feat: Add Phase 4 advanced metrics and components
- Add advanced metrics dashboard with trade analytics - Add new trading components (EntryTypeAnalysis, MultiDayPositionTracker, NewsEventTracker, etc.) - Add strategy mode selector and trend confirmation - Add risk automation panel and slippage correlation analysis - Add daily trading plan enhancements with modal components - Add custom hooks (useApi, useLocalStorage, useAdvancedTradeMetrics) - Add broker service integration and trading API - Add test setup and vitest configuration - Include parquet data files for live market data - Add comprehensive documentation in docs/ folder
This commit is contained in:
Krikorios
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# Implementation Notes - Trading Companion Evolution
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**Comprehensive guide to the platform's evolution from simulator to professional trading companion**
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---
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## 🎯 Overview
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This document tracks the transformation of the Gold Trading Simulator into a **Trading Companion App** - a professional journaling and decision support tool for traders executing on external broker platforms (MT5, cTrader, OANDA, Interactive Brokers, etc.).
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---
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## 📊 Platform Architecture Evolution
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### Phase 1: Basic Simulator (Initial Release)
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- Simulated trading environment
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- Basic buy/sell functionality
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- Simple portfolio tracking
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- Demo price feeds
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### Phase 2: Advanced Analytics (Q3 2024)
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- 12+ technical indicators
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- Advanced risk management
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- Performance analytics
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- AI-powered analysis
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### Phase 3: Trading Companion (Q4 2024)
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- Manual trade logging
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- Trading journal system
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- Broker bridge integration
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- Daily planning workflow
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- Decision tracking
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- Real market data integration
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---
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## 🗄️ Database Schema Extensions
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### New Models Added
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#### 1. TradingPlan Model
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**Purpose**: Store daily/weekly trading plans (manual or AI-generated)
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**Fields**:
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```python
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class TradingPlan(Base):
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id: int
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user_id: int
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date: date
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plan_type: str # 'daily' | 'weekly'
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market_bias: str # 'BULLISH' | 'BEARISH' | 'NEUTRAL'
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bias_confidence: int # 0-100
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# Key levels
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support_levels: JSON # [2045.50, 2038.00, ...]
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resistance_levels: JSON # [2067.50, 2075.00, ...]
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# Trade setups
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entry_zones: JSON
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target_levels: JSON
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stop_loss_levels: JSON
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# Risk parameters
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max_trades: int
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risk_per_trade: str
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max_daily_loss: str
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# Metadata
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notes: Text
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plan_text: Text # Full AI-generated plan
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created_by_ai: bool
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ai_model: str # e.g., 'claude-3.5-sonnet'
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# Performance tracking
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trades_taken: int
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plan_followed: bool
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actual_pnl: Decimal
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# Relationships
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trades: List[ManualTrade] # Related trades
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```
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**Location**: `backend/app/models/models.py`
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**Migration**: `backend/migrate_indicator_ai_tables.py`
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#### 2. ManualTrade Model
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**Purpose**: Log trades executed on external broker platforms
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**Fields**:
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```python
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class ManualTrade(Base):
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id: int
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user_id: int
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trading_plan_id: int # Optional link to plan
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# Trade details
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symbol: str # 'XAUUSD'
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direction: str # 'LONG' | 'SHORT'
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entry_price: Decimal
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exit_price: Decimal
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quantity: Decimal
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# Timestamps
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entry_time: datetime
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exit_time: datetime
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# P&L
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gross_pnl: Decimal
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commission: Decimal
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net_pnl: Decimal
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# Broker info
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broker_name: str # 'MT5' | 'cTrader' | 'OANDA' | etc.
