fix: Telegram bot 全功能修復 — 16個await按鈕/AI對話/模型遷移/DB schema

## Telegram Bot 功能修復 - 補全 16 個 await: 按鈕的 handler（日期選擇/目標設定/促銷追蹤等），新增 _handle_await_callback + _process_await_input 完整狀態機 - cmd: 按鈕加入 ⏳ 即時回饋 + try/except 防 BadRequest - handle_callback 加頂層 try/except 錯誤兜底 - 補 momo:cmd:suggestion + momo:menu:main callback handler - 修復 _enhanced_keyword_matching context NameError ## AI 模型遷移（hermes3@111 → qwen2.5@188） - hermes_analyst_service: URL 192.168.0.111→188, hermes3→qwen2.5:7b-instruct - code_review_pipeline: 改用 HERMES_URL/HERMES_MODEL 常數 - elephant_alpha_orchestrator / nemoton_dispatcher: registry/footprint 同步 - aider_heal_executor: OLLAMA_API_BASE fallback 改 188 - ai_routes: footprint display 字串改 qwen2.5:7b-instruct ## ElephantAlpha 404 修復 - elephant_service: openrouter→NVIDIA NIM, nvidia/llama-3.1-nemotron-ultra-253b-v1 - ai_provider: 模型 ID 同步更新 ## TELEGRAM_CHAT_ID 環境變數修正 - cicd_routes + aider_heal_executor: 優先讀 TELEGRAM_CHAT_IDS[0]， fallback TELEGRAM_CHAT_ID，修復通知靜默失敗 ## AI 對話 logging 改善 - telegram_ai_integration: Hermes 降級改 WARNING，OpenClaw 失敗加 exc_info - hermes_analyst_service: 連線失敗 log 加 host/model context ## DB Schema 修復 - migrations/019: action_plans 補齊全欄位，DROP NOT NULL action_type - autoheal_models: ActionPlan ORM 同步為超集 schema Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-04-25 03:30:14 +08:00
parent 86d80d3f2a
commit d5c0feab5e
13 changed files with 509 additions and 129 deletions
--- a/database/autoheal_models.py
+++ b/database/autoheal_models.py
@@ -28,22 +28,34 @@ class AgentContext(Base):

 class ActionPlan(Base):
    """
-    行動計畫表（NemoTron 輸出，等待審核與執行追蹤）。
+    行動計畫表 — 統一 schema（超集）。
+    Group A（01-init.sql / CodeReview / OpenClaw）:
+      action_type, description, priority, metadata_json
+    Group B（migration 017 / watcher_agent / ai_orchestrator）:
+      session_id, plan_type, sku, payload, created_by, approved_by, executed_at
+    migration 019 已在 DB 補齊所有欄位。
    """
    __tablename__ = 'action_plans'

    id = Column(Integer, primary_key=True, autoincrement=True)
+    # Group A columns
+    action_type = Column(String(100), nullable=True)    # code_review_fix / openclaw_recommendation
+    description = Column(Text)                          # 人類可讀的行動說明
+    status = Column(String(50), default='pending')      # pending/auto_pending/pending_review/executed
+    priority = Column(Integer, default=3)               # 1=critical 2=high 3=medium 4=low
+    metadata_json = Column(Text)                        # JSON: pipeline_id/commit_sha/findings
+    created_at = Column(DateTime, default=datetime.now)
+    # Group B columns (ADR-012 / NemoTron)
    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)
+    sku = Column(String(100), nullable=True)
    payload = Column(Text)                              # JSON 行動內容
-    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
-    created_at = Column(DateTime, default=datetime.now)
    executed_at = Column(DateTime, nullable=True)

