chore(release): bump version to v1.0.9

feat(recipe): add bulk Repair Metadata for Selected operation to recipes page
Adds a new bulk operation in the recipes page that allows users to select multiple recipes and repair their metadata in batch. Backend: - New POST /api/lm/recipes/repair-bulk endpoint accepting recipe_ids array - repair_recipes_bulk handler iterates repair_recipe_by_id for each recipe - Response includes per-recipe updated data for frontend card refresh Frontend: - Bulk context menu: new 'Repair Metadata for Selected' item in Metadata section - BulkManager.repairSelectedRecipes() with loading/toast flow - Uses VirtualScroller.updateSingleItem() per repaired recipe (no full reload) - Visibility controlled via repairMetadata actionConfig flag Locales: - Added repairMetadata, repairBulkComplete, repairBulkSkipped, repairBulkFailed - Translated across all 9 supported languages
2026-06-09 12:39:23 -03:00 · 2026-05-28 21:46:46 +08:00 · 2026-05-28 20:16:59 +08:00 · 2026-05-28 19:11:49 +08:00 · 2026-05-28 17:19:27 +08:00 · 2026-05-28 15:46:38 +08:00
156 changed files with 8077 additions and 1621 deletions
--- a/.gitignore
+++ b/.gitignore
@@ -15,7 +15,9 @@ model_cache/
 # agent
 .opencode/
 .claude/
+.sisyphus/
 .codex
+.omo

