """ orchestrator = AIOrchestrator() return await orchestrator.handle_l1(event, session_id) @@ -20,22 +20,22 @@ async def _handle_l1(event: Dict[str, Any], session_id: str) -> Dict[str, Any]: async def _handle_l2(event: Dict[str, Any], session_id: str) -> Dict[str, Any]: """ - L2：規劃 + 審核閘。 - 產出 ActionPlan 等待批准（Telegram 回調處理）。 + L2: planning + review gate. + Produces an ActionPlan awaiting approval (handled via Telegram callback). """ orchestrator = AIOrchestrator() return await orchestrator.handle_l2(event, session_id) async def _handle_l0(event: Dict[str, Any]) -> Dict[str, Any]: - """L0：直接回傳原始事件（兼容與監控）""" + """L0: return raw event (for compatibility/monitoring).""" return {"status": "ok", "echo": event.get("event_type")} async def dispatch(event: Dict[str, Any], admin_chat_ids: Optional[list] = None) -> Dict[str, Any]: """ - 事件路由主入口（與 routes/bot_api_routes 兼容）。 - 輸出格式與 dispatch_v1 保持一致，以便平滑切換。 + Main event routing entry (compatible with routes/bot_api_routes). + Output format matches dispatch_v1 for smooth migration. """ tier = _classify(event) session_id = f"evt:{event.get('event_type')}:{event.get('source', 'unknown')}" @@ -50,7 +50,7 @@ async def dispatch(event: Dict[str, Any], admin_chat_ids: Optional[list] = None) else: result = await _handle_l0(event) - # 保留舊版回傳格式 + # preserve legacy output format return { "tier": tier, "sent": 1, @@ -59,7 +59,7 @@ async def dispatch(event: Dict[str, Any], admin_chat_ids: Optional[list] = None) "payload": result, } except Exception as e: - logger.exception(f"[EventRouter] dispatch 失敗: {e}") + logger.exception(f"[EventRouter] dispatch failed: {e}") return { "tier": tier, "sent": 0,