    __table_args__ = (
+        Index('idx_action_plans_type', 'action_type'),
        Index('idx_action_plan_sku_status', 'sku', 'status'),
        Index('idx_action_plan_created', 'created_at'),
        {'extend_existing': True},
--- a/migrations/019_fix_action_plans_schema.sql
+++ b/migrations/019_fix_action_plans_schema.sql
@@ -0,0 +1,199 @@
+-- Migration 019: Fix action_plans schema — add ALL columns needed by all callers
+-- 建立日期：2026-04-25
+-- 問題根源：
+--   (A) code_review_pipeline_service.py / openclaw_strategist_service.py 寫入
+--       action_type / description / priority / metadata_json（來自 01-init.sql 定義）
+--   (B) watcher_agent.py / ai_orchestrator.py 寫入
+--       session_id / plan_type / sku / payload / created_by / approved_by（來自 migration 017）
+--   兩組 callers 使用不同 schema，造成寫入失敗。
+--   解決方案：讓 action_plans 成為兩組欄位的超集（superset）。
+-- 修復方式：逐欄 ADD COLUMN IF NOT EXISTS（冪等，不鎖表）
+-- 回滾路徑（若需還原）：
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS action_type;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS description;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS priority;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS metadata_json;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS session_id;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS plan_type;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS sku;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS payload;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS created_by;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS approved_by;
+--   ALTER TABLE action_plans DROP COLUMN IF EXISTS executed_at;
+
+-- ── Group A: 01-init.sql / CodeReview / OpenClaw ──────────────────────────────
+
+-- action_type — 'code_review_fix' | 'openclaw_recommendation'
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'action_type'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN action_type VARCHAR(100);
+        RAISE NOTICE 'action_plans.action_type column added';
+    ELSE
+        RAISE NOTICE 'action_plans.action_type already exists, skipped';
+    END IF;
+END $$;
+
+-- description — 人類可讀行動說明
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'description'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN description TEXT;
+        RAISE NOTICE 'action_plans.description column added';
+    ELSE
+        RAISE NOTICE 'action_plans.description already exists, skipped';
+    END IF;
+END $$;
+
+-- priority — 1=critical 2=high 3=medium 4=low
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'priority'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN priority INTEGER DEFAULT 3;
+        RAISE NOTICE 'action_plans.priority column added';
+    ELSE
+        RAISE NOTICE 'action_plans.priority already exists, skipped';
+    END IF;
+END $$;
+
+-- metadata_json — pipeline_id / commit_sha / findings JSON 擴展
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'metadata_json'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN metadata_json TEXT;
+        RAISE NOTICE 'action_plans.metadata_json column added';
+    ELSE
+        RAISE NOTICE 'action_plans.metadata_json already exists, skipped';
+    END IF;
+END $$;
+
+-- ── Group B: Migration 017 / watcher_agent / ai_orchestrator ─────────────────
+
+-- session_id — Agent session identifier
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'session_id'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN session_id VARCHAR(64);
+        RAISE NOTICE 'action_plans.session_id column added';
+    ELSE
+        RAISE NOTICE 'action_plans.session_id already exists, skipped';
+    END IF;
+END $$;
+
+-- plan_type — 'price_adjust' | 'restock' | 'campaign'
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'plan_type'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN plan_type VARCHAR(50);
+        RAISE NOTICE 'action_plans.plan_type column added';
+    ELSE
+        RAISE NOTICE 'action_plans.plan_type already exists, skipped';
+    END IF;
+END $$;
+
+-- sku — 商品 SKU
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'sku'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN sku VARCHAR(100);
+        RAISE NOTICE 'action_plans.sku column added';
+    ELSE
+        RAISE NOTICE 'action_plans.sku already exists, skipped';
+    END IF;
+END $$;
+
+-- payload — JSON 行動內容（NemoTron 輸出）
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'payload'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN payload TEXT;
+        RAISE NOTICE 'action_plans.payload column added';
+    ELSE
+        RAISE NOTICE 'action_plans.payload already exists, skipped';
+    END IF;
+END $$;
+
+-- created_by — 'nemotron' | 'openclaw' | 'code_review_pipeline'
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'created_by'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN created_by VARCHAR(50);
+        RAISE NOTICE 'action_plans.created_by column added';
+    ELSE
+        RAISE NOTICE 'action_plans.created_by already exists, skipped';
+    END IF;
+END $$;
+
+-- approved_by — Telegram user_id
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'approved_by'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN approved_by VARCHAR(100);
+        RAISE NOTICE 'action_plans.approved_by column added';
+    ELSE
+        RAISE NOTICE 'action_plans.approved_by already exists, skipped';
+    END IF;
+END $$;
+
+-- executed_at — 執行時間戳
+DO $$
+BEGIN
+    IF NOT EXISTS (
+        SELECT 1 FROM information_schema.columns
+        WHERE table_name = 'action_plans' AND column_name = 'executed_at'
+    ) THEN
+        ALTER TABLE action_plans ADD COLUMN executed_at TIMESTAMP;
+        RAISE NOTICE 'action_plans.executed_at column added';
+    ELSE
+        RAISE NOTICE 'action_plans.executed_at already exists, skipped';
+    END IF;
+END $$;
+
+-- ── 索引補充 ──────────────────────────────────────────────────────────────────
+
+CREATE INDEX IF NOT EXISTS idx_action_plans_type      ON action_plans(action_type);
+CREATE INDEX IF NOT EXISTS idx_action_plan_sku_status  ON action_plans(sku, status);
+CREATE INDEX IF NOT EXISTS idx_action_plan_created     ON action_plans(created_at);
+
+-- ── 修正 action_type NOT NULL 殘留問題 ──────────────────────────────────────
+-- 根因：action_type 在 01-init.sql 原始定義中為 NOT NULL，
+--       migration 019 的 IF NOT EXISTS 跳過了該欄位，NOT NULL 約束未被修正。
+--       watcher_agent.py / ai_orchestrator.py 插入時不填 action_type → 違反約束。
+-- 修正：DROP NOT NULL + 設定 DEFAULT 'auto'（冪等，不鎖表）
+ALTER TABLE action_plans ALTER COLUMN action_type DROP NOT NULL;
+ALTER TABLE action_plans ALTER COLUMN action_type SET DEFAULT 'auto';
+
+DO $$
+BEGIN
+    RAISE NOTICE 'Migration 019 done: action_plans unified schema (Group A + Group B columns) + action_type NOT NULL fix';
+END $$;
--- a/routes/ai_routes.py
+++ b/routes/ai_routes.py
@@ -1637,7 +1637,7 @@ def api_icaim_trigger():

            if result.threats:
                hermes_stats = {
-                    'model':        'hermes3:latest',
+                    'model':        'qwen2.5:7b-instruct',
                    'duration_sec': hermes_duration,
                    'tokens':       result.hermes_tokens,
                }
--- a/routes/cicd_routes.py
+++ b/routes/cicd_routes.py
@@ -558,7 +558,12 @@ def run_diagnosis(env):
 # =============================================================================