 # Vue widgets development cache (but keep build output)
 vue-widgets/node_modules/
--- a/README.md
+++ b/README.md
--- a/data/supporters.json
+++ b/data/supporters.json
@@ -12,43 +12,36 @@
    "2018cfh",
    "W+K+White",
    "wackop",
-    "Takkan",
+    "Phil",
    "Carl G.",
+    "Arlecchino Shion",
+    "Charles Blakemore",
+    "Rob Williams",
    "$MetaSamsara",
-    "itismyelement",
-    "onesecondinosaur",
    "stone9k",
    "Rosenthal",
    "Francisco Tatis",
-    "Andrew Wilson",
-    "Greybush",
-    "Gooohokrbe",
-    "Ricky Carter",
    "JongWon Han",
-    "OldBones",
-    "VantAI",
    "runte3221",
    "FreelancerZ",
-    "Edgar Tejeda",
-    "Liam MacDougal",
    "Fraser Cross",
    "Polymorphic Indeterminate",
-    "Birdy",
    "Marc Whiffen",
-    "Jorge Hussni",
-    "Kiba",
    "Skalabananen",
+    "Birdy",
+    "Kiba",
+    "Mozzel",
+    "itismyelement",
+    "Gingko Biloba",
    "Reno Lam",
+    "onesecondinosaur",
    "sig",
    "Christian Byrne",
    "DM",
    "Sen314",
    "Estragon",
    "J\\B/ 8r0wns0n",
-    "Snaggwort",
-    "Arlecchino Shion",
-    "Charles Blakemore",
-    "Rob Williams",
+    "Takkan",
    "ClockDaemon",
    "KD",
    "Omnidex",
@@ -56,20 +49,20 @@
    "Release Cabrakan",
    "Tobi_Swagg",
    "SG",
-    "carozzz",
    "James Dooley",
    "zenbound",
    "Buzzard",
    "jmack",
+    "Andrew Wilson",
+    "Greybush",
    "Mark Corneglio",
    "SarcasticHashtag",
-    "Cosmosis",
    "iamresist",
-    "RedrockVP",
    "Wolffen",
-    "FloPro4Sho",
+    "Ricky Carter",
    "James Todd",
    "Steven Pfeiffer",
+    "VantAI",
    "Tim",
    "Lisster",
    "Michael Wong",
@@ -77,8 +70,6 @@
    "Tom Corrigan",
    "JackieWang",
    "fnkylove",
-    "Julian V",
-    "Steven Owens",
    "Yushio",
    "Vik71it",
    "Echo",
@@ -86,18 +77,16 @@
    "Robert Stacey",
    "PM",
    "Todd Keck",
-    "Mozzel",
-    "Gingko Biloba",
+    "Edgar Tejeda",
+    "Jorge Hussni",
+    "Liam MacDougal",
    "Sterilized",
    "BadassArabianMofo",
-    "Pascal Dahle",
    "quarz",
    "Greg",
-    "Penfore",
    "JSST",
-    "esthe",
+    "Snaggwort",
    "lmsupporter",
-    "IamAyam",
    "wfpearl",
    "Baekdoosixt",
    "Jonathan Ross",
@@ -110,18 +99,19 @@
    "contrite831",
    "Alex",
    "bh",
-    "confiscated Zyra",
+    "carozzz",
    "Marlon Daniels",
    "Starkselle",
    "Aaron Bleuer",
    "LacesOut!",
    "greebles",
    "Adam Shaw",
-    "Tee Gee",
    "Anthony Rizzo",
-    "tarek helmi",
    "M Postkasse",
-    "ASLPro3D",
+    "Gooohokrbe",
+    "RedrockVP",
+    "Wicked Choices by ASLPro3D",
+    "OldBones",
    "Jacob Hoehler",
    "FinalyFree",
    "Weasyl",
@@ -129,7 +119,6 @@
    "Johnny",
    "Cory Paza",
    "Tak",
-    "Gonzalo Andre Allendes Lopez",
    "Zach Gonser",
    "Big Red",
    "whudunit",
@@ -138,149 +127,124 @@
    "Philip Hempel",
    "corde",
    "Nick Walker",
-    "lh qwe",
    "Bishoujoker",
-    "conner",
    "aai",
    "Briton Heilbrun",
    "Tori",
    "wildnut",
-    "Princess Bright Eyes",
-    "AbstractAss",
-    "Felipe dos Santos",
-    "ViperC",
    "jean jahren",
    "Aleksander Wujczyk",
    "AM Kuro",
-    "Markus",
-    "S Sang",
+    "Pascal Dahle",
+    "Penfore",
+    "Sangheili460",
+    "MagnaInsomnia",
    "Karl P.",
    "Akira_HentAI",
-    "MagnaInsomnia",
    "Gordon Cole",
-    "yuxz69",
-    "Douglas Gaspar",
-    "AlexDuKaNa",
-    "George",
+    "AbstractAss",
    "andrew.tappan",
-    "dw",
    "N/A",
    "The Spawn",
-    "Phil",
    "graysock",
    "Greenmoustache",
    "zounic",
    "fancypants",
+    "Eldithor",
    "Digital",
    "JaxMax",
    "takyamtom",
-    "奚明 刘",
    "Jwk0205",
    "Bro Xie",
-    "준희 김",
    "batblue",
    "carey6409",
    "Olive",
    "太郎 ゲーム",
    "Some Guy Named Barry",
-    "Max Marklund",
-    "Tomohiro Baba",
-    "David Ortega",
+    "Cosmosis",
    "AELOX",
    "Nicfit23",
-    "Noora",
+    "FloPro4Sho",
    "wamekukyouzin",
    "drum matthieu",
    "Dogmaster",
    "Matt Wenzel",
-    "Mattssn",
    "Lex Song",
-    "John Saveas",
    "Christopher Michel",
+    "Gonzalo Andre Allendes Lopez",
    "Serge Bekenkamp",
    "Jimmy Ledbetter",
    "LeoZero",
    "Antonio Pontes",
    "ApathyJones",
+    "Julian V",
+    "Steven Owens",
    "nahinahi9",
    "Dustin Chen",
    "dan",
-    "Yaboi",
    "Mouthlessman",
-    "Steam Steam",
-    "Damon Cunliffe",
-    "CryptoTraderJK",
-    "Davaitamin",
    "otaku fra",
+    "ViperC",
    "Ran C",
-    "tedcor",
-    "Fotek Design",
+    "MiraiKuriyamaSy",
+    "yuxz69",
    "Adam Taylor",
    "Weird_With_A_Beard",
-    "MadSpin",
+    "esthe",
    "Pozadine1",
    "Qarob",
    "AIGooner",
-    "inbijiburu",
    "Luc",
    "ProtonPrince",
    "DiffDuck",
    "elu3199",
-    "Nick “Loadstone” D",
    "Hasturkun",
    "Jon Sandman",
    "Ubivis",
    "CloudValley",
-    "thesoftwaredruid",
-    "wundershark",
-    "mr_dinosaur",
    "linnfrey",
-    "Gamalonia",
-    "Vir",
-    "Pkrsky",
+    "IamAyam",
+    "skaterb949",
    "Joboshy",
    "Bohemian Corporal",
    "Dan",
-    "Josef Lanzl",
-    "Seth Christensen",
-    "Griffin Dahlberg",
-    "Draven T",
+    "confiscated Zyra",
    "yer fey",
    "Error_Rule34_Not_found",
-    "Gerald Welly",
    "Roslynd",
-    "Geolog",
+    "Tee Gee",
    "jinxedx",
+    "tarek helmi",
    "Neco28",
-    "Aquatic Coffee",
+    "Max Marklund",
+    "David Ortega",
    "Dankin",
-    "ethanfel",
    "Cristian Vazquez",
    "Frank Nitty",
    "Magic Noob",
-    "Focuschannel",
+    "Pronredn",
    "DougPeterson",
    "Jeff",
    "Bruce",
+    "lh qwe",
    "Kevin John Duck",
-    "Anthony Faxlandez",
+    "conner",
    "Kevin Christopher",
-    "Ouro Boros",
    "Blackfish95",
    "dd",
+    "Princess Bright Eyes",
    "Paul Kroll",
-    "MiraiKuriyamaSy",
-    "semicolon drainpipe",
-    "Thesharingbrother",
+    "Felipe dos Santos",
    "Bas Imagineer",
-    "Pat Hen",
    "John Statham",
-    "ResidentDeviant",
-    "Nihongasuki",
-    "JC",
-    "Prompt Pirate",
-    "uwutismxd",
+    "Douglas Gaspar",
+    "AlexDuKaNa",
+    "George",
+    "dw",
    "decoy",
+    "thesoftwaredruid",
+    "wundershark",
+    "mr_dinosaur",
    "Tyrswood",
    "Ray Wing",
    "Ranzitho",
@@ -298,80 +262,66 @@
    "Piccio08",
    "kumakichi",
    "cppbel",
-    "starbugx",
-    "Moon Knight",
-    "몽타주",
-    "Kland",
-    "zenobeus",
-    "Jackthemind",
-    "ryoma",
-    "Stryker",
-    "raf8osz",
-    "ElitaSSJ4",
-    "blikkies",
-    "Chris",
+    "奚明 刘",
    "Brian M",
+    "Josef Lanzl",
    "Nerezza",
    "sanborondon",
+    "준희 김",
    "Taylor Funk",
    "aezin",
    "Thought2Form",
    "jcay015",
+    "Gerald Welly",
    "Kevin Picco",
    "Erik Lopez",
-    "Shock Shockor",
    "Mateo Curić",
-    "Goldwaters",
-    "Zude",
+    "Geolog",
    "Eris3D",
+    "Tomohiro Baba",
    "m",
+    "Noora",
    "Pierce McBride",
-    "Joshua Gray",
-    "Kyler",
+    "Mattssn",
    "Mikko Hemilä",
-    "aRtFuL_DodGeR",
    "Jamie Ogletree",
    "a _",
    "James Coleman",
-    "CrimsonDX",
    "Martial",
-    "battu",
    "Emil Andersson",
+    "Ouro Boros",
    "Chad Idk",
-    "DarkSunset",
-    "Billy Gladky",
+    "Steam Steam",
+    "CryptoTraderJK",
    "Yuji Kaneko",
-    "Probis",
+    "Davaitamin",
    "Dušan Ryban",
-    "ItsGeneralButtNaked",
-    "Jordan Shaw",
    "Rops Alot",
+    "tedcor",
    "Sam",
+    "Fotek Design",
    "sjon kreutz",
-    "Nimess",
-    "SRDB",
    "Ace Ventura",
-    "g unit",
-    "Youguang",
+    "MadSpin",
    "Metryman55",
-    "andrewzpong",
-    "FrxzenSnxw",
-    "BossGame",
-    "lrdchs",
+    "inbijiburu",
+    "Nick “Loadstone” D",
+    "Gamalonia",
    "momokai",
+    "starbugx",
+    "Moon Knight",
+    "몽타주",
+    "Kland",
    "Hailshem",
    "kudari",
    "Naomi Hale Danchi",
    "dc7431",
    "ken",
-    "Inversity",
-    "AIVORY3D",
    "epicgamer0020690",
    "Joshua Porrata",
    "keemun",
    "SuBu",
    "RedPIXel",
-    "Kevinj",
    "Wind",
    "Nexus",
    "Ramneek“Guy”Ashok",
@@ -383,82 +333,62 @@
    "JohnDoe42054",
    "BillyHill",
    "emyth",
-    "chriphost",
-    "KitKatM",
-    "socrasteeze",
-    "ResidentDeviant",
+    "Vir",
    "gzmzmvp",
-    "Welkor",
-    "John Martin",
    "Richard",
    "Andrew",
    "Robert Wegemund",
    "Littlehuggy",
-    "moranqianlong",
    "Gregory Kozhemiak",
+    "Draven T",
    "mrjuan",
    "Brian Buie",
    "Sadlip",
-    "Haru Yotu",
    "Eric Whitney",
    "Joey Callahan",
+    "Aquatic Coffee",
    "Ivan Tadic",
    "Mike Simone",
+    "ethanfel",
+    "Joshua Gray",
    "Morgandel",
-    "Kyron Mahan",
-    "Matura Arbeit",
+    "Focuschannel",
    "Noah",
    "Jacob McDaniel",
    "X",
    "Sloan Steddy",
-    "TBitz33",
-    "Anonym dkjglfleeoeldldldlkf",
    "Temikus",
    "Artokun",
    "Michael Taylor",
-    "SendingRavens",
    "Derek Baker",
+    "Anthony Faxlandez",
+    "battu",
    "Michael Anthony Scott",
    "Atilla Berke Pekduyar",
-    "Michael Docherty",
-    "Nathan",
    "Decx _",
-    "Paul Hartsuyker",
-    "elitassj",
-    "Jacob Winter",
-    "Distortik",
-    "David",
-    "Meilo",
-    "Pen Bouryoung",
+    "Pat Hen",
+    "Jordan Shaw",
    "四糸凜音",
-    "shinonomeiro",
-    "Snille",
-    "MaartenAlbers",
-    "khanh duy",
-    "xybrightsummer",
-    "jreedatchison",
-    "PhilW",
-    "Tree Tagger",
-    "Janik",
+    "Nihongasuki",
+    "JC",
+    "Prompt Pirate",
+    "uwutismxd",
+    "FrxzenSnxw",
+    "zenobeus",
    "Crocket",
-    "Cruel",
-    "MRBlack",
-    "Mitchell Robson",
-    "Kiyoe",
-    "humptynutz",
-    "michael.isaza",
-    "Kalnei",
-    "Whitepinetrader",
+    "Jackthemind",
+    "chriphost",
+    "KitKatM",
+    "ryoma",
+    "socrasteeze",
    "OrganicArtifact",
-    "Scott",
+    "Stryker",
+    "ResidentDeviant",
    "MudkipMedkitz",
    "deanbrian",
-    "POPPIN",
    "Alex Wortman",
    "Cody",
-    "Raku",
    "smart.edge5178",
-    "emadsultan",
    "InformedViewz",
    "CHKeeho80",
    "Bubbafett",
@@ -466,76 +396,214 @@
    "Menard",
    "Skyfire83",
    "Adam Rinehart",
-    "D",
    "Pitpe11",
    "TheD1rtyD03",
    "moonpetal",
    "SomeDude",
    "g9p0o",
-    "nanana",
    "TheHolySheep",
+    "raf8osz",
    "Monte Won",
    "SpringBootisTrash",
    "carsten",
    "ikok",
-    "Buecyb99",
-    "4IXplr0r3r",
-    "dfklsjfkljslfjd",
-    "hayden",
-    "ahoystan",
-    "Leland Saunders",
+    "ElitaSSJ4",
    "Wolfe7D1",
-    "Ink Temptation",
-    "Bob Barker",
-    "edk",
-    "Kalli Core",
-    "Aeternyx",
+    "blikkies",
+    "Chris",
    "elleshar666",
-    "YOU SINWOO",
-    "ja s",
-    "Doug Mason",
+    "Shock Shockor",
+    "ACTUALLY_the_Real_Willem_Dafoe",
+    "Goldwaters",
    "Kauffy",
-    "Jeremy Townsend",
-    "EpicElric",
-    "Sean voets",
-    "Owen Gwosdz",
+    "Zude",
    "John J Linehan",
+    "Kyler",
    "Elliot E",
-    "Thomas Wanner",
    "Theerat Jiramate",
    "Edward Kennedy",
    "Justin Blaylock",
-    "Devil Lude",
-    "Nick Kage",
-    "kevin stoddard",
-    "Jack Dole",
+    "aRtFuL_DodGeR",
    "Vane Holzer",
    "psytrax",
-    "Ezokewn",
    "hexxish",
-    "CptNeo",
    "notedfakes",
-    "Maso",
-    "Eric Ketchum",
+    "Nathan",
+    "Billy Gladky",
    "NICHOLAS BAXLEY",
    "Michael Scott",
-    "Kevin Wallace",
-    "Matheus Couto",
+    "Probis",
+    "Ed Wang",
+    "Wes Sims",
+    "ItsGeneralButtNaked",
+    "SRDB",
+    "g unit",
+    "Distortik",
+    "Filippo Ferrari",
+    "Youguang",
    "Saya",
+    "andrewzpong",
+    "BossGame",
+    "lrdchs",
+    "Tree Tagger",
+    "Inversity",
+    "AIVORY3D",
+    "Kevinj",
+    "Mitchell Robson",
+    "Whitepinetrader",
+    "POPPIN",
+    "Ginnie",
+    "Raku",
+    "emadsultan",
+    "Pkrsky",
+    "nanana",
+    "FeralOpticsAI",
+    "Pavlaki",
+    "Doug+Rintoul",
+    "Noor",
+    "Yorunai",
+    "quantenmecha",
+    "Jason+Nash",
+    "BillyBoy84",
+    "DarkRoast",
+    "letzte",
+    "Nasty+Hobbit",
+    "Sora+Yori",
+    "lrdchs2",
+    "Duk3+Rand0m",
+    "Nathen+Choi",
+    "T",
+    "LarsesFPC",
+    "cocona",
+    "Buecyb99",
+    "Welkor",
+    "David Schenck",
+    "John Martin",
+    "Ink Temptation",
+    "moranqianlong",
+    "Kalli Core",
+    "Time Valentine",
+    "Михал Михалыч",
+    "Matt",
+    "Frogmilk",
+    "SPJ",
+    "Kyron Mahan",
+    "Bryan Rutkowski",
+    "Nick Kage",
+    "TBitz33",
+    "Anonym dkjglfleeoeldldldlkf",
+    "Cyrus Fett",
+    "Ezokewn",
+    "SendingRavens",
+    "Xenon Xue",
+    "JackJohnnyJim",
+    "Edward Ten Eyck",
+    "Michael Docherty",
+    "Paul Hartsuyker",
+    "Henrique Faiolli",
+    "elitassj",
+    "Solixer",
+    "Jacob Winter",
+    "Ryan Presley Ng",
+    "jinksta187",
+    "Donor4115",
+    "Manu Thetug",
+    "Karlanx",
+    "Lyavph",
+    "David",
+    "Meilo",
+    "operationancut",
+    "shinonomeiro",
+    "Snille",
+    "MaartenAlbers",
+    "khanh duy",
+    "xybrightsummer",
+    "jreedatchison",
+    "PhilW",
+    "Marcus thronico",
+    "Janik",
+    "Cruel",
+    "MRBlack",
+    "Kiyoe",
+    "humptynutz",
+    "michael.isaza",
+    "Kalnei",
+    "Scott",
+    "Muratoraccio",
+    "D",
+    "YassineKhaled",
+    "Y",
+    "MatteKey",
+    "Flob",
+    "ShiroSenpai",
+    "Inkognito",
+    "G",
+    "Tan+Huynh",
+    "D",
+    "Dark_Pest",
+    "Alex",
+    "Jacky+Ho",
+    "Karru",
+    "ghoulars",
+    "ChaChanoKo",
+    "null",
+    "Beau",
+    "redcarrot",
+    "powerbot99",
+    "Fthehappy",
+    "rsamerica",
+    "sfasdfasfdsa",
+    "Alan+Cano",
+    "generic404",
+    "abattoirblues",
+    "zounik",
+    "4IXplr0r3r",
+    "hayden",
+    "ahoystan",
+    "Bob Barker",
+    "edk",
+    "JBsuede",
+    "Christian Schäfer",
+    "りん あめ",
+    "ja s",
+    "Doug Mason",
+    "Jeremy Townsend",
+    "Dave Abraham",
+    "Joaquin Hierrezuelo",
+    "Locrospiel",
+    "Sean voets",
+    "Owen Gwosdz",
+    "Jarrid Lee",
+    "Kor",
+    "Joseph Hanson",
+    "John Rednoulf",
+    "Boba Smith",
+    "Devil Lude",
+    "David Murcko",
+    "Jack Dole",
+    "max blo",
+    "Sauv",
+    "Steven",
+    "CptNeo",
+    "TenaciousD",
+    "Dmitry Ryzhov",
+    "Khánh Đặng",
+    "Maso",
+    "Eric Ketchum",
+    "Kevin Wallace",
+    "Jimmy Borup",
    "ChicRic",
    "mercur",
-    "J C",
-    "Ed Wang",
-    "Ryan Presley Ng",
-    "Wes Sims",
-    "Donor4115",
+    "Pete Pain",
+    "RHopkirk",
+    "Andrew Wilkinson",
+    "Yavizu3d",
+    "Maxim",
    "Yves Poezevara",
    "Teriak47",
    "Just me",
    "Raf Stahelin",
    "Вячеслав Маринин",
-    "Lyavph",
-    "Filippo Ferrari",
    "Cola Matthew",
    "OniNoKen",
    "Iain Wisely",
@@ -555,7 +623,6 @@
    "pixl",
    "Robin",
    "chahknoir",
-    "Marcus thronico",
    "nd",
    "keno94d",
    "James Melzer",
@@ -569,6 +636,7 @@
    "Captain_Swag",
    "obkircher",
    "gwyar",
+    "ResidentDeviant",
    "D",
    "edgecase",
    "Neoxena",
@@ -576,98 +644,137 @@
    "dg",
    "Maarten Harms",
    "Israel",
-    "Muratoraccio",
    "SelfishMedic",
-    "Ginnie",
    "adderleighn",
    "EnragedAntelope",
-    "Alan+Cano",
-    "FeralOpticsAI",
-    "Pavlaki",
-    "generic404",
+    "Kachac",
+    "tyrant2811",
+    "Kevin",
+    "Rune+Osnes",
+    "jcx29",
+    "cloudghost",
+    "Yongkwan+Lee",
+    "PoorStudent",
+    "lucites",
+    "Alex+Zaw",
+    "Mobius2020",
+    "ExLightSaber",
+    "YaboiRay",
+    "Drizzly",
+    "Sildoren",
+    "Darvidous",
+    "Seon+Song",
+    "2turbo",
+    "balut+omelette",
+    "Nebuleux",
+    "Dmitry+Viznesenskiy",
+    "Tanjin90",
+    "Somebody",
+    "sternenkrieger",
+    "eriick",
+    "Join+Chun",
+    "Pascalou",
+    "lighthawke",
+    "Terraformer",
+    "GDS+DEV",
+    "4rt+r3d",
+    "low9",
+    "Winged",
+    "you+halo9",
+    "Somebody",
+    "Somebody",
+    "Crescent~San",
+    "AiGirlTS",
+    "datasl4ve",
+    "Somebody",
+    "koopa990",
+    "The+Forgetful+Dev",
    "Mateusz+Kosela",
-    "Doug+Rintoul",
-    "Noor",
-    "Yorunai",
    "Bula",
-    "quantenmecha",
-    "abattoirblues",
-    "Jason+Nash",
-    "BillyBoy84",
-    "DarkRoast",
-    "zounik",
-    "letzte",
-    "Nasty+Hobbit",
-    "SgtFluffles",
-    "lrdchs2",
-    "Duk3+Rand0m",
    "KUJYAKU",
-    "NathenChoi",
-    "Thomas+Reck",
-    "Larses",
-    "cocona",
    "Coeur+de+cochon",
-    "David Schenck",
+    "Obsidian.Studios",
    "han b",
+    "Zomba Mann",
    "Nico",
+    "Maximilian Krischan",
    "Banana Joe",
    "_ G3n",
    "Donovan Jenkins",
-    "JBsuede",
+    "Hans Meier",
+    "Tú Nguyễn Lý Hoàng",
+    "shira1011",
    "Michael Eid",
    "beersandbacon",
-    "Maximilian Pyko",
-    "Invis",
-    "Justin Houston",
-    "Time Valentine",
-    "james",
-    "OrochiNights",
+    "Neko Desco",
+    "Bob barker",
+    "Ben D",
+    "G",
+    "Ronan Delevacq",
+    "karim ben brik",
+    "Vinarus",
    "Michael Zhu",
-    "ACTUALLY_the_Real_Willem_Dafoe",
-    "gonzalo",
+    "Nemisu",
    "Seraphy",
-    "Михал Михалыч",
    "雨の心 落",
-    "Matt",
    "AllTimeNoobie",
+    "Leslie Andrew Ridings",
    "jumpd",
    "John C",
    "Rim",
-    "Dismem",
-    "Frogmilk",
-    "SPJ",
+    "Jairus Knudsen",
+    "Poophead27 Blyat",
    "Xan Dionysus",
    "Nathan lee",
-    "Mewtora",
+    "Lyle Liston",
    "Middo",
    "Forbidden Atelier",
-    "Bryan Rutkowski",
+    "Thomas Sankowski",
+    "Spire",
+    "DrB",
+    "AZ Party Oasis",
    "Adictedtohumping",
    "Towelie",
-    "Cyrus Fett",
+    "Ryan Smith",
+    "MR.Bear",
+    "matt",
+    "dsffsdfsdfsdfsdfsdf",
+    "somethingtosay8",
    "Jean-françois SEMA",
+    "3zS4QNQ4",
+    "Terminuz",
    "Kurt",
-    "max blo",
-    "Xenon Xue",
-    "JackJohnnyJim",
-    "Edward Ten Eyck",
+    "ivistorm",
+    "Ivan Imes",
+    "Faburizu",
+    "Jack Lawfield",
+    "jimyjomson",
+    "Borte",
    "Chase Kwon",
+    "Ted Cart",
+    "Sage Himeros",
    "Inyoshu",
-    "Goober719",
    "Chad Barnes",
+    "Person Y",
+    "David Spearing",
    "James Ming",
    "vanditking",
    "kripitonga",
    "Rizzi",
    "nimin",
    "OMAR LUCIANO",
+    "Ken+Suzuki",
    "hannibal",
    "Jo+Example",
    "BrentBertram",
+    "inusanorthcape",
+    "Tigon",
    "eumelzocker",
    "dxjaymz",
    "L C",
-    "Dude"
+    "Dude",
+    "Somebody",
+    "CK"
  ],
-  "totalCount": 666
+  "totalCount": 773
 }
--- a/docs/LM-Extension-Wiki.md
+++ b/docs/LM-Extension-Wiki.md
@@ -1,183 +0,0 @@
-## Overview
-
-The **LoRA Manager Civitai Extension** is a Browser extension designed to work seamlessly with [LoRA Manager](https://github.com/willmiao/ComfyUI-Lora-Manager) to significantly enhance your browsing experience on [Civitai](https://civitai.com). With this extension, you can:
-
-✅ Instantly see which models are already present in your local library  
-✅ Download new models with a single click  
-✅ Manage downloads efficiently with queue and parallel download support  
-✅ Keep your downloaded models automatically organized according to your custom settings    
-
-![Civitai Models page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-models-page.png) 
-
-**Update:** It now also supports browsing on [CivArchive](https://civarchive.com/) (formerly CivitaiArchive). 
-
-![CivArchive Models page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civarchive-models-page.png)  
-
---
-
-## Why Supporter Access?
-
-LoRA Manager is built with love for the Stable Diffusion and ComfyUI communities. Your support makes it possible for me to keep improving and maintaining the tool full-time.
-
-Supporter-exclusive features help ensure the long-term sustainability of LoRA Manager, allowing continuous updates, new features, and better performance for everyone.
-
-Every contribution directly fuels development and keeps the core LoRA Manager free and open-source. In addition to monthly supporters, one-time donation supporters will also receive a license key, with the duration scaling according to the contribution amount. Thank you for helping keep this project alive and growing. ❤️
-
-
---
-
-## Installation
-
-### Supported Browsers & Installation Methods
-
-| Browser            | Installation Method                                                                 |
-|--------------------|-------------------------------------------------------------------------------------|
-| **Google Chrome**   | [Chrome Web Store link](https://chromewebstore.google.com/detail/capigligggeijgmocnaflanlbghnamgm?utm_source=item-share-cb) |
-| **Microsoft Edge**  | Install via Chrome Web Store (compatible)                                          |
-| **Brave Browser**   | Install via Chrome Web Store (compatible)                                          |
-| **Opera**           | Install via Chrome Web Store (compatible)                                          |
-| **Firefox**         | <div id="firefox-install" class="install-ok"><a href="https://github.com/willmiao/lm-civitai-extension-firefox/releases/latest/download/extension.xpi">📦 Install Firefox Extension (reviewed and verified by Mozilla)</a></div>             |
-
-For non-Chrome browsers (e.g., Microsoft Edge), you can typically install extensions from the Chrome Web Store by following these steps: open the extension’s Chrome Web Store page, click 'Get extension', then click 'Allow' when prompted to enable installations from other stores, and finally click 'Add extension' to complete the installation.
-
---
-
-## Privacy & Security
-
-I understand concerns around browser extensions and privacy, and I want to be fully transparent about how the **LM Civitai Extension** works:
-
- **Reviewed and Verified**  
-  This extension has been **manually reviewed and approved by the Chrome Web Store**. The Firefox version uses the **exact same code** (only the packaging format differs) and has passed **Mozilla’s Add-on review**.
-
- **Minimal Network Access**  
-  The only external server this extension connects to is:  
-  **`https://willmiao.shop`** — used solely for **license validation**.
-
-  It does **not collect, transmit, or store any personal or usage data**.  
-  No browsing history, no user IDs, no analytics, no hidden trackers.
-
- **Local-Only Model Detection**  
-  Model detection and LoRA Manager communication all happen **locally** within your browser, directly interacting with your local LoRA Manager backend.
-
-I value your trust and are committed to keeping your local setup private and secure. If you have any questions, feel free to reach out!
-
---
-
-## How to Use
-
-After installing the extension, you'll automatically receive a **7-day trial** to explore all features.
-
-When the extension is correctly installed and your license is valid:
-
- Open **Civitai**, and you'll see visual indicators added by the extension on model cards, showing:
-  - ✅ Models already present in your local library  
-  - ⬇️ A download button for models not in your library  
-
-Clicking the download button adds the corresponding model version to the download queue, waiting to be downloaded. You can set up to **5 models to download simultaneously**.
-
-### Visual Indicators Appear On:
-
- **Home Page** — Featured models  
- **Models Page**  
- **Creator Profiles** — If the creator has set their models to be visible  
- **Recommended Resources** — On individual model pages  
-
-### Version Buttons on Model Pages
-
-On a specific model page, visual indicators also appear on version buttons, showing which versions are already in your local library.
-
-**Starting from v0.4.8**, model pages use a dedicated download button for better compatibility. When switching to a specific version by clicking a version button:
-
- The new **dedicated download button** directly triggers download via **LoRA Manager**
- The **original download button** remains unchanged for standard browser downloads
-
-![Civitai Model Page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-model-page.png)
-
-### Hide Models Already in Library (Beta)
-
-**New in v0.4.8**: A new **Hide models already in library (Beta)** option makes it easier to focus on models you haven't added yet. It can be enabled from Settings, or toggled quickly using **Ctrl + Shift + H** (macOS: **Command + Shift + H**).
-
-### Resources on Image Pages — now shows in-library indicators for image resources plus one-click recipe import
-
- **One-Click Import Civitai Image as Recipe** — Import any Civitai image as a recipe with a single click in the Resources Used panel.
- **Auto-Queue Missing Assets** — In Settings you can decide if LoRAs or checkpoints referenced by that image should automatically be added to your download queue.
- **More Accurate Metadata** — Importing directly from the page is faster than copying inside LM and keeps on-site tags and other metadata perfectly aligned.
-
-![Civitai Image Page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-image-page.jpg)
-
-[![alt](url)](https://github.com/user-attachments/assets/41fd4240-c949-4f83-bde7-8f3124c09494)
-
---
-
-## Model Download Location & LoRA Manager Settings
-
-To use the **one-click download function**, you must first set:
-
- Your **Default LoRAs Root**  
- Your **Default Checkpoints Root**  
-
-These are set within LoRA Manager's settings.
-
-When everything is configured, downloaded model files will be placed in:  
-
-`<Default_Models_Root>/<Base_Model_of_the_Model>/<First_Tag_of_the_Model>`
-
-
-### Update: Default Path Customization (2025-07-21)  
-
-A new setting to customize the default download path has been added in the nightly version. You can now personalize where models are saved when downloading via the LM Civitai Extension.
-
-![Default Path Customization](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/default-path-customization.png)
-
-The previous YAML path mapping file will be deprecated—settings will now be unified in settings.json to simplify configuration.
-
---
-
-## Backend Port Configuration
-
-If your **ComfyUI** or **LoRA Manager** backend is running on a port **other than the default 8188**, you must configure the backend port in the extension's settings.
-
-After correctly setting and saving the port, you'll see in the extension's header area:  
- A **Healthy** status with the tooltip:  `Connected to LoRA Manager on port xxxx`
-
-
---
-
-## Advanced Usage
-
-### Connecting to a Remote LoRA Manager
-
-If your LoRA Manager is running on another computer, you can still connect from your browser using port forwarding.
-
-> **Why can't you set a remote IP directly?**
->
-> For privacy and security, the extension only requests access to `http://127.0.0.1/*`. Supporting remote IPs would require much broader permissions, which may be rejected by browser stores and could raise user concerns.
-
-**Solution: Port Forwarding with `socat`**
-
-On your browser computer, run:
-
-`socat TCP-LISTEN:8188,bind=127.0.0.1,fork TCP:REMOTE.IP.ADDRESS.HERE:8188`
-
- Replace `REMOTE.IP.ADDRESS.HERE` with the IP of the machine running LoRA Manager.
- Adjust the port if needed.
-
-This lets the extension connect to `127.0.0.1:8188` as usual, with traffic forwarded to your remote server.
-
-_Thanks to user **Temikus** for sharing this solution!_
-
---
-
-## Roadmap
-
-The extension will evolve alongside **LoRA Manager** improvements. Planned features include:
-
- [x] Support for **additional model types** (e.g., embeddings)
- [x] One-click **Recipe Import**
- [x] Display of in-library status for all resources in the **Resources Used** section of the image page
- [x] One-click **Auto-organize Models**
- [x] **Hide models already in library (Beta)** - Focus on models you haven't added yet
-
-**Stay tuned — and thank you for your support!**
-
---
--- a/locales/de.json
+++ b/locales/de.json
@@ -15,7 +15,8 @@
            "settings": "Einstellungen",
            "help": "Hilfe",
            "add": "Hinzufügen",
-            "close": "Schließen"
+            "close": "Schließen",
+            "menu": "Menü"
        },
        "status": {
            "loading": "Wird geladen...",
@@ -231,7 +232,10 @@
            "license": "Lizenz",
            "noCreditRequired": "Kein Credit erforderlich",
            "allowSellingGeneratedContent": "Verkauf erlaubt",
+            "allowSellingGeneratedContentTooltip": "Verkauf generierter Bilder erlauben",
+            "noCreditRequiredTooltip": "Modell ohne Nennung des Erstellers verwenden",
            "noTags": "Keine Tags",
+            "autoTags": "Auto-Tags",
            "noBaseModelMatches": "Keine Basismodelle entsprechen der aktuellen Suche.",
            "clearAll": "Alle Filter löschen",
            "any": "Beliebig",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "Download-Backend",
-            "help": "Wähle aus, wie Modelldateien heruntergeladen werden. Python verwendet den eingebauten Downloader. aria2 verwendet den experimentellen externen Downloader-Prozess.",
+            "help": "Wähle aus, wie Modelldateien heruntergeladen werden. Python verwendet den eingebauten Downloader. aria2 verwendet den empfohlenen externen Downloader-Prozess.",
            "options": {
                "python": "Python (integriert)",
-                "aria2": "aria2 (experimentell)"
+                "aria2": "aria2 (empfohlen)"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "Bei Hover anzeigen"
            },
            "cardInfoDisplayHelp": "Wählen Sie, wann Modellinformationen und Aktionsschaltflächen angezeigt werden sollen",
+            "showVersionOnCard": "Version auf Karte anzeigen",
+            "showVersionOnCardHelp": "Den Versionsnamen auf Modellkarten ein- oder ausblenden",
            "modelCardFooterAction": "Aktion der Modellkarten-Schaltfläche",
            "modelCardFooterActionOptions": {
                "exampleImages": "Beispielbilder öffnen",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "Trigger Words in LoRA-Syntax einschließen",
-            "includeTriggerWordsHelp": "Trainierte Trigger Words beim Kopieren der LoRA-Syntax in die Zwischenablage einschließen"
+            "includeTriggerWordsHelp": "Trainierte Trigger Words beim Kopieren der LoRA-Syntax in die Zwischenablage einschließen",
+            "loraSyntaxFormat": "LoRA-Syntaxformat",
+            "loraSyntaxFormatHelp": "LoRA-Syntaxformat. Der vollständige Pfad enthält den Unterordnerpfad (<lora:style/anime/x:1.0>) für verlustfreie Modellauflösung. Legacy verwendet nur den Dateinamen (<lora:x:1.0>) — A1111-Konvention, kann bei doppelten Dateinamen in verschiedenen Ordnern zu Mehrdeutigkeiten führen.",
+            "loraSyntaxFormatOptions": {
+                "full": "Vollständiger Pfad (Unterordner/Name)",
+                "legacy": "Legacy A1111 (nur Name)"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "Metadaten-Archiv-Datenbank aktivieren",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "Modelliste aktualisieren",
-                "quick": "Änderungen synchronisieren",
-                "quickTooltip": "Nach neuen oder fehlenden Modelldateien suchen, damit die Liste aktuell bleibt.",
                "full": "Cache neu aufbauen",
                "fullTooltip": "Alle Modelldetails aus Metadatendateien neu laden – nutzen, wenn die Bibliothek veraltet wirkt oder nach manuellen Änderungen."
            },
@@ -679,16 +689,29 @@
            "setContentRating": "Inhaltsbewertung für alle festlegen",
            "copyAll": "Alle Syntax kopieren",
            "refreshAll": "Alle Metadaten aktualisieren",
+            "repairMetadata": "Metadaten der Auswahl reparieren",
            "checkUpdates": "Auswahl auf Updates prüfen",
            "moveAll": "Alle in Ordner verschieben",
            "autoOrganize": "Automatisch organisieren",
            "skipMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle überspringen",
            "resumeMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle fortsetzen",
+            "setFavorite": "Als Favorit setzen",
+            "setFavoriteCount": "Als Favorit setzen ({favorited}/{total})",
+            "unfavorite": "Aus Favoriten entfernen",
            "deleteAll": "Ausgewählte löschen",
            "downloadMissingLoras": "Fehlende LoRAs herunterladen",
+            "downloadExamples": "Beispielbilder herunterladen",
            "clear": "Auswahl löschen",
            "skipMetadataRefreshCount": "Überspringen（{count} Modelle）",
            "resumeMetadataRefreshCount": "Fortsetzen（{count} Modelle）",
+            "sendToWorkflow": "An Workflow senden",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Metadaten",
+                "attributes": "Attribute",
+                "organize": "Organisieren",
+                "download": "Download"
+            },
            "autoOrganizeProgress": {
                "initializing": "Automatische Organisation wird initialisiert...",
                "starting": "Automatische Organisation für {type} wird gestartet...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "Rezeptliste aktualisieren",
-                "quick": "Änderungen synchronisieren",
-                "quickTooltip": "Änderungen synchronisieren - schnelle Aktualisierung ohne Cache-Neubau",
                "full": "Cache neu aufbauen",
                "fullTooltip": "Cache neu aufbauen - vollständiger Rescan aller Rezeptdateien"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "Modelle werden dauerhaft gelöscht.",
            "action": "Alle löschen"
        },
+        "bulkDeleteRecipes": {
+            "title": "Mehrere Rezepte löschen",
+            "message": "Sind Sie sicher, dass Sie alle ausgewählten Rezepte und ihre zugehörigen Dateien löschen möchten?",
+            "countMessage": "Rezepte werden dauerhaft gelöscht.",
+            "action": "Alle löschen"
+        },
        "checkUpdates": {
            "title": "Alle {typePlural} auf Updates prüfen?",
            "message": "Damit werden alle {typePlural} in deiner Bibliothek auf Updates geprüft. Bei großen Sammlungen kann das etwas länger dauern.",
@@ -1154,6 +1181,7 @@
                "editModelName": "Modellname bearbeiten",
                "editFileName": "Dateiname bearbeiten",
                "editBaseModel": "Basis-Modell bearbeiten",
+                "editVersionName": "Versionsname bearbeiten",
                "viewOnCivitai": "Auf Civitai anzeigen",
                "viewOnCivitaiText": "Auf Civitai anzeigen",
                "viewCreatorProfile": "Ersteller-Profil anzeigen",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "Früher Zugriff",
                    "earlyAccessTooltip": "Für diese Version ist derzeit Civitai Early Access erforderlich",
                    "ignored": "Ignoriert",
-                    "ignoredTooltip": "Für diese Version sind Update-Benachrichtigungen deaktiviert"
+                    "ignoredTooltip": "Für diese Version sind Update-Benachrichtigungen deaktiviert",
+                    "onSiteOnly": "Nur On-Site",
+                    "onSiteOnlyTooltip": "Diese Version ist nur für die On-Site-Generierung auf Civitai verfügbar"
                },
                "actions": {
                    "download": "Herunterladen",
                    "downloadTooltip": "Diese Version herunterladen",
                    "downloadEarlyAccessTooltip": "Diese Early-Access-Version von Civitai herunterladen",
+                    "downloadNotAllowedTooltip": "Diese Version ist nur für die On-Site-Generierung auf Civitai verfügbar",
                    "delete": "Löschen",
                    "deleteTooltip": "Diese lokale Version löschen",
                    "ignore": "Ignorieren",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "Failed to browse directory: {message}",
            "batchImportDirectorySelected": "Directory selected: {path}",
            "noRecipesSelected": "Keine Rezepte ausgewählt",
+            "repairBulkComplete": "Reparatur abgeschlossen: {repaired} repariert, {skipped} übersprungen (von {total})",
+            "repairBulkSkipped": "Keine Reparatur für die {total} ausgewählten Rezepte erforderlich",
+            "repairBulkFailed": "Reparatur der ausgewählten Rezepte fehlgeschlagen: {message}",
            "noMissingLorasInSelection": "Keine fehlenden LoRAs in ausgewählten Rezepten gefunden",
            "noLoraRootConfigured": "Kein LoRA-Stammverzeichnis konfiguriert. Bitte legen Sie ein Standard-LoRA-Stammverzeichnis in den Einstellungen fest."
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "Inhaltsbewertung auf {level} für {count} Modell(e) gesetzt",
            "bulkContentRatingPartial": "Inhaltsbewertung auf {level} für {success} Modell(e) gesetzt, {failed} fehlgeschlagen",
            "bulkContentRatingFailed": "Inhaltsbewertung für ausgewählte Modelle konnte nicht aktualisiert werden",
+            "bulkFavoriteUpdating": "Füge {count} Modell(e) zu Favoriten hinzu...",
+            "bulkUnfavoriteUpdating": "Entferne {count} Modell(e) aus Favoriten...",
+            "bulkFavoritePartialAdded": "{success} Modell(e) zu Favoriten hinzugefügt, {failed} fehlgeschlagen",
+            "bulkFavoritePartialRemoved": "{success} Modell(e) aus Favoriten entfernt, {failed} fehlgeschlagen",
+            "bulkFavoriteFailed": "Fehler beim Aktualisieren des Favoritenstatus",
            "bulkUpdatesChecking": "Ausgewählte {type}-Modelle werden auf Updates geprüft...",
            "bulkUpdatesSuccess": "Updates für {count} ausgewählte {type}-Modelle verfügbar",
            "bulkUpdatesNone": "Keine Updates für ausgewählte {type}-Modelle gefunden",
@@ -1895,18 +1934,52 @@
            "warning": "Handlungsbedarf",
            "error": "Aktion erforderlich"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
        "actions": {
            "runAgain": "Erneut ausführen",
-            "exportBundle": "Paket exportieren"
+            "exportBundle": "Paket exportieren",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
        },
        "toast": {
            "loadFailed": "Diagnose konnte nicht geladen werden: {message}",
            "repairSuccess": "Cache-Neuaufbau abgeschlossen.",
            "repairFailed": "Cache-Neuaufbau fehlgeschlagen: {message}",
            "exportSuccess": "Diagnosepaket exportiert.",
-            "exportFailed": "Export des Diagnosepakets fehlgeschlagen: {message}"
+            "exportFailed": "Export des Diagnosepakets fehlgeschlagen: {message}",
+            "conflictsResolved": "{count} Dateinamenskonflikt(e) gelöst.",
+            "conflictsResolveFailed": "Auflösung der Dateinamenskonflikte fehlgeschlagen: {message}"
        }
    },
+    "conflictConfirm": {
+        "title": "Dateinamenskonflikte auflösen",
+        "message": "Umbenennen durch Anhängen eines 4-stelligen Hashs an jeden doppelten Dateinamen.",
+        "note": "Dieser Vorgang benennt Dateien auf der Festplatte um. Modellreferenzen in vorhandenen Workflows müssen möglicherweise aktualisiert werden, wenn Sie das A1111-Syntaxformat verwenden.",
+        "detail": "Beispiel: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Benennt <strong>{count}</strong> Datei(en) in <strong>{groups}</strong> Duplikatgruppe(n) um",
+        "confirm": "Dateien umbenennen",
+        "cancel": "Abbrechen"
+    },
    "banners": {
        "versionMismatch": {
            "title": "Anwendungs-Update erkannt",
--- a/locales/en.json
+++ b/locales/en.json
@@ -15,7 +15,8 @@
            "settings": "Settings",
            "help": "Help",
            "add": "Add",
-            "close": "Close"
+            "close": "Close",
+            "menu": "Menu"
        },
        "status": {
            "loading": "Loading...",
@@ -231,7 +232,10 @@
            "license": "License",
            "noCreditRequired": "No Credit Required",
            "allowSellingGeneratedContent": "Allow Selling",
+            "allowSellingGeneratedContentTooltip": "Allow selling generated images",
+            "noCreditRequiredTooltip": "Use the model without crediting the creator",
            "noTags": "No tags",
+            "autoTags": "Auto Tags",
            "noBaseModelMatches": "No base models match the current search.",
            "clearAll": "Clear All Filters",
            "any": "Any",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "Download backend",
-            "help": "Choose how model files are downloaded. Python uses the built-in downloader. aria2 uses the experimental external downloader process.",
+            "help": "Choose how model files are downloaded. Python uses the built-in downloader. aria2 uses the recommended external downloader process.",
            "options": {
                "python": "Python (built-in)",
-                "aria2": "aria2 (experimental)"
+                "aria2": "aria2 (recommended)"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "Reveal on Hover"
            },
            "cardInfoDisplayHelp": "Choose when to display model information and action buttons",
+            "showVersionOnCard": "Show Version on Card",
+            "showVersionOnCardHelp": "Show or hide the version name on model cards",
            "modelCardFooterAction": "Model Card Button Action",
            "modelCardFooterActionOptions": {
                "exampleImages": "Open Example Images",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "Include Trigger Words in LoRA Syntax",
-            "includeTriggerWordsHelp": "Include trained trigger words when copying LoRA syntax to clipboard"
+            "includeTriggerWordsHelp": "Include trained trigger words when copying LoRA syntax to clipboard",
+            "loraSyntaxFormat": "LoRA Syntax Format",
+            "loraSyntaxFormatHelp": "LoRA syntax format. Full includes subfolder path (<lora:style/anime/x:1.0>) for lossless model resolution. Legacy uses filename only (<lora:x:1.0>) — A1111 convention, may be ambiguous with duplicate filenames across folders.",
+            "loraSyntaxFormatOptions": {
+                "full": "Full path (subfolder/name)",
+                "legacy": "Legacy A1111 (name only)"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "Enable Metadata Archive Database",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "Refresh model list",
-                "quick": "Sync Changes",
-                "quickTooltip": "Scan for new or missing model files so the list stays current.",
                "full": "Rebuild Cache",
                "fullTooltip": "Reload all model details from metadata files—use if the library looks out of date or after manual edits."
            },
@@ -679,16 +689,29 @@
            "setContentRating": "Set Content Rating for Selected",
            "copyAll": "Copy Selected Syntax",
            "refreshAll": "Refresh Selected Metadata",
+            "repairMetadata": "Repair Metadata for Selected",
            "checkUpdates": "Check Updates for Selected",
            "moveAll": "Move Selected to Folder",
            "autoOrganize": "Auto-Organize Selected",
            "skipMetadataRefresh": "Skip Metadata Refresh for Selected",
            "resumeMetadataRefresh": "Resume Metadata Refresh for Selected",
+            "setFavorite": "Set as Favorite",
+            "setFavoriteCount": "Set as Favorite ({favorited}/{total})",
+            "unfavorite": "Remove from Favorites",
            "deleteAll": "Delete Selected",
            "downloadMissingLoras": "Download Missing LoRAs",
+            "downloadExamples": "Download Example Images",
            "clear": "Clear Selection",
            "skipMetadataRefreshCount": "Skip ({count} models)",
            "resumeMetadataRefreshCount": "Resume ({count} models)",
+            "sendToWorkflow": "Send to Workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Metadata",
+                "attributes": "Attributes",
+                "organize": "Organize",
+                "download": "Download"
+            },
            "autoOrganizeProgress": {
                "initializing": "Initializing auto-organize...",
                "starting": "Starting auto-organize for {type}...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "Refresh recipe list",
-                "quick": "Sync Changes",
-                "quickTooltip": "Sync changes - quick refresh without rebuilding cache",
                "full": "Rebuild Cache",
                "fullTooltip": "Rebuild cache - full rescan of all recipe files"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "models will be permanently deleted.",
            "action": "Delete All"
        },
+        "bulkDeleteRecipes": {
+            "title": "Delete Multiple Recipes",
+            "message": "Are you sure you want to delete all selected recipes and their associated files?",
+            "countMessage": "recipes will be permanently deleted.",
+            "action": "Delete All"
+        },
        "checkUpdates": {
            "title": "Check updates for all {typePlural}?",
            "message": "This checks every {typePlural} in your library for updates. Large collections may take a little longer.",
@@ -1154,6 +1181,7 @@
                "editModelName": "Edit model name",
                "editFileName": "Edit file name",
                "editBaseModel": "Edit base model",
+                "editVersionName": "Edit version name",
                "viewOnCivitai": "View on Civitai",
                "viewOnCivitaiText": "View on Civitai",
                "viewCreatorProfile": "View Creator Profile",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "Early Access",
                    "earlyAccessTooltip": "This version currently requires Civitai early access",
                    "ignored": "Ignored",
-                    "ignoredTooltip": "Update notifications are disabled for this version"
+                    "ignoredTooltip": "Update notifications are disabled for this version",
+                    "onSiteOnly": "On-Site Only",
+                    "onSiteOnlyTooltip": "This version is only available for on-site generation on Civitai"
                },
                "actions": {
                    "download": "Download",
                    "downloadTooltip": "Download this version",
                    "downloadEarlyAccessTooltip": "Download this early access version from Civitai",
+                    "downloadNotAllowedTooltip": "This version is only available for on-site generation on Civitai",
                    "delete": "Delete",
                    "deleteTooltip": "Delete this local version",
                    "ignore": "Ignore",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "Failed to browse directory: {message}",
            "batchImportDirectorySelected": "Directory selected: {path}",
            "noRecipesSelected": "No recipes selected",
+            "repairBulkComplete": "Repair complete: {repaired} repaired, {skipped} skipped (of {total})",
+            "repairBulkSkipped": "No repair needed for any of the {total} selected recipes",
+            "repairBulkFailed": "Failed to repair selected recipes: {message}",
            "noMissingLorasInSelection": "No missing LoRAs found in selected recipes",
            "noLoraRootConfigured": "No LoRA root directory configured. Please set a default LoRA root in settings."
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "Set content rating to {level} for {count} model(s)",
            "bulkContentRatingPartial": "Set content rating to {level} for {success} model(s), {failed} failed",
            "bulkContentRatingFailed": "Failed to update content rating for selected models",
+            "bulkFavoriteUpdating": "Adding {count} model(s) to favorites...",
+            "bulkUnfavoriteUpdating": "Removing {count} model(s) from favorites...",
+            "bulkFavoritePartialAdded": "Added {success} model(s) to favorites, {failed} failed",
+            "bulkFavoritePartialRemoved": "Removed {success} model(s) from favorites, {failed} failed",
+            "bulkFavoriteFailed": "Failed to update favorite status for selected models",
            "bulkUpdatesChecking": "Checking selected {type}(s) for updates...",
            "bulkUpdatesSuccess": "Updates available for {count} selected {type}(s)",
            "bulkUpdatesNone": "No updates found for selected {type}(s)",
@@ -1895,18 +1934,52 @@
            "warning": "Needs Attention",
            "error": "Action Required"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
        "actions": {
            "runAgain": "Run Again",
-            "exportBundle": "Export Bundle"
+            "exportBundle": "Export Bundle",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
        },
        "toast": {
            "loadFailed": "Failed to load diagnostics: {message}",
            "repairSuccess": "Cache rebuild completed.",
            "repairFailed": "Cache rebuild failed: {message}",
            "exportSuccess": "Diagnostics bundle exported.",
-            "exportFailed": "Failed to export diagnostics bundle: {message}"
+            "exportFailed": "Failed to export diagnostics bundle: {message}",
+            "conflictsResolved": "{count} filename conflict(s) resolved.",
+            "conflictsResolveFailed": "Failed to resolve filename conflicts: {message}"
        }
    },
+    "conflictConfirm": {
+        "title": "Resolve Filename Conflicts",
+        "message": "Renaming by appending a 4-character hash to each duplicate filename.",
+        "note": "This operation renames files on disk. Model references in existing workflows may need updating if you use the A1111 syntax format.",
+        "detail": "Example: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Will rename <strong>{count}</strong> file(s) across <strong>{groups}</strong> duplicate group(s).",
+        "confirm": "Rename Files",
+        "cancel": "Cancel"
+    },
    "banners": {
        "versionMismatch": {
            "title": "Application Update Detected",
@@ -1936,4 +2009,4 @@
            "retry": "Retry"
        }
    }
-}
+}
--- a/locales/es.json
+++ b/locales/es.json
@@ -15,7 +15,8 @@
            "settings": "Configuración",
            "help": "Ayuda",
            "add": "Añadir",
-            "close": "Cerrar"
+            "close": "Cerrar",
+            "menu": "Menú"
        },
        "status": {
            "loading": "Cargando...",
@@ -231,7 +232,10 @@
            "license": "Licencia",
            "noCreditRequired": "Sin crédito requerido",
            "allowSellingGeneratedContent": "Venta permitida",
+            "allowSellingGeneratedContentTooltip": "Permitir la venta de imágenes generadas",
+            "noCreditRequiredTooltip": "Usar el modelo sin atribuir al creador",
            "noTags": "Sin etiquetas",
+            "autoTags": "Etiquetas automáticas",
            "noBaseModelMatches": "Ningún modelo base coincide con la búsqueda actual.",
            "clearAll": "Limpiar todos los filtros",
            "any": "Cualquiera",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "Backend de descarga",
-            "help": "Elige cómo se descargan los archivos del modelo. Python usa el descargador integrado. aria2 usa el proceso externo experimental de descarga.",
+            "help": "Elige cómo se descargan los archivos del modelo. Python usa el descargador integrado. aria2 usa el proceso externo recomendado de descarga.",
            "options": {
                "python": "Python (integrado)",
-                "aria2": "aria2 (experimental)"
+                "aria2": "aria2 (recomendado)"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "Mostrar al pasar el ratón"
            },
            "cardInfoDisplayHelp": "Elige cuándo mostrar información del modelo y botones de acción",
+            "showVersionOnCard": "Mostrar versión en la tarjeta",
+            "showVersionOnCardHelp": "Mostrar u ocultar el nombre de versión en las tarjetas de modelo",
            "modelCardFooterAction": "Acción del botón de tarjeta de modelo",
            "modelCardFooterActionOptions": {
                "exampleImages": "Abrir imágenes de ejemplo",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "Incluir palabras clave en la sintaxis de LoRA",
-            "includeTriggerWordsHelp": "Incluir palabras clave entrenadas al copiar la sintaxis de LoRA al portapapeles"
+            "includeTriggerWordsHelp": "Incluir palabras clave entrenadas al copiar la sintaxis de LoRA al portapapeles",
+            "loraSyntaxFormat": "Formato de sintaxis LoRA",
+            "loraSyntaxFormatHelp": "Formato de sintaxis LoRA. El formato completo incluye la ruta de la subcarpeta (<lora:style/anime/x:1.0>) para una resolución de modelo sin pérdidas. El formato heredado usa solo el nombre del archivo (<lora:x:1.0>) — convención A1111, puede ser ambiguo con nombres de archivo duplicados entre carpetas.",
+            "loraSyntaxFormatOptions": {
+                "full": "Ruta completa (subcarpeta/nombre)",
+                "legacy": "A1111 heredado (solo nombre)"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "Habilitar base de datos de archivo de metadatos",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "Actualizar lista de modelos",
-                "quick": "Sincronizar cambios",
-                "quickTooltip": "Busca archivos de modelo nuevos o faltantes para mantener la lista al día.",
                "full": "Reconstruir caché",
                "fullTooltip": "Vuelve a cargar todos los detalles desde los archivos de metadatos; úsalo si la biblioteca parece desactualizada o tras ediciones manuales."
            },
@@ -679,16 +689,29 @@
            "setContentRating": "Establecer clasificación de contenido para todos",
            "copyAll": "Copiar toda la sintaxis",
            "refreshAll": "Actualizar todos los metadatos",
+            "repairMetadata": "Reparar metadatos de la selección",
            "checkUpdates": "Comprobar actualizaciones para la selección",
            "moveAll": "Mover todos a carpeta",
            "autoOrganize": "Auto-organizar seleccionados",
            "skipMetadataRefresh": "Omitir actualización de metadatos para seleccionados",
            "resumeMetadataRefresh": "Reanudar actualización de metadatos para seleccionados",
+            "setFavorite": "Marcar como favorito",
+            "setFavoriteCount": "Marcar como favorito ({favorited}/{total})",
+            "unfavorite": "Quitar de favoritos",
            "deleteAll": "Eliminar seleccionados",
            "downloadMissingLoras": "Descargar LoRAs faltantes",
+            "downloadExamples": "Descargar imágenes de ejemplo",
            "clear": "Limpiar selección",
            "skipMetadataRefreshCount": "Omitir（{count} modelos）",
            "resumeMetadataRefreshCount": "Reanudar（{count} modelos）",
+            "sendToWorkflow": "Enviar al workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Metadatos",
+                "attributes": "Atributos",
+                "organize": "Organizar",
+                "download": "Descargar"
+            },
            "autoOrganizeProgress": {
                "initializing": "Inicializando auto-organización...",
                "starting": "Iniciando auto-organización para {type}...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "Actualizar lista de recetas",
-                "quick": "Sincronizar cambios",
-                "quickTooltip": "Sincronizar cambios - actualización rápida sin reconstruir caché",
                "full": "Reconstruir caché",
                "fullTooltip": "Reconstruir caché - reescaneo completo de todos los archivos de recetas"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "modelos serán eliminados permanentemente.",
            "action": "Eliminar todo"
        },
+        "bulkDeleteRecipes": {
+            "title": "Eliminar múltiples recetas",
+            "message": "¿Estás seguro de que quieres eliminar todas las recetas seleccionadas y sus archivos asociados?",
+            "countMessage": "recetas serán eliminadas permanentemente.",
+            "action": "Eliminar todo"
+        },
        "checkUpdates": {
            "title": "¿Comprobar actualizaciones para todos los {typePlural}?",
            "message": "Esto comprobará las actualizaciones de todos los {typePlural} de tu biblioteca. En colecciones grandes puede tardar un poco más.",
@@ -1154,6 +1181,7 @@
                "editModelName": "Editar nombre del modelo",
                "editFileName": "Editar nombre de archivo",
                "editBaseModel": "Editar modelo base",
+                "editVersionName": "Editar nombre de versión",
                "viewOnCivitai": "Ver en Civitai",
                "viewOnCivitaiText": "Ver en Civitai",
                "viewCreatorProfile": "Ver perfil del creador",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "Acceso temprano",
                    "earlyAccessTooltip": "Esta versión requiere actualmente acceso temprano de Civitai",
                    "ignored": "Ignorada",
-                    "ignoredTooltip": "Las notificaciones de actualización están desactivadas para esta versión"
+                    "ignoredTooltip": "Las notificaciones de actualización están desactivadas para esta versión",
+                    "onSiteOnly": "Solo en Sitio",
+                    "onSiteOnlyTooltip": "Esta versión solo está disponible para generación en el sitio de Civitai"
                },
                "actions": {
                    "download": "Descargar",
                    "downloadTooltip": "Descargar esta versión",
                    "downloadEarlyAccessTooltip": "Descargar esta versión de acceso temprano desde Civitai",
+                    "downloadNotAllowedTooltip": "Esta versión solo está disponible para generación en el sitio de Civitai",
                    "delete": "Eliminar",
                    "deleteTooltip": "Eliminar esta versión local",
                    "ignore": "Ignorar",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "Failed to browse directory: {message}",
            "batchImportDirectorySelected": "Directory selected: {path}",
            "noRecipesSelected": "No se han seleccionado recetas",
+            "repairBulkComplete": "Reparación completa: {repaired} reparadas, {skipped} omitidas (de {total})",
+            "repairBulkSkipped": "No se necesita reparación para ninguna de las {total} recetas seleccionadas",
+            "repairBulkFailed": "Error al reparar las recetas seleccionadas: {message}",
            "noMissingLorasInSelection": "No se encontraron LoRAs faltantes en las recetas seleccionadas",
            "noLoraRootConfigured": "No se ha configurado el directorio raíz de LoRA. Por favor, establezca un directorio raíz de LoRA predeterminado en la configuración."
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "Clasificación de contenido establecida en {level} para {count} modelo(s)",
            "bulkContentRatingPartial": "Clasificación de contenido establecida en {level} para {success} modelo(s), {failed} fallaron",
            "bulkContentRatingFailed": "No se pudo actualizar la clasificación de contenido para los modelos seleccionados",
+            "bulkFavoriteUpdating": "Añadiendo {count} modelo(s) a favoritos...",
+            "bulkUnfavoriteUpdating": "Eliminando {count} modelo(s) de favoritos...",
+            "bulkFavoritePartialAdded": "{success} modelo(s) añadido(s) a favoritos, {failed} fallido(s)",
+            "bulkFavoritePartialRemoved": "{success} modelo(s) eliminado(s) de favoritos, {failed} fallido(s)",
+            "bulkFavoriteFailed": "Error al actualizar el estado de favorito",
            "bulkUpdatesChecking": "Comprobando actualizaciones para {type} seleccionados...",
            "bulkUpdatesSuccess": "Actualizaciones disponibles para {count} {type} seleccionados",
            "bulkUpdatesNone": "No se encontraron actualizaciones para los {type} seleccionados",
@@ -1895,18 +1934,52 @@
            "warning": "Requiere atención",
            "error": "Se requiere acción"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
        "actions": {
            "runAgain": "Ejecutar de nuevo",
-            "exportBundle": "Exportar paquete"
+            "exportBundle": "Exportar paquete",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
        },
        "toast": {
            "loadFailed": "Error al cargar los diagnósticos: {message}",
            "repairSuccess": "Reconstrucción de caché completada.",
            "repairFailed": "Error al reconstruir la caché: {message}",
            "exportSuccess": "Paquete de diagnósticos exportado.",
-            "exportFailed": "Error al exportar el paquete de diagnósticos: {message}"
+            "exportFailed": "Error al exportar el paquete de diagnósticos: {message}",
+            "conflictsResolved": "{count} conflicto(s) de nombre de archivo resuelto(s).",
+            "conflictsResolveFailed": "Error al resolver conflictos de nombre de archivo: {message}"
        }
    },
+    "conflictConfirm": {
+        "title": "Resolver conflictos de nombres de archivo",
+        "message": "Renombrar añadiendo un hash de 4 caracteres a cada nombre de archivo duplicado.",
+        "note": "Esta operación renombra archivos en el disco. Es posible que las referencias a modelos en flujos de trabajo existentes deban actualizarse si usas el formato de sintaxis A1111.",
+        "detail": "Ejemplo: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Renombrará <strong>{count}</strong> archivo(s) en <strong>{groups}</strong> grupo(s) de duplicados",
+        "confirm": "Renombrar archivos",
+        "cancel": "Cancelar"
+    },
    "banners": {
        "versionMismatch": {
            "title": "Actualización de la aplicación detectada",
--- a/locales/fr.json
+++ b/locales/fr.json
@@ -15,7 +15,8 @@
            "settings": "Paramètres",
            "help": "Aide",
            "add": "Ajouter",
-            "close": "Fermer"
+            "close": "Fermer",
+            "menu": "Menu"
        },
        "status": {
            "loading": "Chargement...",
@@ -231,7 +232,10 @@
            "license": "Licence",
            "noCreditRequired": "Crédit non requis",
            "allowSellingGeneratedContent": "Vente autorisée",
+            "allowSellingGeneratedContentTooltip": "Autoriser la vente d\"images générées",
+            "noCreditRequiredTooltip": "Utiliser le modèle sans créditer le créateur",
            "noTags": "Aucun tag",
+            "autoTags": "Auto-Tags",
            "noBaseModelMatches": "Aucun modèle de base ne correspond à la recherche actuelle.",
            "clearAll": "Effacer tous les filtres",
            "any": "N'importe quel",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "Moteur de téléchargement",
-            "help": "Choisissez comment les fichiers de modèles sont téléchargés. Python utilise le téléchargeur intégré. aria2 utilise le processus externe expérimental de téléchargement.",
+            "help": "Choisissez comment les fichiers de modèles sont téléchargés. Python utilise le téléchargeur intégré. aria2 utilise le processus externe recommandé de téléchargement.",
            "options": {
                "python": "Python (intégré)",
-                "aria2": "aria2 (expérimental)"
+                "aria2": "aria2 (recommandé)"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "Révéler au survol"
            },
            "cardInfoDisplayHelp": "Choisissez quand afficher les informations du modèle et les boutons d'action",
+            "showVersionOnCard": "Afficher la version sur la carte",
+            "showVersionOnCardHelp": "Afficher ou masquer le nom de version sur les cartes de modèle",
            "modelCardFooterAction": "Action du bouton de carte de modèle",
            "modelCardFooterActionOptions": {
                "exampleImages": "Ouvrir les images d'exemple",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "Inclure les mots-clés dans la syntaxe LoRA",
-            "includeTriggerWordsHelp": "Inclure les mots-clés d'entraînement lors de la copie de la syntaxe LoRA dans le presse-papiers"
+            "includeTriggerWordsHelp": "Inclure les mots-clés d'entraînement lors de la copie de la syntaxe LoRA dans le presse-papiers",
+            "loraSyntaxFormat": "Format de syntaxe LoRA",
+            "loraSyntaxFormatHelp": "Format de syntaxe LoRA. Le format complet inclut le chemin du sous-dossier (<lora:style/anime/x:1.0>) pour une résolution de modèle sans perte. Le format hérité utilise uniquement le nom du fichier (<lora:x:1.0>) — convention A1111, peut être ambiguë en cas de noms de fichiers en double dans différents dossiers.",
+            "loraSyntaxFormatOptions": {
+                "full": "Chemin complet (sous-dossier/nom)",
+                "legacy": "A1111 hérité (nom uniquement)"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "Activer la base de données d'archive des métadonnées",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "Actualiser la liste des modèles",
-                "quick": "Synchroniser les changements",
-                "quickTooltip": "Analyse les nouveaux fichiers de modèle ou les fichiers manquants pour garder la liste à jour.",
                "full": "Reconstruire le cache",
                "fullTooltip": "Recharge tous les détails des modèles depuis les fichiers metadata — à utiliser si la bibliothèque paraît obsolète ou après des modifications manuelles."
            },
@@ -679,16 +689,29 @@
            "setContentRating": "Définir la classification du contenu pour tous",
            "copyAll": "Copier toute la syntaxe",
            "refreshAll": "Actualiser toutes les métadonnées",
+            "repairMetadata": "Réparer les métadonnées de la sélection",
            "checkUpdates": "Vérifier les mises à jour pour la sélection",
            "moveAll": "Déplacer tout vers un dossier",
            "autoOrganize": "Auto-organiser la sélection",
            "skipMetadataRefresh": "Ignorer l'actualisation des métadonnées pour la sélection",
            "resumeMetadataRefresh": "Reprendre l'actualisation des métadonnées pour la sélection",
+            "setFavorite": "Définir comme favori",
+            "setFavoriteCount": "Définir comme favori ({favorited}/{total})",
+            "unfavorite": "Retirer des favoris",
            "deleteAll": "Supprimer la sélection",
            "downloadMissingLoras": "Télécharger les LoRAs manquants",
+            "downloadExamples": "Télécharger les images d'exemple",
            "clear": "Effacer la sélection",
            "skipMetadataRefreshCount": "Ignorer（{count} modèles）",
            "resumeMetadataRefreshCount": "Reprendre（{count} modèles）",
+            "sendToWorkflow": "Envoyer au workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Métadonnées",
+                "attributes": "Attributs",
+                "organize": "Organiser",
+                "download": "Télécharger"
+            },
            "autoOrganizeProgress": {
                "initializing": "Initialisation de l'auto-organisation...",
                "starting": "Démarrage de l'auto-organisation pour {type}...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "Actualiser la liste des recipes",
-                "quick": "Synchroniser les changements",
-                "quickTooltip": "Synchroniser les changements - actualisation rapide sans reconstruire le cache",
                "full": "Reconstruire le cache",
                "fullTooltip": "Reconstruire le cache - rescan complet de tous les fichiers de recipes"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "modèles seront définitivement supprimés.",
            "action": "Tout supprimer"
        },
+        "bulkDeleteRecipes": {
+            "title": "Supprimer plusieurs recipes",
+            "message": "Êtes-vous sûr de vouloir supprimer toutes les recipes sélectionnées et leurs fichiers associés ?",
+            "countMessage": "recipes seront définitivement supprimées.",
+            "action": "Tout supprimer"
+        },
        "checkUpdates": {
            "title": "Vérifier les mises à jour pour tous les {typePlural} ?",
            "message": "Cette action vérifie les mises à jour pour tous les {typePlural} de votre bibliothèque. Les grandes collections peuvent prendre un peu plus de temps.",
@@ -1154,6 +1181,7 @@
                "editModelName": "Modifier le nom du modèle",
                "editFileName": "Modifier le nom de fichier",
                "editBaseModel": "Modifier le modèle de base",
+                "editVersionName": "Modifier le nom de la version",
                "viewOnCivitai": "Voir sur Civitai",
                "viewOnCivitaiText": "Voir sur Civitai",
                "viewCreatorProfile": "Voir le profil du créateur",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "Accès anticipé",
                    "earlyAccessTooltip": "Cette version nécessite actuellement l'accès anticipé Civitai",
                    "ignored": "Ignorée",
-                    "ignoredTooltip": "Les notifications de mise à jour sont désactivées pour cette version"
+                    "ignoredTooltip": "Les notifications de mise à jour sont désactivées pour cette version",
+                    "onSiteOnly": "Uniquement sur Site",
+                    "onSiteOnlyTooltip": "Cette version n'est disponible que pour la génération sur le site Civitai"
                },
                "actions": {
                    "download": "Télécharger",
                    "downloadTooltip": "Télécharger cette version",
                    "downloadEarlyAccessTooltip": "Télécharger cette version en accès anticipé depuis Civitai",
+                    "downloadNotAllowedTooltip": "Cette version n'est disponible que pour la génération sur le site Civitai",
                    "delete": "Supprimer",
                    "deleteTooltip": "Supprimer cette version locale",
                    "ignore": "Ignorer",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "Failed to browse directory: {message}",
            "batchImportDirectorySelected": "Directory selected: {path}",
            "noRecipesSelected": "Aucune recette sélectionnée",
+            "repairBulkComplete": "Réparation terminée : {repaired} réparée(s), {skipped} ignorée(s) (sur {total})",
+            "repairBulkSkipped": "Aucune réparation nécessaire parmi les {total} recettes sélectionnées",
+            "repairBulkFailed": "Échec de la réparation des recettes sélectionnées : {message}",
            "noMissingLorasInSelection": "Aucun LoRA manquant trouvé dans les recettes sélectionnées",
            "noLoraRootConfigured": "Aucun répertoire racine LoRA configuré. Veuillez définir un répertoire racine LoRA par défaut dans les paramètres."
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "Classification du contenu définie sur {level} pour {count} modèle(s)",
            "bulkContentRatingPartial": "Classification du contenu définie sur {level} pour {success} modèle(s), {failed} échec(s)",
            "bulkContentRatingFailed": "Impossible de mettre à jour la classification du contenu pour les modèles sélectionnés",
+            "bulkFavoriteUpdating": "Ajout de {count} modèle(s) aux favoris...",
+            "bulkUnfavoriteUpdating": "Suppression de {count} modèle(s) des favoris...",
+            "bulkFavoritePartialAdded": "{success} modèle(s) ajouté(s) aux favoris, {failed} échec(s)",
+            "bulkFavoritePartialRemoved": "{success} modèle(s) retiré(s) des favoris, {failed} échec(s)",
+            "bulkFavoriteFailed": "Échec de la mise à jour du statut de favori",
            "bulkUpdatesChecking": "Vérification des mises à jour pour les {type} sélectionnés...",
            "bulkUpdatesSuccess": "Mises à jour disponibles pour {count} {type} sélectionnés",
            "bulkUpdatesNone": "Aucune mise à jour trouvée pour les {type} sélectionnés",
@@ -1895,18 +1934,52 @@
            "warning": "Nécessite une attention",
            "error": "Action requise"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
        "actions": {
            "runAgain": "Relancer",
-            "exportBundle": "Exporter le lot"
+            "exportBundle": "Exporter le lot",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
        },
        "toast": {
            "loadFailed": "Échec du chargement des diagnostics : {message}",
            "repairSuccess": "Reconstruction du cache terminée.",
            "repairFailed": "Échec de la reconstruction du cache : {message}",
            "exportSuccess": "Lot de diagnostics exporté.",
-            "exportFailed": "Échec de l'export du lot de diagnostics : {message}"
+            "exportFailed": "Échec de l'export du lot de diagnostics : {message}",
+            "conflictsResolved": "{count} conflit(s) de nom de fichier résolu(s).",
+            "conflictsResolveFailed": "Échec de la résolution des conflits de nom de fichier : {message}"
        }
    },
+    "conflictConfirm": {
+        "title": "Résoudre les conflits de noms de fichiers",
+        "message": "Renommer en ajoutant un hachage de 4 caractères à chaque nom de fichier en double.",
+        "note": "Cette opération renomme les fichiers sur le disque. Les références de modèle dans les workflows existants peuvent nécessiter une mise à jour si vous utilisez le format de syntaxe A1111.",
+        "detail": "Exemple : <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Renommera <strong>{count}</strong> fichier(s) dans <strong>{groups}</strong> groupe(s) de doublons",
+        "confirm": "Renommer les fichiers",
+        "cancel": "Annuler"
+    },
    "banners": {
        "versionMismatch": {
            "title": "Mise à jour de l'application détectée",
--- a/locales/he.json
+++ b/locales/he.json
@@ -15,7 +15,8 @@
            "settings": "הגדרות",
            "help": "עזרה",
            "add": "הוספה",
-            "close": "סגור"
+            "close": "סגור",
+            "menu": "תפריט"
        },
        "status": {
            "loading": "טוען...",
@@ -231,7 +232,10 @@
            "license": "רישיון",
            "noCreditRequired": "ללא קרדיט נדרש",
            "allowSellingGeneratedContent": "אפשר מכירה",
+            "allowSellingGeneratedContentTooltip": "אפשר מכירת תמונות שנוצרו",
+            "noCreditRequiredTooltip": "שימוש במודל ללא מתן קרדיט ליוצר",
            "noTags": "ללא תגיות",
+            "autoTags": "תגיות אוטומטיות",
            "noBaseModelMatches": "אין מודלי בסיס התואמים לחיפוש הנוכחי.",
            "clearAll": "נקה את כל המסננים",
            "any": "כלשהו",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "מנגנון הורדה",
-            "help": "בחר כיצד יורדים קבצי המודל. Python משתמש במוריד המובנה. aria2 משתמש בתהליך הורדה חיצוני ניסיוני.",
+            "help": "בחר כיצד יורדים קבצי המודל. Python משתמש במוריד המובנה. aria2 משתמש בתהליך הורדה חיצוני מומלץ.",
            "options": {
                "python": "Python (מובנה)",
-                "aria2": "aria2 (ניסיוני)"
+                "aria2": "aria2 (מומלץ)"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "חשוף בריחוף"
            },
            "cardInfoDisplayHelp": "בחר מתי להציג מידע על המודל וכפתורי פעולה",
+            "showVersionOnCard": "הצג גרסה בכרטיס",
+            "showVersionOnCardHelp": "הצג או הסתר את שם הגרסה בכרטיסי המודל",
            "modelCardFooterAction": "פעולת כפתור כרטיס מודל",
            "modelCardFooterActionOptions": {
                "exampleImages": "פתח תמונות דוגמה",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "כלול מילות טריגר בתחביר LoRA",
-            "includeTriggerWordsHelp": "כלול מילות טריגר מאומנות בעת העתקת תחביר LoRA ללוח"
+            "includeTriggerWordsHelp": "כלול מילות טריגר מאומנות בעת העתקת תחביר LoRA ללוח",
+            "loraSyntaxFormat": "פורמט תחביר LoRA",
+            "loraSyntaxFormatHelp": "פורמט תחביר LoRA. נתיב מלא כולל תת-תיקייה (<lora:style/anime/x:1.0>) לפתרון מודל ללא אובדן. גרסה ישנה משתמשת בשם קובץ בלבד (<lora:x:1.0>) — מוסכמת A1111, עלולה להיות לא חד משמעית עם שמות קבצים כפולים בתיקיות שונות.",
+            "loraSyntaxFormatOptions": {
+                "full": "נתיב מלא (תת-תיקייה/שם)",
+                "legacy": "A1111 ישן (שם בלבד)"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "הפעל מסד נתונים של ארכיון מטא-דאטה",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "רענן רשימת מודלים",
-                "quick": "סנכרון שינויים",
-                "quickTooltip": "סריקה לאיתור קבצי מודל חדשים או חסרים כדי לשמור את הרשימה מעודכנת.",
                "full": "בניית מטמון מחדש",
                "fullTooltip": "טוען מחדש את כל פרטי המודלים מקבצי המטא-דאטה – לשימוש אם הספרייה נראית לא מעודכנת או לאחר עריכות ידניות."
            },
@@ -679,16 +689,29 @@
            "setContentRating": "הגדר דירוג תוכן לכל המודלים",
            "copyAll": "העתק את כל התחבירים",
            "refreshAll": "רענן את כל המטא-דאטה",
+            "repairMetadata": "תקן מטא-דאטה עבור הנבחרים",
            "checkUpdates": "בדוק עדכונים לבחירה",
            "moveAll": "העבר הכל לתיקייה",
            "autoOrganize": "ארגן אוטומטית נבחרים",
            "skipMetadataRefresh": "דילוג על רענון מטא-נתונים לנבחרים",
            "resumeMetadataRefresh": "המשך רענון מטא-נתונים לנבחרים",
+            "setFavorite": "הגדר כמועדף",
+            "setFavoriteCount": "הגדר כמועדף ({favorited}/{total})",
+            "unfavorite": "הסר ממועדפים",
            "deleteAll": "מחק נבחרים",
            "downloadMissingLoras": "הורדת LoRAs חסרים",
+            "downloadExamples": "הורד תמונות דוגמה",
            "clear": "נקה בחירה",
            "skipMetadataRefreshCount": "דילוג（{count} מודלים）",
            "resumeMetadataRefreshCount": "המשך（{count} מודלים）",
+            "sendToWorkflow": "שלח ל-Workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "מטא-נתונים",
+                "attributes": "מאפיינים",
+                "organize": "ארגן",
+                "download": "הורדה"
+            },
            "autoOrganizeProgress": {
                "initializing": "מאתחל ארגון אוטומטי...",
                "starting": "מתחיל ארגון אוטומטי עבור {type}...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "רענן רשימת מתכונים",
-                "quick": "סנכרן שינויים",
-                "quickTooltip": "סנכרן שינויים - רענון מהיר ללא בניית מטמון מחדש",
                "full": "בנה מטמון מחדש",
                "fullTooltip": "בנה מטמון מחדש - סריקה מחדש מלאה של כל קבצי המתכונים"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "מודלים יימחקו לצמיתות.",
            "action": "מחק הכל"
        },
+        "bulkDeleteRecipes": {
+            "title": "מחק מספר מתכונים",
+            "message": "האם אתה בטוח שברצונך למחוק את כל המתכונים שנבחרו ואת הקבצים הנלווים אליהם?",
+            "countMessage": "מתכונים יימחקו לצמיתות.",
+            "action": "מחק הכל"
+        },
        "checkUpdates": {
            "title": "לבדוק עדכונים לכל ה-{typePlural}?",
            "message": "הפעולה תבדוק עדכונים עבור כל ה-{typePlural} בספרייה שלך. באוספים גדולים זה עלול לקחת מעט יותר זמן.",
@@ -1154,6 +1181,7 @@
                "editModelName": "ערוך שם מודל",
                "editFileName": "ערוך שם קובץ",
                "editBaseModel": "ערוך מודל בסיס",
+                "editVersionName": "ערוך שם גרסה",
                "viewOnCivitai": "הצג ב-Civitai",
                "viewOnCivitaiText": "הצג ב-Civitai",
                "viewCreatorProfile": "הצג פרופיל יוצר",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "גישה מוקדמת",
                    "earlyAccessTooltip": "גרסה זו דורשת כרגע גישת Early Access של Civitai",
                    "ignored": "התעלם",
-                    "ignoredTooltip": "התראות העדכון מושבתות עבור גרסה זו"
+                    "ignoredTooltip": "התראות העדכון מושבתות עבור גרסה זו",
+                    "onSiteOnly": "רק באתר",
+                    "onSiteOnlyTooltip": "גרסה זו זמינה רק ליצירה באתר Civitai"
                },
                "actions": {
                    "download": "הורדה",
                    "downloadTooltip": "הורד את הגרסה הזו",
                    "downloadEarlyAccessTooltip": "הורד את גרסת ה-Early Access הזו מ-Civitai",
+                    "downloadNotAllowedTooltip": "גרסה זו זמינה רק ליצירה באתר Civitai",
                    "delete": "מחיקה",
                    "deleteTooltip": "מחק את הגרסה המקומית הזו",
                    "ignore": "התעלם",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "Failed to browse directory: {message}",
            "batchImportDirectorySelected": "Directory selected: {path}",
            "noRecipesSelected": "לא נבחרו מתכונים",
+            "repairBulkComplete": "התיקון הושלם: {repaired} תוקנו, {skipped} דולגו (מתוך {total})",
+            "repairBulkSkipped": "אין צורך בתיקון עבור {total} המתכונים הנבחרים",
+            "repairBulkFailed": "תיקון המתכונים הנבחרים נכשל: {message}",
            "noMissingLorasInSelection": "לא נמצאו LoRAs חסרים במתכונים שנבחרו",
            "noLoraRootConfigured": "תיקיית השורש של LoRA לא מוגדרת. אנא הגדר תיקיית שורש LoRA ברירת מחדל בהגדרות."
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "דירוג התוכן הוגדר ל-{level} עבור {count} מודלים",
            "bulkContentRatingPartial": "דירוג התוכן הוגדר ל-{level} עבור {success} מודלים, {failed} נכשלו",
            "bulkContentRatingFailed": "עדכון דירוג התוכן עבור המודלים שנבחרו נכשל",
+            "bulkFavoriteUpdating": "מוסיף {count} דגמים למועדפים...",
+            "bulkUnfavoriteUpdating": "מסיר {count} דגמים ממועדפים...",
+            "bulkFavoritePartialAdded": "{success} דגמים נוספו למועדפים, {failed} נכשלו",
+            "bulkFavoritePartialRemoved": "{success} דגמים הוסרו ממועדפים, {failed} נכשלו",
+            "bulkFavoriteFailed": "עדכון סטטוס מועדפים נכשל",
            "bulkUpdatesChecking": "בודק עדכונים עבור {type} שנבחרו...",
            "bulkUpdatesSuccess": "יש עדכונים עבור {count} {type} שנבחרו",
            "bulkUpdatesNone": "לא נמצאו עדכונים עבור {type} שנבחרו",
@@ -1895,18 +1934,52 @@
            "warning": "דורש תשומת לב",
            "error": "נדרשת פעולה"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
        "actions": {
            "runAgain": "הפעל שוב",
-            "exportBundle": "ייצוא חבילה"
+            "exportBundle": "ייצוא חבילה",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
        },
        "toast": {
            "loadFailed": "טעינת האבחון נכשלה: {message}",
            "repairSuccess": "בניית המטמון מחדש הושלמה.",
            "repairFailed": "בניית המטמון מחדש נכשלה: {message}",
            "exportSuccess": "חבילת האבחון יוצאה.",
-            "exportFailed": "ייצוא חבילת האבחון נכשל: {message}"
+            "exportFailed": "ייצוא חבילת האבחון נכשל: {message}",
+            "conflictsResolved": "נפתרו {count} התנגשויות בשמות קבצים.",
+            "conflictsResolveFailed": "פתרון התנגשויות שמות קבצים נכשל: {message}"
        }
    },
+    "conflictConfirm": {
+        "title": "פתור התנגשויות בשמות קבצים",
+        "message": "שינוי שם על ידי הוספת האש באורך 4 תווים לכל שם קובץ כפול.",
+        "note": "פעולה זו משנה שמות של קבצים בדיסק. ייתכן שיהיה צורך לעדכן הפניות למודלים בזרימות עבודה קיימות אם אתה משתמש בפורמט התחביר A1111.",
+        "detail": "דוגמה: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "ישנה שם של <strong>{count}</strong> קבצים ב-<strong>{groups}</strong> קבוצות כפולות",
+        "confirm": "שנה שמות קבצים",
+        "cancel": "ביטול"
+    },
    "banners": {
        "versionMismatch": {
            "title": "זוהה עדכון יישום",
--- a/locales/ja.json
+++ b/locales/ja.json
@@ -15,7 +15,8 @@
            "settings": "設定",
            "help": "ヘルプ",
            "add": "追加",
-            "close": "閉じる"
+            "close": "閉じる",
+            "menu": "メニュー"
        },
        "status": {
            "loading": "読み込み中...",
@@ -231,7 +232,10 @@
            "license": "ライセンス",
            "noCreditRequired": "クレジット不要",
            "allowSellingGeneratedContent": "販売許可",
+            "allowSellingGeneratedContentTooltip": "生成した画像の販売を許可",
+            "noCreditRequiredTooltip": "クレジット表記なしでモデルを使用可能",
            "noTags": "タグなし",
+            "autoTags": "自動タグ",
            "noBaseModelMatches": "現在の検索に一致するベースモデルはありません。",
            "clearAll": "すべてのフィルタをクリア",
            "any": "いずれか",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "ダウンロードバックエンド",
-            "help": "モデルファイルのダウンロード方法を選択します。Python は内蔵ダウンローダーを使用し、aria2 は実験的な外部ダウンローダープロセスを使用します。",
+            "help": "モデルファイルのダウンロード方法を選択します。Python は内蔵ダウンローダーを使用し、aria2 は推奨の外部ダウンローダープロセスを使用します。",
            "options": {
                "python": "Python（内蔵）",
-                "aria2": "aria2（実験的）"
+                "aria2": "aria2（推奨）"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "ホバー時に表示"
            },
            "cardInfoDisplayHelp": "モデル情報とアクションボタンの表示タイミングを選択",
+            "showVersionOnCard": "カードにバージョンを表示",
+            "showVersionOnCardHelp": "モデルカード上のバージョン名の表示/非表示を切り替えます",
            "modelCardFooterAction": "モデルカードボタンのアクション",
            "modelCardFooterActionOptions": {
                "exampleImages": "例画像を開く",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "LoRA構文にトリガーワードを含める",
-            "includeTriggerWordsHelp": "LoRA構文をクリップボードにコピーする際、学習済みトリガーワードを含めます"
+            "includeTriggerWordsHelp": "LoRA構文をクリップボードにコピーする際、学習済みトリガーワードを含めます",
+            "loraSyntaxFormat": "LoRA構文形式",
+            "loraSyntaxFormatHelp": "LoRA構文形式。フルパスはサブフォルダパスを含み（<lora:style/anime/x:1.0>）、モデルをロスレスで解決します。レガシーはファイル名のみ（<lora:x:1.0>）— A1111規約ですが、フォルダ間でファイル名が重複する場合に曖昧になる可能性があります。",
+            "loraSyntaxFormatOptions": {
+                "full": "フルパス（サブフォルダ/名前）",
+                "legacy": "レガシーA1111（名前のみ）"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "メタデータアーカイブデータベースを有効化",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "モデルリストを更新",
-                "quick": "変更を同期",
-                "quickTooltip": "新しいモデルファイルや欠けているファイルをスキャンして一覧を最新に保ちます。",
                "full": "キャッシュを再構築",
                "fullTooltip": "メタデータファイルから全モデル情報を再読み込みします。リストが古いと感じるときや手動編集後に使用してください。"
            },
@@ -679,16 +689,29 @@
            "setContentRating": "すべてのモデルのコンテンツレーティングを設定",
            "copyAll": "すべての構文をコピー",
            "refreshAll": "すべてのメタデータを更新",
+            "repairMetadata": "選択したレシピのメタデータを修復",
            "checkUpdates": "選択項目の更新を確認",
            "moveAll": "すべてをフォルダに移動",
            "autoOrganize": "自動整理を実行",
            "skipMetadataRefresh": "選択したモデルのメタデータ更新をスキップ",
            "resumeMetadataRefresh": "選択したモデルのメタデータ更新を再開",
+            "setFavorite": "お気に入りに設定",
+            "setFavoriteCount": "お気に入りに設定 ({favorited}/{total})",
+            "unfavorite": "お気に入りから削除",
            "deleteAll": "選択したものを削除",
            "downloadMissingLoras": "不足している LoRA をダウンロード",
+            "downloadExamples": "例画像をダウンロード",
            "clear": "選択をクリア",
            "skipMetadataRefreshCount": "スキップ（{count}モデル）",
            "resumeMetadataRefreshCount": "再開（{count}モデル）",
+            "sendToWorkflow": "ワークフローに送信",
+            "sections": {
+                "workflow": "ワークフロー",
+                "metadata": "メタデータ",
+                "attributes": "属性",
+                "organize": "整理",
+                "download": "ダウンロード"
+            },
            "autoOrganizeProgress": {
                "initializing": "自動整理を初期化中...",
                "starting": "{type}の自動整理を開始中...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "レシピリストを更新",
-                "quick": "変更を同期",
-                "quickTooltip": "変更を同期 - キャッシュを再構築せずにクイック更新",
                "full": "キャッシュを再構築",
                "fullTooltip": "キャッシュを再構築 - すべてのレシピファイルを完全に再スキャン"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "モデルが完全に削除されます。",
            "action": "すべて削除"
        },
+        "bulkDeleteRecipes": {
+            "title": "複数のレシピを削除",
+            "message": "選択したすべてのレシピと関連ファイルを削除してもよろしいですか？",
+            "countMessage": "レシピが完全に削除されます。",
+            "action": "すべて削除"
+        },
        "checkUpdates": {
            "title": "すべての{type}の更新を確認しますか？",
            "message": "ライブラリ内のすべての{type}で更新を確認します。コレクションが大きい場合は時間がかかることがあります。",
@@ -1154,6 +1181,7 @@
                "editModelName": "モデル名を編集",
                "editFileName": "ファイル名を編集",
                "editBaseModel": "ベースモデルを編集",
+                "editVersionName": "バージョン名を編集",
                "viewOnCivitai": "Civitaiで表示",
                "viewOnCivitaiText": "Civitaiで表示",
                "viewCreatorProfile": "作成者プロフィールを表示",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "早期アクセス",
                    "earlyAccessTooltip": "このバージョンは現在 Civitai の早期アクセスが必要です",
                    "ignored": "無視中",
-                    "ignoredTooltip": "このバージョンの更新通知は無効です"
+                    "ignoredTooltip": "このバージョンの更新通知は無効です",
+                    "onSiteOnly": "サイト内のみ",
+                    "onSiteOnlyTooltip": "このバージョンはCivitaiサイト内でのみ利用可能で、ダウンロードはできません"
                },
                "actions": {
                    "download": "ダウンロード",
                    "downloadTooltip": "このバージョンをダウンロード",
                    "downloadEarlyAccessTooltip": "Civitai からこの早期アクセス版をダウンロード",
+                    "downloadNotAllowedTooltip": "このバージョンはCivitaiサイト内でのみ利用可能で、ダウンロードはできません",
                    "delete": "削除",
                    "deleteTooltip": "このローカルバージョンを削除",
                    "ignore": "無視",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "Failed to browse directory: {message}",
            "batchImportDirectorySelected": "Directory selected: {path}",
            "noRecipesSelected": "レシピが選択されていません",
+            "repairBulkComplete": "修復完了：{repaired} 件修復、{skipped} 件スキップ（合計 {total} 件）",
+            "repairBulkSkipped": "選択した {total} 件のレシピは修復不要です",
+            "repairBulkFailed": "選択したレシピの修復に失敗しました：{message}",
            "noMissingLorasInSelection": "選択したレシピに不足している LoRA が見つかりませんでした",
            "noLoraRootConfigured": "LoRA ルートディレクトリが設定されていません。設定でデフォルトの LoRA ルートを設定してください。"
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "{count} 件のモデルのコンテンツレーティングを {level} に設定しました",
            "bulkContentRatingPartial": "{success} 件のモデルのコンテンツレーティングを {level} に設定、{failed} 件は失敗しました",
            "bulkContentRatingFailed": "選択したモデルのコンテンツレーティングを更新できませんでした",
+            "bulkFavoriteUpdating": "{count} 個のモデルをお気に入りに追加中...",
+            "bulkUnfavoriteUpdating": "{count} 個のモデルをお気に入りから削除中...",
+            "bulkFavoritePartialAdded": "{success} 個のモデルをお気に入りに追加、{failed} 個失敗",
+            "bulkFavoritePartialRemoved": "{success} 個のモデルをお気に入りから削除、{failed} 個失敗",
+            "bulkFavoriteFailed": "お気に入り状態の更新に失敗しました",
            "bulkUpdatesChecking": "選択された{type}の更新を確認しています...",
            "bulkUpdatesSuccess": "{count} 件の選択された{type}に利用可能な更新があります",
            "bulkUpdatesNone": "選択された{type}には更新が見つかりませんでした",
@@ -1895,18 +1934,52 @@
            "warning": "要注意",
            "error": "対応が必要"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API キー"
+            },
+            "cache_health": {
+                "title": "モデルキャッシュの健全性"
+            },
+            "filename_conflicts": {
+                "title": "ファイル名重複競合"
+            },
+            "ui_version": {
+                "title": "UI バージョン"
+            }
+        },
        "actions": {
            "runAgain": "再実行",
-            "exportBundle": "パッケージをエクスポート"
+            "exportBundle": "パッケージをエクスポート",
+            "open-settings": "設定を開く",
+            "open-settings-syntax-format": "フルパス構文に切り替え",
+            "repair-cache": "キャッシュを再構築",
+            "resolve-filename-conflicts": "競合を解決",
+            "reload-page": "UI をリロード"
+        },
+        "labels": {
+            "conflicts": "競合",
+            "version": "バージョン"
        },
        "toast": {
            "loadFailed": "診断の読み込みに失敗しました: {message}",
            "repairSuccess": "キャッシュの再構築が完了しました。",
            "repairFailed": "キャッシュの再構築に失敗しました: {message}",
            "exportSuccess": "診断パッケージをエクスポートしました。",
-            "exportFailed": "診断パッケージのエクスポートに失敗しました: {message}"
+            "exportFailed": "診断パッケージのエクスポートに失敗しました: {message}",
+            "conflictsResolved": "{count} 件のファイル名競合が解決されました。",
+            "conflictsResolveFailed": "ファイル名競合の解決に失敗しました: {message}"
        }
    },
+    "conflictConfirm": {
+        "title": "ファイル名の競合を解決",
+        "message": "重複したファイル名に4文字のハッシュを追加してリネームします。",
+        "note": "この操作はディスク上のファイルをリネームします。A1111 構文形式を使用している場合、既存のワークフロー内のモデル参照を更新する必要があるかもしれません。",
+        "detail": "例：<code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "<strong>{groups}</strong> 組の重複にわたって <strong>{count}</strong> 個のファイルをリネームします",
+        "confirm": "ファイルをリネーム",
+        "cancel": "キャンセル"
+    },
    "banners": {
        "versionMismatch": {
            "title": "アプリケーション更新が検出されました",
--- a/locales/ko.json
+++ b/locales/ko.json
@@ -15,7 +15,8 @@
            "settings": "설정",
            "help": "도움말",
            "add": "추가",
-            "close": "닫기"
+            "close": "닫기",
+            "menu": "메뉴"
        },
        "status": {
            "loading": "로딩 중...",
@@ -231,7 +232,10 @@
            "license": "라이선스",
            "noCreditRequired": "크레딧 표기 없음",
            "allowSellingGeneratedContent": "판매 허용",
+            "allowSellingGeneratedContentTooltip": "생성된 이미지 판매 허용",
+            "noCreditRequiredTooltip": "크리에이터 저작자 표시 없이 모델 사용 가능",
            "noTags": "태그 없음",
+            "autoTags": "자동 태그",
            "noBaseModelMatches": "현재 검색과 일치하는 베이스 모델이 없습니다.",
            "clearAll": "모든 필터 지우기",
            "any": "아무",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "다운로드 백엔드",
-            "help": "모델 파일을 다운로드하는 방식을 선택합니다. Python은 내장 다운로더를 사용하고, aria2는 실험적인 외부 다운로더 프로세스를 사용합니다.",
+            "help": "모델 파일을 다운로드하는 방식을 선택합니다. Python은 내장 다운로더를 사용하고, aria2는 권장되는 외부 다운로더 프로세스를 사용합니다.",
            "options": {
                "python": "Python(내장)",
-                "aria2": "aria2(실험적)"
+                "aria2": "aria2(권장)"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "호버 시 표시"
            },
            "cardInfoDisplayHelp": "모델 정보 및 액션 버튼을 언제 표시할지 선택하세요",
+            "showVersionOnCard": "카드에 버전 표시",
+            "showVersionOnCardHelp": "모델 카드에 버전 이름 표시 여부를 전환합니다",
            "modelCardFooterAction": "모델 카드 버튼 동작",
            "modelCardFooterActionOptions": {
                "exampleImages": "예시 이미지 열기",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "LoRA 문법에 트리거 단어 포함",
-            "includeTriggerWordsHelp": "LoRA 문법을 클립보드에 복사할 때 학습된 트리거 단어를 포함합니다"
+            "includeTriggerWordsHelp": "LoRA 문법을 클립보드에 복사할 때 학습된 트리거 단어를 포함합니다",
+            "loraSyntaxFormat": "LoRA 구문 형식",
+            "loraSyntaxFormatHelp": "LoRA 구문 형식. 전체 경로는 하위 폴더 경로(<lora:style/anime/x:1.0>)를 포함하여 손실 없는 모델 해상도를 제공합니다. 레거시는 파일 이름만(<lora:x:1.0>) 사용 — A1111 규칙이지만, 폴더 간 파일명 중복 시 모호할 수 있습니다.",
+            "loraSyntaxFormatOptions": {
+                "full": "전체 경로(하위 폴더/이름)",
+                "legacy": "레거시 A1111(이름만)"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "메타데이터 아카이브 데이터베이스 활성화",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "모델 목록 새로고침",
-                "quick": "변경 사항 동기화",
-                "quickTooltip": "새로운 모델 파일이나 누락된 파일을 찾아 목록을 최신 상태로 유지합니다.",
                "full": "캐시 재구성",
                "fullTooltip": "메타데이터 파일에서 모든 모델 정보를 다시 불러옵니다. 라이브러리가 오래되어 보이거나 수동 수정 후에 사용하세요."
            },
@@ -679,16 +689,29 @@
            "setContentRating": "모든 모델에 콘텐츠 등급 설정",
            "copyAll": "모든 문법 복사",
            "refreshAll": "모든 메타데이터 새로고침",
+            "repairMetadata": "선택한 레시피 메타데이터 복구",
            "checkUpdates": "선택 항목 업데이트 확인",
            "moveAll": "모두 폴더로 이동",
            "autoOrganize": "자동 정리 선택",
            "skipMetadataRefresh": "선택한 모델의 메타데이터 새로고침 건너뛰기",
            "resumeMetadataRefresh": "선택한 모델의 메타데이터 새로고침 재개",
+            "setFavorite": "즐겨찾기로 설정",
+            "setFavoriteCount": "즐겨찾기로 설정 ({favorited}/{total})",
+            "unfavorite": "즐겨찾기 해제",
            "deleteAll": "선택된 항목 삭제",
            "downloadMissingLoras": "누락된 LoRA 다운로드",
+            "downloadExamples": "예시 이미지 다운로드",
            "clear": "선택 지우기",
            "skipMetadataRefreshCount": "건너뛰기（{count}개 모델）",
            "resumeMetadataRefreshCount": "재개（{count}개 모델）",
+            "sendToWorkflow": "워크플로우로 보내기",
+            "sections": {
+                "workflow": "워크플로우",
+                "metadata": "메타데이터",
+                "attributes": "속성",
+                "organize": "정리",
+                "download": "다운로드"
+            },
            "autoOrganizeProgress": {
                "initializing": "자동 정리 초기화 중...",
                "starting": "{type}에 대한 자동 정리 시작...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "레시피 목록 새로고침",
-                "quick": "변경 사항 동기화",
-                "quickTooltip": "변경 사항 동기화 - 캐시를 재구성하지 않고 빠른 새로고침",
                "full": "캐시 재구성",
                "fullTooltip": "캐시 재구성 - 모든 레시피 파일을 완전히 다시 스캔"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "개의 모델이 영구적으로 삭제됩니다.",
            "action": "모두 삭제"
        },
+        "bulkDeleteRecipes": {
+            "title": "여러 레시피 삭제",
+            "message": "선택된 모든 레시피와 관련 파일을 삭제하시겠습니까?",
+            "countMessage": "개의 레시피가 영구적으로 삭제됩니다.",
+            "action": "모두 삭제"
+        },
        "checkUpdates": {
            "title": "{type} 전체 업데이트를 확인할까요?",
            "message": "라이브러리에 있는 모든 {type}의 업데이트를 확인합니다. 컬렉션이 클수록 시간이 조금 더 걸릴 수 있습니다.",
@@ -1154,6 +1181,7 @@
                "editModelName": "모델명 편집",
                "editFileName": "파일명 편집",
                "editBaseModel": "베이스 모델 편집",
+                "editVersionName": "버전명 편집",
                "viewOnCivitai": "Civitai에서 보기",
                "viewOnCivitaiText": "Civitai에서 보기",
                "viewCreatorProfile": "제작자 프로필 보기",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "얼리 액세스",
                    "earlyAccessTooltip": "이 버전은 현재 Civitai 얼리 액세스가 필요합니다",
                    "ignored": "무시됨",
-                    "ignoredTooltip": "이 버전은 업데이트 알림이 비활성화되어 있습니다"
+                    "ignoredTooltip": "이 버전은 업데이트 알림이 비활성화되어 있습니다",
+                    "onSiteOnly": "사이트 내 전용",
+                    "onSiteOnlyTooltip": "이 버전은 Civitai 사이트 내에서만 사용 가능하며 다운로드할 수 없습니다"
                },
                "actions": {
                    "download": "다운로드",
                    "downloadTooltip": "이 버전 다운로드",
                    "downloadEarlyAccessTooltip": "Civitai에서 이 얼리 액세스 버전 다운로드",
+                    "downloadNotAllowedTooltip": "이 버전은 Civitai 사이트 내에서만 사용 가능하며 다운로드할 수 없습니다",
                    "delete": "삭제",
                    "deleteTooltip": "이 로컬 버전 삭제",
                    "ignore": "무시",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "Failed to browse directory: {message}",
            "batchImportDirectorySelected": "Directory selected: {path}",
            "noRecipesSelected": "선택한 레시피가 없습니다",
+            "repairBulkComplete": "복구 완료: {repaired}개 복구, {skipped}개 건너뜀 (총 {total}개)",
+            "repairBulkSkipped": "선택한 {total}개 레시피는 복구가 필요하지 않습니다",
+            "repairBulkFailed": "선택한 레시피 복구 실패: {message}",
            "noMissingLorasInSelection": "선택한 레시피에서 누락된 LoRA를 찾을 수 없습니다",
            "noLoraRootConfigured": "LoRA 루트 디렉토리가 구성되지 않았습니다. 설정에서 기본 LoRA 루트를 설정하세요."
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "{count}개 모델의 콘텐츠 등급을 {level}(으)로 설정했습니다",
            "bulkContentRatingPartial": "{success}개 모델의 콘텐츠 등급을 {level}(으)로 설정했고, {failed}개는 실패했습니다",
            "bulkContentRatingFailed": "선택한 모델의 콘텐츠 등급을 업데이트하지 못했습니다",
+            "bulkFavoriteUpdating": "{count}개 모델을 즐겨찾기에 추가 중...",
+            "bulkUnfavoriteUpdating": "{count}개 모델을 즐겨찾기에서 제거 중...",
+            "bulkFavoritePartialAdded": "{success}개 모델을 즐겨찾기에 추가, {failed}개 실패",
+            "bulkFavoritePartialRemoved": "{success}개 모델을 즐겨찾기에서 제거, {failed}개 실패",
+            "bulkFavoriteFailed": "즐겨찾기 상태 업데이트 실패",
            "bulkUpdatesChecking": "선택한 {type}의 업데이트를 확인하는 중...",
            "bulkUpdatesSuccess": "선택한 {count}개의 {type}에 사용할 수 있는 업데이트가 있습니다",
            "bulkUpdatesNone": "선택한 {type}에 대한 업데이트가 없습니다",
@@ -1895,18 +1934,52 @@
            "warning": "주의 필요",
            "error": "조치 필요"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API 키"
+            },
+            "cache_health": {
+                "title": "모델 캐시 상태"
+            },
+            "filename_conflicts": {
+                "title": "파일명 중복 충돌"
+            },
+            "ui_version": {
+                "title": "UI 버전"
+            }
+        },
        "actions": {
            "runAgain": "다시 실행",
-            "exportBundle": "번들 내보내기"
+            "exportBundle": "번들 내보내기",
+            "open-settings": "설정 열기",
+            "open-settings-syntax-format": "전체 경로 구문으로 전환",
+            "repair-cache": "캐시 재구축",
+            "resolve-filename-conflicts": "충돌 해결",
+            "reload-page": "UI 새로고침"
+        },
+        "labels": {
+            "conflicts": "충돌",
+            "version": "버전"
        },
        "toast": {
            "loadFailed": "진단 로드 실패: {message}",
            "repairSuccess": "캐시 재구성이 완료되었습니다.",
            "repairFailed": "캐시 재구성 실패: {message}",
            "exportSuccess": "진단 번들이 내보내졌습니다.",
-            "exportFailed": "진단 번들 내보내기 실패: {message}"
+            "exportFailed": "진단 번들 내보내기 실패: {message}",
+            "conflictsResolved": "{count}개 파일명 충돌이 해결되었습니다.",
+            "conflictsResolveFailed": "파일명 충돌 해결 실패: {message}"
        }
    },
+    "conflictConfirm": {
+        "title": "파일명 충돌 해결",
+        "message": "중복 파일명에 4자리 해시를 추가하여 이름을 변경합니다.",
+        "note": "이 작업은 디스크에 있는 파일의 이름을 변경합니다. A1111 구문 형식을 사용하는 경우 기존 워크플로우의 모델 참조를 업데이트해야 할 수 있습니다.",
+        "detail": "예시: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "<strong>{groups}</strong>개 중복 그룹에서 <strong>{count}</strong>개 파일 이름을 변경합니다",
+        "confirm": "파일 이름 변경",
+        "cancel": "취소"
+    },
    "banners": {
        "versionMismatch": {
            "title": "애플리케이션 업데이트 감지",
--- a/locales/ru.json
+++ b/locales/ru.json
@@ -15,7 +15,8 @@
            "settings": "Настройки",
            "help": "Справка",
            "add": "Добавить",
-            "close": "Закрыть"
+            "close": "Закрыть",
+            "menu": "Меню"
        },
        "status": {
            "loading": "Загрузка...",
@@ -231,7 +232,10 @@
            "license": "Лицензия",
            "noCreditRequired": "Без указания авторства",
            "allowSellingGeneratedContent": "Продажа разрешена",
+            "allowSellingGeneratedContentTooltip": "Разрешить продажу сгенерированных изображений",
+            "noCreditRequiredTooltip": "Использование модели без указания автора",
            "noTags": "Без тегов",
+            "autoTags": "Авто-теги",
            "noBaseModelMatches": "Нет базовых моделей, соответствующих текущему поиску.",
            "clearAll": "Очистить все фильтры",
            "any": "Любой",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "Бэкенд загрузки",
-            "help": "Выберите способ загрузки файлов моделей. Python использует встроенный загрузчик. aria2 использует экспериментальный внешний процесс загрузки.",
+            "help": "Выберите способ загрузки файлов моделей. Python использует встроенный загрузчик. aria2 использует рекомендуемый внешний процесс загрузки.",
            "options": {
                "python": "Python (встроенный)",
-                "aria2": "aria2 (экспериментальный)"
+                "aria2": "aria2 (рекомендуемый)"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "Показать при наведении"
            },
            "cardInfoDisplayHelp": "Выберите когда отображать информацию о модели и кнопки действий",
+            "showVersionOnCard": "Показывать версию на карточке",
+            "showVersionOnCardHelp": "Показать или скрыть название версии на карточках моделей",
            "modelCardFooterAction": "Действие кнопки карточки модели",
            "modelCardFooterActionOptions": {
                "exampleImages": "Открыть примеры изображений",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "Включать триггерные слова в синтаксис LoRA",
-            "includeTriggerWordsHelp": "Включать обученные триггерные слова при копировании синтаксиса LoRA в буфер обмена"
+            "includeTriggerWordsHelp": "Включать обученные триггерные слова при копировании синтаксиса LoRA в буфер обмена",
+            "loraSyntaxFormat": "Формат синтаксиса LoRA",
+            "loraSyntaxFormatHelp": "Формат синтаксиса LoRA. Полный путь включает подпапку (<lora:style/anime/x:1.0>) для безпотерьного разрешения модели. Устаревший использует только имя файла (<lora:x:1.0>) — соглашение A1111, может быть неоднозначным при дублировании имён файлов в разных папках.",
+            "loraSyntaxFormatOptions": {
+                "full": "Полный путь (подпапка/имя)",
+                "legacy": "Устаревший A1111 (только имя)"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "Включить архив метаданных",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "Обновить список моделей",
-                "quick": "Синхронизировать изменения",
-                "quickTooltip": "Находит новые или отсутствующие файлы моделей, чтобы список оставался актуальным.",
                "full": "Перестроить кэш",
                "fullTooltip": "Перечитывает все данные моделей из файлов метаданных — используйте, если библиотека выглядит устаревшей или после ручных правок."
            },
@@ -679,16 +689,29 @@
            "setContentRating": "Установить рейтинг контента для всех",
            "copyAll": "Копировать весь синтаксис",
            "refreshAll": "Обновить все метаданные",
+            "repairMetadata": "Восстановить метаданные для выбранных",
            "checkUpdates": "Проверить обновления для выбранных",
            "moveAll": "Переместить все в папку",
            "autoOrganize": "Автоматически организовать выбранные",
            "skipMetadataRefresh": "Пропустить обновление метаданных для выбранных",
            "resumeMetadataRefresh": "Возобновить обновление метаданных для выбранных",
+            "setFavorite": "Добавить в избранное",
+            "setFavoriteCount": "Добавить в избранное ({favorited}/{total})",
+            "unfavorite": "Удалить из избранного",
            "deleteAll": "Удалить выбранные",
            "downloadMissingLoras": "Скачать отсутствующие LoRAs",
+            "downloadExamples": "Загрузить примеры изображений",
            "clear": "Очистить выбор",
            "skipMetadataRefreshCount": "Пропустить（{count} моделей）",
            "resumeMetadataRefreshCount": "Возобновить（{count} моделей）",
+            "sendToWorkflow": "Отправить в Workflow",
+            "sections": {
+                "workflow": "Workflow",
+                "metadata": "Метаданные",
+                "attributes": "Атрибуты",
+                "organize": "Организовать",
+                "download": "Скачать"
+            },
            "autoOrganizeProgress": {
                "initializing": "Инициализация автоматической организации...",
                "starting": "Запуск автоматической организации для {type}...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "Обновить список рецептов",
-                "quick": "Синхронизировать изменения",
-                "quickTooltip": "Синхронизировать изменения - быстрое обновление без перестроения кэша",
                "full": "Перестроить кэш",
                "fullTooltip": "Перестроить кэш - полное повторное сканирование всех файлов рецептов"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "моделей будут удалены навсегда.",
            "action": "Удалить все"
        },
+        "bulkDeleteRecipes": {
+            "title": "Удалить несколько рецептов",
+            "message": "Вы уверены, что хотите удалить все выбранные рецепты и связанные с ними файлы?",
+            "countMessage": "рецептов будут удалены навсегда.",
+            "action": "Удалить все"
+        },
        "checkUpdates": {
            "title": "Проверить обновления для всех {typePlural}?",
            "message": "Будут проверены обновления для всех {typePlural} в вашей библиотеке. Для больших коллекций это может занять немного больше времени.",
@@ -1154,6 +1181,7 @@
                "editModelName": "Редактировать название модели",
                "editFileName": "Редактировать имя файла",
                "editBaseModel": "Редактировать базовую модель",
+                "editVersionName": "Редактировать название версии",
                "viewOnCivitai": "Посмотреть на Civitai",
                "viewOnCivitaiText": "Посмотреть на Civitai",
                "viewCreatorProfile": "Посмотреть профиль создателя",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "Ранний доступ",
                    "earlyAccessTooltip": "Для этой версии сейчас требуется ранний доступ Civitai",
                    "ignored": "Игнорируется",
-                    "ignoredTooltip": "Уведомления об обновлениях для этой версии отключены"
+                    "ignoredTooltip": "Уведомления об обновлениях для этой версии отключены",
+                    "onSiteOnly": "Только на Сайте",
+                    "onSiteOnlyTooltip": "Эта версия доступна только для генерации на сайте Civitai"
                },
                "actions": {
                    "download": "Скачать",
                    "downloadTooltip": "Скачать эту версию",
                    "downloadEarlyAccessTooltip": "Скачать эту версию раннего доступа с Civitai",
+                    "downloadNotAllowedTooltip": "Эта версия доступна только для генерации на сайте Civitai",
                    "delete": "Удалить",
                    "deleteTooltip": "Удалить эту локальную версию",
                    "ignore": "Игнорировать",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "Failed to browse directory: {message}",
            "batchImportDirectorySelected": "Directory selected: {path}",
            "noRecipesSelected": "Рецепты не выбраны",
+            "repairBulkComplete": "Восстановление завершено: {repaired} восстановлено, {skipped} пропущено (из {total})",
+            "repairBulkSkipped": "Ни один из {total} выбранных рецептов не требует восстановления",
+            "repairBulkFailed": "Не удалось восстановить выбранные рецепты: {message}",
            "noMissingLorasInSelection": "В выбранных рецептах не найдены отсутствующие LoRAs",
            "noLoraRootConfigured": "Корневой каталог LoRA не настроен. Пожалуйста, установите корневой каталог LoRA по умолчанию в настройках."
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "Рейтинг контента установлен на {level} для {count} модель(ей)",
            "bulkContentRatingPartial": "Рейтинг контента {level} установлен для {success} модель(ей), {failed} не удалось",
            "bulkContentRatingFailed": "Не удалось обновить рейтинг контента для выбранных моделей",
+            "bulkFavoriteUpdating": "Добавление {count} моделей в избранное...",
+            "bulkUnfavoriteUpdating": "Удаление {count} моделей из избранного...",
+            "bulkFavoritePartialAdded": "{success} моделей добавлено в избранное, {failed} не удалось",
+            "bulkFavoritePartialRemoved": "{success} моделей удалено из избранного, {failed} не удалось",
+            "bulkFavoriteFailed": "Не удалось обновить статус избранного",
            "bulkUpdatesChecking": "Проверка обновлений для выбранных {type}...",
            "bulkUpdatesSuccess": "Доступны обновления для {count} выбранных {type}",
            "bulkUpdatesNone": "Обновления для выбранных {type} не найдены",
@@ -1895,18 +1934,52 @@
            "warning": "Требует внимания",
            "error": "Требуется действие"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API Key"
+            },
+            "cache_health": {
+                "title": "Model Cache Health"
+            },
+            "filename_conflicts": {
+                "title": "Duplicate Filename Conflicts"
+            },
+            "ui_version": {
+                "title": "UI Version"
+            }
+        },
        "actions": {
            "runAgain": "Запустить снова",
-            "exportBundle": "Экспортировать пакет"
+            "exportBundle": "Экспортировать пакет",
+            "open-settings": "Open Settings",
+            "open-settings-syntax-format": "Switch to Full Path Syntax",
+            "repair-cache": "Rebuild Cache",
+            "resolve-filename-conflicts": "Resolve Conflicts",
+            "reload-page": "Reload UI"
+        },
+        "labels": {
+            "conflicts": "Conflicts",
+            "version": "Version"
        },
        "toast": {
            "loadFailed": "Не удалось загрузить диагностику: {message}",
            "repairSuccess": "Перестройка кэша завершена.",
            "repairFailed": "Не удалось перестроить кэш: {message}",
            "exportSuccess": "Диагностический пакет экспортирован.",
-            "exportFailed": "Не удалось экспортировать диагностический пакет: {message}"
+            "exportFailed": "Не удалось экспортировать диагностический пакет: {message}",
+            "conflictsResolved": "Разрешено конфликтов имён файлов: {count}.",
+            "conflictsResolveFailed": "Не удалось разрешить конфликты имён файлов: {message}"
        }
    },
+    "conflictConfirm": {
+        "title": "Разрешить конфликты имён файлов",
+        "message": "Переименование с добавлением 4-символьного хеша к каждому дублирующемуся имени файла.",
+        "note": "Эта операция переименовывает файлы на диске. Если вы используете синтаксис A1111, ссылки на модели в существующих рабочих процессах могут потребовать обновления.",
+        "detail": "Пример: <code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "Будет переименовано <strong>{count}</strong> файл(ов) в <strong>{groups}</strong> группе(ах) дубликатов",
+        "confirm": "Переименовать файлы",
+        "cancel": "Отмена"
+    },
    "banners": {
        "versionMismatch": {
            "title": "Обнаружено обновление приложения",
--- a/locales/zh-CN.json
+++ b/locales/zh-CN.json
@@ -15,7 +15,8 @@
            "settings": "设置",
            "help": "帮助",
            "add": "添加",
-            "close": "关闭"
+            "close": "关闭",
+            "menu": "菜单"
        },
        "status": {
            "loading": "加载中...",
@@ -231,7 +232,10 @@
            "license": "许可证",
            "noCreditRequired": "无需署名",
            "allowSellingGeneratedContent": "允许销售",
+            "allowSellingGeneratedContentTooltip": "允许出售生成的图片",
+            "noCreditRequiredTooltip": "使用模型时无需注明原作者",
            "noTags": "无标签",
+            "autoTags": "自动标签",
            "noBaseModelMatches": "没有基础模型符合当前搜索。",
            "clearAll": "清除所有筛选",
            "any": "任一",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "下载后端",
-            "help": "选择模型文件的下载方式。Python 使用内置下载器。aria2 使用实验性的外部下载进程。",
+            "help": "选择模型文件的下载方式。Python 使用内置下载器。aria2 使用推荐的外部下载进程。",
            "options": {
                "python": "Python（内置）",
-                "aria2": "aria2（实验性）"
+                "aria2": "aria2（推荐）"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "悬停时显示"
            },
            "cardInfoDisplayHelp": "选择何时显示模型信息和操作按钮",
+            "showVersionOnCard": "在卡片上显示版本",
+            "showVersionOnCardHelp": "在模型卡片上显示或隐藏版本名称",
            "modelCardFooterAction": "模型卡片按钮操作",
            "modelCardFooterActionOptions": {
                "exampleImages": "打开示例图片",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "复制 LoRA 语法时包含触发词",
-            "includeTriggerWordsHelp": "复制 LoRA 语法到剪贴板时包含训练触发词"
+            "includeTriggerWordsHelp": "复制 LoRA 语法到剪贴板时包含训练触发词",
+            "loraSyntaxFormat": "LoRA 语法格式",
+            "loraSyntaxFormatHelp": "LoRA 语法格式。完整路径（Full）包含子文件夹路径 (<lora:style/anime/x:1.0>)，解析精确无歧义。旧版（Legacy）仅使用文件名 (<lora:x:1.0>)——A1111 原始约定，同名文件跨文件夹时可能产生歧义。",
+            "loraSyntaxFormatOptions": {
+                "full": "完整路径（子文件夹/名称）",
+                "legacy": "旧版 A1111（仅名称）"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "启用元数据归档数据库",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "刷新模型列表",
-                "quick": "同步变更",
-                "quickTooltip": "扫描新的或缺失的模型文件，保持列表最新。",
                "full": "重建缓存",
                "fullTooltip": "从元数据文件重新加载所有模型信息；用于列表过时或手动编辑后。"
            },
@@ -679,16 +689,29 @@
            "setContentRating": "为所选中设置内容评级",
            "copyAll": "复制所选中语法",
            "refreshAll": "刷新所选中元数据",
+            "repairMetadata": "修复所选中元数据",
            "checkUpdates": "检查所选更新",
            "moveAll": "移动所选中到文件夹",
            "autoOrganize": "自动整理所选模型",
            "skipMetadataRefresh": "跳过所选模型的元数据刷新",
            "resumeMetadataRefresh": "恢复所选模型的元数据刷新",
+            "setFavorite": "设为收藏",
+            "setFavoriteCount": "设为收藏 ({favorited}/{total})",
+            "unfavorite": "取消收藏",
            "deleteAll": "删除已选",
            "downloadMissingLoras": "下载缺失的 LoRAs",
+            "downloadExamples": "下载示例图片",
            "clear": "清除选择",
            "skipMetadataRefreshCount": "跳过（{count} 个模型）",
            "resumeMetadataRefreshCount": "恢复（{count} 个模型）",
+            "sendToWorkflow": "发送到工作流",
+            "sections": {
+                "workflow": "工作流",
+                "metadata": "元数据",
+                "attributes": "属性",
+                "organize": "整理",
+                "download": "下载"
+            },
            "autoOrganizeProgress": {
                "initializing": "正在初始化自动整理...",
                "starting": "正在为 {type} 启动自动整理...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "刷新配方列表",
-                "quick": "同步变更",
-                "quickTooltip": "同步变更 - 快速刷新而不重建缓存",
                "full": "重建缓存",
                "fullTooltip": "重建缓存 - 重新扫描所有配方文件"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "模型将被永久删除。",
            "action": "全部删除"
        },
+        "bulkDeleteRecipes": {
+            "title": "删除多个配方",
+            "message": "你确定要删除所有选中的配方及其相关文件吗？",
+            "countMessage": "配方将被永久删除。",
+            "action": "全部删除"
+        },
        "checkUpdates": {
            "title": "检查所有 {type} 的更新？",
            "message": "这会为库中的每个 {type} 检查更新，大型集合可能需要一些时间。",
@@ -1154,6 +1181,7 @@
                "editModelName": "编辑模型名称",
                "editFileName": "编辑文件名",
                "editBaseModel": "编辑基础模型",
+                "editVersionName": "编辑版本名称",
                "viewOnCivitai": "在 Civitai 查看",
                "viewOnCivitaiText": "在 Civitai 查看",
                "viewCreatorProfile": "查看创作者主页",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "抢先体验",
                    "earlyAccessTooltip": "此版本当前需要 Civitai 抢先体验权限",
                    "ignored": "已忽略",
-                    "ignoredTooltip": "此版本已关闭更新通知"
+                    "ignoredTooltip": "此版本已关闭更新通知",
+                    "onSiteOnly": "仅站内生成",
+                    "onSiteOnlyTooltip": "此版本仅在 Civitai 站内可用，无法下载"
                },
                "actions": {
                    "download": "下载",
                    "downloadTooltip": "下载此版本",
                    "downloadEarlyAccessTooltip": "从 Civitai 下载此抢先体验版本",
+                    "downloadNotAllowedTooltip": "此版本仅在 Civitai 站内可用，无法下载",
                    "delete": "删除",
                    "deleteTooltip": "删除此本地版本",
                    "ignore": "忽略",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "浏览目录失败：{message}",
            "batchImportDirectorySelected": "已选择目录：{path}",
            "noRecipesSelected": "未选择任何配方",
+            "repairBulkComplete": "修复完成：{repaired} 个已修复，{skipped} 个已跳过（共 {total} 个）",
+            "repairBulkSkipped": "所选 {total} 个配方无需修复",
+            "repairBulkFailed": "修复所选配方失败：{message}",
            "noMissingLorasInSelection": "在选定的配方中未找到缺失的 LoRAs",
            "noLoraRootConfigured": "未配置 LoRA 根目录。请在设置中设置默认的 LoRA 根目录。"
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "已将 {count} 个模型的内容评级设置为 {level}",
            "bulkContentRatingPartial": "已将 {success} 个模型的内容评级设置为 {level}，{failed} 个失败",
            "bulkContentRatingFailed": "未能更新所选模型的内容评级",
+            "bulkFavoriteUpdating": "正在将 {count} 个模型添加到收藏...",
+            "bulkUnfavoriteUpdating": "正在将 {count} 个模型从收藏移除...",
+            "bulkFavoritePartialAdded": "已将 {success} 个模型添加到收藏，{failed} 个失败",
+            "bulkFavoritePartialRemoved": "已将 {success} 个模型从收藏移除，{failed} 个失败",
+            "bulkFavoriteFailed": "更新收藏状态失败",
            "bulkUpdatesChecking": "正在检查所选 {type} 的更新...",
            "bulkUpdatesSuccess": "{count} 个所选 {type} 有可用更新",
            "bulkUpdatesNone": "所选 {type} 未发现更新",
@@ -1895,18 +1934,52 @@
            "warning": "需要关注",
            "error": "需要处理"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API 密钥"
+            },
+            "cache_health": {
+                "title": "模型缓存健康状态"
+            },
+            "filename_conflicts": {
+                "title": "文件名重复冲突"
+            },
+            "ui_version": {
+                "title": "UI 版本"
+            }
+        },
        "actions": {
            "runAgain": "重新检查",
-            "exportBundle": "导出诊断包"
+            "exportBundle": "导出诊断包",
+            "open-settings": "打开设置",
+            "open-settings-syntax-format": "切换为完整路径语法",
+            "repair-cache": "重建缓存",
+            "resolve-filename-conflicts": "解决冲突",
+            "reload-page": "刷新 UI"
+        },
+        "labels": {
+            "conflicts": "冲突详情",
+            "version": "版本信息"
        },
        "toast": {
            "loadFailed": "加载诊断结果失败：{message}",
            "repairSuccess": "缓存重建完成。",
            "repairFailed": "缓存重建失败：{message}",
            "exportSuccess": "诊断包已导出。",
-            "exportFailed": "导出诊断包失败：{message}"
+            "exportFailed": "导出诊断包失败：{message}",
+            "conflictsResolved": "已解决 {count} 个文件名冲突。",
+            "conflictsResolveFailed": "解决文件名冲突失败：{message}"
        }
    },
+    "conflictConfirm": {
+        "title": "解决文件名冲突",
+        "message": "通过在每个重复文件名后附加 4 位哈希值来重命名文件。",
+        "note": "此操作会重命名磁盘上的文件。如果使用 A1111 语法格式，现有工作流中的模型引用可能需要更新。",
+        "detail": "示例：<code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "将重命名 <strong>{count}</strong> 个文件（共 <strong>{groups}</strong> 组重复）",
+        "confirm": "重命名文件",
+        "cancel": "取消"
+    },
    "banners": {
        "versionMismatch": {
            "title": "检测到应用更新",
--- a/locales/zh-TW.json
+++ b/locales/zh-TW.json
@@ -15,7 +15,8 @@
            "settings": "設定",
            "help": "說明",
            "add": "新增",
-            "close": "關閉"
+            "close": "關閉",
+            "menu": "選單"
        },
        "status": {
            "loading": "載入中...",
@@ -231,7 +232,10 @@
            "license": "授權",
            "noCreditRequired": "無需署名",
            "allowSellingGeneratedContent": "允許銷售",
+            "allowSellingGeneratedContentTooltip": "允許出售生成的圖片",
+            "noCreditRequiredTooltip": "使用模型時無需註明原作者",
            "noTags": "無標籤",
+            "autoTags": "自動標籤",
            "noBaseModelMatches": "沒有基礎模型符合目前的搜尋。",
            "clearAll": "清除所有篩選",
            "any": "任一",
@@ -265,10 +269,10 @@
        },
        "downloadBackend": {
            "label": "下載後端",
-            "help": "選擇模型檔案的下載方式。Python 使用內建下載器。aria2 使用實驗性的外部下載程序。",
+            "help": "選擇模型檔案的下載方式。Python 使用內建下載器。aria2 使用推薦的外部下載程序。",
            "options": {
                "python": "Python（內建）",
-                "aria2": "aria2（實驗性）"
+                "aria2": "aria2（推薦）"
            }
        },
        "aria2cPath": {
@@ -428,6 +432,8 @@
                "hover": "滑鼠懸停顯示"
            },
            "cardInfoDisplayHelp": "選擇何時顯示模型資訊與操作按鈕",
+            "showVersionOnCard": "在卡片上顯示版本",
+            "showVersionOnCardHelp": "在模型卡片上顯示或隱藏版本名稱",
            "modelCardFooterAction": "模型卡片按鈕操作",
            "modelCardFooterActionOptions": {
                "exampleImages": "開啟範例圖片",
@@ -573,7 +579,13 @@
        },
        "misc": {
            "includeTriggerWords": "在 LoRA 語法中包含觸發詞",
-            "includeTriggerWordsHelp": "複製 LoRA 語法到剪貼簿時包含訓練觸發詞"
+            "includeTriggerWordsHelp": "複製 LoRA 語法到剪貼簿時包含訓練觸發詞",
+            "loraSyntaxFormat": "LoRA 語法格式",
+            "loraSyntaxFormatHelp": "LoRA 語法格式。完整路徑（Full）包含子資料夾路徑 (<lora:style/anime/x:1.0>)，解析精確無歧義。舊版（Legacy）僅使用檔名 (<lora:x:1.0>)——A1111 原始約定，同名檔案跨資料夾時可能產生歧義。",
+            "loraSyntaxFormatOptions": {
+                "full": "完整路徑（子資料夾/名稱）",
+                "legacy": "舊版 A1111（僅名稱）"
+            }
        },
        "metadataArchive": {
            "enableArchiveDb": "啟用中繼資料封存資料庫",
@@ -637,8 +649,6 @@
            },
            "refresh": {
                "title": "重新整理模型列表",
-                "quick": "同步變更",
-                "quickTooltip": "掃描新的或缺少的模型檔案，讓清單保持最新。",
                "full": "重建快取",
                "fullTooltip": "從中繼資料檔重新載入所有模型資訊；適用於清單過時或手動編輯後。"
            },
@@ -679,16 +689,29 @@
            "setContentRating": "為全部設定內容分級",
            "copyAll": "複製全部語法",
            "refreshAll": "刷新全部 metadata",
+            "repairMetadata": "修復所選中元數據",
            "checkUpdates": "檢查所選更新",
            "moveAll": "全部移動到資料夾",
            "autoOrganize": "自動整理所選模型",
            "skipMetadataRefresh": "跳過所選模型的元數據更新",
            "resumeMetadataRefresh": "恢復所選模型的元數據更新",
+            "setFavorite": "設為收藏",
+            "setFavoriteCount": "設為收藏 ({favorited}/{total})",
+            "unfavorite": "取消收藏",
            "deleteAll": "刪除所選",
            "downloadMissingLoras": "下載缺失的 LoRAs",
+            "downloadExamples": "下載範例圖片",
            "clear": "清除選取",
            "skipMetadataRefreshCount": "跳過（{count} 個模型）",
            "resumeMetadataRefreshCount": "恢復（{count} 個模型）",
+            "sendToWorkflow": "發送到工作流",
+            "sections": {
+                "workflow": "工作流",
+                "metadata": "元數據",
+                "attributes": "屬性",
+                "organize": "整理",
+                "download": "下載"
+            },
            "autoOrganizeProgress": {
                "initializing": "正在初始化自動整理...",
                "starting": "正在開始自動整理 {type}...",
@@ -801,8 +824,6 @@
            },
            "refresh": {
                "title": "重新整理配方列表",
-                "quick": "同步變更",
-                "quickTooltip": "同步變更 - 快速重新整理而不重建快取",
                "full": "重建快取",
                "fullTooltip": "重建快取 - 重新掃描所有配方檔案"
            },
@@ -1074,6 +1095,12 @@
            "countMessage": "模型將被永久刪除。",
            "action": "全部刪除"
        },
+        "bulkDeleteRecipes": {
+            "title": "刪除多個配方",
+            "message": "您確定要刪除所有選取的配方及其相關檔案嗎？",
+            "countMessage": "配方將被永久刪除。",
+            "action": "全部刪除"
+        },
        "checkUpdates": {
            "title": "要檢查所有 {type} 的更新嗎？",
            "message": "這會為資料庫中的每個 {type} 檢查更新，大型收藏可能會花上一些時間。",
@@ -1154,6 +1181,7 @@
                "editModelName": "編輯模型名稱",
                "editFileName": "編輯檔案名稱",
                "editBaseModel": "編輯基礎模型",
+                "editVersionName": "編輯版本名稱",
                "viewOnCivitai": "在 Civitai 查看",
                "viewOnCivitaiText": "在 Civitai 查看",
                "viewCreatorProfile": "查看創作者個人檔案",
@@ -1290,12 +1318,15 @@
                    "earlyAccess": "搶先體驗",
                    "earlyAccessTooltip": "此版本目前需要 Civitai 搶先體驗權限",
                    "ignored": "已忽略",
-                    "ignoredTooltip": "此版本已關閉更新通知"
+                    "ignoredTooltip": "此版本已關閉更新通知",
+                    "onSiteOnly": "僅站內生成",
+                    "onSiteOnlyTooltip": "此版本僅在 Civitai 站內可用，無法下載"
                },
                "actions": {
                    "download": "下載",
                    "downloadTooltip": "下載此版本",
                    "downloadEarlyAccessTooltip": "從 Civitai 下載此搶先體驗版本",
+                    "downloadNotAllowedTooltip": "此版本僅在 Civitai 站內可用，無法下載",
                    "delete": "刪除",
                    "deleteTooltip": "刪除此本地版本",
                    "ignore": "忽略",
@@ -1663,6 +1694,9 @@
            "batchImportBrowseFailed": "瀏覽目錄失敗：{message}",
            "batchImportDirectorySelected": "已選擇目錄：{path}",
            "noRecipesSelected": "未選取任何食譜",
+            "repairBulkComplete": "修復完成：{repaired} 個已修復，{skipped} 個已跳過（共 {total} 個）",
+            "repairBulkSkipped": "所選 {total} 個配方無需修復",
+            "repairBulkFailed": "修復所選配方失敗：{message}",
            "noMissingLorasInSelection": "在選取的食譜中未找到缺失的 LoRAs",
            "noLoraRootConfigured": "未配置 LoRA 根目錄。請在設定中設定預設的 LoRA 根目錄。"
        },
@@ -1693,6 +1727,11 @@
            "bulkContentRatingSet": "已將 {count} 個模型的內容分級設定為 {level}",
            "bulkContentRatingPartial": "已將 {success} 個模型的內容分級設定為 {level}，{failed} 個失敗",
            "bulkContentRatingFailed": "無法更新所選模型的內容分級",
+            "bulkFavoriteUpdating": "正在將 {count} 個模型加入收藏...",
+            "bulkUnfavoriteUpdating": "正在將 {count} 個模型從收藏移除...",
+            "bulkFavoritePartialAdded": "已將 {success} 個模型加入收藏，{failed} 個失敗",
+            "bulkFavoritePartialRemoved": "已將 {success} 個模型從收藏移除，{failed} 個失敗",
+            "bulkFavoriteFailed": "更新收藏狀態失敗",
            "bulkUpdatesChecking": "正在檢查所選 {type} 的更新...",
            "bulkUpdatesSuccess": "{count} 個所選 {type} 有可用更新",
            "bulkUpdatesNone": "所選 {type} 未找到更新",
@@ -1895,18 +1934,52 @@
            "warning": "需要注意",
            "error": "需要處理"
        },
+        "issues": {
+            "civitai_api_key": {
+                "title": "Civitai API 金鑰"
+            },
+            "cache_health": {
+                "title": "模型快取健康狀態"
+            },
+            "filename_conflicts": {
+                "title": "檔案名稱重複衝突"
+            },
+            "ui_version": {
+                "title": "UI 版本"
+            }
+        },
        "actions": {
            "runAgain": "重新執行",
-            "exportBundle": "匯出套件"
+            "exportBundle": "匯出套件",
+            "open-settings": "開啟設定",
+            "open-settings-syntax-format": "切換為完整路徑語法",
+            "repair-cache": "重建快取",
+            "resolve-filename-conflicts": "解決衝突",
+            "reload-page": "重新載入 UI"
+        },
+        "labels": {
+            "conflicts": "衝突詳情",
+            "version": "版本"
        },
        "toast": {
            "loadFailed": "載入診斷失敗：{message}",
            "repairSuccess": "快取重建完成。",
            "repairFailed": "快取重建失敗：{message}",
            "exportSuccess": "診斷套件已匯出。",
-            "exportFailed": "匯出診斷套件失敗：{message}"
+            "exportFailed": "匯出診斷套件失敗：{message}",
+            "conflictsResolved": "已解決 {count} 個檔案名稱衝突。",
+            "conflictsResolveFailed": "解決檔案名稱衝突失敗：{message}"
        }
    },
+    "conflictConfirm": {
+        "title": "解決檔案名稱衝突",
+        "message": "通過在每個重複檔案名稱後附加 4 位元哈希值來重新命名檔案。",
+        "note": "此操作會重新命名磁碟上的檔案。如果使用 A1111 語法格式，現有工作流程中的模型參考可能需要更新。",
+        "detail": "示例：<code>filename_v1.2</code> → <code>filename_v1.2-ab3c</code>",
+        "impact": "將重新命名 <strong>{count}</strong> 個檔案（共 <strong>{groups}</strong> 組重複）",
+        "confirm": "重新命名檔案",
+        "cancel": "取消"
+    },
    "banners": {
        "versionMismatch": {
            "title": "偵測到應用程式更新",
--- a/py/config.py
+++ b/py/config.py
@@ -172,6 +172,12 @@ class Config:
        self.extra_unet_roots: List[str] = []
        self.extra_embeddings_roots: List[str] = []
        self.recipes_path: str = ""
+
+        # Load extra folder paths from active library settings before symlink scan
+        # so both primary and extra paths are discovered in a single pass.
+        if not standalone_mode:
+            self._load_extra_paths_from_settings()
+
        # Scan symbolic links during initialization
        self._initialize_symlink_mappings()

