app.py

# app.py (Fully updated to Explorer-Sentry-Executor architecture)
import os
import traceback
import signal
import sys
import uvicorn
import asyncio
import json
import time
from contextlib import asynccontextmanager
from fastapi import FastAPI, HTTPException
from datetime import datetime

# استيراد الخدمات (بما في ذلك TradeManager المحدث)
try:
    from r2 import R2Service
    from LLM import LLMService
    from data_manager import DataManager
    from ml_engine.processor import MLProcessor 
    from learning_hub.hub_manager import LearningHubManager
    from sentiment_news import SentimentAnalyzer
    from trade_manager import TradeManager # (سيحتوي هذا الملف على منطق ccxt.pro)
    import state # (This is state.py)
    from helpers import safe_float_conversion, validate_candidate_data_enhanced
except ImportError as e:
    print(f"❌ خطأ في استيراد الوحدات: {e}")
    # (تأكد من إضافة ccxt-pro إلى requirements.txt)
    if "ccxtpro" in str(e):
        print("🚨 خطأ فادح: لم يتم العثور على 'ccxt.pro'. يرجى إضافتها إلى requirements.txt")
    sys.exit(1)

# المتغيرات العالمية
r2_service_global = None
data_manager_global = None
llm_service_global = None
learning_hub_global = None
trade_manager_global = None
sentiment_analyzer_global = None
symbol_whale_monitor_global = None

# (StateManager - لا تغيير)
class StateManager:
    def __init__(self):
        self.market_analysis_lock = asyncio.Lock()
        self.trade_analysis_lock = asyncio.Lock() 
        self.initialization_complete = False
        self.initialization_error = None
        self.services_initialized = {
            'r2_service': False, 'data_manager': False, 'llm_service': False,
            'learning_hub': False, 'trade_manager': False, 'sentiment_analyzer': False,
            'symbol_whale_monitor': False
        }

    async def wait_for_initialization(self, timeout=60):
        start_time = time.time()
        while not self.initialization_complete and (time.time() - start_time) < timeout:
            if self.initialization_error: raise Exception(f"فشل التهيئة: {self.initialization_error}")
            await asyncio.sleep(2)
        if not self.initialization_complete: raise Exception(f"انتهت مهلة التهيئة ({timeout} ثانية)")
        return self.initialization_complete

    def set_service_initialized(self, service_name):
        self.services_initialized[service_name] = True
        if all(self.services_initialized.values()):
            self.initialization_complete = True
            print("🎯 جميع الخدمات مهيأة بالكامل")

    def set_initialization_error(self, error):
        self.initialization_error = error
        print(f"❌ خطأ في التهيئة: {error}")

state_manager = StateManager()

async def initialize_services():
    """تهيئة جميع الخدمات بشكل منفصل"""
    global r2_service_global, data_manager_global, llm_service_global
    global learning_hub_global, trade_manager_global, sentiment_analyzer_global
    global symbol_whale_monitor_global
    try:
        print("🚀 بدء تهيئة الخدمات (بنية Sentry الجديدة)...")
        print("   🔄 تهيئة R2Service..."); r2_service_global = R2Service(); state_manager.set_service_initialized('r2_service'); print("   ✅ R2Service مهيأة")
        print("   🔄 جلب قاعدة بيانات العقود..."); contracts_database = await r2_service_global.load_contracts_db_async(); print(f"   ✅ تم تحميل {len(contracts_database)} عقد")
        
        print("   🔄 تهيئة مراقب الحيتان (Layer 1 Data)..."); 
        try:
            from whale_news_data import EnhancedWhaleMonitor
            symbol_whale_monitor_global = EnhancedWhaleMonitor(contracts_database, r2_service_global)
            state_manager.set_service_initialized('symbol_whale_monitor'); print("   ✅ مراقب الحيتان مهيأ")
        except Exception as e: print(f"   ⚠️ فشل تهيئة مراقب الحيتان: {e}"); symbol_whale_monitor_global = None
        
        print("   🔄 تهيئة DataManager (Layer 1 Data)..."); data_manager_global = DataManager(contracts_database, symbol_whale_monitor_global); await data_manager_global.initialize(); state_manager.set_service_initialized('data_manager'); print("   ✅ DataManager مهيأة")
        
