Upload app.py

app.py

@@ -0,0 +1,566 @@
+import os, glob, json, requests
+import numpy as np
+import pandas as pd
+import gradio as gr
+from sklearn.preprocessing import StandardScaler
+
+try:
+    from sentence_transformers import SentenceTransformer
+except Exception:
+    SentenceTransformer = None
+try:
+    from sklearn.feature_extraction.text import HashingVectorizer
+except Exception:
+    HashingVectorizer = None
+
+CSV_MAIN = "RideSearch_dataset.csv"
+CSV_PARTS_GLOB = "RideSearch_part*_small.csv"
+EMB_TEXT_NPY = "emb_text.npy"
+EMB_NUM_NPY  = "emb_num.npy"
+TRIMS_OVERRIDES = "trims_overrides.json"
+EMBED_MODEL = os.environ.get("EMBED_MODEL", "sentence-transformers/all-MiniLM-L6-v2")
+
+NUM_COLS_CANON = [
+    "horsepower","zero_to_100_kmh_s","seats","cargo_liters","price_usd",
+    "popularity_score","comfort_score","reliability_score","tech_score",
+    "ownership_cost_score","safety_rating","year"
+]
+
+REAL_TRIMS = {
+    ("BMW","1 Series"): ["116i","118i","120i","125i","M135i"],
+    ("BMW","2 Series"): ["218i","220i","225i","230i","M235i","M240i"],
+    ("BMW","3 Series"): ["318i","320i","325i","330i","330e","335i","340i","M340i","M3"],
+    ("BMW","4 Series"): ["420i","430i","435i","440i","M440i","M4"],
+    ("BMW","5 Series"): ["520i","525i","530i","530e","535i","540i","550i","M550i","M5"],
+    ("BMW","6 Series"): ["630i","640i","650i","M6"],
+    ("BMW","7 Series"): ["730i","740i","750i","760i","M760i"],
+    ("BMW","8 Series"): ["840i","850i","M850i","M8"],
+    ("BMW","X1"): ["sDrive18i","sDrive20i","xDrive20i","xDrive25i"],
+    ("BMW","X2"): ["sDrive18i","sDrive20i","xDrive20i","xDrive25i","M35i"],
+    ("BMW","X3"): ["sDrive20i","xDrive20i","xDrive30i","M40i","X3 M"],
+    ("BMW","X4"): ["xDrive20i","xDrive30i","M40i","X4 M"],
+    ("BMW","X5"): ["sDrive40i","xDrive40i","xDrive45e","M50i","X5 M"],
+    ("BMW","X6"): ["sDrive40i","xDrive40i","M50i","X6 M"],
+    ("BMW","X7"): ["xDrive40i","xDrive50i","M50i"],
+    ("BMW","Z4"): ["sDrive20i","sDrive30i","M40i"],
+    ("Audi","A1"): ["25 TFSI","30 TFSI","35 TFSI","S1"],
+    ("Audi","A3"): ["30 TFSI","35 TFSI","40 TFSI","45 TFSI e","S3","RS3"],
+    ("Audi","A4"): ["35 TFSI","40 TFSI","45 TFSI","45 TFSI e","S4","RS4"],
+    ("Audi","A5"): ["35 TFSI","40 TFSI","45 TFSI","S5","RS5"],
+    ("Audi","A6"): ["40 TFSI","45 TFSI","50 TFSI","55 TFSI e","S6","RS6"],
+    ("Audi","A7"): ["45 TFSI","50 TFSI","55 TFSI e","S7","RS7"],
+    ("Audi","A8"): ["50 TFSI","55 TFSI","60 TFSI e","S8"],
+    ("Audi","Q2"): ["30 TFSI","35 TFSI","40 TFSI"],
+    ("Audi","Q3"): ["35 TFSI","40 TFSI","45 TFSI e","RS Q3"],
+    ("Audi","Q5"): ["40 TFSI","45 TFSI e","SQ5"],
+    ("Audi","Q7"): ["45 TFSI","50 TDI","55 TFSI e","SQ7"],
+    ("Audi","Q8"): ["50 TDI","55 TFSI","SQ8","RS Q8"],
+    ("Audi","TT"): ["40 TFSI","45 TFSI","TTS","TT RS"],
+    ("Audi","R8"): ["V10","V10 Performance","V10 Plus"],
+    ("Mercedes-Benz","A-Class"): ["A180","A200","A220","A250","A250e","AMG A35","AMG A45"],
+    ("Mercedes-Benz","B-Class"): ["B180","B200","B220","B250e"],
+    ("Mercedes-Benz","C-Class"): ["C180","C200","C220d","C250","C300","C350e","AMG C43","AMG C63"],
+    ("Mercedes-Benz","E-Class"): ["E200","E220d","E250","E300","E350","E400","E450","AMG E53","AMG E63"],
+    ("Mercedes-Benz","S-Class"): ["S350","S400","S450","S500","S580","S600","AMG S63","AMG S65"],
+    ("Mercedes-Benz","CLA"): ["CLA180","CLA200","CLA220","CLA250","AMG CLA35","AMG CLA45"],
+    ("Mercedes-Benz","CLS"): ["CLS350","CLS400","CLS450","AMG CLS53","AMG CLS63"],
+    ("Mercedes-Benz","GLA"): ["GLA180","GLA200","GLA220","GLA250","AMG GLA35","AMG GLA45"],
+    ("Mercedes-Benz","GLB"): ["GLB200","GLB220","GLB250","AMG GLB35"],
+    ("Mercedes-Benz","GLC"): ["GLC200","GLC220d","GLC300","GLC350e","AMG GLC43","AMG GLC63"],
+    ("Mercedes-Benz","GLE"): ["GLE300","GLE350","GLE400","GLE450","GLE580","AMG GLE53","AMG GLE63"],
+    ("Mercedes-Benz","GLS"): ["GLS400","GLS450","GLS580","AMG GLS63"],