@@ -179,6 +185,96 @@ class Config:
            # Save the paths to settings.json when running in ComfyUI mode
            self.save_folder_paths_to_settings()

+    def _load_extra_paths_from_settings(self) -> None:
+        """Read extra folder paths from the active library and apply them.
+
+        Called during ``Config.__init__`` before the symlink scan so both primary and
+        extra paths are discovered in a single pass.  Mirrors the extra-path
+        portion of ``_apply_library_paths`` without replacing the primary roots
+        that were already resolved from ComfyUI's ``folder_paths``.
+        """
+        try:
+            from .services.settings_manager import get_settings_manager
+
+            settings_manager = get_settings_manager()
+            library_name = settings_manager.get_active_library_name()
+            libraries = settings_manager.get_libraries()
+
+            if not library_name or library_name not in libraries:
+                return
+
+            library_config = libraries[library_name]
+            if not isinstance(library_config, dict):
+                return
+
+            extra_folder_paths = library_config.get("extra_folder_paths")
+            if not isinstance(extra_folder_paths, dict):
+                return
+
+            extra_lora = extra_folder_paths.get("loras", []) or []
+            extra_checkpoint = extra_folder_paths.get("checkpoints", []) or []
+            extra_unet = extra_folder_paths.get("unet", []) or []
+            extra_embedding = extra_folder_paths.get("embeddings", []) or []
+
+            if not any([extra_lora, extra_checkpoint, extra_unet, extra_embedding]):
+                return
+
+            filtered_extra_lora = self._filter_overlapping_extra_lora_paths(
+                self.loras_roots, extra_lora
+            )
+            self.extra_loras_roots = self._prepare_lora_paths(filtered_extra_lora)
+            (
+                _,
+                self.extra_checkpoints_roots,
+                self.extra_unet_roots,
+            ) = self._prepare_checkpoint_paths(extra_checkpoint, extra_unet)
+            self.extra_embeddings_roots = self._prepare_embedding_paths(
+                extra_embedding
+            )
+
+            recipes_path = library_config.get("recipes_path", "")
+            if isinstance(recipes_path, str) and recipes_path:
+                self.recipes_path = recipes_path
+
+            if self.extra_loras_roots:
+                logger.info(
+                    "Found extra LoRA roots:"
+                    + "\n - "
+                    + "\n - ".join(self.extra_loras_roots)
+                )
+            if self.extra_checkpoints_roots:
+                logger.info(
+                    "Found extra checkpoint roots:"
+                    + "\n - "
+                    + "\n - ".join(self.extra_checkpoints_roots)
+                )
+            if self.extra_unet_roots:
+                logger.info(
+                    "Found extra diffusion model roots:"
+                    + "\n - "
+                    + "\n - ".join(self.extra_unet_roots)
+                )
+            if self.extra_embeddings_roots:
+                logger.info(
+                    "Found extra embedding roots:"
+                    + "\n - "
+                    + "\n - ".join(self.extra_embeddings_roots)
+                )
+
+            logger.info(
+                "Applied library settings for '%s' with extra paths: loras=%s, "
+                "checkpoints=%s, embeddings=%s",
+                library_name,
+                extra_lora,
+                extra_checkpoint,
+                extra_embedding,
+            )
+
+        except Exception as exc:
+            logger.debug(
+                "Could not load extra paths from library settings: %s", exc
+            )
+
    def save_folder_paths_to_settings(self):
        """Persist ComfyUI-derived folder paths to the multi-library settings."""
        try:
--- a/py/lora_manager.py
+++ b/py/lora_manager.py
@@ -184,39 +184,6 @@ class LoraManager:
    async def _initialize_services(cls):
        """Initialize all services using the ServiceRegistry"""
        try:
-            # Apply library settings to load extra folder paths before scanning
-            # Only apply if extra paths haven't been loaded yet (preserves test mocks)
-            try:
-                from .services.settings_manager import get_settings_manager
-
-                settings_manager = get_settings_manager()
-                library_name = settings_manager.get_active_library_name()
-                libraries = settings_manager.get_libraries()
-                if library_name and library_name in libraries:
-                    library_config = libraries[library_name]
-                    # Only apply settings if extra paths are not already configured
-                    # This preserves values set by tests via monkeypatch
-                    extra_paths = library_config.get("extra_folder_paths", {})
-                    has_extra_paths = (
-                        config.extra_loras_roots
-                        or config.extra_checkpoints_roots
-                        or config.extra_unet_roots
-                        or config.extra_embeddings_roots
-                    )
-                    if not has_extra_paths and any(extra_paths.values()):
-                        config.apply_library_settings(library_config)
-                        logger.info(
-                            "Applied library settings for '%s' with extra paths: loras=%s, checkpoints=%s, embeddings=%s",
-                            library_name,
-                            extra_paths.get("loras", []),
-                            extra_paths.get("checkpoints", []),
-                            extra_paths.get("embeddings", []),
-                        )
-            except Exception as exc:
-                logger.warning(
-                    "Failed to apply library settings during initialization: %s", exc
-                )
-
            # Initialize CivitaiClient first to ensure it's ready for other services
            await ServiceRegistry.get_civitai_client()

--- a/py/metadata_collector/metadata_processor.py
+++ b/py/metadata_collector/metadata_processor.py
@@ -560,8 +560,14 @@ class MetadataProcessor:
        
        params["loras"] = " ".join(lora_parts)
        
-        # Set default clip_skip value
-        params["clip_skip"] = "1"  # Common default
+        # Extract clip_skip from any SAMPLING node that provides it
+        for sampler_info in metadata.get(SAMPLING, {}).values():
+            clip_skip = sampler_info.get("parameters", {}).get("clip_skip")
+            if clip_skip is not None:
+                params["clip_skip"] = clip_skip
+                break
+        if params["clip_skip"] is None:
+            params["clip_skip"] = "1"
        
        return params
    
--- a/py/metadata_collector/node_extractors.py
+++ b/py/metadata_collector/node_extractors.py
@@ -144,6 +144,118 @@ class TSCCheckpointLoaderExtractor(NodeMetadataExtractor):
                metadata[PROMPTS][node_id]["positive_encoded"] = positive_conditioning
                metadata[PROMPTS][node_id]["negative_encoded"] = negative_conditioning

+
+class EasyComfyLoaderExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        if "ckpt_name" in inputs:
+            _store_checkpoint_metadata(metadata, node_id, inputs["ckpt_name"])
+
+        # Only extract from optional_lora_stack — skip the single lora_name to
+        # avoid double-counting LoRAs that come through the LORA_STACK path.
+        active_loras = []
+        optional_lora_stack = inputs.get("optional_lora_stack")
+        if optional_lora_stack is not None and isinstance(optional_lora_stack, (list, tuple)):
+            for item in optional_lora_stack:
+                if isinstance(item, (list, tuple)) and len(item) >= 2:
+                    lora_path = item[0]
+                    model_strength = item[1]
+                    lora_name = os.path.splitext(os.path.basename(lora_path))[0]
+                    active_loras.append({
+                        "name": lora_name,
+                        "strength": model_strength
+                    })
+
+        if active_loras:
+            metadata[LORAS][node_id] = {
+                "lora_list": active_loras,
+                "node_id": node_id
+            }
+
+        positive_text = inputs.get("positive", "")
+        negative_text = inputs.get("negative", "")
+
+        if positive_text or negative_text:
+            if node_id not in metadata[PROMPTS]:
+                metadata[PROMPTS][node_id] = {"node_id": node_id}
+            metadata[PROMPTS][node_id]["positive_text"] = positive_text
+            metadata[PROMPTS][node_id]["negative_text"] = negative_text
+
+        if "clip_skip" in inputs:
+            clip_skip = inputs["clip_skip"]
+            if node_id not in metadata[SAMPLING]:
+                metadata[SAMPLING][node_id] = {"parameters": {}, "node_id": node_id}
+            metadata[SAMPLING][node_id]["parameters"]["clip_skip"] = clip_skip
+
+        width = inputs.get("empty_latent_width")
+        height = inputs.get("empty_latent_height")
+        if width is not None and height is not None:
+            if SIZE not in metadata:
+                metadata[SIZE] = {}
+            metadata[SIZE][node_id] = {
+                "width": int(width),
+                "height": int(height),
+                "node_id": node_id
+            }
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        # outputs: [(pipe_dict, model, vae), ...]
+        if not outputs or not isinstance(outputs, list) or len(outputs) == 0:
+            return
+        first_output = outputs[0]
+        if not isinstance(first_output, tuple) or len(first_output) < 1:
+            return
+        pipe = first_output[0]
+        if not isinstance(pipe, dict):
+            return
+
+        positive_conditioning = pipe.get("positive")
+        negative_conditioning = pipe.get("negative")
+
+        if positive_conditioning is not None or negative_conditioning is not None:
+            if node_id not in metadata[PROMPTS]:
+                metadata[PROMPTS][node_id] = {"node_id": node_id}
+            if positive_conditioning is not None:
+                metadata[PROMPTS][node_id]["positive_encoded"] = positive_conditioning
+            if negative_conditioning is not None:
+                metadata[PROMPTS][node_id]["negative_encoded"] = negative_conditioning
+
+
+class EasyPreSamplingExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        sampling_params = {}
+        for key in ("steps", "cfg", "sampler_name", "scheduler", "denoise", "seed"):
+            if key in inputs:
+                sampling_params[key] = inputs[key]
+
+        metadata[SAMPLING][node_id] = {
+            "parameters": sampling_params,
+            "node_id": node_id,
+            IS_SAMPLER: True
+        }
+
+
+class EasySeedExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "seed" not in inputs:
+            return
+
+        metadata[SAMPLING][node_id] = {
+            "parameters": {"seed": inputs["seed"]},
+            "node_id": node_id,
+            IS_SAMPLER: False
+        }
+
+
 class CLIPTextEncodeExtractor(NodeMetadataExtractor):
    @staticmethod
    def extract(node_id, inputs, outputs, metadata):
@@ -1013,9 +1125,12 @@ NODE_EXTRACTORS = {
    "KSamplerSelect": KSamplerSelectExtractor,  # Add KSamplerSelect
    "BasicScheduler": BasicSchedulerExtractor,  # Add BasicScheduler
    "AlignYourStepsScheduler": BasicSchedulerExtractor,  # Add AlignYourStepsScheduler
+    # ComfyUI-Easy-Use pre-sampling / seed
+    "samplerSettings": EasyPreSamplingExtractor,  # easy preSampling
+    "easySeed": EasySeedExtractor,  # easy seed
    # Loaders
    "CheckpointLoaderSimple": CheckpointLoaderExtractor,
-    "comfyLoader": CheckpointLoaderExtractor,  # easy comfyLoader
+    "comfyLoader": EasyComfyLoaderExtractor,  # ComfyUI-Easy-Use easy comfyLoader
    "CheckpointLoaderSimpleWithImages": CheckpointLoaderExtractor,  # CheckpointLoader|pysssss
    "TSC_EfficientLoader": TSCCheckpointLoaderExtractor,  # Efficient Nodes
    "NunchakuFluxDiTLoader": NunchakuFluxDiTLoaderExtractor,  # ComfyUI-Nunchaku
--- a/py/nodes/lora_loader.py
+++ b/py/nodes/lora_loader.py
@@ -9,6 +9,7 @@ from ..utils.utils import get_lora_info_absolute
 from .utils import (
    FlexibleOptionalInputType,
    any_type,
+    apply_lora_syntax_format,
    detect_nunchaku_model_kind,
    extract_lora_name,
    get_loras_list,
@@ -52,7 +53,7 @@ def _collect_widget_entries(kwargs):
    for lora in get_loras_list(kwargs):
        if not lora.get("active", False):
            continue
-        lora_name = lora["name"]
+        lora_name = apply_lora_syntax_format(lora["name"])
        model_strength = float(lora["strength"])
        clip_strength = float(lora.get("clipStrength", model_strength))
        lora_path, trigger_words = get_lora_info_absolute(lora_name)
--- a/py/nodes/lora_stacker.py
+++ b/py/nodes/lora_stacker.py
@@ -1,6 +1,6 @@
 import os
 from ..utils.utils import get_lora_info
-from .utils import FlexibleOptionalInputType, any_type, extract_lora_name, get_loras_list
+from .utils import FlexibleOptionalInputType, any_type, apply_lora_syntax_format, extract_lora_name, get_loras_list

 import logging

@@ -48,7 +48,7 @@ class LoraStackerLM:
            if not lora.get('active', False):
                continue
                
-            lora_name = lora['name']
+            lora_name = apply_lora_syntax_format(lora['name'])
            model_strength = float(lora['strength'])
            # Get clip strength - use model strength as default if not specified
            clip_strength = float(lora.get('clipStrength', model_strength))
--- a/py/nodes/utils.py
+++ b/py/nodes/utils.py
@@ -44,11 +44,29 @@ import folder_paths  # type: ignore
 logger = logging.getLogger(__name__)


+def get_lora_syntax_format():
+    try:
+        from ..services.settings_manager import get_settings_manager
+        return get_settings_manager().get("lora_syntax_format", "legacy")
+    except Exception:
+        return "legacy"
+
+
+def apply_lora_syntax_format(name):
+    fmt = get_lora_syntax_format()
+    if fmt == "legacy":
+        return name.replace("\\", "/").rstrip("/").split("/")[-1]
+    return name
+
+
 def extract_lora_name(lora_path):
-    """Extract the lora name from a lora path (e.g., 'IL\\aorunIllstrious.safetensors' -> 'aorunIllstrious')"""
-    # Get the basename without extension
-    basename = os.path.basename(lora_path)
-    return os.path.splitext(basename)[0]
+    normalized = lora_path.replace("\\", "/")
+    basename = os.path.basename(normalized)
+    name_no_ext = os.path.splitext(basename)[0]
+    dirname = os.path.dirname(normalized)
+    if dirname and dirname not in (".", "/") and not normalized.startswith("/"):
+        return apply_lora_syntax_format(f"{dirname}/{name_no_ext}")
+    return apply_lora_syntax_format(name_no_ext)


 def get_loras_list(kwargs):
--- a/py/nodes/wanvideo_lora_select.py
+++ b/py/nodes/wanvideo_lora_select.py
@@ -1,10 +1,22 @@
-import folder_paths # type: ignore
-from ..utils.utils import get_lora_info
+import os
+from ..utils.utils import get_lora_info_absolute
+from ..config import config
 from .utils import FlexibleOptionalInputType, any_type, get_loras_list
 import logging

 logger = logging.getLogger(__name__)

+
+def _relpath_within_loras(abs_path):
+    """Return abs_path relative to the first matching lora root, or basename as fallback."""
+    all_roots = list(config.loras_roots or []) + list(config.extra_loras_roots or [])
+    for root in all_roots:
+        try:
+            return os.path.relpath(abs_path, root)
+        except ValueError:
+            continue
+    return os.path.basename(abs_path)
+
 class WanVideoLoraSelectLM:
    NAME = "WanVideo Lora Select (LoraManager)"
    CATEGORY = "Lora Manager/stackers"
@@ -56,13 +68,13 @@ class WanVideoLoraSelectLM:
            clip_strength = float(lora.get('clipStrength', model_strength))
            
            # Get lora path and trigger words
-            lora_path, trigger_words = get_lora_info(lora_name)
+            lora_path, trigger_words = get_lora_info_absolute(lora_name)
            
            # Create lora item for WanVideo format
            lora_item = {
-                "path": folder_paths.get_full_path("loras", lora_path),
+                "path": lora_path,
                "strength": model_strength,
-                "name": lora_path.split(".")[0],
+                "name": os.path.splitext(_relpath_within_loras(lora_path))[0],
                "blocks": selected_blocks,
                "layer_filter": layer_filter,
                "low_mem_load": low_mem_load,
--- a/py/nodes/wanvideo_lora_select_from_text.py
+++ b/py/nodes/wanvideo_lora_select_from_text.py
@@ -1,11 +1,23 @@
-import folder_paths # type: ignore
-from ..utils.utils import get_lora_info
+import os
+from ..utils.utils import get_lora_info_absolute
+from ..config import config
 from .utils import any_type 
 import logging

 # 初始化日志记录器
 logger = logging.getLogger(__name__)

+
+def _relpath_within_loras(abs_path):
+    """Return abs_path relative to the first matching lora root, or basename as fallback."""
+    all_roots = list(config.loras_roots or []) + list(config.extra_loras_roots or [])
+    for root in all_roots:
+        try:
+            return os.path.relpath(abs_path, root)
+        except ValueError:
+            continue
+    return os.path.basename(abs_path)
+
 # 定义新节点的类
 class WanVideoLoraTextSelectLM:
    # 节点在UI中显示的名称
@@ -87,12 +99,12 @@ class WanVideoLoraTextSelectLM:
            else:
                continue

-            lora_path, trigger_words = get_lora_info(lora_name_raw)
+            lora_path, trigger_words = get_lora_info_absolute(lora_name_raw)

            lora_item = {
-                "path": folder_paths.get_full_path("loras", lora_path),
+                "path": lora_path,
                "strength": model_strength,
-                "name": lora_path.split(".")[0],
+                "name": os.path.splitext(_relpath_within_loras(lora_path))[0],
                "blocks": selected_blocks,
                "layer_filter": layer_filter,
                "low_mem_load": low_mem_load,
--- a/py/recipes/base.py
+++ b/py/recipes/base.py
@@ -7,7 +7,7 @@ import re
 from typing import Dict, List, Any, Optional, Tuple
 from abc import ABC, abstractmethod
 from ..config import config
-from ..utils.constants import VALID_LORA_TYPES
+from ..utils.constants import VALID_LORA_TYPES, VALID_CHECKPOINT_SUB_TYPES
 from ..utils.civitai_utils import rewrite_preview_url

 logger = logging.getLogger(__name__)
@@ -173,6 +173,20 @@ class RecipeMetadataParser(ABC):
                checkpoint['isDeleted'] = True
                return checkpoint

+            # Validate that the model type is actually a checkpoint.
+            # Unlike populate_lora_from_civitai which has this check,
+            # this function was missing type validation — allowing LoRA
+            # version data to be saved as the recipe's checkpoint when the
+            # wrong version ID was passed downstream (fixed in v2.7+).
+            model_type = civitai_data.get('model', {}).get('type', '').lower()
+            if model_type not in VALID_CHECKPOINT_SUB_TYPES:
+                logger.warning(
+                    f"Cannot populate checkpoint: model version {civitai_data.get('id')} "
+                    f"has type '{model_type}', expected one of {VALID_CHECKPOINT_SUB_TYPES}. "
+                    f"Skipping checkpoint enrichment."
+                )
+                return checkpoint
+
            if 'model' in civitai_data and 'name' in civitai_data['model']:
                checkpoint['name'] = civitai_data['model']['name']

--- a/py/recipes/enrichment.py
+++ b/py/recipes/enrichment.py
@@ -16,55 +16,65 @@ class RecipeEnricher:
    async def enrich_recipe(
        recipe: Dict[str, Any],
        civitai_client: Any,
-        request_params: Optional[Dict[str, Any]] = None
+        request_params: Optional[Dict[str, Any]] = None,
+        prefetched_civitai_meta_raw: Optional[Dict[str, Any]] = None,
+        prefetched_model_version_id: Optional[int] = None,
    ) -> bool:
        """
        Enrich a recipe dictionary in-place with metadata from Civitai and embedded params.
-        
+
        Args:
            recipe: The recipe dictionary to enrich. Must have 'gen_params' initialized.
            civitai_client: Authenticated Civitai client instance.
            request_params: (Optional) Parameters from a user request (e.g. import).
-            
+            prefetched_civitai_meta_raw: (Optional) Pre-fetched raw meta from Civitai
+                get_image_info, avoiding a duplicate API call.
+            prefetched_model_version_id: (Optional) Pre-fetched model version ID.
+
        Returns:
            bool: True if the recipe was modified, False otherwise.
        """
        updated = False
        gen_params = recipe.get("gen_params", {})
-        
-        # 1. Fetch Civitai Info if available
+
+        # 1. Obtain Civitai metadata
        civitai_meta = None
-        model_version_id = None
-        
-        source_url = recipe.get("source_url") or recipe.get("source_path", "")
-        
-        # Check if it's a Civitai image URL
-        image_id = extract_civitai_image_id(str(source_url))
-        if image_id:
-            try:
-                image_info = await civitai_client.get_image_info(
-                    image_id, source_url=str(source_url)
-                )
-                if image_info:
-                    # Handle nested meta often found in Civitai API responses
-                    raw_meta = image_info.get("meta")
-                    if isinstance(raw_meta, dict):
-                        if "meta" in raw_meta and isinstance(raw_meta["meta"], dict):
-                            civitai_meta = raw_meta["meta"]
-                        else:
-                            civitai_meta = raw_meta
-                    
-                    model_version_id = image_info.get("modelVersionId")
-                    
-                    # If not at top level, check resources in meta
-                    if not model_version_id and civitai_meta:
-                        resources = civitai_meta.get("civitaiResources", [])
-                        for res in resources:
-                            if res.get("type") == "checkpoint":
-                                model_version_id = res.get("modelVersionId")
-                                break
-            except Exception as e:
-                logger.warning(f"Failed to fetch Civitai image info: {e}")
+        model_version_id = prefetched_model_version_id
+
+        source_path = recipe.get("source_path", "")
+
+        if prefetched_civitai_meta_raw is not None:
+            raw_meta = prefetched_civitai_meta_raw
+            if isinstance(raw_meta, dict):
+                if "meta" in raw_meta and isinstance(raw_meta["meta"], dict):
+                    civitai_meta = raw_meta["meta"]
+                else:
+                    civitai_meta = raw_meta
+        else:
+            image_id = extract_civitai_image_id(str(source_path))
+            if image_id:
+                try:
+                    image_info = await civitai_client.get_image_info(
+                        image_id, source_url=str(source_path)
+                    )
+                    if image_info:
+                        raw_meta = image_info.get("meta")
+                        if isinstance(raw_meta, dict):
+                            if "meta" in raw_meta and isinstance(raw_meta["meta"], dict):
+                                civitai_meta = raw_meta["meta"]
+                            else:
+                                civitai_meta = raw_meta
+
+                        model_version_id = image_info.get("modelVersionId")
+                except Exception as e:
+                    logger.warning(f"Failed to fetch Civitai image info: {e}")
+
+        if not model_version_id and civitai_meta:
+            resources = civitai_meta.get("civitaiResources", [])
+            for res in resources:
+                if res.get("type") == "checkpoint":
+                    model_version_id = res.get("modelVersionId")
+                    break

