File size: 78,233 Bytes
6ea7409 944ac8b 6ea7409 944ac8b 6ea7409 944ac8b 6ea7409 944ac8b 6ea7409 944ac8b 6ea7409 944ac8b 6ea7409 944ac8b 6ea7409 944ac8b 6ea7409 944ac8b 6ea7409 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 600 601 602 603 604 605 606 607 608 609 610 611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637 638 639 640 641 642 643 644 645 646 647 648 649 650 651 652 653 654 655 656 657 658 659 660 661 662 663 664 665 666 667 668 669 670 671 672 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 861 862 863 864 865 866 867 868 869 870 871 872 873 874 875 876 877 878 879 880 881 882 883 884 885 886 887 888 889 890 891 892 893 894 895 896 897 898 899 900 901 902 903 904 905 906 907 908 909 910 911 912 913 914 915 916 917 918 919 920 921 922 923 924 925 926 927 928 929 930 931 932 933 934 935 936 937 938 939 940 941 942 943 944 945 946 947 948 949 950 951 952 953 954 955 956 957 958 959 960 961 962 963 964 965 966 967 968 969 970 971 972 973 974 975 976 977 978 979 980 981 982 983 984 985 986 987 988 989 990 991 992 993 994 995 996 997 998 999 1000 1001 1002 1003 1004 1005 1006 1007 1008 1009 1010 1011 1012 1013 1014 1015 1016 1017 1018 1019 1020 1021 1022 1023 1024 1025 1026 1027 1028 1029 1030 1031 1032 1033 1034 1035 1036 1037 1038 1039 1040 1041 1042 1043 1044 1045 1046 1047 1048 1049 1050 1051 1052 1053 1054 1055 1056 1057 1058 1059 1060 1061 1062 1063 1064 1065 1066 1067 1068 1069 1070 1071 1072 1073 1074 1075 1076 1077 1078 1079 1080 1081 1082 1083 1084 1085 1086 1087 1088 1089 1090 1091 1092 1093 1094 1095 1096 1097 1098 1099 1100 1101 1102 1103 1104 1105 1106 1107 1108 1109 1110 1111 1112 1113 1114 1115 1116 1117 1118 1119 1120 1121 1122 1123 1124 1125 1126 1127 1128 1129 1130 1131 1132 1133 1134 1135 1136 1137 1138 1139 1140 1141 1142 1143 1144 1145 1146 1147 1148 1149 1150 1151 1152 1153 1154 1155 1156 1157 1158 1159 1160 1161 1162 1163 1164 1165 1166 1167 1168 1169 1170 1171 1172 1173 1174 1175 1176 1177 1178 1179 1180 1181 1182 1183 1184 1185 1186 1187 1188 1189 1190 1191 1192 1193 1194 1195 1196 1197 1198 1199 1200 1201 1202 1203 1204 1205 1206 1207 1208 1209 1210 1211 1212 1213 1214 1215 1216 1217 1218 1219 1220 1221 1222 1223 1224 1225 1226 1227 1228 1229 1230 1231 1232 1233 1234 1235 1236 1237 1238 1239 1240 1241 1242 1243 1244 1245 1246 1247 1248 1249 1250 1251 1252 1253 1254 1255 1256 1257 1258 1259 1260 1261 1262 1263 1264 1265 1266 1267 1268 1269 1270 1271 1272 1273 1274 1275 1276 1277 1278 1279 1280 1281 1282 1283 1284 1285 1286 1287 1288 1289 1290 1291 1292 1293 1294 1295 1296 1297 1298 1299 1300 1301 1302 1303 1304 1305 1306 1307 1308 1309 1310 1311 1312 1313 1314 1315 1316 1317 1318 1319 1320 1321 1322 1323 1324 1325 1326 1327 1328 1329 1330 1331 1332 1333 1334 1335 1336 1337 1338 1339 1340 1341 1342 1343 1344 1345 1346 1347 1348 1349 1350 1351 1352 1353 1354 1355 1356 1357 1358 1359 1360 1361 1362 1363 1364 1365 1366 1367 1368 1369 1370 1371 1372 1373 1374 1375 1376 1377 1378 1379 1380 1381 1382 1383 1384 1385 1386 1387 1388 1389 1390 1391 1392 1393 1394 1395 1396 1397 1398 1399 1400 1401 1402 1403 1404 1405 1406 1407 1408 1409 1410 1411 1412 1413 1414 1415 1416 1417 1418 1419 1420 1421 1422 1423 1424 1425 1426 1427 1428 1429 1430 1431 1432 1433 1434 1435 1436 1437 1438 1439 1440 1441 1442 1443 1444 1445 1446 1447 1448 1449 1450 1451 1452 1453 1454 1455 1456 1457 1458 1459 1460 1461 1462 1463 1464 1465 1466 1467 1468 1469 1470 1471 1472 1473 1474 1475 1476 1477 1478 1479 1480 1481 1482 1483 1484 1485 1486 1487 1488 1489 1490 1491 1492 1493 1494 1495 1496 1497 1498 1499 1500 1501 1502 1503 1504 1505 1506 1507 1508 1509 1510 1511 1512 1513 1514 1515 1516 1517 1518 1519 1520 1521 1522 1523 1524 1525 1526 1527 1528 1529 1530 1531 1532 1533 1534 1535 1536 1537 1538 1539 1540 1541 1542 1543 1544 1545 1546 1547 1548 1549 1550 1551 1552 1553 1554 1555 1556 1557 1558 1559 1560 1561 1562 1563 1564 1565 1566 1567 1568 1569 1570 1571 1572 1573 1574 1575 1576 1577 1578 1579 1580 1581 1582 1583 1584 1585 1586 1587 1588 1589 1590 1591 1592 1593 1594 1595 1596 1597 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622 1623 1624 1625 1626 1627 1628 1629 1630 1631 1632 1633 1634 1635 1636 1637 1638 1639 1640 1641 1642 1643 1644 1645 1646 1647 1648 1649 1650 1651 1652 1653 1654 1655 1656 1657 1658 1659 1660 1661 1662 1663 1664 1665 1666 1667 1668 1669 1670 1671 1672 1673 1674 1675 1676 1677 1678 1679 1680 1681 1682 1683 1684 1685 1686 1687 1688 1689 1690 1691 1692 1693 1694 1695 1696 1697 1698 1699 1700 1701 1702 1703 1704 1705 1706 1707 1708 1709 1710 1711 1712 1713 1714 1715 1716 1717 1718 1719 1720 1721 1722 1723 1724 1725 1726 1727 1728 1729 1730 1731 1732 1733 1734 1735 1736 1737 1738 1739 1740 1741 1742 1743 1744 1745 1746 1747 1748 1749 1750 1751 1752 1753 1754 1755 1756 1757 1758 1759 1760 1761 1762 1763 1764 1765 1766 1767 1768 1769 1770 1771 1772 1773 1774 1775 1776 1777 1778 1779 1780 1781 1782 1783 1784 1785 1786 1787 1788 1789 1790 1791 1792 1793 1794 1795 1796 1797 1798 1799 1800 1801 1802 1803 1804 1805 1806 1807 1808 1809 1810 1811 1812 1813 |
# -*- coding: utf-8 -*-
"""
Trek WhatsApp AI Asistani - Hybrid Model Version
Gorsel varsa: GPT-4o (vision)
Metin varsa: GPT-5.2 (daha akilli)
"""
import os
import json
import re
import requests
import xml.etree.ElementTree as ET
import warnings
import time
import threading
import datetime
import unicodedata
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 moduller - Basit sistem
from prompts import get_active_prompts
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 BASA EKLENDI
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
warnings.simplefilter('ignore')
# ===============================
# BLOCKLIST & RATE LIMITER
# ===============================
# Engellenen numaralar - mesajlari sessizce ignore edilir (0 token)
BLOCKED_NUMBERS = {
"whatsapp:+905376627860", # Spam - sonsuz sacma soru
}