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broker_ticket_id: str # External trade ID
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# Documentation
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screenshot_url: str # Path to trade screenshot
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notes: Text
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# Analysis
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followed_plan: bool
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ai_recommendation: str # What AI suggested
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actual_action: str # What trader did
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# Relationships
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plan: TradingPlan
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journal_entry: JournalEntry
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```
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**Location**: `backend/app/models/models.py`
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#### 3. JournalEntry Model
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**Purpose**: Daily reflections and trading lessons
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**Fields**:
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```python
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class JournalEntry(Base):
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id: int
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user_id: int
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date: date
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# Emotional state
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mood: str # 'excellent' | 'good' | 'neutral' | 'poor'
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energy_level: int # 1-10
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stress_level: int # 1-10
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# Reflections
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what_went_well: Text
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what_to_improve: Text
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lessons_learned: Text
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# Market observations
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market_notes: Text
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key_events: JSON # Major news, economic data
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# Performance
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daily_pnl: Decimal
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trades_count: int
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wins: int
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losses: int
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# Relationships
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trades: List[ManualTrade]
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```
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**Location**: `backend/app/models/models.py`
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#### 4. DecisionLog Model
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**Purpose**: Track AI recommendations vs actual trader actions
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**Fields**:
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```python
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class DecisionLog(Base):
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id: int
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user_id: int
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timestamp: datetime
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# AI recommendation
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ai_suggestion: str # 'BUY' | 'SELL' | 'HOLD'
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ai_confidence: int # 0-100
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ai_reasoning: Text
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suggested_entry: Decimal
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suggested_stop: Decimal
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suggested_target: Decimal
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# Trader action
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action_taken: str # 'FOLLOWED' | 'IGNORED' | 'MODIFIED'
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actual_entry: Decimal
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actual_stop: Decimal
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actual_target: Decimal
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trader_reasoning: Text
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# Outcome
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trade_id: int # Links to ManualTrade if executed
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outcome: str # 'WIN' | 'LOSS' | 'BREAKEVEN' | 'NOT_TAKEN'
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outcome_pnl: Decimal
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# Analysis
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was_ai_correct: bool
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```
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**Location**: `backend/app/models/models.py`
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#### 5. WeeklyPlan Model
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**Purpose**: Weekly macro outlook and strategy
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**Fields**:
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```python
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class WeeklyPlan(Base):
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id: int
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user_id: int
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week_start: date
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# Macro outlook
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weekly_bias: str
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key_economic_events: JSON
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major_levels: JSON
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# Strategy
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weekly_targets: JSON
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risk_limits: str
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focus_setups: Text
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# Review
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weekly_review: Text
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actual_pnl: Decimal
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goals_met: bool
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# Relationships
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daily_plans: List[TradingPlan]
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```
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**Location**: `backend/app/models/models.py`
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---
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## 🔌 API Endpoints
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### Journal API (`/api/journal/*`)
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**Trading Plans**:
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- `POST /api/journal/plans` - Create new plan
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- `GET /api/journal/plans/today` - Get today's plan
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- `GET /api/journal/plans/date/{date}` - Get plan by specific date
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- `GET /api/journal/plans` - List recent plans (query params: limit, offset)
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- `PUT /api/journal/plans/{id}` - Update plan
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- `DELETE /api/journal/plans/{id}` - Delete plan
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**Manual Trades**:
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- `POST /api/journal/trades` - Log new trade
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- `GET /api/journal/trades` - List all trades (filterable)
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- `GET /api/journal/trades/{id}` - Get specific trade
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- `PUT /api/journal/trades/{id}` - Update trade
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- `DELETE /api/journal/trades/{id}` - Delete trade
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- `POST /api/journal/trades/bulk` - Import multiple trades (CSV/JSON)
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**Journal Entries**:
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- `POST /api/journal/entries` - Create journal entry
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- `GET /api/journal/entries/today` - Get today's entry
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- `GET /api/journal/entries/date/{date}` - Get entry by date
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- `GET /api/journal/entries` - List entries (date range)
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- `PUT /api/journal/entries/{id}` - Update entry
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**Decision Logs**:
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- `POST /api/journal/decisions` - Log AI recommendation + action
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- `GET /api/journal/decisions` - List decisions (filterable)
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- `GET /api/journal/decisions/analysis` - Analyze AI accuracy
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**Weekly Plans**:
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- `POST /api/journal/weekly-plans` - Create weekly plan
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- `GET /api/journal/weekly-plans/current` - Get current week plan
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- `GET /api/journal/weekly-plans` - List weekly plans
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**File**: `backend/app/api/journal.py`
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### Broker Bridge API (`/api/brokers/*`)
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**Purpose**: Integrate with external broker platforms
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**Endpoints**:
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- `GET /api/brokers/positions` - Fetch current positions from broker
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- `POST /api/brokers/sync` - Sync trades from broker to journal
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- `GET /api/brokers/supported` - List supported broker platforms
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- `POST /api/brokers/connect` - Connect to broker API
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- `GET /api/brokers/account` - Get broker account info