        print("   🔄 تهيئة LLMService (Layer 1 Brain)..."); 
        llm_service_global = LLMService(); 
        llm_service_global.r2_service = r2_service_global; 
        
        print("   🔄 تهيئة محلل المشاعر (Layer 1 Data)..."); 
        sentiment_analyzer_global = SentimentAnalyzer(data_manager_global); 
        state_manager.set_service_initialized('sentiment_analyzer'); 
        print("   ✅ محلل المشاعر مهيأ")
        
        print("   🔄 تهيئة محور التعلم (Hub)..."); 
        learning_hub_global = LearningHubManager(
            r2_service=r2_service_global,
            llm_service=llm_service_global,
            data_manager=data_manager_global
        )
        await learning_hub_global.initialize()
        state_manager.set_service_initialized('learning_hub'); 
        print("   ✅ محور التعلم (Hub) مهيأ")

        llm_service_global.learning_hub = learning_hub_global
        state_manager.set_service_initialized('llm_service');
        print("   ✅ LLMService مربوط بمحور التعلم")

        # 🔴 --- START OF CHANGE --- 🔴
        print("   🔄 تهيئة مدير الصفقات (Layer 2 Sentry + Layer 3 Executor)..."); 
        trade_manager_global = TradeManager(
            r2_service=r2_service_global, 
            learning_hub=learning_hub_global,
            data_manager=data_manager_global, # (لا يزال مطلوباً لبعض بيانات الخروج)
            state_manager=state_manager
        )
        # (التهيئة الفعلية لـ ccxt.pro ستتم داخل TradeManager)
        await trade_manager_global.initialize_sentry_exchanges() 
        
        state_manager.set_service_initialized('trade_manager'); 
        print("   ✅ مدير الصفقات (Sentry/Executor) مهيأ")
        # 🔴 --- END OF CHANGE --- 🔴

        print("🎯 اكتملت تهيئة جميع الخدمات بنجاح"); return True
    except Exception as e: error_msg = f"فشل تهيئة الخدمات: {str(e)}"; print(f"❌ {error_msg}"); state_manager.set_initialization_error(error_msg); return False

# (monitor_market_async - لا تغيير)
async def monitor_market_async():
    """(لا تغيير) يراقب حالة السوق العامة (BTC)"""
    global data_manager_global, sentiment_analyzer_global
    try:
        if not await state_manager.wait_for_initialization(): print("❌ فشل تهيئة الخدمات - إيقاف مراقبة السوق"); return
        while True:
            try:
                async with state_manager.market_analysis_lock:
                    market_context = await sentiment_analyzer_global.get_market_sentiment()
                    if not market_context: state.MARKET_STATE_OK = True; await asyncio.sleep(60); continue
                    bitcoin_sentiment = market_context.get('btc_sentiment')
                    fear_greed_index = market_context.get('fear_and_greed_index')
                    should_halt_trading, halt_reason = False, ""
                    if bitcoin_sentiment == 'BEARISH' and (fear_greed_index is not None and fear_greed_index < 30): should_halt_trading, halt_reason = True, "ظروف سوق هابطة"
                    if should_halt_trading: state.MARKET_STATE_OK = False; await r2_service_global.save_system_logs_async({"market_halt": True, "reason": halt_reason})
                    else:
                        if not state.MARKET_STATE_OK: print("✅ تحسنت ظروف السوق. استئناف العمليات العادية.")
                        state.MARKET_STATE_OK = True
                await asyncio.sleep(60)
            except Exception as error: print(f"❌ خطأ أثناء مراقبة السوق: {error}"); state.MARKET_STATE_OK = True; await asyncio.sleep(60)
    except Exception as e: print(f"❌ فشل تشغيل مراقبة السوق: {e}")

# (run_periodic_distillation - لا تغيير)
async def run_periodic_distillation():
    """(لا تغيير) يشغل عملية التقطير للتعلم السريع"""
    print("background task: Periodic Distillation (Curator) scheduled.")
    await asyncio.sleep(300) 
    
    while True:
        try:
            if not await state_manager.wait_for_initialization():
                await asyncio.sleep(60)
                continue
                
            print("🔄 [Scheduler] Running periodic distillation check...")
            await learning_hub_global.run_distillation_check()
            await asyncio.sleep(6 * 60 * 60) 
            
        except Exception as e:
            print(f"❌ [Scheduler] Error in periodic distillation task: {e}")
            traceback.print_exc()
            await asyncio.sleep(60 * 60)