 TELEGRAM_BOT_TOKEN = os.environ.get('TELEGRAM_BOT_TOKEN', '')
-TELEGRAM_CHAT_ID = os.environ.get('TELEGRAM_CHAT_ID', '')
+_chat_ids_raw = os.environ.get('TELEGRAM_CHAT_IDS', '[]')
+try:
+    _chat_ids_list = json.loads(_chat_ids_raw)
+    TELEGRAM_CHAT_ID = str(_chat_ids_list[0]) if _chat_ids_list else os.environ.get('TELEGRAM_CHAT_ID', '')
+except Exception:
+    TELEGRAM_CHAT_ID = os.environ.get('TELEGRAM_CHAT_ID', '')

 if not TELEGRAM_BOT_TOKEN or not TELEGRAM_CHAT_ID:
    import logging
--- a/services/ai_provider.py
+++ b/services/ai_provider.py
@@ -134,7 +134,7 @@ class AIProviderService:
            'elephant': {
                'connected': elephant_connected,
                'model': self._elephant.model if elephant_connected else None,
-                'available_models': [{'id': 'openrouter/elephant-alpha', 'name': 'Elephant Alpha'}],
+                'available_models': [{'id': 'nvidia/llama-3.1-nemotron-ultra-253b-v1', 'name': 'Nemotron Ultra 253B'}],
                'type': 'cloud',
                'cost': 'efficient'
            },
--- a/services/aider_heal_executor.py
+++ b/services/aider_heal_executor.py
@@ -13,6 +13,7 @@ ADR-014: Autonomous Code Heal Pipeline
  L5 - Telegram 通知每次修復結果（成功/失敗/回滾）
 """

+import json
 import os
 import re
 import time
@@ -41,14 +42,19 @@ HEALTH_CHECK_URL: str = (
    os.getenv("MOMO_BASE_URL", "https://mo.wooo.work").rstrip("/") + "/health"
 )

-OLLAMA_API_BASE: str = os.getenv("OLLAMA_API_BASE", "http://192.168.0.111:11434")
+OLLAMA_API_BASE: str = os.getenv("OLLAMA_API_BASE", "http://192.168.0.188:11434")
 AIDER_MODEL: str = os.getenv("AIDER_MODEL", "ollama/qwen3-coder-next")

 MAX_DIFF_LINES: int = int(os.getenv("AIDER_MAX_DIFF_LINES", "50"))
 MAX_HOURLY_FIX: int = int(os.getenv("AIDER_MAX_HOURLY_FIX", "5"))

 TELEGRAM_BOT_TOKEN: str = os.getenv("TELEGRAM_BOT_TOKEN", "")
-TELEGRAM_CHAT_ID: str = os.getenv("TELEGRAM_CHAT_ID", "")
+_chat_ids_raw = os.getenv("TELEGRAM_CHAT_IDS", "[]")
+try:
+    _chat_ids_list = json.loads(_chat_ids_raw)
+    TELEGRAM_CHAT_ID: str = str(_chat_ids_list[0]) if _chat_ids_list else os.getenv("TELEGRAM_CHAT_ID", "")
+except Exception:
+    TELEGRAM_CHAT_ID = os.getenv("TELEGRAM_CHAT_ID", "")

 # 允許 Aider 修改的路徑（正規表示式）
 ALLOWED_FILE_PATTERN = re.compile(
--- a/services/code_review_pipeline_service.py
+++ b/services/code_review_pipeline_service.py
@@ -29,6 +29,7 @@ from typing import Any, Dict, List, Optional

 from database.manager import get_session
 from sqlalchemy import text
+from services.hermes_analyst_service import HERMES_URL as _HERMES_URL, HERMES_MODEL as _HERMES_MODEL

 logger = logging.getLogger(__name__)

@@ -189,7 +190,7 @@ class CodeReviewPipeline:
    # ── Step 2：Hermes 掃描 ───────────────────────────────────────────────────

    def _hermes_scan(self, files: Dict[str, str]) -> List[Dict]:
-        """直呼內網 Ollama（http://192.168.0.111:11434），免認證"""
+        """直呼內網 Ollama（http://192.168.0.188:11434），免認證"""
        try:
            import requests as _req

@@ -213,8 +214,8 @@ class CodeReviewPipeline:
 只輸出 JSON 陣列，不含其他文字。無問題時輸出 []"""

            resp = _req.post(
-                "http://192.168.0.111:11434/api/generate",
-                json={"model": "hermes3:latest", "prompt": prompt,
+                f"{_HERMES_URL}/api/generate",
+                json={"model": _HERMES_MODEL, "prompt": prompt,
                      "stream": False, "options": {"temperature": 0.1}},
                timeout=120,
            )
--- a/services/elephant_alpha_orchestrator.py
+++ b/services/elephant_alpha_orchestrator.py
@@ -69,7 +69,7 @@ class ElephantAlphaOrchestrator:
        self.agents = {
            "hermes": AgentCapability(
                name="Hermes Analyst",
-                model="hermes3:latest",
+                model="qwen2.5:7b-instruct",
                strengths=["price_competition_analysis", "threat_detection", "market_intelligence"],
                limitations=["context_window", "real_time_data"],
                cost_per_token=0.0,
@@ -112,7 +112,7 @@ CURRENT ARCHITECTURE:
 - Your role: Autonomous decision-making and agent orchestration