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**Supported Brokers**:
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- MetaTrader 5 (via MT5 Python API)
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- cTrader (via OpenAPI)
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- OANDA (via REST API)
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- Interactive Brokers (via TWS API)
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- Manual CSV import
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**File**: `backend/app/api/brokers.py`
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### Positions API Extensions (`/api/positions/*`)
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**New Endpoints**:
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- `GET /api/positions/metrics` - Advanced position metrics
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- Bollinger Bands guard rails (bb_upper, bb_lower, bb_signal)
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- Zero-lag LSMA trend (zlsma, zlsma_slope)
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- Chandelier Exit stops (long_stop, short_stop)
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- Candlestick pattern signals
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**File**: `backend/app/api/positions.py`
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---
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## 🎨 Frontend Components
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### New Components
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#### 1. ManualTradeLogger
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**Purpose**: Log trades from external broker
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**Features**:
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- Quick trade entry form
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- Screenshot upload
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- Broker platform selection
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- Link to daily plan
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- P&L calculation
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- Tags and notes
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**File**: `frontend/src/components/ManualTradeLogger.tsx`
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#### 2. IndicatorPreferences
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**Purpose**: Configure preferred indicators for AI analysis
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**Features**:
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- Select favorite indicators
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- Set custom parameters
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- Save preferences per user
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- Apply to AI plan generation
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**File**: `frontend/src/components/IndicatorPreferences.tsx`
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#### 3. BrokerBridgePanel
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**Purpose**: Connect to external broker APIs
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**Features**:
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- Broker selection
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- API credential configuration
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- Connection testing
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- Auto-sync settings
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- Position display
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**File**: `frontend/src/components/BrokerBridgePanel.tsx`
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#### 4. BrokerPositionsPanel
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**Purpose**: View live positions from connected broker
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**Features**:
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- Real-time position updates
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- P&L tracking
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- Risk metrics
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- Quick close actions
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**File**: `frontend/src/components/BrokerPositionsPanel.tsx`
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### Enhanced Components
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#### DailyTradingPlan (Enhanced)
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**New Features**:
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- AI-generated plan display
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- Manual plan creation
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- Plan adherence tracking
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- Performance comparison (planned vs actual)
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- Integration with ManualTradeLogger
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**File**: `frontend/src/components/DailyTradingPlan.tsx`
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#### SettingsPanel (Enhanced)
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**New Sections**:
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- Indicator preferences
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- Broker connections
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- Journal preferences
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- AI model selection
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**File**: `frontend/src/components/SettingsPanel.tsx`
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---
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## 🔧 Backend Services
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### New Services
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#### 1. AI Plan Service
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**Purpose**: Generate AI-powered daily trading plans
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**Features**:
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- User profile integration (capital, risk tolerance)
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- Technical indicator analysis
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- Multi-setup planning
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- Session timing recommendations
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- Contingency scenarios
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**File**: `backend/app/services/ai_plan_service.py`
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**Key Methods**:
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```python
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async def generate_plan(db, request, user_id):
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"""Generate comprehensive daily trading plan"""
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async def analyze_trader_profile(user_id):
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"""Analyze trader's historical performance"""
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async def save_plan_to_db(plan_data, user_id):
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"""Store plan in database"""
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```
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#### 2. AI Context Builder
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**Purpose**: Build rich context for AI prompts
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**Features**:
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- Position metrics calculation
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- Bollinger Bands with RSI guard rails
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- Zero-lag LSMA trend analysis
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- Chandelier Exit stop levels
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- Candlestick pattern detection
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|
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**File**: `backend/app/services/ai_context_builder.py`
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**Key Methods**:
|
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```python
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def build_context(price_data, indicators, positions):
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"""Build comprehensive AI context"""
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def calculate_position_metrics(current_price, positions):
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"""Calculate advanced position metrics"""
|
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def detect_candlestick_patterns(candles):
|
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"""Detect major candlestick patterns"""
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```
|
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|
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#### 3. Broker Bridge Service
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**Purpose**: Connect to external broker platforms
|
||||
|
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**Features**:
|
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- Multi-broker support
|
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- API abstraction layer
|
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- Trade synchronization
|
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- Position fetching
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- Account info retrieval
|
||||
|
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**File**: `backend/app/services/broker_bridge.py`
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|
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**Key Methods**:
|
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```python
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async def connect_broker(broker_type, credentials):
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"""Establish broker connection"""
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async def sync_trades(broker, start_date, end_date):
|
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"""Sync trades from broker to journal"""
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|
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async def fetch_positions(broker):
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"""Get current open positions"""
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```
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#### 4. Candlestick Pattern Service
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**Purpose**: Detect and analyze candlestick patterns
|
||||
|
||||
**Features**:
|
||||
- 20+ pattern detection (Doji, Hammer, Engulfing, etc.)
