Update app.py

app.py

@@ -1,5 +1,5 @@
 # ==============================================================================
-# 🚀 app.py (V36.2 - GEM-Architect: Secured & Scheduled)
+# 🚀 app.py (V36.3 - GEM-Architect: Neural Dashboard)
 # ==============================================================================
 
 import os
@@ -43,7 +43,7 @@ try:
     from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer
     from learning_hub.adaptive_hub import AdaptiveHub
     from trade_manager import TradeManager
-    from periodic_tuner import AutoTunerScheduler  # ✅ Added Import
+    from periodic_tuner import AutoTunerScheduler
     
     # محاولة استيراد محرك الباكتست (اختياري للتشغيل عبر الواجهة)
     try:
@@ -69,7 +69,7 @@ whale_monitor: EnhancedWhaleMonitor = None
 news_fetcher: NewsFetcher = None
 senti_analyzer: SentimentIntensityAnalyzer = None
 sys_state: 'SystemState' = None
-scheduler: AutoTunerScheduler = None # ✅ Global reference
+scheduler: AutoTunerScheduler = None
 
 # ------------------------------------------------------------------------------
 # State Management
@@ -164,7 +164,6 @@ async def auto_pilot_loop():
             if trade_manager and len(trade_manager.open_positions) > 0:
                 wd_status = await trade_manager.ensure_active_guardians()
                 if "No active" not in wd_status:
-                    # تحديث السجلات بحالة الحارس فقط إذا لم تكن هناك دورة مسح نشطة
                     if not sys_state.cycle_running:
                         sys_state.last_cycle_logs = trade_manager.latest_guardian_log
                 continue 
@@ -191,7 +190,7 @@ async def auto_pilot_loop():
 async def lifespan(app: FastAPI):
     global r2, data_manager, ml_processor, adaptive_hub, trade_manager, whale_monitor, news_fetcher, senti_analyzer, sys_state, scheduler
     
-    logger.info("\n🚀 [System] Startup Sequence (Titan V36.2 - Cybernetic)...")
+    logger.info("\n🚀 [System] Startup Sequence (Titan V36.3 - Neural Dashboard)...")
     try:
         # 1. الخدمات الأساسية
         r2 = R2Service()
@@ -209,26 +208,21 @@ async def lifespan(app: FastAPI):
         data_manager.whale_monitor = whale_monitor
         
         # 3. العقل الاستراتيجي (Adaptive Hub)
-        # يتم تهيئته أولاً ليحقن الـ DNA في SystemLimits
         adaptive_hub = AdaptiveHub(r2_service=r2)
         await adaptive_hub.initialize()
 
         # 4. المعالج العصبي (Processor)
-        # سيقرأ SystemLimits المحدثة من AdaptiveHub
         ml_processor = MLProcessor(data_manager=data_manager)
         await ml_processor.initialize()
         
         # 5. مدير التنفيذ (Trade Manager)
         trade_manager = TradeManager(r2_service=r2, data_manager=data_manager, processor=ml_processor)
-        
-        # 🔥 الربط العصبي: حقن LearningHub داخل TradeManager
-        # هذا يغلق حلقة التعلم (Feedback Loop)
         trade_manager.learning_hub = adaptive_hub 
         
         await trade_manager.initialize_sentry_exchanges()
         await trade_manager.start_sentry_loops()
         
-        # 6. المجدول التلقائي (Auto-Tuner Scheduler) ✅ Added Logic
+        # 6. المجدول التلقائي (Auto-Tuner Scheduler)
         scheduler = AutoTunerScheduler(trade_manager)
         asyncio.create_task(scheduler.start_loop())
         logger.info("🕰️ [Scheduler] Auto-Tuner Background Task Started.")
@@ -268,7 +262,6 @@ async def _analyze_symbol_task(symbol: str) -> Dict[str, Any]:
         current_price = await data_manager.get_latest_price_async(symbol)
         raw_data = {'symbol': symbol, 'ohlcv': ohlcv_data, 'current_price': current_price, 'timestamp': time.time()}
         
-        # المعالجة (تستخدم الأوزان الديناميكية الحالية)
         res = await ml_processor.process_compound_signal(raw_data)
         if not res: return None
 
@@ -293,7 +286,6 @@ async def run_unified_cycle():
         # LAYER 0: Guardian & Portfolio Check
         await trade_manager.sync_internal_state_with_r2()
         
-        # عرض سريع للصفقات
         if len(trade_manager.open_positions) > 0:
             log_and_print(f"ℹ️ [Cycle] Active Positions: {len(trade_manager.open_positions)}")
             for sym, tr in trade_manager.open_positions.items():
@@ -303,7 +295,6 @@ async def run_unified_cycle():
                 log_and_print(f"   🔒 {sym}: {pnl:+.2f}%")
 
         # LAYER 1: Adaptive Screening
-        # يستخدم الآن النظام المتكيف (Bull/Bear/Range)
         current_regime = getattr(SystemLimits, 'CURRENT_REGIME', 'UNKNOWN')
         log_and_print(f"   [1/5] 🔍 L1 Screening (Regime: {current_regime})...")
         