+    ("Mercedes-Benz","G-Class"): ["G350","G400","G500","G550","AMG G63","AMG G65"],
+    ("Toyota","Corolla"): ["L","LE","XLE","SE","XSE","GR Corolla"],
+    ("Toyota","Camry"): ["L","LE","SE","XLE","XSE","TRD"],
+    ("Toyota","Avalon"): ["XLE","XSE","Limited","TRD"],
+    ("Toyota","Prius"): ["L","LE","XLE","Limited","Prime"],
+    ("Toyota","RAV4"): ["LE","XLE","XLE Premium","Adventure","TRD Off-Road","Limited","Prime"],
+    ("Toyota","Highlander"): ["L","LE","XLE","Limited","Platinum","Hybrid"],
+    ("Toyota","4Runner"): ["SR5","TRD Off-Road","TRD Pro","Limited"],
+    ("Toyota","Tacoma"): ["SR","SR5","TRD Sport","TRD Off-Road","TRD Pro","Limited"],
+    ("Toyota","Tundra"): ["SR","SR5","Limited","Platinum","1794","TRD Pro"],
+    ("Toyota","Land Cruiser"): ["Base","Heritage Edition"],
+    ("Toyota","Supra"): ["2.0","3.0","3.0 Premium"],
+    ("Toyota","Yaris"): ["L","LE","XLE","GRMN"],
+    ("Toyota","C-HR"): ["LE","XLE","Nightshade","Limited"],
+    ("Toyota","Sequoia"): ["SR5","Limited","Platinum","TRD Pro","Capstone"],
+    ("Toyota","Sienna"): ["LE","XLE","XSE","Limited","Platinum"],
+    ("Honda","Civic"): ["LX","Sport","EX","EX-L","Sport Touring","Touring","Si","Type R"],
+    ("Honda","Accord"): ["LX","Sport","EX","EX-L","Touring","Sport-L"],
+    ("Honda","CR-V"): ["LX","EX","EX-L","Touring","Hybrid"],
+    ("Honda","HR-V"): ["LX","Sport","EX","EX-L"],
+    ("Honda","Pilot"): ["LX","EX","EX-L","Touring","Elite","TrailSport"],
+    ("Honda","Passport"): ["Sport","EX-L","Touring","Elite","TrailSport"],
+    ("Honda","Ridgeline"): ["Sport","RTL","RTL-E","Black Edition"],
+    ("Honda","Insight"): ["LX","EX","Touring"],
+    ("Honda","Fit / Jazz"): ["LX","Sport","EX","EX-L"],
+    ("Honda","Odyssey"): ["EX","EX-L","Touring","Elite"],
+    ("Volkswagen","Golf"): ["S","SE","SEL","Autobahn","GTI","R"],
+    ("Volkswagen","Jetta"): ["S","SE","SEL","SEL Premium","GLI"],
+    ("Volkswagen","Passat"): ["S","SE","SEL Premium","R-Line"],
+    ("Volkswagen","Tiguan"): ["S","SE","SEL","SEL Premium","R-Line"],
+    ("Volkswagen","Atlas"): ["S","SE","SEL","SEL Premium","Cross Sport"],
+    ("Volkswagen","Arteon"): ["SE","SEL","SEL Premium","R-Line"],
+    ("Volkswagen","ID.4"): ["Pro","Pro S","1st Edition"],
+    ("Nissan","Sentra"): ["S","SV","SR"],
+    ("Nissan","Altima"): ["S","SV","SL","SR","Platinum"],
+    ("Nissan","Maxima"): ["S","SV","SL","SR","Platinum"],
+    ("Nissan","Versa"): ["S","SV","SR"],
+    ("Nissan","Rogue"): ["S","SV","SL","Platinum"],
+    ("Nissan","Murano"): ["S","SV","SL","Platinum"],
+    ("Nissan","Pathfinder"): ["S","SV","SL","Platinum"],
+    ("Nissan","Armada"): ["SV","SL","Platinum"],
+    ("Nissan","Frontier"): ["S","SV","PRO-4X"],
+    ("Nissan","Titan"): ["S","SV","PRO-4X","Platinum Reserve"],
+    ("Nissan","Z"): ["Sport","Performance"],
+    ("Nissan","GT-R"): ["Premium","NISMO","Track Edition"],
+    ("Nissan","Qashqai / Rogue Sport"): ["S","SV","SL"],
+    ("Nissan","X-Trail"): ["Visia","Acenta","N-Connecta","Tekna"],
+    ("Hyundai","Elantra"): ["SE","SEL","Limited","N Line","N"],
+    ("Hyundai","Sonata"): ["SE","SEL","Limited","N Line"],
+    ("Hyundai","Accent"): ["SE","SEL"],
+    ("Hyundai","Tucson"): ["SE","SEL","Limited","N Line"],
+    ("Hyundai","Santa Fe"): ["SE","SEL","Limited","Calligraphy"],
+    ("Hyundai","Palisade"): ["SE","SEL","Limited","Calligraphy"],
+    ("Hyundai","Kona"): ["SE","SEL","Limited","N Line","N"],
+    ("Hyundai","Venue"): ["SE","SEL"],
+    ("Hyundai","Ioniq 5"): ["SE","SEL","Limited"],
+    ("Hyundai","Ioniq 6"): ["SE","SEL","Limited"],
+    ("Hyundai","Santa Cruz"): ["SE","SEL","Night","Limited"],
+    ("Hyundai","Ioniq 7 / SEVEN"): ["Concept","Preview"],
+    ("Hyundai","Genesis G70"): ["2.0T","3.3T Sport"],
+    ("Hyundai","Genesis G80"): ["2.5T","3.5T Sport"],
+    ("Hyundai","Genesis G90"): ["3.3T Premium","5.0 Ultimate"],
+    ("Kia","Rio"): ["LX","S"],