|
||||
- Pattern strength scoring
|
||||
- Bullish/bearish classification
|
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- Integration with AI context
|
||||
|
||||
**File**: `backend/app/services/candlestick_patterns.py`
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||||
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||||
**Patterns Supported**:
|
||||
- Doji (Standard, Gravestone, Dragonfly)
|
||||
- Hammer / Inverted Hammer
|
||||
- Shooting Star
|
||||
- Bullish / Bearish Engulfing
|
||||
- Morning / Evening Star
|
||||
- Tweezer Tops / Bottoms
|
||||
- Long Upper / Lower Shadows
|
||||
- Three White Soldiers / Black Crows
|
||||
|
||||
### Enhanced Services
|
||||
|
||||
#### OpenRouter Service (Enhanced)
|
||||
**New Features**:
|
||||
- Gold-specific prompts
|
||||
- Professional analyst persona
|
||||
- Comprehensive market structure analysis
|
||||
- Risk-aware recommendations
|
||||
- Empty data graceful handling
|
||||
|
||||
**File**: `backend/app/services/openrouter.py`
|
||||
|
||||
---
|
||||
|
||||
## 📊 Data Integration
|
||||
|
||||
### Real Market Data Sources
|
||||
|
||||
#### Current Implementations
|
||||
|
||||
**1. GoldPrice.org**
|
||||
- Live spot prices
|
||||
- No API key required
|
||||
- Updates every few seconds
|
||||
- Primary data source
|
||||
|
||||
**File**: `backend/app/services/metals/goldprice.py`
|
||||
|
||||
**2. yfinance (Yahoo Finance)**
|
||||
- Historical gold data (GC=F futures)
|
||||
- FX pairs (EURUSD, GBPUSD, etc.)
|
||||
- No API key required
|
||||
- Backup data source
|
||||
|
||||
**File**: `backend/app/services/metals/yfinance_provider.py`
|
||||
|
||||
**3. Yahoo Finance REST API**
|
||||
- Alternative to yfinance library
|
||||
- Direct HTTP requests
|
||||
- OHLCV data
|
||||
- Tertiary backup
|
||||
|
||||
**File**: `backend/app/services/metals/yahoo_fx.py`
|
||||
|
||||
**4. Alpha Vantage** (Optional)
|
||||
- High-quality historical data
|
||||
- Requires free API key
|
||||
- Limited to 5 requests/minute (free tier)
|
||||
- Quaternary backup
|
||||
|
||||
**File**: `backend/app/streaming/alpha_hub.py`
|
||||
|
||||
**5. BullionVault** (Optional)
|
||||
- Real-time spot prices
|
||||
- Bid/ask spreads
|
||||
- Requires scraping or API key
|
||||
|
||||
**File**: `backend/app/services/metals/bullionvault_service.py`
|