# (process_batch_parallel - لا تغيير)
async def process_batch_parallel(batch, ml_processor, batch_num, total_batches, preloaded_whale_data):
    """(لا تغيير) معالج الدفعات لـ Layer 1"""
    try:
        batch_tasks = []
        for symbol_data in batch:
            task = asyncio.create_task(ml_processor.process_multiple_symbols_parallel([symbol_data], preloaded_whale_data)) 
            batch_tasks.append(task)
        
        batch_results_list_of_lists = await asyncio.gather(*batch_tasks, return_exceptions=True)
        
        successful_results = []
        low_score_results = []
        failed_results = []

        for i, result_list in enumerate(batch_results_list_of_lists):
            symbol = batch[i].get('symbol', 'unknown') 
            if isinstance(result_list, Exception):
                 failed_results.append({"symbol": symbol, "error": f"Task Execution Error: {str(result_list)}"})
                 continue
            
            if result_list:
                result = result_list[0] 
                if isinstance(result, dict): 
                    if result.get('enhanced_final_score', 0) > 0.4:
                        successful_results.append(result)
                    else:
                        low_score_results.append(result)
                else:
                     failed_results.append({"symbol": symbol, "error": f"ML processor returned invalid type: {type(result)}"})
            else:
                 failed_results.append({"symbol": symbol, "error": "ML processing returned None or empty list"})
        
        return {'success': successful_results, 'low_score': low_score_results, 'failures': failed_results}
        
    except Exception as error:
        print(f"❌ [Consumer] Error processing batch {batch_num}: {error}")
        return {'success': [], 'low_score': [], 'failures': []}


# 🔴 --- START OF CHANGE --- 🔴
async def run_3_layer_analysis_explorer() -> List[Dict[str, Any]]:
    """
    (معدل) - هذا هو "المستكشف" (Layer 1).
    لم يعد يتخذ قرارات، بل ينشئ "قائمة مراقبة" (Watchlist) للحارس (Sentry).
    """
    
    layer1_candidates = []
    layer2_candidates = []
    final_layer2_candidates = []
    watchlist_candidates = [] # (النتيجة الجديدة)
    preloaded_whale_data_dict = {} 
    
    try:
        print("🎯 Starting Explorer Analysis (Layer 1)...")
        
        if not await state_manager.wait_for_initialization(): 
            print("❌ Services not fully initialized (Explorer)"); return []

        # (Layer 1 - DataManager Screening - لا تغيير)
        print("\n🔍 Layer 1.1: Rapid Screening (data_manager)...")
        layer1_candidates = await data_manager_global.layer1_rapid_screening()
        if not layer1_candidates: print("❌ No candidates found in Layer 1.1"); return []
        print(f"✅ Selected {len(layer1_candidates)} symbols for Layer 1.2")
        layer1_symbols = [c['symbol'] for c in layer1_candidates]

        # (Layer 1.5 - Whale Fetch - لا تغيير)
        start_whale_fetch = time.time()
        print(f"\n🐋 Layer 1.2: Fetching whale data for {len(layer1_symbols)} symbols (async)...")
        async def fetch_whale_data_task(symbols, results_dict):
            # (منطق جلب بيانات الحيتان - لا تغيير)
            WHALE_FETCH_CONCURRENCY = 3 
            semaphore = asyncio.Semaphore(WHALE_FETCH_CONCURRENCY)
            tasks = []
            async def get_data_with_semaphore(symbol):
                async with semaphore:
                    try:
                        data = await data_manager_global.get_whale_data_for_symbol(symbol)
                        if data: results_dict[symbol] = data
                    except Exception as e:
                        results_dict[symbol] = {'data_available': False, 'error': str(e)} 
            for symbol in symbols: tasks.append(asyncio.create_task(get_data_with_semaphore(symbol)))
            await asyncio.gather(*tasks) 
        whale_fetcher_task = asyncio.create_task(fetch_whale_data_task(layer1_symbols, preloaded_whale_data_dict))