+    ("Kia","Forte"): ["LX","S","EX","GT-Line","GT"],
+    ("Kia","K5"): ["LX","S","EX","GT-Line"],
+    ("Kia","Stinger"): ["GT-Line","GT1","GT2"],
+    ("Kia","Soul"): ["LX","S","EX","GT-Line"],
+    ("Kia","Seltos"): ["LX","S","EX","SX Turbo"],
+    ("Kia","Sportage"): ["LX","S","EX","SX Turbo"],
+    ("Kia","Sorento"): ["LX","S","EX","SX","SX Turbo"],
+    ("Kia","Telluride"): ["LX","S","EX","SX"],
+    ("Kia","Carnival"): ["LX","S","EX","SX"],
+    ("Kia","EV6"): ["Light","Wind","GT-Line"],
+    ("Kia","Niro"): ["LX","EX","SX Touring"],
+    ("Kia","EV9"): ["Light","Wind","Land","GT-Line"],
+    ("Ford","Fiesta"): ["S","SE","Titanium","ST"],
+    ("Ford","Focus"): ["S","SE","SEL","Titanium","ST","RS"],
+    ("Ford","Fusion"): ["S","SE","SEL","Titanium","Sport"],
+    ("Ford","Mustang"): ["EcoBoost","GT","Mach 1","Shelby GT350","Shelby GT500"],
+    ("Ford","Escape"): ["S","SE","SEL","Titanium"],
+    ("Ford","Edge"): ["SE","SEL","Titanium","ST"],
+    ("Ford","Explorer"): ["Base","XLT","Limited","King Ranch","Platinum","ST"],
+    ("Ford","Expedition"): ["XLT","Limited","King Ranch","Platinum"],
+    ("Ford","F-150"): ["Regular Cab","SuperCab","SuperCrew","Raptor","Lightning"],
+    ("Ford","Ranger"): ["XL","XLT","Lariat"],
+    ("Ford","Bronco"): ["Base","Big Bend","Black Diamond","Outer Banks","Badlands","Wildtrak","Raptor"],
+    ("Ford","Maverick"): ["XL","XLT","Lariat","Tremor"],
+    ("Ford","Bronco Sport"): ["Base","Big Bend","Outer Banks","Badlands"],
+    ("Chevrolet","Spark"): ["LS","LT","Premier"],
+    ("Chevrolet","Sonic"): ["LS","LT","Premier"],
+    ("Chevrolet","Cruze"): ["L","LS","LT","Premier"],
+    ("Chevrolet","Malibu"): ["L","LS","LT","Premier"],
+    ("Chevrolet","Impala"): ["LS","LT","Premier"],
+    ("Chevrolet","Camaro"): ["1LS","1LT","2LT","1SS","2SS","ZL1"],
+    ("Chevrolet","Corvette"): ["1LT","2LT","3LT","Z06","ZR1"],
+    ("Chevrolet","Trax"): ["L","LS","LT","Premier"],
+    ("Chevrolet","Equinox"): ["L","LS","LT","Premier"],
+    ("Chevrolet","Traverse"): ["L","LS","LT","Premier","High Country"],
+    ("Chevrolet","Tahoe"): ["LS","LT","RST","Premier","High Country"],
+    ("Chevrolet","Suburban"): ["LS","LT","RST","Premier","High Country"],
+    ("Chevrolet","Silverado 1500"): ["Work Truck","Custom","LT","RST","LTZ","High Country"],
+    ("Chevrolet","Blazer"): ["LT","RS","Premier"],
+    ("Chevrolet","Trailblazer"): ["LS","LT","ACTIV","RS"],
+    ("Chevrolet","Bolt EV"): ["1LT","2LT"],
+    ("Lexus","IS"): ["300","350","500 F SPORT Performance"],
+    ("Lexus","ES"): ["250","300h","350"],
+    ("Lexus","GS"): ["300","350","450h","F"],
+    ("Lexus","LS"): ["500","500h"],
+    ("Lexus","LC"): ["500","500h"],
+    ("Lexus","RC"): ["300","350","F"],
+    ("Lexus","UX"): ["200","250h"],
+    ("Lexus","NX"): ["250","350","350h","450h+"],
+    ("Lexus","RX"): ["350","350h","500h F SPORT Performance"],
+    ("Lexus","GX"): ["460"],
+    ("Lexus","LX"): ["570","600"],
+    ("Infiniti","Q50"): ["Pure","Luxe","Sensory","Red Sport 400"],
+    ("Infiniti","Q60"): ["Pure","Luxe","Sensory","Red Sport 400"],
+    ("Infiniti","Q70"): ["Base","Sport"],
+    ("Infiniti","QX50"): ["Pure","Luxe","Sensory","Autograph"],
+    ("Infiniti","QX60"): ["Pure","Luxe","Sensory","Autograph"],
+    ("Infiniti","QX80"): ["Pure","Luxe","Sensory","Autograph"],
+    ("Infiniti","QX55"): ["Luxe","Essential","Sensory"],
+    ("Acura","ILX"): ["Base","Premium","A-Spec"],
+    ("Acura","TLX"): ["Base","Technology","A-Spec","Advance","Type S"],
+    ("Acura","RLX"): ["Base","Technology","Advance"],
+    ("Acura","NSX"): ["Base","Type S"],
+    ("Acura","RDX"): ["Base","Technology","A-Spec","Advance"],
+    ("Acura","MDX"): ["Base","Technology","A-Spec","Advance","Type S"],
+    ("Cadillac","ATS"): ["Base","Luxury","Premium Luxury","V-Sport","V"],
+    ("Cadillac","CTS"): ["Base","Luxury","Premium Luxury","V-Sport","V"],
+    ("Cadillac","CT4"): ["Luxury","Premium Luxury","Sport","V-Series","V-Series Blackwing"],