# Rate limiter - dakikada max mesaj sayisi (tum numaralar icin)
RATE_LIMIT_PER_MINUTE = 10
rate_limit_tracker = {} # {phone_number: [timestamp1, timestamp2, ...]}
def is_blocked(phone_number):
"""Numara blocklist'te mi kontrol et"""
if phone_number in BLOCKED_NUMBERS:
logger.warning(f"🚫 ENGELLENEN NUMARA: {phone_number} - mesaj ignore edildi")
return True
return False
def is_rate_limited(phone_number):
"""Dakikada cok fazla mesaj atan numarayi gecici engelle"""
now = time.time()
if phone_number not in rate_limit_tracker:
rate_limit_tracker[phone_number] = []
# Son 60 saniyedeki mesajlari filtrele
rate_limit_tracker[phone_number] = [
t for t in rate_limit_tracker[phone_number] if now - t < 60
]
if len(rate_limit_tracker[phone_number]) >= RATE_LIMIT_PER_MINUTE:
logger.warning(f"⏱️ RATE LIMIT: {phone_number} - dakikada {RATE_LIMIT_PER_MINUTE}+ mesaj")
return True
rate_limit_tracker[phone_number].append(now)
return False
# ===============================
# MODEL KONFIGURASYONU
# ===============================
MODEL_CONFIG = {
"vision": "gpt-4o", # Gorsel analizi icin (Vision destekli)
"text": "gpt-5.2-chat-latest", # Metin icin (en akilli model)
"fallback": "gpt-4o" # Yedek model (GPT-5.2 hata verirse)
}
# Model secimi icin yardimci fonksiyon
def get_model_for_request(has_media=False):
"""
Istek tipine gore uygun modeli sec
has_media=True -> GPT-4o (vision destekli)
has_media=False -> GPT-5.2 (daha akilli metin isleme)
"""
if has_media:
logger.info(f"🖼️ Gorsel tespit edildi -> Model: {MODEL_CONFIG['vision']}")
return MODEL_CONFIG["vision"]
else:
logger.info(f"📝 Metin mesaji -> Model: {MODEL_CONFIG['text']}")
return MODEL_CONFIG["text"]
# ===============================
# API AYARLARI
# ===============================
API_URL = "https://api.openai.com/v1/chat/completions"
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
logger.info(f"OpenAI API Key var mi: {'Evet' if OPENAI_API_KEY else 'Hayir'}")
# Twilio WhatsApp ayarlari
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 numaramiz
logger.info(f"Twilio SID var mi: {'Evet' if TWILIO_ACCOUNT_SID else 'Hayir'}")
logger.info(f"Twilio Auth Token var mi: {'Evet' if TWILIO_AUTH_TOKEN else 'Hayir'}")
logger.info(f"Messaging Service SID var mi: {'Evet' if TWILIO_MESSAGING_SERVICE_SID else 'Hayir'}")
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 basariyla olusturuldu!")
except Exception as e:
logger.error(f"❌ Twilio client hatasi: {e}")
twilio_client = None
# ===============================
# GPT-5 SMART WAREHOUSE
# ===============================
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")
# 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")
# ===============================
# STOK API ENTEGRASYONU
# ===============================
STOCK_API_BASE = "https://video.trek-turkey.com/bizimhesap-proxy.php"
# Stock cache (5 dakikalik cache)
stock_cache = {}
CACHE_DURATION = 300 # 5 dakika (saniye cinsinden)
# Turkish character normalization
turkish_map = {'ı': 'i', 'ğ': 'g', 'ü': 'u', 'ş': 's', 'ö': 'o', 'ç': 'c', 'İ': 'i', 'I': 'i'}
def normalize_turkish(text):
"""Turkce karakterleri normalize et"""
if not text:
return ""
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.lower()
def fetch_warehouse_inventory(warehouse, product_name, search_terms):
"""Tek bir magazanin stok bilgisini al"""
try:
warehouse_id = warehouse['id']
warehouse_name = warehouse['title']
# DSW'yi ayri tut (gelecek stok icin)
is_dsw = 'DSW' in warehouse_name or 'ÖN SİPARİŞ' in warehouse_name.upper()
# Magaza stoklarini 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 yanitini kontrol et
if 'data' not in inventory_data or 'inventory' not in inventory_data['data']:
return None
products_list = inventory_data['data']['inventory']
# Beden terimleri kontrolu
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 mi 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
# Eger sadece beden sorgusu varsa (or: "m", "xl")
is_only_size_query = len(search_terms) == 1 and has_size_query
# Urunu ara
warehouse_variants = []
dsw_stock_count = 0
for product in products_list:
product_title = normalize_turkish(product.get('title', '')).lower()
original_title = product.get('title', '')
# Eger sadece beden sorgusu ise
if is_only_size_query:
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 urun aramasi
if has_size_query:
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)
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
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:
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")
# Sonuc dondur
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 gercek zamanli stok bilgisini cek - Paralel versiyon with cache"""
try:
# Cache kontrolu
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]
if current_time - cached_time < CACHE_DURATION:
logger.info(f"Cache'den donduruluyor: {product_name}")
return cached_data
# Once magaza 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"Magaza listesi alinamadi: {warehouses_response.status_code}")
return None
warehouses_data = warehouses_response.json()
if 'data' not in warehouses_data or 'warehouses' not in warehouses_data['data']:
logger.error("Magaza verisi bulunamadi")
return None
warehouses = warehouses_data['data']['warehouses']
# Urun adini normalize et
search_terms = normalize_turkish(product_name).lower().split()
logger.info(f"Aranan urun: {product_name} -> {search_terms}")
stock_info = {}
total_dsw_stock = 0
total_stock = 0
# Paralel olarak tum magazalari sorgula
with ThreadPoolExecutor(max_workers=10) as executor:
futures = {
executor.submit(fetch_warehouse_inventory, warehouse, product_name, search_terms): warehouse
for warehouse in warehouses
}
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
# Sonucu olustur
if not stock_info:
if total_dsw_stock > 0:
result = f"{product_name}: Su anda magazalarda stokta yok, ancak yakinda gelecek. On siparis verebilirsiniz."
else:
result = f"{product_name}: Su anda hicbir magazada stokta bulunmuyor."