||||
|
||||
#### Data Provider Fallback Chain
|
||||
|
||||
```
|
||||
1. GoldPrice.org (live spot)
|
||||
↓ (if fails)
|
||||
2. yfinance (GC=F futures)
|
||||
↓ (if fails)
|
||||
3. Yahoo Finance REST
|
||||
↓ (if fails)
|
||||
4. Alpha Vantage (if API key set)
|
||||
↓ (if fails)
|
||||
5. Local Simulator (fallback)
|
||||
```
|
||||
|
||||
**Configuration**:
|
||||
```bash
|
||||
# backend/.env
|
||||
DATA_PROVIDER=auto # Auto-selects best available
|
||||
# Options: auto | goldprice | yfinance | yahoo | alphavantage | simulator
|
||||
|
||||
ALPHA_VANTAGE_API_KEY=your_key_here # Optional
|
||||
```
|
||||
|
||||
### Alternative Data Feeds
|
||||
|
||||
#### MetaTrader 5 Integration
|
||||
**Purpose**: Stream real-time data from MT5 terminal
|
||||
|
||||
**Requirements**:
|
||||
- MT5 terminal installed
|
||||
- MetaTrader5 Python package
|
||||
- Active broker connection
|
||||
|
||||
**Configuration**:
|
||||
```bash
|
||||
DATA_PROVIDER=metatrader
|
||||
|
||||
# Optional MT5 settings
|
||||
MT5_LOGIN=12345678
|
||||
MT5_PASSWORD=yourpassword
|
||||
MT5_SERVER=YourBroker-Live
|
||||
```
|
||||
|
||||
**File**: `backend/app/streaming/metatrader_feed.py`
|
||||
|
||||
#### CSV Replay Feed
|
||||
**Purpose**: Replay historical data from CSV/Parquet files
|
||||
|
||||
**Use Cases**:
|
||||
- Backtesting
|
||||
- Training
|
||||
- Offline development
|
||||
- Consistent testing data
|
||||
|
||||
**Configuration**:
|
||||
```bash
|
||||
DATA_PROVIDER=csv_replay
|
||||
|
||||
# Data location
|
||||
CSV_DATA_DIR=data/parquet/live/
|
||||
CSV_SYMBOL=XAUUSD
|
||||
CSV_TIMEFRAME=1m
|
||||
```
|
||||
|
||||
**File**: `backend/app/streaming/csv_feed.py`
|
||||
|
||||
**Data Format**:
|
||||
```
|
||||
data/parquet/live/XAUUSD_1m.parquet
|
||||
Columns: timestamp, open, high, low, close, volume
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 🚀 Migration Scripts
|
||||
|
||||
### Database Migrations
|
||||
|
||||
#### Indicator AI Tables Migration
|
||||
**Purpose**: Add indicator preferences and AI plan tables
|
||||
|
||||
**File**: `backend/migrate_indicator_ai_tables.py`
|
||||
|
||||
**Run**:
|
||||
```bash
|
||||
cd backend
|
||||
python migrate_indicator_ai_tables.py
|
||||
```
|
||||
|
||||
**Creates**:
|
||||
- `indicator_preferences` table
|
||||
- `trading_plans` table (if not exists)