+    ("Cadillac","CT5"): ["Luxury","Premium Luxury","Sport","V-Series","V-Series Blackwing"],
+    ("Cadillac","XTS"): ["Base","Luxury","Premium Luxury","Platinum"],
+    ("Cadillac","XT4"): ["Luxury","Premium Luxury","Sport"],
+    ("Cadillac","XT5"): ["Luxury","Premium Luxury","Sport"],
+    ("Cadillac","XT6"): ["Luxury","Premium Luxury","Sport"],
+    ("Cadillac","Escalade"): ["Luxury","Premium Luxury","Sport","V-Series"],
+    ("Lincoln","MKZ"): ["Premiere","Select","Reserve"],
+    ("Lincoln","Continental"): ["Premiere","Select","Reserve","Coach Door Edition"],
+    ("Lincoln","Corsair"): ["Base","Reserve"],
+    ("Lincoln","Nautilus"): ["Base","Reserve"],
+    ("Lincoln","Aviator"): ["Premiere","Reserve","Grand Touring","Black Label"],
+    ("Lincoln","Navigator"): ["Premiere","Select","Reserve","Black Label"],
+    ("Buick","Verano"): ["Base","Convenience","Leather","Premium"],
+    ("Buick","Regal"): ["1SV","Preferred","Essence","GS"],
+    ("Buick","LaCrosse"): ["Base","Preferred","Essence","Premium","Avenir"],
+    ("Buick","Encore"): ["Base","Convenience","Leather","Premium"],
+    ("Buick","Envision"): ["Preferred","Essence","Premium","Avenir"],
+    ("Buick","Enclave"): ["Base","Essence","Premium","Avenir"],
+    ("Genesis","G70"): ["2.0T","2.0T Advanced","3.3T Sport","3.3T Sport Prestige"],
+    ("Genesis","G80"): ["2.5T","2.5T Advanced","3.5T Sport","3.5T Sport Prestige"],
+    ("Genesis","G90"): ["3.3T Premium","3.3T Prestige","5.0 Ultimate"],
+    ("Genesis","GV70"): ["2.5T","2.5T Advanced","3.5T Sport","3.5T Sport Prestige"],
+    ("Genesis","GV80"): ["2.5T","2.5T Advanced","3.5T","3.5T Prestige"],
+    ("Tesla","Model S"): ["Standard Range","Long Range","Plaid"],
+    ("Tesla","Model 3"): ["Standard Range Plus","Long Range","Performance"],
+    ("Tesla","Model X"): ["Standard Range","Long Range","Plaid"],
+    ("Tesla","Model Y"): ["Standard Range","Long Range","Performance"],
+    ("Porsche","911"): ["Carrera","Carrera S","Carrera 4","Carrera 4S","Turbo","Turbo S","GT3","GT3 RS","GT2 RS"],
+    ("Porsche","Boxster"): ["Base","S","GTS","Spyder"],
+    ("Porsche","Cayman"): ["Base","S","GTS","GT4"],
+    ("Porsche","Panamera"): ["Base","4","S","4S","GTS","Turbo","Turbo S"],
+    ("Porsche","Macan"): ["Base","S","GTS","Turbo"],
+    ("Porsche","Cayenne"): ["Base","S","GTS","Turbo","Turbo S","E-Hybrid"],
+    ("Porsche","Taycan"): ["Base","4S","Turbo","Turbo S"],
+    ("Jaguar","XE"): ["Base","Premium","Prestige","R-Sport","S"],
+    ("Jaguar","XF"): ["Premium","Prestige","R-Sport","S"],
+    ("Jaguar","XJ"): ["Premium Luxury","Portfolio","Autobiography","XJR575"],
+    ("Jaguar","F-TYPE"): ["Base","Premium","R-Dynamic","R","SVR"],
+    ("Jaguar","E-PACE"): ["Base","S","SE","HSE","R-Dynamic"],
+    ("Jaguar","F-PACE"): ["Premium","Prestige","R-Sport","S","SVR"],
+    ("Jaguar","I-PACE"): ["S","SE","HSE","First Edition"],
+    ("Land Rover","Range Rover Evoque"): ["S","SE","HSE","HSE Dynamic","Autobiography"],
+    ("Land Rover","Range Rover Velar"): ["S","SE","HSE","R-Dynamic","P380","P550"],
+    ("Land Rover","Range Rover Sport"): ["HSE","HSE Dynamic","Autobiography","SVR"],
+    ("Land Rover","Range Rover"): ["Base","HSE","Autobiography","SV","SVAutobiography"],
+    ("Land Rover","Discovery Sport"): ["S","SE","HSE","HSE Luxury"],
+    ("Land Rover","Discovery"): ["S","SE","HSE","HSE Luxury"],
+    ("Land Rover","Defender"): ["90","110","130","X","X-Dynamic","First Edition"],
+    ("Volvo","S60"): ["T5 Momentum","T5 R-Design","T6 R-Design","T8 Polestar"],
+    ("Volvo","S90"): ["T5 Momentum","T6 Momentum","T6 R-Design","T8 Inscription"],
+    ("Volvo","V60"): ["T5 Momentum","T5 R-Design","T6 R-Design","T8 Polestar"],
+    ("Volvo","V90"): ["T5 Momentum","T6 Momentum","T6 R-Design","T8 Inscription"],
+    ("Volvo","XC40"): ["T4 Momentum","T5 Momentum","T5 R-Design","Recharge"],
+    ("Volvo","XC60"): ["Core","Plus","Ultimate","Polestar Engineered"],