else:
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}")
if total_stock > 0:
prompt_lines.append(f"✓ Urun 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 hatasi: {e}")
return None
def is_stock_query(message):
"""Mesajin stok sorgusu olup olmadigini kontrol et - Basit yedek kontrol"""
# Bu fonksiyon artik sadece yedek olarak kullaniliyor
# Ana tespit Intent Analyzer tarafindan yapiliyor
basic_keywords = ['stok', 'stock', 'var mı', 'mevcut']
message_lower = message.lower()
return any(keyword in message_lower for keyword in basic_keywords)
# ===============================
# MAGAZA STOK BILGISI CEKME
# ===============================
def get_warehouse_stock(product_name):
"""B2B API'den magaza stok bilgilerini cek - 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):
if all(isinstance(item, str) for item in gpt5_result):
return gpt5_result
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}")
# 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)
# 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 = []
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]
is_size_color_query = len(variant_words) > 0 and len(search_words) <= 4
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())
product_name_matches = True
if product_words:
product_name_matches = all(word in normalized_product_name for word in product_words)
if product_name_matches:
if variant_elem is not None and variant_elem.text:
variant_text = normalize_turkish(variant_elem.text.lower().replace('-', ' '))
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:
is_size_color_query = False
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()
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))
if not candidates:
candidates = exact_matches if exact_matches else []
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()
common_words = set(search_words) & set(xml_words)
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)))
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]
warehouse_stock_map = {}
for product, xml_name, _ in candidates:
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:
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:
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 ["Hicbir magazada stokta bulunmuyor"]
except Exception as e:
logger.error(f"Magaza stok bilgisi cekme hatasi: {e}")
return None
# ===============================
# TREK BISIKLET URUNLERINI CEKME
# ===============================
try:
url = 'https://www.trekbisiklet.com.tr/output/8582384479'
response = requests.get(url, verify=False, timeout=10)
root = ET.fromstring(response.content)
all_items = root.findall('item')
products = []
for item in all_items:
stock_number = 0
stock_amount = "stokta degil"
price = ""
price_eft = ""
product_link = ""
picture_url = ""
category_tree = ""
category_label = ""
stock_code = ""
root_product_stock_code = ""
is_option_of_product = "0"
is_optioned_product = "0"
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 KONTROLU - SAYISAL KARSILASTIRMA
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 degil"
except (ValueError, TypeError):
stock_number = 0
stock_amount = "stokta degil"
# Urun linki - HER URUN ICIN AL
link_element = item.find('productLink')
product_link = link_element.text if link_element is not None and link_element.text else ""
# Urun resmi - HER URUN ICIN AL
picture_element = item.find('picture1Path')
picture_url = picture_element.text if picture_element is not None and picture_element.text else ""
# Kategori bilgileri - HER URUN ICIN AL
category_tree_element = item.find('categoryTree')
category_tree = category_tree_element.text if category_tree_element is not None and category_tree_element.text else ""
category_label_element = item.find('productCategoryLabel')
category_label = category_label_element.text if category_label_element is not None and category_label_element.text else ""
# Stock Code (SKU) - HER URUN ICIN AL
stock_code_element = item.find('stockCode')
stock_code = stock_code_element.text if stock_code_element is not None and stock_code_element.text else ""
# Variant/main product iliski alanlari
root_product_stock_code_element = item.find('rootProductStockCode')
root_product_stock_code = root_product_stock_code_element.text if root_product_stock_code_element is not None and root_product_stock_code_element.text else ""
is_option_of_product_element = item.find('isOptionOfAProduct')
is_option_of_product = is_option_of_product_element.text if is_option_of_product_element is not None and is_option_of_product_element.text else "0"
is_optioned_product_element = item.find('isOptionedProduct')
is_optioned_product = is_optioned_product_element.text if is_optioned_product_element is not None and is_optioned_product_element.text else "0"
# Stokta olan urunler icin 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 fiyati
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 ""
final_price_str = price_str
if price_rebate_str:
try:
normal_price = float(price_str)
rebate_price = float(price_rebate_str)
if rebate_price < normal_price:
final_price_str = price_rebate_str
except (ValueError, TypeError):
final_price_str = price_str
# EFT fiyati
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 ""
# Fiyat formatting
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 = ""
# Urun bilgilerini tuple olarak olustur
item_info = (stock_amount, price, product_link, price_eft, str(stock_number),
picture_url, category_tree, category_label, stock_code,
root_product_stock_code, is_option_of_product, is_optioned_product)
products.append((name, item_info, full_name))
logger.info(f"✅ {len(products)} urun yuklendi")
except Exception as e:
logger.error(f"❌ Urun yukleme hatasi: {e}")
import traceback
traceback.print_exc()
products = []
# ===============================
# SISTEM MESAJLARI
# ===============================
def get_system_messages():
"""Sistem mesajlarini yukle - Moduler prompts'tan"""
try:
return get_active_prompts()
except:
# Fallback sistem mesajlari
return [
{"role": "system", "content": "Sen Trek bisiklet uzmani AI asistanisin. Trek ve Electra bisikletler konusunda uzmansin. Stokta bulunan urunlerin fiyat bilgilerini verebilirsin."}
]
# ===============================
# SOHBET HAFIZASI SISTEMI
# ===============================
conversation_memory = {}
def get_conversation_context(phone_number):
"""Kullanicinin sohbet gecmisini getir"""
if phone_number not in conversation_memory:
conversation_memory[phone_number] = {
"messages": [],
"current_category": None,
"current_product": None,
"current_product_link": None,
"current_product_price": None,
"last_activity": None
}
return conversation_memory[phone_number]
def add_to_conversation(phone_number, user_message, ai_response):
"""Sohbet gecmisine ekle"""
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 mesaji 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):
"""Konusulan kategoriyi ve tam urun adini 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
# TAM URUN ADINI CIKAR - ornegin "Marlin 5", "Madone SLR 9"
# Model numarasini da yakala
import re
# Keyword + sayi pattern'i ara (ornegin "marlin 5", "madone slr 9")
pattern = rf'{keyword}\s*\+?\s*(?:slr\s*)?(\d+)?'
match = re.search(pattern, user_lower)
if match:
model_num = match.group(1)
if model_num:
# Tam urun adi: "marlin 5" veya "madone slr 9"
full_product = match.group(0).strip()
context["current_product"] = full_product
else:
# Sadece kategori adi
context["current_product"] = keyword
else:
context["current_product"] = keyword
return category
return context.get("current_category")
def build_context_messages(phone_number, current_message):
"""Sohbet gecmisi ile sistem mesajlarini olustur"""
context = get_conversation_context(phone_number)
system_messages = get_system_messages()
# Mevcut kategori varsa, sistem mesajina ekle - GUCLENDIRILMIS BAGLAIM
if context.get("current_category"):
cat = context['current_category'].upper()
category_msg = f"""KRITIK BAGLAIM BILGISI:
Musteri su anda {cat} modelleri hakkinda konusuyor.
Butun sorulari bu baglamda cevapla.