@@ -319,7 +310,6 @@ async def run_unified_cycle():
         results = await asyncio.gather(*tasks)
         valid_l2 = [res for res in results if res is not None]
         
-        # ترتيب حسب النقاط النهائية (التي تم حسابها بالأوزان الديناميكية)
         semi_finalists = sorted(valid_l2, key=lambda x: x.get('enhanced_final_score', 0.0), reverse=True)[:10]
         
         if not semi_finalists:
@@ -392,7 +382,6 @@ async def run_unified_cycle():
         for sig in final_candidates:
             symbol = sig['symbol']
             
-            # Oracle Check (يستخدم العتبة الديناميكية)
             decision = await ml_processor.consult_oracle(sig)
             
             action = decision.get('action', 'WAIT')
@@ -448,21 +437,18 @@ async def run_unified_cycle():
         sys_state.set_cycle_end(error=e, logs=log_buffer.getvalue())
 
 # ------------------------------------------------------------------------------
-# Handlers (Reset Logic & Training)
+# Handlers
 # ------------------------------------------------------------------------------
 async def trigger_training_cycle():
-    """عرض الحالة الحالية للأوزان والاستراتيجية"""
     if adaptive_hub:
         status = adaptive_hub.get_status()
         return f"🤖 Adaptive System: {status}"
     return "⚠️ System not ready."
 
 async def trigger_strategic_backtest():
-    """تشغيل الباكتست الاستراتيجي في الخلفية (مع فحص الأمان)"""
     if not BACKTEST_AVAILABLE:
         return "⚠️ Backtest Engine not found."
     
-    # 🔒 Safety Check: Active Trades ✅ Added Logic
     if trade_manager and len(trade_manager.open_positions) > 0:
         return "⛔ Cannot start Backtest: Active trades exist! Close them first."
     
@@ -475,7 +461,6 @@ async def trigger_strategic_backtest():
         try:
             logger.info("🧪 [Manual Trigger] Starting Strategic Backtest...")
             await run_strategic_optimization_task()
-            # إعادة حقن الإعدادات الجديدة
             if adaptive_hub: 
                 await adaptive_hub.initialize()
             logger.info("✅ [Manual Trigger] Backtest Complete. DNA Updated.")
@@ -496,12 +481,9 @@ async def manual_close_current_trade():
 
 async def reset_history_handler():
     if trade_manager.open_positions: return "⚠️ Close active trades first."
-    
     current_state = await r2.get_portfolio_state_async()
     preserved_capital = current_state.get('current_capital_usd', INITIAL_CAPITAL)
-    
     await r2.reset_all_stats_async()
-    
     if trade_manager and trade_manager.smart_portfolio:
          sp = trade_manager.smart_portfolio
          sp.state["current_capital"] = preserved_capital 
@@ -510,12 +492,10 @@ async def reset_history_handler():
          sp.state["daily_net_pnl"] = 0.0
          sp.state["is_trading_halted"] = False
          await sp._save_state_to_r2()
-         
     return f"✅ History Cleared. Capital Preserved at ${preserved_capital:.2f}"
 
 async def reset_capital_handler():
     if trade_manager.open_positions: return "⚠️ Close active trades first."
-    
     if trade_manager and trade_manager.smart_portfolio:
          sp = trade_manager.smart_portfolio
          sp.state["current_capital"] = INITIAL_CAPITAL 
@@ -524,7 +504,6 @@ async def reset_capital_handler():
          sp.state["daily_net_pnl"] = 0.0
          sp.state["is_trading_halted"] = False
          await sp._save_state_to_r2()
-    
     return f"✅ Capital Reset to ${INITIAL_CAPITAL} (History Kept)"
 
 async def toggle_auto_pilot(enable):
@@ -545,7 +524,7 @@ async def check_live_pnl_and_status(selected_view="Dual-Core (Hybrid)"):
     wl_df_empty = pd.DataFrame(columns=["Coin", "Score"])
     
     if not sys_state.ready:
-        return "Initializing...", "...", empty_chart, "0.0", "0.0", "0.0", "0.0", "0.0%", wl_df_empty, "Loading...", "Loading...", "Checking..."
+        return "Initializing...", "...", empty_chart, "0.0", "0.0", "0.0", "0.0", "0.0%", wl_df_empty, "Loading...", "Loading...", "Loading..."
 