+    ("Volvo","XC90"): ["Momentum","R-Design","Inscription","Recharge"],
+    ("MINI","Cooper"): ["One","Cooper","Cooper S","John Cooper Works"],
+    ("Mini","Cooper"): ["Base","Classic","Signature","Iconic","John Cooper Works"],
+    ("Mini","Countryman"): ["Classic","Signature","Iconic","John Cooper Works"],
+    ("Mini","Clubman"): ["Classic","Signature","Iconic","John Cooper Works"],
+    ("Mazda","Mazda3"): ["Base","Select","Preferred","Premium","Turbo"],
+    ("Mazda","Mazda6"): ["Sport","Touring","Grand Touring","Grand Touring Reserve","Signature"],
+    ("Mazda","CX-3"): ["Sport","Touring","Grand Touring"],
+    ("Mazda","CX-30"): ["S","Select","Preferred","Premium","Turbo","Turbo Premium Plus"],
+    ("Mazda","CX-5"): ["S","Select","Preferred","Premium","Turbo","Turbo Signature"],
+    ("Mazda","CX-50"): ["2.5 S","2.5 S Select","2.5 S Preferred","2.5 Turbo","2.5 Turbo Premium"],
+    ("Mazda","CX-9"): ["Sport","Touring","Grand Touring","Signature","Carbon Edition"],
+    ("Mazda","MX-5 Miata"): ["Sport","Club","Grand Touring"],
+    ("Mazda","MX-30"): ["EV","EV Premium Plus"],
+    ("Subaru","Impreza"): ["Base","Premium","Sport","Limited"],
+    ("Subaru","WRX"): ["Base","Premium","Limited","GT","STI"],
+    ("Subaru","BRZ"): ["Premium","Limited","tS"],
+    ("Subaru","Legacy"): ["Base","Premium","Sport","Limited","Touring XT"],
+    ("Subaru","Outback"): ["Base","Premium","Limited","Onyx Edition XT","Wilderness","Touring XT"],
+    ("Subaru","Forester"): ["Base","Premium","Sport","Wilderness","Limited","Touring"],
+    ("Subaru","Crosstrek"): ["Base","Premium","Sport","Limited","Hybrid"],
+    ("Subaru","Ascent"): ["Base","Premium","Onyx Edition","Limited","Touring"],
+    ("Mitsubishi","Mirage"): ["ES","LE","SE","GT"],
+    ("Mitsubishi","Outlander"): ["ES","SE","SEL","Black Edition","GT","PHEV"],
+    ("Mitsubishi","Outlander Sport"): ["S","ES","LE","SE","GT"],
+    ("Mitsubishi","Eclipse Cross"): ["ES","LE","SE","SEL"],
+    ("Mitsubishi","Pajero"): ["GL","GLS","Exceed"],
+    ("Mitsubishi","L200 / Triton"): ["GLX","GLS","Exceed"],
+    ("Peugeot","208"): ["Active","Allure","GT"],
+    ("Peugeot","2008"): ["Active","Allure","GT"],
+    ("Peugeot","308"): ["Active","Allure","GT"],
+    ("Peugeot","3008"): ["Active","Allure","GT","GT Pack"],
+    ("Peugeot","5008"): ["Active","Allure","GT"],
+    ("Peugeot","508"): ["Active","Allure","GT","PSE"],
+    ("Renault","Clio"): ["Play","Iconic","S Edition","RS Line"],
+    ("Renault","Megane"): ["Play","Iconic","RS Line","RS Trophy"],
+    ("Renault","Captur"): ["Play","Iconic","S Edition","RS Line"],
+    ("Renault","Kadjar"): ["Play","Iconic","S Edition","GT Line"],
+    ("Renault","Arkana"): ["Iconic","S Edition","RS Line"],
+    ("Renault","Austral"): ["Equilibre","Techno","Esprit Alpine"],
+    ("Skoda","Fabia"): ["S","SE","SE L","Monte Carlo"],
+    ("Skoda","Octavia"): ["S","SE","SE L","SportLine","vRS"],
+    ("Skoda","Superb"): ["SE","SE L","SportLine","L&K"],
+    ("Skoda","Karoq"): ["SE Drive","SE L","SportLine"],
+    ("Skoda","Kodiaq"): ["SE","SE L","SportLine","vRS"],
+    ("Seat","Ibiza"): ["Reference","Style","Xcellence","FR"],
+    ("Seat","Leon"): ["Reference","Style","Xcellence","FR","Cupra"],
+    ("Seat","Arona"): ["Reference","Style","Xcellence","FR"],
+    ("Seat","Ateca"): ["Reference","Style","Xcellence","FR"],
+    ("Seat","Tarraco"): ["SE","SE Technology","Xcellence","FR"],
+}
+def _norm(x): return str(x or "").strip().lower()
+REAL_TRIMS_N = {(_norm(mk), _norm(md)): trims for (mk, md), trims in REAL_TRIMS.items()}
+
+def load_df():
+    if os.path.exists(CSV_MAIN):
+        return pd.read_csv(CSV_MAIN)
+    parts = sorted(glob.glob(CSV_PARTS_GLOB))
+    if parts:
+        df = pd.concat([pd.read_csv(p) for p in parts], ignore_index=True)
+        df.to_csv(CSV_MAIN, index=False)
+        return df
+    raise FileNotFoundError("Upload RideSearch_dataset.csv or the parts RideSearch_part*_small.csv.")
