feat(p49): Telegram 補完 9 頁對應 + daily summary 加商業面未跟進警示
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M-B: Telegram 對應從 6/9 → 9/9 新增 3 個 cmd handler，對應 Phase 45-48 的 3 個新觀測頁： - cmd:obs_overview — 一頁式總覽（三主機 24h + AI 呼叫 + 月成本 + 待審 episode） - cmd:obs_orchestration — Agent 編排矩陣（4 Agent × Models 24h 數字） 本地 Ollama % / RAG 命中 % / 錯誤率 + cost - cmd:obs_business — 商業面 × AI（價格決策 7d by strategy + 未跟進機會 + Outcomes verdict 30d） services/openclaw_bot/menu_keyboards.py::_submenu_observability 升級為 9 項 M-C: daily summary（每日 09:30）加商業面警示 - 從 ai_price_recommendations × action_plans 跨表 JOIN 偵測 high-confidence (≥0.7) 卻無對應 action_plan 的「機會流失」 - 7d 內若有未跟進，daily summary 自動標 ⚠️ 警示 - 對應 Phase 48 business_intel 頁同個邏輯，閉環推送 inline keyboard 升級：日報附 6 個入口（總覽/編排/商業面/主機/AI/預算）， 不再只有 4 個 Phase 38→49 累計 14 commits。觀測台戰役完整收官： - 9 頁全部對應 Telegram cmd - DB 22/22 = 100% 全覆蓋 - 6 個 L2 一鍵 + 3 種主動推送（即時/異常/日常） - 日報含商業面警示 Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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@@ -8318,6 +8318,157 @@ def handle_cmd(cmd, arg, chat_id, reply_to):
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except Exception as e:
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send_message(chat_id, f"❌ 查詢預算失敗：{e}", reply_to, parse_mode=None)
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elif cmd == 'obs_overview':
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# Phase 49: 觀測台總覽（一頁式 KPI）
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try:
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from database.manager import DatabaseManager
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from sqlalchemy import text as _sa
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from datetime import datetime as _dt
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today = _dt.now()
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month_start = _dt(today.year, today.month, 1)
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session = DatabaseManager().get_session()
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host_rows = session.execute(_sa("""
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SELECT host_label, COUNT(*), COUNT(*) FILTER (WHERE healthy)
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FROM host_health_probes
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WHERE probed_at >= NOW() - INTERVAL '24 hours'
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GROUP BY host_label ORDER BY host_label
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""")).fetchall()
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ai = session.execute(_sa("""
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SELECT COUNT(*), COALESCE(SUM(cost_usd), 0),
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COUNT(*) FILTER (WHERE status NOT IN ('ok','cache_only')),
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COUNT(*) FILTER (WHERE rag_hit)
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FROM ai_calls WHERE called_at >= NOW() - INTERVAL '24 hours'
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""")).fetchone()
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month_cost = session.execute(
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_sa("SELECT COALESCE(SUM(cost_usd), 0) FROM ai_calls WHERE called_at >= :ms"),
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{'ms': month_start},
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).fetchone()[0] or 0
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ep_pending = session.execute(
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_sa("SELECT COUNT(*) FROM learning_episodes WHERE promotion_status = 'awaiting_review' AND reviewed_at IS NULL"),
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).fetchone()[0] or 0
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session.close()
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ai_total = int(ai[0] or 0)
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err_rate = (int(ai[2] or 0) / ai_total * 100) if ai_total else 0
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rag_rate = (int(ai[3] or 0) / ai_total * 100) if ai_total else 0
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lines = ["🛰 *觀測台總覽（24h）*", ""]
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lines.append("*三主機在線率：*")
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for label, total, up in host_rows:
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pct = (float(up) / float(total) * 100) if total else 0
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emoji = "✅" if pct >= 99 else "⚠️" if pct >= 90 else "🚨"
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lines.append(f"{emoji} {label}：*{pct:.1f}%*")
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lines.append("")
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lines.append(f"📊 AI 呼叫：*{ai_total:,}* 次（錯誤 {err_rate:.1f}%）")
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lines.append(f"💰 24h 成本：*${float(ai[1] or 0):.2f}* · 當月 *${float(month_cost):.2f}*")
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lines.append(f"💡 RAG 命中率：*{rag_rate:.1f}%*")
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if ep_pending:
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lines.append(f"📋 待審 episodes：*{ep_pending}* 筆")
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lines.append("")
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lines.append("詳細：mo.wooo.work/observability/overview")
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kb = [_row(('🤖 Agent 編排', 'cmd:obs_orchestration'), ('💼 商業面 AI', 'cmd:obs_business')),
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_row(('🏥 主機健康', 'cmd:obs_health'), ('📊 AI 呼叫', 'cmd:obs_ai_calls')),
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_row(('← 返回主選單', 'menu:main'))]
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send_message(chat_id, '\n'.join(lines), reply_to, kb, parse_mode='Markdown')
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except Exception as e:
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send_message(chat_id, f"❌ 查詢觀測台總覽失敗：{e}", reply_to, parse_mode=None)
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elif cmd == 'obs_orchestration':
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# Phase 49: Agent 編排矩陣（4 Agent × Models）
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try:
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from database.manager import DatabaseManager
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from sqlalchemy import text as _sa
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agent_groups = [
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('🤖 OpenClaw', ['openclaw_qa', 'openclaw_daily', 'openclaw_meta', 'openclaw_monthly', 'openclaw_weekly', 'openclaw_bot_main', 'openclaw_bot_gemini', 'openclaw_bot_nim', 'sales_copy', 'code_review_openclaw', 'openclaw_daily_insight']),