        # 2. Merge Parameters
        # Priority: request_params > civitai_meta > embedded (existing gen_params)
--- a/py/recipes/parsers/civitai_image.py
+++ b/py/recipes/parsers/civitai_image.py
@@ -185,8 +185,67 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
            # Process standard resources array
            if "resources" in metadata and isinstance(metadata["resources"], list):
                for resource in metadata["resources"]:
+                    resource_type = resource.get("type", "lora")
+
+                    # Track resources with type "model" — these are checkpoint models.
+                    # The resources array is the most reliable source for checkpoint
+                    # identification because it has an explicit type field and hash,
+                    # unlike modelVersionIds which is a flat list with no type info.
+                    if resource_type == "model":
+                        checkpoint_entry = {
+                            "id": 0,
+                            "modelId": 0,
+                            "name": resource.get("name", "Unknown Model"),
+                            "version": "",
+                            "type": resource.get("type", "model"),
+                            "existsLocally": False,
+                            "localPath": None,
+                            "file_name": resource.get("name", ""),
+                            "hash": resource.get("hash", "") or "",
+                            "thumbnailUrl": "/loras_static/images/no-preview.png",
+                            "baseModel": "",
+                            "size": 0,
+                            "downloadUrl": "",
+                            "isDeleted": False,
+                        }
+
+                        # Try to look up base model from the checkpoint hash
+                        if checkpoint_entry["hash"] and metadata_provider:
+                            try:
+                                civitai_info = (
+                                    await metadata_provider.get_model_by_hash(
+                                        checkpoint_entry["hash"]
+                                    )
+                                )
+                                civitai_data, error_msg = (
+                                    (civitai_info, None)
+                                    if not isinstance(civitai_info, tuple)
+                                    else civitai_info
+                                )
+                                if civitai_data and error_msg != "Model not found":
+                                    if 'model' in civitai_data and 'name' in civitai_data['model']:
+                                        checkpoint_entry['name'] = civitai_data['model']['name']
+                                    checkpoint_entry['id'] = civitai_data.get('id', 0)
+                                    checkpoint_entry['modelId'] = civitai_data.get('modelId', 0)
+                                    if 'name' in civitai_data:
+                                        checkpoint_entry['version'] = civitai_data['name']
+                                    base_model = civitai_data.get('baseModel', '')
+                                    if base_model:
+                                        checkpoint_entry['baseModel'] = base_model
+                                        if not result['base_model']:
+                                            result['base_model'] = base_model
+                            except Exception as e:
+                                logger.error(
+                                    f"Error fetching checkpoint info for hash "
+                                    f"{checkpoint_entry['hash']}: {e}"
+                                )
+
+                        if result["model"] is None:
+                            result["model"] = checkpoint_entry
+                        continue
+
                    # Modified to process resources without a type field as potential LoRAs
-                    if resource.get("type", "lora") == "lora":
+                    if resource_type == "lora":
                        lora_hash = resource.get("hash", "")

                        # Try to get hash from the hashes field if not present in resource
--- a/py/routes/base_model_routes.py
+++ b/py/routes/base_model_routes.py
@@ -251,7 +251,7 @@ class BaseModelRoutes(ABC):

    def _find_model_file(self, files):
        """Find the appropriate model file from the files list - can be overridden by subclasses."""
-        return next((file for file in files if file.get("type") == "Model" and file.get("primary") is True), None)
+        return next((file for file in files if file.get("type") in ("Model", "Diffusion Model") and file.get("primary") is True), None)

    def get_handler(self, name: str) -> Callable[[web.Request], web.StreamResponse]:
        """Expose handlers for subclasses or tests."""
--- a/py/routes/handlers/misc_handlers.py
+++ b/py/routes/handlers/misc_handlers.py
@@ -33,15 +33,18 @@ from ...services.metadata_service import (
    update_metadata_providers,
 )
 from ...services.service_registry import ServiceRegistry
+from ...services.model_lifecycle_service import delete_model_artifacts
 from ...services.settings_manager import get_settings_manager
 from ...services.websocket_manager import ws_manager
 from ...services.downloader import get_downloader
 from ...services.errors import ResourceNotFoundError
 from ...services.cache_health_monitor import CacheHealthMonitor, CacheHealthStatus
+from ...utils.models import BaseModelMetadata
 from ...utils.constants import (
    CIVITAI_USER_MODEL_TYPES,
    DEFAULT_NODE_COLOR,
    NODE_TYPES,
+    PREVIEW_EXTENSIONS,
    SUPPORTED_MEDIA_EXTENSIONS,
    VALID_LORA_TYPES,
 )
@@ -617,6 +620,7 @@ class DoctorHandler:
            diagnostics = [
                await self._check_civitai_api_key(),
                await self._check_cache_health(),
+                await self._check_filename_conflicts(),
                self._check_ui_version(client_version, app_version),
            ]

@@ -681,6 +685,148 @@ class DoctorHandler:
            status=status,
        )

+    async def resolve_filename_conflicts(self, request: web.Request) -> web.Response:
+        if self._settings.get("lora_syntax_format", "legacy") == "full":
+            return web.json_response({"success": True, "renamed": [], "count": 0})
+
+        renamed: list[dict[str, Any]] = []
+
+        try:
+            for model_type, label, factory in self._scanner_factories:
+                try:
+                    scanner = await factory()
+                    hash_index = getattr(scanner, "_hash_index", None)
+                    if hash_index is None:
+                        continue
+                    duplicates = {
+                        filename: list(paths)
+                        for filename, paths in hash_index.get_duplicate_filenames().items()
+                    }
+                    if not duplicates:
+                        continue
+
+                    cache = await scanner.get_cached_data()
+                    path_to_model = {m["file_path"]: m for m in cache.raw_data}
+
+                    used_basenames: set[str] = set()
+                    for paths in duplicates.values():
+                        if paths:
+                            used_basenames.add(
+                                os.path.splitext(os.path.basename(paths[0]))[0]
+                            )
+
+                    for filename, paths in duplicates.items():
+                        for idx, path in enumerate(paths):
+                            if idx == 0:
+                                continue
+                            dirname = os.path.dirname(path)
+                            base_name = os.path.splitext(os.path.basename(path))[0]
+                            ext = os.path.splitext(path)[1]
+                            if not ext:
+                                continue
+
+                            model_data = path_to_model.get(path)
+                            sha256 = (
+                                model_data.get("sha256", "") if model_data else ""
+                            )
+                            hash_provider = (
+                                lambda s=sha256: s if s else "0000"
+                            )
+
+                            new_filename = (
+                                BaseModelMetadata.generate_unique_filename(
+                                    dirname,
+                                    base_name,
+                                    ext,
+                                    hash_provider=hash_provider,
+                                )
+                            )
+
+                            candidate_base = os.path.splitext(new_filename)[0]
+                            counter = 1
+                            original_base = candidate_base
+                            while candidate_base in used_basenames:
+                                candidate_base = f"{original_base}-{counter}"
+                                new_filename = f"{candidate_base}{ext}"
+                                counter += 1
+                            used_basenames.add(candidate_base)
+
+                            new_path = os.path.join(dirname, new_filename)
+
+                            if new_filename == os.path.basename(path):
+                                continue
+
+                            if not os.path.exists(path):
+                                continue
+
+                            old_base_no_ext = os.path.splitext(path)[0]
+                            new_base_no_ext = (
+                                os.path.splitext(new_path)[0]
+                            )
+
+                            os.rename(path, new_path)
+
+                            for suffix in (".metadata.json", ".civitai.info"):
+                                old_sidecar = old_base_no_ext + suffix
+                                new_sidecar = new_base_no_ext + suffix
+                                if os.path.exists(old_sidecar):
+                                    os.rename(old_sidecar, new_sidecar)
+
+                            for preview_ext in PREVIEW_EXTENSIONS:
+                                old_preview = old_base_no_ext + preview_ext
+                                new_preview = new_base_no_ext + preview_ext
+                                if os.path.exists(old_preview):
+                                    os.rename(old_preview, new_preview)
+
+                            entry = path_to_model.get(path)
+                            if entry:
+                                entry = dict(entry)
+                                entry["file_name"] = os.path.splitext(new_filename)[0]
+                                if entry.get("preview_url"):
+                                    old_preview_url = entry["preview_url"].replace("\\", "/")
+                                    preview_ext = os.path.splitext(old_preview_url)[1]
+                                    if preview_ext:
+                                        entry["preview_url"] = (new_base_no_ext + preview_ext).replace(os.sep, "/")
+                                await scanner.update_single_model_cache(
+                                    path, new_path, entry
+                                )
+
+                            logger.info(
+                                "Resolved duplicate filename '%s': "
+                                "renamed '%s' to '%s'",
+                                filename,
+                                path,
+                                new_path,
+                            )
+                            renamed.append({
+                                "model_type": model_type,
+                                "label": label,
+                                "filename": filename,
+                                "old_path": path,
+                                "new_path": new_path,
+                                "new_filename": new_filename,
+                            })
+                except Exception as exc:  # pragma: no cover - defensive
+                    logger.error(
+                        "Failed to resolve filename conflicts for %s: %s",
+                        model_type,
+                        exc,
+                        exc_info=True,
+                    )
+
+            return web.json_response({
+                "success": True,
+                "renamed": renamed,
+                "count": len(renamed),
+            })
+        except Exception as exc:
+            logger.error(
+                "Error resolving filename conflicts: %s", exc, exc_info=True
+            )
+            return web.json_response(
+                {"success": False, "error": str(exc)}, status=500
+            )
+
    async def export_doctor_bundle(self, request: web.Request) -> web.Response:
        try:
            payload = await request.json()
@@ -846,6 +992,111 @@ class DoctorHandler:
            "actions": [{"id": "repair-cache", "label": "Rebuild Cache"}],
        }

+    async def _check_filename_conflicts(self) -> dict[str, Any]:
+        # When full path syntax is active, duplicate filenames across subfolders
+        # are not ambiguous (<lora:subfolder/name:strength>), so skip the check.
+        if self._settings.get("lora_syntax_format", "legacy") == "full":
+            return {
+                "id": "filename_conflicts",
+                "title": "Duplicate Filename Conflicts",
+                "status": "ok",
+                "summary": "Full path syntax is active — duplicate filenames across folders are not ambiguous.",
+                "details": [],
+                "actions": [],
+            }
+
+        all_conflicts: list[dict[str, Any]] = []
+        total_conflict_groups = 0
+        total_conflict_files = 0
+
+        for model_type, label, factory in self._scanner_factories:
+            # Duplicate filename detection targets LoRAs which use basename-only
+            # syntax (<lora:name:strength>). Checkpoints/embeddings reference
+            # models via relative paths with extensions, so conflicts there would
+            # be false positives.
+            if model_type != "lora":
+                continue
+            try:
+                scanner = await factory()
+                hash_index = getattr(scanner, "_hash_index", None)
+                if hash_index is None:
+                    continue
+                duplicates = hash_index.get_duplicate_filenames()
+                if not duplicates:
+                    continue
+
+                total_conflict_groups += len(duplicates)
+                for filename, paths in duplicates.items():
+                    total_conflict_files += len(paths)
+                    all_conflicts.append({
+                        "model_type": model_type,
+                        "label": label,
+                        "filename": filename,
+                        "paths": paths,
+                    })
+            except Exception as exc:  # pragma: no cover - defensive
+                logger.error(
+                    "Doctor filename conflict check failed for %s: %s",
+                    model_type,
+                    exc,
+                    exc_info=True,
+                )
+
+        if not all_conflicts:
+            return {
+                "id": "filename_conflicts",
+                "title": "Duplicate Filename Conflicts",
+                "status": "ok",
+                "summary": "No duplicate filenames found across model directories.",
+                "details": [],
+                "actions": [],
+            }
+
+        summary = (
+            f"{total_conflict_groups} filename(s) shared by "
+            f"{total_conflict_files} files across your library. "
+            f"This causes ambiguity when loading LoRAs by name."
+        )
+        details: list[str | dict[str, Any]] = [
+            {
+                "conflict_groups": total_conflict_groups,
+                "total_conflict_files": total_conflict_files,
+            }
+        ]
+
+        # Show at most 5 conflict groups inline; note any remainder.
+        MAX_VISIBLE_CONFLICTS = 5
+        visible_conflicts = all_conflicts[:MAX_VISIBLE_CONFLICTS]
+        for conflict in visible_conflicts:
+            details.append(
+                f"'{conflict['filename']}' "
+                f"found in {len(conflict['paths'])} locations"
+            )
+
+        hidden_count = len(all_conflicts) - MAX_VISIBLE_CONFLICTS
+        if hidden_count > 0:
+            details.append(
+                f"...and {hidden_count} more duplicate filename group(s)"
+            )
+
+        return {
+            "id": "filename_conflicts",
+            "title": "Duplicate Filename Conflicts",
+            "status": "warning",
+            "summary": summary,
+            "details": details,
+            "actions": [
+                {
+                    "id": "resolve-filename-conflicts",
+                    "label": "Resolve Conflicts",
+                },
+                {
+                    "id": "open-settings-syntax-format",
+                    "label": "Switch to Full Path Syntax",
+                },
+            ],
+        }
+
    def _check_ui_version(self, client_version: str, app_version: str) -> dict[str, Any]:
        if client_version and client_version != app_version:
            return {
@@ -1576,29 +1827,33 @@ class ModelLibraryHandler:
                    exists = True
                    model_type = "embedding"

+                if exists:
+                    return web.json_response(
+                        {
+                            "success": True,
+                            "exists": True,
+                            "modelType": model_type,
+                            "hasBeenDownloaded": False,
+                        }
+                    )
+
                history_service = await self._get_download_history_service()
                has_been_downloaded = False
-                history_type = model_type
-                if history_type:
-                    has_been_downloaded = await history_service.has_been_downloaded(
-                        history_type,
+                history_type = None
+                for candidate_type in ("lora", "checkpoint", "embedding"):
+                    if await history_service.has_been_downloaded(
+                        candidate_type,
                        model_version_id,
-                    )
-                else:
-                    for candidate_type in ("lora", "checkpoint", "embedding"):
-                        if await history_service.has_been_downloaded(
-                            candidate_type,
-                            model_version_id,
-                        ):
-                            has_been_downloaded = True
-                            history_type = candidate_type
-                            break
+                    ):
+                        has_been_downloaded = True
+                        history_type = candidate_type
+                        break

                return web.json_response(
                    {
                        "success": True,
-                        "exists": exists,
-                        "modelType": model_type if exists else history_type,
+                        "exists": False,
+                        "modelType": history_type,
                        "hasBeenDownloaded": has_been_downloaded,
                    }
                )
@@ -1618,40 +1873,46 @@ class ModelLibraryHandler:
            model_type = None
            versions = []
            downloaded_version_ids = []
-            history_service = await self._get_download_history_service()
            if lora_versions:
-                model_type = "lora"
-                versions = self._with_downloaded_flag(lora_versions)
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
-                    model_type,
-                    model_id,
+                return web.json_response(
+                    {
+                        "success": True,
+                        "modelType": "lora",
+                        "versions": self._with_downloaded_flag(lora_versions),
+                        "downloadedVersionIds": [],
+                    }
                )
-            elif checkpoint_versions:
-                model_type = "checkpoint"
-                versions = self._with_downloaded_flag(checkpoint_versions)
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
-                    model_type,
-                    model_id,
+            if checkpoint_versions:
+                return web.json_response(
+                    {
+                        "success": True,
+                        "modelType": "checkpoint",
+                        "versions": self._with_downloaded_flag(checkpoint_versions),
+                        "downloadedVersionIds": [],
+                    }
                )
-            elif embedding_versions:
-                model_type = "embedding"
-                versions = self._with_downloaded_flag(embedding_versions)
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
-                    model_type,
-                    model_id,
+            if embedding_versions:
+                return web.json_response(
+                    {
+                        "success": True,
+                        "modelType": "embedding",
+                        "versions": self._with_downloaded_flag(embedding_versions),
+                        "downloadedVersionIds": [],
+                    }
                )
-            else:
-                for candidate_type in ("lora", "checkpoint", "embedding"):
-                    candidate_downloaded_version_ids = (
-                        await history_service.get_downloaded_version_ids(
-                            candidate_type,
-                            model_id,
-                        )
+
+            history_service = await self._get_download_history_service()
+            for candidate_type in ("lora", "checkpoint", "embedding"):
+                candidate_downloaded_version_ids = (
+                    await history_service.get_downloaded_version_ids(
+                        candidate_type,
+                        model_id,
                    )
-                    if candidate_downloaded_version_ids:
-                        model_type = candidate_type
-                        downloaded_version_ids = candidate_downloaded_version_ids
-                        break
+                )
+                if candidate_downloaded_version_ids:
+                    model_type = candidate_type
+                    downloaded_version_ids = candidate_downloaded_version_ids
+                    break

            return web.json_response(
                {
@@ -1665,6 +1926,86 @@ class ModelLibraryHandler:
            logger.error("Failed to check model existence: %s", exc, exc_info=True)
            return web.json_response({"success": False, "error": str(exc)}, status=500)

+    async def check_models_exist(self, request: web.Request) -> web.Response:
+        try:
+            model_ids_raw = request.query.get("modelIds", "")
+            if not model_ids_raw:
+                return web.json_response(
+                    {"success": True, "results": []}
+                )
+
+            raw_ids = model_ids_raw.split(",")
+            seen: set[int] = set()
+            model_ids: list[int] = []
+            for raw in raw_ids:
+                stripped = raw.strip()
+                if not stripped:
+                    continue
+                try:
+                    mid = int(stripped)
+                except ValueError:
+                    continue
+                if mid not in seen:
+                    seen.add(mid)
+                    model_ids.append(mid)
+
+            if not model_ids:
+                return web.json_response(
+                    {"success": True, "results": []}
+                )
+
+            lora_scanner = await self._service_registry.get_lora_scanner()
+            checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
+            embedding_scanner = await self._service_registry.get_embedding_scanner()
+
+            results: list[dict] = []
+            for model_id in model_ids:
+                lora_versions = await lora_scanner.get_model_versions_by_id(model_id)
+                if lora_versions:
+                    results.append({
+                        "modelId": model_id,
+                        "modelType": "lora",
+                        "versions": self._with_downloaded_flag(lora_versions),
+                        "downloadedVersionIds": [],
+                    })
+                    continue
+
+                if checkpoint_scanner:
+                    checkpoint_versions = await checkpoint_scanner.get_model_versions_by_id(model_id)
+                    if checkpoint_versions:
+                        results.append({
+                            "modelId": model_id,
+                            "modelType": "checkpoint",
+                            "versions": self._with_downloaded_flag(checkpoint_versions),
+                            "downloadedVersionIds": [],
+                        })
+                        continue
+
+                if embedding_scanner:
+                    embedding_versions = await embedding_scanner.get_model_versions_by_id(model_id)
+                    if embedding_versions:
+                        results.append({
+                            "modelId": model_id,
+                            "modelType": "embedding",
+                            "versions": self._with_downloaded_flag(embedding_versions),
+                            "downloadedVersionIds": [],
+                        })
+                        continue
+
+                results.append({
+                    "modelId": model_id,
+                    "modelType": None,
+                    "versions": [],
+                    "downloadedVersionIds": [],
+                })
+
+            return web.json_response(
+                {"success": True, "results": results}
+            )
+        except Exception as exc:
+            logger.error("Failed to check models existence: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
    async def get_model_version_download_status(
        self, request: web.Request
    ) -> web.Response:
@@ -1759,7 +2100,7 @@ class ModelLibraryHandler:
                    file_path=file_path if isinstance(file_path, str) else None,
                )
            else:
-                await history_service.mark_not_downloaded(model_type, model_version_id)
+                await history_service.mark_as_deleted(model_type, model_version_id)

            return web.json_response(
                {
@@ -1777,6 +2118,89 @@ class ModelLibraryHandler:
            )
            return web.json_response({"success": False, "error": str(exc)}, status=500)

+    async def delete_model_version(self, request: web.Request) -> web.Response:
+        try:
+            model_version_id_str = request.query.get("modelVersionId")
+            if not model_version_id_str:
+                return web.json_response(
+                    {"success": False, "error": "Missing required parameter: modelVersionId"},
+                    status=400,
+                )
+            try:
+                model_version_id = int(model_version_id_str)
+            except ValueError:
+                return web.json_response(
+                    {"success": False, "error": "Parameter modelVersionId must be an integer"},
+                    status=400,
+                )
+
+            lora_scanner = await self._service_registry.get_lora_scanner()
+            checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
+            embedding_scanner = await self._service_registry.get_embedding_scanner()
+
+            found_type = None
+            file_path = None
+            found_cache = None
+
+            for model_type, scanner in (
+                ("lora", lora_scanner),
+                ("checkpoint", checkpoint_scanner),
+                ("embedding", embedding_scanner),
+            ):
+                cache = await scanner.get_cached_data()
+                if cache and model_version_id in cache.version_index:
+                    found_type = model_type
+                    found_cache = cache
+                    entry = cache.version_index[model_version_id]
+                    file_path = entry.get("file_path")
+                    break
+
+            if not file_path:
+                return web.json_response(
+                    {"success": False, "error": "Model version not found in any scanner cache"},
+                    status=404,
+                )
+
+            target_dir = os.path.dirname(file_path)
+            base_name = os.path.basename(file_path)
+            file_name, extension = os.path.splitext(base_name)
+            await delete_model_artifacts(target_dir, file_name, main_extension=extension)
+
+            if found_cache:
+                found_cache.raw_data = [
+                    item
+                    for item in found_cache.raw_data
+                    if item.get("file_path") != file_path
+                ]
+                await found_cache.resort()
+
+            scanner_map = {
+                "lora": lora_scanner,
+                "checkpoint": checkpoint_scanner,
+                "embedding": embedding_scanner,
+            }
+            scanner = scanner_map.get(found_type)
+            if scanner:
+                persist = getattr(scanner, "_persist_current_cache", None)
+                if callable(persist):
+                    await persist()
+
+            history_service = await self._get_download_history_service()
+            await history_service.mark_as_deleted(found_type, model_version_id)
+
+            return web.json_response(
+                {
+                    "success": True,
+                    "modelType": found_type,
+                    "modelVersionId": model_version_id,
+                }
+            )
+        except Exception as exc:
+            logger.error(
+                "Failed to delete model version: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
    async def get_model_versions_status(self, request: web.Request) -> web.Response:
        try:
            model_id_str = request.query.get("modelId")
@@ -2796,6 +3220,7 @@ class MiscHandlerSet:
            "update_settings": self.settings.update_settings,
            "get_doctor_diagnostics": self.doctor.get_doctor_diagnostics,
            "repair_doctor_cache": self.doctor.repair_doctor_cache,
+            "resolve_doctor_filename_conflicts": self.doctor.resolve_filename_conflicts,
            "export_doctor_bundle": self.doctor.export_doctor_bundle,
            "get_priority_tags": self.settings.get_priority_tags,
            "get_settings_libraries": self.settings.get_libraries,
@@ -2809,8 +3234,10 @@ class MiscHandlerSet:
            "update_node_widget": self.node_registry.update_node_widget,
            "get_registry": self.node_registry.get_registry,
            "check_model_exists": self.model_library.check_model_exists,
+            "check_models_exist": self.model_library.check_models_exist,
            "get_model_version_download_status": self.model_library.get_model_version_download_status,
            "set_model_version_download_status": self.model_library.set_model_version_download_status,
+            "delete_model_version": self.model_library.delete_model_version,
            "get_civitai_user_models": self.model_library.get_civitai_user_models,
            "download_metadata_archive": self.metadata_archive.download_metadata_archive,
            "remove_metadata_archive": self.metadata_archive.remove_metadata_archive,
--- a/py/routes/handlers/model_handlers.py
+++ b/py/routes/handlers/model_handlers.py
@@ -301,6 +301,15 @@ class ModelListingHandler:
        for tag in exclude_tags:
            if tag:
                tag_filters[tag] = "exclude"
+
+        auto_tag_filters: Dict[str, str] = {}
+        for tag in request.query.getall("auto_tag_include", []):
+            if tag:
+                auto_tag_filters[tag] = "include"
+        for tag in request.query.getall("auto_tag_exclude", []):
+            if tag:
+                auto_tag_filters[tag] = "exclude"
+
        favorites_only = request.query.get("favorites_only", "false").lower() == "true"

        search_options = {
@@ -367,6 +376,7 @@ class ModelListingHandler:
            "fuzzy_search": fuzzy_search,
            "base_models": base_models,
            "tags": tag_filters,
+            "auto_tags": auto_tag_filters,
            "tag_logic": tag_logic,
            "search_options": search_options,
            "hash_filters": hash_filters,
@@ -778,7 +788,7 @@ class ModelManagementHandler:

            metadata_updates = {k: v for k, v in data.items() if k != "file_path"}

-            await self._metadata_sync.save_metadata_updates(
+            updated_metadata = await self._metadata_sync.save_metadata_updates(
                file_path=file_path,
                updates=metadata_updates,
                metadata_loader=self._metadata_sync.load_local_metadata,
@@ -789,7 +799,12 @@ class ModelManagementHandler:
                cache = await self._service.scanner.get_cached_data()
                await cache.resort()

-            return web.json_response({"success": True})
+            from ...services.auto_tag_service import extract_auto_tags
+            auto_tags = extract_auto_tags(updated_metadata)
+
+            return web.json_response(
+                {"success": True, "auto_tags": auto_tags}
+            )
        except Exception as exc:
            self._logger.error("Error saving metadata: %s", exc, exc_info=True)
            return web.Response(text=str(exc), status=500)
@@ -806,14 +821,16 @@ class ModelManagementHandler:
            if not isinstance(new_tags, list):
                return web.Response(text="Tags must be a list", status=400)

-            tags = await self._tag_update_service.add_tags(
+            tags, auto_tags = await self._tag_update_service.add_tags(
                file_path=file_path,
                new_tags=new_tags,
                metadata_loader=self._metadata_sync.load_local_metadata,
                update_cache=self._service.scanner.update_single_model_cache,
            )

-            return web.json_response({"success": True, "tags": tags})
+            return web.json_response(
+                {"success": True, "tags": tags, "auto_tags": auto_tags}
+            )
        except Exception as exc:
            self._logger.error("Error adding tags: %s", exc, exc_info=True)
            return web.Response(text=str(exc), status=500)
@@ -1160,6 +1177,12 @@ class ModelQueryHandler:

    async def find_filename_conflicts(self, request: web.Request) -> web.Response:
        try:
+            settings = get_settings_manager()
+            if settings.get("lora_syntax_format", "legacy") == "full":
+                return web.json_response(
+                    {"success": True, "conflicts": [], "count": 0}
+                )
+
            duplicates = self._service.find_duplicate_filenames()
            result = []
            cache = await self._service.scanner.get_cached_data()
@@ -2423,6 +2446,7 @@ class ModelUpdateHandler:
            "shouldIgnore": version.should_ignore,
            "earlyAccessEndsAt": version.early_access_ends_at,
            "isEarlyAccess": is_early_access,
+            "usageControl": version.usage_control,
            "filePath": context.get("file_path"),
            "fileName": context.get("file_name"),
        }
--- a/py/routes/handlers/preview_handlers.py
+++ b/py/routes/handlers/preview_handlers.py
@@ -3,6 +3,7 @@
 from __future__ import annotations

 import logging
+import mimetypes
 import urllib.parse
 from pathlib import Path

@@ -12,6 +13,12 @@ from ...config import config as global_config

 logger = logging.getLogger(__name__)

+_CHUNK_SIZE = 256 * 1024  # 256 KB
+
+# Video file extensions that bypass native sendfile on Windows
+# to avoid IOCP/ProactorEventLoop crashes during client disconnect.
+_VIDEO_EXTENSIONS = frozenset({".mp4", ".webm", ".mov", ".avi", ".mkv"})
+

 class PreviewHandler:
    """Serve preview assets for the active library at request time."""
@@ -48,8 +55,51 @@ class PreviewHandler:
            logger.debug("Preview file not found at %s", str(resolved))
            raise web.HTTPNotFound(text="Preview file not found")

+        # Video files: stream manually to avoid Windows native sendfile crash.
+        # aiohttp's FileResponse uses _sendfile_native on Windows (IOCP-based),
+        # which breaks when the client disconnects mid-transfer — this happens
+        # constantly when users scroll through a gallery of animated previews.
+        suffix = resolved.suffix.lower()
+        if suffix in _VIDEO_EXTENSIONS:
+            return await self._stream_file(request, resolved)
+
        # aiohttp's FileResponse handles range requests and content headers for us.
-        return web.FileResponse(path=resolved, chunk_size=256 * 1024)
+        return web.FileResponse(path=resolved, chunk_size=_CHUNK_SIZE)
+
+    async def _stream_file(
+        self, request: web.Request, path: Path
+    ) -> web.StreamResponse:
+        """Stream a file chunk-by-chunk, bypassing native sendfile.
+
+        This avoids the Windows IOCP ``_sendfile_native`` crash that occurs
+        when the client disconnects during a large file transfer.
+        """
+        content_type, _ = mimetypes.guess_type(str(path))
+        if content_type is None:
+            content_type = "application/octet-stream"
+
+        file_size = path.stat().st_size
+        resp = web.StreamResponse()
+        resp.content_type = content_type
+        resp.content_length = file_size
+
+        await resp.prepare(request)
+
+        try:
+            with open(path, "rb") as f:
+                while True:
+                    chunk = f.read(_CHUNK_SIZE)
+                    if not chunk:
+                        break
+                    await resp.write(chunk)
+        except (ConnectionResetError, ConnectionAbortedError):
+            # Client disconnected during streaming — expected when scrolling
+            # rapidly through a library with animated previews.
+            pass
+        except OSError as exc:
+            logger.debug("I/O error streaming preview %s: %s", path, exc)
+
+        return resp


 __all__ = ["PreviewHandler"]
--- a/py/routes/handlers/recipe_handlers.py
+++ b/py/routes/handlers/recipe_handlers.py
@@ -87,12 +87,15 @@ class RecipeHandlerSet:
            "repair_recipes": self.management.repair_recipes,
            "cancel_repair": self.management.cancel_repair,
            "repair_recipe": self.management.repair_recipe,
+            "repair_recipes_bulk": self.management.repair_recipes_bulk,
            "get_repair_progress": self.management.get_repair_progress,
            "start_batch_import": self.batch_import.start_batch_import,
            "get_batch_import_progress": self.batch_import.get_batch_import_progress,
            "cancel_batch_import": self.batch_import.cancel_batch_import,
            "start_directory_import": self.batch_import.start_directory_import,
            "browse_directory": self.batch_import.browse_directory,
+            "check_image_exists": self.management.check_image_exists,
+            "import_from_url": self.management.import_from_url,
        }


@@ -541,7 +544,7 @@ class RecipeQueryHandler:
                    )
                    response_data.append(
                        {
-                            "type": "source_url",
+                            "type": "source_path",
                            "fingerprint": url,
                            "count": len(recipes),
                            "recipes": recipes,
@@ -607,6 +610,7 @@ class RecipeManagementHandler:
        self._downloader_factory = downloader_factory
        self._civitai_client_getter = civitai_client_getter
        self._ws_manager = ws_manager
+        self._import_semaphore = asyncio.Semaphore(2)

    async def save_recipe(self, request: web.Request) -> web.Response:
        try:
@@ -703,6 +707,69 @@ class RecipeManagementHandler:
            self._logger.error("Error cancelling recipe repair: %s", exc, exc_info=True)
            return web.json_response({"success": False, "error": str(exc)}, status=500)

+    async def repair_recipes_bulk(self, request: web.Request) -> web.Response:
+        """Bulk repair metadata for multiple recipes by their IDs.
+
+        Accepts a JSON body with a "recipe_ids" array and iterates
+        repair_recipe_by_id over each entry, collecting statistics.
+        """
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                return web.json_response(
+                    {"success": False, "error": "Recipe scanner unavailable"},
+                    status=503,
+                )
+
+            data = await request.json()
+            recipe_ids = data.get("recipe_ids", [])
+            if not recipe_ids:
+                return web.json_response(
+                    {"success": False, "error": "recipe_ids are required"},
+                    status=400,
+                )
+
+            total = len(recipe_ids)
+            repaired = 0
+            skipped = 0
+            errors = 0
+            recipes = []
+
+            for recipe_id in recipe_ids:
+                try:
+                    result = await recipe_scanner.repair_recipe_by_id(recipe_id)
+                    if result.get("success"):
+                        repaired += result.get("repaired", 0)
+                        skipped += result.get("skipped", 0)
+                        if result.get("recipe"):
+                            recipes.append(result["recipe"])
+                    else:
+                        errors += 1
+                except RecipeNotFoundError:
+                    skipped += 1
+                except Exception as exc:
+                    self._logger.error(
+                        "Error repairing recipe %s: %s", recipe_id, exc
+                    )
+                    errors += 1
+
+            return web.json_response({
+                "success": True,
+                "total": total,
+                "repaired": repaired,
+                "skipped": skipped,
+                "errors": errors,
+                "recipes": recipes,
+            })
+        except Exception as exc:
+            self._logger.error(
+                "Error performing bulk repair: %s", exc, exc_info=True
+            )
+            return web.json_response(
+                {"success": False, "error": str(exc)}, status=500
+            )
+
    async def repair_recipe(self, request: web.Request) -> web.Response:
        try:
            await self._ensure_dependencies_ready()
@@ -760,125 +827,28 @@ class RecipeManagementHandler:
            gen_params_request = self._parse_gen_params(params.get("gen_params"))

            self._logger.info(
-                "Remote recipe import received: url=%s, request_gen_params_keys=%s, lora_count=%d, checkpoint_keys=%s",
+                "Remote recipe import received: url=%s, lora_count=%d",
                image_url,
-                sorted(gen_params_request.keys()) if gen_params_request else [],
                len(lora_entries),
+            )
+            self._logger.debug(
+                "  gen_params_keys=%s, checkpoint_keys=%s",
+                sorted(gen_params_request.keys()) if gen_params_request else [],
                sorted(checkpoint_entry.keys()) if isinstance(checkpoint_entry, dict) else [],
            )

-            # 2. Initial Metadata Construction
-            metadata: Dict[str, Any] = {
-                "base_model": params.get("base_model", "") or "",
-                "loras": lora_entries,
-                "gen_params": gen_params_request or {},
-                "source_url": image_url,
-            }
-
-            source_path = params.get("source_path")
-            if source_path:
-                metadata["source_path"] = source_path
-
-            # Checkpoint handling
-            if checkpoint_entry:
-                metadata["checkpoint"] = checkpoint_entry
-                # Ensure checkpoint is also in gen_params for consistency if needed by enricher?
-                # Actually enricher looks at metadata['checkpoint'], so this is fine.
-
-                # Try to resolve base model from checkpoint if not explicitly provided
-                if not metadata["base_model"]:
-                    base_model_from_metadata = (
-                        await self._resolve_base_model_from_checkpoint(checkpoint_entry)
-                    )
-                    if base_model_from_metadata:
-                        metadata["base_model"] = base_model_from_metadata
-
-            tags = self._parse_tags(params.get("tags"))
-
-            # 3. Download Image
-            (
-                image_bytes,
-                extension,
-                civitai_meta_from_download,
-            ) = await self._download_remote_media(image_url)
-
-            # 4. Extract Embedded Metadata
-            # Note: We still extract this here because Enricher currently expects 'gen_params' to already be populated
-            # with embedded data if we want it to merge it.
-            # However, logic in Enricher merges: request > civitai > embedded.
-            # So we should gather embedded params and put them into the recipe's gen_params (as initial state)
-            # OR pass them to enricher to handle?
-            # The interface of Enricher.enrich_recipe takes `recipe` (with gen_params) and `request_params`.
-            # So let's extract embedded and put it into recipe['gen_params'] but careful not to overwrite request params.
-            # Actually, `GenParamsMerger` which `Enricher` uses handles 3 layers.
-            # But `Enricher` interface is: recipe['gen_params'] (as embedded) + request_params + civitai (fetched internally).
-            # Wait, `Enricher` fetches Civitai info internally based on URL.
-            # `civitai_meta_from_download` is returned by `_download_remote_media` which might be useful if URL didn't have ID.
-
-            # Let's extract embedded metadata first
-            embedded_gen_params = {}
-            try:
-                with tempfile.NamedTemporaryFile(
-                    suffix=extension, delete=False
-                ) as temp_img:
-                    temp_img.write(image_bytes)
-                    temp_img_path = temp_img.name
-
-                try:
-                    raw_embedded = ExifUtils.extract_image_metadata(temp_img_path)
-                    if raw_embedded:
-                        parser = (
-                            self._analysis_service._recipe_parser_factory.create_parser(
-                                raw_embedded
-                            )
-                        )
-                        if parser:
-                            parsed_embedded = await parser.parse_metadata(
-                                raw_embedded, recipe_scanner=recipe_scanner
-                            )
-                            if parsed_embedded and "gen_params" in parsed_embedded:
-                                embedded_gen_params = parsed_embedded["gen_params"]
-                        else:
-                            embedded_gen_params = {"raw_metadata": raw_embedded}
-                finally:
-                    if os.path.exists(temp_img_path):
-                        os.unlink(temp_img_path)
-            except Exception as exc:
-                self._logger.warning(
-                    "Failed to extract embedded metadata during import: %s", exc
+            # Throttle concurrent imports to avoid starving ComfyUI's event loop
+            async with self._import_semaphore:
+                return await self._do_import_remote_recipe(
+                    image_url=image_url,
+                    name=name,
+                    lora_entries=lora_entries,
+                    checkpoint_entry=checkpoint_entry,
+                    gen_params_request=gen_params_request,
+                    tags=self._parse_tags(params.get("tags")),
+                    base_model=params.get("base_model", "") or "",
+                    source_path=params.get("source_path") or image_url,
                )
-
-            # Pre-populate gen_params with embedded data so Enricher treats it as the "base" layer
-            if embedded_gen_params:
-                # Merge embedded into existing gen_params (which currently only has request params if any)
-                # But wait, we want request params to override everything.
-                # So we should set recipe['gen_params'] = embedded, and pass request params to enricher.
-                metadata["gen_params"] = embedded_gen_params
-
-            # 5. Enrich with unified logic
-            # This will fetch Civitai info (if URL matches) and merge: request > civitai > embedded
-            civitai_client = self._civitai_client_getter()
-            await RecipeEnricher.enrich_recipe(
-                recipe=metadata,
-                civitai_client=civitai_client,
-                request_params=gen_params_request,  # Pass explicit request params here to override
-            )
-
-            # If we got civitai_meta from download but Enricher didn't fetch it (e.g. not a civitai URL or failed),
-            # we might want to manually merge it?
-            # But usually `import_remote_recipe` is used with Civitai URLs.
-            # For now, relying on Enricher's internal fetch is consistent with repair.
-
-            result = await self._persistence_service.save_recipe(
-                recipe_scanner=recipe_scanner,
-                image_bytes=image_bytes,
-                image_base64=None,
-                name=name,
-                tags=tags,
-                metadata=metadata,
-                extension=extension,
-            )
-            return web.json_response(result.payload, status=result.status)
        except RecipeValidationError as exc:
            return web.json_response({"error": str(exc)}, status=400)
        except RecipeDownloadError as exc:
@@ -889,6 +859,150 @@ class RecipeManagementHandler:
            )
            return web.json_response({"error": str(exc)}, status=500)

+    async def _do_import_remote_recipe(
+        self,
+        *,
+        image_url: str,
+        name: str,
+        lora_entries: list,
+        checkpoint_entry: dict,
+        gen_params_request: dict,
+        tags: list,
+        base_model: str,
+        source_path: str,
+    ) -> web.Response:
+        recipe_scanner = self._recipe_scanner_getter()
+        if recipe_scanner is None:
+            raise RuntimeError("Recipe scanner unavailable")
+
+        metadata: Dict[str, Any] = {
+            "base_model": base_model,
+            "loras": lora_entries,
+            "gen_params": gen_params_request or {},
+            "source_path": source_path,
+        }
+
+        if checkpoint_entry:
+            metadata["checkpoint"] = checkpoint_entry
+            if not metadata["base_model"]:
+                base_model_from_metadata = (
+                    await self._resolve_base_model_from_checkpoint(checkpoint_entry)
+                )
+                if base_model_from_metadata:
+                    metadata["base_model"] = base_model_from_metadata
+
+        # Download image
+        (
+            image_bytes,
+            extension,
+            civitai_meta_raw,
+            model_version_id,
+        ) = await self._download_remote_media(image_url)
+
+        # Extract embedded EXIF metadata (offloaded to thread pool in this call)
+        embedded_gen_params = {}
+        parsed_embedded = None
+        try:
+            with tempfile.NamedTemporaryFile(
+                suffix=extension, delete=False
+            ) as temp_img:
+                temp_img.write(image_bytes)
+                temp_img_path = temp_img.name
+
+            try:
+                raw_embedded = await asyncio.to_thread(
+                    ExifUtils.extract_image_metadata, temp_img_path
+                )
+                if raw_embedded:
+                    parser = (
+                        self._analysis_service._recipe_parser_factory.create_parser(
+                            raw_embedded
+                        )
+                    )
+                    if parser:
+                        parsed_embedded = await parser.parse_metadata(
+                            raw_embedded, recipe_scanner=recipe_scanner
+                        )
+                        if parsed_embedded and "gen_params" in parsed_embedded:
+                            embedded_gen_params = parsed_embedded["gen_params"]
+                    else:
+                        embedded_gen_params = {"raw_metadata": raw_embedded}
+            finally:
+                if os.path.exists(temp_img_path):
+                    os.unlink(temp_img_path)
+        except Exception as exc:
+            self._logger.warning(
+                "Failed to extract embedded metadata during import: %s", exc
+            )
+
+        # Parse CivitAI API meta to discover all resources from modelVersionIds
+        # (modelVersionIds is injected at root level by _download_remote_media).
+        # Run unconditionally — EXIF parsing may succeed for gen_params but miss
+        # LoRAs since modelVersionIds is NOT embedded in the image EXIF.
+        civitai_parsed = None
+        if civitai_meta_raw:
+            civitai_inner_meta = civitai_meta_raw
+            if isinstance(civitai_meta_raw, dict) and "meta" in civitai_meta_raw:
+                civitai_inner_meta = civitai_meta_raw["meta"]
+                # modelVersionIds lives at outer meta level; propagate after unwrap
+                _mvids = civitai_meta_raw.get("modelVersionIds")
+                if _mvids and isinstance(civitai_inner_meta, dict):
+                    civitai_inner_meta["modelVersionIds"] = _mvids
+            if isinstance(civitai_inner_meta, dict):
+                parser = self._analysis_service._recipe_parser_factory.create_parser(
+                    civitai_inner_meta
+                )
+                if parser:
+                    civitai_parsed = await parser.parse_metadata(
+                        civitai_inner_meta, recipe_scanner=recipe_scanner
+                    )
+                    if civitai_parsed and "gen_params" in civitai_parsed:
+                        # Merge: API gen_params override EXIF at field level,
+                        # EXIF fills in fields the API doesn't have.
+                        embedded_gen_params = {
+                            **(embedded_gen_params or {}),
+                            **civitai_parsed["gen_params"],
+                        }
+
+        if embedded_gen_params:
+            metadata["gen_params"] = embedded_gen_params
+
+        # Merge LoRAs: prefer frontend resources, supplement with CivitAI modelVersionIds
+        if civitai_parsed:
+            civitai_loras = civitai_parsed.get("loras", [])
+            if civitai_loras and not metadata.get("loras"):
+                metadata["loras"] = civitai_loras
+            civitai_model = civitai_parsed.get("model")
+            if civitai_model and not metadata.get("checkpoint"):
+                metadata["checkpoint"] = civitai_model
+        elif parsed_embedded:
+            parsed_loras = parsed_embedded.get("loras")
+            if parsed_loras and not metadata.get("loras"):
+                metadata["loras"] = parsed_loras
+            parsed_model = parsed_embedded.get("model")
+            if parsed_model and not metadata.get("checkpoint"):
+                metadata["checkpoint"] = parsed_model
+
+        civitai_client = self._civitai_client_getter()
+        await RecipeEnricher.enrich_recipe(
+            recipe=metadata,
+            civitai_client=civitai_client,
+            request_params=gen_params_request,
+            prefetched_civitai_meta_raw=civitai_meta_raw,
+            prefetched_model_version_id=model_version_id,
+        )
+
+        result = await self._persistence_service.save_recipe(
+            recipe_scanner=recipe_scanner,
+            image_bytes=image_bytes,
+            image_base64=None,
+            name=name,
+            tags=tags,
+            metadata=metadata,
+            extension=extension,
+        )
+        return web.json_response(result.payload, status=result.status)
+
    async def delete_recipe(self, request: web.Request) -> web.Response:
        try:
            await self._ensure_dependencies_ready()
@@ -1190,7 +1304,7 @@ class RecipeManagementHandler:
            "exclude": False,
        }

-    async def _download_remote_media(self, image_url: str) -> tuple[bytes, str, Any]:
+    async def _download_remote_media(self, image_url: str) -> tuple[bytes, str, Any, Any]:
        civitai_client = self._civitai_client_getter()
        downloader = await self._downloader_factory()
        temp_path = None
@@ -1238,10 +1352,38 @@ class RecipeManagementHandler:
                extension = ".webp"  # Default to webp if unknown

            with open(temp_path, "rb") as file_obj:
+                model_ver_id = None
+                civitai_meta_raw = (
+                    image_info.get("meta") if civitai_image_id and image_info else None
+                )
+                if civitai_image_id and image_info:
+                    # modelVersionId (singular) — the primary version for this
+                    # image on CivitAI.  May be absent, or may *not* be the
+                    # checkpoint (e.g. when the image was generated with a LoRA
+                    # as the primary subject).  When absent, DO NOT fall back to
+                    # modelVersionIds[0] — that array mixes checkpoints, LoRAs,
+                    # and other model version IDs without ordering guarantees.
+                    # The downstream enrichment flow will find the real
+                    # checkpoint via meta.resources (type:"model" hash) or
+                    # meta.civitaiResources (type:"checkpoint" version ID), so
+                    # leaving model_ver_id as None is safe and avoids the bug
+                    # where a LoRA version ID was treated as the checkpoint.
+                    model_ver_id = image_info.get("modelVersionId")
+
+                    # Inject root-level modelVersionIds into meta so downstream
+                    # parsers (CivitaiApiMetadataParser) can discover ALL resources
+                    # (checkpoint + LoRAs), not just the first model version ID.
+                    # CivitAI API returns modelVersionIds at the root level of
+                    # the image response, NOT inside the meta object.
+                    mvids = image_info.get("modelVersionIds")
+                    if mvids and isinstance(civitai_meta_raw, dict):
+                        civitai_meta_raw["modelVersionIds"] = mvids
+
                return (
                    file_obj.read(),
                    extension,
-                    image_info.get("meta") if civitai_image_id and image_info else None,
+                    civitai_meta_raw,
+                    model_ver_id,
                )
        except RecipeDownloadError:
            raise
@@ -1289,6 +1431,226 @@ class RecipeManagementHandler:

        return ""

+    async def check_image_exists(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            image_ids_raw = request.query.get("image_ids", "")
+            if not image_ids_raw:
+                return web.json_response({"success": True, "results": {}})
+
+            requested_ids = set()
+            for raw in image_ids_raw.split(","):
+                stripped = raw.strip()
+                if stripped and stripped.isdigit():
+                    requested_ids.add(stripped)
+
+            if not requested_ids:
+                return web.json_response({"success": True, "results": {}})
+
+            cache = await recipe_scanner.get_cached_data()
+
+            # Build lookup: image_id -> recipe_id from stored source_path
+            image_to_recipe = {}
+            for recipe in getattr(cache, "raw_data", []):
+                source = recipe.get("source_path")
+                if not source:
+                    continue
+                image_id = extract_civitai_image_id(source)
+                if image_id and image_id not in image_to_recipe:
+                    image_to_recipe[image_id] = recipe.get("id")
+
+            results = {}
+            for img_id in requested_ids:
+                recipe_id = image_to_recipe.get(img_id)
+                results[img_id] = {
+                    "in_library": recipe_id is not None,
+                    "recipe_id": recipe_id,
+                }
+
+            return web.json_response({"success": True, "results": results})
+        except Exception as exc:
+            self._logger.error(
+                "Error checking image existence: %s", exc, exc_info=True
+            )
+            return web.json_response({"error": str(exc)}, status=500)
+
+    async def import_from_url(self, request: web.Request) -> web.Response:
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            image_url = request.query.get("image_url")
+            if not image_url:
+                raise RecipeValidationError("Missing required field: image_url")
+
+            image_id = extract_civitai_image_id(image_url)
+            if not image_id:
+                raise RecipeValidationError(
+                    "Could not extract Civitai image ID from URL"
+                )
+
+            # Check for duplicate (fast, before acquiring semaphore)
+            cache = await recipe_scanner.get_cached_data()
+            for recipe in getattr(cache, "raw_data", []):
+                source = recipe.get("source_path")
+                if source:
+                    existing_id = extract_civitai_image_id(source)
+                    if existing_id == image_id:
+                        return web.json_response({
+                            "success": True,
+                            "recipe_id": recipe.get("id"),
+                            "name": recipe.get("title", ""),
+                            "already_exists": True,
+                        })
+
+            async with self._import_semaphore:
+                return await self._do_import_from_url(image_url, recipe_scanner)
+        except RecipeValidationError as exc:
+            return web.json_response({"error": str(exc)}, status=400)
+        except RecipeDownloadError as exc:
+            return web.json_response({"error": str(exc)}, status=400)
+        except Exception as exc:
+            self._logger.error(
+                "Error importing recipe from URL: %s", exc, exc_info=True
+            )
+            return web.json_response({"error": str(exc)}, status=500)
+
+    async def _do_import_from_url(
+        self,
+        image_url: str,
+        recipe_scanner: Any,
+    ) -> web.Response:
+        image_id = extract_civitai_image_id(image_url)
+        if not image_id:
+            raise RecipeValidationError(
+                "Could not extract Civitai image ID from URL"
+            )
+
+        image_bytes, extension, civitai_meta_raw, model_version_id = (
+            await self._download_remote_media(image_url)
+        )
+
+        # Extract embedded EXIF metadata
+        embedded_gen_params = {}
+        parsed_embedded = None
+        try:
+            with tempfile.NamedTemporaryFile(
+                suffix=extension, delete=False
+            ) as temp_img:
+                temp_img.write(image_bytes)
+                temp_img_path = temp_img.name
+
+            try:
+                raw_embedded = await asyncio.to_thread(
+                    ExifUtils.extract_image_metadata, temp_img_path
+                )
+                if raw_embedded:
+                    parser = (
+                        self._analysis_service._recipe_parser_factory.create_parser(
+                            raw_embedded
+                        )
+                    )
+                    if parser:
+                        parsed_embedded = await parser.parse_metadata(
+                            raw_embedded, recipe_scanner=recipe_scanner
+                        )
+                        if parsed_embedded and "gen_params" in parsed_embedded:
+                            embedded_gen_params = parsed_embedded["gen_params"]
+            finally:
+                if os.path.exists(temp_img_path):
+                    os.unlink(temp_img_path)
+        except Exception as exc:
+            self._logger.warning(
+                "Failed to extract embedded metadata: %s", exc
+            )
+
+        # Parse CivitAI API meta to discover all resources from modelVersionIds.
+        # Run unconditionally — EXIF parsing succeeds for gen_params but misses
+        # LoRAs (modelVersionIds is NOT in the image EXIF).
+        civitai_parsed = None
+        if civitai_meta_raw:
+            civitai_inner_meta = civitai_meta_raw
+            if isinstance(civitai_meta_raw, dict) and "meta" in civitai_meta_raw:
+                civitai_inner_meta = civitai_meta_raw["meta"]
+                # Propagate modelVersionIds into unwrapped meta — it lives
+                # at the outer meta level in the CivitAI API response.
+                _mvids = civitai_meta_raw.get("modelVersionIds")
+                if _mvids and isinstance(civitai_inner_meta, dict):
+                    civitai_inner_meta["modelVersionIds"] = _mvids
+            if isinstance(civitai_inner_meta, dict):
+                parser = self._analysis_service._recipe_parser_factory.create_parser(
+                    civitai_inner_meta
+                )
+                if parser:
+                    civitai_parsed = await parser.parse_metadata(
+                        civitai_inner_meta, recipe_scanner=recipe_scanner
+                    )
+                    if civitai_parsed and "gen_params" in civitai_parsed:
+                        # Merge: API gen_params override EXIF at field level,
+                        # EXIF fills in fields the API doesn't have.
+                        embedded_gen_params = {
+                            **(embedded_gen_params or {}),
+                            **civitai_parsed["gen_params"],
+                        }
+
+        metadata: Dict[str, Any] = {
+            "base_model": "",
+            "loras": [],
+            "gen_params": embedded_gen_params or {},
+            "source_path": image_url,
+        }
+
+        if civitai_parsed:
+            civitai_loras = civitai_parsed.get("loras", [])
+            if civitai_loras and not metadata.get("loras"):
+                metadata["loras"] = civitai_loras
+            civitai_model = civitai_parsed.get("model")
+            if civitai_model and not metadata.get("checkpoint"):
+                metadata["checkpoint"] = civitai_model
+        elif parsed_embedded:
+            parsed_loras = parsed_embedded.get("loras")
+            if parsed_loras and not metadata.get("loras"):
+                metadata["loras"] = parsed_loras
+            parsed_model = parsed_embedded.get("model")
+            if parsed_model and not metadata.get("checkpoint"):
+                metadata["checkpoint"] = parsed_model
+
+        civitai_client = self._civitai_client_getter()
+        await RecipeEnricher.enrich_recipe(
+            recipe=metadata,
+            civitai_client=civitai_client,
+            request_params={},
+            prefetched_civitai_meta_raw=civitai_meta_raw,
+            prefetched_model_version_id=model_version_id,
+        )
+
+        prompt = (
+            metadata.get("gen_params", {}).get("prompt")
+            or metadata.get("gen_params", {}).get("positivePrompt")
+            or ""
+        )
+        if prompt:
+            name = " ".join(str(prompt).split()[:10])
+        else:
+            name = f"Civitai Image {image_id}"
+
+        result = await self._persistence_service.save_recipe(
+            recipe_scanner=recipe_scanner,
+            image_bytes=image_bytes,
+            image_base64=None,
+            name=name,
+            tags=[],
+            metadata=metadata,
+            extension=extension,
+        )
+        return web.json_response(result.payload, status=result.status)
+

 class RecipeAnalysisHandler:
    """Analyze images to extract recipe metadata."""
--- a/py/routes/misc_route_registrar.py
+++ b/py/routes/misc_route_registrar.py
@@ -24,6 +24,7 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
    RouteDefinition("POST", "/api/lm/settings", "update_settings"),
    RouteDefinition("GET", "/api/lm/doctor/diagnostics", "get_doctor_diagnostics"),
    RouteDefinition("POST", "/api/lm/doctor/repair-cache", "repair_doctor_cache"),
+    RouteDefinition("POST", "/api/lm/doctor/resolve-filename-conflicts", "resolve_doctor_filename_conflicts"),
    RouteDefinition("POST", "/api/lm/doctor/export-bundle", "export_doctor_bundle"),
    RouteDefinition("GET", "/api/lm/priority-tags", "get_priority_tags"),
    RouteDefinition("GET", "/api/lm/settings/libraries", "get_settings_libraries"),
@@ -42,6 +43,7 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
    RouteDefinition("POST", "/api/lm/update-node-widget", "update_node_widget"),
    RouteDefinition("GET", "/api/lm/get-registry", "get_registry"),
    RouteDefinition("GET", "/api/lm/check-model-exists", "check_model_exists"),
+    RouteDefinition("GET", "/api/lm/check-models-exist", "check_models_exist"),
    RouteDefinition(
        "GET",
        "/api/lm/model-version-download-status",
@@ -89,6 +91,9 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
    RouteDefinition(
        "GET", "/api/lm/base-models/cache-status", "get_base_model_cache_status"
    ),
+    RouteDefinition(
+        "GET", "/api/lm/delete-model-version", "delete_model_version"
+    ),
 )


--- a/py/routes/recipe_route_registrar.py
+++ b/py/routes/recipe_route_registrar.py
@@ -58,6 +58,7 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
    RouteDefinition("POST", "/api/lm/recipes/repair", "repair_recipes"),
    RouteDefinition("POST", "/api/lm/recipes/cancel-repair", "cancel_repair"),
    RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
+    RouteDefinition("POST", "/api/lm/recipes/repair-bulk", "repair_recipes_bulk"),
    RouteDefinition("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
    RouteDefinition("POST", "/api/lm/recipes/batch-import/start", "start_batch_import"),
    RouteDefinition(
@@ -70,6 +71,10 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
        "POST", "/api/lm/recipes/batch-import/directory", "start_directory_import"
    ),
    RouteDefinition("POST", "/api/lm/recipes/browse-directory", "browse_directory"),
+    RouteDefinition(
+        "GET", "/api/lm/recipes/check-image-exists", "check_image_exists"
+    ),
+    RouteDefinition("GET", "/api/lm/recipes/import-from-url", "import_from_url"),
 )


--- a/py/services/aria2_downloader.py
+++ b/py/services/aria2_downloader.py
@@ -39,7 +39,7 @@ class Aria2Transfer:


 class Aria2Downloader:
-    """Manage an aria2 RPC daemon for experimental model downloads."""
+    """Manage an aria2 RPC daemon for recommended model downloads."""