+
+def unify_columns(df: pd.DataFrame) -> pd.DataFrame:
+    df = df.copy()
+    if "popularity" in df.columns and "popularity_score" not in df.columns: df["popularity_score"] = df["popularity"]
+    if "comfort" in df.columns and "comfort_score" not in df.columns: df["comfort_score"] = df["comfort"]
+    if "reliability" in df.columns and "reliability_score" not in df.columns: df["reliability_score"] = df["reliability"]
+    if "safety" in df.columns and "safety_rating" not in df.columns: df["safety_rating"] = df["safety"]
+    if "trim_display" not in df.columns: df["trim_display"] = df["trim"] if "trim" in df.columns else ""
+    for c in NUM_COLS_CANON:
+        if c not in df.columns: df[c] = np.nan
+    for c in NUM_COLS_CANON: df[c] = pd.to_numeric(df[c], errors="coerce")
+    if "text_record" not in df.columns:
+        cols = ["make","model","trim_display","body_type","fuel","engine_type"]
+        cols = [c for c in cols if c in df.columns]
+        df["text_record"] = df[cols].fillna("").astype(str).agg(" ".join, axis=1)
+    for col in ["make","model","body_type","fuel","engine_type","name"]:
+        if col not in df.columns: df[col] = ""
+    return df
+
+def suspicious_zero_to_100(series: pd.Series) -> bool:
+    s = series.dropna()
+    if len(s) < 20: return False
+    return (s.nunique() <= max(2, int(0.03*len(s)))) or (s.std() < 0.18)
+
+def estimate_0_100(row):
+    try: hp = float(row.get("horsepower", 150) or 150)
+    except Exception: hp = 150.0
+    body = str(row.get("body_type","")).lower()
+    fuel = str(row.get("fuel","")).lower()
+    trim = f"{row.get('model','')} {row.get('trim_display','')}".lower()
+    base = 26.0 - 3.2*np.log(max(hp, 60.0))
+    if any(k in body for k in ["suv","crossover","pickup","truck","van"]): base += 0.7
+    if any(k in body for k in ["coupe","roadster"]): base -= 0.4
+    if "electric" in fuel or "ev" in fuel: base -= 0.8
+    if "hybrid" in fuel: base -= 0.3
+    if "diesel" in fuel: base += 0.2
+    if any(x in trim for x in [" m "," amg","rs","type r","sti","gts","gt3","hellcat","svr","cupra","john cooper works"]): base -= 0.6
+    return float(np.clip(round(base,2), 2.8, 14.5))
+
+def ensure_embeddings(df):
+    txt_ok = os.path.exists(EMB_TEXT_NPY)
+    num_ok = os.path.exists(EMB_NUM_NPY)
+    if txt_ok and num_ok:
+        return np.load(EMB_TEXT_NPY), np.load(EMB_NUM_NPY)
+    if SentenceTransformer is not None:
+        model = SentenceTransformer(EMBED_MODEL)
+        Etext = model.encode(df["text_record"].astype(str).tolist(), batch_size=256, show_progress_bar=False, normalize_embeddings=True).astype("float32")
+    else:
+        if HashingVectorizer is None: raise RuntimeError("Install sentence-transformers or scikit-learn for text embeddings.")
+        hv = HashingVectorizer(n_features=512, alternate_sign=False, norm="l2")
+        Etext = hv.transform(df["text_record"].fillna("").tolist()).toarray().astype("float32")
+    np.save(EMB_TEXT_NPY, Etext)
+    X = df[["horsepower","zero_to_100_kmh_s","seats","cargo_liters","price_usd","popularity_score","comfort_score","reliability_score","tech_score","ownership_cost_score","safety_rating"]].copy()
+    X = X.fillna(X.mean(numeric_only=True))
+    scaler = StandardScaler()
+    Enum = scaler.fit_transform(X.values.astype("float32")).astype("float32")
+    np.save(EMB_NUM_NPY, Enum)
+    return Etext, Enum
+
+def load_overrides():
+    if os.path.exists(TRIMS_OVERRIDES):
+        try:
+            with open(TRIMS_OVERRIDES, "r", encoding="utf-8") as f: return json.load(f)
+        except Exception: return {}
+    return {}
+
+def save_overrides(data):
+    with open(TRIMS_OVERRIDES, "w", encoding="utf-8") as f: json.dump(data, f, indent=2, ensure_ascii=False)
+
+def learned_trims_from_csv(df):
+    out = {}
+    for (mk, md), sub in df.groupby(["make", "model"]):
+        vals = (sub["trim_display"].dropna().astype(str).map(str.strip).replace({"": np.nan}).dropna().value_counts().index.tolist())
+        if vals: out[(_norm(mk), _norm(md))] = vals[:20]
+    return out
+
+def get_trims_for(make, model, learned, overrides):
+    if overrides.get(make, {}).get(model): return overrides[make][model]
+    mk, md = _norm(make), _norm(model)
+    if (mk, md) in REAL_TRIMS_N: return REAL_TRIMS_N[(mk, md)]
+    if (mk, md) in learned: return learned[(mk, md)]
+    return ["Base"]
+
+def wiki_image(make, model, year=None):
+    q = f"{year} {make} {model}" if year else f"{make} {model}"
+    try:
+        r = requests.get("https://en.wikipedia.org/w/api.php", params={"action":"query","format":"json","prop":"pageimages","piprop":"thumbnail","pithumbsize":600,"generator":"search","gsrsearch":q,"gsrlimit":1,"gsrnamespace":0}, timeout=6).json()
+        pages = r.get("query",{}).get("pages",{})
+        if pages:
