Reorganize UI for external trading workflow with manual trade logging

- Restructure tabs to analysis-focused workflow:
  * Analysis Hub: AI analysis, risk management, manual trade logger
  * Daily Prep: Market summary, alerts, checklist, news, trading plan
  * Journal & Review: Trading journal, habit tracker, advanced analytics
  * Live Charts: Technical analysis with streaming charts

- Add ManualTradeLogger component for logging trades from MT5/TradingView/cTrader
- Remove execution-focused components (TradeControls, PortfolioTracker)
- Update XAU/USD price to realistic ,084.99
- Add indicator preferences and AI plan service
- Add comprehensive documentation on decision coverage and implementation

backend/app/models/models.py

@@ -169,3 +169,55 @@ class HabitTracker(Base):
     total_completions = Column(Integer, default=0)
     created_at = Column(DateTime(timezone=True), server_default=func.now())
     updated_at = Column(DateTime(timezone=True), onupdate=func.now())
+
+
+class UserIndicatorPreferences(Base):
+    """User's preferred technical indicators for analysis and AI plan generation"""
+    __tablename__ = "user_indicator_preferences"
+
+    id = Column(Integer, primary_key=True, index=True)
+    user_id = Column(String, nullable=True)
+    indicator_name = Column(String)  # SMA, EMA, RSI, MACD, BB, ATR, Stochastic, Fibonacci, VWAP, Pivot
+    enabled = Column(Boolean, default=True)
+    parameters = Column(JSON, nullable=True)  # Indicator-specific parameters (e.g., period, length)
+    priority = Column(Integer, default=0)  # Higher priority = more important in AI analysis
+    notes = Column(Text, nullable=True)  # User notes about why they prefer this indicator
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    updated_at = Column(DateTime(timezone=True), onupdate=func.now())
+
+
+class AIPlanGeneration(Base):
+    """AI-generated daily trading plans"""
+    __tablename__ = "ai_plan_generations"
+
+    id = Column(Integer, primary_key=True, index=True)
+    user_id = Column(String, nullable=True)
+    plan_date = Column(Date, default=func.current_date())
+    
+    # AI-generated plan details
+    market_bias = Column(String)  # BULLISH, BEARISH, NEUTRAL
+    confidence = Column(Float)  # 0-100
+    daily_target = Column(Float, nullable=True)
+    max_loss = Column(Float, nullable=True)
+    entry_zone_min = Column(Float, nullable=True)
+    entry_zone_max = Column(Float, nullable=True)
+    target_price = Column(Float, nullable=True)
+    stop_loss = Column(Float, nullable=True)
+    support_levels = Column(JSON, default=[])  # List of support prices
+    resistance_levels = Column(JSON, default=[])  # List of resistance prices
+    max_trades = Column(Integer, default=3)
+    trading_notes = Column(Text, nullable=True)  # AI-generated strategy notes
+    
+    # AI analysis metadata
+    indicators_used = Column(JSON, default=[])  # List of indicators used in analysis
+    reasoning = Column(Text, nullable=True)  # AI's reasoning for the plan
+    market_conditions = Column(JSON, nullable=True)  # Market data used in analysis
+    ai_model = Column(String, nullable=True)  # Model used for generation
+    
+    # User interaction
+    accepted = Column(Boolean, default=False)  # User accepted this plan
+    modified = Column(Boolean, default=False)  # User modified after generation
+    feedback = Column(Text, nullable=True)  # User feedback on plan accuracy
+    
+    created_at = Column(DateTime(timezone=True), server_default=func.now())
+    updated_at = Column(DateTime(timezone=True), onupdate=func.now())