import os import json import requests import xml.etree.ElementTree as ET import warnings import time import threading from concurrent.futures import ThreadPoolExecutor, as_completed from fastapi import FastAPI, Request from twilio.rest import Client from twilio.twiml.messaging_response import MessagingResponse # Yeni modüller - Basit sistem from prompts import get_prompt_content_only from whatsapp_renderer import extract_product_info_whatsapp from whatsapp_passive_profiler import ( analyze_user_message, get_user_profile_summary, get_personalized_recommendations ) # LOGGING EN BAŞA EKLENDİ import logging logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') logger = logging.getLogger(__name__) # Import improved WhatsApp search for BF space # DISABLED - Using GPT-5 smart warehouse search instead USE_IMPROVED_SEARCH = False # try: # from whatsapp_improved_chatbot import WhatsAppImprovedChatbot # USE_IMPROVED_SEARCH = True # except ImportError: # print("Improved WhatsApp chatbot not available, using basic search") # USE_IMPROVED_SEARCH = False # Import GPT-5 powered smart warehouse search - complete BF algorithm try: from smart_warehouse_with_price import get_warehouse_stock_smart_with_price USE_GPT5_SEARCH = True logger.info("✅ GPT-5 complete smart warehouse with price (BF algorithm) loaded") except ImportError: USE_GPT5_SEARCH = False logger.info("❌ GPT-5 search not available") warnings.simplefilter('ignore') # Import Media Queue V2 try: from media_queue_v2 import media_queue USE_MEDIA_QUEUE = True logger.info("✅ Media Queue V2 loaded successfully") except ImportError: USE_MEDIA_QUEUE = False logger.info("❌ Media Queue V2 not available") # Import Store Notification System try: from store_notification import ( notify_product_reservation, notify_price_inquiry, notify_stock_inquiry, send_test_notification, send_store_notification, should_notify_mehmet_bey ) USE_STORE_NOTIFICATION = True logger.info("✅ Store Notification System loaded") except ImportError: USE_STORE_NOTIFICATION = False logger.info("❌ Store Notification System not available") # Import Follow-Up System try: from follow_up_system import ( FollowUpManager, analyze_message_for_follow_up, FollowUpType ) USE_FOLLOW_UP = True follow_up_manager = FollowUpManager() logger.info("✅ Follow-Up System loaded") except ImportError: USE_FOLLOW_UP = False follow_up_manager = None logger.info("❌ Follow-Up System not available") # Import Intent Analyzer try: from intent_analyzer import ( analyze_customer_intent, should_notify_store, get_smart_notification_message ) USE_INTENT_ANALYZER = True logger.info("✅ GPT-5 Intent Analyzer loaded") except ImportError: USE_INTENT_ANALYZER = False logger.info("❌ Intent Analyzer not available") # API ayarları API_URL = "https://api.openai.com/v1/chat/completions" OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") logger.info(f"OpenAI API Key var mı: {'Evet' if OPENAI_API_KEY else 'Hayır'}") # Twilio WhatsApp ayarları TWILIO_ACCOUNT_SID = os.getenv("TWILIO_ACCOUNT_SID") TWILIO_AUTH_TOKEN = os.getenv("TWILIO_AUTH_TOKEN") TWILIO_MESSAGING_SERVICE_SID = os.getenv("TWILIO_MESSAGING_SERVICE_SID", "MG11c1dfac28ad5f81908ec9ede0f7247f") TWILIO_WHATSAPP_NUMBER = "whatsapp:+905332047254" # Bizim WhatsApp Business numaramız logger.info(f"Twilio SID var mı: {'Evet' if TWILIO_ACCOUNT_SID else 'Hayır'}") logger.info(f"Twilio Auth Token var mı: {'Evet' if TWILIO_AUTH_TOKEN else 'Hayır'}") logger.info(f"Messaging Service SID var mı: {'Evet' if TWILIO_MESSAGING_SERVICE_SID else 'Hayır'}") if not TWILIO_ACCOUNT_SID or not TWILIO_AUTH_TOKEN: logger.error("❌ Twilio bilgileri eksik!") twilio_client = None else: try: twilio_client = Client(TWILIO_ACCOUNT_SID, TWILIO_AUTH_TOKEN) logger.info("✅ Twilio client başarıyla oluşturuldu!") except Exception as e: logger.error(f"❌ Twilio client hatası: {e}") twilio_client = None # Mağaza stok bilgilerini çekme fonksiyonu def get_warehouse_stock(product_name): """B2B API'den mağaza stok bilgilerini çek - GPT-5 enhanced""" # Try GPT-5 complete smart search (BF algorithm) if USE_GPT5_SEARCH: try: gpt5_result = get_warehouse_stock_smart_with_price(product_name) if gpt5_result and isinstance(gpt5_result, list): # Return directly if it's already formatted strings if all(isinstance(item, str) for item in gpt5_result): return gpt5_result # Format for WhatsApp if dict format warehouse_info = [] for item in gpt5_result: if isinstance(item, dict): info = f"📦 {item.get('name', '')}" if item.get('variant'): info += f" ({item['variant']})" if item.get('warehouses'): info += f"\n📍 Mevcut: {', '.join(item['warehouses'])}" if item.get('price'): info += f"\n💰 {item['price']}" warehouse_info.append(info) else: warehouse_info.append(str(item)) return warehouse_info if warehouse_info else None except Exception as e: logger.error(f"GPT-5 warehouse search error: {e}") # Continue to fallback search # Fallback to original search try: import re warehouse_url = 'https://video.trek-turkey.com/bizimhesap-warehouse-xml-b2b-api-v2.php' response = requests.get(warehouse_url, verify=False, timeout=15) if response.status_code != 200: return None root = ET.fromstring(response.content) # Turkish character normalization function turkish_map = {'ı': 'i', 'ğ': 'g', 'ü': 'u', 'ş': 's', 'ö': 'o', 'ç': 'c', 'İ': 'i', 'I': 'i'} def normalize_turkish(text): import unicodedata text = unicodedata.normalize('NFD', text) text = ''.join(char for char in text if unicodedata.category(char) != 'Mn') for tr_char, en_char in turkish_map.items(): text = text.replace(tr_char, en_char) return text # Normalize search product name search_name = normalize_turkish(product_name.lower().strip()) search_name = search_name.replace('(2026)', '').replace('(2025)', '').replace(' gen 3', '').replace(' gen', '').strip() search_words = search_name.split() best_matches = [] exact_matches = [] variant_matches = [] candidates = [] # Separate size/color words from product words size_color_words = ['s', 'm', 'l', 'xl', 'xs', 'small', 'medium', 'large', 'turuncu', 'siyah', 'beyaz', 'mavi', 'kirmizi', 'yesil', 'orange', 'black', 'white', 'blue', 'red', 'green'] variant_words = [word for word in search_words if word in size_color_words] product_words = [word for word in search_words if word not in size_color_words] # Check if this is a size/color specific query is_size_color_query = len(variant_words) > 0 and len(search_words) <= 4 # İlk geçiş: Variant alanında beden/renk araması if is_size_color_query: for product in root.findall('Product'): product_name_elem = product.find('ProductName') variant_elem = product.find('ProductVariant') if product_name_elem is not None and product_name_elem.text: xml_product_name = product_name_elem.text.strip() normalized_product_name = normalize_turkish(xml_product_name.lower()) # If there are product words, check if they match the product name product_name_matches = True if product_words: product_name_matches = all(word in normalized_product_name for word in product_words) # Only proceed if product name matches (or no product context) if product_name_matches: # Variant field check if variant_elem is not None and variant_elem.text: variant_text = normalize_turkish(variant_elem.text.lower().replace('-', ' ')) # Check if all variant words are in variant field if all(word in variant_text for word in variant_words): variant_matches.append((product, xml_product_name, variant_text)) if variant_matches: candidates = variant_matches else: # Fallback to normal product name search is_size_color_query = False # İkinci geçiş: Normal ürün adı tam eşleşmeleri (variant match yoksa) if not is_size_color_query or not candidates: for product in root.findall('Product'): product_name_elem = product.find('ProductName') if product_name_elem is not None and product_name_elem.text: xml_product_name = product_name_elem.text.strip() normalized_xml = normalize_turkish(xml_product_name.lower()) normalized_xml = normalized_xml.replace('(2026)', '').replace('(2025)', '').replace(' gen 3', '').replace(' gen', '').strip() xml_words = normalized_xml.split() # Tam eşleşme kontrolü - ilk iki kelime tam aynı olmalı if len(search_words) >= 2 and len(xml_words) >= 2: search_key = f"{search_words[0]} {search_words[1]}" xml_key = f"{xml_words[0]} {xml_words[1]}" if search_key == xml_key: exact_matches.append((product, xml_product_name, normalized_xml)) # Eğer variant match varsa onu kullan, yoksa exact matches kullan if not candidates: candidates = exact_matches if exact_matches else [] # Eğer hala bir match yoksa, fuzzy matching yap if not candidates: for product in root.findall('Product'): product_name_elem = product.find('ProductName') if product_name_elem is not None and product_name_elem.text: xml_product_name = product_name_elem.text.strip() normalized_xml = normalize_turkish(xml_product_name.lower()) normalized_xml = normalized_xml.replace('(2026)', '').replace('(2025)', '').replace(' gen 3', '').replace(' gen', '').strip() xml_words = normalized_xml.split() # Ortak kelime sayısını hesapla common_words = set(search_words) & set(xml_words) # En az 2 ortak kelime olmalı VE ilk kelime aynı olmalı (marka kontrolü) if (len(common_words) >= 2 and len(search_words) > 0 and len(xml_words) > 0 and search_words[0] == xml_words[0]): best_matches.append((product, xml_product_name, normalized_xml, len(common_words))) # En çok ortak kelimeye sahip olanları seç if best_matches: max_common = max(match[3] for match in best_matches) candidates = [(match[0], match[1], match[2]) for match in best_matches if match[3] == max_common] # Stok bilgilerini topla ve tekrarları önle warehouse_stock_map = {} # warehouse_name -> total_stock for product, xml_name, _ in candidates: # New B2B API structure: Warehouse elements are direct children of Product for warehouse in product.findall('Warehouse'): name_elem = warehouse.find('Name') stock_elem = warehouse.find('Stock') if name_elem is not None and stock_elem is not None: warehouse_name = name_elem.text if name_elem.text else "Bilinmeyen" try: stock_count = int(stock_elem.text) if stock_elem.text else 0 if stock_count > 0: # Aynı mağaza için stokları topla if warehouse_name in warehouse_stock_map: warehouse_stock_map[warehouse_name] += stock_count else: warehouse_stock_map[warehouse_name] = stock_count except (ValueError, TypeError): pass if warehouse_stock_map: # Mağaza stoklarını liste halinde döndür all_warehouse_info = [] for warehouse_name, total_stock in warehouse_stock_map.items(): all_warehouse_info.append(f"{warehouse_name}: Stokta var") return all_warehouse_info else: return ["Hiçbir mağazada stokta bulunmuyor"] except Exception as e: print(f"Mağaza stok bilgisi çekme hatası: {e}") return None # Trek bisiklet ürünlerini çekme - DÜZELTİLMİŞ VERSİYON try: # All XML debug prints disabled to reduce noise url = 'https://www.trekbisiklet.com.tr/output/8582384479' response = requests.get(url, verify=False, timeout=10) # XML parsing - all debug prints disabled content_preview = response.content[:500].decode('utf-8', errors='ignore') root = ET.fromstring(response.content) all_items = root.findall('item') # Item analysis disabled for production # Marlin arama testi marlin_count = 0 products = [] for item in all_items: # Değişkenleri önceden tanımla stock_number = 0 stock_amount = "stokta değil" price = "" price_eft = "" product_link = "" rootlabel = item.find('rootlabel') if rootlabel is None or not rootlabel.text: continue full_name = rootlabel.text.strip() name_words = full_name.lower().split() name = name_words[0] if name_words else "unknown" # STOK KONTROLÜ - SAYISAL KARŞILAŞTIRMA stock_element = item.find('stockAmount') if stock_element is not None and stock_element.text: try: stock_number = int(stock_element.text.strip()) stock_amount = "stokta" if stock_number > 0 else "stokta değil" except (ValueError, TypeError): stock_number = 0 stock_amount = "stokta değil" # Marlin kontrolü if 'marlin' in full_name.lower(): marlin_count += 1 pass # Stokta olan ürünler için fiyat bilgilerini al if stock_amount == "stokta": # Normal fiyat price_element = item.find('priceTaxWithCur') price_str = price_element.text if price_element is not None and price_element.text else "0" # Kampanya fiyatı price_rebate_element = item.find('priceRebateWithTax') price_rebate_str = price_rebate_element.text if price_rebate_element is not None and price_rebate_element.text else "" # Kampanya fiyatı varsa onu kullan, yoksa normal fiyatı kullan final_price_str = price_str if price_rebate_str: try: normal_price = float(price_str) rebate_price = float(price_rebate_str) # Kampanya fiyatı normal fiyattan farklı ve düşükse kullan if rebate_price < normal_price: final_price_str = price_rebate_str except (ValueError, TypeError): final_price_str = price_str # EFT fiyatı price_eft_element = item.find('priceEft') price_eft_str = price_eft_element.text if price_eft_element is not None and price_eft_element.text else "" # Ürün linki link_element = item.find('productLink') product_link = link_element.text if link_element is not None and link_element.text else "" # Fiyat formatting (kampanya fiyatı veya normal fiyat) try: price_float = float(final_price_str) if price_float > 200000: price = str(round(price_float / 5000) * 5000) elif price_float > 30000: price = str(round(price_float / 1000) * 1000) elif price_float > 10000: price = str(round(price_float / 100) * 100) else: price = str(round(price_float / 10) * 10) except (ValueError, TypeError): price = final_price_str # EFT fiyat formatting if price_eft_str: try: price_eft_float = float(price_eft_str) if price_eft_float > 200000: price_eft = str(round(price_eft_float / 5000) * 5000) elif price_eft_float > 30000: price_eft = str(round(price_eft_float / 1000) * 1000) elif price_eft_float > 10000: price_eft = str(round(price_eft_float / 100) * 100) else: price_eft = str(round(price_eft_float / 10) * 10) except (ValueError, TypeError): price_eft = price_eft_str else: try: price_eft_float = float(price_str) price_eft = str(round(price_eft_float * 0.975 / 10) * 10) except: price_eft = "" # Ürün bilgilerini tuple olarak oluştur item_info = (stock_amount, price, product_link, price_eft, str(stock_number)) products.append((name, item_info, full_name)) # Summary disabled for production # Initialize improved WhatsApp chatbot for BF space global improved_whatsapp_bot improved_whatsapp_bot = None if USE_IMPROVED_SEARCH: try: improved_whatsapp_bot = WhatsAppImprovedChatbot(products) # print("✅ BF Space: Improved WhatsApp product search initialized successfully") except Exception as e: logger.error(f"BF Space: Failed to initialize improved WhatsApp search: {e}") USE_IMPROVED_SEARCH = False improved_whatsapp_bot = None # Enhanced features kaldırıldı - GPT-4 doğal dil anlama kullanacak # print("✅ Basit sistem aktif - GPT-4 doğal dil anlama") # Marlin debug reports disabled for production if marlin_count == 0: pass # No Marlin products found else: # Marlin stok raporu marlin_products = [p for p in products if 'marlin' in p[2].lower()] marlin_in_stock = [p for p in marlin_products if p[1][0] == "stokta"] marlin_out_of_stock = [p for p in marlin_products if p[1][0] == "stokta değil"] # Product lists disabled for production pass except Exception as e: logger.error(f"Ürün yükleme hatası: {e}") import traceback traceback.print_exc() products = [] # =============================== # STOK API ENTEGRASYONU # =============================== STOCK_API_BASE = "https://video.trek-turkey.com/bizimhesap-proxy.php" # Stock cache (5 dakikalık cache) stock_cache = {} CACHE_DURATION = 300 # 5 dakika (saniye cinsinden) def normalize_turkish(text): """Türkçe karakterleri normalize et""" if not text: return "" replacements = { 'ı': 'i', 'İ': 'i', 'ş': 's', 'Ş': 's', 'ğ': 'g', 'Ğ': 'g', 'ü': 'u', 'Ü': 'u', 'ö': 'o', 'Ö': 'o', 'ç': 'c', 'Ç': 'c' } text = text.lower() for tr_char, eng_char in replacements.items(): text = text.replace(tr_char, eng_char) return text def fetch_warehouse_inventory(warehouse, product_name, search_terms): """Tek bir mağazanın stok bilgisini al""" try: warehouse_id = warehouse['id'] warehouse_name = warehouse['title'] # DSW'yi ayrı tut (gelecek stok için) is_dsw = 'DSW' in warehouse_name or 'ÖN SİPARİŞ' in warehouse_name.upper() # Mağaza stoklarını al inventory_url = f"{STOCK_API_BASE}?action=inventory&warehouse={warehouse_id}&endpoint=inventory/{warehouse_id}" inventory_response = requests.get(inventory_url, timeout=3, verify=False) if inventory_response.status_code != 200: return None inventory_data = inventory_response.json() # API yanıtını kontrol et if 'data' not in inventory_data or 'inventory' not in inventory_data['data']: return None products = inventory_data['data']['inventory'] # Beden terimleri kontrolü size_terms = ['xs', 's', 'm', 'ml', 'l', 'xl', 'xxl', '2xl', '3xl', 'small', 'medium', 'large'] size_numbers = ['44', '46', '48', '50', '52', '54', '56', '58', '60'] # Arama terimlerinde beden var mı kontrol et has_size_query = False size_query = None for term in search_terms: if term in size_terms or term in size_numbers: has_size_query = True size_query = term break # Eğer sadece beden sorgusu varsa (ör: "m", "xl") is_only_size_query = len(search_terms) == 1 and has_size_query # Ürünü ara warehouse_variants = [] dsw_stock_count = 0 for product in products: product_title = normalize_turkish(product.get('title', '')).lower() original_title = product.get('title', '') # Eğer sadece beden sorgusu ise if is_only_size_query: # Beden terimini ürün başlığında ara (parantez içinde veya dışında) if size_query in product_title.split() or f'({size_query})' in product_title or f' {size_query} ' in product_title or product_title.endswith(f' {size_query}'): qty = int(product.get('qty', 0)) stock = int(product.get('stock', 0)) actual_stock = max(qty, stock) if actual_stock > 0: if is_dsw: dsw_stock_count += actual_stock continue warehouse_variants.append(f"{original_title}: ✓ Stokta") else: # Normal ürün araması - tüm terimler eşleşmeli # Ama beden terimi varsa özel kontrol yap if has_size_query: # Beden hariç diğer terimleri kontrol et non_size_terms = [t for t in search_terms if t != size_query] product_matches = all(term in product_title for term in non_size_terms) # Beden kontrolü - daha esnek size_matches = size_query in product_title.split() or f'({size_query})' in product_title or f' {size_query} ' in product_title or product_title.endswith(f' {size_query}') if product_matches and size_matches: qty = int(product.get('qty', 0)) stock = int(product.get('stock', 0)) actual_stock = max(qty, stock) if actual_stock > 0: if is_dsw: dsw_stock_count += actual_stock continue # Varyant bilgisini göster variant_info = original_title possible_names = [ product_name.upper(), product_name.lower(), product_name.title(), product_name.upper().replace('I', 'İ'), product_name.upper().replace('İ', 'I'), ] if 'fx sport' in product_name.lower(): possible_names.extend(['FX Sport AL 3', 'FX SPORT AL 3', 'Fx Sport Al 3']) for possible_name in possible_names: variant_info = variant_info.replace(possible_name, '').strip() variant_info = ' '.join(variant_info.split()) if variant_info and variant_info != original_title: warehouse_variants.append(f"{variant_info}: ✓ Stokta") else: warehouse_variants.append(f"{original_title}: ✓ Stokta") else: # Beden sorgusu yoksa normal kontrol if all(term in product_title for term in search_terms): qty = int(product.get('qty', 0)) stock = int(product.get('stock', 0)) actual_stock = max(qty, stock) if actual_stock > 0: if is_dsw: dsw_stock_count += actual_stock continue variant_info = original_title possible_names = [ product_name.upper(), product_name.lower(), product_name.title(), product_name.upper().replace('I', 'İ'), product_name.upper().replace('İ', 'I'), ] if 'fx sport' in product_name.lower(): possible_names.extend(['FX Sport AL 3', 'FX SPORT AL 3', 'Fx Sport Al 3']) for possible_name in possible_names: variant_info = variant_info.replace(possible_name, '').strip() variant_info = ' '.join(variant_info.split()) if variant_info and variant_info != original_title: warehouse_variants.append(f"{variant_info}: ✓ Stokta") else: warehouse_variants.append(f"{original_title}: ✓ Stokta") # Sonuç döndür if warehouse_variants and not is_dsw: return {'warehouse': warehouse_name, 'variants': warehouse_variants, 'is_dsw': False} elif dsw_stock_count > 0: return {'dsw_stock': dsw_stock_count, 'is_dsw': True} return None except Exception: return None def get_realtime_stock_parallel(product_name): """API'den gerçek zamanlı stok bilgisini çek - Paralel versiyon with cache""" try: # Cache kontrolü cache_key = normalize_turkish(product_name).lower() current_time = time.time() if cache_key in stock_cache: cached_data, cached_time = stock_cache[cache_key] # Cache hala geçerli mi? if current_time - cached_time < CACHE_DURATION: logger.info(f"Cache'den döndürülüyor: {product_name}") return cached_data # Önce mağaza listesini al warehouses_url = f"{STOCK_API_BASE}?action=warehouses&endpoint=warehouses" warehouses_response = requests.get(warehouses_url, timeout=3, verify=False) if warehouses_response.status_code != 200: logger.error(f"Mağaza listesi alınamadı: {warehouses_response.status_code}") return None warehouses_data = warehouses_response.json() # API yanıtını kontrol et if 'data' not in warehouses_data or 'warehouses' not in warehouses_data['data']: logger.error("Mağaza verisi bulunamadı") return None warehouses = warehouses_data['data']['warehouses'] # Ürün adını normalize et search_terms = normalize_turkish(product_name).lower().split() logger.info(f"Aranan ürün: {product_name} -> {search_terms}") stock_info = {} total_dsw_stock = 0 total_stock = 0 # Paralel olarak tüm mağazaları sorgula with ThreadPoolExecutor(max_workers=10) as executor: # Tüm mağazalar için görev oluştur futures = { executor.submit(fetch_warehouse_inventory, warehouse, product_name, search_terms): warehouse for warehouse in warehouses } # Sonuçları topla for future in as_completed(futures): result = future.result() if result: if result.get('is_dsw'): total_dsw_stock += result.get('dsw_stock', 0) else: warehouse_name = result['warehouse'] stock_info[warehouse_name] = result['variants'] total_stock += 1 # En az bir mağazada var # Sonucu oluştur if not stock_info: # Mağazada yok ama DSW'de varsa if total_dsw_stock > 0: result = f"{product_name}: Şu anda mağazalarda stokta yok, ancak yakında gelecek. Ön sipariş verebilirsiniz." else: result = f"{product_name}: Şu anda hiçbir mağazada stokta bulunmuyor." else: # Minimal prompt oluştur - varyant detaylarıyla prompt_lines = [f"{product_name} stok durumu:"] for warehouse, variants in stock_info.items(): if isinstance(variants, list): prompt_lines.append(f"- {warehouse}:") for variant in variants: prompt_lines.append(f" • {variant}") else: prompt_lines.append(f"- {warehouse}: {variants}") # Güvenlik: Toplam adet bilgisi gösterme if total_stock > 0: prompt_lines.append(f"✓ Ürün stokta mevcut") result = "\n".join(prompt_lines) # Sonucu cache'e kaydet stock_cache[cache_key] = (result, current_time) return result except Exception as e: logger.error(f"API hatası: {e}") return None def is_stock_query(message): """Mesajın stok sorgusu olup olmadığını kontrol et""" stock_keywords = ['stok', 'stock', 'var mı', 'mevcut mu', 'kaç adet', 'kaç tane', 'bulunuyor mu', 'hangi mağaza', 'nerede var', 'beden', 'numara'] message_lower = message.lower() return any(keyword in message_lower for keyword in stock_keywords) # Sistem mesajları - Modüler prompts'tan yükle def get_system_messages(): return get_prompt_content_only() # prompts.py'dan yükle # =============================== # SOHBET HAFIZASI SİSTEMİ # =============================== # Sohbet hafızası için basit bir dictionary conversation_memory = {} def get_conversation_context(phone_number): """Kullanıcının sohbet geçmişini getir""" if phone_number not in conversation_memory: conversation_memory[phone_number] = { "messages": [], "current_category": None, "last_activity": None } return conversation_memory[phone_number] def add_to_conversation(phone_number, user_message, ai_response): """Sohbet geçmişine ekle""" import datetime context = get_conversation_context(phone_number) context["last_activity"] = datetime.datetime.now() context["messages"].append({ "user": user_message, "ai": ai_response, "timestamp": datetime.datetime.now() }) # Sadece son 10 mesajı tut if len(context["messages"]) > 10: context["messages"] = context["messages"][-10:] detect_category(phone_number, user_message, ai_response) def detect_category(phone_number, user_message, ai_response): """Konuşulan kategoriyi tespit et""" context = get_conversation_context(phone_number) categories = { "marlin": ["marlin", "marlin+"], "madone": ["madone"], "emonda": ["emonda", "émonda"], "domane": ["domane"], "checkpoint": ["checkpoint"], "fuel": ["fuel", "fuel ex", "fuel exe"], "procaliber": ["procaliber"], "supercaliber": ["supercaliber"], "fx": ["fx"], "ds": ["ds", "dual sport"], "powerfly": ["powerfly"], "rail": ["rail"], "verve": ["verve"], "townie": ["townie"] } user_lower = user_message.lower() for category, keywords in categories.items(): for keyword in keywords: if keyword in user_lower: context["current_category"] = category return category return context.get("current_category") def build_context_messages(phone_number, current_message): """Sohbet geçmişi ile sistem mesajlarını oluştur""" context = get_conversation_context(phone_number) system_messages = get_system_messages() # Mevcut kategori varsa, sistem mesajına ekle if context.get("current_category"): category_msg = f"Kullanıcı şu anda {context['current_category'].upper()} kategorisi hakkında konuşuyor. Tüm cevaplarını bu kategori bağlamında ver. Kullanıcı yeni bir kategori belirtmediği sürece {context['current_category']} hakkında bilgi vermek istediğini varsay." system_messages.append({"role": "system", "content": category_msg}) # Son 3 mesaj alışverişini ekle recent_messages = context["messages"][-3:] if context["messages"] else [] all_messages = system_messages.copy() # Geçmiş mesajları ekle for msg in recent_messages: all_messages.append({"role": "user", "content": msg["user"]}) all_messages.append({"role": "assistant", "content": msg["ai"]}) # Mevcut mesajı ekle all_messages.append({"role": "user", "content": current_message}) return all_messages def process_whatsapp_message_with_media(user_message, phone_number, media_urls, media_types): """Medya içeriği olan WhatsApp mesajı işleme - GPT-5 Vision ile""" try: logger.info(f"🖼️ Medya analizi başlıyor: {len(media_urls)} medya") # Pasif profil analizi profile_analysis = analyze_user_message(phone_number, user_message) logger.info(f"📊 Profil analizi: {phone_number} -> {profile_analysis}") # Sohbet geçmişi ile sistem mesajlarını oluştur messages = build_context_messages(phone_number, user_message if user_message else "Gönderilen görseli analiz et") # GPT-5 Vision için mesaj hazırla vision_message = { "role": "user", "content": [] } # Metin mesajı varsa ekle if user_message and user_message.strip(): vision_message["content"].append({ "type": "text", "text": user_message }) else: vision_message["content"].append({ "type": "text", "text": "Bu görselde ne var? Detaylı açıkla." }) # Medya URL'lerini ekle (Twilio medya URL'leri için proxy kullan) for i, media_url in enumerate(media_urls): media_type = media_types[i] if i < len(media_types) else "image/jpeg" # Sadece görsel medyaları işle if media_type and media_type.startswith('image/'): # Twilio medya URL'sini proxy üzerinden çevir if 'api.twilio.com' in media_url: # URL'den message SID ve media SID'yi çıkar import re match = re.search(r'/Messages/([^/]+)/Media/([^/]+)', media_url) if match: message_sid = match.group(1) media_sid = match.group(2) # Proxy URL'sini oluştur proxy_url = f"https://video.trek-turkey.com/twilio-media-proxy.php?action=media&message={message_sid}&media={media_sid}" logger.info(f"🔄 Proxy URL: {proxy_url}") vision_message["content"].append({ "type": "image_url", "image_url": { "url": proxy_url } }) else: # Diğer URL'leri doğrudan kullan vision_message["content"].append({ "type": "image_url", "image_url": { "url": media_url } }) # Son user mesajını vision mesajıyla değiştir messages = [msg for msg in messages if msg.get("role") != "user" or msg != messages[-1]] messages.append(vision_message) # Sistem mesajına bisiklet tanıma talimatı ekle messages.insert(0, { "role": "system", "content": "Gönderilen görsellerde bisiklet veya bisiklet parçaları varsa, bunları detaylıca tanımla. Marka, model, renk, özellikler gibi detayları belirt. Eğer Trek bisiklet ise modeli tahmin etmeye çalış. Stok durumu sorulursa, görseldeki bisikletin