        # (Producer/Consumer Setup - لا تغيير)
        DATA_QUEUE_MAX_SIZE = 2
        ohlcv_data_queue = asyncio.Queue(maxsize=DATA_QUEUE_MAX_SIZE)
        ml_results_list = []
        market_context = await data_manager_global.get_market_context_async()
        
        # (MLProcessor - لا تغيير، لا يزال يستخدم Learning Hub للأوزان)
        ml_processor = MLProcessor(market_context, data_manager_global, learning_hub_global)
        
        batch_size = 15 
        total_batches = (len(layer1_candidates) + batch_size - 1) // batch_size
        
        # (ML Consumer Task - لا تغيير)
        async def ml_consumer_task(queue: asyncio.Queue, results_list: list, whale_data_store: dict):
            batch_num = 0
            while True:
                try:
                    batch_data = await queue.get()
                    if batch_data is None: queue.task_done(); break
                    batch_num += 1
                    batch_results_dict = await process_batch_parallel(
                        batch_data, ml_processor, batch_num, total_batches, whale_data_store
                    )
                    results_list.append(batch_results_dict)
                    queue.task_done()
                except Exception as e: print(f"❌ [ML Consumer] Fatal Error: {e}"); traceback.print_exc(); queue.task_done() 

        # (Run Producer/Consumer - لا تغيير)
        consumer_task = asyncio.create_task(ml_consumer_task(ohlcv_data_queue, ml_results_list, preloaded_whale_data_dict))
        producer_task = asyncio.create_task(data_manager_global.stream_ohlcv_data(layer1_symbols, ohlcv_data_queue))
        await producer_task;
        await ohlcv_data_queue.put(None) 
        await ohlcv_data_queue.join() 
        await consumer_task;
        
        # (Wait for Whale Fetch - لا تغيير)
        WHALE_FETCH_TIMEOUT_SECONDS = 180 
        try:
            await asyncio.wait_for(whale_fetcher_task, timeout=WHALE_FETCH_TIMEOUT_SECONDS)
        except asyncio.TimeoutError:
            print(f"   ⚠️ Whale fetch timeout ({WHALE_FETCH_TIMEOUT_SECONDS}s)!")
        except Exception as whale_task_err:
             print(f"   ❌ Whale fetch task error: {whale_task_err}")

        # (Aggregate Results - لا تغيير)
        print("🔄 Aggregating all ML (Layer 1.3) results...")
        for batch_result in ml_results_list:
            for success_item in batch_result['success']:
                symbol = success_item['symbol']
                l1_data = next((c for c in layer1_candidates if c['symbol'] == symbol), None)
                if l1_data:
                    success_item['reasons_for_candidacy'] = l1_data.get('reasons', [])
                    success_item['layer1_score'] = l1_data.get('layer1_score', 0)
                if symbol in preloaded_whale_data_dict: success_item['whale_data'] = preloaded_whale_data_dict[symbol]
                elif 'whale_data' not in success_item: success_item['whale_data'] = {'data_available': False, 'reason': 'Fetch timed out or failed'}
                layer2_candidates.append(success_item)
        
        if not layer2_candidates: print("❌ No candidates found in Layer 1.3"); return []
        
        # (Sort and Filter - لا تغيير)
        layer2_candidates.sort(key=lambda x: x.get('enhanced_final_score', 0), reverse=True)
        target_count = min(10, len(layer2_candidates))
        final_layer2_candidates = layer2_candidates[:target_count]
        
        # (Layer 1.4: Advanced MC - لا تغيير)
        print(f"\n🔬 Layer 1.4: Running Advanced MC (GARCH+LGBM) on top {len(final_layer2_candidates)} candidates...")
        advanced_mc_analyzer = ml_processor.monte_carlo_analyzer
        updated_candidates_for_llm = []
        for candidate in final_layer2_candidates:
            symbol = candidate.get('symbol', 'UNKNOWN')
            try:
                advanced_mc_results = await advanced_mc_analyzer.generate_1h_distribution_advanced(
                    candidate.get('ohlcv')
                )
                if advanced_mc_results and advanced_mc_results.get('simulation_model') == 'Phase2_GARCH_LGBM':
                    candidate['monte_carlo_distribution'] = advanced_mc_results
                    candidate['monte_carlo_probability'] = advanced_mc_results.get('probability_of_gain', 0)
                    candidate['advanced_mc_run'] = True
                else:
                    candidate['advanced_mc_run'] = False
                updated_candidates_for_llm.append(candidate)
            except Exception as e:
                print(f"   ❌ [Advanced MC] {symbol} - Error: {e}. Using Phase 1 results.")
                candidate['advanced_mc_run'] = False
                updated_candidates_for_llm.append(candidate)
        final_layer2_candidates = updated_candidates_for_llm

        await r2_service_global.save_candidates_async(final_layer2_candidates)