     try:
         sp = trade_manager.smart_portfolio
@@ -557,7 +536,6 @@ async def check_live_pnl_and_status(selected_view="Dual-Core (Hybrid)"):
         market_mood = sp.market_trend
         fg_index = sp.fear_greed_index
         
-        # معلومات الصفقة النشطة
         symbol = None; entry_p = 0.0; tp_p = 0.0; sl_p = 0.0; curr_p = 0.0; pnl_pct = 0.0; pnl_val_unrealized = 0.0
         active_trade_info = ""
         trade_dur_str = "--:--:--"
@@ -589,8 +567,6 @@ async def check_live_pnl_and_status(selected_view="Dual-Core (Hybrid)"):
         virtual_equity = equity + pnl_val_unrealized
         active_trade_pnl_val = pnl_val_unrealized
         active_pnl_color = "#00ff00" if active_trade_pnl_val >= 0 else "#ff0000"
-
-        # معلومات المحفظة
         portfolio = await r2.get_portfolio_state_async()
         total_t = portfolio.get('total_trades', 0)
         wins = portfolio.get('winning_trades', 0)
@@ -600,11 +576,8 @@ async def check_live_pnl_and_status(selected_view="Dual-Core (Hybrid)"):
         tot_loss = portfolio.get('total_loss_usd', 0.0)
         net_prof = tot_prof - tot_loss
         win_rate = (wins / total_t * 100) if total_t > 0 else 0.0
-
         color = "#00ff00" if daily_pnl >= 0 else "#ff0000"
         halt_status = "<span style='color:red; font-weight:bold;'>HALTED</span>" if is_halted else "<span style='color:#00ff00;'>ACTIVE</span>"
-        
-        # عرض الحالة الاستراتيجية الحالية
         current_regime = getattr(SystemLimits, 'CURRENT_REGIME', 'N/A')
 
         wallet_md = f"""
@@ -667,6 +640,57 @@ async def check_live_pnl_and_status(selected_view="Dual-Core (Hybrid)"):
         </div>
         """
 
+        # --- 🧠 Neural Cycles Status Construction ---
+        fast_learn_prog = "0/100"
+        if adaptive_hub:
+            if hasattr(adaptive_hub, 'get_learning_progress'):
+                fast_learn_prog = adaptive_hub.get_learning_progress()
+            else:
+                fast_learn_prog = "N/A"
+        
+        sch_w_time = "Wait"; sch_w_cnt = 0
+        sch_m_time = "Wait"; sch_m_cnt = 0
+        sch_running = False
+        
+        if scheduler:
+            metrics = scheduler.get_status_metrics()
+            sch_w_time = metrics["weekly_timer"]
+            sch_w_cnt = metrics["weekly_count"]
+            sch_m_time = metrics["monthly_timer"]
+            sch_m_cnt = metrics["monthly_count"]
+            sch_running = metrics["is_running"]
+
+        running_badge = "<span style='color:#00ff00; float:right; animation: blink 1s infinite;'>RUNNING ⚙️</span>" if sch_running else ""
+
+        neural_md = f"""
+        <div style='background-color: #1a1a1a; padding: 10px; border-radius: 8px; border: 1px solid #333; font-size: 12px; margin-top: 10px;'>
+            <div style='display:flex; justify-content:space-between; align-items:center; margin-bottom:5px;'>
+                <h3 style='margin:0; color:#00e5ff; font-size:14px;'>🧠 Neural Cycles</h3>
+                {running_badge}
+            </div>
+            <table style='width:100%; color:#ccc;'>
+                <tr style='border-bottom: 1px solid #333;'>
+                    <td style='padding:4px 0;'>⚡ Fast Learner:</td>
+                    <td style='text-align:right; color:#ffff00; font-weight:bold;'>{fast_learn_prog}</td>
+                    <td style='text-align:right; font-size:10px; color:#666;'>Trades</td>
+                </tr>
+                <tr style='border-bottom: 1px solid #333;'>
+                    <td style='padding:4px 0;'>📅 Weekly Tune:</td>
+                    <td style='text-align:right; color:#fff;'>{sch_w_time}</td>
+                    <td style='text-align:right; color:#00ff00;'>#{sch_w_cnt}</td>
+                </tr>
+                <tr>
+                    <td style='padding:4px 0;'>🗓️ Monthly Evo:</td>
+                    <td style='text-align:right; color:#fff;'>{sch_m_time}</td>
+                    <td style='text-align:right; color:#00ff00;'>#{sch_m_cnt}</td>
+                </tr>
+            </table>
+            <div style='margin-top:5px; font-size:10px; color:#555; text-align:center;'>
+                Adaptive DNA Active: {getattr(SystemLimits, 'CURRENT_REGIME', 'N/A')}
+            </div>
+        </div>
+        """
+
         wl_data = [[k, f"{v.get('final_total_score',0):.2f}"] for k, v in trade_manager.watchlist.items()]
         wl_df = pd.DataFrame(wl_data, columns=["Coin", "Score"])
 