özelliklerini belirterek stok kontrolü yapılması gerektiğini söyle." }) if not OPENAI_API_KEY: return "OpenAI API anahtarı eksik. Lütfen environment variables'ları kontrol edin." logger.info(f"📤 GPT-5 Vision'a gönderiliyor: {len(messages)} mesaj") payload = { "model": "gpt-5-chat-latest", "messages": messages, "temperature": 0, # Deterministik cevaplar için "max_tokens": 800, "stream": False, "top_p": 0.1, # Daha tutarlı cevaplar için düşük değer "frequency_penalty": 0.1, # Tekrarları azaltmak için "presence_penalty": 0 # Yeni konulara açık olması için } headers = { "Content-Type": "application/json", "Authorization": f"Bearer {OPENAI_API_KEY}" } response = requests.post(API_URL, headers=headers, json=payload) if response.status_code == 200: result = response.json() ai_response = result['choices'][0]['message']['content'] # WhatsApp için formatla formatted_response = extract_product_info_whatsapp(ai_response) # Sohbet geçmişine ekle add_to_conversation(phone_number, f"[Görsel gönderildi] {user_message if user_message else ''}", formatted_response) return formatted_response else: logger.error(f"OpenAI API Error: {response.status_code} - {response.text}") return f"Görsel analizi başarısız oldu. Lütfen tekrar deneyin." except Exception as e: logger.error(f"❌ Medya işleme hatası: {e}") import traceback traceback.print_exc() return "Görsel işlenirken bir hata oluştu. Lütfen tekrar deneyin." def process_whatsapp_message_with_memory(user_message, phone_number): """Hafızalı WhatsApp mesaj işleme""" try: # 🔔 Yeni Mağaza Bildirim Sistemi - Mehmet Bey'e otomatik bildirim if USE_STORE_NOTIFICATION: # Önce basit keyword kontrolü yap should_notify_mehmet, notification_reason, urgency = should_notify_mehmet_bey(user_message) # Eğer keyword'le yakalanmadıysa ve Intent Analyzer varsa, onu da kontrol et if not should_notify_mehmet and USE_INTENT_ANALYZER: context = get_conversation_context(phone_number) intent_analysis = analyze_customer_intent(user_message, context) should_notify_mehmet, notification_reason, urgency = should_notify_mehmet_bey(user_message, intent_analysis) else: intent_analysis = None if should_notify_mehmet: # Ürün bilgisini belirle if intent_analysis: product = intent_analysis.get("product") or "Belirtilmemiş" else: # Basit keyword'den ürün çıkar context = get_conversation_context(phone_number) product = context.get("current_category") or "Ürün belirtilmemiş" # Bildirim tipini belirle if "rezervasyon" in notification_reason.lower() or urgency == "high": action = "reserve" elif "mağaza" in notification_reason.lower() or "lokasyon" in notification_reason.lower(): action = "info" elif "fiyat" in notification_reason.lower() or "ödeme" in notification_reason.lower(): action = "price" else: action = "info" # Detaylı bilgi mesajı additional_info = f"{notification_reason}\n\nMüşteri Mesajı: '{user_message}'" if urgency == "high": additional_info = "⚠️ YÜKSEK ÖNCELİK ⚠️\n" + additional_info # Bildirim gönder result = send_store_notification( customer_phone=phone_number, customer_name=None, product_name=product, action=action, store_name=None, additional_info=additional_info ) if result: logger.info(f"✅ Mehmet Bey'e bildirim gönderildi!") logger.info(f" 📍 Sebep: {notification_reason}") logger.info(f" ⚡ Öncelik: {urgency}") logger.info(f" 📦 Ürün: {product}") # TAKIP SISTEMINI KONTROL ET if USE_FOLLOW_UP and follow_up_manager: follow_up_analysis = analyze_message_for_follow_up(user_message) if follow_up_analysis and follow_up_analysis["needs_follow_up"]: # Takip oluştur follow_up = follow_up_manager.create_follow_up( customer_phone=phone_number, product_name=product, follow_up_type=follow_up_analysis["follow_up_type"], original_message=user_message, follow_up_hours=follow_up_analysis["follow_up_hours"], notes=follow_up_analysis["reason"] ) logger.info(f"📌 Takip oluşturuldu: {follow_up_analysis['reason']}") logger.info(f" ⏰ {follow_up_analysis['follow_up_hours']} saat sonra hatırlatılacak") else: logger.error("❌ Mehmet Bey'e bildirim gönderilemedi") # 🧠 Pasif profil analizi - kullanıcı mesajını analiz et profile_analysis = analyze_user_message(phone_number, user_message) logger.info(f"📊 Profil analizi: {phone_number} -> {profile_analysis}") # 🎯 Kişiselleştirilmiş öneriler kontrolü if any(keyword in user_message.lower() for keyword in ["öneri", "öner", "tavsiye", "ne önerirsin"]): personalized = get_personalized_recommendations(phone_number, products) if personalized.get("personalized") and personalized.get("recommendations"): # Kullanıcı profiline göre özelleştirilmiş cevap hazırla profile_summary = get_user_profile_summary(phone_number) custom_response = create_personalized_response(personalized, profile_summary) return extract_product_info_whatsapp(custom_response) # Enhanced features kaldırıldı - GPT-4 doğal dil anlama kullanacak # Sohbet geçmişi ile sistem mesajlarını oluştur messages = build_context_messages(phone_number, user_message) # 🎯 Profil bilgilerini sistem mesajlarına ekle profile_summary = get_user_profile_summary(phone_number) if profile_summary.get("exists") and profile_summary.get("confidence", 0) > 0.3: profile_context = create_profile_context_message(profile_summary) messages.append({"role": "system", "content": profile_context}) # 🔍 BF Space: Use improved product search if available product_found_improved = False if USE_IMPROVED_SEARCH and improved_whatsapp_bot: try: product_result = improved_whatsapp_bot.process_message(user_message) if product_result['is_product_query'] and product_result['response']: # Check if user is asking about specific warehouse/store location if any(keyword in user_message.lower() for keyword in ['mağaza', 'mağazada', 'nerede', 'hangi mağaza', 'şube']): # First, always search for products using improved search # This will find products even with partial/typo names warehouse_info_parts = [] # Use the response text from improved search to extract product names if product_result['response']: # Extract product names from the response import re # Look for product names in bold (between * markers) product_names = re.findall(r'\*([^*]+)\*', product_result['response']) if product_names: for product_name in product_names[:3]: # Max 3 products # Clean up the product name product_name = product_name.strip() # Remove numbering like "1." "2." from the beginning import re product_name = re.sub(r'^\d+\.