"Hangi model var", "stok var mi", "fiyat ne" gibi sorular {cat} icin sorulmus demektir.
DS, FX, Verve gibi BASKA kategorilerden bahsetme - sadece {cat} hakkinda konusuyoruz!"""
system_messages.append({"role": "system", "content": category_msg})
# Son konusulan urun bilgilerini ekle (link, fiyat sorulari icin)
if context.get("current_product"):
product_context = f"Son konusulan urun: {context['current_product']}"
if context.get("current_product_link"):
product_context += f"\nUrun linki: {context['current_product_link']}"
if context.get("current_product_price"):
product_context += f"\nUrun fiyati: {context['current_product_price']}"
system_messages.append({"role": "system", "content": product_context})
# Son 3 mesaj alisverisini ekle
recent_messages = context["messages"][-3:] if context["messages"] else []
all_messages = system_messages.copy()
# Gecmis mesajlari ekle
for msg in recent_messages:
all_messages.append({"role": "user", "content": msg["user"]})
all_messages.append({"role": "assistant", "content": msg["ai"]})
# Mevcut mesaji ekle
all_messages.append({"role": "user", "content": current_message})
return all_messages
# ===============================
# HYBRID MODEL MESAJ ISLEME
# ===============================
def extract_product_from_vision_response(response):
"""
GPT Vision yanitindan urun adini cikarir
Ornek: "Trek Domane+ SLR 7 AXS" -> "Domane+ SLR 7 AXS"
"""
import re
# Bilinen Trek model pattern'leri
patterns = [
# Trek Domane+ SLR 7 AXS gibi tam isimler
r'Trek\s+((?:Domane|Madone|Emonda|Marlin|Fuel|Rail|Powerfly|Checkpoint|FX|Verve|Dual\s*Sport|Procaliber|Supercaliber|Roscoe|Top\s*Fuel|Slash|Remedy|X-?Caliber|Allant)[+]?\s*(?:SLR|SL|Gen|EX|EXe)?\s*\d*\s*(?:AXS|Di2|eTap|Frameset)?)',
# Sadece model adi + numara
r'((?:Domane|Madone|Emonda|Marlin|Fuel|Rail|Powerfly|Checkpoint|FX|Verve|Dual\s*Sport|Procaliber|Supercaliber|Roscoe|Top\s*Fuel|Slash|Remedy|X-?Caliber|Allant)[+]?\s*(?:SLR|SL|Gen|EX|EXe)?\s*\d+\s*(?:AXS|Di2|eTap|Frameset)?)',
# Model + SLR/SL + numara
r'((?:Domane|Madone|Emonda)[+]?\s+(?:SLR|SL)\s*\d+)',
# Marlin + numara
r'(Marlin\s*\d+)',
# FX + numara
r'(FX\s*(?:Sport)?\s*\d+)',
]
response_lower = response.lower()
for pattern in patterns:
match = re.search(pattern, response, re.IGNORECASE)
if match:
product = match.group(1).strip()
# "Trek " prefix varsa kaldir
product = re.sub(r'^Trek\s+', '', product, flags=re.IGNORECASE)
return product
return None
def process_whatsapp_message_with_media(user_message, phone_number, media_urls, media_types):
"""
GORSEL MESAJ ISLEME - GPT-4o Vision kullanir
"""
try:
logger.info(f"🖼️ Gorsel analizi basliyor: {len(media_urls)} medya")
logger.info(f"📎 Medya URL'leri: {media_urls}")
logger.info(f"📎 Medya tipleri: {media_types}")
# Pasif profil analizi
try:
profile_analysis = analyze_user_message(phone_number, user_message)
logger.info(f"📊 Profil analizi: {phone_number} -> {profile_analysis}")
except:
pass
# Gorsel icin GPT-4o kullan
model = get_model_for_request(has_media=True)
# Sohbet gecmisi ile sistem mesajlarini olustur
messages = build_context_messages(phone_number, user_message if user_message else "Gonderilen gorseli analiz et")
# GPT-4o Vision icin mesaj hazirla
vision_message = {
"role": "user",
"content": []
}
# Metin mesaji 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 gorselde ne var? Eger bisiklet veya bisiklet parcasi ise detayli acikla."
})
# Medya URL'lerini isle
valid_images = 0
for i, media_url in enumerate(media_urls):
media_type = media_types[i] if i < len(media_types) else "image/jpeg"
# Sadece gorsel medyalari isle
if media_type and media_type.startswith('image/'):
try:
# Twilio medya URL'sini proxy uzerinden cevir
if 'api.twilio.com' in media_url:
import re
match = re.search(r'/Messages/([^/]+)/Media/([^/]+)', media_url)
if match:
message_sid = match.group(1)
media_sid = match.group(2)
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 olusturuldu: {proxy_url}")
# Proxy URL'sinin calisip calismadigini kontrol et
try:
test_response = requests.head(proxy_url, timeout=5, verify=False)
if test_response.status_code == 200:
vision_message["content"].append({
"type": "image_url",
"image_url": {"url": proxy_url}
})
valid_images += 1
logger.info(f"✅ Proxy URL gecerli: {proxy_url}")
else:
logger.error(f"❌ Proxy URL calismiyor: {test_response.status_code}")
vision_message["content"].append({
"type": "image_url",
"image_url": {"url": media_url}
})
valid_images += 1
except Exception as proxy_error:
logger.error(f"❌ Proxy test hatasi: {proxy_error}")
vision_message["content"].append({
"type": "image_url",
"image_url": {"url": media_url}
})
valid_images += 1
else:
logger.error(f"❌ Twilio URL parse edilemedi: {media_url}")
else:
vision_message["content"].append({
"type": "image_url",
"image_url": {"url": media_url}
})
valid_images += 1
logger.info(f"✅ Dogrudan URL eklendi: {media_url}")
except Exception as url_error:
logger.error(f"❌ URL isleme hatasi: {url_error}")
else:
logger.warning(f"⚠️ Gorsel olmayan medya atlandi: {media_type}")
# Hic gecerli gorsel yoksa
if valid_images == 0:
logger.error("❌ Hic gecerli gorsel bulunamadi")
return "Gonderdiginiz gorsel islenemedi. Lutfen farkli bir gorsel gonderin veya sorunuzu yazili olarak iletin."
logger.info(f"✅ {valid_images} gorsel islenecek")
# Son user mesajini vision mesajiyla degistir
messages = [msg for msg in messages if not (msg.get("role") == "user" and msg == messages[-1])]
messages.append(vision_message)
# Sistem mesajina bisiklet tanima talimati ekle
bike_recognition_prompt = {
"role": "system",
"content": """Gonderilen gorselleri dikkatle analiz et:
1. Eger bisiklet veya bisiklet parcasi goruyorsan, detaylica tanimla (marka, model, renk, beden, ozellikler)
2. Trek bisiklet ise modeli tahmin etmeye calis
3. Stok veya fiyat sorulursa, gorseldeki bisikletin ozelliklerini belirterek bilgi ver
4. Gorsel net degilse veya tanimlanamiyorsa, kullanicidan daha net bir gorsel istemek yerine, gorselde gorduklerini acikla
5. Eger gorsel bisikletle ilgili degilse, ne gordugunu kisaca acikla"""
}
messages.insert(0, bike_recognition_prompt)
if not OPENAI_API_KEY:
logger.error("❌ OpenAI API anahtari eksik")
return "Sistem hatasi olustu. Lutfen daha sonra tekrar deneyin."
logger.info(f"📤 GPT Vision API'ye gonderiliyor: {len(messages)} mesaj, {valid_images} gorsel")
payload = {
"model": model, # GPT-4o
"messages": messages,
"max_tokens": 800,
"temperature": 0.3
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {OPENAI_API_KEY}"
}
response = requests.post(API_URL, headers=headers, json=payload, timeout=30)
logger.info(f"📥 API yaniti: {response.status_code}")
if response.status_code == 200:
result = response.json()
ai_response = result['choices'][0]['message']['content']
logger.info(f"✅ Gorsel analizi basarili: {ai_response[:100]}...")
