Update helpers.py

helpers.py

@@ -1,63 +1,44 @@
-import os, re
+import os, re, json
 from datetime import datetime
 
 def safe_float_conversion(value, default=0.0):
     try:
-        if value is None:
-            return default
-        if isinstance(value, (int, float)):
-            return float(value)
+        if value is None: return default
+        if isinstance(value, (int, float)): return float(value)
         if isinstance(value, str):
-            cleaned = ''.join(character for character in value if character.isdigit() or character in '.-')
+            cleaned = ''.join(c for c in value if c.isdigit() or c in '.-')
             return float(cleaned) if cleaned else default
         return default
-    except (ValueError, TypeError):
-        return default
+    except (ValueError, TypeError): return default
 
 def _apply_patience_logic(decision, hold_minutes, trade_data, processed_data):
     action = decision.get('action')
-    
     if action == "CLOSE_TRADE" and hold_minutes < 20:
         current_price = processed_data.get('current_price', 0)
         entry_price = trade_data.get('entry_price', 0)
-        
-        try:
-            profit_loss_percent = ((current_price - entry_price) / entry_price) * 100
-        except (TypeError, ZeroDivisionError):
-            profit_loss_percent = 0
-        
+        try: profit_loss_percent = ((current_price - entry_price) / entry_price) * 100
+        except (TypeError, ZeroDivisionError): profit_loss_percent = 0
         if profit_loss_percent < 2:
-            print(f"Blocked premature selling! Only {hold_minutes:.1f} minutes held, PnL: {profit_loss_percent:.2f}%")
-            decision['action'] = "HOLD"
-            decision['reasoning'] = f"Patience Filter: Blocked premature sell. Held for {hold_minutes:.1f}m. Giving trade more time."
-            return decision
-    
+            decision.update({
+                'action': "HOLD",
+                'reasoning': f"Patience Filter: Blocked premature sell. Held for {hold_minutes:.1f}m. Giving trade more time."
+            })
     return decision
 
 def parse_json_from_response(response_text: str):
-    """استخراج JSON من رد النموذج"""
     try:
         json_match = re.search(r'```json\n(.*?)\n```', response_text, re.DOTALL)
-        if json_match:
-            return json_match.group(1).strip()
-        
+        if json_match: return json_match.group(1).strip()
         json_match = re.search(r'\{.*\}', response_text, re.DOTALL)
-        if json_match:
-            return json_match.group()
-        
-        return None
-    except Exception:
+        if json_match: return json_match.group()
         return None
+    except Exception: return None
 
 def validate_required_fields(data_dict: dict, required_fields: list) -> bool:
-    """التحقق من وجود الحقول المطلوبة"""
     return all(field in data_dict for field in required_fields)
 
 def format_technical_indicators(advanced_indicators):
-    """تنسيق المؤشرات الفنية"""
-    if not advanced_indicators:
-        return "No data for advanced indicators."
-    
+    if not advanced_indicators: return "No data for advanced indicators."
     summary = []
     for timeframe, indicators in advanced_indicators.items():
         if indicators:
@@ -65,20 +46,85 @@ def format_technical_indicators(advanced_indicators):
             if 'rsi' in indicators: parts.append(f"RSI: {indicators['rsi']:.2f}")
             if 'macd_hist' in indicators: parts.append(f"MACD Hist: {indicators['macd_hist']:.4f}")
             if 'volume_ratio' in indicators: parts.append(f"Volume: {indicators['volume_ratio']:.2f}x")
-            if parts:
-                summary.append(f"{timeframe}: {', '.join(parts)}")
-    
+            if parts: summary.append(f"{timeframe}: {', '.join(parts)}")
     return "\n".join(summary) if summary else "Insufficient indicator data."
 