        # (Layer 1.5 - LLM Strategic Analysis)
        print("\n🧠 Layer 1.5: LLM Strategic Analysis (Explorer Brain)...")
        for candidate in final_layer2_candidates: 
            try:
                symbol = candidate['symbol']
                ohlcv_data = candidate.get('ohlcv'); 
                if not ohlcv_data: continue
                candidate['raw_ohlcv'] = ohlcv_data
                total_candles = sum(len(data) for data in ohlcv_data.values()) if ohlcv_data else 0
                if total_candles < 30: continue
                
                candidate['sentiment_data'] = await data_manager_global.get_market_context_async() 
                
                # (استدعاء النموذج الضخم - سيتم تعديل النموذج ليعطي "WATCH" بدلاً من "BUY")
                llm_analysis = await llm_service_global.get_trading_decision(candidate) 
                
                # (تغيير: نحن نبحث عن "WATCH" بدلاً من "BUY")
                if llm_analysis and llm_analysis.get('action') in ['WATCH']: 
                    strategy_to_watch = llm_analysis.get('strategy', 'GENERIC')
                    confidence = llm_analysis.get('confidence_level', 0)
                    
                    # (هذه هي البيانات التي سيستخدمها "الحارس" (Sentry))
                    watchlist_entry = {
                        'symbol': symbol, 
                        'strategy_hint': strategy_to_watch,
                        'explorer_score': candidate.get('enhanced_final_score', 0),
                        'llm_confidence': confidence,
                        'analysis_timestamp': datetime.now().isoformat(),
                        'llm_decision_context': candidate # (سياق القرار الكامل للـ Sentry)
                    }
                    watchlist_candidates.append(watchlist_entry)
                    print(f"   ✅ {symbol}: Added to Sentry Watchlist (Strategy: {strategy_to_watch} | Conf: {confidence:.2f})")
                else: 
                    action = llm_analysis.get('action', 'NO_DECISION') if llm_analysis else 'NO_RESPONSE'; 
                    print(f"   ⚠️ {symbol}: Not recommended by LLM for watching ({action})")
            except Exception as e: print(f"❌ Error in LLM analysis for {candidate.get('symbol')}: {e}"); traceback.print_exc(); continue

        if watchlist_candidates:
            # (ترتيب قائمة المراقبة حسب الثقة والدرجة)
            watchlist_candidates.sort(key=lambda x: (x['llm_confidence'] + x['explorer_score']) / 2, reverse=True)
        
        if not watchlist_candidates: 
            print("❌ Explorer analysis complete: No suitable candidates for Sentry Watchlist.")
            return []
            
        # (إرجاع أفضل 5 مرشحين فقط للحارس للتركيز)
        top_watchlist = watchlist_candidates[:5]
        print(f"✅ Explorer analysis complete. Sending {len(top_watchlist)} candidates to Sentry.")
        return top_watchlist
        
    except Exception as error:
        print(f"❌ Fatal error in Explorer (Layer 1) system: {error}"); traceback.print_exc()
        return []
# 🔴 --- END OF CHANGE --- 🔴


async def re_analyze_open_trade_async(trade_data):
    """(لا تغيير) - هذا لا يزال تحليلاً استراتيجياً (Explorer)"""
    symbol = trade_data.get('symbol')
    try:
        async with state_manager.trade_analysis_lock:
            print(f"🔄 [Re-Analyze] Starting strategic analysis for {symbol}...")
            market_context = await data_manager_global.get_market_context_async()
            ohlcv_data_list = []
            temp_queue = asyncio.Queue()
            await data_manager_global.stream_ohlcv_data([symbol], temp_queue)
            while True:
                try:
                    batch = await asyncio.wait_for(temp_queue.get(), timeout=1.0) 
                    if batch is None: temp_queue.task_done(); break
                    ohlcv_data_list.extend(batch)
                    temp_queue.task_done()
                except asyncio.TimeoutError:
                    if temp_queue.empty(): break 
                except Exception: break 

