fix: eliminate duplicate SQLAlchemy table definitions in ai_models.py

AgentContext/ActionPlan/ActionOutcome/AgentStrategyWeights were defined
in both ai_models.py and autoheal_models.py, causing:
  "Table 'agent_context' is already defined for this MetaData instance"
on every scheduler startup.

ai_models.py is now a pure re-export shim from autoheal_models.py.
autoheal_models.py remains the single source of truth (ADR-013).

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

database/ai_models.py

@@ -1,89 +1,125 @@
 # database/ai_models.py
-from sqlalchemy import Column, Integer, String, DateTime, Text, Float, ForeignKey, Index
-from sqlalchemy.orm import relationship
+# ⚠️  這四個 class 的原始定義已移至 autoheal_models.py（ADR-013 統一管理）。
+# 此檔僅作向後相容 re-export shim，不再重複定義 SQLAlchemy Table，
+# 以避免 "Table already defined for this MetaData instance" 衝突。
+from .autoheal_models import (  # noqa: F401
+    AgentContext,
+    ActionPlan,
+    ActionOutcome,
+    AgentStrategyWeights,
+)
+
+# AI history and template models
+from sqlalchemy import Column, Integer, String, DateTime, Text, Boolean, Float
 from database.models import Base
-from datetime import datetime, timezone
+from datetime import datetime
 
-# helper for default timestamps
-datetime_now = lambda: datetime.now(timezone.utc)
-
-
-class AgentContext(Base):
+class AIGenerationHistory(Base):
     """
-    Shared context table (replaces hardcoded chain), supporting multi-agent access and TTL.
-    Index: (session_id, agent_name, context_key) for fast cross-agent queries.
+    AI generation history tracking
     """
-    __tablename__ = 'agent_context'
+    __tablename__ = 'ai_generation_history'
 
     id = Column(Integer, primary_key=True, autoincrement=True)
-    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 string
-    created_at = Column(DateTime, default=datetime_now)
-    ttl_minutes = Column(Integer, default=60)
+    generation_type = Column(String(50), nullable=False)  # product_desc, marketing_copy, etc.
+    product_name = Column(String(200))
+    input_keywords = Column(Text)  # JSON string
+    input_trend_topic = Column(String(500))
+    output_content = Column(Text)
+    generation_duration = Column(Float)  # seconds
+    is_favorite = Column(Boolean, default=False)
+    is_used = Column(Boolean, default=False)
+    created_by = Column(String(100))
+    created_at = Column(DateTime, default=datetime.now)
 
-    __table_args__ = (
-        Index('idx_agent_context_session_key', 'session_id', 'agent_name', 'context_key'),
-        Index('idx_agent_context_session_ttl', 'session_id', 'created_at'),
-    )
+    def to_dict(self):
+        return {
+            'id': self.id,
+            'generation_type': self.generation_type,
+            'product_name': self.product_name,
+            'input_keywords': self.input_keywords,
+            'input_trend_topic': self.input_trend_topic,
+            'output_content': self.output_content,
+            'generation_duration': self.generation_duration,
+            'is_favorite': self.is_favorite,
+            'is_used': self.is_used,
+            'created_by': self.created_by,
+            'created_at': self.created_at.isoformat() if self.created_at else None
+        }
 
-
-class ActionPlan(Base):
+class AIPromptTemplate(Base):
     """
-    Action plan table (NemoTron output, awaiting review/execution tracking).
+    AI prompt templates
     """
-    __tablename__ = 'action_plans'
+    __tablename__ = 'ai_prompt_templates'
 
     id = Column(Integer, primary_key=True, autoincrement=True)
-    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 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
-    created_at = Column(DateTime, default=datetime_now)
-    executed_at = Column(DateTime, nullable=True)
+    name = Column(String(200), nullable=False)
+    description = Column(Text)
+    template_type = Column(String(50), nullable=False)  # product_desc, marketing_copy, etc.
+    prompt_content = Column(Text, nullable=False)
+    variables = Column(Text)  # JSON string of variable definitions
+    is_active = Column(Boolean, default=True)
+    is_system = Column(Boolean, default=False)
+    created_by = Column(String(100))
+    created_at = Column(DateTime, default=datetime.now)
+    updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)
 