    _instance = None
    _lock = asyncio.Lock()
--- a/py/services/auto_tag_service.py
+++ b/py/services/auto_tag_service.py
@@ -0,0 +1,139 @@
+"""
+Auto-tag extraction service for model cards.
+
+Extracts implicit model attributes (HIGH/LOW, I2V/T2V/TI2V, Lightning, Turbo)
+from filename, base_model, and CivitAI version name — no manual tagging required.
+"""
+
+from __future__ import annotations
+
+import re
+from typing import Dict, List, Set
+
+# ── Tag category definitions ──────────────────────────────────────────
+# Each category maps a display label to a regex pattern.
+# Patterns are case-insensitive and matched against filename, base_model,
+# and civitai version name.
+
+# Use (?<![a-zA-Z0-9]) and (?![a-zA-Z0-9]) instead of \b because
+# Python's \b treats underscore as a word character, so \bHIGH\b
+# won't match '_HIGH_' in filenames.
+_B = r"(?<![a-zA-Z0-9])"   # left boundary
+_E = r"(?![a-zA-Z0-9])"    # right boundary
+
+AUTO_TAG_CATEGORIES: Dict[str, str] = {
+    "HIGH":      _B + r"HIGH" + _E,
+    "LOW":       _B + r"(?<!F)LOW" + _E,
+    "I2V":       _B + r"I2V" + _E,
+    "T2V":       _B + r"T2V" + _E,
+    "TI2V":      _B + r"TI2V" + _E,
+    "Lightning": _B + r"Lightning" + _E,
+    "Turbo":     _B + r"Turbo" + _E,
+}
+
+# Tags that belong to the "mode" group (HIGH/LOW)
+MODE_TAGS = {"HIGH", "LOW"}
+
+# Tags that belong to the "video mode" group (I2V/T2V/TI2V)
+VIDEO_MODE_TAGS = {"I2V", "T2V", "TI2V"}
+
+# Tags that belong to the "speed/optimization" group
+SPEED_TAGS = {"Lightning", "Turbo"}
+
+# ── Display category groups (for settings UI) ─────────────────────────
+
+AUTO_TAG_GROUPS = {
+    "mode":   {"HIGH", "LOW"},
+    "video":  {"I2V", "T2V", "TI2V"},
+    "speed":  {"Lightning", "Turbo"},
+}
+
+# Default enabled categories
+DEFAULT_ENABLED_GROUPS = {"mode", "video"}
+
+
+def _collect_sources(model_data: Dict) -> List[str]:
+    """Collect all text sources from model data for tag matching."""
+    sources: List[str] = []
+
+    file_name = model_data.get("file_name", "")
+    if file_name:
+        sources.append(file_name)
+
+    base_model = model_data.get("base_model", "")
+    if base_model:
+        sources.append(base_model)
+
+    civitai = model_data.get("civitai", {})
+    if isinstance(civitai, dict):
+        version_name = civitai.get("name", "")
+        if version_name:
+            sources.append(version_name)
+
+    return sources
+
+
+def extract_auto_tags(model_data: Dict) -> List[str]:
+    """Extract auto-detected tags from model metadata.
+
+    Uses a two-layer approach:
+      Layer 1 — Regex-based detection against filename, base_model, and
+                CivitAI version name.
+      Layer 2 — Merge in any user-defined tags that overlap with known
+                auto-tag categories. This provides a manual fallback when
+                auto-detection fails (e.g. "I2V HN" or unlabeled models).
+
+    HIGH/LOW tags are only returned when the base_model indicates a Wan
+    family model — no other model architecture uses this distinction.
+
+    Args:
+        model_data: Model metadata dict with keys:
+            file_name, base_model, civitai (with optional 'name' field),
+            tags (user-defined tag list, used as fallback).
+
+    Returns:
+        Sorted list of unique auto-tag strings (e.g. ["I2V"]).
+    """
+    sources = _collect_sources(model_data)
+    base_model = model_data.get("base_model", "")
+    is_wan = "wan" in base_model.lower()
+
+    found: Set[str] = set()
+
+    # ── Layer 1: regex-based detection ────────────────────────────
+    if sources:
+        for label, pattern in AUTO_TAG_CATEGORIES.items():
+            # HIGH/LOW are Wan-specific — skip for non-Wan to avoid noise
+            if label in ("HIGH", "LOW"):
+                if not is_wan:
+                    continue
+                # Use case-insensitive character class + case-sensitive boundary,
+                # so "HighNoise" (camelCase) matches but "highlight" doesn't.
+                # Boundary: not followed by lowercase letter (= word has ended).
+                ci = "".join(f"[{c.lower()}{c.upper()}]" for c in label)
+                if label == "LOW":
+                    regex = re.compile(r"(?<![Ff])" + ci + r"(?![a-z])")
+                else:
+                    regex = re.compile(ci + r"(?![a-z])")
+            else:
+                regex = re.compile(pattern, re.IGNORECASE)
+            for source in sources:
+                if regex.search(source):
+                    found.add(label)
+                    break
+
+    # ── Layer 2: user-defined tags as manual fallback ─────────────
+    # When auto-detection fails (abbreviated names like "Hi"/"Lo",
+    # "I2V HN", or unlabeled models), users can add canonical tags
+    # (HIGH, LOW, I2V, etc.) to the model's regular tags for correct
+    # badge display and filtering. Matching is case-insensitive so
+    # "high"/"High"/"HIGH" all resolve to the canonical label.
+    user_tags = model_data.get("tags")
+    if user_tags:
+        label_map = {label.lower(): label for label in AUTO_TAG_CATEGORIES}
+        for t in user_tags:
+            canonical = label_map.get(t.lower())
+            if canonical:
+                found.add(canonical)
+
+    return sorted(found)
--- a/py/services/base_model_service.py
+++ b/py/services/base_model_service.py
@@ -77,6 +77,7 @@ class BaseModelService(ABC):
        base_models: list = None,
        model_types: list = None,
        tags: Optional[Dict[str, str]] = None,
+        auto_tags: Optional[Dict[str, str]] = None,
        search_options: dict = None,
        hash_filters: dict = None,
        favorites_only: bool = False,
@@ -95,6 +96,11 @@ class BaseModelService(ABC):
            sorted_data = await self._fetch_with_usage_sort(sort_params)
        else:
            sorted_data = await self.cache_repository.fetch_sorted(sort_params)
+        # Pre-compute auto_tags for every item — needed for both filtering
+        # and display. Computation is cheap (string regex on 2-3 fields).
+        from .auto_tag_service import extract_auto_tags
+        for item in sorted_data:
+            item["auto_tags"] = extract_auto_tags(item)
        fetch_duration = time.perf_counter() - t0
        initial_count = len(sorted_data)

@@ -110,6 +116,7 @@ class BaseModelService(ABC):
                base_models=base_models,
                model_types=model_types,
                tags=tags,
+                auto_tags=auto_tags,
                favorites_only=favorites_only,
                search_options=search_options,
                tag_logic=tag_logic,
@@ -354,6 +361,7 @@ class BaseModelService(ABC):
        base_models: list = None,
        model_types: list = None,
        tags: Optional[Dict[str, str]] = None,
+        auto_tags: Optional[Dict[str, str]] = None,
        favorites_only: bool = False,
        search_options: dict = None,
        tag_logic: str = "any",
@@ -367,6 +375,7 @@ class BaseModelService(ABC):
            base_models=base_models,
            model_types=model_types,
            tags=tags,
+            auto_tags=auto_tags,
            favorites_only=favorites_only,
            search_options=normalized_options,
            tag_logic=tag_logic,
@@ -861,22 +870,75 @@ class BaseModelService(ABC):
        """Get the static preview URL for a model file"""
        cache = await self.scanner.get_cached_data()

+        name_normalized = model_name.replace("\\", "/")
+        name_no_ext = name_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if name_no_ext.lower().endswith(ext):
+                name_no_ext = name_no_ext[: -len(ext)]
+                break
+
+        has_path = "/" in name_no_ext
+        basename = os.path.basename(name_no_ext) if has_path else name_no_ext
+        best_fallback = None
+
        for model in cache.raw_data:
-            if model["file_name"] == model_name:
+            file_name = model.get("file_name", "")
+            folder = model.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+            if name_no_ext == file_name_no_ext or name_no_ext == path_name:
                preview_url = model.get("preview_url")
                if preview_url:
                    from ..config import config

                    return config.get_preview_static_url(preview_url)

+            if has_path and file_name_no_ext == basename:
+                if folder and name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                    best_fallback = model
+                elif best_fallback is None:
+                    best_fallback = model
+
+        if best_fallback:
+            preview_url = best_fallback.get("preview_url")
+            if preview_url:
+                from ..config import config
+
+                return config.get_preview_static_url(preview_url)
+
        return "/loras_static/images/no-preview.png"

    async def get_model_civitai_url(self, model_name: str) -> Dict[str, Optional[str]]:
        """Get the Civitai URL for a model file"""
        cache = await self.scanner.get_cached_data()

+        name_normalized = model_name.replace("\\", "/")
+        name_no_ext = name_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if name_no_ext.lower().endswith(ext):
+                name_no_ext = name_no_ext[: -len(ext)]
+                break
+
+        has_path = "/" in name_no_ext
+        basename = os.path.basename(name_no_ext) if has_path else name_no_ext
+        best_fallback = None
+
        for model in cache.raw_data:
-            if model["file_name"] == model_name:
+            file_name = model.get("file_name", "")
+            folder = model.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+            if name_no_ext == file_name_no_ext or name_no_ext == path_name:
                civitai_data = model.get("civitai", {})
                model_id = civitai_data.get("modelId")
                version_id = civitai_data.get("id")
@@ -895,6 +957,27 @@ class BaseModelService(ABC):
                        "version_id": str(version_id) if version_id else None,
                    }

+            if has_path and file_name_no_ext == basename:
+                if folder and name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                    best_fallback = model
+                elif best_fallback is None:
+                    best_fallback = model
+
+        if best_fallback:
+            civitai_data = best_fallback.get("civitai", {})
+            model_id = civitai_data.get("modelId")
+            if model_id:
+                version_id = civitai_data.get("id")
+                civitai_host = self.settings.get("civitai_host", "civitai.com")
+                civitai_url = build_civitai_model_page_url(
+                    model_id, version_id, host=civitai_host
+                )
+                return {
+                    "civitai_url": civitai_url,
+                    "model_id": str(model_id),
+                    "version_id": str(version_id) if version_id else None,
+                }
+
        return {"civitai_url": None, "model_id": None, "version_id": None}

    async def get_model_metadata(self, file_path: str) -> Optional[Dict]:
@@ -908,6 +991,17 @@ class BaseModelService(ABC):
        )
        if should_skip or metadata is None:
            return None
+
+        # Prune stale example-image metadata entries whose files no longer
+        # exist on disk (e.g. a user deleted the files manually).
+        from ..utils.example_images_metadata import MetadataUpdater
+
+        was_modified = await MetadataUpdater.prune_stale_example_images(metadata)
+        if was_modified:
+            asyncio.create_task(
+                MetadataManager.save_metadata(file_path, metadata)
+            )
+
        return self.filter_civitai_data(metadata.to_dict().get("civitai", {}))

    async def get_model_description(self, file_path: str) -> Optional[str]:
--- a/py/services/batch_import_service.py
+++ b/py/services/batch_import_service.py
@@ -224,7 +224,7 @@ class BatchImportService:
                return False

            for recipe in getattr(cache, "raw_data", []):
-                source_path = recipe.get("source_path") or recipe.get("source_url")
+                source_path = recipe.get("source_path")
                if source_path and source_path == source:
                    return True
            return False
--- a/py/services/checkpoint_service.py
+++ b/py/services/checkpoint_service.py
@@ -3,6 +3,7 @@ import logging
 from typing import Dict

 from .base_model_service import BaseModelService
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import CheckpointMetadata
 from ..config import config

@@ -45,7 +46,8 @@ class CheckpointService(BaseModelService):
            "exclude": bool(checkpoint_data.get("exclude", False)),
            "update_available": bool(checkpoint_data.get("update_available", False)),
            "skip_metadata_refresh": bool(checkpoint_data.get("skip_metadata_refresh", False)),
-            "civitai": self.filter_civitai_data(checkpoint_data.get("civitai", {}), minimal=True)
+            "civitai": self.filter_civitai_data(checkpoint_data.get("civitai", {}), minimal=True),
+            "auto_tags": checkpoint_data.get("auto_tags") or extract_auto_tags(checkpoint_data),
        }
    
    def find_duplicate_hashes(self) -> Dict:
--- a/py/services/civitai_base_model_service.py
+++ b/py/services/civitai_base_model_service.py
@@ -193,6 +193,9 @@ class CivitaiBaseModelService:
            "zimageturbo": "ZIT",
            "zimagebase": "ZIB",
            "anima": "ANI",
+            "ernie": "ERNI",
+            "ernie turbo": "ETRB",
+            "nucleus": "NUCL",
            "svd": "SVD",
            "ltxv": "LTXV",
            "ltxv2": "LTV2",
@@ -418,6 +421,9 @@ class CivitaiBaseModelService:
                "Kolors",
                "NoobAI",
                "Anima",
+                "Ernie",
+                "Ernie Turbo",
+                "Nucleus",
            ],
        }

--- a/py/services/civitai_client.py
+++ b/py/services/civitai_client.py
@@ -2,6 +2,7 @@ import asyncio
 import copy
 import logging
 import os
+from collections import OrderedDict
 from typing import Any, Optional, Dict, Tuple, List, Sequence
 from .connectivity_guard import (
    OFFLINE_FRIENDLY_MESSAGE,
@@ -45,6 +46,14 @@ class CivitaiClient:
        self._initialized = True

        self.base_url = "https://civitai.red/api/v1"
+        # In-memory cache to avoid redundant get_model_version_info calls
+        # within the same import/scan flow. Only successful results are cached.
+        # Uses OrderedDict with LRU eviction at MAX_CACHE_ENTRIES to prevent
+        # unbounded growth in long-running server processes.
+        self._version_info_cache: OrderedDict[
+            str, Tuple[Optional[Dict], Optional[str]]
+        ] = OrderedDict()
+        self._MAX_CACHE_ENTRIES = 500

    def _build_image_info_url(self, image_id: str) -> str:
        return f"{self.base_url}/images?imageId={image_id}&nsfw=X"
@@ -57,22 +66,57 @@ class CivitaiClient:
        use_auth: bool = False,
        **kwargs,
    ) -> Tuple[bool, Dict | str]:
-        """Wrapper around downloader.make_request that surfaces rate limits."""
+        """Wrapper around downloader.make_request that surfaces rate limits,
+        with retry for transient server errors (5xx, Cloudflare 524, network flakiness)."""

-        downloader = await get_downloader()
-        success, result = await downloader.make_request(
-            method,
-            url,
-            use_auth=use_auth,
-            **kwargs,
-        )
-        if not success and isinstance(result, RateLimitError):
-            if result.provider is None:
-                result.provider = "civitai_api"
-            raise result
-        if not success and is_offline_cooldown_error(result):
-            return False, OFFLINE_FRIENDLY_MESSAGE
-        return success, result
+        max_retries = 3
+        for attempt in range(max_retries):
+            downloader = await get_downloader()
+            success, result = await downloader.make_request(
+                method,
+                url,
+                use_auth=use_auth,
+                **kwargs,
+            )
+            if success:
+                return True, result
+
+            if isinstance(result, RateLimitError):
+                if result.provider is None:
+                    result.provider = "civitai_api"
+                raise result
+
+            if is_offline_cooldown_error(result):
+                return False, OFFLINE_FRIENDLY_MESSAGE
+
+            # Transient server error — retry with exponential backoff
+            if self._is_transient_server_error(str(result)):
+                if attempt < max_retries - 1:
+                    wait = 2**attempt  # 1s, 2s, 4s
+                    logger.info(
+                        "Transient error on %s %s, retrying in %ds "
+                        "(attempt %d/%d): %s",
+                        method,
+                        url,
+                        wait,
+                        attempt + 1,
+                        max_retries,
+                        result,
+                    )
+                    await asyncio.sleep(wait)
+                    continue
+                logger.warning(
+                    "All %d retries exhausted for %s %s: %s",
+                    max_retries,
+                    method,
+                    url,
+                    result,
+                )
+                return False, result
+
+            return False, result
+
+        return False, "Unexpected error in _make_request"

    @staticmethod
    def _remove_comfy_metadata(model_version: Optional[Dict]) -> None:
@@ -201,6 +245,29 @@ class CivitaiClient:

        return _from_value(payload)

+    @staticmethod
+    def _is_transient_server_error(message: str) -> bool:
+        """Return True when the message indicates a transient upstream failure.
+
+        Recognises Cloudflare 524, generic 5xx, and connectivity-level flakiness
+        that should not be treated as a permanent failure.
+        """
+        normalized = message.lower()
+        if "status 5" in normalized or "status 524" in normalized:
+            return True
+        if any(
+            keyword in normalized
+            for keyword in (
+                "connection refused",
+                "connection reset",
+                "temporary failure",
+                "name resolution",
+                "connection closed",
+            )
+        ):
+            return True
+        return False
+
    async def get_model_versions(self, model_id: str) -> Optional[Dict]:
        """Get all versions of a model with local availability info"""
        try:
@@ -223,6 +290,13 @@ class CivitaiClient:
                logger.info("Civitai request skipped: %s", OFFLINE_FRIENDLY_MESSAGE)
                return None
            if message:
+                if self._is_transient_server_error(message):
+                    logger.info(
+                        "Transient server error for model %s: %s",
+                        model_id,
+                        message,
+                    )
+                    return None
                raise RuntimeError(message)
            return None
        except RateLimitError:
@@ -257,7 +331,7 @@ class CivitaiClient:
                "GET",
                f"{self.base_url}/models",
                use_auth=True,
-                params={"ids": query},
+                params={"ids": query, "nsfw": "true"},
            )
            if not success:
                return None
@@ -336,6 +410,25 @@ class CivitaiClient:
            return None

        target_version = self._select_target_version(model_data, model_id, version_id)
+
+        # If modelVersions is empty (e.g. CivitAI cache lag for newly published
+        # models) but a specific version_id is known, fall back to fetching the
+        # version directly via the individual model-versions endpoint, then
+        # enrich it with the model-level data we already have.
+        if target_version is None and version_id is not None:
+            logger.info(
+                "modelVersions empty for model %s; falling back to direct "
+                "version lookup for %s",
+                model_id,
+                version_id,
+            )
+            version = await self._fetch_version_by_id(version_id)
+            if version:
+                self._enrich_version_with_model_data(version, model_data)
+                self._remove_comfy_metadata(version)
+                return version
+            return None
+
        if target_version is None:
            return None

@@ -482,6 +575,14 @@ class CivitaiClient:
                - The model version data or None if not found
                - An error message if there was an error, or None on success
        """
+        # In-memory cache avoids redundant API calls within the same
+        # import/scan flow (e.g. _resolve_base_model_from_checkpoint
+        # followed by _resolve_and_populate_checkpoint with the same id).
+        if version_id in self._version_info_cache:
+            logger.debug("Cache hit for model version info: %s", version_id)
+            self._version_info_cache.move_to_end(version_id)  # LRU bump
+            return self._version_info_cache[version_id]
+
        try:
            url = f"{self.base_url}/model-versions/{version_id}"

@@ -491,6 +592,11 @@ class CivitaiClient:
            if success:
                logger.debug("Successfully fetched model version info for: %s", version_id)
                self._remove_comfy_metadata(result)
+                self._version_info_cache[version_id] = (result, None)
+                self._version_info_cache.move_to_end(version_id)
+                # Evict oldest entry when over capacity
+                if len(self._version_info_cache) > self._MAX_CACHE_ENTRIES:
+                    self._version_info_cache.popitem(last=False)
                return result, None

            # Handle specific error cases
@@ -532,6 +638,13 @@ class CivitaiClient:
            if not success:
                if is_expected_offline_error(result):
                    return None
+                if self._is_transient_server_error(str(result)):
+                    logger.info(
+                        "Transient server error fetching image info for ID %s: %s",
+                        image_id,
+                        result,
+                    )
+                    return None
                logger.error(
                    "Failed to fetch image info for ID %s from civitai.red: %s",
                    image_id,
@@ -577,6 +690,59 @@ class CivitaiClient:
            logger.error(error_msg)
            return None

+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        """Fetch full version details for up to 100 SHA256 hashes via the batch endpoint.
+
+        Uses POST /api/v1/model-versions/by-hash which returns full version
+        details including ``usageControl`` and ``earlyAccessEndsAt`` that are
+        not available from the model-level API.
+
+        Args:
+            hashes: List of SHA256 hashes (max 100 per batch; auto-split).
+
+        Returns:
+            List of version dicts or None on failure.
+        """
+        if not hashes:
+            return []
+
+        BATCH_SIZE = 100
+        all_versions: List[Dict] = []
+
+        for start in range(0, len(hashes), BATCH_SIZE):
+            batch = hashes[start : start + BATCH_SIZE]
+            try:
+                success, result = await self._make_request(
+                    "POST",
+                    f"{self.base_url}/model-versions/by-hash",
+                    use_auth=True,
+                    json=batch,
+                )
+                if not success:
+                    logger.warning(
+                        "Batch by-hash request failed for %d hashes: %s",
+                        len(batch),
+                        result,
+                    )
+                    continue
+
+                if isinstance(result, list):
+                    all_versions.extend(result)
+                else:
+                    logger.debug(
+                        "Unexpected by-hash response type: %s", type(result)
+                    )
+            except RateLimitError:
+                raise
+            except Exception as exc:  # pragma: no cover - defensive logging
+                logger.error(
+                    "Error fetching model versions by hashes: %s", exc
+                )
+
+        return all_versions if all_versions else None
+
    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
        """Fetch all models for a specific Civitai user."""
        if not username:
@@ -587,7 +753,7 @@ class CivitaiClient:
                "GET",
                f"{self.base_url}/models",
                use_auth=True,
-                params={"username": username},
+                params={"username": username, "nsfw": "true"},
            )

            if not success:
--- a/py/services/download_manager.py
+++ b/py/services/download_manager.py
@@ -18,6 +18,7 @@ from ..utils.constants import (
    VALID_LORA_TYPES,
 )
 from ..utils.civitai_utils import normalize_civitai_download_url, rewrite_preview_url
+from ..utils.file_utils import calculate_sha256
 from ..utils.preview_selection import resolve_mature_threshold, select_preview_media
 from ..utils.utils import sanitize_folder_name
 from ..utils.exif_utils import ExifUtils
@@ -1364,7 +1365,7 @@ class DownloadManager:
                            f
                            for f in files
                            if f.get("primary")
-                            and f.get("type") in ("Model", "Negative")
+                            and f.get("type") in ("Model", "Negative", "Diffusion Model")
                        ),
                        None,
                    )
@@ -1395,7 +1396,7 @@ class DownloadManager:
                    (
                        f
                        for f in files
-                        if f.get("primary") and f.get("type") in ("Model", "Negative")
+                        if f.get("primary") and f.get("type") in ("Model", "Negative", "Diffusion Model")
                    ),
                    None,
                )
@@ -2239,8 +2240,11 @@ class DownloadManager:
            entry.file_name = os.path.splitext(os.path.basename(file_path))[0]
            # Update size to actual downloaded file size
            entry.size = os.path.getsize(file_path)
-            # Use SHA256 from API metadata (already set in from_civitai_info)
-            # Do not recalculate to avoid blocking during ComfyUI execution
+            # Compute SHA256 locally when the API response didn't include it
+            if not entry.sha256:
+                sha256 = await calculate_sha256(file_path)
+                if sha256:
+                    entry.sha256 = sha256.lower()
            entries.append(entry)

        return entries
--- a/py/services/downloaded_version_history_service.py
+++ b/py/services/downloaded_version_history_service.py
@@ -64,6 +64,7 @@ class DownloadedVersionHistoryService:
        self._db_path = db_path or _resolve_database_path()
        self._settings = settings_manager or get_settings_manager()
        self._lock = asyncio.Lock()
+        self._conn: sqlite3.Connection | None = None
        self._schema_initialized = False
        self._ensure_directory()
        self._initialize_schema()
@@ -78,6 +79,12 @@ class DownloadedVersionHistoryService:
        conn.row_factory = sqlite3.Row
        return conn

+    def _get_conn(self) -> sqlite3.Connection:
+        if self._conn is None:
+            self._conn = sqlite3.connect(self._db_path, check_same_thread=False)
+            self._conn.row_factory = sqlite3.Row
+        return self._conn
+
    def _initialize_schema(self) -> None:
        if self._schema_initialized:
            return
@@ -116,33 +123,33 @@ class DownloadedVersionHistoryService:
        timestamp = time.time()

        async with self._lock:
-            with self._connect() as conn:
-                conn.execute(
-                    """
-                    INSERT INTO downloaded_model_versions (
-                        model_type, version_id, model_id, first_seen_at, last_seen_at,
-                        source, last_file_path, last_library_name, is_deleted_override
-                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0)
-                    ON CONFLICT(model_type, version_id) DO UPDATE SET
-                        model_id = COALESCE(excluded.model_id, downloaded_model_versions.model_id),
-                        last_seen_at = excluded.last_seen_at,
-                        source = excluded.source,
-                        last_file_path = COALESCE(excluded.last_file_path, downloaded_model_versions.last_file_path),
-                        last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
-                        is_deleted_override = 0
-                    """,
-                    (
-                        normalized_type,
-                        normalized_version_id,
-                        normalized_model_id,
-                        timestamp,
-                        timestamp,
-                        source,
-                        file_path,
-                        active_library_name,
-                    ),
-                )
-                conn.commit()
+            conn = self._get_conn()
+            conn.execute(
+                """
+                INSERT INTO downloaded_model_versions (
+                    model_type, version_id, model_id, first_seen_at, last_seen_at,
+                    source, last_file_path, last_library_name, is_deleted_override
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0)
+                ON CONFLICT(model_type, version_id) DO UPDATE SET
+                    model_id = COALESCE(excluded.model_id, downloaded_model_versions.model_id),
+                    last_seen_at = excluded.last_seen_at,
+                    source = excluded.source,
+                    last_file_path = COALESCE(excluded.last_file_path, downloaded_model_versions.last_file_path),
+                    last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
+                    is_deleted_override = 0
+                """,
+                (
+                    normalized_type,
+                    normalized_version_id,
+                    normalized_model_id,
+                    timestamp,
+                    timestamp,
+                    source,
+                    file_path,
+                    active_library_name,
+                ),
+            )
+            conn.commit()

    async def mark_downloaded_bulk(
        self,
@@ -180,26 +187,26 @@ class DownloadedVersionHistoryService:
            return

        async with self._lock:
-            with self._connect() as conn:
-                conn.executemany(
-                    """
-                    INSERT INTO downloaded_model_versions (
-                        model_type, version_id, model_id, first_seen_at, last_seen_at,
-                        source, last_file_path, last_library_name, is_deleted_override
-                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0)
-                    ON CONFLICT(model_type, version_id) DO UPDATE SET
-                        model_id = COALESCE(excluded.model_id, downloaded_model_versions.model_id),
-                        last_seen_at = excluded.last_seen_at,
-                        source = excluded.source,
-                        last_file_path = COALESCE(excluded.last_file_path, downloaded_model_versions.last_file_path),
-                        last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
-                        is_deleted_override = 0
-                    """,
-                    payload,
-                )
-                conn.commit()
+            conn = self._get_conn()
+            conn.executemany(
+                """
+                INSERT INTO downloaded_model_versions (
+                    model_type, version_id, model_id, first_seen_at, last_seen_at,
+                    source, last_file_path, last_library_name, is_deleted_override
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, 0)
+                ON CONFLICT(model_type, version_id) DO UPDATE SET
+                    model_id = COALESCE(excluded.model_id, downloaded_model_versions.model_id),
+                    last_seen_at = excluded.last_seen_at,
+                    source = excluded.source,
+                    last_file_path = COALESCE(excluded.last_file_path, downloaded_model_versions.last_file_path),
+                    last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
+                    is_deleted_override = 0
+                """,
+                payload,
+            )
+            conn.commit()

-    async def mark_not_downloaded(self, model_type: str, version_id: int) -> None:
+    async def mark_as_deleted(self, model_type: str, version_id: int) -> None:
        normalized_type = _normalize_model_type(model_type)
        normalized_version_id = _normalize_int(version_id)
        if normalized_type is None or normalized_version_id is None:
@@ -208,28 +215,28 @@ class DownloadedVersionHistoryService:
        timestamp = time.time()

        async with self._lock:
-            with self._connect() as conn:
-                conn.execute(
-                    """
-                    INSERT INTO downloaded_model_versions (
-                        model_type, version_id, model_id, first_seen_at, last_seen_at,
-                        source, last_file_path, last_library_name, is_deleted_override
-                    ) VALUES (?, ?, NULL, ?, ?, 'manual', NULL, ?, 1)
-                    ON CONFLICT(model_type, version_id) DO UPDATE SET
-                        last_seen_at = excluded.last_seen_at,
-                        source = excluded.source,
-                        last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
-                        is_deleted_override = 1
-                    """,
-                    (
-                        normalized_type,
-                        normalized_version_id,
-                        timestamp,
-                        timestamp,
-                        self._get_active_library_name(),
-                    ),
-                )
-                conn.commit()
+            conn = self._get_conn()
+            conn.execute(
+                """
+                INSERT INTO downloaded_model_versions (
+                    model_type, version_id, model_id, first_seen_at, last_seen_at,
+                    source, last_file_path, last_library_name, is_deleted_override
+                ) VALUES (?, ?, NULL, ?, ?, 'manual', NULL, ?, 1)
+                ON CONFLICT(model_type, version_id) DO UPDATE SET
+                    last_seen_at = excluded.last_seen_at,
+                    source = excluded.source,
+                    last_library_name = COALESCE(excluded.last_library_name, downloaded_model_versions.last_library_name),
+                    is_deleted_override = 1
+                """,
+                (
+                    normalized_type,
+                    normalized_version_id,
+                    timestamp,
+                    timestamp,
+                    self._get_active_library_name(),
+                ),
+            )
+            conn.commit()

    async def has_been_downloaded(self, model_type: str, version_id: int) -> bool:
        normalized_type = _normalize_model_type(model_type)
@@ -238,15 +245,15 @@ class DownloadedVersionHistoryService:
            return False

        async with self._lock:
-            with self._connect() as conn:
-                row = conn.execute(
-                    """
-                    SELECT is_deleted_override
-                    FROM downloaded_model_versions
-                    WHERE model_type = ? AND version_id = ?
-                    """,
-                    (normalized_type, normalized_version_id),
-                ).fetchone()
+            conn = self._get_conn()
+            row = conn.execute(
+                """
+                SELECT is_deleted_override
+                FROM downloaded_model_versions
+                WHERE model_type = ? AND version_id = ?
+                """,
+                (normalized_type, normalized_version_id),
+            ).fetchone()
        return bool(row) and not bool(row["is_deleted_override"])

    async def get_downloaded_version_ids(
@@ -258,16 +265,16 @@ class DownloadedVersionHistoryService:
            return []

        async with self._lock:
-            with self._connect() as conn:
-                rows = conn.execute(
-                    """
-                    SELECT version_id
-                    FROM downloaded_model_versions
-                    WHERE model_type = ? AND model_id = ? AND is_deleted_override = 0
-                    ORDER BY version_id ASC
-                    """,
-                    (normalized_type, normalized_model_id),
-                ).fetchall()
+            conn = self._get_conn()
+            rows = conn.execute(
+                """
+                SELECT version_id
+                FROM downloaded_model_versions
+                WHERE model_type = ? AND model_id = ? AND is_deleted_override = 0
+                ORDER BY version_id ASC
+                """,
+                (normalized_type, normalized_model_id),
+            ).fetchall()
        return [int(row["version_id"]) for row in rows]

    async def get_downloaded_version_ids_bulk(
@@ -291,17 +298,17 @@ class DownloadedVersionHistoryService:
        params: list[object] = [normalized_type, *normalized_model_ids]

        async with self._lock:
-            with self._connect() as conn:
-                rows = conn.execute(
-                    f"""
-                    SELECT model_id, version_id
-                    FROM downloaded_model_versions
-                    WHERE model_type = ?
-                      AND model_id IN ({placeholders})
-                      AND is_deleted_override = 0
-                    """,
-                    params,
-                ).fetchall()
+            conn = self._get_conn()
+            rows = conn.execute(
+                f"""
+                SELECT model_id, version_id
+                FROM downloaded_model_versions
+                WHERE model_type = ?
+                  AND model_id IN ({placeholders})
+                  AND is_deleted_override = 0
+                """,
+                params,
+            ).fetchall()

        result: dict[int, set[int]] = {}
        for row in rows:
--- a/py/services/embedding_service.py
+++ b/py/services/embedding_service.py
@@ -3,6 +3,7 @@ import logging
 from typing import Dict

 from .base_model_service import BaseModelService
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import EmbeddingMetadata
 from ..config import config

@@ -45,7 +46,8 @@ class EmbeddingService(BaseModelService):
            "exclude": bool(embedding_data.get("exclude", False)),
            "update_available": bool(embedding_data.get("update_available", False)),
            "skip_metadata_refresh": bool(embedding_data.get("skip_metadata_refresh", False)),
-            "civitai": self.filter_civitai_data(embedding_data.get("civitai", {}), minimal=True)
+            "civitai": self.filter_civitai_data(embedding_data.get("civitai", {}), minimal=True),
+            "auto_tags": embedding_data.get("auto_tags") or extract_auto_tags(embedding_data),
        }
    
    def find_duplicate_hashes(self) -> Dict:
--- a/py/services/lora_service.py
+++ b/py/services/lora_service.py
@@ -5,6 +5,7 @@ from typing import Dict, List, Optional

 from .base_model_service import BaseModelService
 from .model_query import resolve_sub_type
+from .auto_tag_service import extract_auto_tags
 from ..utils.models import LoraMetadata
 from ..config import config

@@ -57,6 +58,7 @@ class LoraService(BaseModelService):
            "civitai": self.filter_civitai_data(
                lora_data.get("civitai", {}), minimal=True
            ),
+            "auto_tags": lora_data.get("auto_tags") or extract_auto_tags(lora_data),
        }

    async def _apply_specific_filters(self, data: List[Dict], **kwargs) -> List[Dict]:
@@ -310,8 +312,23 @@ class LoraService(BaseModelService):
        """Return cached raw metadata for a LoRA matching the given filename."""
        cache = await self.scanner.get_cached_data(force_refresh=False)

+        fn_normalized = filename.replace("\\", "/")
+        fn_no_ext = fn_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if fn_no_ext.lower().endswith(ext):
+                fn_no_ext = fn_no_ext[: -len(ext)]
+                break
+
        for lora in cache.raw_data if cache else []:
-            if lora.get("file_name") == filename:
+            file_name = lora.get("file_name", "")
+            folder = lora.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+            if fn_no_ext in (file_name_no_ext, path_name):
                return lora

        return None
@@ -399,7 +416,10 @@ class LoraService(BaseModelService):
            locked_loras = locked_loras[:target_count]

        # Filter out locked LoRAs from available pool
-        locked_names = {lora["name"] for lora in locked_loras}
+        locked_names = {
+            os.path.basename(lora["name"]) if "/" in str(lora.get("name", "")) else lora["name"]
+            for lora in locked_loras
+        }
        available_pool = [
            l for l in available_loras if l["file_name"] not in locked_names
        ]
@@ -454,7 +474,7 @@ class LoraService(BaseModelService):

            result_loras.append(
                {
-                    "name": lora["file_name"],
+                    "name": f"{lora['folder']}/{lora['file_name']}" if lora.get("folder") else lora["file_name"],
                    "strength": model_str,
                    "clipStrength": clip_str,
                    "active": True,
@@ -670,8 +690,9 @@ class LoraService(BaseModelService):
        # Return minimal data needed for cycling
        return [
            {
-                "file_name": lora["file_name"],
+                "file_name": f"{lora['folder']}/{lora['file_name']}" if lora.get("folder") else lora["file_name"],
                "model_name": lora.get("model_name", lora["file_name"]),
+                "folder": lora.get("folder", ""),
            }
            for lora in available_loras
        ]
--- a/py/services/model_hash_index.py
+++ b/py/services/model_hash_index.py
@@ -7,6 +7,7 @@ class ModelHashIndex:
    def __init__(self):
        self._hash_to_path: Dict[str, str] = {}
        self._filename_to_hash: Dict[str, str] = {}
+        self._autov2_to_path: Dict[str, str] = {}
        # New data structures for tracking duplicates
        self._duplicate_hashes: Dict[str, List[str]] = {}  # sha256 -> list of paths
        self._duplicate_filenames: Dict[str, List[str]] = {}  # filename -> list of paths
@@ -63,6 +64,9 @@ class ModelHashIndex:
        # Add new mappings
        self._hash_to_path[sha256] = file_path
        self._filename_to_hash[filename] = sha256
+        # AutoV2 = first 10 chars of SHA256
+        if len(sha256) >= 10:
+            self._autov2_to_path[sha256[:10]] = file_path
    
    def _get_filename_from_path(self, file_path: str) -> str:
        """Extract filename without extension from path"""
@@ -79,6 +83,12 @@ class ModelHashIndex:
                    hash_val = h
                    break
        
+        if hash_val is None:
+            for h, paths in self._duplicate_hashes.items():
+                if file_path in paths:
+                    hash_val = h
+                    break
+        
        # If we didn't find a hash, nothing to do
        if not hash_val:
            return
@@ -151,7 +161,12 @@ class ModelHashIndex:
                del self._duplicate_filenames[filename]
                if filename in self._filename_to_hash:
                    del self._filename_to_hash[filename]
-    
+
+        # Remove from AutoV2 index
+        autov2_keys_to_remove = [k for k, v in self._autov2_to_path.items() if v == file_path]
+        for k in autov2_keys_to_remove:
+            del self._autov2_to_path[k]
+
    def remove_by_hash(self, sha256: str) -> None:
        """Remove entry by hash"""
        sha256 = sha256.lower()
@@ -171,6 +186,10 @@ class ModelHashIndex:
        # Remove hash-to-path mapping
        del self._hash_to_path[sha256]
        
+        autov2_key = sha256[:10]
+        if autov2_key in self._autov2_to_path:
+            del self._autov2_to_path[autov2_key]
+        
        # Update filename-to-hash and duplicate filenames for all paths
        for path_to_remove in paths_to_remove:
            fname = self._get_filename_from_path(path_to_remove)
@@ -189,13 +208,24 @@ class ModelHashIndex:
                    # If only one entry remains, it's no longer a duplicate
                    del self._duplicate_filenames[fname]
    
-    def has_hash(self, sha256: str) -> bool:
-        """Check if hash exists in index"""
-        return sha256.lower() in self._hash_to_path
-    
-    def get_path(self, sha256: str) -> Optional[str]:
-        """Get file path for a hash"""
-        return self._hash_to_path.get(sha256.lower())
+    def has_hash(self, hash_value: str) -> bool:
+        """Check if hash exists in index (SHA256 or AutoV2)"""
+        normalized = hash_value.lower()
+        if normalized in self._hash_to_path:
+            return True
+        if len(normalized) == 10:
+            return normalized in self._autov2_to_path
+        return False
+
+    def get_path(self, hash_value: str) -> Optional[str]:
+        """Get file path for a hash (SHA256 or AutoV2)"""
+        normalized = hash_value.lower()
+        path = self._hash_to_path.get(normalized)
+        if path is not None:
+            return path
+        if len(normalized) == 10:
+            return self._autov2_to_path.get(normalized)
+        return None
    
    def get_hash(self, file_path: str) -> Optional[str]:
        """Get hash for a file path"""
@@ -203,13 +233,16 @@ class ModelHashIndex:
        return self._filename_to_hash.get(filename)
    
    def get_hash_by_filename(self, filename: str) -> Optional[str]:
-        """Get hash for a filename without extension"""
+        """Get hash for a filename (bare basename or path-prefixed name)"""
+        if "/" in filename or "\\" in filename:
+            filename = os.path.splitext(os.path.basename(filename.replace("\\", "/")))[0]
        return self._filename_to_hash.get(filename)
    
    def clear(self) -> None:
        """Clear all entries"""
        self._hash_to_path.clear()
        self._filename_to_hash.clear()
+        self._autov2_to_path.clear()
        self._duplicate_hashes.clear()
        self._duplicate_filenames.clear()
    
--- a/py/services/model_lifecycle_service.py
+++ b/py/services/model_lifecycle_service.py
@@ -111,6 +111,11 @@ class ModelLifecycleService:
            self._scanner._hash_index.remove_by_path(file_path)

        await self._sync_update_for_model(model_id)
+
+        persist_current_cache = getattr(self._scanner, "_persist_current_cache", None)
+        if callable(persist_current_cache):
+            await persist_current_cache()
+
        return {"success": True, "deleted_files": deleted_files}

    @staticmethod
--- a/py/services/model_metadata_provider.py
+++ b/py/services/model_metadata_provider.py
@@ -5,7 +5,7 @@ import logging
 import random
 from typing import Optional, Dict, Tuple, Any, List, Sequence
 from .downloader import get_downloader
-from .errors import RateLimitError
+from .errors import RateLimitError, ResourceNotFoundError

 try:
    from bs4 import BeautifulSoup
@@ -108,6 +108,18 @@ class ModelMetadataProvider(ABC):
    ) -> Optional[Dict[int, Dict]]:
        """Fetch model versions for multiple model ids when supported."""
        raise NotImplementedError
+
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        """Fetch full version details for multiple SHA256 hashes.
+
+        Used specifically to retrieve ``usageControl`` which is only
+        available from the per-version / by-hash API, not from model-level
+        responses.  Providers that cannot resolve hashes should let the
+        default ``NotImplementedError`` propagate.
+        """
+        raise NotImplementedError
        
    @abstractmethod
    async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
@@ -140,6 +152,11 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
        self, model_ids: Sequence[int]
    ) -> Optional[Dict[int, Dict]]:
        return await self.client.get_model_versions_bulk(model_ids)
+
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        return await self.client.get_model_versions_by_hashes(hashes)
        
    async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
        return await self.client.get_model_version(model_id, version_id)
@@ -465,6 +482,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
        return None, "Model not found"

    async def get_model_versions(self, model_id: str) -> Optional[Dict]:
+        not_found_confirmed = False
        for provider, label in self._iter_providers():
            try:
                result = await self._call_with_rate_limit(
@@ -475,8 +493,24 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                if result:
                    return result
            except RateLimitError as exc:
+                if not_found_confirmed:
+                    logger.debug(
+                        "Suppressing rate limit from %s for model %s: "
+                        "already confirmed as not found by another provider",
+                        label,
+                        model_id,
+                    )
+                    return None
                exc.provider = exc.provider or label
                raise exc
+            except ResourceNotFoundError:
+                not_found_confirmed = True
+                logger.debug(
+                    "Provider %s reports model %s as not found",
+                    label,
+                    model_id,
+                )
+                continue
            except Exception as e:
                logger.debug("Provider %s failed for get_model_versions: %s", label, e)
                continue
@@ -519,6 +553,32 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                continue
        return None, "No provider could retrieve the data"

+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        for provider, label in self._iter_providers():
+            try:
+                result = await self._call_with_rate_limit(
+                    label,
+                    provider.get_model_versions_by_hashes,
+                    hashes,
+                )
+                if result is not None:
+                    return result
+            except NotImplementedError:
+                continue
+            except RateLimitError as exc:
+                exc.provider = exc.provider or label
+                raise exc
+            except Exception as e:
+                logger.debug(
+                    "Provider %s failed for get_model_versions_by_hashes: %s",
+                    label,
+                    e,
+                )
+                continue
+        return None
+
    async def get_user_models(self, username: str) -> Optional[List[Dict]]:
        for provider, label in self._iter_providers():
            try:
@@ -593,6 +653,15 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
            model_ids,
        )

+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        return await self._rate_limit_helper.run(
+            self._label,
+            self._provider.get_model_versions_by_hashes,
+            hashes,
+        )
+
    async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
        return await self._rate_limit_helper.run(
            self._label,
@@ -669,6 +738,17 @@ class ModelMetadataProviderManager:
        provider = self._get_provider(provider_name)
        return await provider.get_model_version_info(version_id)

+    async def get_model_versions_by_hashes(
+        self,
+        hashes: List[str],
+        provider_name: str = None,
+    ) -> Optional[List[Dict]]:
+        provider = self._get_provider(provider_name)
+        try:
+            return await provider.get_model_versions_by_hashes(hashes)
+        except NotImplementedError:
+            return None
+
    async def get_user_models(self, username: str, provider_name: str = None) -> Optional[List[Dict]]:
        """Fetch models owned by the specified user"""
        provider = self._get_provider(provider_name)
--- a/py/services/model_query.py
+++ b/py/services/model_query.py
@@ -96,6 +96,7 @@ class FilterCriteria:
    folder_exclude: Optional[Sequence[str]] = None
    base_models: Optional[Sequence[str]] = None
    tags: Optional[Dict[str, str]] = None
+    auto_tags: Optional[Dict[str, str]] = None
    favorites_only: bool = False
    search_options: Optional[Dict[str, Any]] = None
    model_types: Optional[Sequence[str]] = None
@@ -359,10 +360,37 @@ class ModelFilterSet:
                ]
            model_types_duration = time.perf_counter() - t0

+        auto_tags_duration = 0
+        auto_tag_filters = criteria.auto_tags or {}
+        if auto_tag_filters:
+            t0 = time.perf_counter()
+            include_at = set()
+            exclude_at = set()
+            for tag, state in auto_tag_filters.items():
+                if not tag:
+                    continue
+                if state == "exclude":
+                    exclude_at.add(tag)
+                else:
+                    include_at.add(tag)
+
+            if include_at:
+                items = [
+                    item for item in items
+                    if any(tag in include_at for tag in (item.get("auto_tags") or []))
+                ]
+
+            if exclude_at:
+                items = [
+                    item for item in items
+                    if not any(tag in exclude_at for tag in (item.get("auto_tags") or []))
+                ]
+            auto_tags_duration = time.perf_counter() - t0
+
        duration = time.perf_counter() - overall_start
        if duration > 0.1:  # Only log if it's potentially slow
            logger.debug(
-                "ModelFilterSet.apply took %.3fs (sfw: %.3fs, fav: %.3fs, folder: %.3fs, base: %.3fs, tags: %.3fs, types: %.3fs). "
+                "ModelFilterSet.apply took %.3fs (sfw: %.3fs, fav: %.3fs, folder: %.3fs, base: %.3fs, tags: %.3fs, types: %.3fs, auto_tags: %.3fs). "
                "Count: %d -> %d",
                duration,
                sfw_duration,
@@ -371,6 +399,7 @@ class ModelFilterSet:
                base_models_duration,
                tags_duration,
                model_types_duration,
+                auto_tags_duration,
                initial_count,
                len(items),
            )
--- a/py/services/model_scanner.py
+++ b/py/services/model_scanner.py
@@ -9,7 +9,7 @@ from typing import Any, Awaitable, Callable, Dict, List, Mapping, Optional, Set,

 from ..utils.models import BaseModelMetadata
 from ..config import config
-from ..utils.file_utils import find_preview_file, get_preview_extension
+from ..utils.file_utils import find_preview_file, get_preview_extension, calculate_sha256
 from ..utils.metadata_manager import MetadataManager
 from ..utils.civitai_utils import resolve_license_info
 from .model_cache import ModelCache
@@ -1067,19 +1067,24 @@ class ModelScanner:

        model_data = self._build_cache_entry(metadata, folder=normalized_folder)

+        # Compute SHA256 hash when metadata provided none (e.g., CivitAI API response has empty hashes)
+        if not model_data.get('sha256') and file_path:
+            try:
+                logger.info(f"Computing SHA256 hash for {file_path} (was empty from metadata)")
+                sha256 = await calculate_sha256(file_path)
+                if sha256:
+                    model_data['sha256'] = sha256.lower()
+                    if isinstance(metadata, BaseModelMetadata):
+                        metadata.sha256 = sha256.lower()
+                    await MetadataManager.save_metadata(file_path, metadata)
+            except Exception as e:
+                logger.error(f"Failed to compute SHA256 for {file_path}: {e}")
+
        # Skip excluded models
        if model_data.get('exclude', False):
            excluded_models.append(model_data['file_path'])
            return None

-        # Check for duplicate filename before adding to hash index
-        # filename = os.path.splitext(os.path.basename(file_path))[0]
-        # existing_hash = hash_index.get_hash_by_filename(filename)
-        # if existing_hash and existing_hash != model_data.get('sha256', '').lower():
-        #     existing_path = hash_index.get_path(existing_hash)
-        #     if existing_path and existing_path != file_path:
-        #         logger.warning(f"Duplicate filename detected: '{filename}' - files: '{existing_path}' and '{file_path}'")
-
        return model_data

    async def _apply_scan_result(self, scan_result: CacheBuildResult) -> None:
@@ -1105,6 +1110,39 @@ class ModelScanner:

        await self._cache.resort()

+        self._log_duplicate_filename_summary()
+
+    def _log_duplicate_filename_summary(self) -> None:
+        """Log a batched summary of duplicate filename conflicts once per scan."""
+        # Duplicate filename detection is only relevant for LoRAs, which use
+        # basename-only syntax (<lora:name:strength>). Checkpoints and embeddings
+        # use full relative paths for resolution, so conflicts are not ambiguous.
+        if self._hash_index is None or self.model_type != "lora":
+            return
+
+        # When full path syntax is active, duplicate filenames across subfolders
+        # are fully qualified, so there is no ambiguity — skip the warning.
+        if get_settings_manager().get("lora_syntax_format", "legacy") == "full":
+            return
+
+        duplicates = self._hash_index.get_duplicate_filenames()
+        if not duplicates:
+            return
+
+        total_files = sum(len(paths) for paths in duplicates.values())
+        conflict_count = len(duplicates)
+        model_type_label = self.model_type or "model"
+
+        logger.warning(
+            "Duplicate filename conflict detected: %d %s filename(s) "
+            "are shared by %d files total, causing ambiguity in %s resolution. "
+            "Open the Doctor panel to resolve one-click.",
+            conflict_count,
+            model_type_label,
+            total_files,
+            model_type_label.capitalize(),
+        )
+
    async def _sync_download_history(
        self,
        raw_data: List[Mapping[str, Any]],
@@ -1456,6 +1494,15 @@ class ModelScanner:
                file_path_override=normalized_new_path,
            )

+            # Ensure sha256 is populated even when metadata doesn't have it
+            if not cache_entry.get('sha256') and normalized_new_path and os.path.exists(normalized_new_path):
+                try:
+                    sha256 = await calculate_sha256(normalized_new_path)
+                    if sha256:
+                        cache_entry['sha256'] = sha256.lower()
+                except Exception as e:
+                    logger.error(f"Failed to compute SHA256 for {normalized_new_path}: {e}")
+
            if recalculate_type:
                cache_entry = self.adjust_cached_entry(cache_entry)

@@ -1555,12 +1602,39 @@ class ModelScanner:
        """Get model information by name"""
        try:
            cache = await self.get_cached_data()
-            
+
+            name_normalized = name.replace("\\", "/")
+            name_no_ext = name_normalized
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if name_no_ext.lower().endswith(ext):
+                    name_no_ext = name_no_ext[: -len(ext)]
+                    break
+
+            has_path = "/" in name_no_ext
+            basename = os.path.basename(name_no_ext) if has_path else name_no_ext
+            best_fallback = None
+
            for model in cache.raw_data:
-                if model.get("file_name") == name:
+                file_name = model.get("file_name", "")
+                folder = model.get("folder", "")
+                file_name_no_ext = file_name
+                for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                    if file_name_no_ext.lower().endswith(ext):
+                        file_name_no_ext = file_name_no_ext[: -len(ext)]
+                        break
+                path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+                if name_no_ext == file_name_no_ext or name_no_ext == path_name:
                    return model
-                    
-            return None
+
+                if has_path and file_name_no_ext == basename:
+                    if folder and name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                        best_fallback = model
+                    elif best_fallback is None:
+                        best_fallback = model
+
+            return best_fallback
+
        except Exception as e:
            logger.error(f"Error getting model info by name: {e}", exc_info=True)
            return None
--- a/py/services/model_update_service.py
+++ b/py/services/model_update_service.py
@@ -69,6 +69,7 @@ class ModelVersionRecord:
    early_access_ends_at: Optional[str] = None
    sort_index: int = 0
    is_early_access: bool = False
+    usage_control: Optional[str] = None  # "Download", "Generation", "InternalGeneration"


@dataclass
@@ -101,11 +102,14 @@ class ModelUpdateRecord:

        return [version.version_id for version in self.versions if version.is_in_library]

-    def has_update(self, hide_early_access: bool = False) -> bool:
+    def has_update(
+        self, hide_early_access: bool = False, hide_non_downloadable: bool = True
+    ) -> bool:
        """Return True when a non-ignored remote version newer than the newest local copy is available.