# KRITIK: Gorselden urun adini cikar ve GERCEK stok kontrolu yap
try:
from smart_warehouse_with_price import get_warehouse_stock
# GPT yanitindan urun adini cikar
product_name = extract_product_from_vision_response(ai_response)
if product_name:
logger.info(f"🔍 Gorselden tespit edilen urun: {product_name}")
# GERCEK stok kontrolu yap
stock_info = get_warehouse_stock(product_name)
if stock_info:
logger.info(f"✅ Stok bilgisi bulundu: {stock_info[:100]}...")
# GPT yanlis "stokta yok" dediyse duzelt
if "stokta bulunmuyor" in ai_response.lower() or "stokta yok" in ai_response.lower():
if "stokta bulunmuyor" not in stock_info.lower():
# Yanlis bilgiyi kaldir ve dogru stok bilgisini ekle
ai_response = re.sub(
r'[^.]*stok[^.]*bulunmuyor[^.]*[.]?',
'',
ai_response,
flags=re.IGNORECASE
)
ai_response = ai_response.strip()
# Stok bilgisini ekle (eger zaten yoksa)
if "Stok:" not in ai_response and "stokta" not in stock_info.lower():
ai_response = ai_response + "\n\n" + stock_info
elif "Stok:" not in ai_response:
ai_response = ai_response + "\n\n" + stock_info
else:
logger.info(f"⚠️ Urun icin stok bilgisi bulunamadi: {product_name}")
else:
logger.info("⚠️ Gorselden urun adi cikarilamadi")
except Exception as stock_error:
logger.error(f"❌ Vision stok kontrolu hatasi: {stock_error}")
# WhatsApp icin formatla
try:
formatted_response = extract_product_info_whatsapp(ai_response)
except:
formatted_response = ai_response
# Sohbet gecmisine ekle
add_to_conversation(phone_number, f"[Gorsel gonderildi] {user_message if user_message else ''}", formatted_response)
return formatted_response
else:
error_detail = response.text[:500] if response.text else "Detay yok"
logger.error(f"❌ OpenAI API Error: {response.status_code} - {error_detail}")
if response.status_code == 400:
return "Gorsel formati desteklenmiyor. Lutfen JPG veya PNG formatinda bir gorsel gonderin."
elif response.status_code == 413:
return "Gorsel boyutu cok buyuk. Lutfen daha kucuk bir gorsel gonderin."
elif response.status_code == 429:
return "Sistem su anda yogun. Lutfen birkac saniye sonra tekrar deneyin."
else:
return "Gorsel su anda analiz edilemiyor. Sorunuzu yazili olarak iletebilir misiniz?"
except requests.exceptions.Timeout:
logger.error("❌ API timeout hatasi")
return "Islem zaman asimina ugradi. Lutfen tekrar deneyin."
except Exception as e:
logger.error(f"❌ Medya isleme hatasi: {e}")
import traceback
traceback.print_exc()
return "Gorsel islenirken bir sorun olustu. Lutfen sorunuzu yazili olarak iletin veya farkli bir gorsel deneyin."
def process_whatsapp_message_with_memory(user_message, phone_number):
"""
METIN MESAJ ISLEME - GPT-5.2 kullanir (daha akilli)
"""
try:
# Metin icin GPT-5.2 kullan
model = get_model_for_request(has_media=False)
# Pasif profil analizi
try:
profile_analysis = analyze_user_message(phone_number, user_message)
logger.info(f"📊 Profil analizi: {phone_number}")
except:
pass
# 🔔 Yeni Magaza Bildirim Sistemi - Mehmet Bey'e otomatik bildirim
if USE_STORE_NOTIFICATION:
try:
should_notify_mehmet, notification_reason, urgency = should_notify_mehmet_bey(user_message)
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:
if intent_analysis:
product = intent_analysis.get("product") or "Belirtilmemis"
else:
context = get_conversation_context(phone_number)
product = context.get("current_category") or "Urun belirtilmemis"
if "rezervasyon" in notification_reason.lower() or urgency == "high":
action = "reserve"
elif "magaza" in notification_reason.lower() or "lokasyon" in notification_reason.lower():
action = "info"
elif "fiyat" in notification_reason.lower() or "odeme" in notification_reason.lower():
action = "price"
else:
action = "info"
additional_info = f"{notification_reason}\n\nMusteri Mesaji: '{user_message}'"
if urgency == "high":
additional_info = "⚠️ YUKSEK ONCELIK ⚠️\n" + additional_info
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 gonderildi!")
logger.info(f" 📍 Sebep: {notification_reason}")
logger.info(f" ⚡ Oncelik: {urgency}")
logger.info(f" 📦 Urun: {product}")
# TAKIP SISTEMINI KONTROL ET
if USE_FOLLOW_UP and follow_up_manager:
try:
follow_up_analysis = analyze_message_for_follow_up(user_message)
if follow_up_analysis and follow_up_analysis.get("needs_follow_up"):
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.get("follow_up_hours", 24),
notes=follow_up_analysis.get("reason", "")
)
logger.info(f"📌 Takip olusturuldu: {follow_up_analysis.get('reason', '')}")
except Exception as follow_up_error:
logger.error(f"Takip sistemi hatasi: {follow_up_error}")
except Exception as notify_error:
logger.error(f"Bildirim hatasi: {notify_error}")
# Sohbet gecmisi ile mesajlari olustur
messages = build_context_messages(phone_number, user_message)
# Intent Analyzer veya context'ten urun bilgisini al
detected_product = None
intent_analysis = None # Scope disinda da kullanilacak
if USE_INTENT_ANALYZER:
try:
context = get_conversation_context(phone_number)
intent_analysis = analyze_customer_intent(user_message, context)
if intent_analysis and intent_analysis.get("product"):
detected_product = intent_analysis.get("product")
logger.info(f"🎯 Intent'ten tespit edilen urun: {detected_product}")
except Exception as e:
logger.error(f"Intent analiz hatasi: {e}")
intent_analysis = None
# Eger Intent'ten urun bulunamadiysa, context'ten al
# ONEMLI: current_product TAM URUN ADINI icerir (ornegin "marlin 5")
# current_category ise sadece kategori adidir (ornegin "marlin")
if not detected_product:
context = get_conversation_context(phone_number)
# Oncelikle tam urun adini dene
if context.get("current_product"):
detected_product = context.get("current_product")
logger.info(f"🎯 Context'ten tespit edilen TAM URUN: {detected_product}")
elif context.get("current_category"):
detected_product = context.get("current_category")
logger.info(f"🎯 Context'ten tespit edilen kategori: {detected_product}")
# Stok sorgusu icin kullanilacak urun adi
stock_query_product = detected_product if detected_product else user_message
# Urun bilgilerini ekle
input_words = user_message.lower().split()
# Detected product'i da input_words'e ekle
if detected_product:
input_words.extend(detected_product.lower().split())
# Bulunan urunun link ve gorsel bilgilerini sakla
found_product_link = None
found_product_image = None
found_product_name = None
best_match_score = 0
# Kullanici mesaji veya detected_product'i normalize et
search_text = (detected_product or user_message).lower()
search_words = search_text.split()
# AKILLI URUN ESLESTIRME
# 1. Kategori bazli filtreleme - Bisiklet aramasinda aksesuar gosterme
# 2. Urun tipi benzerligi - Ayni tip urunler oncelikli
# 3. Kelime eslesmesi - En cok eslesen urun
def is_bicycle_search(text):
"""Arama bisiklet mi yoksa aksesuar mi?"""