 def format_strategy_scores(strategy_scores, recommended_strategy):
-    """تنسيق نتائج الاستراتيجيات"""
-    if not strategy_scores:
-        return "No strategy data available."
-    
+    if not strategy_scores: return "No strategy data available."
     summary = [f"Recommended Strategy: {recommended_strategy}"]
     sorted_scores = sorted(strategy_scores.items(), key=lambda item: item[1], reverse=True)
     for strategy, score in sorted_scores:
         score_display = f"{score:.3f}" if isinstance(score, (int, float)) else str(score)
         summary.append(f"   • {strategy}: {score_display}")
-    
-    return "\n".join(summary)
+    return "\n".join(summary)
+
+def local_analyze_opportunity(candidate_data):
+    score = candidate_data.get('enhanced_final_score', candidate_data.get('final_score', 0))
+    quality_warnings = candidate_data.get('quality_warnings', [])
+    rsi_critical = any('🚨 RSI CRITICAL' in warning for warning in quality_warnings)
+    rsi_warning = any('⚠️ RSI WARNING' in warning for warning in quality_warnings)
+    if rsi_critical:
+        return {
+            "action": "HOLD", "reasoning": "Local analysis: CRITICAL RSI levels - extreme overbought condition.",
+            "trade_type": "NONE", "stop_loss": None, "take_profit": None, "expected_target_minutes": 15,
+            "confidence_level": 0.1, "model_source": "local_safety_filter", "strategy": "GENERIC"
+        }
+    advanced_indicators = candidate_data.get('advanced_indicators', {})
+    if not advanced_indicators:
+        return {
+            "action": "HOLD", "reasoning": "Local analysis: Insufficient advanced indicator data.",
+            "trade_type": "NONE", "stop_loss": None, "take_profit": None, "expected_target_minutes": 15,
+            "confidence_level": 0.3, "model_source": "local", "strategy": "GENERIC"
+        }
+    action, reasoning, trade_type = "HOLD", "Local analysis: No strong buy signal based on enhanced rules.", "NONE"
+    stop_loss, take_profit, expected_minutes, confidence = None, None, 15, 0.3
+    five_minute_indicators = advanced_indicators.get('5m', {})
+    one_hour_indicators = advanced_indicators.get('1h', {})
+    buy_conditions = total_conditions = 0
+    if isinstance(score, (int, float)) and score > 0.70: buy_conditions += 1
+    total_conditions += 1
+    rsi_five_minute = five_minute_indicators.get('rsi', 50)
+    if 30 <= rsi_five_minute <= 65: buy_conditions += 1
+    total_conditions += 1
+    if five_minute_indicators.get('macd_hist', 0) > 0: buy_conditions += 1
+    total_conditions += 1
+    if (five_minute_indicators.get('ema_9', 0) > five_minute_indicators.get('ema_21', 0) and
+        one_hour_indicators.get('ema_9', 0) > one_hour_indicators.get('ema_21', 0)): buy_conditions += 1
+    total_conditions += 1
+    if five_minute_indicators.get('volume_ratio', 0) > 1.5: buy_conditions += 1
+    total_conditions += 1
+    confidence = buy_conditions / total_conditions if total_conditions > 0 else 0.3
+    if rsi_warning:
+        confidence *= 0.7
+        reasoning += " RSI warning applied."
+    if confidence >= 0.6:
+        action = "BUY"
+        current_price = candidate_data['current_price']
+        trade_type = "LONG"
+        stop_loss = current_price * 0.93 if rsi_warning else current_price * 0.95
+        take_profit = five_minute_indicators.get('bb_upper', current_price * 1.05) * 1.02
+        expected_minutes = 10 if confidence >= 0.8 else 18 if confidence >= 0.6 else 25
+        reasoning = f"Local enhanced analysis: Strong buy signal with {buy_conditions}/{total_conditions} conditions met. Confidence: {confidence:.2f}"
+        if rsi_warning: reasoning += " (RSI warning - trading with caution)"
+    return {
+        "action": action, "reasoning": reasoning, "trade_type": trade_type, "stop_loss": stop_loss,
+        "take_profit": take_profit, "expected_target_minutes": expected_minutes, "confidence_level": confidence,
+        "model_source": "local", "strategy": "GENERIC"
+    }
+
+def local_re_analyze_trade(trade_data, processed_data):
+    current_price = processed_data['current_price']
+    stop_loss = trade_data['stop_loss']
+    take_profit = trade_data['take_profit']
+    action = "HOLD"
+    reasoning = "Local re-analysis: No significant change to trigger an update or close."
+    if stop_loss and current_price <= stop_loss: 
+        action, reasoning = "CLOSE_TRADE", "Local re-analysis: Stop loss has been hit."
+    elif take_profit and current_price >= take_profit: 
+        action, reasoning = "CLOSE_TRADE", "Local re-analysis: Take profit has been hit."
+    strategy = trade_data.get('strategy', 'GENERIC')
+    if strategy == 'unknown': strategy = trade_data.get('decision_data', {}).get('strategy', 'GENERIC')
+    return {
+        "action": action, "reasoning": reasoning, "new_stop_loss": None, "new_take_profit": None,
+        "new_expected_minutes": None, "model_source": "local", "strategy": strategy
+    }