            if not ohlcv_data_list: print(f"⚠️ Failed to get re-analysis data for {symbol}"); return None
            ohlcv_data = ohlcv_data_list[0]
            
            l1_data = await data_manager_global._get_detailed_symbol_data(symbol)
            if l1_data: ohlcv_data.update(l1_data); ohlcv_data['reasons_for_candidacy'] = ['re-analysis']
            
            re_analysis_whale_data = await data_manager_global.get_whale_data_for_symbol(symbol)

            ml_processor = MLProcessor(market_context, data_manager_global, learning_hub_global)
            
            print(f"🔄 [Re-Analyze] Using Advanced MC (Phase 2+3) for {symbol}...")
            advanced_mc_results = await ml_processor.monte_carlo_analyzer.generate_1h_distribution_advanced(
                ohlcv_data.get('ohlcv')
            )
            
            processed_data = await ml_processor.process_and_score_symbol_enhanced(ohlcv_data, {symbol: re_analysis_whale_data} if re_analysis_whale_data else {})
            if not processed_data: return None
            
            if advanced_mc_results:
                processed_data['monte_carlo_distribution'] = advanced_mc_results
                processed_data['monte_carlo_probability'] = advanced_mc_results.get('probability_of_gain', 0)
            
            processed_data['raw_ohlcv'] = ohlcv_data.get('raw_ohlcv') or ohlcv_data.get('ohlcv')
            processed_data['ohlcv'] = processed_data['raw_ohlcv']
            processed_data['sentiment_data'] = market_context
            
            re_analysis_decision = await llm_service_global.re_analyze_trade_async(trade_data, processed_data)
            
            if re_analysis_decision:
                await r2_service_global.save_system_logs_async({ "trade_reanalyzed": True, "symbol": symbol, "action": re_analysis_decision.get('action'), 'strategy': re_analysis_decision.get('strategy', 'GENERIC') })
                print(f"✅ [Re-Analyze] Strategic analysis complete for {symbol}. Decision: {re_analysis_decision.get('action')}")
                return {"symbol": symbol, "decision": re_analysis_decision, "current_price": processed_data.get('current_price')}
            else: return None
    except Exception as error: await r2_service_global.save_system_logs_async({ "reanalysis_error": True, "symbol": symbol, "error": str(error) }); print(f"❌ Error in re_analyze_open_trade_async for {symbol}: {error}"); traceback.print_exc(); return None


# 🔴 --- START OF CHANGE --- 🔴
async def run_bot_cycle_async():
    """
    (معدل) - دورة البوت الرئيسية (المستكشف)
    """
    try:
        if not await state_manager.wait_for_initialization(): 
            print("❌ Services not fully initialized - skipping cycle"); return
            
        print("🔄 Starting Explorer cycle (Layer 1)..."); 
        await r2_service_global.save_system_logs_async({"explorer_cycle_started": True})
        
        if not r2_service_global.acquire_lock(): 
            print("❌ Failed to acquire lock - skipping cycle"); return
        
        open_trades = [] 
        try:
            open_trades = await trade_manager_global.get_open_trades(); 
            print(f"📋 Open trades: {len(open_trades)}")
            