-    __table_args__ = (
-        Index('idx_action_plan_sku_status', 'sku', 'status'),
-        Index('idx_action_plan_created', 'created_at'),
-    )
+    def to_dict(self):
+        return {
+            'id': self.id,
+            'name': self.name,
+            'description': self.description,
+            'template_type': self.template_type,
+            'prompt_content': self.prompt_content,
+            'variables': self.variables,
+            'is_active': self.is_active,
+            'is_system': self.is_system,
+            'created_by': self.created_by,
+            'created_at': self.created_at.isoformat() if self.created_at else None,
+            'updated_at': self.updated_at.isoformat() if self.updated_at else None
+        }
 
-
-class ActionOutcome(Base):
+class AIUsageTracking(Base):
     """
-    Action outcome tracking (closed-loop learning core).
+    AI usage tracking for analytics and billing
     """
-    __tablename__ = 'action_outcomes'
+    __tablename__ = 'ai_usage_tracking'
 
     id = Column(Integer, primary_key=True, autoincrement=True)
-    plan_id = Column(Integer, ForeignKey('action_plans.id'), nullable=False)
-    metric_type = Column(String(50), nullable=True)      # sales_7d / price_rank / conversion
-    before_val = Column(Float)
-    after_val = Column(Float)
-    measured_at = Column(DateTime)
-    verdict = Column(String(20))                         # effective / neutral / backfired
-    created_at = Column(DateTime, default=datetime_now)
+    user_id = Column(String(100))
+    session_id = Column(String(100))
+    service_type = Column(String(50), nullable=False)  # openai, ollama, etc.
+    model_name = Column(String(100))
+    prompt_tokens = Column(Integer, default=0)
+    completion_tokens = Column(Integer, default=0)
+    total_tokens = Column(Integer, default=0)
+    cost_usd = Column(Float, default=0.0)
+    request_type = Column(String(50))  # generation, analysis, etc.
+    status = Column(String(20), default='success')  # success, failed
+    error_message = Column(Text)
+    duration_ms = Column(Float)
+    created_at = Column(DateTime, default=datetime.now)
 
-    plan = relationship("ActionPlan", backref="outcomes")
+    def to_dict(self):
+        return {
+            'id': self.id,
+            'user_id': self.user_id,
+            'session_id': self.session_id,
+            'service_type': self.service_type,
+            'model_name': self.model_name,
+            'prompt_tokens': self.prompt_tokens,
+            'completion_tokens': self.completion_tokens,
+            'total_tokens': self.total_tokens,
+            'cost_usd': self.cost_usd,
+            'request_type': self.request_type,
+            'status': self.status,
+            'error_message': self.error_message,
+            'duration_ms': self.duration_ms,
+            'created_at': self.created_at.isoformat() if self.created_at else None
+        }
 
-
-class AgentStrategyWeights(Base):
-    """
-    Agent strategy weights (OpenClaw learning accumulation).
-    Index: strategy_key for fast updates/query.
-    """
-    __tablename__ = 'agent_strategy_weights'
-
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    strategy_key = Column(String(100), unique=True, nullable=False)  # e.g. price_cut_when_gap_gt_5pct
-    weight = Column(Float, default=1.0)
-    success_cnt = Column(Integer, default=0)
-    fail_cnt = Column(Integer, default=0)
-    updated_at = Column(DateTime, default=datetime_now)
-
-    __table_args__ = (
-        Index('idx_strategy_key', 'strategy_key'),
-    )
+__all__ = [
+    "AgentContext", "ActionPlan", "ActionOutcome", "AgentStrategyWeights",
+    "AIGenerationHistory", "AIPromptTemplate", "AIUsageTracking"
+]