\s*', '', product_name) # Skip status indicators if product_name in ['Stokta mevcut', 'Stokta yok', 'Fiyat:', 'Kampanya:', 'İndirim:', 'Birden fazla ürün buldum:']: continue warehouse_stock = get_warehouse_stock(product_name) if warehouse_stock and warehouse_stock != ['Ürün bulunamadı'] and warehouse_stock != ['Hiçbir mağazada stokta bulunmuyor']: warehouse_info_parts.append(f"{product_name} mağaza stogu:") warehouse_info_parts.extend(warehouse_stock) warehouse_info_parts.append("") break # Found warehouse info, stop searching # If still no warehouse info, use products_found as backup if not warehouse_info_parts and product_result['products_found']: for product in product_result['products_found'][:2]: product_name = product[2] # Full product name warehouse_stock = get_warehouse_stock(product_name) if warehouse_stock and warehouse_stock != ['Ürün bulunamadı'] and warehouse_stock != ['Hiçbir mağazada stokta bulunmuyor']: warehouse_info_parts.append(f"{product_name} mağaza stogu:") warehouse_info_parts.extend(warehouse_stock) warehouse_info_parts.append("") break if warehouse_info_parts: warehouse_response = "\n".join(warehouse_info_parts) messages.append({ "role": "system", "content": f"MAĞAZA STOK BİLGİSİ (BF Space):\n{warehouse_response}\n\nSADECE bu bilgileri kullanarak kullanıcıya yardımcı ol." }) product_found_improved = True logger.info("✅ BF Space: Warehouse stock info used") if not product_found_improved: # Use improved search response directly messages.append({ "role": "system", "content": f"ÜRÜN BİLGİSİ (BF Space):\n{product_result['response']}\n\nSADECE bu bilgileri kullanarak kullanıcıya yardımcı ol. Bu bilgiler dışında ek bilgi ekleme." }) product_found_improved = True logger.info("✅ BF Space: Improved product search used") except Exception as e: logger.error(f"❌ BF Space: Improved search error: {e}") # Fallback to warehouse search if improved search didn't work if not product_found_improved: # Check if message seems to be asking about products product_keywords = ['fiyat', 'kaç', 'stok', 'var mı', 'mevcut', 'bisiklet', 'bike', 'trek', 'model', 'beden', 'renk', 'mağaza', 'nerede', 'hangi'] # Common non-product responses non_product_responses = ['süper', 'harika', 'güzel', 'teşekkür', 'tamam', 'olur', 'evet', 'hayır', 'peki', 'anladım', 'tamamdır'] is_product_query = False lower_message = user_message.lower() # Check if it's likely a product query if any(keyword in lower_message for keyword in product_keywords): is_product_query = True # Check if it's NOT a simple response elif lower_message not in non_product_responses and len(lower_message.split()) > 1: # Multi-word queries might be product searches is_product_query = True # Single short words are usually not products elif len(lower_message.split()) == 1 and len(lower_message) < 6: is_product_query = False if is_product_query: # Use GPT-5 warehouse search for product queries logger.info("📦 Using GPT-5 warehouse search") warehouse_result = get_warehouse_stock(user_message) if warehouse_result and warehouse_result != ['Ürün bulunamadı']: warehouse_response = "\n".join(warehouse_result) messages.append({ "role": "system", "content": f"MAĞAZA STOK BİLGİSİ:\n{warehouse_response}\n\nBu bilgileri kullanarak kullanıcıya yardımcı ol. Fiyat ve stok bilgilerini AYNEN kullan." }) logger.info(f"✅ Warehouse stock info added: {warehouse_response[:200]}...") else: logger.info(f"🚫 Skipping product search for: '{user_message}'") if not OPENAI_API_KEY: return "OpenAI API anahtarı eksik. Lütfen environment variables'ları kontrol edin." # Debug: Log what we're sending to GPT logger.info(f"📤 Sending to GPT-5: {len(messages)} messages") for i, msg in enumerate(messages): if msg.get('role') == 'system': content_preview = msg.get('content', '')[:500] if 'Fiyat:' in content_preview or 'TL' in content_preview: logger.info(f"💰 System message with price info: {content_preview}") payload = { "model": "gpt-5-chat-latest", "messages": messages, "temperature": 0, # Deterministik cevaplar için "max_tokens": 800, "stream": False, "top_p": 0.1, # Daha tutarlı cevaplar için düşük değer "frequency_penalty": 0.1, # Tekrarları azaltmak için "presence_penalty": 0 # Yeni konulara açık olması için } headers = { "Content-Type": "application/json", "Authorization": f"Bearer {OPENAI_API_KEY}" } response = requests.post(API_URL, headers=headers, json=payload) if response.status_code == 200: result = response.json() ai_response = result['choices'][0]['message']['content'] # WhatsApp için resim URL'lerini formatla formatted_response = extract_product_info_whatsapp(ai_response) # Sohbet geçmişine ekle add_to_conversation(phone_number, user_message, formatted_response) return formatted_response else: print(f"OpenAI API Error: {response.status_code} - {response.text}") return f"API hatası: {response.status_code}. Lütfen daha sonra tekrar deneyin." except Exception as e: print(f"❌ WhatsApp mesaj işleme hatası: {e}") import traceback traceback.print_exc() logger.error(f"Detailed error: {str(e)}") logger.error(f"Error type: {type(e).__name__}") return "Teknik bir sorun oluştu. Lütfen daha sonra tekrar deneyin." def create_profile_context_message(profile_summary): """Profil bilgilerini sistem mesajına çevir""" context_parts = [] preferences = profile_summary.get("preferences", {}) behavior = profile_summary.get("behavior", {}) # Bütçe bilgisi if preferences.get("budget_min") and preferences.get("budget_max"): budget_min = preferences["budget_min"] budget_max = preferences["budget_max"] context_parts.append(f"Kullanıcının bütçesi: {budget_min:,}-{budget_max:,} TL") # Kategori tercihleri if preferences.get("categories"): categories = ", ".join(preferences["categories"]) context_parts.append(f"İlgilendiği kategoriler: {categories}") # Kullanım amacı if preferences.get("usage_purpose"): purposes = ", ".join(preferences["usage_purpose"]) context_parts.append(f"Kullanım amacı: {purposes}") # Davranış kalıpları if behavior.get("price_sensitive"): context_parts.append("Fiyata duyarlı bir kullanıcı") if behavior.get("tech_interested"): context_parts.append("Teknik detaylarla ilgilenen bir kullanıcı") if behavior.get("comparison_lover"): context_parts.append("Karşılaştırma yapmayı seven bir kullanıcı") # Etkileşim stili interaction_style = profile_summary.get("interaction_style", "balanced") style_descriptions = { "analytical": "Detaylı ve analitik bilgi bekleyen", "budget_conscious": "Bütçe odaklı ve ekonomik seçenekleri arayan", "technical": "Teknik özellikler ve spesifikasyonlarla ilgilenen", "decisive": "Hızlı karar veren ve özet bilgi isteyen", "balanced": "Dengeli yaklaşım sergileyen" } context_parts.append(f"{style_descriptions.get(interaction_style, 'balanced')} bir kullanıcı") if context_parts: return f"Kullanıcı profili: {'. '.join(context_parts)}. Bu bilgileri göz önünde bulundurarak cevap ver." return "" def create_personalized_response(personalized_data, profile_summary): """Kişiselleştirilmiş öneri cevabı oluştur""" response_parts = [] # Kullanıcı stiline göre selamlama interaction_style = profile_summary.get("interaction_style", "balanced") if interaction_style == "analytical": response_parts.append("🔍 Profilinizi analiz ederek sizin için en uygun seçenekleri belirledim:") elif interaction_style == "budget_conscious": response_parts.append("💰 Bütçenize uygun en iyi seçenekleri hazırladım:") elif interaction_style == "technical": response_parts.append("⚙️ Teknik tercihlerinize göre önerilerim:") else: response_parts.append("🎯 Size özel seçtiklerim:") # Önerileri listele recommendations = personalized_data.get("recommendations", [])[:3] # İlk 3 öneri if recommendations: response_parts.append("\n") for i, product in enumerate(recommendations, 1): name, item_info, full_name = product price = item_info[1] if len(item_info) > 1 else "Fiyat yok" response_parts.append(f"**{i}. {full_name}**") response_parts.append(f"💰 Fiyat: {price} TL") response_parts.append("") # Profil bazlı açıklama preferences = profile_summary.get("preferences", {}) if preferences.get("categories"): category = preferences["categories"][0] response_parts.append(f"Bu öneriler {category} kategorisindeki ilginizi ve tercihlerinizi dikkate alarak hazırlandı.") return "\n".join(response_parts) def split_long_message(message, max_length=1600): """Uzun mesajları WhatsApp için uygun parçalara böler""" if len(message) <= max_length: return [message] parts = [] remaining = message while len(remaining) > max_length: cut_point = max_length # Geriye doğru git ve uygun kesme noktası ara for i in range(max_length, max_length - 200, -1): if i < len(remaining) and remaining[i] in ['.', '!', '?', '\n']: cut_point = i + 1 break elif i < len(remaining) and remaining[i] in [' ', ',', ';']: cut_point = i parts.append(remaining[:cut_point].strip()) remaining = remaining[cut_point:].strip() if remaining: parts.append(remaining) return parts # =============================== # HAFIZA SİSTEMİ SONU # =============================== # WhatsApp mesajı işleme (eski fonksiyon - yedek için) def process_whatsapp_message(user_message): try: system_messages = get_system_messages() # 🔍 BF Space: Use improved product search if available (backup function) product_found_improved = False if USE_IMPROVED_SEARCH and improved_whatsapp_bot: try: product_result = improved_whatsapp_bot.process_message(user_message) if product_result['is_product_query'] and product_result['response']: # Check if user is asking about specific warehouse/store location if any(keyword in user_message.lower() for keyword in ['mağaza', 'mağazada', 'nerede', 'hangi mağaza', 'şube']): # Get warehouse stock info for the found products if product_result['products_found']: warehouse_info_parts = [] for product in product_result['products_found'][:2]: # Max 2 products product_name = product[2] # Full product name warehouse_stock = get_warehouse_stock(product_name) if warehouse_stock: warehouse_info_parts.append(f"{product_name} mağaza stogu:") warehouse_info_parts.extend(warehouse_stock) warehouse_info_parts.append("") if warehouse_info_parts: warehouse_response = "\n".join(warehouse_info_parts) system_messages.append({ "role": "system", "content": f"MAĞAZA STOK BİLGİSİ (BF Space Backup):\n{warehouse_response}\n\nSADECE bu bilgileri kullanarak kullanıcıya yardımcı ol." }) product_found_improved = True if not product_found_improved: system_messages.append({ "role": "system", "content": f"ÜRÜN BİLGİSİ (BF Space Backup):\n{product_result['response']}\n\nSADECE bu bilgileri kullanarak kullanıcıya yardımcı ol. Bu bilgiler dışında ek bilgi ekleme." }) product_found_improved = True except Exception as e: logger.error(f"BF Space backup: Improved search error: {e}") # Fallback to basic search if not product_found_improved: # Ürün bilgilerini kontrol et (basic search) input_words = user_message.lower().split() for product_info in products: if product_info[0] in input_words: if product_info[1][0] == "stokta": normal_price = f"Fiyat: {product_info[1][1]} TL" if product_info[1][3]: eft_price = f"Havale: {product_info[1][3]} TL" price_info = f"{normal_price}, {eft_price}" else: price_info = normal_price new_msg = f"{product_info[2]} {product_info[1][0]} - {price_info}" else: new_msg = f"{product_info[2]} {product_info[1][0]}" system_messages.append({"role": "system", "content": new_msg}) break messages = system_messages + [{"role": "user", "content": user_message}] if not OPENAI_API_KEY: return "OpenAI API anahtarı eksik. Lütfen environment variables'ları kontrol edin." payload = { "model": "gpt-5-chat-latest", "messages": messages, "temperature": 0, # Deterministik cevaplar için "max_tokens": 800, "stream": False, "top_p": 0.1, # Daha tutarlı cevaplar için düşük değer "frequency_penalty": 0.1, # Tekrarları azaltmak için "presence_penalty": 0 # Yeni konulara açık olması için } headers = { "Content-Type": "application/json", "Authorization": f"Bearer {OPENAI_API_KEY}" } response = requests.post(API_URL, headers=headers, json=payload) if response.status_code == 200: result = response.json() return result['choices'][0]['message']['content'] else: print(f"OpenAI API Error: {response.status_code} - {response.text}") return f"API hatası: {response.status_code}. Lütfen daha sonra tekrar deneyin." except Exception as e: print(f"❌ WhatsApp mesaj işleme hatası: {e}") import traceback traceback.print_exc() logger.error(f"Detailed error: {str(e)}") logger.error(f"Error type: {type(e).__name__}") return "Teknik bir sorun oluştu. Lütfen daha sonra tekrar deneyin." # FastAPI uygulaması app = FastAPI() @app.post("/whatsapp-webhook") async def whatsapp_webhook(request: Request): try: form_data = await request.form() from_number = form_data.get('From') to_number = form_data.get('To') message_body = form_data.get('Body') message_status = form_data.get('MessageStatus') # Medya içeriği kontrolü num_media = form_data.get('NumMedia', '0') media_urls = [] media_types = [] # Medya varsa URL'leri topla if num_media and int(num_media) > 0: for i in range(int(num_media)): media_url = form_data.get(f'MediaUrl{i}') media_type = form_data.get(f'MediaContentType{i}') if media_url: media_urls.append(media_url) media_types.append(media_type) logger.info(f"📸 Medya alındı: {media_type} - {media_url[:100]}...") print(f"📱 Webhook - From: {from_number}, Body: {message_body}, Status: {message_status}") # Durum güncellemelerini ignore et if message_status in ['sent', 'delivered', 'read', 'failed']: return {"status": "ignored", "message": f"Status: {message_status}"} # Giden mesajları ignore et if to_number != TWILIO_WHATSAPP_NUMBER: return {"status": "ignored", "message": "Outgoing message"} # Media Queue V2 İşleme if USE_MEDIA_QUEUE: if media_urls: # Medya mesajı geldi logger.info(f"📸 Media Queue V2: Medya alındı - {from_number}") # Media Queue'ya ekle ve bekleme mesajı al wait_message = media_queue.handle_media( from_number, media_urls, media_types, message_body or "" ) # Bekleme mesajını gönder if twilio_client: twilio_client.messages.create( messaging_service_sid=TWILIO_MESSAGING_SERVICE_SID, body=wait_message, to=from_number ) logger.info(f"📤 Bekleme mesajı gönderildi: {wait_message}") return {"status": "media_queued", "message": wait_message} else: # Metin mesajı geldi - cache'de medya var mı kontrol et combined_text, cached_media_urls, cached_media_types = media_queue.handle_text(from_number, message_body) if combined_text and cached_media_urls: # Medya + metin birleştirildi logger.info(f"✅ Media Queue V2: Birleştirildi - {from_number}") logger.info(f" Birleşik mesaj: {combined_text[:100]}...") logger.info(f" Medya sayısı: {len(cached_media_urls)}") # Birleştirilmiş mesajı işle message_body = combined_text media_urls = cached_media_urls media_types = cached_media_types # Aşağıdaki normal akışa devam et else: # Normal metin mesajı, cache'de medya yok logger.info(f"💬 Media Queue V2: Normal metin - {from_number}") # Normal akışa devam et # Boş mesaj kontrolü if not message_body or message_body.strip() == "": if not media_urls: # Medya da yoksa ignore et return {"status": "ignored", "message": "Empty message"} print(f"✅ MESAJ ALINDI: {from_number} -> {message_body}") if