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/api/ai.py

@@ -1,7 +1,18 @@
-from fastapi import APIRouter, HTTPException
+from fastapi import APIRouter, HTTPException, Depends
+from sqlalchemy.orm import Session
+from typing import List, Optional
+
 from app.services.openrouter import openrouter_service
-from app.schemas.schemas import AIAnalysisRequest, AIAnalysisResponse
+from app.schemas.schemas import (
+    AIAnalysisRequest,
+    AIAnalysisResponse,
+    AIPlanGenerationRequest,
+    AIPlanGenerationResponse,
+    AIPlanFeedback
+)
 from app.services.decisions import log_decision
+from app.services.ai_plan_service import ai_plan_service
+from app.db.database import get_db
 
 router = APIRouter(prefix="/ai", tags=["AI Analysis"])
 
@@ -41,3 +52,68 @@ async def analyze_scenario(request: AIAnalysisRequest):
         raise HTTPException(
             status_code=500, detail=f"AI analysis failed: {str(e)}"
         )
+
+
+@router.post("/generate-plan", response_model=AIPlanGenerationResponse)
+async def generate_trading_plan(
+    request: AIPlanGenerationRequest,
+    user_id: Optional[str] = None,
+    db: Session = Depends(get_db)
+):
+    """
+    Generate a comprehensive daily trading plan using AI
+    
+    Uses user's indicator preferences and market data to create:
+    - Market bias (BULLISH/BEARISH/NEUTRAL)
+    - Entry zones and targets
+    - Support and resistance levels
+    - Risk management parameters
+    - Trading strategy notes
+    """
+    try:
+        plan = await ai_plan_service.generate_plan(db, request, user_id)
+        return plan
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=f"AI plan generation failed: {str(e)}"
+        )
+
+
+@router.get("/plans/history", response_model=List[AIPlanGenerationResponse])
+async def get_plan_history(
+    user_id: Optional[str] = None,
+    limit: int = 10,
+    db: Session = Depends(get_db)
+):
+    """Get historical AI-generated trading plans"""
+    try:
+        plans = await ai_plan_service.get_plan_history(db, user_id, limit)
+        return plans
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=f"Failed to fetch plan history: {str(e)}"
+        )
+
+
+@router.post("/plans/feedback")
+async def submit_plan_feedback(
+    feedback: AIPlanFeedback,
+    db: Session = Depends(get_db)
+):
+    """Submit feedback on an AI-generated plan"""
+    try:
+        plan = await ai_plan_service.submit_feedback(
+            db,
+            feedback.plan_id,
+            feedback.accepted,
+            feedback.modified,
+            feedback.feedback
+        )
+        return {"success": True, "message": "Feedback submitted successfully"}
+    except Exception as e:
+        raise HTTPException(
+            status_code=500,
+            detail=f"Failed to submit feedback: {str(e)}"
+        )