 AGENT CAPABILITIES:
-1. HERMES (hermes3:latest)
+1. HERMES (qwen2.5:7b-instruct)
   - Strengths: Price competition analysis, threat detection, market intelligence
   - Limitations: Limited context window, no real-time data access
   - Best for: Analyzing large datasets, identifying patterns, threat assessment
--- a/services/elephant_service.py
+++ b/services/elephant_service.py
@@ -15,15 +15,15 @@ from dataclasses import dataclass

 logger = logging.getLogger(__name__)

-# Elephant Alpha 設定
-OPENROUTER_API_KEY = os.getenv('OPENROUTER_API_KEY', '')
-ELEPHANT_ALPHA_URL = "https://openrouter.ai/api/v1/chat/completions"
-DEFAULT_ELEPHANT_MODEL = "openrouter/elephant-alpha"
+# Elephant Alpha 設定（NVIDIA NIM API）
+NVIDIA_API_KEY = os.getenv('NVIDIA_API_KEY', '')
+ELEPHANT_ALPHA_URL = "https://integrate.api.nvidia.com/v1/chat/completions"
+DEFAULT_ELEPHANT_MODEL = "nvidia/llama-3.1-nemotron-ultra-253b-v1"
 ELEPHANT_TIMEOUT = int(os.getenv('ELEPHANT_TIMEOUT', '120'))  # 預設 2 分鐘

-# Elephant Alpha 定價 (USD per 1M tokens) - 預估效能型定價
+# Elephant Alpha 定價 (USD per 1M tokens) - NVIDIA NIM 定價
 ELEPHANT_PRICING = {
-    'openrouter/elephant-alpha': {'input': 0.10, 'output': 0.40},
+    'nvidia/llama-3.1-nemotron-ultra-253b-v1': {'input': 0.10, 'output': 0.40},
 }

@dataclass
@@ -48,7 +48,7 @@ class ElephantService:
        """
        初始化 Elephant 服務
        """
-        self.api_key = api_key or OPENROUTER_API_KEY
+        self.api_key = api_key or NVIDIA_API_KEY
        self.model = model or DEFAULT_ELEPHANT_MODEL

    # W3-A: 護欄 2 — 斷線降級 cache (300s TTL，不每次 ping OpenRouter)
@@ -79,7 +79,7 @@ class ElephantService:
    @staticmethod
    def calculate_cost(model: str, input_tokens: int, output_tokens: int) -> Dict[str, float]:
        """計算費用"""
-        pricing = ELEPHANT_PRICING.get(model, ELEPHANT_PRICING['openrouter/elephant-alpha'])
+        pricing = ELEPHANT_PRICING.get(model, ELEPHANT_PRICING['nvidia/llama-3.1-nemotron-ultra-253b-v1'])
        input_cost = (input_tokens / 1_000_000) * pricing['input']
        output_cost = (output_tokens / 1_000_000) * pricing['output']
        return {
--- a/services/hermes_analyst_service.py
+++ b/services/hermes_analyst_service.py
@@ -4,7 +4,7 @@
 Hermes 3 競價情報分析服務 (Module 2)

 角色：分析師 (Analyst)
-模型：hermes3:latest @ 192.168.0.111:11434
+模型：qwen2.5:7b-instruct @ 192.168.0.188:11434
 輸入：SQL 漏斗篩選後的候選商品（~300筆）
 輸出：Top N 威脅清單（結構化 JSON）→ 交給 NemoTron dispatcher

@@ -25,8 +25,8 @@ from sqlalchemy import text

 logger = logging.getLogger(__name__)

-HERMES_MODEL = "hermes3:latest"
-HERMES_URL = "http://192.168.0.111:11434"
+HERMES_MODEL = "qwen2.5:7b-instruct"
+HERMES_URL = "http://192.168.0.188:11434"
 HERMES_TIMEOUT = 120  # 秒，批量 300 筆最長預估 ~90s
 TOP_N = 20  # 輸出前 N 個威脅，控制 NemoTron 每次消耗配額

@@ -118,7 +118,11 @@ class HermesAnalystService:
                None, self._call_hermes_intent, message
            )
        except Exception as e:
-            logger.warning(f"[Hermes.handle_l1] LLM 意圖分析失敗（降級規則引擎）: {e}")
+            logger.error(
+                f"[Hermes.handle_l1] run_in_executor 例外，降級規則引擎"
+                f"（{type(e).__name__}: {e}）",
+                exc_info=True,
+            )

        if llm_result:
            return llm_result
@@ -167,7 +171,10 @@ class HermesAnalystService:
                "metadata": {"source": "hermes_llm"},
            }
        except Exception as e:
-            logger.info(f"[Hermes.intent] 降級規則引擎（{type(e).__name__}: {e}）")
+            logger.warning(
+                f"[Hermes.intent] Ollama 連線失敗，降級規則引擎"
+                f"（host={HERMES_URL} model={HERMES_MODEL} error={type(e).__name__}: {e}）"
+            )
            return None

    def _rule_based_intent(self, message: str) -> dict:
@@ -527,7 +534,7 @@ if __name__ == "__main__":
    ]
    fake_pchome = {"A001": 280, "A003": 980, "A005": 760, "A007": 590, "A009": 350}