        Args:
            hide_early_access: If True, exclude early access versions from update check.
+            hide_non_downloadable: If True, exclude versions that don't allow downloads.
        """

        if self.should_ignore_model:
@@ -121,6 +125,7 @@ class ModelUpdateRecord:
                not version.is_in_library
                and not version.should_ignore
                and not (hide_early_access and ModelUpdateRecord._is_early_access_active(version))
+                and not (hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version))
                for version in self.versions
            )

@@ -129,6 +134,8 @@ class ModelUpdateRecord:
                continue
            if hide_early_access and ModelUpdateRecord._is_early_access_active(version):
                continue
+            if hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version):
+                continue
            if version.version_id > max_in_library:
                return True
        return False
@@ -155,11 +162,18 @@ class ModelUpdateRecord:
        # Phase 1: Basic EA flag from bulk API
        return version.is_early_access

+    @staticmethod
+    def _is_downloadable(version: ModelVersionRecord) -> bool:
+        if version.usage_control is None:
+            return True
+        return version.usage_control == "Download"
+
    def has_update_for_base(
        self,
        local_version_id: Optional[int],
        local_base_model: Optional[str],
        hide_early_access: bool = False,
+        hide_non_downloadable: bool = True,
    ) -> bool:
        """Return True when a newer remote version with the same base model exists.

@@ -167,6 +181,7 @@ class ModelUpdateRecord:
            local_version_id: The current local version id.
            local_base_model: The base model to filter by.
            hide_early_access: If True, exclude early access versions from update check.
+            hide_non_downloadable: If True, exclude versions that don't allow downloads.
        """

        if self.should_ignore_model:
@@ -197,6 +212,8 @@ class ModelUpdateRecord:
                continue
            if hide_early_access and ModelUpdateRecord._is_early_access_active(version):
                continue
+            if hide_non_downloadable and not ModelUpdateRecord._is_downloadable(version):
+                continue
            version_base = _normalize_base_model(version.base_model)
            if version_base != normalized_base:
                continue
@@ -230,6 +247,7 @@ class ModelUpdateService:
            preview_url TEXT,
            is_in_library INTEGER NOT NULL DEFAULT 0,
            should_ignore INTEGER NOT NULL DEFAULT 0,
+            usage_control TEXT,
            PRIMARY KEY (model_id, version_id),
            FOREIGN KEY(model_id) REFERENCES model_update_status(model_id) ON DELETE CASCADE
        );
@@ -465,6 +483,10 @@ class ModelUpdateService:
                "ALTER TABLE model_update_versions "
                "ADD COLUMN is_early_access INTEGER NOT NULL DEFAULT 0"
            ),
+            "usage_control": (
+                "ALTER TABLE model_update_versions "
+                "ADD COLUMN usage_control TEXT"
+            ),
        }

        for column, statement in migrations.items():
@@ -967,18 +989,22 @@ class ModelUpdateService:
                fallback_attempted = True
                try:
                    response = await metadata_provider.get_model_versions(model_id)
+                    if response is not None:
+                        await self._enrich_version_entries(
+                            metadata_provider,
+                            {model_id: response},
+                        )
                except RateLimitError:
                    raise
                except ResourceNotFoundError as exc:
                    fallback_error_message = str(exc) or "resource not found"
                    mark_model_as_ignored = True
                except Exception as exc:  # pragma: no cover - defensive log
-                    logger.error(
+                    logger.warning(
                        "Failed to fetch versions for model %s (%s): %s",
                        model_id,
                        model_type,
                        exc,
-                        exc_info=True,
                    )
                    fallback_error_message = str(exc)
            if response is not None:
@@ -1061,6 +1087,136 @@ class ModelUpdateService:
            self._upsert_record(record)
            return record

+    async def _enrich_version_entries(
+        self,
+        metadata_provider,
+        responses_by_model_id: Dict[int, Mapping],
+    ) -> None:
+        """Enrich version entries with ``usageControl`` via batch hash endpoint.
+
+        The model-level API does not include ``usageControl`` on version
+        entries. This method collects SHA256 hashes from every version's
+        primary model file, calls ``POST /api/v1/model-versions/by-hash``
+        (up to 100 hashes per request), and injects ``usageControl`` +
+        ``earlyAccessEndsAt`` into each version entry dict in-place.
+        """
+        if not metadata_provider or not responses_by_model_id:
+            return
+
+        hashes_by_version: Dict[int, str] = {}
+        for response in responses_by_model_id.values():
+            hashes_by_version.update(
+                self._collect_hashes_from_response(response)
+            )
+
+        if not hashes_by_version:
+            return
+
+        version_ids_by_hash: Dict[str, List[int]] = {}
+        for version_id, sha256 in hashes_by_version.items():
+            version_ids_by_hash.setdefault(sha256, []).append(version_id)
+
+        all_hashes = list(version_ids_by_hash.keys())
+        BATCH_SIZE = 100
+
+        enrichment: Dict[int, Dict] = {}
+        try:
+            for start in range(0, len(all_hashes), BATCH_SIZE):
+                batch = all_hashes[start : start + BATCH_SIZE]
+                try:
+                    enriched = await metadata_provider.get_model_versions_by_hashes(
+                        batch
+                    )
+                except NotImplementedError:
+                    return
+                except RateLimitError:
+                    raise
+                except Exception:
+                    continue
+
+                if not enriched:
+                    continue
+
+                for entry in enriched:
+                    if not isinstance(entry, dict):
+                        continue
+                    version_id = entry.get("id")
+                    if version_id is None:
+                        continue
+                    enrichment[version_id] = {
+                        "usageControl": _normalize_string(
+                            entry.get("usageControl")
+                        ),
+                        "earlyAccessEndsAt": _normalize_string(
+                            entry.get("earlyAccessEndsAt")
+                        ),
+                    }
+        except RateLimitError:
+            raise
+
+        if not enrichment:
+            return
+
+        for response in responses_by_model_id.values():
+            versions = response.get("modelVersions")
+            if not isinstance(versions, list):
+                continue
+            for version in versions:
+                if not isinstance(version, dict):
+                    continue
+                version_id = version.get("id")
+                if version_id not in enrichment:
+                    continue
+                extra = enrichment[version_id]
+                if extra.get("usageControl") and not version.get("usageControl"):
+                    version["usageControl"] = extra["usageControl"]
+                if extra.get("earlyAccessEndsAt") and not version.get(
+                    "earlyAccessEndsAt"
+                ):
+                    version["earlyAccessEndsAt"] = extra["earlyAccessEndsAt"]
+
+    @staticmethod
+    def _collect_hashes_from_response(response: Mapping) -> Dict[int, str]:
+        """Extract ``{version_id: sha256}`` from a model-level API response.
+
+        Returns an empty dict if the response structure is unexpected.
+        """
+        result: Dict[int, str] = {}
+        versions = response.get("modelVersions")
+        if not isinstance(versions, list):
+            return result
+        for entry in versions:
+            if not isinstance(entry, dict):
+                continue
+            version_id = _normalize_int(entry.get("id"))
+            if version_id is None:
+                continue
+            sha256 = ModelUpdateService._extract_sha256_from_version_entry(entry)
+            if sha256:
+                result[version_id] = sha256
+        return result
+
+    @staticmethod
+    def _extract_sha256_from_version_entry(entry: Mapping) -> Optional[str]:
+        """Return the SHA256 hash from the primary model file of a version entry."""
+        files = entry.get("files")
+        if not isinstance(files, list):
+            return None
+        for file_info in files:
+            if not isinstance(file_info, dict):
+                continue
+            if file_info.get("type") != "Model":
+                continue
+            primary = file_info.get("primary")
+            if primary is not True and str(primary).strip().lower() != "true":
+                continue
+            hashes = file_info.get("hashes")
+            if isinstance(hashes, dict):
+                sha256 = hashes.get("SHA256")
+                if sha256:
+                    return sha256
+        return None
+
    async def _fetch_model_versions_bulk(
        self,
        metadata_provider,
@@ -1112,6 +1268,7 @@ class ModelUpdateService:
            len(aggregated),
            provider_name,
        )
+        await self._enrich_version_entries(metadata_provider, aggregated)
        return aggregated

    async def _collect_local_versions(
@@ -1239,6 +1396,7 @@ class ModelUpdateService:
                    sort_index=sort_map.get(version_id, index),
                    early_access_ends_at=remote_version.early_access_ends_at,
                    is_early_access=remote_version.is_early_access,
+                    usage_control=remote_version.usage_control,
                )
            )

@@ -1337,6 +1495,7 @@ class ModelUpdateService:
        # Check availability field from bulk API for basic EA detection
        availability = _normalize_string(entry.get("availability"))
        is_early_access = availability == "EarlyAccess"
+        usage_control = _normalize_string(entry.get("usageControl"))

        return ModelVersionRecord(
            version_id=version_id,
@@ -1350,6 +1509,7 @@ class ModelUpdateService:
            early_access_ends_at=early_access_ends_at,
            sort_index=index,
            is_early_access=is_early_access,
+            usage_control=usage_control,
        )

    def _extract_size_bytes(self, files) -> Optional[int]:
@@ -1464,7 +1624,7 @@ class ModelUpdateService:
                    f"""
                    SELECT model_id, version_id, sort_index, name, base_model, released_at,
                           size_bytes, preview_url, is_in_library, should_ignore, early_access_ends_at,
-                           is_early_access
+                           is_early_access, usage_control
                    FROM model_update_versions
                    WHERE model_id IN ({placeholders})
                    ORDER BY model_id ASC, sort_index ASC, version_id ASC
@@ -1492,6 +1652,7 @@ class ModelUpdateService:
                    early_access_ends_at=row["early_access_ends_at"],
                    sort_index=_normalize_int(row["sort_index"]) or 0,
                    is_early_access=bool(row["is_early_access"]),
+                    usage_control=row["usage_control"],
                )
            )

@@ -1548,8 +1709,8 @@ class ModelUpdateService:
                    INSERT INTO model_update_versions (
                        version_id, model_id, sort_index, name, base_model, released_at,
                        size_bytes, preview_url, is_in_library, should_ignore, early_access_ends_at,
-                        is_early_access
-                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+                        is_early_access, usage_control
+                    ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
                    """,
                    (
                        version.version_id,
@@ -1564,6 +1725,7 @@ class ModelUpdateService:
                        1 if version.should_ignore else 0,
                        version.early_access_ends_at,
                        1 if version.is_early_access else 0,
+                        version.usage_control,
                    ),
                )
            conn.commit()
--- a/py/services/persistent_recipe_cache.py
+++ b/py/services/persistent_recipe_cache.py
@@ -38,6 +38,7 @@ class PersistentRecipeCache:
        "json_path",
        "title",
        "folder",
+        "source_path",
        "base_model",
        "fingerprint",
        "created_date",
@@ -334,6 +335,7 @@ class PersistentRecipeCache:
                            json_path TEXT,
                            title TEXT,
                            folder TEXT,
+                            source_path TEXT,
                            base_model TEXT,
                            fingerprint TEXT,
                            created_date REAL,
@@ -358,6 +360,13 @@ class PersistentRecipeCache:
                        );
                        """
                    )
+                    # Migration: add source_path column to existing databases
+                    try:
+                        conn.execute(
+                            "ALTER TABLE recipes ADD COLUMN source_path TEXT"
+                        )
+                    except Exception:
+                        pass  # column already exists
                    conn.commit()
                self._schema_initialized = True
            except Exception as exc:
@@ -406,6 +415,7 @@ class PersistentRecipeCache:
            json_path,
            recipe.get("title"),
            recipe.get("folder"),
+            recipe.get("source_path"),
            recipe.get("base_model"),
            recipe.get("fingerprint"),
            float(recipe.get("created_date") or 0.0),
@@ -456,6 +466,7 @@ class PersistentRecipeCache:
            "file_path": row["file_path"] or "",
            "title": row["title"] or "",
            "folder": row["folder"] or "",
+            "source_path": row["source_path"] or "",
            "base_model": row["base_model"] or "",
            "fingerprint": row["fingerprint"] or "",
            "created_date": row["created_date"] or 0.0,
--- a/py/services/recipe_scanner.py
+++ b/py/services/recipe_scanner.py
@@ -65,7 +65,7 @@ class RecipeScanner:
            cls._instance._civitai_client = None  # Will be lazily initialized
        return cls._instance

-    REPAIR_VERSION = 3
+    REPAIR_VERSION = 4

    def __init__(
        self,
@@ -292,6 +292,32 @@ class RecipeScanner:
        if recipe.get("repair_version", 0) >= self.REPAIR_VERSION:
            return False

+        # 1.5 Detect and clear corrupted checkpoint (LoRA data saved as checkpoint).
+        #     A checkpoint whose modelVersionId also appears in a LoRA entry is
+        #     definitely wrong — the CivitAI import code used to pick
+        #     modelVersionIds[0] as the checkpoint, which was often a LoRA.
+        #     Clearing it lets the enrichment flow re-resolve the correct
+        #     checkpoint from CivitAI image metadata.
+        cp = recipe.get("checkpoint")
+        lora_mvids = {
+            l.get("modelVersionId")
+            for l in recipe.get("loras", [])
+            if l.get("modelVersionId")
+        }
+        if cp and cp.get("modelVersionId") and cp["modelVersionId"] in lora_mvids:
+            cp_mvid = cp["modelVersionId"]
+            logger.info(
+                "Recipe %s: checkpoint modelVersionId %s matches a LoRA — "
+                "clearing corrupted checkpoint and removing matching LoRA entry",
+                recipe.get("id"),
+                cp_mvid,
+            )
+            recipe["checkpoint"] = None
+            recipe["loras"] = [
+                l for l in recipe.get("loras", [])
+                if l.get("modelVersionId") != cp_mvid
+            ]
+
        # 2. Identification: Is repair needed?
        has_checkpoint = (
            "checkpoint" in recipe
@@ -504,6 +530,9 @@ class RecipeScanner:
                    self._cache.raw_data = recipes
                    self._update_folder_metadata(self._cache)
                    self._sort_cache_sync()
+                    # Backfill source_path from JSON files if missing (schema migration)
+                    if self._backfill_source_path_if_needed(recipes, json_paths):
+                        self._persistent_cache.save_cache(recipes, json_paths)
                    return self._cache
                else:
                    # Partial update: some files changed
@@ -514,6 +543,8 @@ class RecipeScanner:
                    self._cache.raw_data = recipes
                    self._update_folder_metadata(self._cache)
                    self._sort_cache_sync()
+                    # Backfill source_path from JSON files if missing (schema migration)
+                    self._backfill_source_path_if_needed(recipes, json_paths)
                    # Persist updated cache
                    self._persistent_cache.save_cache(recipes, json_paths)
                    return self._cache
@@ -642,6 +673,34 @@ class RecipeScanner:

        return recipes, changed, json_paths

+    def _backfill_source_path_if_needed(
+        self,
+        recipes: List[Dict],
+        json_paths: Dict[str, str],
+    ) -> bool:
+        """Backfill source_path from recipe JSON files if missing from cache.
+
+        Returns True if any recipes were updated (caller should persist cache).
+        """
+        updated = False
+        for recipe in recipes:
+            if recipe.get("source_path"):
+                continue
+            recipe_id = str(recipe.get("id", ""))
+            json_path = json_paths.get(recipe_id)
+            if not json_path or not os.path.exists(json_path):
+                continue
+            try:
+                with open(json_path, "r", encoding="utf-8") as f:
+                    json_data = json.load(f)
+                file_source_path = json_data.get("source_path")
+                if file_source_path:
+                    recipe["source_path"] = file_source_path
+                    updated = True
+            except Exception:
+                pass
+        return updated
+
    def _full_directory_scan_sync(
        self, recipes_dir: str
    ) -> Tuple[List[Dict], Dict[str, str]]:
@@ -2484,6 +2543,7 @@ class RecipeScanner:
                continue

            file_name = None
+            folder = ""
            hash_value = (lora.get("hash") or "").lower()
            if (
                hash_value
@@ -2493,6 +2553,11 @@ class RecipeScanner:
                file_path = self._lora_scanner._hash_index.get_path(hash_value)
                if file_path:
                    file_name = os.path.splitext(os.path.basename(file_path))[0]
+                    if lora_cache is not None:
+                        for cached_lora in getattr(lora_cache, "raw_data", []):
+                            if cached_lora.get("file_path") == file_path:
+                                folder = cached_lora.get("folder", "")
+                                break

            if not file_name and lora.get("modelVersionId") and lora_cache is not None:
                for cached_lora in getattr(lora_cache, "raw_data", []):
@@ -2507,13 +2572,16 @@ class RecipeScanner:
                            file_name = os.path.splitext(os.path.basename(cached_path))[
                                0
                            ]
+                            folder = cached_lora.get("folder", "")
                        break

            if not file_name:
                file_name = lora.get("file_name", "unknown-lora")
+                folder = lora.get("folder", "")

+            lora_name = f"{folder}/{file_name}" if folder else file_name
            strength = lora.get("strength", 1.0)
-            syntax_parts.append(f"<lora:{file_name}:{strength}>")
+            syntax_parts.append(f"<lora:{lora_name}:{strength}>")

        return syntax_parts

--- a/py/services/recipes/analysis_service.py
+++ b/py/services/recipes/analysis_service.py
@@ -2,6 +2,7 @@

 from __future__ import annotations

+import asyncio
 import base64
 import io
 import os
@@ -14,6 +15,7 @@ from PIL import Image

 from ...utils.utils import calculate_recipe_fingerprint
 from ...utils.civitai_utils import extract_civitai_image_id, rewrite_preview_url
+from ...recipes.enrichment import RecipeEnricher
 from .errors import (
    RecipeDownloadError,
    RecipeNotFoundError,
@@ -170,9 +172,11 @@ class RecipeAnalysisService:
                await self._download_image(url, temp_path)

            if metadata is None and not is_video:
-                metadata = self._exif_utils.extract_image_metadata(temp_path)
+                metadata = await asyncio.to_thread(
+                    self._exif_utils.extract_image_metadata, temp_path
+                )

-            return await self._parse_metadata(
+            result = await self._parse_metadata(
                metadata or {},
                recipe_scanner=recipe_scanner,
                image_path=temp_path,
@@ -180,6 +184,37 @@ class RecipeAnalysisService:
                is_video=is_video,
                extension=extension,
            )
+
+            if civitai_image_id and image_info and not result.payload.get("error"):
+                mvid = image_info.get("modelVersionId")
+                if not mvid:
+                    mvids = image_info.get("modelVersionIds")
+                    if isinstance(mvids, list) and mvids:
+                        mvid = mvids[0]
+
+                recipe_for_enrich = {
+                    "gen_params": result.payload.get("gen_params", {}),
+                    "loras": result.payload.get("loras", []),
+                    "base_model": result.payload.get("base_model", "") or "",
+                    "checkpoint": result.payload.get("checkpoint") or result.payload.get("model"),
+                    "source_path": url,
+                }
+
+                await RecipeEnricher.enrich_recipe(
+                    recipe=recipe_for_enrich,
+                    civitai_client=civitai_client,
+                    request_params=None,
+                    prefetched_civitai_meta_raw=image_info.get("meta"),
+                    prefetched_model_version_id=mvid,
+                )
+
+                result.payload["gen_params"] = recipe_for_enrich["gen_params"]
+                if recipe_for_enrich.get("checkpoint"):
+                    result.payload["checkpoint"] = recipe_for_enrich["checkpoint"]
+                if recipe_for_enrich.get("base_model"):
+                    result.payload["base_model"] = recipe_for_enrich["base_model"]
+
+            return result
        finally:
            if temp_path:
                self._safe_cleanup(temp_path)
@@ -199,7 +234,9 @@ class RecipeAnalysisService:
        if not os.path.isfile(normalized_path):
            raise RecipeNotFoundError("File not found")

-        metadata = self._exif_utils.extract_image_metadata(normalized_path)
+        metadata = await asyncio.to_thread(
+            self._exif_utils.extract_image_metadata, normalized_path
+        )
        if not metadata:
            return self._metadata_not_found_response(normalized_path)

--- a/py/services/settings_manager.py
+++ b/py/services/settings_manager.py
@@ -96,7 +96,9 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
    "compact_mode": False,
    "priority_tags": DEFAULT_PRIORITY_TAG_CONFIG.copy(),
    "model_name_display": "model_name",
+    "lora_syntax_format": "legacy",
    "model_card_footer_action": "replace_preview",
+    "show_version_on_card": True,
    "update_flag_strategy": "same_base",
    "auto_organize_exclusions": [],
    "metadata_refresh_skip_paths": [],
--- a/py/services/tag_update_service.py
+++ b/py/services/tag_update_service.py
@@ -4,7 +4,9 @@ from __future__ import annotations

 import os

-from typing import Awaitable, Callable, Dict, List, Sequence
+from typing import Awaitable, Callable, Dict, List, Sequence, Tuple
+
+from .auto_tag_service import extract_auto_tags


 class TagUpdateService:
@@ -20,9 +22,8 @@ class TagUpdateService:
        new_tags: Sequence[str],
        metadata_loader: Callable[[str], Awaitable[Dict[str, object]]],
        update_cache: Callable[[str, str, Dict[str, object]], Awaitable[bool]],
-    ) -> List[str]:
-        """Add tags to a metadata entry while keeping case-insensitive uniqueness."""
-
+    ) -> Tuple[List[str], List[str]]:
+        """Add tags to a metadata entry and return updated tags and auto_tags."""
        base, _ = os.path.splitext(file_path)
        metadata_path = f"{base}.metadata.json"
        metadata = await metadata_loader(metadata_path)
@@ -44,5 +45,6 @@ class TagUpdateService:
        await self._metadata_manager.save_metadata(file_path, metadata)
        await update_cache(file_path, file_path, metadata)

-        return existing_tags
+        auto_tags = extract_auto_tags(metadata)
+        return existing_tags, auto_tags

--- a/py/utils/civitai_utils.py
+++ b/py/utils/civitai_utils.py
@@ -7,7 +7,7 @@ from typing import Any, Dict, Iterable, Mapping, Sequence
 from urllib.parse import parse_qs, urlparse, urlunparse


-_SUPPORTED_CIVITAI_PAGE_HOSTS = frozenset({"civitai.com", "civitai.red"})
+_SUPPORTED_CIVITAI_PAGE_HOSTS = frozenset({"civitai.com", "civitai.red", "civitai.green"})
 DEFAULT_CIVITAI_PAGE_HOST = "civitai.com"
 _DEFAULT_ALLOW_COMMERCIAL_USE: Sequence[str] = ("Sell",)
 _LICENSE_DEFAULTS: Dict[str, Any] = {
@@ -239,9 +239,9 @@ def _resolve_commercial_bits(values: Sequence[str]) -> int:
            normalized_values.add(normalized)

    has_sell = "sell" in normalized_values
-    has_rent = has_sell or "rent" in normalized_values
-    has_rentcivit = has_rent or "rentcivit" in normalized_values
-    has_image = has_sell or "image" in normalized_values
+    has_rent = "rent" in normalized_values
+    has_rentcivit = "rentcivit" in normalized_values
+    has_image = "image" in normalized_values

    commercial_bits = (
        (1 if has_sell else 0) << 3
--- a/py/utils/constants.py
+++ b/py/utils/constants.py
@@ -178,5 +178,8 @@ SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS = frozenset(
        "Wan Video 2.5 I2V",
        "Hunyuan Video",
        "Anima",
+        "Ernie",
+        "Ernie Turbo",
+        "Nucleus",
    ]
 )
--- a/py/utils/example_images_download_manager.py
+++ b/py/utils/example_images_download_manager.py
@@ -397,13 +397,12 @@ class DownloadManager:

            models_with_hash = len(all_models_with_hash)

-            # Calculate pending count: check which models actually need processing
-            # A model is pending if it has a hash, is not in processed_models,
-            # and its folder doesn't exist or is empty
+            # Calculate pending count: check which models actually need processing.
+            # A model is pending if it has a hash, is not already processed or known-failed,
+            # and its folder doesn't exist or is empty.
            pending_hashes = set()
            for model_hash, model_name in all_models_with_hash:
-                if model_hash not in processed_models:
-                    # Check if model folder exists with files
+                if model_hash not in processed_models and model_hash not in failed_models:
                    model_dir = ExampleImagePathResolver.get_model_folder(
                        model_hash, active_library
                    )
--- a/py/utils/example_images_metadata.py
+++ b/py/utils/example_images_metadata.py
@@ -452,3 +452,111 @@ class MetadataUpdater:
        except Exception as e:
            logger.error(f"Error parsing image metadata: {e}", exc_info=True)
            return None
+
+    @staticmethod
+    async def prune_stale_example_images(metadata) -> bool:
+        """Remove example-image metadata entries whose files no longer exist on disk.
+
+        Checks ``civitai.customImages`` (by ``id``) and ``civitai.images`` entries
+        that have an empty ``url`` (no remote fallback) against actual files in
+        the model's example-image folder.  Stale entries are removed in-place so
+        the caller can persist the cleaned metadata afterwards.
+
+        Args:
+            metadata: A ``BaseModelMetadata`` instance (modified in place).
+
+        Returns:
+            True if at least one entry was removed.
+        """
+        from ..utils.example_images_paths import get_model_folder
+
+        model_hash = getattr(metadata, "sha256", None)
+        if not model_hash:
+            return False
+
+        model_folder = get_model_folder(model_hash)
+        if not model_folder:
+            return False
+
+        civitai = getattr(metadata, "civitai", None)
+        if not isinstance(civitai, dict):
+            return False
+
+        has_changes = False
+
+        custom_images = civitai.get("customImages")
+        if isinstance(custom_images, list) and custom_images:
+            stale: list[int] = []
+
+            for idx, img in enumerate(custom_images):
+                img_id = img.get("id", "")
+                if not img_id:
+                    continue
+
+                if not os.path.isdir(model_folder):
+                    stale.append(idx)
+                else:
+                    found = False
+                    try:
+                        prefix = f"custom_{img_id}"
+                        for fname in os.listdir(model_folder):
+                            if fname.startswith(prefix) and os.path.isfile(
+                                os.path.join(model_folder, fname)
+                            ):
+                                found = True
+                                break
+                    except OSError:
+                        stale.append(idx)
+                        continue
+
+                    if not found:
+                        stale.append(idx)
+
+            if stale:
+                for idx in reversed(stale):
+                    custom_images.pop(idx)
+                has_changes = True
+                logger.info(
+                    "Pruned %d stale custom image(s) for %s",
+                    len(stale),
+                    getattr(metadata, "model_name", model_hash),
+                )
+
+        images = civitai.get("images")
+        if isinstance(images, list) and images:
+            stale: list[int] = []
+
+            for idx, img in enumerate(images):
+                if img.get("url", ""):
+                    # Has a remote fallback – keep it even if the local copy
+                    # is gone.
+                    continue
+
+                if not os.path.isdir(model_folder):
+                    stale.append(idx)
+                else:
+                    found = False
+                    try:
+                        prefix = f"image_{idx}."
+                        for fname in os.listdir(model_folder):
+                            if fname.startswith(prefix):
+                                found = True
+                                break
+                    except OSError:
+                        stale.append(idx)
+                        continue
+
+                    if not found:
+                        stale.append(idx)
+
+            if stale:
+                for idx in reversed(stale):
+                    images.pop(idx)
+                has_changes = True
+                logger.info(
+                    "Pruned %d stale image entry(ies) for %s",
+                    len(stale),
+                    getattr(metadata, "model_name", model_hash),
+                )
+
+        return has_changes
--- a/py/utils/utils.py
+++ b/py/utils/utils.py
@@ -15,30 +15,64 @@ def get_lora_info(lora_name):
        scanner = await ServiceRegistry.get_lora_scanner()
        cache = await scanner.get_cached_data()

+        lora_name_normalized = lora_name.replace("\\", "/")
+        lora_name_no_ext = lora_name_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if lora_name_no_ext.lower().endswith(ext):
+                lora_name_no_ext = lora_name_no_ext[: -len(ext)]
+                break
+
+        has_path = "/" in lora_name_no_ext
+        basename = os.path.basename(lora_name_no_ext) if has_path else lora_name_no_ext
+        best_fallback = None
+
        for item in cache.raw_data:
-            if item.get("file_name") == lora_name:
-                file_path = item.get("file_path")
-                if file_path:
-                    # Check all lora roots including extra paths
-                    all_roots = list(config.loras_roots or []) + list(
-                        config.extra_loras_roots or []
+            file_name = item.get("file_name", "")
+            folder = item.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+            if lora_name_no_ext not in (file_name_no_ext, path_name):
+                if has_path and file_name_no_ext == basename:
+                    if folder and lora_name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                        best_fallback = item
+                    elif best_fallback is None:
+                        best_fallback = item
+                continue
+
+            file_path = item.get("file_path")
+            if not file_path:
+                continue
+
+            all_roots = list(config.loras_roots or []) + list(
+                config.extra_loras_roots or []
+            )
+            for root in all_roots:
+                root = root.replace(os.sep, "/")
+                if file_path.startswith(root):
+                    relative_path = os.path.relpath(file_path, root).replace(
+                        os.sep, "/"
                    )
-                    for root in all_roots:
-                        root = root.replace(os.sep, "/")
-                        if file_path.startswith(root):
-                            relative_path = os.path.relpath(file_path, root).replace(
-                                os.sep, "/"
-                            )
-                            # Get trigger words from civitai metadata
-                            civitai = item.get("civitai", {})
-                            trigger_words = (
-                                civitai.get("trainedWords", []) if civitai else []
-                            )
-                            return relative_path, trigger_words
-                    # If not found in any root, return path with trigger words from cache
                    civitai = item.get("civitai", {})
-                    trigger_words = civitai.get("trainedWords", []) if civitai else []
-                    return file_path, trigger_words
+                    trigger_words = (
+                        civitai.get("trainedWords", []) if civitai else []
+                    )
+                    return relative_path, trigger_words
+            civitai = item.get("civitai", {})
+            trigger_words = civitai.get("trainedWords", []) if civitai else []
+            return file_path, trigger_words
+
+        if best_fallback:
+            file_path = best_fallback.get("file_path")
+            if file_path:
+                civitai = best_fallback.get("civitai", {})
+                trigger_words = civitai.get("trainedWords", []) if civitai else []
+                return file_path, trigger_words
+
        return lora_name, []

    try:
@@ -77,15 +111,54 @@ def get_lora_info_absolute(lora_name):
        scanner = await ServiceRegistry.get_lora_scanner()
        cache = await scanner.get_cached_data()

+        lora_name_normalized = lora_name.replace("\\", "/")
+        lora_name_no_ext = lora_name_normalized
+        for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+            if lora_name_no_ext.lower().endswith(ext):
+                lora_name_no_ext = lora_name_no_ext[: -len(ext)]
+                break
+
+        has_path = "/" in lora_name_no_ext
+        basename = os.path.basename(lora_name_no_ext) if has_path else lora_name_no_ext
+        best_fallback = None
+
        for item in cache.raw_data:
-            if item.get("file_name") == lora_name:
+            file_name = item.get("file_name", "")
+            folder = item.get("folder", "")
+            file_name_no_ext = file_name
+            for ext in (".safetensors", ".ckpt", ".pt", ".bin"):
+                if file_name_no_ext.lower().endswith(ext):
+                    file_name_no_ext = file_name_no_ext[: -len(ext)]
+                    break
+            path_name = f"{folder}/{file_name_no_ext}".replace("\\", "/") if folder else file_name_no_ext
+
+            if lora_name_no_ext == file_name_no_ext:
                file_path = item.get("file_path")
                if file_path:
-                    # Return absolute path directly
-                    # Get trigger words from civitai metadata
                    civitai = item.get("civitai", {})
                    trigger_words = civitai.get("trainedWords", []) if civitai else []
                    return file_path, trigger_words
+
+            if lora_name_no_ext == path_name:
+                file_path = item.get("file_path")
+                if file_path:
+                    civitai = item.get("civitai", {})
+                    trigger_words = civitai.get("trainedWords", []) if civitai else []
+                    return file_path, trigger_words
+
+            if has_path and file_name_no_ext == basename:
+                if folder and lora_name_no_ext.startswith(folder.replace("\\", "/") + "/"):
+                    best_fallback = item
+                elif best_fallback is None:
+                    best_fallback = item
+
+        if best_fallback:
+            file_path = best_fallback.get("file_path")
+            if file_path:
+                civitai = best_fallback.get("civitai", {})
+                trigger_words = civitai.get("trainedWords", []) if civitai else []
+                return file_path, trigger_words
+
        return lora_name, []

    try:
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.0.5"
+version = "1.0.9"
 license = {file = "LICENSE"}
 dependencies = [
    "aiohttp",
--- a/scripts/migrate_legacy_metadata.py
+++ b/scripts/migrate_legacy_metadata.py
@@ -0,0 +1,354 @@
+#!/usr/bin/env python3
+"""
+Migrate metadata from old sidecar JSON format to LoRA Manager's metadata.json format.
+
+This script automatically discovers model folders from LoRA Manager's settings.json,
+finds JSON files with the same basename as model files (e.g., `model.json` for
+`model.safetensors`), and migrates their content to the corresponding `.metadata.json` files.
+
+Fields migrated:
+- "activation text" → civitai.trainedWords (array of trigger words)
+- "preferred weight" → usage_tips.strength (LoRA only, skipped for Checkpoint)
+- "notes" → notes (user-defined notes)
+
+Supported model types: LoRA, Checkpoint
+
+Usage:
+    python scripts/migrate_legacy_metadata.py [--dry-run] [--verbose]
+
+The script will:
+1. Read settings.json to find all configured model folders
+2. Recursively scan for model files (.safetensors, .ckpt, .pt, .pth, .bin)
+3. Find corresponding legacy metadata JSON files
+4. Migrate data to .metadata.json files
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import os
+import re
+import sys
+from pathlib import Path
+from typing import Any
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(asctime)s - %(levelname)s - %(message)s",
+)
+logger = logging.getLogger(__name__)
+
+APP_NAME = "ComfyUI-LoRA-Manager"
+MODEL_EXTENSIONS = {".safetensors", ".ckpt", ".pt", ".pth", ".bin"}
+SECRET_PATTERN = re.compile(r"(key|token|secret|password|auth|credential)", re.IGNORECASE)
+
+
+def resolve_settings_path() -> Path:
+    repo_root = Path(__file__).parent.parent.resolve()
+    portable = repo_root / "settings.json"
+    if portable.exists():
+        payload = load_json(portable)
+        if isinstance(payload, dict) and payload.get("use_portable_settings") is True:
+            return portable
+
+    config_home = os.environ.get("XDG_CONFIG_HOME")
+    if config_home:
+        return Path(config_home).expanduser() / APP_NAME / "settings.json"
+    return Path.home() / ".config" / APP_NAME / "settings.json"
+
+
+def load_json(path: Path) -> dict[str, Any]:
+    try:
+        with path.open("r", encoding="utf-8") as f:
+            return json.load(f)
+    except FileNotFoundError:
+        return {}
+    except json.JSONDecodeError as exc:
+        logger.error(f"Invalid JSON in {path}: {exc}")
+        return {}
+    except OSError as exc:
+        logger.error(f"Cannot read {path}: {exc}")
+        return {}
+
+
+def expand_path(value: str) -> str:
+    return str(Path(value).expanduser().resolve(strict=False))
+
+
+def normalize_path_list(value: Any) -> list[str]:
+    if isinstance(value, str):
+        return [expand_path(value)] if value else []
+    if isinstance(value, list):
+        return [expand_path(item) for item in value if isinstance(item, str) and item]
+    return []
+
+
+def dedupe(values: list[str]) -> list[str]:
+    seen: set[str] = set()
+    result: list[str] = []
+    for value in values:
+        if value not in seen:
+            result.append(value)
+            seen.add(value)
+    return result
+
+
+def get_model_roots(settings: dict[str, Any]) -> dict[str, list[str]]:
+    roots: dict[str, list[str]] = {}
+    active_library = settings.get("active_library") or "default"
+    sources = [settings]
+    library = settings.get("libraries", {}).get(active_library)
+    if isinstance(library, dict):
+        sources.insert(0, library)
+    for source in sources:
+        folder_paths = source.get("folder_paths")
+        if isinstance(folder_paths, dict):
+            for key, value in folder_paths.items():
+                roots.setdefault(key, []).extend(normalize_path_list(value))
+    for default_key, folder_key in (
+        ("default_lora_root", "loras"),
+        ("default_checkpoint_root", "checkpoints"),
+        ("default_embedding_root", "embeddings"),
+        ("default_unet_root", "unet"),
+    ):
+        value = settings.get(default_key)
+        if isinstance(value, str) and value:
+            roots.setdefault(folder_key, []).append(expand_path(value))
+    return {key: dedupe(values) for key, values in roots.items()}
+
+
+def find_model_files(directory: Path) -> list[Path]:
+    model_files = []
+    for ext in MODEL_EXTENSIONS:
+        model_files.extend(directory.rglob(f"*{ext}"))
+    return model_files
+
+
+def find_legacy_metadata(model_path: Path) -> Path | None:
+    base_name = model_path.stem
+    legacy_path = model_path.with_name(f"{base_name}.json")
+    if legacy_path.exists() and legacy_path.is_file():
+        return legacy_path
+    return None
+
+
+def load_legacy_metadata(legacy_path: Path) -> dict[str, Any] | None:
+    try:
+        with open(legacy_path, "r", encoding="utf-8") as f:
+            return json.load(f)
+    except json.JSONDecodeError as e:
+        logger.error(f"Invalid JSON in legacy file {legacy_path}: {e}")
+        return None
+    except Exception as e:
+        logger.error(f"Error reading legacy file {legacy_path}: {e}")
+        return None
+
+
+def load_metadata(metadata_path: Path) -> dict[str, Any]:
+    if not metadata_path.exists():
+        return {}
+    try:
+        with open(metadata_path, "r", encoding="utf-8") as f:
+            return json.load(f)
+    except json.JSONDecodeError as e:
+        logger.warning(f"Invalid JSON in metadata file {metadata_path}: {e}. Starting fresh.")
+        return {}
+    except Exception as e:
+        logger.error(f"Error reading metadata file {metadata_path}: {e}")
+        return {}
+
+
+def save_metadata(metadata_path: Path, data: dict[str, Any], dry_run: bool = False) -> bool:
+    if dry_run:
+        logger.info(f"[DRY RUN] Would save metadata to: {metadata_path}")
+        return True
+    temp_path = metadata_path.with_suffix(".tmp")
+    try:
+        with open(temp_path, "w", encoding="utf-8") as f:
+            json.dump(data, f, indent=2, ensure_ascii=False)
+        os.replace(temp_path, metadata_path)
+        return True
+    except Exception as e:
+        logger.error(f"Error saving metadata to {metadata_path}: {e}")
+        if temp_path.exists():
+            try:
+                temp_path.unlink()
+            except:
+                pass
+        return False
+
+
+def migrate_metadata(
+    legacy_data: dict[str, Any],
+    existing_metadata: dict[str, Any],
+    model_type: str
+) -> dict[str, Any] | None:
+    metadata = existing_metadata.copy()
+    changes_made = False
+    if "civitai" not in metadata:
+        metadata["civitai"] = {}
+    activation_text = legacy_data.get("activation text")
+    if activation_text and isinstance(activation_text, str):
+        trigger_words = [
+            word.strip()
+            for word in activation_text.replace("\n", ",").split(",")
+            if word.strip()
+        ]
+        if trigger_words:
+            existing_trained = metadata["civitai"].get("trainedWords", [])
+            if not isinstance(existing_trained, list):
+                existing_trained = []
+            merged = list(dict.fromkeys(existing_trained + trigger_words))
+            if merged != existing_trained:
+                metadata["civitai"]["trainedWords"] = merged
+                changes_made = True
+                logger.debug(f"  Migrated activation text: {trigger_words}")
+    if model_type == "lora":
+        preferred_weight = legacy_data.get("preferred weight")
+        if preferred_weight is not None:
+            try:
+                weight_value = float(preferred_weight)
+                usage_tips_str = metadata.get("usage_tips", "{}")
+                if isinstance(usage_tips_str, str):
+                    try:
+                        usage_tips = json.loads(usage_tips_str)
+                    except json.JSONDecodeError:
+                        usage_tips = {}
+                elif isinstance(usage_tips_str, dict):
+                    usage_tips = usage_tips_str
+                else:
+                    usage_tips = {}
+                if "strength" not in usage_tips:
+                    usage_tips["strength"] = weight_value
+                    metadata["usage_tips"] = json.dumps(usage_tips, ensure_ascii=False)
+                    changes_made = True
+                    logger.debug(f"  Migrated preferred weight: {weight_value}")
+            except (ValueError, TypeError) as e:
+                logger.warning(f"  Could not parse preferred weight '{preferred_weight}': {e}")
+    else:
+        if legacy_data.get("preferred weight") is not None:
+            logger.debug("  Skipping 'preferred weight' for non-LoRA model")
+    notes = legacy_data.get("notes")
+    if notes and isinstance(notes, str) and notes.strip():
+        existing_notes = metadata.get("notes", "")
+        if not existing_notes:
+            metadata["notes"] = notes.strip()
+            changes_made = True
+            logger.debug("  Migrated notes")
+        elif notes.strip() not in existing_notes:
+            metadata["notes"] = f"{existing_notes}\n\n{notes.strip()}".strip()
+            changes_made = True
+            logger.debug("  Appended notes")
+    return metadata if changes_made else None
+
+
+def process_model(model_path: Path, model_type: str, dry_run: bool = False) -> bool:
+    legacy_path = find_legacy_metadata(model_path)
+    if not legacy_path:
+        return True
+    logger.info(f"Processing: {model_path.name} ({model_type})")
+    logger.info(f"  Found legacy metadata: {legacy_path.name}")
+    legacy_data = load_legacy_metadata(legacy_path)
+    if legacy_data is None:
+        return False
+    metadata_path = model_path.with_suffix(".metadata.json")
+    existing_metadata = load_metadata(metadata_path)
+    migrated = migrate_metadata(legacy_data, existing_metadata, model_type)
+    if migrated is None:
+        logger.info("  No changes needed (fields already exist or no migratable data)")
+        return True
+    if save_metadata(metadata_path, migrated, dry_run):
+        logger.info(f"  ✓ Successfully migrated metadata to: {metadata_path.name}")
+        return True
+    else:
+        logger.error("  ✗ Failed to save metadata")
+        return False
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description="Migrate legacy metadata JSON files to LoRA Manager's metadata.json format.",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog="""
+Examples:
+  python scripts/migrate_legacy_metadata.py
+  python scripts/migrate_legacy_metadata.py --dry-run
+  python scripts/migrate_legacy_metadata.py --verbose
+        """
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="Preview changes without modifying any files"
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        action="store_true",
+        help="Enable verbose output"
+    )
+    args = parser.parse_args()
+    if args.verbose:
+        logging.getLogger().setLevel(logging.DEBUG)
+    settings_path = resolve_settings_path()
+    logger.info(f"Using settings: {settings_path}")
+    settings = load_json(settings_path)
+    if not settings:
+        logger.error("Could not load settings.json. Please ensure LoRA Manager is configured.")
+        return 1
+    roots = get_model_roots(settings)
+    if not roots:
+        logger.error("No model folders configured in settings.json.")
+        return 1
+    lora_roots = roots.get("loras", [])
+    checkpoint_roots = roots.get("checkpoints", []) + roots.get("unet", [])
+    all_roots = []
+    for root_list in [lora_roots, checkpoint_roots]:
+        for root in root_list:
+            path = Path(root)
+            if path.exists() and path.is_dir():
+                all_roots.append((path, "lora" if root in lora_roots else "checkpoint"))
+    if not all_roots:
+        logger.error("No valid model folders found.")
+        return 1
+    logger.info(f"Found {len(lora_roots)} LoRA root(s), {len(checkpoint_roots)} Checkpoint root(s)")
+    processed = 0
+    migrated = 0
+    errors = 0
+    skipped = 0
+    lora_count = 0
+    checkpoint_count = 0
+    for root_path, model_type in all_roots:
+        logger.info(f"Scanning: {root_path} ({model_type})")
+        model_files = find_model_files(root_path)
+        logger.debug(f"  Found {len(model_files)} model files")
+        for model_path in model_files:
+            legacy_path = find_legacy_metadata(model_path)
+            if not legacy_path:
+                skipped += 1
+                continue
+            processed += 1
+            if process_model(model_path, model_type, dry_run=args.dry_run):
+                migrated += 1
+                if model_type == "lora":
+                    lora_count += 1
+                else:
+                    checkpoint_count += 1
+            else:
+                errors += 1
+    logger.info("\n" + "=" * 50)
+    logger.info("Migration Summary:")
+    logger.info(f"  Models with legacy metadata: {processed}")
+    logger.info(f"  Successfully migrated: {migrated}")
+    logger.info(f"    - LoRA models: {lora_count}")
+    logger.info(f"    - Checkpoint models: {checkpoint_count}")
+    logger.info(f"  Errors: {errors}")
+    logger.info(f"  Skipped (no legacy file): {skipped}")
+    if args.dry_run:
+        logger.info("\n  [DRY RUN MODE - No files were modified]")
+    return 0 if errors == 0 else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())
--- a/settings.json.example
+++ b/settings.json.example
@@ -10,13 +10,14 @@
      "C:/path/to/your/checkpoints_folder",
      "C:/path/to/another/checkpoints_folder"
    ],
+    "unet": [
+      "C:/path/to/your/diffusion_models_folder",
+      "C:/path/to/another/diffusion_models_folder"
+    ],
    "embeddings": [
      "C:/path/to/your/embeddings_folder",
      "C:/path/to/another/embeddings_folder"
    ]
  },
-  "example_images_open_mode": "system",
-  "example_images_local_root": "",
-  "example_images_open_uri_template": "",
  "auto_organize_exclusions": []
 }
--- a/static/css/components/batch-import-modal.css
+++ b/static/css/components/batch-import-modal.css
@@ -87,7 +87,7 @@

 .checkbox-label input[type="checkbox"]:checked + .checkmark::after {
    content: '\f00c';
-    font-family: 'Font Awesome 6 Free';
+    font-family: 'Font Awesome 6 Free', sans-serif;
    font-weight: 900;
    color: var(--lora-text);
    font-size: 12px;
--- a/static/css/components/card.css
+++ b/static/css/components/card.css
@@ -22,6 +22,7 @@
    transition: transform 160ms ease-out;
    aspect-ratio: 896/1152; /* Preserve aspect ratio */
    max-width: 260px; /* Base size */
+    min-width: 200px; /* Prevent cards from becoming too narrow */
    width: 100%;
    margin: 0 auto;
    cursor: pointer;
@@ -328,7 +329,6 @@
 }

 .card-actions i {
-    margin-left: var(--space-1);
    cursor: pointer;
    color: white;
    transition: opacity 0.2s, transform 0.15s ease;
@@ -370,7 +370,16 @@
    text-shadow: 0 0 5px rgba(255, 193, 7, 0.5);
 }

-/* 响应式设计 */
+@media (max-width: 1200px) {
+    .card-grid {
+        grid-template-columns: repeat(auto-fill, minmax(220px, 1fr));
+    }
+    
+    .model-card {
+        max-width: 240px;
+        min-width: 180px;
+    }
+}
@media (max-width: 768px) {
    .card-grid {
        grid-template-columns: minmax(260px, 1fr); /* Adjusted minimum size for mobile */
@@ -378,6 +387,7 @@
    
    .model-card {
        max-width: 100%; /* Allow cards to fill available space on mobile */
+        min-width: 200px;
    }
 }

@@ -497,11 +507,91 @@
    background: rgba(0,0,0,0.18); /* Optional: subtle background for contrast */
 }

+/* Version row — flex container for badges + version names */
+.version-row {
+    display: flex;
+    flex-wrap: wrap;
+    align-items: center;
+    gap: 3px;
+    margin-top: 2px;
+}
+
+/* Badge + version-name binding: they wrap as a single unit */
+.badge-version-unit {
+    display: inline-flex;
+    align-items: center;
+    gap: 3px;
+    min-width: 0;
+    flex-shrink: 0;
+}
+
 /* Medium density adjustments for version name */
 .medium-density .version-name {
    font-size: 0.8em;
 }

+.medium-density .badge-version-unit .version-name {
+    max-width: 90px;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+
+/* Compact density adjustments for version name */
+.compact-density .version-name {
+    font-size: 0.75em;
+}
+
+.compact-density .badge-version-unit .version-name {
+    max-width: 70px;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+
+.medium-density .version-row {
+    gap: 2px;
+}
+
+/* HIGH / LOW badges — shown inline before version name in card footer */
+.hl-badge {
+    display: inline-block;
+    font-size: 0.7em;
+    font-weight: 600;
+    line-height: 1.1;
+    padding: 1px 5px;
+    border-radius: var(--border-radius-xs);
+    border: 1px solid rgba(255, 255, 255, 0.2);
+    white-space: nowrap;
+}
+
+.hl-badge--high {
+    color: oklch(75% 0.12 230);
+    background: oklch(55% 0.15 240 / 0.25);
+    border-color: oklch(60% 0.18 250 / 0.3);
+}
+
+.hl-badge--low {
+    color: oklch(78% 0.10 185);
+    background: oklch(50% 0.10 190 / 0.25);
+    border-color: oklch(55% 0.12 195 / 0.3);
+}
+
+.medium-density .hl-badge {
+    font-size: 0.65em;
+}
+
+.compact-density .hl-badge {
+    font-size: 0.62em;
+    padding: 0px 4px;
+}
+
+/* Hide version-related elements when setting is disabled */
+body.hide-card-version .civitai-version,
+body.hide-card-version .hl-badge {
+    display: none;
+}
+
 /* Compact density adjustments for version name */
 .compact-density .version-name {
    font-size: 0.75em;
@@ -558,8 +648,13 @@
    position: absolute;
    box-sizing: border-box;
    transition: transform 160ms ease-out;
-    margin: 0; /* Remove margins, positioning is handled by VirtualScroller */
-    width: 100%; /* Allow width to be set by the VirtualScroller */
+    margin: 0;
+    width: 100%;
+}
+
+/* Allow cards to grow beyond 260px in virtual scroll mode */
+.virtual-scroll-item.model-card {
+    max-width: none;
 }

 .virtual-scroll-item:hover {
@@ -571,11 +666,11 @@
 .card-grid.virtual-scroll {
    display: block;
    position: relative;
-    margin: 0 auto;
+    margin: 0; /* Remove auto margins - positioning handled by VirtualScroller leftOffset */
    padding: 4px 0; /* Add top/bottom padding equivalent to card padding */
    height: auto;
    width: 100%;
-    max-width: 1400px; /* Keep the max-width from original grid */
+    max-width: none; /* Remove max-width constraint - handled by VirtualScroller */
    box-sizing: border-box; /* Include padding in width calculation */
    overflow-x: hidden; /* Prevent horizontal overflow */
 }
--- a/static/css/components/header.css
+++ b/static/css/components/header.css
@@ -22,6 +22,22 @@
  gap: 1rem;
 }

+/* Left section: Logo + Navigation */
+.header-left {
+  display: flex;
+  align-items: center;
+  gap: 1rem;
+  flex-shrink: 0;
+}
+
+/* Right section: Controls */
+.header-right {
+  display: flex;
+  align-items: center;
+  gap: 1rem;
+  flex-shrink: 0;
+}
+
 /* Responsive header container for larger screens */
@media (min-width: 2150px) {
  .header-container {
@@ -77,6 +93,7 @@
  align-items: center;
  gap: 0.5rem;
  font-size: 0.9rem;
+  white-space: nowrap;
 }

 .nav-item:hover,
@@ -97,13 +114,99 @@
  color: white;
 }

-/* Header search */
+/* Header search - Centered with VS Code command palette style */
 .header-search {
  flex: 1;
-  max-width: 400px;
+  display: flex;
+  justify-content: center;
+  max-width: 600px;
+  margin: 0 auto;
  transition: opacity 0.2s ease;
 }