@@ -679,12 +703,10 @@ async def check_live_pnl_and_status(selected_view="Dual-Core (Hybrid)"):
             if ohlcv:
                 df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume'])
                 df['datetime'] = pd.to_datetime(df['timestamp'], unit='ms')
-                
                 fig = go.Figure(data=[go.Candlestick(
                     x=df['datetime'], open=df['open'], high=df['high'], low=df['low'], close=df['close'],
                     increasing_line_color='#00ff00', decreasing_line_color='#ff0000', name=symbol
                 )])
-                
                 if entry_p > 0:
                     fig.add_hline(y=entry_p, line_dash="dash", line_color="white", annotation_text="ENTRY", annotation_position="top left")
                 if tp_p > 0:
@@ -706,7 +728,7 @@ async def check_live_pnl_and_status(selected_view="Dual-Core (Hybrid)"):
         if sys_state.training_running: train_status = "🧪 Backtest Running..."
 
         return (status_txt, status_line, fig, f"{curr_p:.6f}", f"{entry_p:.6f}", f"{tp_p:.6f}", f"{sl_p:.6f}",
-                f"{pnl_pct:+.2f}%", wl_df, wallet_md, history_md, train_status)
+                f"{pnl_pct:+.2f}%", wl_df, wallet_md, history_md, neural_md)
 
     except Exception:
         traceback.print_exc()
@@ -718,10 +740,10 @@ async def check_live_pnl_and_status(selected_view="Dual-Core (Hybrid)"):
 def create_gradio_ui():
     custom_css = ".gradio-container {background:#0b0f19} .dataframe {background:#1a1a1a!important} .html-box {min-height:180px}"
     
-    with gr.Blocks(title="Titan V36.2 (Cybernetic)") as demo:
+    with gr.Blocks(title="Titan V36.3 (Neural Dashboard)") as demo:
         gr.HTML(f"<style>{custom_css}</style>")
         
-        gr.Markdown("# 🚀 Titan V36.2 (Cybernetic: Regime-Adaptive)")
+        gr.Markdown("# 🚀 Titan V36.3 (Cybernetic: Neural Dashboard)")
         
         with gr.Row():
             with gr.Column(scale=3):
@@ -736,6 +758,9 @@ def create_gradio_ui():
 
             with gr.Column(scale=1):
                 wallet_out = gr.HTML(label="Smart Wallet", elem_classes="html-box")
+                # 🔥 إضافة المخرج الجديد
+                neural_out = gr.HTML(label="Neural Cycles", elem_classes="html-box")
+                
                 stats_dd = gr.Dropdown([
                     "Dual-Core (Hybrid)", 
                     "Hydra: Crash (Panic)", 
@@ -761,7 +786,6 @@ def create_gradio_ui():
                     btn_cap_reset = gr.Button("💰 Reset Capital", variant="secondary")
                     
                 status = gr.Markdown("Init...")
-                train_status = gr.Textbox(label="Adaptive DNA Status", interactive=False, value="Active")
                 alert = gr.Textbox(label="Alerts", interactive=False)
             
             with gr.Column(scale=3):
@@ -771,17 +795,14 @@ def create_gradio_ui():
         # Event Handlers
         btn_run.click(fn=run_cycle_from_gradio, outputs=alert)
         btn_close.click(fn=manual_close_current_trade, outputs=alert)
-        
         btn_history_reset.click(fn=reset_history_handler, outputs=alert)
         btn_cap_reset.click(fn=reset_capital_handler, outputs=alert)
-        
         btn_train.click(fn=trigger_training_cycle, outputs=alert)
-        btn_backtest.click(fn=trigger_strategic_backtest, outputs=alert) # زر الباكتست الجديد
-        
+        btn_backtest.click(fn=trigger_strategic_backtest, outputs=alert)
         auto_pilot.change(fn=toggle_auto_pilot, inputs=auto_pilot, outputs=alert)
         
         gr.Timer(3).tick(fn=check_live_pnl_and_status, inputs=stats_dd, 
-                         outputs=[logs, status, live_chart, t_price, t_entry, t_tp, t_sl, t_pnl, watchlist_out, wallet_out, history_out, train_status])
+                         outputs=[logs, status, live_chart, t_price, t_entry, t_tp, t_sl, t_pnl, watchlist_out, wallet_out, history_out, neural_out])
     return demo
 
 fast_api_server = FastAPI(lifespan=lifespan)