bike_indicators = ['madone', 'domane', 'emonda', 'checkpoint', 'fuel', 'slash',
'marlin', 'procaliber', 'supercaliber', 'fx', 'verve', 'dual sport',
'powerfly', 'rail', 'allant', 'bisiklet', 'bike']
text_lower = text.lower()
return any(ind in text_lower for ind in bike_indicators)
def get_product_type(category_tree, product_name):
"""Urun tipini belirle"""
cat_lower = (category_tree or "").lower()
name_lower = (product_name or "").lower()
# Kategori agacindan tip belirle
if 'bisiklet' in cat_lower or 'bike' in cat_lower:
if 'yol' in cat_lower or 'road' in cat_lower:
return 'road_bike'
elif 'dag' in cat_lower or 'mountain' in cat_lower or 'mtb' in cat_lower:
return 'mtb'
elif 'elektrik' in cat_lower or 'e-bike' in cat_lower:
return 'ebike'
elif 'sehir' in cat_lower or 'hybrid' in cat_lower:
return 'hybrid'
return 'bicycle'
elif 'aksesuar' in cat_lower or 'parça' in cat_lower or 'parca' in cat_lower or 'accessory' in cat_lower or 'yedek' in cat_lower:
return 'accessory'
# Isimden tip belirle (fallback)
# ONEMLI: Aksesuar kontrolu ONCE yapilmali cunku "Domane Kadro Kulagi" gibi
# urunlerde model adi gecebilir ama aksesuar kelimeleri varsa aksesuar'dir
accessory_keywords = ['sele', 'gidon', 'pedal', 'zincir', 'lastik', 'jant', 'fren', 'vites',
'kadro kulağı', 'kadro kulagi', 'kulak', 'kablo', 'kasnak', 'dişli',
'zil', 'far', 'lamba', 'pompa', 'kilit', 'çanta', 'canta', 'suluk',
'gözlük', 'gozluk', 'kask', 'eldiven', 'ayakkabı', 'ayakkabi',
'forma', 'tayt', 'şort', 'sort', 'mont', 'yağmurluk', 'yagmurluk']
if any(x in name_lower for x in accessory_keywords):
return 'accessory'
if any(x in name_lower for x in ['madone', 'domane', 'emonda', 'checkpoint', 'fuel', 'marlin', 'fx']):
return 'bicycle'
return 'unknown'
def calculate_smart_match_score(search_words, product_name, product_category, is_bike_search):
"""Akilli eslesme skoru hesapla"""
product_name_lower = product_name.lower()
product_words = product_name_lower.split()
product_type = get_product_type(product_category, product_name)
# Temel kelime eslesmesi
base_score = sum(1 for word in search_words if word in product_name_lower)
# Kategori uyumu bonusu/cezasi
if is_bike_search:
if product_type == 'bicycle':
base_score += 2 # Bisiklet aramasinda bisiklet bulunca bonus
elif product_type == 'accessory':
base_score -= 100 # Bisiklet aramasinda aksesuar KESINLIKLE gosterilmemeli
# KRITIK VARYANT KONTROLU
# AXS, Di2, eTap gibi varyantlar FARKLI URUNLERDIR
# Kullanici "Madone SLR 9" diyorsa "Madone SLR 9 AXS" GOSTERILMEMELI
critical_variants = ['axs', 'etap', 'di2', 'frameset']
# Urunde olan kritik varyantlar
product_critical_variants = [v for v in critical_variants if v in product_name_lower]
# Kullanicinin soyledigi kritik varyantlar
user_critical_variants = [v for v in critical_variants if v in ' '.join(search_words)]
# Urunde kritik varyant var AMA kullanici soylemedi -> BUYUK CEZA
for variant in product_critical_variants:
if variant not in user_critical_variants:
base_score -= 50 # Bu urun gosterilmemeli
# Kullanici kritik varyant soyledi AMA urunde yok -> CEZA
for variant in user_critical_variants:
if variant not in product_critical_variants:
base_score -= 50 # Bu urun gosterilmemeli
# Tam esleme bonusu - Tum arama kelimeleri urunde varsa
all_words_match = all(word in product_name_lower for word in search_words if len(word) > 2)
if all_words_match and len(search_words) > 1:
base_score += 3
# Model numarasi eslesmesi - "9" araniyorsa "9" olmali, "7" olmamali
for word in search_words:
if word.isdigit():
if word in product_words:
base_score += 2 # Tam numara eslesmesi
else:
# Farkli numara varsa ceza
for pword in product_words:
if pword.isdigit() and pword != word:
base_score -= 20 # Farkli model numarasi
return base_score
# Arama bisiklet mi?
is_bike_search = is_bicycle_search(search_text)
for product_info in products:
product_full_name = product_info[2] # Tam urun adi
product_category = product_info[1][6] if len(product_info[1]) > 6 else "" # category_tree
# Akilli skor hesapla
match_score = calculate_smart_match_score(
search_words,
product_full_name,
product_category,
is_bike_search
)
# Daha iyi eslesme bulduysa guncelle
if match_score > best_match_score and product_info[1][0] == "stokta":
best_match_score = match_score
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
# Urun linki ve gorseli al - EN IYI ESLESEN URUN
if product_info[1][2]: # product_link
found_product_link = product_info[1][2]
if product_info[1][5]: # picture_url
found_product_image = product_info[1][5]
found_product_name = product_info[2]
# System message'a LINK EKLEME - cunku GPT linki yanitina dahil ediyor
# ve sonra biz de ekledigimizde 2 kere gorunuyor
new_msg = f"{product_info[2]} {product_info[1][0]} - {price_info}"
messages.append({"role": "system", "content": new_msg})
# Eger match bulunamadiysa, basit eslesme dene
if best_match_score == 0:
for product_info in products:
if product_info[0] in input_words and 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
if product_info[1][2]:
found_product_link = product_info[1][2]
if product_info[1][5]:
found_product_image = product_info[1][5]
found_product_name = product_info[2]
new_msg = f"{product_info[2]} {product_info[1][0]} - {price_info}"
messages.append({"role": "system", "content": new_msg})
break # Ilk eslesen yeterli
# Stok bilgisi ekle - detected_product kullan
# ONCELIK: XML sonucu (smart_warehouse_with_price.py) daha guvenilir
warehouse_info = get_warehouse_stock(stock_query_product)
xml_has_valid_stock = False
if warehouse_info:
stock_msg = "Magaza Stok Durumu:\n" + "\n".join(warehouse_info) if isinstance(warehouse_info, list) else str(warehouse_info)
messages.append({"role": "system", "content": stock_msg})
# XML sonucunda gercek stok bilgisi var mi kontrol et
# "mevcut degil", "bulunamadi", "tukendi" gibi ifadeler yoksa stok var demektir
stock_msg_lower = stock_msg.lower()
negative_indicators = ["mevcut değil", "mevcut degil", "bulunamadi", "bulunmuyor", "tükendi", "tukendi", "stokta yok"]
xml_has_valid_stock = not any(indicator in stock_msg_lower for indicator in negative_indicators)
if xml_has_valid_stock:
logger.info(f"✅ XML'den stok bilgisi bulundu: {stock_query_product}")
# Link ve fiyat bilgisini context'e kaydet (follow-up sorular icin)
context = get_conversation_context(phone_number)
link_match = re.search(r'Link: (https?://[^\s]+)', stock_msg)
if link_match:
context["current_product_link"] = link_match.group(1)
logger.info(f"🔗 Link context'e kaydedildi: {link_match.group(1)}")
price_match = re.search(r'Fiyat: ([^\n]+)', stock_msg)
if price_match:
context["current_product_price"] = price_match.group(1)
# Urun adini da kaydet
if stock_query_product:
context["current_product"] = stock_query_product
# Gercek zamanli stok sorgusu - SADECE XML sonucu bos veya olumsuzsa calistir
# Bu sayede XML'de bulunan urunler icin yanlis "stokta yok" mesaji onlenir
should_query_stock = False
if not xml_has_valid_stock:
if intent_analysis:
# Intent Analyzer'dan gelen intent'lere bak
intents = intent_analysis.get("intents", [])
# stock, info, price gibi intent'ler stok sorgusu gerektirir
stock_related_intents = ["stock", "info", "price", "availability"]
should_query_stock = any(intent in intents for intent in stock_related_intents)
# Urun tespit edildiyse de stok sorgula (kullanici urun hakkinda konusuyor demektir)
if detected_product:
should_query_stock = True
# Yedek: Intent Analyzer calismazsa basit keyword kontrolu
if not intent_analysis and is_stock_query(user_message):
should_query_stock = True
if should_query_stock and stock_query_product and not xml_has_valid_stock:
realtime_stock = get_realtime_stock_parallel(stock_query_product)
if realtime_stock:
messages.append({"role": "system", "content": f"Gercek Zamanli Stok:\n{realtime_stock}"})
logger.info(f"📦 API'den stok bilgisi eklendi: {stock_query_product}")
if not OPENAI_API_KEY:
return "Sistem hatasi olustu."
# SON HATIRLATMA: Turkce dil kurallari - GPT'ye her yanit oncesi hatirlatma
# Bu mesaj en sona ekleniyor ki GPT son gordukleri kurallari uygulasın
turkish_reminder = """KRITIK KURALLAR (HER YANIT ICIN GECERLI):
1. ASLA 'sen' kullanma, HER ZAMAN 'siz' kullan (istersen -> isterseniz, sana -> size)
2. ASLA soru ile bitirme (ayirtayim mi?, ister misiniz?, bakar misiniz? YASAK)
3. Bilgiyi ver ve sus, musteri karar versin
4. ONEMLI: Onceki mesajlarda bahsedilen urunleri UNUTMA! "Hangi model var" gibi sorular onceki konudan devam eder.
YANLIS: "Istersen beden ve magaza bazli stok bilgisini de netlestirebilirim."
DOGRU: "Beden ve magaza bazli stok bilgisi icin yazabilirsiniz." """
messages.append({"role": "system", "content": turkish_reminder})
# Model tipine gore payload olustur
# GPT-5.2 ve o1/o3 modelleri: temperature ve max_tokens desteklemiyor
if "gpt-5" in model or "o1" in model or "o3" in model:
payload = {
"model": model,
"messages": messages,
"max_completion_tokens": 1000
}
else:
payload = {
"model": model,
"messages": messages,
"temperature": 0.3,
"max_tokens": 1000
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {OPENAI_API_KEY}"
}
logger.info(f"📤 API istegi gonderiliyor - Model: {model}")
response = requests.post(API_URL, headers=headers, json=payload, timeout=30)
if response.status_code == 200:
result = response.json()
ai_response = result['choices'][0]['message']['content']
# Kullanilan modeli logla
used_model = result.get('model', model)
logger.info(f"✅ Yanit alindi - Kullanilan model: {used_model}")
try:
formatted_response = extract_product_info_whatsapp(ai_response)
except:
formatted_response = ai_response
# Urun linki ve gorseli varsa ekle
# NOT: Stok/magaza sorularinda yanlis gorsel gostermemek icin
# sadece TEK URUN soruldugundan eminsen gorsel gonder
is_specific_product_query = best_match_score >= 3 # En az 3 kelime eslesmeli
if found_product_link and is_specific_product_query:
formatted_response += f"\n\n🔗 {found_product_link}"
add_to_conversation(phone_number, user_message, formatted_response)
# Gorsel sadece spesifik urun sorgusu ise gonder
# "Sariyer'de hangi renk var" gibi genel sorularda gorsel gonderme
if found_product_image and is_specific_product_query:
return (formatted_response, found_product_image)
return formatted_response
else:
error_msg = response.text[:200] if response.text else "Bilinmeyen hata"
logger.error(f"❌ API hatasi {response.status_code}: {error_msg}")
# Fallback modele gec
if model != MODEL_CONFIG["fallback"]:
logger.info(f"🔄 Fallback modele geciliyor: {MODEL_CONFIG['fallback']}")
fallback_model = MODEL_CONFIG["fallback"]
# Fallback icin payload'i yeniden olustur (max_tokens kullan)
fallback_payload = {
"model": fallback_model,
"messages": messages,
"temperature": 0.3,
"max_tokens": 1000
}
response = requests.post(API_URL, headers=headers, json=fallback_payload, timeout=30)
if response.status_code == 200:
result = response.json()
ai_response = result['choices'][0]['message']['content']
add_to_conversation(phone_number, user_message, ai_response)
return ai_response
return "Su anda bir sorun yasiyorum. Lutfen tekrar deneyin."
except requests.exceptions.Timeout:
logger.error("❌ API timeout hatasi")
return "Islem zaman asimina ugradi. Lutfen tekrar deneyin."
except Exception as e:
logger.error(f"❌ Mesaj isleme hatasi: {e}")
import traceback
traceback.print_exc()
return "Teknik bir sorun olustu. Lutfen tekrar deneyin."