not twilio_client: return {"status": "error", "message": "Twilio yapılandırması eksik"} # HAFIZALİ MESAJ İŞLEME - Medya desteği ile if media_urls: # Medya varsa, görsel analiz yap ai_response = process_whatsapp_message_with_media(message_body, from_number, media_urls, media_types) else: # Normal metin mesajı işle ai_response = process_whatsapp_message_with_memory(message_body, from_number) # Mesajı parçalara böl message_parts = split_long_message(ai_response, max_length=1600) sent_messages = [] # Her parçayı sırayla gönder for i, part in enumerate(message_parts): if len(message_parts) > 1: if i == 0: part = f"{part}\n\n(1/{len(message_parts)})" elif i == len(message_parts) - 1: part = f"({i+1}/{len(message_parts)})\n\n{part}" else: part = f"({i+1}/{len(message_parts)})\n\n{part}" # WhatsApp'a gönder message = twilio_client.messages.create( messaging_service_sid=TWILIO_MESSAGING_SERVICE_SID, body=part, to=from_number ) sent_messages.append(message.sid) if i < len(message_parts) - 1: import time time.sleep(0.5) print(f"✅ {len(message_parts)} PARÇA GÖNDERİLDİ") # Debug için mevcut kategoriyi logla context = get_conversation_context(from_number) if context.get("current_category"): print(f"💭 Aktif kategori: {context['current_category']}") return { "status": "success", "message_parts": len(message_parts), "message_sids": sent_messages, "current_category": context.get("current_category") } except Exception as e: print(f"❌ Webhook hatası: {str(e)}") return {"status": "error", "message": str(e)} @app.get("/") async def root(): return {"message": "Trek WhatsApp Bot çalışıyor!", "status": "active"} # Hafızayı temizleme endpoint'i @app.get("/clear-memory/{phone_number}") async def clear_memory(phone_number: str): """Belirli bir telefon numarasının hafızasını temizle""" if phone_number in conversation_memory: del conversation_memory[phone_number] return {"status": "success", "message": f"{phone_number} hafızası temizlendi"} return {"status": "info", "message": "Hafıza bulunamadı"} # Mehmet Bey bildirimlerini görüntüleme endpoint'i @app.get("/mehmet-bey-notifications") async def view_mehmet_bey_notifications(): """Mehmet Bey için kaydedilen bildirimleri görüntüle""" import json from datetime import datetime, timedelta try: with open("mehmet_bey_notifications.json", "r") as f: notifications = json.load(f) # Son 24 saatin bildirimlerini filtrele now = datetime.now() recent_notifications = [] for notif in notifications: notif_time = datetime.fromisoformat(notif["timestamp"]) if now - notif_time < timedelta(hours=24): recent_notifications.append(notif) # HTML formatında döndür html_content = """ Mehmet Bey Bildirimleri

🔔 Mehmet Bey Bildirim Sistemi

📊 Toplam: """ + str(len(notifications)) + """ bildirim | 🕐 Son 24 saat: """ + str(len(recent_notifications)) + """ bildirim
""" # Son 20 bildirimi göster (en yeniden eskiye) for notif in reversed(notifications[-20:]): timestamp = notif.get('timestamp', '') action = notif.get('action', 'info') product = notif.get('product_name', 'Belirtilmemiş') customer = notif.get('customer_phone', '').replace('whatsapp:', '') message = notif.get('formatted_message', '') # CSS class belirleme urgency_class = '' if 'reserve' in action or 'ayırt' in message.lower(): urgency_class = 'urgent' elif 'price' in action or 'stock' in action: urgency_class = 'medium' action_class = action html_content += f'''
⏰ {timestamp}
{action.upper()} {product}
📱 Müşteri: {customer}
{message}
''' html_content += """ """ from fastapi.responses import HTMLResponse return HTMLResponse(content=html_content) except FileNotFoundError: return HTMLResponse(content="""

📭 Henüz bildirim yok

Müşteri mesajları geldiğinde burada görünecek.

""") except Exception as e: return {"status": "error", "message": str(e)} # Tüm hafızayı görme endpoint'i @app.get("/debug-memory") async def debug_memory(): """Tüm hafızayı görüntüle (debug için)""" memory_info = {} for phone, context in conversation_memory.items(): memory_info[phone] = { "current_category": context.get("current_category"), "message_count": len(context.get("messages", [])), "last_activity": str(context.get("last_activity")) } return {"conversation_memory": memory_info} # Profil bilgilerini görme endpoint'i @app.get("/debug-profile/{phone_number}") async def debug_profile(phone_number: str): """Belirli kullanıcının profil bilgilerini görüntüle""" profile_summary = get_user_profile_summary(phone_number) return {"phone_number": phone_number, "profile": profile_summary} # Tüm profilleri görme endpoint'i @app.get("/debug-profiles") async def debug_profiles(): """Tüm kullanıcı profillerini görüntüle""" from whatsapp_passive_profiler import passive_profiler all_profiles = {} for phone_number in passive_profiler.profiles.keys(): all_profiles[phone_number] = get_user_profile_summary(phone_number) return {"profiles": all_profiles} @app.get("/health") async def health(): return { "status": "healthy", "twilio_configured": twilio_client is not None, "openai_configured": OPENAI_API_KEY is not None, "products_loaded": len(products), "webhook_endpoint": "/whatsapp-webhook" } @app.get("/test-madone") async def test_madone(): """Test MADONE search directly""" from smart_warehouse_with_price import get_warehouse_stock_smart_with_price # Set a test API key if needed import os if not os.getenv("OPENAI_API_KEY"): return {"error": "No OPENAI_API_KEY set"} try: result = get_warehouse_stock_smart_with_price("madone sl 6") return { "query": "madone sl 6", "result": result if result else "No result", "api_key_set": bool(os.getenv("OPENAI_API_KEY")) } except Exception as e: return {"error": str(e), "type": type(e).__name__} @app.post("/test-vision") async def test_vision(request: Request): """Test vision capabilities with a sample image URL""" try: data = await request.json() image_url = data.get("image_url") text = data.get("text", "Bu görselde ne var?") if not image_url: return {"error": "image_url is required"} # Test vision API messages = [ { "role": "system", "content": "Sen bir bisiklet uzmanısın. Görselleri analiz et ve detaylı bilgi ver." }, { "role": "user", "content": [ {"type": "text", "text": text}, {"type": "image_url", "image_url": {"url": image_url}} ] } ] payload = { "model": "gpt-5-chat-latest", "messages": messages, "temperature": 0, # Deterministik cevaplar için "max_tokens": 500, "stream": False, "top_p": 0.1, # Daha tutarlı cevaplar için düşük değer "frequency_penalty": 0.1, # Tekrarları azaltmak için "presence_penalty": 0 # Yeni konulara açık olması için } headers = { "Content-Type": "application/json", "Authorization": f"Bearer {OPENAI_API_KEY}" } response = requests.post(API_URL, headers=headers, json=payload) if response.status_code == 200: result = response.json() return { "success": True, "response": result['choices'][0]['message']['content'], "model": result.get('model', 'unknown') } else: return { "success": False, "error": response.text, "status_code": response.status_code } except Exception as e: return {"error": str(e), "type": type(e).__name__} if __name__ == "__main__": import uvicorn print("🚀 Trek WhatsApp Bot başlatılıyor...") uvicorn.run(app, host="0.0.0.0", port=7860)