-    print("=== Hermes 3 競價分析 CLI 測試 ===\n")
+    print("=== AI分析師 競價分析 CLI 測試 ===\n")
    raw = service._batch_analyze(fake_candidates, fake_pchome)

    for t in raw:
--- a/services/nemoton_dispatcher_service.py
+++ b/services/nemoton_dispatcher_service.py
@@ -283,8 +283,8 @@ def _build_footprint_json(hermes_stats: Optional[dict], nim_stats: Optional[dict
    result = {}
    if hermes_stats:
        result["analyst"] = {
-            "model":        "hermes3:latest",
-            "host":         "192.168.0.111",
+            "model":        "qwen2.5:7b-instruct",
+            "host":         "192.168.0.188",
            "duration_sec": hermes_stats.get("duration_sec", 0),
            "tokens":       hermes_stats.get("tokens", 0),
            "cost_usd":     0,
@@ -317,11 +317,11 @@ def _build_footprint_block(hermes_stats: Optional[dict], nim_stats: Optional[dic
        dur = hermes_stats.get("duration_sec", 0)
        tok = hermes_stats.get("tokens", "?")
        lines.append(
-            f"• 🔍 分析: Hermes 3 8B (本地 111) | "
+            f"• 🔍 分析: Qwen2.5 7B (本地 188) | "
            f"耗時: {dur:.1f}s | Tokens: {tok} | $0 成本"
        )
    else:
-        lines.append("• 🔍 分析: Hermes 3 8B (本地 111) | $0 成本")
+        lines.append("• 🔍 分析: Qwen2.5 7B (本地 188) | $0 成本")

    if nim_stats:
        tok   = nim_stats.get("total_tokens", "?")
--- a/services/telegram_bot_service.py
+++ b/services/telegram_bot_service.py
@@ -442,112 +442,185 @@ class TrendTelegramBot:
        await query.answer()
        data = query.data

-        # ===== 主選單按鈕 =====
-        if data == "menu_main" or data == "menu:main":
-            await query.edit_message_text(
-                "👋 *MOMO 趨勢助手 Bot* — 請選擇功能類別：",
-                parse_mode='Markdown',
-                reply_markup=self._get_main_menu_keyboard()
-            )
+        try:
+            # ===== 主選單按鈕 =====
+            if data == "menu_main" or data == "menu:main":
+                await query.edit_message_text(
+                    "👋 *MOMO 趨勢助手 Bot* — 請選擇功能類別：",
+                    parse_mode='Markdown',
+                    reply_markup=self._get_main_menu_keyboard()
+                )

-        # ===== 新的完整菜單系統 =====
-        elif data.startswith("menu:"):
-            await self._handle_main_menu_callback(query, data)
+            # ===== 新的完整菜單系統 =====
+            elif data.startswith("menu:"):
+                await self._handle_main_menu_callback(query, data)

-        # ===== 舊的簡單菜單（向下相容） =====
-        elif data == "menu_trend":
-            await query.edit_message_text(
-                "📊 *熱門趨勢*\n\n請選擇分類：",
-                parse_mode='Markdown',
-                reply_markup=self._get_category_keyboard("trend")
-            )
+            # ===== 舊的簡單菜單（向下相容） =====
+            elif data == "menu_trend":
+                await query.edit_message_text(
+                    "📊 *熱門趨勢*\n\n請選擇分類：",
+                    parse_mode='Markdown',
+                    reply_markup=self._get_category_keyboard("trend")
+                )

-        elif data == "menu_search":
-            context.user_data['waiting_for'] = 'search_query'
-            await query.edit_message_text(
-                "🔍 *AI 搜尋*\n\n請輸入要搜尋的關鍵字：\n\n"
-                "例如：夏季防曬推薦、母親節禮物",
-                parse_mode='Markdown',
-                reply_markup=InlineKeyboardMarkup([[
-                    InlineKeyboardButton("🔙 返回主選單", callback_data="menu:main")
-                ]])
-            )
+            elif data == "menu_search":
+                context.user_data['waiting_for'] = 'search_query'
+                await query.edit_message_text(
+                    "🔍 *AI 搜尋*\n\n請輸入要搜尋的關鍵字：\n\n"
+                    "例如：夏季防曬推薦、母親節禮物",
+                    parse_mode='Markdown',
+                    reply_markup=InlineKeyboardMarkup([[
+                        InlineKeyboardButton("🔙 返回主選單", callback_data="menu:main")
+                    ]])
+                )

-        elif data == "menu_copy":
-            context.user_data['waiting_for'] = 'copy_product'
-            await query.edit_message_text(
-                "✍️ *生成文案*\n\n請輸入商品名稱：\n\n"
-                "例如：防曬乳、保濕面膜",
-                parse_mode='Markdown',
-                reply_markup=InlineKeyboardMarkup([[
-                    InlineKeyboardButton("🔙 返回主選單", callback_data="menu:main")
-                ]])
-            )
+            elif data == "menu_copy":
+                context.user_data['waiting_for'] = 'copy_product'
+                await query.edit_message_text(
+                    "✍️ *生成文案*\n\n請輸入商品名稱：\n\n"
+                    "例如：防曬乳、保濕面膜",
+                    parse_mode='Markdown',
+                    reply_markup=InlineKeyboardMarkup([[
+                        InlineKeyboardButton("🔙 返回主選單", callback_data="menu:main")
+                    ]])
+                )

-        elif data == "menu_keywords":
-            await query.edit_message_text(
-                "🏷️ *熱門關鍵字*\n\n請選擇分類：",
-                parse_mode='Markdown',
-                reply_markup=self._get_category_keyboard("keywords")
-            )
+            elif data == "menu_keywords":
+                await query.edit_message_text(
+                    "🏷️ *熱門關鍵字*\n\n請選擇分類：",
+                    parse_mode='Markdown',
+                    reply_markup=self._get_category_keyboard("keywords")
+                )