+            page = next(iter(pages.values()))
+            return page.get("thumbnail",{}).get("source")
+    except Exception:
+        pass
+    return None
+
+def cosine_sim_row_vs_mat(mat, vec):
+    mat = mat / (np.linalg.norm(mat, axis=1, keepdims=True)+1e-9)
+    v = vec / (np.linalg.norm(vec)+1e-9)
+    return mat @ v
+
+def recommend(df, Etext, Enum, make, model, trim, year, topk, alpha, body, fuel, y_min, y_max, p_min, p_max, safety, reliab, cross_brand_only=True, exclude_same_model=True, unique_brand=True):
+    sub = df[(df["make"]==make) & (df["model"]==model)].copy()
+    if trim: sub = sub[sub["trim_display"].astype(str).str.lower()==str(trim).lower()]
+    if year: sub = sub[pd.to_numeric(sub["year"], errors="coerce")==int(year)]
+    if sub.empty:
+        sub = df[(df["make"]==make) & (df["model"]==model)].copy()
+        if sub.empty: return "No such make/model in dataset.", None, "", []
+    a = sub.sort_values("popularity_score", ascending=False).iloc[0]
+    a_idx = int(a.name)
+    pool = df.copy()
+    if cross_brand_only: pool = pool[pool["make"] != a["make"]]
+    if exclude_same_model: pool = pool[~((pool["make"]==a["make"]) & (pool["model"]==a["model"]))]
+    if body and body!="Any": pool = pool[pool["body_type"]==body]
+    if fuel and fuel!="Any": pool = pool[pool["fuel"]==fuel]
+    pool = pool[(pool["year"]>=y_min) & (pool["year"]<=y_max)]
+    pool = pool[(pool["price_usd"]>=p_min) & (pool["price_usd"]<=p_max)]
+    pool = pool[(pool["safety_rating"]>=safety) & (pool["reliability_score"]>=reliab)]
+    if pool.empty: return "No cars after your filters. Loosen price/year/safety.", None, "", []
+    cand_idx = pool.index.values
+    st = cosine_sim_row_vs_mat(Etext[cand_idx], Etext[a_idx])
+    sn = cosine_sim_row_vs_mat(Enum[cand_idx], Enum[a_idx])
+    s = float(alpha)*st + (1-float(alpha))*sn
+    order = np.argsort(-s)
+    chosen, seen = [], set()
+    for j in order:
+        k = cand_idx[j]
+        brand = str(df.loc[k,"make"]).lower()
+        if unique_brand and brand in seen: continue
+        seen.add(brand)
+        chosen.append(k)
+        if len(chosen) >= int(topk): break
+    if not chosen: return "No recommendations after constraints.", None, "", []
+    out = df.loc[chosen].copy()
+    sim_lookup = {cand_idx[i]: float(s[i]) for i in range(len(cand_idx))}
+    out["similarity_%"] = [round(sim_lookup[k]*100,1) for k in chosen]
+    cols = ["name","make","model","trim_display","year","body_type","fuel","engine_type","price_usd","horsepower","zero_to_100_kmh_s","popularity_score","comfort_score","reliability_score","tech_score","ownership_cost_score","safety_rating","similarity_%"]
+    table = out[[c for c in cols if c in out.columns]].reset_index(drop=True)
+    disp_trim = str(a.get("trim_display","")).strip()
+    anchor_md = (f"**{a['make']} {a['model']} {disp_trim} {int(a['year']) if pd.notna(a['year']) else ''}**  \n"
+                 f"Body: {a.get('body_type','')} • Fuel: {a.get('fuel','')} • Engine: {a.get('engine_type','')}  \n"
+                 f"HP: {int(a['horsepower']) if pd.notna(a['horsepower']) else '—'} • 0–100: {a.get('zero_to_100_kmh_s','—')}s "
+                 f"• Price: ${int(a['price_usd']) if pd.notna(a['price_usd']) else '—'}  \n"
+                 f"Popularity {int(a.get('popularity_score',0))}/10 • Comfort {int(a.get('comfort_score',0))}/10 • "
+                 f"Reliability {int(a.get('reliability_score',0))}/100 • Safety {int(a.get('safety_rating',0))}★")
+    cards = []
+    for _, r in out.head(3).iterrows():
+        img = wiki_image(r.get("make",""), r.get("model",""), r.get("year",None))
+        title = f"{r.get('make','')} {r.get('model','')} {str(r.get('trim_display','')).strip()}"
+        cards.append((img, title))
+    return None, table, anchor_md, cards
+
+def build_app():
+    df = unify_columns(load_df())
+    if suspicious_zero_to_100(df["zero_to_100_kmh_s"]): df["zero_to_100_kmh_s"] = df.apply(estimate_0_100, axis=1)
+    Etext, Enum = ensure_embeddings(df)
+    learned = learned_trims_from_csv(df)
+    overrides = load_overrides()
+    makes = sorted(df["make"].dropna().astype(str).unique().tolist())
+    body_choices = ["Any"] + sorted([b for b in df["body_type"].dropna().astype(str).unique().tolist() if b])
+    fuel_choices = ["Any"] + sorted([f for f in df["fuel"].dropna().astype(str).unique().tolist() if f])
+    y_lo, y_hi = int(df["year"].min(skipna=True)), int(df["year"].max(skipna=True))
+    p_lo, p_hi = int(df["price_usd"].min(skipna=True)), int(df["price_usd"].max(skipna=True))
+
+    def models_for(make):
+        if not make: return gr.update(choices=[], value=None)
+        opts = sorted(df.loc[df["make"].eq(make), "model"].dropna().astype(str).unique().tolist())
+        return gr.update(choices=opts, value=None)
+
+    def trims_years_for(make, model):