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('🔍 Hermes', ['hermes_analyst', 'hermes_intent', 'code_review_hermes']),
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('🧬 NemoTron', ['nemotron_dispatch']),
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('🐘 ElephantAlpha', ['ea_engine', 'code_review_elephant']),
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]
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session = DatabaseManager().get_session()
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lines = ["🌐 *Agent 編排矩陣（24h）*", ""]
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for label, callers in agent_groups:
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row = session.execute(_sa("""
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SELECT COUNT(*),
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COALESCE(SUM(cost_usd), 0),
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COUNT(*) FILTER (WHERE provider IN ('gcp_ollama','ollama_secondary','ollama_111','ollama_other')),
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COUNT(*) FILTER (WHERE rag_hit),
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COUNT(*) FILTER (WHERE status NOT IN ('ok','cache_only'))
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FROM ai_calls
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WHERE called_at >= NOW() - INTERVAL '24 hours'
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AND caller = ANY(:c)
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"""), {'c': callers}).fetchone()
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calls = int(row[0] or 0)
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if calls == 0:
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lines.append(f"{label}：（無呼叫）")
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continue
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cost = float(row[1] or 0)
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ollama_pct = float(row[2] or 0) / calls * 100
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rag_pct = float(row[3] or 0) / calls * 100
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err_pct = float(row[4] or 0) / calls * 100
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lines.append(f"{label}：*{calls:,}* 次 · ${cost:.2f}")
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lines.append(f" 本地 Ollama {ollama_pct:.0f}% · RAG {rag_pct:.0f}% · 錯誤 {err_pct:.1f}%")
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session.close()
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lines.append("")
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lines.append("詳細：mo.wooo.work/observability/agent\\_orchestration")
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kb = [_row(('🛰 觀測台總覽', 'cmd:obs_overview'), ('💼 商業面 AI', 'cmd:obs_business')),
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_row(('← 返回主選單', 'menu:main'))]
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send_message(chat_id, '\n'.join(lines), reply_to, kb, parse_mode='Markdown')
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except Exception as e:
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send_message(chat_id, f"❌ 查詢 Agent 編排失敗：{e}", reply_to, parse_mode=None)
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elif cmd == 'obs_business':
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# Phase 49: 商業面 × AI 編排（AI 在做什麼生意）
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try:
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from database.manager import DatabaseManager
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from sqlalchemy import text as _sa
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session = DatabaseManager().get_session()
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rec_rows = session.execute(_sa("""
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SELECT strategy, COUNT(*), COALESCE(AVG(confidence), 0)
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FROM ai_price_recommendations
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WHERE created_at >= NOW() - INTERVAL '7 days'
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GROUP BY strategy ORDER BY 2 DESC
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""")).fetchall()
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verdict_rows = session.execute(_sa("""
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SELECT verdict, COUNT(*) FROM action_outcomes
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WHERE created_at >= NOW() - INTERVAL '30 days'
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GROUP BY verdict
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""")).fetchall()
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unfollowed = session.execute(_sa("""
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SELECT COUNT(*) FROM ai_price_recommendations r
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WHERE r.created_at >= NOW() - INTERVAL '7 days'
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AND r.confidence >= 0.7
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AND NOT EXISTS (
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SELECT 1 FROM action_plans p
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WHERE p.sku = r.sku
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AND p.created_at >= r.created_at
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AND p.created_at < r.created_at + INTERVAL '7 days'
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)
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""")).fetchone()[0] or 0
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session.close()
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lines = ["💼 *商業面 × AI 編排*", ""]
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if rec_rows:
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lines.append("*AI 價格決策 7d：*")
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for strategy, cnt, conf in rec_rows:
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lines.append(f"• {strategy}：*{int(cnt):,}* 筆（信心 {float(conf):.2f}）")
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else:
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lines.append("（過去 7 日無 AI 價格決策）")
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if unfollowed > 0:
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lines.append("")
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lines.append(f"⚠️ *未跟進機會：{unfollowed} 筆*（high-confidence 卻無 action_plan）")
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if verdict_rows:
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lines.append("")