            # 1. (لا تغيير) التحليل الاستراتيجي للصفقات المفتوحة
            if open_trades:
                now = datetime.now()
                trades_to_reanalyze = [t for t in open_trades if now >= datetime.fromisoformat(t.get('expected_target_time', now.isoformat()))]
                if trades_to_reanalyze:
                    print(f"🔄 (Explorer) Re-analyzing {len(trades_to_reanalyze)} trades strategically...")
                    reanalysis_results = await asyncio.gather(*[re_analyze_open_trade_async(trade) for trade in trades_to_reanalyze], return_exceptions=True)
                    for i, result in enumerate(reanalysis_results):
                         trade = trades_to_reanalyze[i] 
                         if isinstance(result, Exception): print(f"   ❌ Re-analysis failed for {trade.get('symbol')}: {result}")
                         # (ملاحظة: Sentry/Executor هو الذي سيقرر الإغلاق اللحظي، هذا فقط لتحديث الأهداف الاستراتيجية)
                         elif result and result['decision'].get('action') == "UPDATE_TRADE": 
                             print(f"   ✅ (Explorer) Updating strategy for {trade.get('symbol')}."); 
                             await trade_manager_global.update_trade_strategy(trade, result['decision'])
                         elif result: print(f"   ℹ️ (Explorer) Holding {trade.get('symbol')} based on re-analysis.")
                         else: print(f"   ⚠️ Re-analysis for {trade.get('symbol')} yielded no decision.")
            
            current_open_trades_count = len(await trade_manager_global.get_open_trades())
            # (يمكننا البحث عن فرص جديدة حتى لو كانت هناك صفقات مفتوحة، الحارس سيقرر)
            # (لكن للسلامة، سنبقيها كما هي حالياً: ابحث فقط إذا كانت 0)
            should_look_for_new_trade = current_open_trades_count == 0

            if should_look_for_new_trade:
                portfolio_state = await r2_service_global.get_portfolio_state_async(); 
                current_capital = portfolio_state.get("current_capital_usd", 0)
                if current_capital > 1:
                    print("🎯 (Explorer) Looking for new trading opportunities...")
                    
                    # (استدعاء المستكشف الجديد)
                    sentry_watchlist = await run_3_layer_analysis_explorer()
                    
                    if sentry_watchlist: 
                        print(f"✅ (Explorer) Found {len(sentry_watchlist)} candidates. Sending to Sentry (Layer 2)...")
                        # (إرسال قائمة المراقبة إلى الحارس)
                        await trade_manager_global.update_sentry_watchlist(sentry_watchlist)
                    else: 
                        print("❌ (Explorer) No suitable trading opportunities found for Sentry.")
                        # (إرسال قائمة فارغة لإيقاف المراقبة غير الضرورية)
                        await trade_manager_global.update_sentry_watchlist([])
                else: 
                    print("❌ Insufficient capital to open new trades")
            else: 
                print("ℹ️ A trade is already open, skipping new trade search.")
                # (إرسال قائمة فارغة لإيقاف مراقبة الفرص الجديدة)
                await trade_manager_global.update_sentry_watchlist([])
                
        finally:
            if r2_service_global.lock_acquired: r2_service_global.release_lock()
            await r2_service_global.save_system_logs_async({ "explorer_cycle_completed": True, "open_trades": len(open_trades)}) 
            print("✅ Explorer cycle complete")
            
    except Exception as error:
        print(f"❌ Unhandled error in main cycle: {error}"); traceback.print_exc() 
        await r2_service_global.save_system_logs_async({ "cycle_error": True, "error": str(error) });
        if r2_service_global and r2_service_global.lock_acquired: r2_service_global.release_lock() 
# 🔴 --- END OF CHANGE --- 🔴

@asynccontextmanager
async def lifespan(application: FastAPI):
    """Application lifecycle management"""
    print("🚀 Starting application initialization (Explorer/Sentry/Executor)...")
    try:
        success = await initialize_services()
        if not success: print("❌ Application initialization failed - shutting down..."); yield; return
        
        asyncio.create_task(monitor_market_async())
        
        # 🔴 --- START OF CHANGE --- 🔴
        # (بدلاً من start_trade_monitoring القديم)
        asyncio.create_task(trade_manager_global.start_sentry_and_monitoring_loops())
        # 🔴 --- END OF CHANGE --- 🔴
        
        asyncio.create_task(run_periodic_distillation())
        
        await r2_service_global.save_system_logs_async({"application_started": True})
        print("🎯 Application ready - Explorer-Sentry-Executor Architecture is active")
        print("   -> 📈 Sentry (Layer 2) & Executor (Layer 3) are active")
        print("   -> 🧠 Periodic Distillation (Curator) is scheduled")
        yield
    except Exception as error: 
        print(f"❌ Application startup failed: {error}"); 
        traceback.print_exc() 
        if r2_service_global: 
            await r2_service_global.save_system_logs_async({ "application_startup_failed": True, "error": str(error) })
        raise 
    finally: 
        await cleanup_on_shutdown()


application = FastAPI(lifespan=lifespan, title="AI Trading Bot", description="Explorer-Sentry-Executor Architecture (V5.0)", version="5.0.0")