-        elif data == "menu_daily":
-            await query.edit_message_text("📰 正在載入今日趨勢摘要...")
-            await self._show_daily_summary(query)
+            elif data == "menu_daily":
+                await query.edit_message_text("📰 正在載入今日趨勢摘要...")
+                await self._show_daily_summary(query)

-        elif data == "menu_settings":
-            await self._show_settings(query)
+            elif data == "menu_settings":
+                await self._show_settings(query)

-        # ===== 趨勢分類按鈕 =====
-        elif data.startswith("trend_"):
-            category = data[6:]
-            await query.edit_message_text(f"🔄 正在查詢 {category} 趨勢...")
-            await self._show_trend_by_category(query, category)
+            # ===== 趨勢分類按鈕 =====
+            elif data.startswith("trend_"):
+                category = data[6:]
+                await query.edit_message_text(f"🔄 正在查詢 {category} 趨勢...")
+                await self._show_trend_by_category(query, category)

-        # ===== 關鍵字分類按鈕 =====
-        elif data.startswith("keywords_"):
-            category = data[9:]
-            await query.edit_message_text(f"🔄 正在查詢 {category} 熱門關鍵字...")
-            await self._show_keywords_by_category(query, category)
+            # ===== 關鍵字分類按鈕 =====
+            elif data.startswith("keywords_"):
+                category = data[9:]
+                await query.edit_message_text(f"🔄 正在查詢 {category} 熱門關鍵字...")
+                await self._show_keywords_by_category(query, category)

-        # ===== 設定按鈕 =====
-        elif data.startswith("settings_"):
-            await self._handle_settings_callback(query, data)
+            # ===== 設定按鈕 =====
+            elif data.startswith("settings_"):
+                await self._handle_settings_callback(query, data)

-        # ===== 降價決策按鈕（僅支援 momo:pa:xxx / momo:pr:xxx 格式）=====
-        elif data.startswith("momo:pa:"):
-            await self._handle_price_approve(query, data.split(":")[-1])
+            # ===== 降價決策按鈕（僅支援 momo:pa:xxx / momo:pr:xxx 格式）=====
+            elif data.startswith("momo:pa:"):
+                await self._handle_price_approve(query, data.split(":")[-1])

-        elif data.startswith("momo:pr:"):
-            await self._handle_price_reject(query, data.split(":")[-1])
+            elif data.startswith("momo:pr:"):
+                await self._handle_price_reject(query, data.split(":")[-1])

-        # ===== L3 運維決策按鈕（momo:ops:<action>:<task_name>）=====
-        elif data.startswith("momo:ops:"):
-            await self._handle_ops_callback(query, data)
+            # ===== L3 運維決策按鈕（momo:ops:<action>:<task_name>）=====
+            elif data.startswith("momo:ops:"):
+                await self._handle_ops_callback(query, data)

-        # ===== 批次定價決策（momo:bpa / bpr:<batch_id>）=====
-        elif data.startswith("momo:bpa:"):
-            await self._handle_batch_price_decision(query, data.split(":", 2)[-1], "approve")
+            # ===== 批次定價決策（momo:bpa / bpr:<batch_id>）=====
+            elif data.startswith("momo:bpa:"):
+                await self._handle_batch_price_decision(query, data.split(":", 2)[-1], "approve")

-        elif data.startswith("momo:bpr:"):
-            await self._handle_batch_price_decision(query, data.split(":", 2)[-1], "reject")
+            elif data.startswith("momo:bpr:"):
+                await self._handle_batch_price_decision(query, data.split(":", 2)[-1], "reject")

-        # ===== 事件忽略（momo:eig:<event_id>）=====
-        elif data.startswith("momo:eig:"):
-            await self._handle_event_ignore(query, data.split(":", 2)[-1])
+            # ===== 事件忽略（momo:eig:<event_id>）=====
+            elif data.startswith("momo:eig:"):
+                await self._handle_event_ignore(query, data.split(":", 2)[-1])