# ===============================
# FASTAPI UYGULAMASI
# ===============================
app = FastAPI(title="Trek WhatsApp Bot - Hybrid Model")
@app.post("/whatsapp-webhook")
async def whatsapp_webhook(request: Request):
"""WhatsApp webhook - Hybrid model ile"""
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 kontrolu
num_media = int(form_data.get('NumMedia', 0))
media_urls = []
media_types = []
for i in range(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"📱 Webhook - From: {from_number}, Body: {message_body[:50] if message_body else 'N/A'}, Media: {num_media}")
# BLOCKLIST KONTROLU - engellenen numaralar sessizce ignore edilir (0 token)
if from_number and is_blocked(from_number):
return {"status": "blocked", "message": "Blocked number"}
# RATE LIMIT KONTROLU - dakikada cok fazla mesaj atanlari engelle
if from_number and is_rate_limited(from_number):
return {"status": "rate_limited", "message": "Too many messages"}
# Durum guncellemelerini ignore et
if message_status in ['sent', 'delivered', 'read', 'failed']:
return {"status": "ignored", "message": f"Status: {message_status}"}
# Giden mesajlari ignore et
if to_number != TWILIO_WHATSAPP_NUMBER:
return {"status": "ignored", "message": "Outgoing message"}
# Bos mesaj ve medya yoksa ignore et
if not message_body and num_media == 0:
return {"status": "ignored", "message": "Empty message"}
logger.info(f"✅ MESAJ ALINDI: {from_number} -> Metin: {bool(message_body)}, Medya: {num_media}")
if not twilio_client:
return {"status": "error", "message": "Twilio yapilandirmasi eksik"}
# ========================================
# HYBRID MODEL SECIMI
# ========================================
product_image_url = None
if num_media > 0 and media_urls:
# GORSEL VAR -> GPT-4o kullan
logger.info("🖼️ GORSEL TESPIT EDILDI -> GPT-4o Vision kullanilacak")
ai_response = process_whatsapp_message_with_media(
message_body,
from_number,
media_urls,
media_types
)
else:
# SADECE METIN -> GPT-5.2 kullan
logger.info("📝 METIN MESAJI -> GPT-5.2 kullanilacak")
result = process_whatsapp_message_with_memory(
message_body,
from_number
)
# Tuple donerse (metin, gorsel_url) seklinde
if isinstance(result, tuple):
ai_response, product_image_url = result
logger.info(f"🖼️ Urun gorseli bulundu: {product_image_url}")
else:
ai_response = result
# Yanit kisalt
if len(ai_response) > 1500:
ai_response = ai_response[:1500] + "...\n\nDetayli bilgi: trekbisiklet.com.tr"
# WhatsApp'a gonder
# Once metin mesaji gonder
message = twilio_client.messages.create(
messaging_service_sid=TWILIO_MESSAGING_SERVICE_SID,
body=ai_response,
to=from_number
)
logger.info(f"✅ YANIT GONDERILDI: {ai_response[:100]}...")
# Urun gorseli varsa ayrica gonder
if product_image_url:
try:
image_message = twilio_client.messages.create(
messaging_service_sid=TWILIO_MESSAGING_SERVICE_SID,
media_url=[product_image_url],
to=from_number
)
logger.info(f"🖼️ URUN GORSELI GONDERILDI: {product_image_url}")
except Exception as img_error:
logger.error(f"❌ Gorsel gonderme hatasi: {img_error}")
return {"status": "success", "message_sid": message.sid}
except Exception as e:
logger.error(f"❌ Webhook hatasi: {str(e)}")
import traceback
traceback.print_exc()
return {"status": "error", "message": str(e)}
@app.get("/")
async def root():
return {
"message": "Trek WhatsApp Bot - Hybrid Model calisiyor!",
"status": "active",
"models": {
"vision": MODEL_CONFIG["vision"],
"text": MODEL_CONFIG["text"],
"fallback": MODEL_CONFIG["fallback"]
}
}
@app.get("/health")
async def health():
return {
"status": "healthy",
"twilio_configured": twilio_client is not None,
"openai_configured": OPENAI_API_KEY is not None,
"models": MODEL_CONFIG,
"products_loaded": len(products),
"modules": {
"gpt5_search": USE_GPT5_SEARCH,
"media_queue": USE_MEDIA_QUEUE,
"store_notification": USE_STORE_NOTIFICATION,
"follow_up": USE_FOLLOW_UP,
"intent_analyzer": USE_INTENT_ANALYZER
}
}
@app.get("/test-models")
async def test_models():
"""Model durumlarini test et"""
results = {}
for model_type, model_name in MODEL_CONFIG.items():
try:
payload = {
"model": model_name,
"messages": [{"role": "user", "content": "Merhaba, test mesaji."}],
"max_tokens": 10
}
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {OPENAI_API_KEY}"
}
response = requests.post(API_URL, headers=headers, json=payload, timeout=10)
results[model_type] = {
"model": model_name,
"status": "OK" if response.status_code == 200 else f"Error: {response.status_code}",
"available": response.status_code == 200
}
except Exception as e:
results[model_type] = {
"model": model_name,
"status": f"Error: {str(e)}",
"available": False
}
return results
@app.get("/cache-status")
async def cache_status():
"""Cache durumunu goster"""
return {
"cache_size": len(stock_cache),
"cache_duration_seconds": CACHE_DURATION,
"cached_products": list(stock_cache.keys())[:10] # Ilk 10
}
@app.post("/clear-cache")
async def clear_cache():
"""Cache'i temizle"""
global stock_cache
old_size = len(stock_cache)
stock_cache = {}
return {"message": f"Cache temizlendi. {old_size} kayit silindi."}
if __name__ == "__main__":
import uvicorn
print("=" * 60)
print(" Trek WhatsApp Bot - HYBRID MODEL")
print("=" * 60)
print(f" 🖼️ Gorsel mesajlar -> {MODEL_CONFIG['vision']}")
print(f" 📝 Metin mesajlar -> {MODEL_CONFIG['text']}")
print(f" 🔄 Fallback -> {MODEL_CONFIG['fallback']}")
print("=" * 60)
print(f" 📦 Yuklenen urun sayisi: {len(products)}")
print(f" 🔍 GPT-5 Search: {'Aktif' if USE_GPT5_SEARCH else 'Pasif'}")
print(f" 🔔 Store Notification: {'Aktif' if USE_STORE_NOTIFICATION else 'Pasif'}")
print(f" 📌 Follow-Up System: {'Aktif' if USE_FOLLOW_UP else 'Pasif'}")
print(f" 🧠 Intent Analyzer: {'Aktif' if USE_INTENT_ANALYZER else 'Pasif'}")
print("=" * 60)
uvicorn.run(app, host="0.0.0.0", port=7860)
|