# (Endpoints - لا تغيير كبير)
@application.get("/")
async def root(): return {"message": "Welcome to the AI Trading System", "system": "Explorer-Sentry-Executor", "status": "running" if state_manager.initialization_complete else "initializing", "timestamp": datetime.now().isoformat()}

@application.get("/run-cycle")
async def run_cycle_api():
    if not state_manager.initialization_complete: raise HTTPException(status_code=503, detail="Services not fully initialized")
    asyncio.create_task(run_bot_cycle_async())
    return {"message": "Explorer (Layer 1) cycle initiated", "system": "Explorer-Sentry-Executor"}

@application.get("/health")
async def health_check(): return {"status": "healthy" if state_manager.initialization_complete else "initializing", "initialization_complete": state_manager.initialization_complete, "services_initialized": state_manager.services_initialized, "initialization_error": state_manager.initialization_error, "timestamp": datetime.now().isoformat(), "system_architecture": "Explorer-Sentry-Executor (V5.0)"}

@application.get("/analyze-market")
async def analyze_market_api():
    if not state_manager.initialization_complete: raise HTTPException(status_code=503, detail="Services not fully initialized")
    result = await run_3_layer_analysis_explorer()
    if result: return {"watchlist_generated": True, "count": len(result), "top_candidate": result[0]}
    else: return {"watchlist_generated": False, "message": "No suitable candidates found for Sentry"}

@application.get("/portfolio")
async def get_portfolio_api():
    if not state_manager.initialization_complete: raise HTTPException(status_code=503, detail="Services not fully initialized")
    try: portfolio_state = await r2_service_global.get_portfolio_state_async(); open_trades = await trade_manager_global.get_open_trades(); return {"portfolio": portfolio_state, "open_trades": open_trades, "timestamp": datetime.now().isoformat()}
    except Exception as e: raise HTTPException(status_code=500, detail=f"Error getting portfolio: {str(e)}")

@application.get("/system-status")
async def get_system_status(): 
    monitoring_status = trade_manager_global.get_sentry_status() if trade_manager_global else {}; 
    return {"initialization_complete": state_manager.initialization_complete, "services_initialized": state_manager.services_initialized, "initialization_error": state_manager.initialization_error, "market_state_ok": state.MARKET_STATE_OK, "sentry_status": monitoring_status, "timestamp": datetime.now().isoformat()}

async def cleanup_on_shutdown():
    global r2_service_global, data_manager_global, trade_manager_global, learning_hub_global
    
    print("🛑 Shutdown signal received. Cleaning up...")
    
    # 🔴 --- START OF CHANGE --- 🔴
    if trade_manager_global: 
        await trade_manager_global.stop_sentry_loops()
        print("✅ Sentry/Executor loops stopped")
    # 🔴 --- END OF CHANGE --- 🔴
        
    if learning_hub_global and learning_hub_global.initialized:
        try: 
            await learning_hub_global.shutdown() 
            print("✅ Learning hub data saved")
        except Exception as e: print(f"❌ Failed to save learning hub data: {e}")
        
    if data_manager_global: await data_manager_global.close(); print("✅ Data manager closed")
    if r2_service_global:
        try: await r2_service_global.save_system_logs_async({"application_shutdown": True}); print("✅ Shutdown log saved")
        except Exception as e: print(f"❌ Failed to save shutdown log: {e}")
        if r2_service_global.lock_acquired: r2_service_global.release_lock(); print("✅ R2 lock released")

def signal_handler(signum, frame): print(f"🛑 Received signal {signum}. Initiating shutdown..."); asyncio.create_task(cleanup_on_shutdown()); sys.exit(0)
signal.signal(signal.SIGINT, signal_handler); signal.signal(signal.SIGTERM, signal_handler)

if __name__ == "__main__": 
    print("🚀 Starting AI Trading Bot (Explorer-Sentry-Executor V5.0)...")
    uvicorn.run( application, host="0.0.0.0", port=7860, log_level="info", access_log=True )