-        # ===== OpenClaw 指令按鈕（cmd:<cmd>:<arg>）=====
-        elif data.startswith("cmd:"):
-            parts = data[4:].split(":", 1)
-            cmd = parts[0]
-            arg = parts[1] if len(parts) > 1 else ""
-            chat_id = query.message.chat_id
-            import threading as _t
-            _t.Thread(
-                target=self._forward_cmd_to_openclaw,
-                args=(cmd, arg, chat_id),
-                daemon=True,
-            ).start()
+            # ===== AI 回應建議按鈕 =====
+            elif data == "momo:menu:main":
+                await query.edit_message_text(
+                    "👋 *MOMO 趨勢助手 Bot* — 請選擇功能類別：",
+                    parse_mode='Markdown',
+                    reply_markup=self._get_main_menu_keyboard()
+                )
+
+            elif data.startswith("momo:cmd:suggestion:"):
+                suggestion_text = data.split(":", 3)[-1].replace("_", " ")
+                await query.edit_message_text(f"⏳ 正在查詢：{suggestion_text}...")
+                chat_id = query.message.chat_id
+                import threading as _t
+                _t.Thread(
+                    target=self._forward_cmd_to_openclaw,
+                    args=("suggestion", suggestion_text, chat_id),
+                    daemon=True,
+                ).start()
+
+            # ===== 待輸入狀態按鈕（await:xxx）=====
+            elif data.startswith("await:"):
+                await self._handle_await_callback(query, data[6:], context)
+
+            # ===== OpenClaw 指令按鈕（cmd:<cmd>:<arg>）=====
+            elif data.startswith("cmd:"):
+                parts = data[4:].split(":", 1)
+                cmd = parts[0]
+                arg = parts[1] if len(parts) > 1 else ""
+                chat_id = query.message.chat_id
+                try:
+                    await query.edit_message_text("⏳ 正在處理，請稍候...")
+                except Exception:
+                    pass
+                import threading as _t
+                _t.Thread(
+                    target=self._forward_cmd_to_openclaw,
+                    args=(cmd, arg, chat_id),
+                    daemon=True,
+                ).start()
+
+        except Exception as _e:
+            logger.error(f"[handle_callback] error processing '{data}': {_e}", exc_info=True)
+            try:
+                await query.edit_message_text(
+                    "❌ 系統處理異常，請重試或返回主選單",
+                    reply_markup=InlineKeyboardMarkup([[
+                        InlineKeyboardButton("🔙 返回主選單", callback_data="menu:main")
+                    ]])
+                )
+            except Exception:
+                pass
+
+    async def _handle_await_callback(self, query, await_type: str, context):
+        """處理所有 await: 類型的按鈕，設定 waiting_for 狀態並提示用戶輸入"""
+        prompts = {
+            'date_range_sales': ('📅 業績查詢 — 指定日期區間', '請輸入日期區間\n格式：YYYY/MM/DD-YYYY/MM/DD\n例如：2026/04/01-2026/04/07'),
+            'date_top':         ('📅 商品排行 — 指定日期',     '請輸入日期\n格式：YYYY/MM/DD\n例如：2026/04/25'),
+            'date_competitor':  ('📅 競品報告 — 指定日期',     '請輸入日期\n格式：YYYY/MM/DD\n例如：2026/04/25'),
+            'date_ppt_daily':   ('📅 日報簡報 — 指定日期',     '請輸入日期\n格式：YYYY/MM/DD\n例如：2026/04/25'),
+            'date_ppt_monthly': ('📅 月報簡報 — 指定月份',     '請輸入月份\n格式：YYYY/MM\n例如：2026/04'),
+            'date_ppt_vendor':  ('📅 廠商簡報 — 指定月份',     '請輸入月份\n格式：YYYY/MM\n例如：2026/04'),
+            'date_trend_month': ('📅 月份趨勢 — 指定月份',     '請輸入月份\n格式：YYYY/MM\n例如：2026/04'),
+            'date_trend_year':  ('📅 年度趨勢 — 指定年份',     '請輸入年份\n格式：YYYY\n例如：2026'),
+            'date_trend_quarter':('📅 季度趨勢 — 指定季度',    '請輸入季度\n格式：YYYY/Q（Q=1~4）\n例如：2026/2'),
+            'goal_daily':       ('🎯 日目標設定',              '請輸入日目標金額（元，純數字）\n例如：500000'),
+            'goal_monthly':     ('🎯 月目標設定',              '請輸入月目標金額（元，純數字）\n例如：15000000'),
+            'goal_quarterly':   ('🎯 季目標設定',              '請輸入季目標金額（元，純數字）\n例如：45000000'),
+            'goal_half':        ('🎯 半年目標設定',            '請輸入半年目標金額（元，純數字）\n例如：90000000'),
+            'goal_yearly':      ('🎯 年目標設定',              '請輸入年目標金額（元，純數字）\n例如：180000000'),
+            'promo_range':      ('🎉 促銷效益追蹤',            '請輸入促銷日期區間\n格式：YYYY/MM/DD-YYYY/MM/DD\n例如：2026/04/01-2026/04/07'),
+            'search_compare':   ('🔍 競品關鍵字比價',          '請輸入商品關鍵字\n例如：防曬乳 SPF50'),
+        }
+        if await_type not in prompts:
+            await query.answer(f"未知類型：{await_type}", show_alert=True)
+            return
+        title, hint = prompts[await_type]
+        context.user_data['waiting_for'] = await_type
+        await query.edit_message_text(
+            f"*{title}*\n\n{hint}\n\n請直接在對話框輸入：",
+            parse_mode='Markdown',
+            reply_markup=InlineKeyboardMarkup([[
+                InlineKeyboardButton("❌ 取消", callback_data="menu:main")
+            ]])
+        )

    def _forward_cmd_to_openclaw(self, cmd: str, arg: str, chat_id: int):
        """轉發 cmd:* 指令到 OpenClaw Flask 內部 API"""
@@ -1290,6 +1363,11 @@ class TrendTelegramBot:
            await self._process_copy(update, text)
            return

+        if waiting_for and waiting_for.startswith(('date_', 'goal_', 'promo_', 'search_compare')):
+            context.user_data['waiting_for'] = None
+            await self._process_await_input(update, context, waiting_for, text)
+            return
+
        # Enhanced natural language processing with AI integration
        try:
            # Import AI integration
@@ -1312,12 +1390,12 @@ class TrendTelegramBot:
                    await self._handle_simple_ai_response(update, ai_result)
            else:
                # Fallback to enhanced keyword matching
-                await self._enhanced_keyword_matching(update, text)
-                
+                await self._enhanced_keyword_matching(update, context, text)
+
        except Exception as e:
            logger.error(f"[handle_message] AI processing error: {e}", exc_info=True)
            # Fallback to enhanced keyword matching
-            await self._enhanced_keyword_matching(update, text)
+            await self._enhanced_keyword_matching(update, context, text)