+/* VS Code command palette style search container */
+.header-search .search-container {
+  width: 100%;
+  max-width: 600px;
+  position: relative;
+  display: flex;
+  align-items: center;
+  background: var(--input-bg, var(--card-bg));
+  border: 1px solid var(--border-color);
+  border-radius: var(--border-radius-sm, 6px);
+  transition: all 0.2s ease;
+  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08);
+  overflow: hidden;
+}
+
+.header-search .search-container:focus-within {
+  border-color: var(--lora-accent);
+  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08), 0 0 0 1px var(--lora-accent);
+}
+
+.header-search input {
+  flex: 1;
+  width: 100%;
+  padding: 0.5rem 0.75rem;
+  padding-left: 2.25rem !important;
+  padding-right: 5rem !important;
+  border: none;
+  background: transparent;
+  color: var(--text-color);
+  font-size: 0.95rem;
+  outline: none;
+}
+
+.header-search input::placeholder {
+  color: var(--text-muted);
+}
+
+.header-search .search-icon {
+  position: absolute;
+  left: 0.75rem;
+  color: var(--text-muted);
+  font-size: 0.9rem;
+  pointer-events: none;
+}
+
+.header-search .search-options-toggle,
+.header-search .search-filter-toggle {
+  position: absolute;
+  right: 0.5rem;
+  width: 28px;
+  height: 28px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  background: transparent;
+  border: none;
+  color: var(--text-muted);
+  cursor: pointer;
+  border-radius: var(--border-radius-xs, 4px);
+  transition: all 0.2s ease;
+}
+
+.header-search .search-options-toggle {
+  right: 2.25rem;
+}
+
+.header-search .search-options-toggle:hover,
+.header-search .search-filter-toggle:hover {
+  background: var(--lora-surface-hover, oklch(95% 0.02 256));
+  color: var(--lora-accent);
+}
+
+.header-search .filter-badge {
+  position: absolute;
+  top: 2px;
+  right: 2px;
+  width: 8px;
+  height: 8px;
+  background: var(--lora-accent);
+  border-radius: 50%;
+  font-size: 0;
+}
+
 /* Disabled state for header search */
 .header-search.disabled {
  opacity: 0.5;
@@ -247,44 +350,207 @@
  opacity: 1;
 }

-/* Mobile adjustments */
-@media (max-width: 768px) {
-  .app-title {
-    display: none;
-    /* Hide text title on mobile */
+/* Hamburger menu button - hidden by default */
+.hamburger-menu-btn {
+  display: none;
+  width: 32px;
+  height: 32px;
+  border-radius: 50%;
+  background: var(--card-bg);
+  border: 1px solid var(--border-color);
+  color: var(--text-color);
+  align-items: center;
+  justify-content: center;
+  cursor: pointer;
+  transition: all 0.2s ease;
+  flex-shrink: 0;
+}
+
+.hamburger-menu-btn:hover {
+  background: var(--lora-accent);
+  color: white;
+}
+
+/* Hamburger dropdown menu */
+.hamburger-dropdown {
+  display: none;
+  position: absolute;
+  top: 100%;
+  right: 0;
+  margin-top: 8px;
+  background: var(--card-bg);
+  border: 1px solid var(--border-color);
+  border-radius: var(--border-radius-sm, 6px);
+  box-shadow: 0 4px 16px rgba(0, 0, 0, 0.15);
+  padding: 0.5rem;
+  min-width: 160px;
+  z-index: var(--z-dropdown, 200);
+}
+
+.hamburger-dropdown.active {
+  display: flex;
+  flex-direction: column;
+  gap: 0.25rem;
+}
+
+.hamburger-dropdown .dropdown-item {
+  display: flex;
+  align-items: center;
+  gap: 0.75rem;
+  padding: 0.5rem 0.75rem;
+  border-radius: var(--border-radius-xs, 4px);
+  color: var(--text-color);
+  cursor: pointer;
+  transition: all 0.2s ease;
+  font-size: 0.9rem;
+  white-space: nowrap;
+}
+
+.hamburger-dropdown .dropdown-item:hover {
+  background: var(--lora-surface-hover, oklch(95% 0.02 256));
+  color: var(--lora-accent);
+}
+
+.hamburger-dropdown .dropdown-item i {
+  width: 20px;
+  text-align: center;
+}
+
+.hamburger-dropdown .dropdown-divider {
+  height: 1px;
+  background: var(--border-color);
+  margin: 0.25rem 0;
+}
+
+/* Responsive: Early optimization at 1200px - reduce gaps and padding */
+@media (max-width: 1200px) {
+  .header-container {
+    gap: 0.75rem;
+    padding: 0 12px;
+  }
+
+  .main-nav {
+    gap: 0.25rem;
+  }
+
+  .nav-item {
+    padding: 0.25rem 0.5rem;
+    font-size: 0.85rem;
  }

  .header-controls {
-    gap: 4px;
+    gap: 6px;
  }

-  .header-controls>div {
-    width: 28px;
-    height: 28px;
+  .header-controls > div {
+    width: 30px;
+    height: 30px;
+  }
+}
+
+/* Responsive: Hide nav icons at 1100px to save space */
+@media (max-width: 1100px) {
+  .nav-item {
+    gap: 0;
+    padding: 0.25rem 0.4rem;
+  }
+
+  .nav-item i {
+    display: none;
+  }
+
+  .header-search {
+    max-width: 450px;
+  }
+}
+
+@media (max-width: 950px) {
+  .app-title {
+    display: none !important;
+  }
+
+  .header-container {
+    padding: 0 10px;
+    gap: 0.5rem;
+  }
+
+  .header-controls {
+    display: none !important;
+  }
+
+  .hamburger-menu-btn {
+    display: flex !important;
+  }
+
+  .hamburger-dropdown {
+    display: none;
+  }
+
+  .hamburger-dropdown.active {
+    display: flex;
  }

  .header-search {
    max-width: none;
-    margin: 0 0.5rem;
+    margin: 0;
+    flex: 1;
+    min-width: 200px;
  }

  .main-nav {
-    margin-right: 0.5rem;
+    gap: 0.25rem;
+    margin-right: 0;
+  }
+
+  .nav-item {
+    padding: 0.25rem 0.35rem;
+    font-size: 0.8rem;
  }
 }

-/* For very small screens */
+/* Responsive: Compact mode at 768px */
+@media (max-width: 768px) {
+  .header-search input {
+    padding: 0.4rem 0.6rem;
+    padding-left: 2rem !important;
+    padding-right: 4.5rem !important;
+    font-size: 0.9rem;
+  }
+
+  .header-search .search-container {
+    border-radius: var(--border-radius-xs, 4px);
+  }
+}
+
+/* For very small screens - switch nav to icons only */
@media (max-width: 600px) {
  .header-container {
    padding: 0 8px;
+    gap: 0.4rem;
  }

  .main-nav {
-    display: none;
-    /* Hide navigation on very small screens */
+    display: flex;
+    gap: 0.15rem;
+    margin-right: 0;
  }

-  .header-search {
-    flex: 1;
+  .nav-item {
+    padding: 0.25rem;
+    font-size: 0.75rem;
+  }
+
+  .nav-item span {
+    display: none;
+  }
+
+  .nav-item i {
+    display: block;
+    font-size: 1rem;
  }
 }
+
+/* Position relative for hamburger menu positioning */
+.header-right {
+  position: relative;
+}
--- a/static/css/components/lora-modal/lora-modal.css
+++ b/static/css/components/lora-modal/lora-modal.css
@@ -255,25 +255,28 @@
    transform: translateY(-2px);
 }

-/* File name copy styles */
-.file-name-wrapper {
+/* Editable inline field styles (file name, version name, etc.) */
+.file-name-wrapper,
+.version-name-wrapper {
    display: flex;
    align-items: center;
    gap: 8px;
-    padding: 4px;
+    padding: 4px 0;
    border-radius: var(--border-radius-xs);
    transition: background-color 0.2s;
    position: relative;
 }

-.file-name-content {
-    padding: 2px 4px;
+.file-name-content,
+.version-name-content {
+    padding: 2px 4px 2px 0;
    border-radius: var(--border-radius-xs);
    border: 1px solid transparent;
    flex: 1;
 }

-.file-name-wrapper.editing .file-name-content {
+.file-name-wrapper.editing .file-name-content,
+.version-name-wrapper.editing .version-name-content {
    border: 1px solid var(--lora-accent);
    background: var(--bg-color);
    outline: none;
@@ -283,7 +286,8 @@
 .edit-model-name-btn,
 .edit-file-name-btn,
 .edit-base-model-btn,
-.edit-model-description-btn {
+.edit-model-description-btn,
+.edit-version-name-btn {
    background: transparent;
    border: none;
    color: var(--text-color);
@@ -299,9 +303,11 @@
 .edit-file-name-btn.visible,
 .edit-base-model-btn.visible,
 .edit-model-description-btn.visible,
+.edit-version-name-btn.visible,
 .model-name-header:hover .edit-model-name-btn,
 .file-name-wrapper:hover .edit-file-name-btn,
 .base-model-display:hover .edit-base-model-btn,
+.version-name-wrapper:hover .edit-version-name-btn,
 .model-name-header:hover .edit-model-description-btn {
    opacity: 0.5;
 }
@@ -309,14 +315,16 @@
 .edit-model-name-btn:hover,
 .edit-file-name-btn:hover,
 .edit-base-model-btn:hover,
-.edit-model-description-btn:hover {
+.edit-model-description-btn:hover,
+.edit-version-name-btn:hover {
    opacity: 0.8 !important;
    background: rgba(0, 0, 0, 0.05);
 }

 [data-theme="dark"] .edit-model-name-btn:hover,
 [data-theme="dark"] .edit-file-name-btn:hover,
-[data-theme="dark"] .edit-base-model-btn:hover {
+[data-theme="dark"] .edit-base-model-btn:hover,
+[data-theme="dark"] .edit-version-name-btn:hover {
    background: rgba(255, 255, 255, 0.05);
 }

@@ -338,7 +346,7 @@
 }

 .base-model-content {
-    padding: 2px 4px;
+    padding: 2px 4px 2px 0;
    border-radius: var(--border-radius-xs);
    border: 1px solid transparent;
    color: var(--text-color);
--- a/static/css/components/lora-modal/versions.css
+++ b/static/css/components/lora-modal/versions.css
@@ -374,11 +374,23 @@
    background: color-mix(in oklch, var(--lora-surface) 35%, transparent);
 }

+.version-action-disabled {
+    background: transparent;
+    border-color: var(--border-color);
+    color: var(--text-muted);
+    opacity: 0.6;
+    cursor: not-allowed;
+}
+
 .version-action:disabled {
    opacity: 0.6;
    cursor: not-allowed;
 }

+.version-action-disabled-wrapper {
+    display: inline-flex;
+}
+
 .versions-loading-state,
 .versions-empty,
 .versions-error {
--- a/static/css/components/media-viewer.css
+++ b/static/css/components/media-viewer.css
@@ -0,0 +1,124 @@
+.media-viewer-overlay {
+  position: fixed;
+  top: 0;
+  left: 0;
+  right: 0;
+  bottom: 0;
+  background: rgba(0, 0, 0, 0);
+  z-index: 10000;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  cursor: pointer;
+  transition: background 0.3s ease;
+}
+
+.media-viewer-overlay.active {
+  background: rgba(0, 0, 0, 0.92);
+}
+
+.media-viewer-close {
+  position: fixed;
+  top: 16px;
+  right: 16px;
+  width: 40px;
+  height: 40px;
+  border-radius: 50%;
+  background: rgba(255, 255, 255, 0.1);
+  border: none;
+  color: #fff;
+  font-size: 18px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  cursor: pointer;
+  z-index: 10001;
+  transition: background 0.2s ease;
+  opacity: 0;
+}
+
+.media-viewer-overlay.active .media-viewer-close {
+  opacity: 1;
+}
+
+.media-viewer-close:hover {
+  background: rgba(255, 255, 255, 0.25);
+}
+
+.media-viewer-content-container {
+  display: flex;
+  flex-direction: column;
+  align-items: center;
+  justify-content: center;
+  max-width: 90vw;
+  max-height: 95vh;
+  cursor: default;
+}
+
+.media-viewer-media {
+  display: block;
+  max-width: 90vw;
+  max-height: 85vh;
+  object-fit: contain;
+  border-radius: 4px;
+  box-shadow: 0 4px 24px rgba(0, 0, 0, 0.4);
+}
+
+.media-viewer-video {
+  max-height: 80vh;
+}
+
+.media-viewer-counter {
+  margin-top: 8px;
+  color: rgba(255, 255, 255, 0.5);
+  font-size: 0.85em;
+  text-align: center;
+  min-height: 1.2em;
+}
+
+.media-viewer-title {
+  margin-top: 4px;
+  color: rgba(255, 255, 255, 0.7);
+  font-size: 0.9em;
+  text-align: center;
+  max-width: 90vw;
+  overflow: hidden;
+  text-overflow: ellipsis;
+  white-space: nowrap;
+}
+
+.media-viewer-nav {
+  position: fixed;
+  top: 50%;
+  transform: translateY(-50%);
+  width: 48px;
+  height: 80px;
+  border-radius: 4px;
+  background: rgba(255, 255, 255, 0.06);
+  border: none;
+  color: #fff;
+  font-size: 24px;
+  display: flex;
+  align-items: center;
+  justify-content: center;
+  cursor: pointer;
+  z-index: 10001;
+  opacity: 0;
+  transition: opacity 0.2s ease, background 0.2s ease;
+}
+
+.media-viewer-overlay.active .media-viewer-nav {
+  opacity: 1;
+}
+
+.media-viewer-nav:hover {
+  background: rgba(255, 255, 255, 0.18);
+}
+
+.media-viewer-prev {
+  left: 16px;
+}
+
+.media-viewer-next {
+  right: 16px;
+}
--- a/static/css/components/menu.css
+++ b/static/css/components/menu.css
@@ -41,6 +41,63 @@
    text-align: center;
 }

+/* Section Headers */
+.context-menu-section-header {
+    padding: 6px 12px 2px;
+    font-size: 11px;
+    font-weight: 600;
+    text-transform: uppercase;
+    letter-spacing: 0.5px;
+    color: var(--text-muted);
+    cursor: default;
+    user-select: none;
+}
+
+/* Submenu */
+.context-menu-item.has-submenu {
+    position: relative;
+    justify-content: space-between;
+}
+
+.submenu-arrow {
+    margin-left: auto;
+    font-size: 10px;
+    width: auto !important;
+}
+
+.context-submenu {
+    position: absolute;
+    left: calc(100% - 4px);
+    top: -1px;
+    display: none;
+    background: var(--lora-surface);
+    border: 1px solid var(--border-color);
+    border-radius: var(--border-radius-xs);
+    padding: 0;
+    min-width: 200px;
+    box-shadow: 0 2px 10px rgba(0, 0, 0, 0.2);
+    z-index: 1001;
+    backdrop-filter: blur(10px);
+}
+
+.context-submenu .context-menu-item {
+    white-space: nowrap;
+    margin: 0;
+}
+
+.context-submenu .context-menu-item:first-child {
+    padding-top: 9px;
+}
+
+.context-submenu .context-menu-item:last-child {
+    padding-bottom: 9px;
+}
+
+.context-submenu.flip-left {
+    left: auto;
+    right: 100%;
+}
+
 /* NSFW Level Selector */
 .nsfw-level-selector {
    position: fixed;
--- a/static/css/components/modal/delete-modal.css
+++ b/static/css/components/modal/delete-modal.css
@@ -33,6 +33,39 @@
    animation: modalFadeIn 0.2s ease-out;
 }

+#resolveFilenameConflictsModal .confirmation-message {
+    color: var(--text-color);
+    margin: var(--space-2) 0;
+    font-size: 1em;
+    line-height: 1.5;
+}
+
+#resolveFilenameConflictsModal .resolve-conflicts-detail {
+    color: var(--text-color);
+    margin: var(--space-2) 0;
+    font-size: 0.95em;
+    line-height: 1.5;
+}
+
+#resolveFilenameConflictsModal .resolve-conflicts-detail code {
+    background: var(--lora-surface);
+    padding: 2px 6px;
+    border-radius: 3px;
+    font-family: monospace;
+    border: 1px solid var(--lora-border);
+}
+
+#resolveFilenameConflictsModal .resolve-conflicts-impact {
+    background: var(--lora-surface);
+    border: 1px solid var(--lora-border);
+    border-radius: var(--border-radius-sm);
+    padding: var(--space-2);
+    margin: var(--space-2) 0;
+    color: var(--text-color);
+    text-align: left;
+    line-height: 1.5;
+}
+
 .delete-model-info,
 .exclude-model-info {
    /* Update info display styling */
--- a/static/css/components/modal/settings-modal.css
+++ b/static/css/components/modal/settings-modal.css
@@ -1369,3 +1369,14 @@ input:checked + .toggle-slider:before {
    background: var(--lora-error);
    color: white;
 }
+
+/* Highlight animation for setting items targeted from Doctor actions */
+@keyframes settings-highlight-pulse {
+    0%, 100% { box-shadow: 0 0 0 0 rgba(from var(--lora-accent) r g b / 0.4); }
+    50% { box-shadow: 0 0 0 4px rgba(from var(--lora-accent) r g b / 0.2); }
+}
+
+.settings-setting-highlight {
+    animation: settings-highlight-pulse 1.5s ease-in-out 3;
+    border-radius: var(--border-radius-xs);
+}
--- a/static/css/components/recipe-modal.css
+++ b/static/css/components/recipe-modal.css
@@ -4,15 +4,20 @@
    justify-content: flex-start;
    align-items: flex-start;
    border-bottom: 1px solid var(--lora-border);
-    padding-bottom: 10px;
-    margin-bottom: 10px;
+    padding-bottom: var(--space-2);
+    margin-bottom: var(--space-3);
+    position: relative;
 }

 .recipe-modal-header h2 {
-    font-size: 1.4em; /* Reduced from default h2 size */
-    line-height: 1.3;
-    margin: 0;
-    max-height: 2.6em; /* Limit to 2 lines */
+    margin: 0 0 var(--space-1);
+    padding: var(--space-1);
+    border-radius: var(--border-radius-xs);
+    font-size: 1.5em;
+    font-weight: 600;
+    line-height: 1.2;
+    color: var(--text-color);
+    max-height: 2.8em;
    overflow: hidden;
    text-overflow: ellipsis;
    display: -webkit-box;
@@ -127,7 +132,7 @@
 /* Recipe Tags styles */
 .recipe-tags-container {
    position: relative;
-    margin-top: 6px;
+    margin-top: 0;
    margin-bottom: 10px;
 }

@@ -225,6 +230,62 @@
    overflow: hidden;
 }

+/* Recipe Header Actions */
+.recipe-header-actions {
+    display: flex;
+    align-items: center;
+    gap: var(--space-2);
+    flex-wrap: wrap;
+    width: 100%;
+    margin-bottom: var(--space-1);
+    flex-shrink: 0;
+    min-height: 0;
+}
+
+.recipe-header-actions:empty {
+    display: none;
+}
+
+.recipe-source-url-btn {
+    display: inline-flex;
+    align-items: center;
+    gap: 6px;
+    padding: 6px 12px;
+    background: rgba(0, 0, 0, 0.03);
+    border: 1px solid rgba(0, 0, 0, 0.1);
+    border-radius: var(--border-radius-sm);
+    color: var(--text-color);
+    cursor: pointer;
+    font-weight: 500;
+    font-size: 0.9em;
+    transition: all 0.2s;
+    white-space: nowrap;
+}
+
+[data-theme="dark"] .recipe-source-url-btn {
+    background: rgba(255, 255, 255, 0.03);
+    border: 1px solid var(--lora-border);
+}
+
+.recipe-source-url-btn:hover {
+    background: oklch(var(--lora-accent-l) var(--lora-accent-c) var(--lora-accent-h) / 0.1);
+    border-color: var(--lora-accent);
+    transform: translateY(-1px);
+}
+
+.recipe-source-url-btn i {
+    font-size: 14px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+}
+
+@media (max-height: 860px) {
+    .recipe-header-actions {
+        padding-bottom: 4px;
+    }
+}
+
 /* Top Section: Preview and Gen Params */
 .recipe-top-section {
    display: grid;
@@ -396,14 +457,54 @@
    flex-direction: column;
 }

-.recipe-gen-params h3 {
-    margin-top: 0;
+.gen-params-header-row {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
    margin-bottom: var(--space-2);
-    font-size: 1.2em;
-    color: var(--text-color);
    padding-bottom: var(--space-1);
    border-bottom: 1px solid var(--border-color);
    flex-shrink: 0;
+    gap: 8px;
+}
+
+.gen-params-header-row h3 {
+    margin: 0;
+    font-size: 1.2em;
+    color: var(--text-color);
+}
+
+/* Inline toggle for lora strip setting */
+.lora-strip-toggle {
+    flex-shrink: 0;
+    gap: 6px;
+}
+
+.lora-strip-toggle .inline-toggle-label {
+    font-size: 0.78em;
+    white-space: nowrap;
+    opacity: 0.7;
+    transition: opacity 0.2s;
+}
+
+.lora-strip-toggle:hover .inline-toggle-label {
+    opacity: 1;
+}
+
+.lora-strip-toggle .toggle-switch {
+    width: 32px;
+    height: 16px;
+}
+
+.lora-strip-toggle .toggle-slider:before {
+    height: 10px;
+    width: 10px;
+    left: 3px;
+    bottom: 3px;
+}
+
+.lora-strip-toggle .toggle-switch input:checked + .toggle-slider:before {
+    transform: translateX(16px);
 }

 .gen-params-container {
@@ -1043,13 +1144,13 @@
    }

    .recipe-modal-header {
-        padding-bottom: 6px;
-        margin-bottom: 8px;
+        padding-bottom: var(--space-1);
+        margin-bottom: var(--space-2);
    }

    .recipe-modal-header h2 {
-        font-size: 1.25em;
-        max-height: 2.5em;
+        font-size: 1.3em;
+        max-height: 2.4em;
    }

    .recipe-tags-container {
--- a/static/css/components/shared.css
+++ b/static/css/components/shared.css
@@ -67,7 +67,6 @@

 .early-access-info {
    display: none;
-    position: absolute;
    top: 100%;
    right: 0;
    background: var(--card-bg);
@@ -97,7 +96,6 @@

 .local-path {
    display: none;
-    position: absolute;
    top: 100%;
    right: 0;
    background: var(--card-bg);
--- a/static/css/components/sidebar.css
+++ b/static/css/components/sidebar.css
@@ -271,11 +271,16 @@

 /* Enhanced Sidebar Breadcrumb Styles */
 .sidebar-breadcrumb-container {
-    margin-top: 8px;
    padding: 8px 0;
    border-bottom: 1px solid var(--border-color);
    background: var(--bg-color);
    border-radius: var(--border-radius-xs);
+    /* Sticky positioning to stick below header when scrolling
+       top: 0 means stick at the top of the scroll container (page-content)
+       which is at header height (48px) from the viewport */
+    position: sticky;
+    top: 0;
+    z-index: calc(var(--z-header) - 1);
 }

 .sidebar-breadcrumb-nav {
@@ -284,7 +289,6 @@
    flex-wrap: wrap;
    gap: 4px;
    font-size: 0.85em;
-    padding: 0 8px;
 }

 .sidebar-breadcrumb-item {
--- a/static/css/layout.css
+++ b/static/css/layout.css
@@ -21,7 +21,7 @@
    top: -54px;
    z-index: calc(var(--z-header) - 1);
    background: var(--bg-color);
-    padding: var(--space-2) 0;
+    padding: var(--space-1) 0;
    box-shadow: 0 1px 3px rgba(0,0,0,0.05);
 }

@@ -371,6 +371,14 @@
    display: block;
 }

+/* Elevate the controls stacking context above breadcrumb nav when a dropdown is open,
+   so the dropdown menu isn't obscured. Only active when dropdown is shown to avoid
+   the entire controls bar (which can wrap to 2 rows on narrow viewports) covering
+   the sticky breadcrumb. */
+.controls:has(.dropdown-group.active) {
+    z-index: var(--z-header);
+}
+
 .dropdown-item {
    display: block;
    padding: 6px 15px;
@@ -397,6 +405,33 @@
    text-align: center;
 }

+/* Intermediate breakpoint: wrap controls-right to prevent overflow */
+@media (max-width: 1500px) {
+    .actions {
+        flex-wrap: wrap;
+        gap: var(--space-2);
+    }
+
+    .action-buttons {
+        flex-wrap: wrap;
+        gap: var(--space-1);
+    }
+
+    .controls-right {
+        width: 100%;
+        justify-content: flex-end;
+        margin-top: 8px;
+        padding-left: 0;
+    }
+
+    /* Reduce button sizes to fit better */
+    .control-group button {
+        min-width: 80px;
+        padding: 4px 8px;
+        font-size: 0.8em;
+    }
+}
+
@media (max-width: 768px) {
    .actions {
        flex-wrap: wrap;
--- a/static/css/style.css
+++ b/static/css/style.css
@@ -39,6 +39,7 @@
@import 'components/keyboard-nav.css'; /* Add keyboard navigation component */
@import 'components/statistics.css'; /* Add statistics component */
@import 'components/sidebar.css'; /* Add sidebar component */
+@import 'components/media-viewer.css';

 .initialization-notice {
    display: flex;
--- a/static/js/api/baseModelApi.js
+++ b/static/js/api/baseModelApi.js
@@ -422,8 +422,12 @@ export class BaseModelApiClient {
                throw new Error('Failed to save metadata');
            }

-            state.virtualScroller.updateSingleItem(filePath, data);
-            return response.json();
+            const result = await response.json();
+            state.virtualScroller.updateSingleItem(filePath, {
+                ...data,
+                auto_tags: result.auto_tags,
+            });
+            return result;
        } finally {
            state.loadingManager.hide();
        }
@@ -448,7 +452,10 @@ export class BaseModelApiClient {
            const result = await response.json();

            if (result.success && result.tags) {
-                state.virtualScroller.updateSingleItem(filePath, { tags: result.tags });
+                state.virtualScroller.updateSingleItem(filePath, {
+                    tags: result.tags,
+                    auto_tags: result.auto_tags,
+                });
            }

            return result;
@@ -978,6 +985,16 @@ export class BaseModelApiClient {
                });
            }

+            if (pageState.filters.autoTags && Object.keys(pageState.filters.autoTags).length > 0) {
+                Object.entries(pageState.filters.autoTags).forEach(([tag, state]) => {
+                    if (state === 'include') {
+                        params.append('auto_tag_include', tag);
+                    } else if (state === 'exclude') {
+                        params.append('auto_tag_exclude', tag);
+                    }
+                });
+            }
+
            if (pageState.filters.baseModel && pageState.filters.baseModel.length > 0) {
                // Check for empty wildcard marker - if present, no models should match
                const EMPTY_WILDCARD_MARKER = '__EMPTY_WILDCARD_RESULT__';
--- a/static/js/api/recipeApi.js
+++ b/static/js/api/recipeApi.js
@@ -15,6 +15,7 @@ const RECIPE_ENDPOINTS = {
    move: '/api/lm/recipe/move',
    moveBulk: '/api/lm/recipes/move-bulk',
    bulkDelete: '/api/lm/recipes/bulk-delete',
+    repairBulk: '/api/lm/recipes/repair-bulk',
 };

 const RECIPE_SIDEBAR_CONFIG = {
@@ -557,6 +558,38 @@ export class RecipeSidebarApiClient {
        };
    }

+    async repairBulkModels(filePaths) {
+        if (!filePaths || filePaths.length === 0) {
+            throw new Error('No file paths provided');
+        }
+
+        const recipeIds = filePaths
+            .map((path) => extractRecipeId(path))
+            .filter((id) => !!id);
+
+        if (recipeIds.length === 0) {
+            throw new Error('No recipe IDs could be derived from file paths');
+        }
+
+        const response = await fetch(this.apiConfig.endpoints.repairBulk, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                recipe_ids: recipeIds,
+            }),
+        });
+
+        const result = await response.json();
+
+        if (!response.ok || !result.success) {
+            throw new Error(result.error || 'Failed to repair recipes');
+        }
+
+        return result;
+    }
+
    async bulkDeleteModels(filePaths) {
        if (!filePaths || filePaths.length === 0) {
            throw new Error('No file paths provided');
--- a/static/js/components/ContextMenu/BaseContextMenu.js
+++ b/static/js/components/ContextMenu/BaseContextMenu.js
@@ -3,32 +3,113 @@ export class BaseContextMenu {
        this.menu = document.getElementById(menuId);
        this.cardSelector = cardSelector;
        this.currentCard = null;
-        
+        this.submenuTimeout = null;
+        this.openSubmenu = null;
+
        if (!this.menu) {
            console.error(`Context menu element with ID ${menuId} not found`);
            return;
        }
-        
+
        this.init();
    }

    init() {
-        // Hide menu on regular clicks
-        document.addEventListener('click', () => this.hideMenu());
+        // Hide menu when clicking outside
+        document.addEventListener('click', (e) => {
+            if (!this.menu.contains(e.target)) {
+                this.hideMenu();
+            }
+        });

-        // Handle menu item clicks
+        // Handle menu item clicks (including submenu items)
        this.menu.addEventListener('click', (e) => {
            const menuItem = e.target.closest('.context-menu-item');
            if (!menuItem || !this.currentCard) return;

+            // Ignore clicks on submenu trigger (has-submenu parent)
+            if (menuItem.classList.contains('has-submenu')) return;
+
            const action = menuItem.dataset.action;
            if (!action) return;
-            
+
            this.handleMenuAction(action, menuItem);
            this.hideMenu();
        });
+
+        // Submenu hover handling
+        // Use mouseover/mouseout (which bubble) with relatedTarget checks
+        // to reliably detect crossing the .has-submenu boundary
+        this.menu.addEventListener('mouseover', (e) => {
+            const trigger = e.target.closest('.has-submenu');
+            if (!trigger) return;
+
+            // Only act when entering from outside this trigger's tree
+            if (e.relatedTarget && trigger.contains(e.relatedTarget)) return;
+
+            this._openSubmenu(trigger);
+        });
+
+        this.menu.addEventListener('mouseout', (e) => {
+            const trigger = e.target.closest('.has-submenu');
+            if (!trigger) return;
+
+            // Only close when leaving the trigger's tree entirely
+            if (e.relatedTarget && trigger.contains(e.relatedTarget)) return;
+
+            this._scheduleSubmenuClose(trigger);
+        });
    }
-    
+
+    _openSubmenu(trigger) {
+        // Clear any pending close
+        if (this.submenuTimeout) {
+            clearTimeout(this.submenuTimeout);
+            this.submenuTimeout = null;
+        }
+
+        // Hide any previously open submenu
+        if (this.openSubmenu && this.openSubmenu !== trigger) {
+            this._hideSubmenu(this.openSubmenu);
+        }
+
+        const submenu = trigger.querySelector('.context-submenu');
+        if (!submenu) return;
+
+        submenu.style.display = 'block';
+        this.openSubmenu = trigger;
+        this._positionSubmenu(submenu);
+    }
+
+    _scheduleSubmenuClose(trigger) {
+        this.submenuTimeout = setTimeout(() => {
+            this._hideSubmenu(trigger);
+            this.submenuTimeout = null;
+        }, 250);
+    }
+
+    _hideSubmenu(trigger) {
+        const submenu = trigger.querySelector('.context-submenu');
+        if (submenu) {
+            submenu.style.display = 'none';
+            submenu.classList.remove('flip-left');
+        }
+        if (this.openSubmenu === trigger) {
+            this.openSubmenu = null;
+        }
+    }
+
+    _positionSubmenu(submenu) {
+        const submenuRect = submenu.getBoundingClientRect();
+        const viewportWidth = document.documentElement.clientWidth;
+
+        if (submenuRect.right > viewportWidth) {
+            submenu.classList.add('flip-left');
+        } else {
+            submenu.classList.remove('flip-left');
+        }
+    }
+
    handleMenuAction(action, menuItem) {
        // Override in subclass
        console.warn('handleMenuAction not implemented');
@@ -40,34 +121,41 @@ export class BaseContextMenu {

        // Get menu dimensions
        const menuRect = this.menu.getBoundingClientRect();
-        
+
        // Get viewport dimensions
        const viewportWidth = document.documentElement.clientWidth;
        const viewportHeight = document.documentElement.clientHeight;
-        
+
        // Calculate position
        let finalX = x;
        let finalY = y;
-        
+
        // Ensure menu doesn't go offscreen right
        if (x + menuRect.width > viewportWidth) {
            finalX = x - menuRect.width;
        }
-        
+
        // Ensure menu doesn't go offscreen bottom
        if (y + menuRect.height > viewportHeight) {
            finalY = y - menuRect.height;
        }
-        
+
        // Position menu
        this.menu.style.left = `${finalX}px`;
        this.menu.style.top = `${finalY}px`;
    }

    hideMenu() {
+        if (this.submenuTimeout) {
+            clearTimeout(this.submenuTimeout);
+            this.submenuTimeout = null;
+        }
+        if (this.openSubmenu) {
+            this._hideSubmenu(this.openSubmenu);
+        }
        if (this.menu) {
            this.menu.style.display = 'none';
        }
        this.currentCard = null;
    }
-}
+}
--- a/static/js/components/ContextMenu/BulkContextMenu.js
+++ b/static/js/components/ContextMenu/BulkContextMenu.js
@@ -4,6 +4,7 @@ import { bulkManager } from '../../managers/BulkManager.js';
 import { updateElementText, translate } from '../../utils/i18nHelpers.js';
 import { bulkMissingLoraDownloadManager } from '../../managers/BulkMissingLoraDownloadManager.js';
 import { showToast } from '../../utils/uiHelpers.js';
+import { getModelApiClient } from '../../api/modelApiFactory.js';

 export class BulkContextMenu extends BaseContextMenu {
    constructor() {
@@ -40,6 +41,11 @@ export class BulkContextMenu extends BaseContextMenu {
        const autoOrganizeItem = this.menu.querySelector('[data-action="auto-organize"]');
        const deleteAllItem = this.menu.querySelector('[data-action="delete-all"]');
        const downloadMissingLorasItem = this.menu.querySelector('[data-action="download-missing-loras"]');
+        const repairMetadataItem = this.menu.querySelector('[data-action="repair-metadata"]');
+
+        if (repairMetadataItem) {
+            repairMetadataItem.style.display = config.repairMetadata ? 'flex' : 'none';
+        }

        if (sendToWorkflowAppendItem) {
            sendToWorkflowAppendItem.style.display = config.sendToWorkflow ? 'flex' : 'none';
@@ -50,6 +56,14 @@ export class BulkContextMenu extends BaseContextMenu {
        if (copyAllItem) {
            copyAllItem.style.display = config.copyAll ? 'flex' : 'none';
        }
+
+        // Submenu parent visibility
+        const sendToWorkflowSubmenu = this.menu.querySelector('[data-has-submenu="send-to-workflow"]');
+        if (sendToWorkflowSubmenu) {
+            const hasWorkflowActions = config.sendToWorkflow || config.copyAll;
+            sendToWorkflowSubmenu.style.display = hasWorkflowActions ? 'flex' : 'none';
+        }
+
        if (refreshAllItem) {
            refreshAllItem.style.display = config.refreshAll ? 'flex' : 'none';
        }
@@ -74,44 +88,92 @@ export class BulkContextMenu extends BaseContextMenu {
        if (setContentRatingItem) {
            setContentRatingItem.style.display = config.setContentRating ? 'flex' : 'none';
        }
+
+        const setFavoriteItem = this.menu.querySelector('[data-action="set-favorite"]');
+
+        if (setFavoriteItem && config.setFavorite) {
+            setFavoriteItem.style.display = 'flex';
+
+            const total = state.selectedModels.size;
+            const favoritedCount = this.countFavoritedInSelection();
+            const allFavorited = total > 0 && favoritedCount === total;
+
+            const icon = setFavoriteItem.querySelector('i');
+            const label = setFavoriteItem.querySelector('span');
+
+            if (allFavorited) {
+                if (icon) { icon.className = 'far fa-star'; }
+                if (label) { label.textContent = translate('loras.bulkOperations.unfavorite'); }
+            } else {
+                if (icon) { icon.className = 'fas fa-star'; }
+                if (label) {
+                    label.textContent = favoritedCount > 0
+                        ? translate('loras.bulkOperations.setFavoriteCount', { favorited: favoritedCount, total })
+                        : translate('loras.bulkOperations.setFavorite');
+                }
+            }
+        } else if (setFavoriteItem) {
+            setFavoriteItem.style.display = 'none';
+        }
+
        if (downloadMissingLorasItem) {
            // Only show for recipes page
            downloadMissingLorasItem.style.display = currentModelType === 'recipes' ? 'flex' : 'none';
        }

+        const downloadExampleImagesItem = this.menu.querySelector('[data-action="download-example-images"]');
+        if (downloadExampleImagesItem) {
+            // Show on model pages (loras, checkpoints, embeddings), hide on recipes
+            const modelPages = ['loras', 'checkpoints', 'embeddings'];
+            downloadExampleImagesItem.style.display = modelPages.includes(currentModelType) ? 'flex' : 'none';
+        }
+
        const skipMetadataRefreshItem = this.menu.querySelector('[data-action="skip-metadata-refresh"]');
        const resumeMetadataRefreshItem = this.menu.querySelector('[data-action="resume-metadata-refresh"]');

        if (skipMetadataRefreshItem && resumeMetadataRefreshItem) {
-            const skipCount = this.countSkipStatus(true);
-            const resumeCount = this.countSkipStatus(false);
-            const totalCount = skipCount + resumeCount;
-
-            if (skipCount === totalCount) {
+            if (!config.skipMetadataRefresh) {
                skipMetadataRefreshItem.style.display = 'none';
-                resumeMetadataRefreshItem.style.display = 'flex';
-                resumeMetadataRefreshItem.querySelector('span').textContent = translate(
-                    'loras.bulkOperations.resumeMetadataRefresh'
-                );
-            } else if (resumeCount === totalCount) {
-                skipMetadataRefreshItem.style.display = 'flex';
                resumeMetadataRefreshItem.style.display = 'none';
-                skipMetadataRefreshItem.querySelector('span').textContent = translate(
-                    'loras.bulkOperations.skipMetadataRefresh'
-                );
            } else {
-                skipMetadataRefreshItem.style.display = 'flex';
-                resumeMetadataRefreshItem.style.display = 'flex';
-                skipMetadataRefreshItem.querySelector('span').textContent = translate(
-                    'loras.bulkOperations.skipMetadataRefreshCount',
-                    { count: resumeCount }
-                );
-                resumeMetadataRefreshItem.querySelector('span').textContent = translate(
-                    'loras.bulkOperations.resumeMetadataRefreshCount',
-                    { count: skipCount }
-                );
+                const skipCount = this.countSkipStatus(true);
+                const resumeCount = this.countSkipStatus(false);
+                const totalCount = skipCount + resumeCount;
+
+                if (skipCount === totalCount) {
+                    skipMetadataRefreshItem.style.display = 'none';
+                    resumeMetadataRefreshItem.style.display = 'flex';
+                    resumeMetadataRefreshItem.querySelector('span').textContent = translate(
+                        'loras.bulkOperations.resumeMetadataRefresh'
+                    );
+                } else if (resumeCount === totalCount) {
+                    skipMetadataRefreshItem.style.display = 'flex';
+                    resumeMetadataRefreshItem.style.display = 'none';
+                    skipMetadataRefreshItem.querySelector('span').textContent = translate(
+                        'loras.bulkOperations.skipMetadataRefresh'
+                    );
+                } else {
+                    skipMetadataRefreshItem.style.display = 'flex';
+                    resumeMetadataRefreshItem.style.display = 'flex';
+                    skipMetadataRefreshItem.querySelector('span').textContent = translate(
+                        'loras.bulkOperations.skipMetadataRefreshCount',
+                        { count: resumeCount }
+                    );
+                    resumeMetadataRefreshItem.querySelector('span').textContent = translate(
+                        'loras.bulkOperations.resumeMetadataRefreshCount',
+                        { count: skipCount }
+                    );
+                }
            }
        }
+
+        // Hide empty sections
+        this.menu.querySelectorAll('.context-menu-section').forEach(section => {
+            const items = Array.from(section.querySelectorAll('.context-menu-item'))
+                .filter(item => !item.closest('.context-submenu'));
+            const allHidden = items.length > 0 && items.every(item => item.style.display === 'none');
+            section.style.display = allHidden ? 'none' : '';
+        });
    }

    updateSelectedCountHeader() {
@@ -138,6 +200,20 @@ export class BulkContextMenu extends BaseContextMenu {
        return count;
    }

+    countFavoritedInSelection() {
+        let count = 0;
+        for (const filePath of state.selectedModels) {
+            const escapedPath = window.CSS && typeof window.CSS.escape === 'function'
+                ? window.CSS.escape(filePath)
+                : filePath.replace(/["\\]/g, '\\$&');
+            const card = document.querySelector(`.model-card[data-filepath="${escapedPath}"]`);
+            if (card && card.dataset.favorite === 'true') {
+                count++;
+            }
+        }
+        return count;
+    }
+
    showMenu(x, y, card) {
        this.updateMenuItemsForModelType();
        this.updateSelectedCountHeader();
@@ -185,9 +261,20 @@ export class BulkContextMenu extends BaseContextMenu {
            case 'delete-all':
                bulkManager.showBulkDeleteModal();
                break;
+            case 'repair-metadata':
+                bulkManager.repairSelectedRecipes();
+                break;
+            case 'set-favorite': {
+                const allFavorited = this.countFavoritedInSelection() === state.selectedModels.size;
+                bulkManager.setBulkFavorites(!allFavorited);
+                break;
+            }
            case 'download-missing-loras':
                this.handleDownloadMissingLoras();
                break;
+            case 'download-example-images':
+                this.handleDownloadExampleImages();
+                break;
            case 'clear':
                bulkManager.clearSelection();
                break;
@@ -230,4 +317,31 @@ export class BulkContextMenu extends BaseContextMenu {

        await bulkMissingLoraDownloadManager.downloadMissingLoras(selectedRecipes);
    }
+
+    async handleDownloadExampleImages() {
+        if (state.selectedModels.size === 0) {
+            return;
+        }
+
+        const hashes = new Set();
+        for (const filePath of state.selectedModels) {
+            const escapedPath = CSS.escape(filePath);
+            const card = document.querySelector(`.model-card[data-filepath="${escapedPath}"]`);
+            if (card?.dataset?.sha256) {
+                hashes.add(card.dataset.sha256);
+            }
+        }
+
+        if (hashes.size === 0) {
+            showToast('No valid model hashes found in selection', {}, 'warning');
+            return;
+        }
+
+        try {
+            const apiClient = getModelApiClient();
+            await apiClient.downloadExampleImages([...hashes]);
+        } catch (error) {
+            console.error('Bulk download example images failed:', error);
+        }
+    }
 }
--- a/static/js/components/Header.js
+++ b/static/js/components/Header.js
@@ -129,6 +129,126 @@ export class HeaderManager {
      
      // Hide search functionality on Statistics page
      this.updateHeaderForPage();
+
+      // Initialize hamburger menu for mobile
+      this.initializeHamburgerMenu();
+    }
+
+    initializeHamburgerMenu() {
+      const hamburgerBtn = document.getElementById('hamburgerMenuBtn');
+      const hamburgerDropdown = document.getElementById('hamburgerDropdown');
+
+      if (!hamburgerBtn || !hamburgerDropdown) return;
+
+      // Toggle dropdown on hamburger button click
+      hamburgerBtn.addEventListener('click', (e) => {
+        e.stopPropagation();
+        hamburgerDropdown.classList.toggle('active');
+        const icon = hamburgerBtn.querySelector('i');
+        if (hamburgerDropdown.classList.contains('active')) {
+          icon.classList.remove('fa-bars');
+          icon.classList.add('fa-times');
+        } else {
+          icon.classList.remove('fa-times');
+          icon.classList.add('fa-bars');
+        }
+      });
+
+      // Handle dropdown item clicks
+      const dropdownItems = hamburgerDropdown.querySelectorAll('.dropdown-item');
+      dropdownItems.forEach(item => {
+        item.addEventListener('click', (e) => {
+          const action = item.dataset.action;
+          this.handleHamburgerAction(action);
+          hamburgerDropdown.classList.remove('active');
+          const icon = hamburgerBtn.querySelector('i');
+          icon.classList.remove('fa-times');
+          icon.classList.add('fa-bars');
+        });
+      });
+
+      // Close dropdown when clicking outside
+      document.addEventListener('click', (e) => {
+        if (!hamburgerDropdown.contains(e.target) && !hamburgerBtn.contains(e.target)) {
+          hamburgerDropdown.classList.remove('active');
+          const icon = hamburgerBtn.querySelector('i');
+          if (icon) {
+            icon.classList.remove('fa-times');
+            icon.classList.add('fa-bars');
+          }
+        }
+      });
+
+      // Update theme icon in hamburger menu based on current theme
+      this.updateHamburgerThemeIcon();
+    }
+
+    handleHamburgerAction(action) {
+      switch (action) {
+        case 'theme':
+          if (typeof toggleTheme === 'function') {
+            const newTheme = toggleTheme();
+            // Update theme toggle in header if it exists
+            const themeToggle = document.querySelector('.theme-toggle');
+            if (themeToggle) {
+              themeToggle.classList.remove('theme-light', 'theme-dark', 'theme-auto');
+              themeToggle.classList.add(`theme-${newTheme}`);
+              this.updateThemeTooltip(themeToggle, newTheme);
+            }
+            this.updateHamburgerThemeIcon();
+          }
+          break;
+        case 'settings':
+          if (window.settingsManager) {
+            window.settingsManager.toggleSettings();
+          }
+          break;
+        case 'help':
+          const helpToggle = document.getElementById('helpToggleBtn');
+          if (helpToggle) {
+            helpToggle.click();
+          }
+          break;
+        case 'notifications':
+          updateService.toggleUpdateModal();
+          break;
+        case 'support':
+          if (window.modalManager) {
+            window.modalManager.toggleModal('supportModal');
+            renderSupporters().catch(error => {
+              console.error('Error loading supporters:', error);
+            });
+          }
+          break;
+      }
+    }
+
+    updateHamburgerThemeIcon() {
+      const themeItem = document.querySelector('.dropdown-item[data-action="theme"]');
+      if (!themeItem) return;
+
+      const currentTheme = getStorageItem('theme') || 'auto';
+      const icon = themeItem.querySelector('i');
+      const text = themeItem.querySelector('span');
+
+      if (icon) {
+        icon.classList.remove('fa-moon', 'fa-sun', 'fa-adjust');
+        if (currentTheme === 'light') {
+          icon.classList.add('fa-sun');
+        } else if (currentTheme === 'dark') {
+          icon.classList.add('fa-moon');
+        } else {
+          icon.classList.add('fa-adjust');
+        }
+      }
+
+      // Update text based on current theme
+      if (text) {
+        const key = currentTheme === 'light' ? 'header.theme.switchToDark' :
+                    currentTheme === 'dark' ? 'header.theme.switchToLight' :
+                    'header.theme.toggle';
+        updateElementAttribute(themeItem, 'aria-label', key, {}, '');
+      }
    }

    updateHeaderForPage() {
--- a/static/js/components/RecipeModal.js
+++ b/static/js/components/RecipeModal.js
@@ -2,10 +2,11 @@
 import { showToast, copyToClipboard, sendLoraToWorkflow, sendModelPathToWorkflow, openCivitaiByMetadata } from '../utils/uiHelpers.js';
 import { translate } from '../utils/i18nHelpers.js';
 import { state } from '../state/index.js';
-import { setSessionItem, removeSessionItem } from '../utils/storageHelpers.js';
+import { setSessionItem, removeSessionItem, getStorageItem, setStorageItem } from '../utils/storageHelpers.js';
 import { fetchRecipeDetails, updateRecipeMetadata } from '../api/recipeApi.js';
 import { downloadManager } from '../managers/DownloadManager.js';
 import { MODEL_TYPES } from '../api/apiConfig.js';
+import { openMediaViewer } from './shared/MediaViewer.js';

 const ALLOWED_GEN_PARAM_KEYS = new Set([
    'prompt',
@@ -104,6 +105,7 @@ class RecipeModal {

    init() {
        this.setupCopyButtons();
+        this.setupStripLoraToggle();
        this.setupPromptEditors();
        // Set up tooltip positioning handlers after DOM is ready
        document.addEventListener('DOMContentLoaded', () => {
@@ -112,6 +114,23 @@ class RecipeModal {

        // Set up document click handler to close edit fields
        document.addEventListener('click', (event) => {
+            const recipeModal = document.getElementById('recipeModal');
+            if (recipeModal && recipeModal.style.display !== 'none') {
+                const mediaEl = event.target.closest('.recipe-preview-media');
+                if (mediaEl && mediaEl.tagName) {
+                    event.stopPropagation();
+                    const isVideo = mediaEl.tagName === 'VIDEO';
+                    const url = mediaEl.src || mediaEl.currentSrc;
+                    if (url) {
+                        openMediaViewer(url, {
+                            type: isVideo ? 'video' : 'image',
+                            title: document.getElementById('recipeModalTitle')?.textContent || ''
+                        });
+                    }
+                    return;
+                }
+            }
+
            // Handle title edit
            const titleEditor = document.getElementById('recipeTitleEditor');
            if (titleEditor && titleEditor.classList.contains('active') &&
@@ -364,6 +383,7 @@ class RecipeModal {

        this.syncGenerationParams(hydratedRecipe.gen_params);
        this.syncResourcesSection(hydratedRecipe);
+        this.syncSourceUrlAction();

        // Show the modal
        modalManager.showModal('recipeModal');
@@ -496,6 +516,7 @@ class RecipeModal {
        } else {
            this.updateSourceUrlDisplay(this.currentRecipe.source_path || '');
        }
+        this.syncSourceUrlAction();
    }

    getPreviewMediaUrl(recipe = {}) {
@@ -563,6 +584,30 @@ class RecipeModal {
        }
    }

+    syncSourceUrlAction() {
+        const actionsContainer = document.getElementById('recipeHeaderActions');
+        if (!actionsContainer) {
+            return;
+        }
+
+        actionsContainer.innerHTML = '';
+
+        const sourcePath = this.currentRecipe?.source_path || '';
+        const isValidUrl = sourcePath.startsWith('http://') || sourcePath.startsWith('https://');
+        if (!isValidUrl) {
+            return;
+        }
+
+        const btn = document.createElement('button');
+        btn.className = 'recipe-source-url-btn';
+        btn.title = sourcePath;
+        btn.innerHTML = '<i class="fas fa-globe"></i> Open Source URL';
+        btn.addEventListener('click', () => {
+            window.open(sourcePath, '_blank');
+        });
+        actionsContainer.appendChild(btn);
+    }
+
    syncTagsDisplay(tags) {
        const tagsContainer = document.getElementById('recipeTagsCompact');
        if (!tagsContainer) {
@@ -1297,6 +1342,7 @@ class RecipeModal {
                        // Update source URL in the UI
                        this.commitField('source_path');
                        this.updateSourceUrlDisplay(newSourceUrl, { forceInputSync: true });
+                        this.syncSourceUrlAction();

                        // Update the current recipe object
                        this.currentRecipe.source_path = newSourceUrl;
@@ -1332,14 +1378,20 @@ class RecipeModal {

        if (copyPromptBtn) {
            copyPromptBtn.addEventListener('click', () => {
-                const promptText = this.currentRecipe?.gen_params?.prompt || '';
+                let promptText = this.currentRecipe?.gen_params?.prompt || '';
+                if (this.shouldStripLoraOnCopy()) {
+                    promptText = RecipeModal.stripLoraTags(promptText);
+                }
                this.copyToClipboard(promptText, 'Prompt copied to clipboard');
            });
        }

        if (copyNegativePromptBtn) {
            copyNegativePromptBtn.addEventListener('click', () => {
-                const negativePromptText = this.currentRecipe?.gen_params?.negative_prompt || '';
+                let negativePromptText = this.currentRecipe?.gen_params?.negative_prompt || '';
+                if (this.shouldStripLoraOnCopy()) {
+                    negativePromptText = RecipeModal.stripLoraTags(negativePromptText);
+                }
                this.copyToClipboard(negativePromptText, 'Negative prompt copied to clipboard');
            });
        }
@@ -1359,6 +1411,43 @@ class RecipeModal {
        }
    }

+    /**
+     * Strip <lora:...> tags from prompt text and clean up residual punctuation/whitespace.
+     * Handles both unescaped (<lora:...>) and HTML-escaped (&lt;lora:...&gt;) variants.
+     * Cleans up artifacts like leading ", ", double commas, and extra whitespace.
+     */
+    static stripLoraTags(text) {
+        return text
+            .replace(/<lora:[^>]*>/gi, '')
+            .replace(/&lt;lora:[^&]*&gt;/gi, '')
+            .replace(/,(\s*,)+/g, ',')
+            .replace(/^,\s*/, '')
+            .replace(/,\s*$/, '')
+            .replace(/\s{2,}/g, ' ')
+            .trim();
+    }
+
+    shouldStripLoraOnCopy() {
+        const toggle = document.getElementById('stripLoraOnCopyToggle');
+        return toggle ? toggle.checked : false;
+    }
+
+    setupStripLoraToggle() {
+        const toggle = document.getElementById('stripLoraOnCopyToggle');
+        if (!toggle) return;
+
+        const stored = getStorageItem('strip_lora_on_copy');
+        if (stored !== null) {
+            toggle.checked = stored === true;
+        }
+
+        toggle.addEventListener('change', () => {
+            const checked = toggle.checked;
+            setStorageItem('strip_lora_on_copy', checked);
+            state.global.settings.strip_lora_on_copy = checked;
+        });
+    }
+
    // Fetch recipe syntax from backend and copy to clipboard
    async fetchAndCopyRecipeSyntax() {
        if (!this.recipeId) {
--- a/static/js/components/controls/PageControls.js
+++ b/static/js/components/controls/PageControls.js
@@ -166,17 +166,6 @@ export class PageControls {
            });
        });
        