+        if not make or not model: return gr.update(choices=[], value=None), gr.update(choices=[], value=None)
+        trims = get_trims_for(make, model, learned, overrides)
+        years = sorted(pd.to_numeric(df[(df["make"]==make)&(df["model"]==model)]["year"], errors="coerce").dropna().astype(int).unique().tolist())
+        return gr.update(choices=trims, value=None), gr.update(choices=[None]+years, value=None)
+
+    with gr.Blocks(theme=gr.themes.Soft(), title="RideSearch") as demo:
+        gr.Markdown("## RideSearch — cross-brand recommendations with realistic trims & photos")
+        with gr.Tab("Pick & Recommend"):
+            with gr.Row():
+                mk = gr.Dropdown(makes, label="Make")
+                md = gr.Dropdown([], label="Model")
+                tr = gr.Dropdown([], label="Trim (optional)")
+                yr = gr.Dropdown([], label="Year (optional)")
+            mk.change(models_for, mk, md)
+            md.change(lambda a,b: trims_years_for(a,b), [mk, md], [tr, yr])
+            with gr.Row():
+                body = gr.Dropdown(body_choices, value="Any", label="Body")
+                fuel = gr.Dropdown(fuel_choices, value="Any", label="Fuel")
+            with gr.Row():
+                y_min = gr.Slider(y_lo, y_hi, value=y_lo, step=1, label="Year min")
+                y_max = gr.Slider(y_lo, y_hi, value=y_hi, step=1, label="Year max")
+            with gr.Row():
+                p_min = gr.Slider(p_lo, p_hi, value=p_lo, step=500, label="Price min (USD)")
+                p_max = gr.Slider(p_lo, p_hi, value=min(p_hi, max(p_lo+5000, p_lo+20000)), step=500, label="Price max (USD)")
+            with gr.Row():
+                safety = gr.Slider(3, 5, value=4, step=1, label="Min Safety ★")
+                reliab = gr.Slider(55, 99, value=70, step=1, label="Min Reliability")
+            with gr.Row():
+                topk = gr.Slider(1, 10, value=5, step=1, label="Recommendations")
+                alpha = gr.Slider(0, 1, value=0.7, step=0.05, label="α — Text vs Numeric")
+            with gr.Row():
+                cross = gr.Checkbox(True, label="Cross-brand only")
+                xmodel = gr.Checkbox(True, label="Exclude same model family")
+                uniqb = gr.Checkbox(True, label="Unique brands (no repeats)")
+            run = gr.Button("Recommend", variant="primary")
+            err = gr.Markdown()
+            anchor_md = gr.Markdown()
+            table = gr.Dataframe(interactive=False, wrap=True, label="Recommendations")
+            gallery = gr.Gallery(label="Photos", height=220, columns=[3])
+
+            def on_click(mk_, md_, tr_, yr_, topk_, alpha_, body_, fuel_, y_min_, y_max_, p_min_, p_max_, safety_, reliab_, cross_, xmodel_, uniqb_):
+                msg, tbl, atext, cards = recommend(
+                    df, Etext, Enum, mk_, md_, tr_, yr_, int(topk_), float(alpha_),
+                    body_, fuel_, int(y_min_), int(y_max_), int(p_min_), int(p_max_), int(safety_), int(reliab_),
+                    cross_brand_only=bool(cross_), exclude_same_model=bool(xmodel_), unique_brand=bool(uniqb_)
+                )
+                if msg: return gr.update(value=f"**{msg}**"), gr.update(value=""), pd.DataFrame(), []
+                return gr.update(value=""), gr.update(value=atext), tbl, cards
+
+            run.click(on_click,
+                      [mk, md, tr, yr, topk, alpha, body, fuel, y_min, y_max, p_min, p_max, safety, reliab, cross, xmodel, uniqb],
+                      [err, anchor_md, table, gallery])
+
+        with gr.Tab("Admin • Trim Overrides"):
+            gr.Markdown("Paste correct trims (one per line) for a model. Saved to trims_overrides.json.")
+            a_mk = gr.Dropdown(makes, label="Make")
+            a_md = gr.Dropdown([], label="Model")
+            a_txt = gr.Textbox(lines=8, label="Display trims (one per line)")
+            save_btn = gr.Button("Save override")
+            save_msg = gr.Markdown()
+            a_mk.change(models_for, a_mk, a_md)
+
+            def do_save(make, model, txt):
+                nonlocal overrides
+                trims = [t.strip() for t in str(txt).splitlines() if t.strip()]
+                if not make or not model or not trims: return "⚠️ Provide make, model, and at least one trim."
+                if make not in overrides: overrides[make] = {}
+                overrides[make][model] = trims
+                save_overrides(overrides)
+                return f"✅ Saved {len(trims)} trims for {make} {model}. Refresh the Pick tab."
+            save_btn.click(do_save, [a_mk, a_md, a_txt], save_msg)
+
+        gr.Markdown("First run may be slow while embeddings build.")
+    return demo
+
+if __name__ == "__main__":
+    demo = build_app()
+    demo.queue().launch(server_name="0.0.0.0", server_port=7860)