    async def _handle_complex_ai_response(self, update: Update, ai_result: dict):
        """Handle complex AI responses"""
@@ -1354,11 +1432,11 @@ class TrendTelegramBot:
                    keyboard.append([])
                keyboard[-1].append({
                    'text': suggestion,
-                    'callback_data': f'cmd:suggestion:{suggestion.lower().replace(" ", "_")}'
+                    'callback_data': f'momo:cmd:suggestion:{suggestion.lower().replace(" ", "_")}'
                })
-            
+
            # Add main menu button
-            keyboard.append([{'text': 'Main Menu', 'callback_data': 'menu:main'}])
+            keyboard.append([{'text': '主選單', 'callback_data': 'momo:menu:main'}])
            
            await update.message.reply_text(
                response_text,
@@ -1371,7 +1449,7 @@ class TrendTelegramBot:
                reply_markup=self._get_main_menu_keyboard()
            )

-    async def _enhanced_keyword_matching(self, update: Update, text: str):
+    async def _enhanced_keyword_matching(self, update: Update, context, text: str):
        """Enhanced keyword matching as fallback with Traditional Chinese responses"""
        import re
        from datetime import datetime, timedelta
@@ -1493,6 +1571,69 @@ class TrendTelegramBot:
            "Product analysis",
            "Market intelligence"
        ])
+
+    async def _process_await_input(self, update, context, await_type: str, text: str):
+        """處理所有 await: 狀態的用戶輸入，路由到對應 cmd"""
+        import re
+        chat_id = update.effective_chat.id
+
+        date_cmd_map = {
+            'date_range_sales': ('sales',      text.strip()),
+            'date_top':         ('top',        text.strip()),
+            'date_competitor':  ('ppt',        'competitor ' + text.strip()),
+            'date_ppt_daily':   ('ppt',        'daily ' + text.strip()),
+            'date_ppt_monthly': ('ppt',        'monthly ' + text.strip()),
+            'date_ppt_vendor':  ('ppt',        'vendor ' + text.strip()),
+            'date_trend_month': ('trend',      text.strip()),
+            'date_trend_year':  ('trend',      text.strip()),
+            'date_trend_quarter':('trend',     text.strip()),
+            'promo_range':      ('promo',      text.strip()),
+            'search_compare':   ('competitor', text.strip()),
+        }
+        goal_types = {
+            'goal_daily':     'daily',
+            'goal_monthly':   'monthly',
+            'goal_quarterly': 'quarterly',
+            'goal_half':      'half',
+            'goal_yearly':    'yearly',
+        }
+
+        if await_type in date_cmd_map:
+            cmd, arg = date_cmd_map[await_type]
+            await update.message.reply_text(f"⏳ 正在處理 `{text.strip()}`...", parse_mode='Markdown')
+            import threading as _t
+            _t.Thread(
+                target=self._forward_cmd_to_openclaw,
+                args=(cmd, arg, chat_id),
+                daemon=True,
+            ).start()
+        elif await_type in goal_types:
+            period = goal_types[await_type]
+            amount_str = re.sub(r'[^\d]', '', text)
+            if not amount_str:
+                await update.message.reply_text(
+                    "⚠️ 格式錯誤，請輸入純數字（例如：500000）",
+                    reply_markup=InlineKeyboardMarkup([[
+                        InlineKeyboardButton("🔙 返回目標管理", callback_data="menu:goals")
+                    ]])
+                )
+                return
+            await update.message.reply_text(
+                f"⏳ 正在設定{period}目標 {int(amount_str):,} 元...",
+                parse_mode='Markdown'
+            )
+            import threading as _t
+            _t.Thread(
+                target=self._forward_cmd_to_openclaw,
+                args=('goal', f'set:{period}:{amount_str}', chat_id),
+                daemon=True,
+            ).start()
+        else:
+            await update.message.reply_text(
+                "⚠️ 無法識別輸入類型，請重新選擇功能",
+                reply_markup=self._get_main_menu_keyboard()
+            )
+
    async def _process_search(self, update: Update, query: str):
        """處理搜尋請求"""
        await update.message.reply_text(f"🔍 正在搜尋「{query}」...")
--- a/telegram_ai_integration.py
+++ b/telegram_ai_integration.py
@@ -50,6 +50,11 @@ class TelegramAIIntegration:
            
            # L1: Semantic understanding (Hermes)
            l1_result = await self.orchestrator.handle_l1(event, session_id)
+            if not l1_result or l1_result.get("metadata", {}).get("source") != "hermes_llm":
+                logger.warning(
+                    f"[TelegramAIIntegration] Hermes LLM 未回應，走規則引擎降級"
+                    f"（session={session_id} source={( l1_result or {}).get('metadata', {}).get('source', 'none')}）"
+                )

            # Check if this is a complex query requiring L2 processing
            if self._is_complex_query(user_message, l1_result):
@@ -76,7 +81,11 @@ class TelegramAIIntegration:
                            },
                        )
                    except Exception as e:
-                        logger.warning(f"[TelegramAIIntegration] OpenClaw 策略師呼叫失敗: {e}")
+                        logger.error(
+                            f"[TelegramAIIntegration] OpenClaw 策略師呼叫失敗"
+                            f"（{type(e).__name__}: {e}）",
+                            exc_info=True,
+                        )
                        strategist_text = ""

                    response = self._format_complex_response(l1_result, l2_result, user_message)