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lines.append("*Outcomes Verdict 30d：*")
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for v, c in verdict_rows:
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icon = "✅" if v == 'effective' else "❌" if v == 'backfired' else "➖"
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lines.append(f"{icon} {v}：*{int(c):,}*")
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lines.append("")
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lines.append("詳細：mo.wooo.work/observability/business\\_intel")
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kb = [_row(('🛰 觀測台總覽', 'cmd:obs_overview'), ('🌐 Agent 編排', 'cmd:obs_orchestration')),
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_row(('← 返回主選單', 'menu:main'))]
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send_message(chat_id, '\n'.join(lines), reply_to, kb, parse_mode='Markdown')
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except Exception as e:
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send_message(chat_id, f"❌ 查詢商業面失敗：{e}", reply_to, parse_mode=None)
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elif cmd == 'obs_trigger_review':
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# Phase 44 (L2)：Telegram inline 觸發 Code Review Pipeline
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try:
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@@ -585,6 +585,24 @@ def run_observability_daily_summary():
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WHERE audited_at >= NOW() - INTERVAL '7 days'
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"""),
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).fetchone()
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# Phase 49: 商業面未跟進機會（high-confidence 卻無 action_plan）
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unfollowed_count = 0
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try:
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unfollowed_count = session.execute(
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_sa("""
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SELECT COUNT(*) FROM ai_price_recommendations r
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WHERE r.created_at >= NOW() - INTERVAL '7 days'
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AND r.confidence >= 0.7
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AND NOT EXISTS (
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SELECT 1 FROM action_plans p
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WHERE p.sku = r.sku
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AND p.created_at >= r.created_at
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AND p.created_at < r.created_at + INTERVAL '7 days'
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)
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"""),
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).fetchone()[0] or 0
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except Exception:
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pass
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finally:
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session.close()
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@@ -632,16 +650,23 @@ def run_observability_daily_summary():
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if ppt_failed:
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lines.append(f" 失敗：{ppt_failed} 筆")
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if unfollowed_count > 0:
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lines.append("")
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lines.append(f"⚠️ <b>商業面未跟進：{unfollowed_count} 筆</b>"
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f"（high-confidence AI 建議未轉化為 action_plan）")
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lines.append("")
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lines.append('<a href="https://mo.wooo.work/observability/host_health">→ 開觀測台詳查</a>')
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lines.append('<a href="https://mo.wooo.work/observability/overview">→ 開觀測台總覽</a>')
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from services.telegram_templates import send_telegram_with_result
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reply_markup = {
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"inline_keyboard": [
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[{"text": "🏥 主機健康", "callback_data": "cmd:obs_health"},
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{"text": "📊 AI 呼叫", "callback_data": "cmd:obs_ai_calls"}],
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[{"text": "💰 預算", "callback_data": "cmd:obs_budget"},
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{"text": "💬 反饋趨勢", "callback_data": "cmd:obs_quality"}],
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[{"text": "🛰 觀測台總覽", "callback_data": "cmd:obs_overview"},
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{"text": "🌐 Agent 編排", "callback_data": "cmd:obs_orchestration"}],
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[{"text": "💼 商業面 AI", "callback_data": "cmd:obs_business"},
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{"text": "🏥 主機健康", "callback_data": "cmd:obs_health"}],
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[{"text": "📊 AI 呼叫", "callback_data": "cmd:obs_ai_calls"},
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{"text": "💰 預算", "callback_data": "cmd:obs_budget"}],
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],
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}
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send_telegram_with_result('\n'.join(lines), reply_markup=reply_markup, parse_mode='HTML')
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@@ -271,8 +271,11 @@ def _submenu_competitor_ppt():
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def _submenu_observability():
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"""Phase 38 AI 觀測台 — 對應 /observability/* 6 頁。"""
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"""Phase 38-49 AI 觀測台 — 對應 /observability/* 9 頁。"""
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return _menu_with_back([
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_row(('🛰 觀測台總覽 (24h)', 'cmd:obs_overview'),
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('🌐 Agent 編排矩陣', 'cmd:obs_orchestration')),
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_row(('💼 商業面 × AI', 'cmd:obs_business'),),
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_row(('📊 AI 呼叫總覽 (24h)', 'cmd:obs_ai_calls'),
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('🏥 主機健康狀態', 'cmd:obs_health')),
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_row(('💰 預算控管 (當月)', 'cmd:obs_budget'),
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