fix: 所有 Telegram 告警內容統一繁體中文

新增 _TRIGGER_ZH / _AGENT_ZH / _ACTION_ZH 翻譯表：
- trigger_type 英文代碼 → 繁中標籤（價格下滑警報、市場機會偵測等）
- agent 名稱 → 繁中（Hermes 分析師、NemoTron 監控、OpenClaw 策略師）
- action 代碼 → 繁中（競品價格分析、派送告警通知等）
- 升級審核觸發類型、參與模組、執行步驟全面繁中化

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

services/elephant_alpha_autonomous_engine.py

@@ -49,6 +49,42 @@ _TRIGGER_TO_DECISION_TYPE = {
     "resource_optimization": DecisionType.RESOURCE_ALLOCATION,
 }
 
+# 告警繁中翻譯表（所有 Telegram 告警內容統一使用繁體中文）
+_TRIGGER_ZH: Dict[str, str] = {
+    "price_drop_alert":      "價格下滑警報",
+    "market_opportunity":    "市場機會偵測",
+    "threat_escalation":     "威脅升級通報",
+    "resource_optimization": "資源調配優化",
+    "sales_anomaly":         "銷售異常偵測",
+    "ea_escalation":         "EA 升級審核",
+}
+
+_AGENT_ZH: Dict[str, str] = {
+    "hermes":    "Hermes 分析師",
+    "nemotron":  "NemoTron 監控",
+    "openclaw":  "OpenClaw 策略師",
+    "scheduler": "排程器",
+    "?":         "未知模組",
+}
+
+_ACTION_ZH: Dict[str, str] = {
+    "analyze_price_competition":  "競品價格分析",
+    "dispatch_alert":             "派送告警通知",
+    "generate_strategic_analysis": "產出策略分析報告",
+    "adjust_price":               "調整定價",
+    "send_alert":                 "發送告警",
+}
+
+
+def _zh_trigger(trigger_type: str) -> str:
+    return _TRIGGER_ZH.get(trigger_type, trigger_type)
+
+
+def _zh_step(step: dict) -> str:
+    agent = _AGENT_ZH.get(step.get("agent", "?"), step.get("agent", "?"))
+    action = _ACTION_ZH.get(step.get("action", ""), step.get("action", "?"))
+    return f"[{agent}] {action}"
+
 
 @dataclass
 class DecisionOutcome:
@@ -551,14 +587,14 @@ class ElephantAlphaAutonomousEngine:
             msg, keyboard = triaged_alert(
                 base_event={
                     "event_type": trigger.trigger_type,
-                    "title": f"🐘 EA 自主執行完畢 · {trigger.trigger_type}",
+                    "title": f"🐘 EA 自主執行完畢 · {_zh_trigger(trigger.trigger_type)}",
                     "summary": decision.expected_outcome or "EA 完成自主決策",
                     "id": f"ea_{trigger.trigger_type}_{int(datetime.now().timestamp())}",
                 },
                 tier_label="🐘 Elephant Alpha · 自主執行",
                 ai_summary=(decision.reasoning or "")[:300],
                 ai_executed=[
-                    f"[{s.get('agent', '?')}] {s.get('action', '?')}"
+                    _zh_step(s)
                     for s in decision.execution_plan[:5]
                 ] or ["（無具體執行計畫）"],
             )
@@ -632,7 +668,7 @@ class ElephantAlphaAutonomousEngine:
             msg, keyboard = triaged_alert(
                 base_event={
                     "event_type": "ea_escalation",
-                    "title": f"🐘 EA 升級審核 · {trigger.trigger_type}",
+                    "title": f"🐘 EA 升級審核 · {_zh_trigger(trigger.trigger_type)}",
                     "summary": (
                         f"自主決策信心度 {decision.confidence:.2f} 低於門檻，需人工批准"
                     ),
@@ -641,12 +677,12 @@ class ElephantAlphaAutonomousEngine:
                 tier_label="🐘 Elephant Alpha · L3 HITL",
                 ai_summary=(decision.reasoning or "")[:300],
                 ai_cause=(
-                    f"觸發器：{trigger.trigger_type} | "
+                    f"觸發類型：{_zh_trigger(trigger.trigger_type)} | "
                     f"信心度：{decision.confidence:.2f} | "
-                    f"需求 Agent：{', '.join(decision.agents_required)}"
+                    f"參與模組：{', '.join(_AGENT_ZH.get(a, a) for a in decision.agents_required)}"
                 ),
                 ai_actions=[
-                    f"Step {s.get('step', i+1)}: [{s.get('agent', '?')}] {s.get('action', '?')}"
+                    f"步驟 {s.get('step', i+1)}：{_zh_step(s)}"
                     for i, s in enumerate(decision.execution_plan[:3])
                 ] or ["無具體執行計畫"],
             )