|
||||
- Indexes for performance
|
||||
|
||||
#### Journal Tables Migration
|
||||
**Purpose**: Add trading journal tables
|
||||
|
||||
**File**: `backend/migrate_journal_tables.py`
|
||||
|
||||
**Run**:
|
||||
```bash
|
||||
cd backend
|
||||
python migrate_journal_tables.py
|
||||
```
|
||||
|
||||
**Creates**:
|
||||
- `trading_plans` table
|
||||
- `manual_trades` table
|
||||
- `journal_entries` table
|
||||
- `decision_logs` table
|
||||
- `weekly_plans` table
|
||||
- Foreign key relationships
|
||||
- Indexes
|
||||
|
||||
---
|
||||
|
||||
## 🎯 Usage Workflows
|
||||
|
||||
### Daily Workflow (Trading Companion Mode)
|
||||
|
||||
**Morning Routine**:
|
||||
1. Generate AI daily plan (`/api/ai/daily-plan`)
|
||||
2. Review plan in DailyTradingPlan component
|
||||
3. Adjust levels based on overnight news
|
||||
4. Set up alerts for key levels
|
||||
5. Open external broker platform (MT5, cTrader, etc.)
|
||||
|
||||
**During Trading**:
|
||||
6. Monitor live charts in platform
|
||||
7. Get AI scenario analysis for specific setups
|
||||
8. Execute trades on external broker
|
||||
9. Log trades via ManualTradeLogger component
|
||||
10. Link trades to daily plan
|
||||
|
||||
**End of Day**:
|
||||
11. Import trades from broker (auto-sync or CSV)
|
||||
12. Create journal entry with reflections
|
||||
13. Review plan adherence
|
||||
14. Calculate actual vs planned performance
|
||||
15. Note lessons learned
|
||||
|
||||
**Weekly Review**:
|
||||
16. Create weekly plan for next week
|
||||
17. Review all daily plans
|
||||
18. Analyze DecisionLog (AI accuracy)
|
||||
19. Identify patterns in performance
|
||||
20. Adjust strategy based on results
|
||||
|
||||
---
|
||||
|
||||
## 📈 Performance Tracking
|
||||
|
||||
### Key Metrics
|
||||
|
||||
**Plan Adherence**:
|
||||
- % of trades following daily plan
|
||||
- Deviation from planned entry/exit
|
||||
- Risk rule compliance
|
||||
|
||||
**AI Accuracy**:
|
||||
- AI recommendation vs actual outcome
|
||||
- Confidence calibration
|
||||
- Model comparison (Claude vs GPT-4)
|
||||
|
||||
**Trading Performance**:
|
||||
- Win rate
|
||||
- Profit factor
|
||||
- Sharpe ratio
|
||||
- Max drawdown
|
||||
- Average R-multiple
|
||||
|
||||
**Behavioral Analysis**:
|
||||
- Emotional state correlation with P&L
|
||||
- Best/worst trading times
|
||||
- Setup success rates
|
||||
- Revenge trading detection
|
||||
|
||||
---
|
||||
|
||||
## 🔐 Security Considerations
|
||||
|
||||
### API Key Management
|
||||
|
||||
**Never Commit**:
|
||||
```bash
|
||||
# Add to .gitignore
|
||||
backend/.env
|
||||
backend/app/config/secrets.py
|
||||
**/credentials.json
|
||||
```
|
||||
|
||||
**Environment Variables**:
|
||||
- `OPENROUTER_API_KEY` - AI service
|
||||
- `ALPHA_VANTAGE_API_KEY` - Market data (optional)
|
||||
- `MT5_PASSWORD` - Broker connection (if used)
|
||||
- `OANDA_API_KEY` - Broker API (if used)
|
||||
|
||||
**Broker Credentials**:
|
||||
- Store encrypted in database
|
||||
- Never log in plaintext
|
||||
- Use app-specific API keys (not account password)
|
||||
- Limit API permissions to read-only when possible
|
||||
|
||||
---
|
||||
|
||||
## 🧪 Testing
|
||||
|
||||
### Test Scripts
|
||||
|
||||
```bash
|
||||
# Test OpenRouter AI
|
||||
python backend/test_openrouter.py
|
||||
|
||||
# Test improved prompts
|
||||
python backend/test_improved_prompts.py
|
||||
|
||||
# Test position metrics with indicators
|
||||
python backend/tests/test_position_metrics_indicators.py
|
||||
|
||||
# Test Phase 1 API endpoints
|
||||
python backend/tests/test_phase1_api.py
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 📝 Future Enhancements
|
||||
|
||||
### Planned Features
|
||||
|
||||
- [ ] Multi-account support
|
||||
- [ ] Trade execution via broker API (not just logging)
|
||||
- [ ] Automated strategy execution based on AI signals
|
||||
- [ ] Social trading (share plans with community)
|
||||
- [ ] Mobile app for trade logging
|
||||
- [ ] Voice journaling
|
||||
- [ ] Video trade review playback
|
||||
- [ ] AI-powered pattern recognition training
|
||||
- [ ] Correlation analysis with other markets
|
||||
- [ ] Sentiment analysis from social media
|
||||
|
||||
---
|
||||
|
||||
## 📚 Related Documentation
|
||||
|
||||
- [AI Features](./AI_FEATURES.md) - AI capabilities and configuration
|
||||
- [Real Data Integration](./REAL_DATA_INTEGRATION.md) - Market data sources
|
||||
- [Enhancement Summary](./ENHANCEMENT_SUMMARY.md) - All features overview
|
||||
- [Setup Notes](./SETUP_NOTES.md) - Installation and configuration
|
||||
|
||||
---
|
||||
|
||||
**Status**: ✅ Phase 3 Complete
|
||||
**Version**: 3.0
|
||||
**Last Updated**: November 2025
|
||||
Reference in New Issue
Block a user