-        // Handle quick refresh option
-        const quickRefreshOption = document.querySelector('[data-action="quick-refresh"]');
-        if (quickRefreshOption) {
-            quickRefreshOption.addEventListener('click', (e) => {
-                e.stopPropagation();
-                this.refreshModels(false);
-                // Close the dropdown
-                document.querySelector('.dropdown-group.active')?.classList.remove('active');
-            });
-        }
-        
        // Handle full rebuild option
        const fullRebuildOption = document.querySelector('[data-action="full-rebuild"]');
        if (fullRebuildOption) {
@@ -829,4 +818,4 @@ export class PageControls {
            this.sidebarManager.cleanup();
        }
    }
-}
+}
--- a/static/js/components/shared/MediaViewer.js
+++ b/static/js/components/shared/MediaViewer.js
@@ -0,0 +1,204 @@
+let activeViewer = null;
+
+function createMediaElement(item) {
+    const { url, type = 'image' } = item;
+    if (type === 'video') {
+        const el = document.createElement('video');
+        el.controls = true;
+        el.autoplay = true;
+        el.loop = true;
+        el.muted = true;
+        el.className = 'media-viewer-media media-viewer-video';
+        el.src = url;
+        return el;
+    }
+    const el = document.createElement('img');
+    el.className = 'media-viewer-media media-viewer-image';
+    el.src = url;
+    el.alt = 'Full size preview';
+    el.draggable = false;
+    return el;
+}
+
+function preloadAdjacent(items, index) {
+    [index - 1, index + 1].forEach(i => {
+        if (i >= 0 && i < items.length && items[i].type !== 'video') {
+            const preload = new Image();
+            preload.src = items[i].url;
+        }
+    });
+}
+
+export function openMediaViewer(arg1, arg2, arg3) {
+    closeMediaViewer();
+
+    let items, currentIndex, title = '';
+
+    if (Array.isArray(arg1)) {
+        items = arg1;
+        currentIndex = typeof arg2 === 'number' ? arg2 : 0;
+        title = (arg3 && arg3.title) || '';
+    } else {
+        items = [{ url: arg1, type: (arg2 && arg2.type) || 'image' }];
+        currentIndex = 0;
+        title = (arg2 && arg2.title) || '';
+    }
+
+    if (currentIndex < 0 || currentIndex >= items.length) currentIndex = 0;
+
+    const overlay = document.createElement('div');
+    overlay.className = 'media-viewer-overlay';
+    overlay.setAttribute('role', 'dialog');
+    overlay.setAttribute('aria-label', title || 'Media viewer');
+
+    const closeBtn = document.createElement('button');
+    closeBtn.className = 'media-viewer-close';
+    closeBtn.innerHTML = '<i class="fas fa-times"></i>';
+    closeBtn.title = 'Close (Esc)';
+    closeBtn.addEventListener('click', (e) => {
+        e.stopPropagation();
+        closeMediaViewer();
+    });
+
+    const contentContainer = document.createElement('div');
+    contentContainer.className = 'media-viewer-content-container';
+
+    let mediaElement = createMediaElement(items[currentIndex]);
+    contentContainer.appendChild(mediaElement);
+
+    const hasNavigation = items.length > 1;
+
+    const counter = document.createElement('div');
+    counter.className = 'media-viewer-counter';
+    counter.textContent = hasNavigation ? `${currentIndex + 1} / ${items.length}` : '';
+    contentContainer.appendChild(counter);
+
+    if (title) {
+        const titleBar = document.createElement('div');
+        titleBar.className = 'media-viewer-title';
+        titleBar.textContent = title;
+        contentContainer.appendChild(titleBar);
+    }
+
+    let prevBtn, nextBtn;
+    if (hasNavigation) {
+        prevBtn = document.createElement('button');
+        prevBtn.className = 'media-viewer-nav media-viewer-prev';
+        prevBtn.innerHTML = '<i class="fas fa-chevron-left"></i>';
+        prevBtn.title = 'Previous (←)';
+        nextBtn = document.createElement('button');
+        nextBtn.className = 'media-viewer-nav media-viewer-next';
+        nextBtn.innerHTML = '<i class="fas fa-chevron-right"></i>';
+        nextBtn.title = 'Next (→)';
+
+        const navigate = (delta) => {
+            const newIndex = (currentIndex + delta + items.length) % items.length;
+            currentIndex = newIndex;
+
+            const oldMedia = contentContainer.querySelector('.media-viewer-media');
+            const newMedia = createMediaElement(items[currentIndex]);
+
+            if (oldMedia) {
+                if (oldMedia.tagName === 'VIDEO') {
+                    oldMedia.pause();
+                    oldMedia.src = '';
+                }
+                oldMedia.replaceWith(newMedia);
+            }
+            mediaElement = newMedia;
+
+            counter.textContent = `${currentIndex + 1} / ${items.length}`;
+            preloadAdjacent(items, currentIndex);
+        };
+
+        prevBtn.addEventListener('click', (e) => { e.stopPropagation(); navigate(-1); });
+        nextBtn.addEventListener('click', (e) => { e.stopPropagation(); navigate(1); });
+
+        overlay.appendChild(prevBtn);
+        overlay.appendChild(nextBtn);
+    }
+
+    overlay.appendChild(closeBtn);
+    overlay.appendChild(contentContainer);
+    document.body.appendChild(overlay);
+
+    requestAnimationFrame(() => {
+        overlay.classList.add('active');
+    });
+
+    overlay.addEventListener('click', (e) => {
+        if (e.target === overlay) {
+            closeMediaViewer();
+        }
+    });
+
+    const keyHandler = (e) => {
+        if (e.key === 'Escape') {
+            closeMediaViewer();
+            return;
+        }
+        if (hasNavigation) {
+            if (e.key === 'ArrowLeft') {
+                e.stopPropagation();
+                e.preventDefault();
+                prevBtn.click();
+                return;
+            }
+            if (e.key === 'ArrowRight') {
+                e.stopPropagation();
+                e.preventDefault();
+                nextBtn.click();
+                return;
+            }
+        }
+    };
+    document.addEventListener('keydown', keyHandler, true);
+
+    activeViewer = { overlay, keyHandler };
+    preloadAdjacent(items, currentIndex);
+
+    if (items[currentIndex].type === 'video') {
+        const recipeVideo = document.getElementById('recipeModalVideo');
+        if (recipeVideo && !recipeVideo.paused) {
+            recipeVideo.pause();
+        }
+    }
+}
+
+export function closeMediaViewer() {
+    if (!activeViewer) return;
+
+    const { overlay, keyHandler } = activeViewer;
+
+    const video = overlay.querySelector('video');
+    if (video) {
+        video.pause();
+        video.src = '';
+    }
+
+    const img = overlay.querySelector('img');
+    if (img) {
+        img.src = '';
+    }
+
+    document.removeEventListener('keydown', keyHandler, true);
+
+    overlay.classList.remove('active');
+    overlay.addEventListener('transitionend', () => {
+        if (overlay.parentNode) {
+            overlay.parentNode.removeChild(overlay);
+        }
+    }, { once: true });
+
+    setTimeout(() => {
+        if (overlay.parentNode) {
+            overlay.parentNode.removeChild(overlay);
+        }
+    }, 500);
+
+    activeViewer = null;
+}
+
+export function isMediaViewerOpen() {
+    return activeViewer !== null;
+}
--- a/static/js/components/shared/ModelCard.js
+++ b/static/js/components/shared/ModelCard.js
@@ -166,7 +166,9 @@ async function toggleFavorite(card) {
 function handleSendToWorkflow(card, replaceMode, modelType) {
    if (modelType === MODEL_TYPES.LORA) {
        const usageTips = JSON.parse(card.dataset.usage_tips || '{}');
-        const loraSyntax = buildLoraSyntax(card.dataset.file_name, usageTips);
+        const folder = card.dataset.folder || '';
+        const loraName = folder ? `${folder}/${card.dataset.file_name}` : card.dataset.file_name;
+        const loraSyntax = buildLoraSyntax(loraName, usageTips);
        sendLoraToWorkflow(loraSyntax, replaceMode, 'lora');
    } else if (modelType === MODEL_TYPES.CHECKPOINT) {
        const modelPath = card.dataset.filepath;
@@ -644,8 +646,23 @@ export function createModelCard(model, modelType) {
            <div class="card-footer">
                <div class="model-info">
                    <span class="model-name" title="${getDisplayName(model).replace(/"/g, '&quot;')}">${getDisplayName(model)}</span>
-                    <div>
-                        ${model.civitai?.name ? `<span class="version-name">${model.civitai.name}</span>` : ''}
+                    <div class="version-row">
+                        ${(() => {
+                            const autoTags = model.auto_tags || [];
+                            const hlTags = autoTags.filter(t => t === 'HIGH' || t === 'LOW');
+                            const hasVersionName = model.civitai?.name;
+                            if (!hlTags.length && !hasVersionName) return '';
+                            const density = state.global.settings.display_density || 'default';
+                            const shortLabels = density === 'medium' || density === 'compact';
+                            const badges = hlTags.map(t => {
+                                const cls = t === 'HIGH' ? 'hl-badge hl-badge--high' : 'hl-badge hl-badge--low';
+                                const label = shortLabels ? (t === 'HIGH' ? 'H' : 'L') : t;
+                                const titleAttr = shortLabels ? ` title="${t}"` : '';
+                                return `<span class="${cls}"${titleAttr}>${label}</span>`;
+                            }).join('');
+                            const versionHtml = hasVersionName ? `<span class="version-name civitai-version">${model.civitai.name}</span>` : '';
+                            return `<span class="badge-version-unit">${badges}${versionHtml}</span>`;
+                        })()}
                        ${hasUsageCount ? `<span class="version-name" title="${translate('modelCard.usage.timesUsed', {}, 'Times used')}">${model.usage_count}×</span>` : ''}
                    </div>
                </div>
--- a/static/js/components/shared/ModelMetadata.js
+++ b/static/js/components/shared/ModelMetadata.js
@@ -66,6 +66,12 @@ function updateModalFilePathReferences(newFilePath) {
        fileNameContent.setAttribute('data-file-path', newFilePath);
    }

+    const versionNameContent = scopedQuery('.version-name-content');
+    if (versionNameContent && versionNameContent.dataset) {
+        versionNameContent.dataset.filePath = newFilePath;
+        versionNameContent.setAttribute('data-file-path', newFilePath);
+    }
+
    const editTagsBtn = scopedQuery('.edit-tags-btn');
    if (editTagsBtn) {
        editTagsBtn.dataset.filePath = newFilePath;
@@ -516,3 +522,127 @@ export function setupFileNameEditing(filePath) {
        editBtn.classList.remove('visible');
    }
 }
+
+/**
+ * Set up version name editing functionality
+ * @param {string} filePath - File path
+ */
+export function setupVersionNameEditing(filePath) {
+    const versionNameContent = document.querySelector('.version-name-content');
+    const editBtn = document.querySelector('.edit-version-name-btn');
+
+    if (!versionNameContent || !editBtn) return;
+
+    // Store the file path in a data attribute for later use
+    versionNameContent.dataset.filePath = filePath;
+
+    // Show edit button on hover
+    const versionNameWrapper = document.querySelector('.version-name-wrapper');
+    versionNameWrapper.addEventListener('mouseenter', () => {
+        editBtn.classList.add('visible');
+    });
+
+    versionNameWrapper.addEventListener('mouseleave', () => {
+        if (!versionNameWrapper.classList.contains('editing')) {
+            editBtn.classList.remove('visible');
+        }
+    });
+
+    // Handle edit button click
+    editBtn.addEventListener('click', () => {
+        versionNameWrapper.classList.add('editing');
+        versionNameContent.setAttribute('contenteditable', 'true');
+        // Store original value for comparison later
+        versionNameContent.dataset.originalValue = versionNameContent.textContent.trim();
+        versionNameContent.focus();
+
+        // Place cursor at the end
+        const range = document.createRange();
+        const sel = window.getSelection();
+        if (versionNameContent.childNodes.length > 0) {
+            range.setStart(versionNameContent.childNodes[0], versionNameContent.textContent.length);
+            range.collapse(true);
+            sel.removeAllRanges();
+            sel.addRange(range);
+        }
+
+        editBtn.classList.add('visible');
+    });
+
+    // Handle keyboard events in edit mode
+    versionNameContent.addEventListener('keydown', function(e) {
+        if (!this.getAttribute('contenteditable')) return;
+
+        if (e.key === 'Enter') {
+            e.preventDefault();
+            this.blur(); // Trigger save on Enter
+        } else if (e.key === 'Escape') {
+            e.preventDefault();
+            // Restore original value
+            this.textContent = this.dataset.originalValue;
+            exitEditMode();
+        }
+    });
+
+    // Limit version name length
+    versionNameContent.addEventListener('input', function() {
+        if (!this.getAttribute('contenteditable')) return;
+
+        if (this.textContent.length > 100) {
+            this.textContent = this.textContent.substring(0, 100);
+            // Place cursor at the end
+            const range = document.createRange();
+            const sel = window.getSelection();
+            range.setStart(this.childNodes[0], 100);
+            range.collapse(true);
+            sel.removeAllRanges();
+            sel.addRange(range);
+
+            showToast('toast.models.nameTooLong', {}, 'warning');
+        }
+    });
+
+    // Handle focus out - save changes
+    versionNameContent.addEventListener('blur', async function() {
+        if (!this.getAttribute('contenteditable')) return;
+
+        const newVersionName = this.textContent.trim();
+        const originalValue = this.dataset.originalValue;
+
+        // Basic validation
+        if (!newVersionName) {
+            // Restore original value if empty
+            this.textContent = originalValue;
+            showToast('toast.models.nameCannotBeEmpty', {}, 'error');
+            exitEditMode();
+            return;
+        }
+
+        if (newVersionName === originalValue) {
+            // No changes, just exit edit mode
+            exitEditMode();
+            return;
+        }
+
+        try {
+            // Resolve current file path from modal state
+            const filePath = getActiveModalFilePath(this.dataset.filePath);
+
+            await getModelApiClient().saveModelMetadata(filePath, { civitai: { name: newVersionName } });
+
+            showToast('toast.models.nameUpdatedSuccessfully', {}, 'success');
+        } catch (error) {
+            console.error('Error updating version name:', error);
+            this.textContent = originalValue; // Restore original version name
+            showToast('toast.models.nameUpdateFailed', {}, 'error');
+        } finally {
+            exitEditMode();
+        }
+    });
+
+    function exitEditMode() {
+        versionNameContent.removeAttribute('contenteditable');
+        versionNameWrapper.classList.remove('editing');
+        editBtn.classList.remove('visible');
+    }
+}
--- a/static/js/components/shared/ModelModal.js
+++ b/static/js/components/shared/ModelModal.js
@@ -11,7 +11,8 @@ import { setupTabSwitching } from './ModelDescription.js';
 import {
    setupModelNameEditing,
    setupBaseModelEditing,
-    setupFileNameEditing
+    setupFileNameEditing,
+    setupVersionNameEditing
 } from './ModelMetadata.js';
 import { setupTagEditMode } from './ModelTags.js';
 import { getModelApiClient } from '../../api/modelApiFactory.js';
@@ -466,7 +467,12 @@ export async function showModelModal(model, modelType) {
                    <div class="info-grid">
                        <div class="info-item">
                            <label>${translate('modals.model.metadata.version', {}, 'Version')}</label>
-                            <span>${modelWithFullData.civitai?.name || 'N/A'}</span>
+                            <div class="version-name-wrapper">
+                                <span class="version-name-content">${modelWithFullData.civitai?.name || 'N/A'}</span>
+                                <button class="edit-version-name-btn" title="${translate('modals.model.actions.editVersionName', {}, 'Edit version name')}">
+                                    <i class="fas fa-pencil-alt"></i>
+                                </button>
+                            </div>
                        </div>
                        <div class="info-item">
                            <label>${translate('modals.model.metadata.fileName', {}, 'File Name')}</label>
@@ -660,6 +666,7 @@ export async function showModelModal(model, modelType) {
    setupTagTooltip();
    setupTagEditMode(modelType);
    setupModelNameEditing(modelWithFullData.file_path);
+    setupVersionNameEditing(modelWithFullData.file_path);
    setupBaseModelEditing(modelWithFullData.file_path);
    setupFileNameEditing(modelWithFullData.file_path);
    setupEventHandlers(modelWithFullData.file_path, modelType);
--- a/static/js/components/shared/ModelTags.js
+++ b/static/js/components/shared/ModelTags.js
@@ -274,7 +274,17 @@ async function saveTags() {
    
    const filePath = editBtn.dataset.filePath;
    const tagElements = document.querySelectorAll('.metadata-item');
-    const tags = Array.from(tagElements).map(tag => tag.dataset.tag);
+    let tags = Array.from(tagElements).map(tag => tag.dataset.tag);
+    
+    // Flush uncommitted input as a tag so it's not silently lost on save
+    const tagInput = document.querySelector('.metadata-input');
+    if (tagInput) {
+        const pendingTag = tagInput.value.trim().toLowerCase();
+        if (pendingTag && !tags.includes(pendingTag)) {
+            tags.push(pendingTag);
+        }
+        tagInput.value = '';
+    }

    // Get original tags to compare
    const originalTagElements = document.querySelectorAll('.tooltip-tag');
@@ -465,6 +475,7 @@ function setupTagInput() {
    const tagInput = document.querySelector('.metadata-input');
    
    if (tagInput) {
+        tagInput.focus();
        tagInput.addEventListener('keydown', function(e) {
            if (e.key === 'Enter') {
                e.preventDefault();
--- a/static/js/components/shared/ModelVersionsTab.js
+++ b/static/js/components/shared/ModelVersionsTab.js
@@ -181,6 +181,13 @@ function isEarlyAccessActive(version) {
    }
 }

+function isDownloadAllowed(version) {
+    if (!version.usageControl) {
+        return true;
+    }
+    return version.usageControl === 'Download';
+}
+
 function buildMetaMarkup(version, options = {}) {
    const segments = [];
    if (version.baseModel) {
@@ -230,16 +237,25 @@ function buildBadge(label, tone, options = {}) {
 function buildActionButton(label, variant, action, options = {}) {
    const attributes = [
        `class="version-action ${variant}"`,
-        `data-version-action="${escapeHtml(action)}"`,
    ];
-    if (options.title) {
+    if (action) {
+        attributes.push(`data-version-action="${escapeHtml(action)}"`);
+    }
+    if (!options.disabled && options.title) {
        attributes.push(`title="${escapeHtml(options.title)}"`);
        attributes.push(`aria-label="${escapeHtml(options.title)}"`);
    }
+    if (options.disabled) {
+        attributes.push('disabled');
+    }
    if (options.extraAttributes) {
        attributes.push(options.extraAttributes);
    }
-    return `<button ${attributes.join(' ')}>${options.iconMarkup || ''}${escapeHtml(label)}</button>`;
+    const buttonHtml = `<button ${attributes.join(' ')}>${options.iconMarkup || ''}${escapeHtml(label)}</button>`;
+    if (options.disabled && options.title) {
+        return `<span class="version-action-disabled-wrapper" title="${escapeHtml(options.title)}" aria-label="${escapeHtml(options.title)}">${buttonHtml}</span>`;
+    }
+    return buttonHtml;
 }

 const DISPLAY_FILTER_MODES = Object.freeze({
@@ -371,6 +387,9 @@ function resolveUpdateAvailability(record, baseModel, currentVersionId) {
        if (hideEarlyAccess && isEarlyAccessActive(version)) {
            return false;
        }
+        if (!isDownloadAllowed(version)) {
+            return false;
+        }
        const versionBase = normalizeBaseModelName(version.baseModel);
        if (versionBase !== normalizedBase) {
            return false;
@@ -502,6 +521,17 @@ function renderRow(version, options) {
        }));
    }

+    if (!isDownloadAllowed(version)) {
+        const onSiteOnlyBadgeLabel = translate('modals.model.versions.badges.onSiteOnly', {}, 'On-Site Only');
+        badges.push(buildBadge(onSiteOnlyBadgeLabel, 'info', {
+            title: translate(
+                'modals.model.versions.badges.onSiteOnlyTooltip',
+                {},
+                'This version is only available for on-site generation on Civitai'
+            ),
+        }));
+    }
+
    if (version.shouldIgnore) {
        badges.push(buildBadge(ignoredBadgeLabel, 'muted', {
            title: translate(
@@ -524,25 +554,36 @@ function renderRow(version, options) {

    const actions = [];
    if (!version.isInLibrary) {
-        // Download button with optional EA bolt icon
+        const canDownload = isDownloadAllowed(version);
        const downloadIcon = isEarlyAccess ? '<i class="fas fa-bolt"></i> ' : '';
+        let downloadTitle;
+        if (!canDownload) {
+            downloadTitle = translate(
+                'modals.model.versions.actions.downloadNotAllowedTooltip',
+                {},
+                'This version is only available for on-site generation on Civitai'
+            );
+        } else if (isEarlyAccess) {
+            downloadTitle = translate(
+                'modals.model.versions.actions.downloadEarlyAccessTooltip',
+                {},
+                'Download this early access version from Civitai'
+            );
+        } else {
+            downloadTitle = translate(
+                'modals.model.versions.actions.downloadTooltip',
+                {},
+                'Download this version'
+            );
+        }
        actions.push(buildActionButton(
            downloadLabel,
-            'version-action-primary',
-            'download',
+            canDownload ? 'version-action-primary' : 'version-action-disabled',
+            canDownload ? 'download' : '',
            {
-                title: isEarlyAccess
-                    ? translate(
-                        'modals.model.versions.actions.downloadEarlyAccessTooltip',
-                        {},
-                        'Download this early access version from Civitai'
-                    )
-                    : translate(
-                        'modals.model.versions.actions.downloadTooltip',
-                        {},
-                        'Download this version'
-                    ),
+                title: downloadTitle,
                iconMarkup: downloadIcon,
+                disabled: !canDownload,
            }
        ));
    } else if (version.filePath) {
--- a/static/js/components/shared/showcase/ShowcaseView.js
+++ b/static/js/components/shared/showcase/ShowcaseView.js
@@ -17,6 +17,7 @@ import {
 import { generateMetadataPanel } from './MetadataPanel.js';
 import { generateImageWrapper, generateVideoWrapper } from './MediaRenderers.js';
 import { getShowcaseUrl } from '../../../utils/civitaiUtils.js';
+import { openMediaViewer } from '../MediaViewer.js';

 export const showcaseListenerMetrics = {
    wheelListeners: 0,
@@ -640,6 +641,27 @@ export function initShowcaseContent(carousel) {
    initMediaControlHandlers(carousel);
    positionAllMediaControls(carousel);

+    // Click-to-view: open full-size media viewer when clicking showcase images/videos
+    const viewerElements = carousel.querySelectorAll('.media-wrapper img, .media-wrapper video');
+    const allItems = [];
+    const elementIndexMap = new Map();
+    viewerElements.forEach((el) => {
+        const isVideo = el.tagName === 'VIDEO';
+        const url = el.src || el.dataset.localSrc || el.dataset.remoteSrc;
+        if (url) {
+            elementIndexMap.set(el, allItems.length);
+            allItems.push({ url, type: isVideo ? 'video' : 'image' });
+        }
+    });
+    viewerElements.forEach((mediaEl) => {
+        const idx = elementIndexMap.get(mediaEl);
+        if (idx === undefined) return;
+        mediaEl.addEventListener('click', (e) => {
+            e.stopPropagation();
+            openMediaViewer(allItems, idx);
+        });
+    });
+
    // Bind scroll-indicator click events
    bindScrollIndicatorEvents(carousel);
    
--- a/static/js/managers/BulkManager.js
+++ b/static/js/managers/BulkManager.js
@@ -3,7 +3,7 @@ import { showToast, copyToClipboard, sendLoraToWorkflow, buildLoraSyntax, getNSF
 import { updateCardsForBulkMode } from '../components/shared/ModelCard.js';
 import { modalManager } from './ModalManager.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
-import { RecipeSidebarApiClient } from '../api/recipeApi.js';
+import { RecipeSidebarApiClient, updateRecipeMetadata, extractRecipeId } from '../api/recipeApi.js';
 import { MODEL_TYPES, MODEL_CONFIG } from '../api/apiConfig.js';
 import { BASE_MODEL_CATEGORIES } from '../utils/constants.js';
 import { getPriorityTagSuggestions } from '../utils/priorityTagHelpers.js';
@@ -41,7 +41,9 @@ export class BulkManager {
                autoOrganize: true,
                deleteAll: true,
                setContentRating: true,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
            },
            [MODEL_TYPES.EMBEDDING]: {
                addTags: true,
@@ -53,7 +55,9 @@ export class BulkManager {
                autoOrganize: true,
                deleteAll: true,
                setContentRating: false,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
            },
            [MODEL_TYPES.CHECKPOINT]: {
                addTags: true,
@@ -65,10 +69,12 @@ export class BulkManager {
                autoOrganize: true,
                deleteAll: true,
                setContentRating: true,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
            },
            recipes: {
-                addTags: false,
+                addTags: true,
                sendToWorkflow: false,
                copyAll: false,
                refreshAll: false,
@@ -77,7 +83,10 @@ export class BulkManager {
                autoOrganize: false,
                deleteAll: true,
                setContentRating: false,
-                skipMetadataRefresh: false
+                skipMetadataRefresh: false,
+                setFavorite: true,
+                unfavorite: true,
+                repairMetadata: true
            }
        };

@@ -538,9 +547,23 @@ export class BulkManager {
            return;
        }

-        const countElement = document.getElementById('bulkDeleteCount');
-        if (countElement) {
-            countElement.textContent = state.selectedModels.size;
+        const count = state.selectedModels.size;
+        const isRecipes = state.currentPageType === 'recipes';
+        const keyPrefix = isRecipes ? 'modals.bulkDeleteRecipes' : 'modals.bulkDelete';
+
+        const titleEl = document.querySelector('#bulkDeleteModal h2');
+        if (titleEl) {
+            titleEl.textContent = translate(`${keyPrefix}.title`);
+        }
+
+        const messageEl = document.querySelector('#bulkDeleteModal .delete-message');
+        if (messageEl) {
+            messageEl.textContent = translate(`${keyPrefix}.message`);
+        }
+
+        const countInfoEl = document.querySelector('#bulkDeleteModal .delete-model-info p');
+        if (countInfoEl) {
+            countInfoEl.innerHTML = `<span id="bulkDeleteCount">${count}</span> ${translate(`${keyPrefix}.countMessage`)}`;
        }

        modalManager.showModal('bulkDeleteModal');
@@ -634,6 +657,76 @@ export class BulkManager {
        }
    }

+    async repairSelectedRecipes() {
+        if (state.selectedModels.size === 0) {
+            showToast('toast.recipes.noRecipesSelected', {}, 'warning');
+            return;
+        }
+
+        if (state.currentPageType !== 'recipes') {
+            showToast('This operation is only available for recipes', {}, 'warning');
+            return;
+        }
+
+        try {
+            const apiClient = this.getActiveApiClient();
+            const filePaths = Array.from(state.selectedModels);
+
+            if (typeof apiClient.repairBulkModels !== 'function') {
+                showToast('Bulk repair is not supported for this model type', {}, 'error');
+                return;
+            }
+
+            state.loadingManager.showSimpleLoading('Repairing recipe metadata...');
+
+            const result = await apiClient.repairBulkModels(filePaths);
+
+            if (result.success) {
+                const total = result.total || filePaths.length;
+                const repaired = result.repaired || 0;
+                const skipped = result.skipped || 0;
+
+                const recipes = result.recipes || [];
+                for (const recipe of recipes) {
+                    if (recipe.file_path) {
+                        state.virtualScroller.updateSingleItem(
+                            recipe.file_path,
+                            recipe
+                        );
+                    }
+                }
+
+                if (repaired > 0) {
+                    showToast(
+                        'toast.recipes.repairBulkComplete',
+                        { repaired, skipped, total },
+                        'success'
+                    );
+                } else {
+                    showToast(
+                        'toast.recipes.repairBulkSkipped',
+                        { total },
+                        'info'
+                    );
+                }
+
+                this.clearSelection();
+            } else {
+                throw new Error(result.error || 'Bulk repair failed');
+            }
+        } catch (error) {
+            console.error('Error during bulk recipe repair:', error);
+            showToast('toast.recipes.repairBulkFailed', { message: error.message }, 'error');
+        } finally {
+            if (state.loadingManager?.hide) {
+                state.loadingManager.hide();
+            }
+            if (typeof state.loadingManager?.restoreProgressBar === 'function') {
+                state.loadingManager.restoreProgressBar();
+            }
+        }
+    }
+
    async refreshAllMetadata() {
        if (state.selectedModels.size === 0) {
            showToast('toast.models.noModelsSelected', {}, 'warning');
@@ -763,6 +856,7 @@ export class BulkManager {
        // Setup tag input behavior
        const tagInput = document.querySelector('.bulk-metadata-input');
        if (tagInput) {
+            tagInput.focus();
            tagInput.addEventListener('keydown', (e) => {
                if (e.key === 'Enter') {
                    e.preventDefault();
@@ -986,7 +1080,17 @@ export class BulkManager {

    async saveBulkTags(mode = 'append') {
        const tagElements = document.querySelectorAll('#bulkTagsItems .metadata-item');
-        const tags = Array.from(tagElements).map(tag => tag.dataset.tag);
+        let tags = Array.from(tagElements).map(tag => tag.dataset.tag);
+
+        // Flush uncommitted input as a tag so it's not silently lost on save
+        const tagInput = document.querySelector('.bulk-metadata-input');
+        if (tagInput) {
+            const pendingTag = tagInput.value.trim().toLowerCase();
+            if (pendingTag && !tags.includes(pendingTag)) {
+                tags.push(pendingTag);
+            }
+            tagInput.value = '';
+        }

        if (tags.length === 0) {
            showToast('toast.models.noTagsToAdd', {}, 'warning');
@@ -1010,6 +1114,8 @@ export class BulkManager {
                cancelled = true;
            });

+            const isRecipes = state.currentPageType === 'recipes';
+
            // Add or replace tags for each selected model based on mode
            for (const filePath of filePaths) {
                if (cancelled) {
@@ -1017,7 +1123,9 @@ export class BulkManager {
                    break;
                }
                try {
-                    if (mode === 'replace') {
+                    if (isRecipes) {
+                        await this._saveRecipeTags(filePath, tags, mode);
+                    } else if (mode === 'replace') {
                        await apiClient.saveModelMetadata(filePath, { tags: tags });
                    } else {
                        await apiClient.addTags(filePath, { tags: tags });
@@ -1056,6 +1164,35 @@ export class BulkManager {
        }
    }

+    async _saveRecipeTags(filePath, newTags, mode) {
+        const recipeId = extractRecipeId(filePath);
+        if (!recipeId) throw new Error('Unable to determine recipe ID');
+
+        let finalTags = newTags;
+        if (mode === 'append') {
+            const recipeItem = state.virtualScroller?.items?.find(
+                item => item.file_path === filePath
+            );
+            const existingTags = recipeItem?.tags || [];
+            finalTags = [...new Set([...existingTags, ...newTags])];
+        }
+
+        const response = await fetch(
+            `/api/lm/recipe/${encodeURIComponent(recipeId)}/update`,
+            {
+                method: 'PUT',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({ tags: finalTags }),
+            }
+        );
+        const data = await response.json();
+        if (!data.success) {
+            throw new Error(data.error || 'Failed to update recipe tags');
+        }
+
+        state.virtualScroller.updateSingleItem(filePath, { tags: finalTags });
+    }
+
    cleanupBulkAddTagsModal() {
        // Clear tags container
        const tagsContainer = document.getElementById('bulkTagsItems');
@@ -1090,6 +1227,60 @@ export class BulkManager {
        }
    }

+    async setBulkFavorites(value) {
+        if (state.selectedModels.size === 0) {
+            showToast('toast.models.noModelsSelected', {}, 'warning');
+            return;
+        }
+
+        const totalCount = state.selectedModels.size;
+        const isRecipesPage = state.currentPageType === 'recipes';
+
+        state.loadingManager.showSimpleLoading(
+            translate(value ? 'toast.models.bulkFavoriteUpdating' : 'toast.models.bulkUnfavoriteUpdating', { count: totalCount })
+        );
+        let cancelled = false;
+        state.loadingManager.showCancelButton(() => {
+            cancelled = true;
+        });
+
+        let successCount = 0;
+        let failureCount = 0;
+
+        try {
+            for (const filePath of state.selectedModels) {
+                if (cancelled) {
+                    showToast('toast.api.operationCancelled', {}, 'info');
+                    break;
+                }
+                try {
+                    if (isRecipesPage) {
+                        await updateRecipeMetadata(filePath, { favorite: value });
+                    } else {
+                        const apiClient = getModelApiClient();
+                        await apiClient.saveModelMetadata(filePath, { favorite: value });
+                    }
+                    successCount++;
+                } catch (error) {
+                    failureCount++;
+                    console.error(`Failed to set favorite=${value} for ${filePath}:`, error);
+                }
+            }
+        } finally {
+            state.loadingManager?.hide?.();
+        }
+
+        if (successCount === totalCount) {
+            const toastKey = value ? 'modelCard.favorites.added' : 'modelCard.favorites.removed';
+            showToast(toastKey, {}, 'success');
+        } else if (successCount > 0) {
+            const toastKey = value ? 'toast.models.bulkFavoritePartialAdded' : 'toast.models.bulkFavoritePartialRemoved';
+            showToast(toastKey, { success: successCount, failed: failureCount }, 'warning');
+        } else {
+            showToast('toast.models.bulkFavoriteFailed', {}, 'error');
+        }
+    }
+
    /**
     * Show bulk base model modal
     */
--- a/static/js/managers/DoctorManager.js
+++ b/static/js/managers/DoctorManager.js
@@ -2,6 +2,7 @@ import { modalManager } from './ModalManager.js';
 import { showToast } from '../utils/uiHelpers.js';
 import { translate } from '../utils/i18nHelpers.js';
 import { escapeHtml } from '../components/shared/utils.js';
+import { state } from '../state/index.js';

 const MAX_CONSOLE_ENTRIES = 200;

@@ -224,6 +225,13 @@ export class DoctorManager {
    renderIssueCard(item) {
        const status = item.status || 'ok';
        const tagLabel = this.getStatusLabel(status);
+
+        const titleKey = `doctor.issues.${item.id || ''}.title`;
+        const displayTitle = translate(titleKey, {}, item.title || '');
+
+        const summaryKey = `doctor.issues.${item.id || ''}.summary.${status}`;
+        const displaySummary = translate(summaryKey, {}, item.summary || '');
+
        const details = Array.isArray(item.details) ? item.details : [];
        const listItems = details
            .filter((detail) => typeof detail === 'string')
@@ -234,19 +242,22 @@ export class DoctorManager {
            .map((detail) => this.renderInlineDetail(detail))
            .join('');
        const actions = (item.actions || [])
-            .map((action) => `
+            .map((action) => {
+                const actionLabel = translate(`doctor.actions.${action.id}`, {}, action.label);
+                return `
                <button class="${action.id === 'repair-cache' || action.id === 'reload-page' ? 'primary-btn' : 'secondary-btn'}" data-doctor-action="${escapeHtml(action.id)}">
-                    ${escapeHtml(action.label)}
+                    ${escapeHtml(actionLabel)}
                </button>
-            `)
+            `;
+            })
            .join('');

        return `
            <section class="doctor-issue-card" data-status="${escapeHtml(status)}" data-issue-id="${escapeHtml(item.id || '')}">
                <div class="doctor-issue-header">
                    <div>
-                        <h3>${escapeHtml(item.title || '')}</h3>
-                        <p class="doctor-issue-summary">${escapeHtml(item.summary || '')}</p>
+                        <h3>${escapeHtml(displayTitle)}</h3>
+                        <p class="doctor-issue-summary">${escapeHtml(displaySummary)}</p>
                    </div>
                    <span class="doctor-issue-tag">${escapeHtml(tagLabel)}</span>
                </div>
@@ -258,6 +269,15 @@ export class DoctorManager {
    }

    renderInlineDetail(detail) {
+        if (detail.conflict_groups || detail.total_conflict_files) {
+            return `
+                <div class="doctor-inline-detail">
+                    <strong>${escapeHtml(translate('doctor.labels.conflicts', {}, 'Conflicts'))}</strong>
+                    <div>${escapeHtml(`${detail.conflict_groups || 0} filenames, ${detail.total_conflict_files || 0} files`)}</div>
+                </div>
+            `;
+        }
+
        if (detail.client_version || detail.server_version) {
            return `
                <div class="doctor-inline-detail">
@@ -314,9 +334,43 @@ export class DoctorManager {
                    }
                }, 100);
                break;
+            case 'open-settings-syntax-format':
+                modalManager.showModal('settingsModal');
+                window.setTimeout(() => {
+                    // Switch to Interface section
+                    document.querySelectorAll('.settings-section').forEach((s) => s.classList.remove('active'));
+                    const interfaceSection = document.getElementById('section-interface');
+                    if (interfaceSection) {
+                        interfaceSection.classList.add('active');
+                    }
+                    document.querySelectorAll('.settings-nav-item').forEach((n) => n.classList.remove('active'));
+                    const interfaceNav = document.querySelector('.settings-nav-item[data-section="interface"]');
+                    if (interfaceNav) {
+                        interfaceNav.classList.add('active');
+                    }
+
+                    // Focus and scroll to the LoRA Syntax Format dropdown
+                    const select = document.getElementById('loraSyntaxFormat');
+                    if (select) {
+                        select.focus();
+                        select.scrollIntoView({ behavior: 'smooth', block: 'center' });
+                        // Add temporary highlight animation
+                        const settingItem = select.closest('.setting-item');
+                        if (settingItem) {
+                            settingItem.classList.add('settings-setting-highlight');
+                            setTimeout(() => {
+                                settingItem.classList.remove('settings-setting-highlight');
+                            }, 4500);
+                        }
+                    }
+                }, 100);
+                break;
            case 'repair-cache':
                await this.repairCache();
                break;
+            case 'resolve-filename-conflicts':
+                await this.promptResolveConflicts();
+                break;
            case 'reload-page':
                this.reloadUi();
                break;
@@ -345,6 +399,103 @@ export class DoctorManager {
        }
    }

+    _getConflictStats() {
+        const conflict = (this.lastDiagnostics?.diagnostics || []).find(
+            (d) => d.id === 'filename_conflicts'
+        );
+        if (!conflict || !Array.isArray(conflict.details)) {
+            return { groups: 0, files: 0 };
+        }
+        const summary = conflict.details.find(
+            (d) => d && typeof d === 'object' && d.conflict_groups !== undefined
+        );
+        return {
+            groups: summary?.conflict_groups || 0,
+            files: summary?.total_conflict_files || 0,
+        };
+    }
+
+    async promptResolveConflicts() {
+        const stats = this._getConflictStats();
+        if (stats.groups === 0) {
+            return;
+        }
+
+        const detailEl = document.getElementById('resolveConflictsDetail');
+        if (detailEl) {
+            detailEl.innerHTML = translate(
+                'conflictConfirm.detail',
+                {},
+                'Example: <code>Add_Details_v1.2</code> \u2192 <code>Add_Details_v1.2-a3f7</code>'
+            );
+        }
+
+        const impactEl = document.getElementById('resolveConflictsImpact');
+        if (impactEl) {
+            impactEl.innerHTML = translate(
+                'conflictConfirm.impact',
+                { count: stats.files, groups: stats.groups },
+                `Will rename <strong>${stats.files}</strong> file(s) across <strong>${stats.groups}</strong> duplicate group(s).`
+            );
+        }
+
+        this._confirmResolveResolve = null;
+        modalManager.showModal('resolveFilenameConflictsModal');
+        return new Promise((resolve) => {
+            this._confirmResolveResolve = resolve;
+        });
+    }
+
+    async confirmResolveConflicts() {
+        modalManager.closeModal('resolveFilenameConflictsModal');
+        if (this._confirmResolveResolve) {
+            this._confirmResolveResolve(true);
+            this._confirmResolveResolve = null;
+        }
+        await this.resolveFilenameConflicts();
+    }
+
+    async resolveFilenameConflicts() {
+        try {
+            this.setLoading(true);
+            const response = await fetch('/api/lm/doctor/resolve-filename-conflicts', { method: 'POST' });
+            const payload = await response.json();
+
+            if (!response.ok || payload.success === false) {
+                throw new Error(payload.error || 'Failed to resolve filename conflicts.');
+            }
+
+            const renamedCount = payload.count || 0;
+            showToast(
+                'doctor.toast.conflictsResolved',
+                { count: renamedCount },
+                'success'
+            );
+
+            // Update scroller items so model cards reflect new filenames immediately
+            if (state.virtualScroller && payload.renamed) {
+                for (const renamed of payload.renamed) {
+                    const baseName = renamed.new_filename.replace(/\.[^.]+$/, '');
+                    state.virtualScroller.updateSingleItem(renamed.old_path, {
+                        file_name: baseName,
+                        file_path: renamed.new_path,
+                    });
+                }
+            }
+
+            await this.refreshDiagnostics({ silent: true });
+        } catch (error) {
+            console.error('Doctor filename conflict resolution failed:', error);
+            showToast(
+                'doctor.toast.conflictsResolveFailed',
+                { message: error.message },
+                'error'
+            );
+        } finally {
+            this.setLoading(false);
+        }
+    }
+
    async exportBundle() {
        try {
            this.setLoading(true);
@@ -395,3 +546,8 @@ export class DoctorManager {
 }

 export const doctorManager = new DoctorManager();
+
+// Make available globally for HTML onclick handlers
+if (typeof window !== 'undefined') {
+    window.doctorManager = doctorManager;
+}
--- a/static/js/managers/FilterManager.js
+++ b/static/js/managers/FilterManager.js
@@ -70,6 +70,9 @@ export class FilterManager {
        // Initialize tag logic toggle
        this.initializeTagLogicToggle();

+        // Create auto-tag filter section (I2V, T2V, TI2V, Lightning, Turbo)
+        this.createAutoTagFilters();
+
        // Add click handler for filter button
        if (this.filterButton) {
            this.filterButton.addEventListener('click', () => {
@@ -480,6 +483,58 @@ export class FilterManager {
        }
    }

+    AUTO_TAG_FILTER_TAGS = ['I2V', 'T2V', 'TI2V', 'Lightning', 'Turbo'];
+
+    createAutoTagFilters() {
+        const container = document.getElementById('autoTagFilterTags');
+        if (container) return;
+
+        const modelTypeSection = document.getElementById('modelTypeTags')?.closest('.filter-section');
+        if (!modelTypeSection) return;
+
+        const section = document.createElement('div');
+        section.className = 'filter-section';
+        section.innerHTML = `
+            <h4>${translate('header.filter.autoTags', {}, 'Auto Tags')}</h4>
+            <div class="filter-tags" id="autoTagFilterTags"></div>
+        `;
+        modelTypeSection.parentNode.insertBefore(section, modelTypeSection.nextSibling);
+
+        const tagsContainer = document.getElementById('autoTagFilterTags');
+        this.AUTO_TAG_FILTER_TAGS.forEach(tag => {
+            const el = document.createElement('div');
+            el.className = 'filter-tag auto-tag-filter';
+            el.dataset.autoTag = tag;
+            el.textContent = tag;
+
+            // Restore previous state
+            const state = (this.filters.autoTags && this.filters.autoTags[tag]) || 'none';
+            this._applyTriState(el, state);
+
+            el.addEventListener('click', async () => {
+                const current = (this.filters.autoTags && this.filters.autoTags[tag]) || 'none';
+                const next = current === 'none' ? 'include' : current === 'include' ? 'exclude' : 'none';
+                if (!this.filters.autoTags) this.filters.autoTags = {};
+                if (next === 'none') {
+                    delete this.filters.autoTags[tag];
+                } else {
+                    this.filters.autoTags[tag] = next;
+                }
+                this._applyTriState(el, next);
+                this.updateActiveFiltersCount();
+                await this.applyFilters(false);
+            });
+
+            tagsContainer.appendChild(el);
+        });
+    }
+
+    _applyTriState(el, state) {
+        el.classList.remove('active', 'exclude');
+        if (state === 'include') el.classList.add('active');
+        else if (state === 'exclude') el.classList.add('exclude');
+    }
+
    toggleFilterPanel() {
        if (this.filterPanel) {
            const isHidden = this.filterPanel.classList.contains('hidden');
@@ -540,6 +595,13 @@ export class FilterManager {
            this.updateLicenseSelections();
        }
        this.updateModelTypeSelections();
+
+        const autoTagEls = document.querySelectorAll('.auto-tag-filter');
+        autoTagEls.forEach(el => {
+            const tag = el.dataset.autoTag;
+            const state = (this.filters.autoTags && this.filters.autoTags[tag]) || 'none';
+            this._applyTriState(el, state);
+        });
    }

    updateModelTypeSelections() {
@@ -556,11 +618,12 @@ export class FilterManager {

    updateActiveFiltersCount() {
        const tagFilterCount = this.filters.tags ? Object.keys(this.filters.tags).length : 0;
+        const autoTagFilterCount = this.filters.autoTags ? Object.keys(this.filters.autoTags).length : 0;
        const licenseFilterCount = this.filters.license ? Object.keys(this.filters.license).length : 0;
        const modelTypeFilterCount = this.filters.modelTypes.length;
        // Exclude EMPTY_WILDCARD_MARKER from base model count
        const baseModelCount = this.filters.baseModel.filter(m => m !== EMPTY_WILDCARD_MARKER).length;
-        const totalActiveFilters = baseModelCount + tagFilterCount + licenseFilterCount + modelTypeFilterCount;
+        const totalActiveFilters = baseModelCount + tagFilterCount + autoTagFilterCount + licenseFilterCount + modelTypeFilterCount;

        if (this.activeFiltersCount) {
            if (totalActiveFilters > 0) {
@@ -599,7 +662,7 @@ export class FilterManager {

        // Call the appropriate manager's load method based on page type
        if (this.currentPage === 'recipes' && window.recipeManager) {
-            await window.recipeManager.loadRecipes(true);
+            await window.recipeManager.loadRecipes({ preserveScroll: true });
        } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints') {
            // For models page, reset the page and reload
            await getModelApiClient().loadMoreWithVirtualScroll(true, false);
@@ -652,6 +715,7 @@ export class FilterManager {
            ...this.filters,
            baseModel: [],
            tags: {},
+            autoTags: {},
            license: {},
            modelTypes: [],
            tagLogic: 'any'
@@ -682,7 +746,7 @@ export class FilterManager {

        // Reload data using the appropriate method for the current page
        if (this.currentPage === 'recipes' && window.recipeManager) {
-            await window.recipeManager.loadRecipes(true);
+            await window.recipeManager.loadRecipes({ preserveScroll: true });
        } else if (this.currentPage === 'loras' || this.currentPage === 'checkpoints' || this.currentPage === 'embeddings') {
            await getModelApiClient().loadMoreWithVirtualScroll(true, true);
        }
@@ -721,6 +785,7 @@ export class FilterManager {

    hasActiveFilters() {
        const tagCount = this.filters.tags ? Object.keys(this.filters.tags).length : 0;
+        const autoTagCount = this.filters.autoTags ? Object.keys(this.filters.autoTags).length : 0;
        const licenseCount = this.filters.license ? Object.keys(this.filters.license).length : 0;
        const modelTypeCount = this.filters.modelTypes.length;
        // Exclude EMPTY_WILDCARD_MARKER from base model count
@@ -728,6 +793,7 @@ export class FilterManager {
        return (
            baseModelCount > 0 ||
            tagCount > 0 ||
+            autoTagCount > 0 ||
            licenseCount > 0 ||
            modelTypeCount > 0
        );
@@ -739,6 +805,7 @@ export class FilterManager {
            ...source,
            baseModel: Array.isArray(source.baseModel) ? [...source.baseModel] : [],
            tags: this.normalizeTagFilters(source.tags),
+            autoTags: this.normalizeTagFilters(source.autoTags),
            license: this.shouldShowLicenseFilters() ? this.normalizeLicenseFilters(source.license) : {},
            modelTypes: this.normalizeModelTypeFilters(source.modelTypes),
            tagLogic: source.tagLogic || 'any'
@@ -822,6 +889,7 @@ export class FilterManager {
            ...this.filters,
            baseModel: [...(this.filters.baseModel || [])],
            tags: { ...(this.filters.tags || {}) },
+            autoTags: { ...(this.filters.autoTags || {}) },
            license: { ...(this.filters.license || {}) },
            modelTypes: [...(this.filters.modelTypes || [])],
            tagLogic: this.filters.tagLogic || 'any'
--- a/static/js/managers/ModalManager.js
+++ b/static/js/managers/ModalManager.js
@@ -316,6 +316,19 @@ export class ModalManager {
            });
        }

+        // Register resolveFilenameConflictsModal
+        const resolveFilenameConflictsModal = document.getElementById('resolveFilenameConflictsModal');
+        if (resolveFilenameConflictsModal) {
+            this.registerModal('resolveFilenameConflictsModal', {
+                element: resolveFilenameConflictsModal,
+                onClose: () => {
+                    this.getModal('resolveFilenameConflictsModal').element.classList.remove('show');
+                    document.body.classList.remove('modal-open');
+                },
+                closeOnOutsideClick: true
+            });
+        }
+
        document.addEventListener('keydown', this.boundHandleEscape);
        this.initialized = true;
    }
@@ -396,7 +409,8 @@ export class ModalManager {
          id === "modelDuplicateDeleteModal" ||
          id === "clearCacheModal" ||
          id === "bulkDeleteModal" ||
-          id === "checkUpdatesConfirmModal"
+          id === "checkUpdatesConfirmModal" ||
+          id === "resolveFilenameConflictsModal"
        ) {
          modal.element.classList.add("show");
        } else {
--- a/static/js/managers/SearchManager.js
+++ b/static/js/managers/SearchManager.js
@@ -301,7 +301,7 @@ export class SearchManager {
      
      // Call the appropriate manager's load method based on page type
      if (this.currentPage === 'recipes' && window.recipeManager) {
-        window.recipeManager.loadRecipes(true); // true to reset pagination
+        window.recipeManager.loadRecipes({ preserveScroll: true });
      } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints') {
        // For models page, reset the page and reload
        getModelApiClient().loadMoreWithVirtualScroll(true, false);
--- a/static/js/managers/SettingsManager.js
+++ b/static/js/managers/SettingsManager.js
@@ -295,6 +295,13 @@ export class SettingsManager {
        // Update state
        state.global.settings[settingKey] = value;

+        if (settingKey === 'lora_syntax_format') {
+            try {
+                localStorage.setItem('lm:lora-syntax-format-changed', Date.now().toString());
+            } catch (_) {
+            }
+        }
+
        if (!this.isBackendSetting(settingKey)) {
            return;
        }
@@ -879,6 +886,12 @@ export class SettingsManager {
            modelCardFooterActionSelect.value = state.global.settings.model_card_footer_action || 'example_images';
        }

+        // Set show version on card
+        const showVersionOnCardCheckbox = document.getElementById('showVersionOnCard');
+        if (showVersionOnCardCheckbox) {
+            showVersionOnCardCheckbox.checked = state.global.settings.show_version_on_card !== false;
+        }
+
        // Set model name display setting
        const modelNameDisplaySelect = document.getElementById('modelNameDisplay');
        if (modelNameDisplaySelect) {
@@ -943,6 +956,12 @@ export class SettingsManager {
            includeTriggerWordsCheckbox.checked = state.global.settings.include_trigger_words || false;
        }

+        // Set lora syntax format
+        const loraSyntaxFormatSelect = document.getElementById('loraSyntaxFormat');
+        if (loraSyntaxFormatSelect) {
+            loraSyntaxFormatSelect.value = state.global.settings.lora_syntax_format || 'legacy';
+        }
+
        // Load metadata archive settings
        await this.loadMetadataArchiveSettings();

@@ -2857,7 +2876,7 @@ export class SettingsManager {
            await resetAndReload(false);
        } else if (this.currentPage === 'recipes') {
            // Reload the recipes without updating folders
-            await window.recipeManager.loadRecipes();
+            await window.recipeManager.loadRecipes({ preserveScroll: true });
        } else if (this.currentPage === 'checkpoints') {
            // Reload the checkpoints without updating folders
            await resetAndReload(false);
@@ -2890,6 +2909,10 @@ export class SettingsManager {
        const cardInfoDisplay = state.global.settings.card_info_display || 'always';
        document.body.classList.toggle('hover-reveal', cardInfoDisplay === 'hover');

+        // Apply show version on card setting
+        const showVersionOnCard = state.global.settings.show_version_on_card !== false;
+        document.body.classList.toggle('hide-card-version', !showVersionOnCard);
+
        const shouldShowSidebar = state.global.settings.show_folder_sidebar !== false;
        if (sidebarManager && typeof sidebarManager.setSidebarEnabled === 'function') {
            sidebarManager.setSidebarEnabled(shouldShowSidebar).catch((error) => {
--- a/static/js/managers/UpdateService.js
+++ b/static/js/managers/UpdateService.js
@@ -731,9 +731,16 @@ export class UpdateService {
    }
    
    // Simple markdown parser for changelog items
+    // Simple markdown parser for changelog items
+    // Escape HTML entities first so angle brackets in content (e.g. `<lora:x>`)
+    // aren't swallowed by innerHTML's HTML parser as invalid tags
    parseMarkdown(text) {
        if (!text) return '';
        
+        text = text.replace(/&/g, '&amp;');
+        text = text.replace(/</g, '&lt;');
+        text = text.replace(/>/g, '&gt;');
+        
        // Handle bold text (**text**)
        text = text.replace(/\*\*(.*?)\*\*/g, '<strong>$1</strong>');
        
--- a/static/js/recipes.js
+++ b/static/js/recipes.js
@@ -19,7 +19,7 @@ class RecipePageControls {
    }

    async resetAndReload() {
-        refreshVirtualScroll();
+        await refreshVirtualScroll({ preserveScroll: true });
    }

    async refreshModels(fullRebuild = false) {
@@ -286,16 +286,6 @@ class RecipeManager {
            });
        });

-        // Handle quick refresh option (Sync Changes)
-        const quickRefreshOption = document.querySelector('[data-action="quick-refresh"]');
-        if (quickRefreshOption) {
-            quickRefreshOption.addEventListener('click', (e) => {
-                e.stopPropagation();
-                this.pageControls.refreshModels(false);
-                this.closeDropdowns();
-            });
-        }
-
        // Handle full rebuild option (Rebuild Cache)
        const fullRebuildOption = document.querySelector('[data-action="full-rebuild"]');
        if (fullRebuildOption) {
@@ -407,4 +397,4 @@ document.addEventListener('DOMContentLoaded', async () => {
 });

 // Export for use in other modules
-export { RecipeManager };
+export { RecipeManager };
--- a/static/js/state/index.js
+++ b/static/js/state/index.js
@@ -37,7 +37,9 @@ const DEFAULT_SETTINGS_BASE = Object.freeze({
    card_info_display: 'always',
    show_folder_sidebar: true,
    model_name_display: 'model_name',
+    lora_syntax_format: 'legacy',
    model_card_footer_action: 'example_images',
+    show_version_on_card: true,
    include_trigger_words: false,
    compact_mode: false,
    priority_tags: { ...DEFAULT_PRIORITY_TAG_CONFIG },
@@ -49,6 +51,7 @@ const DEFAULT_SETTINGS_BASE = Object.freeze({
    download_skip_base_models: [],
    backup_auto_enabled: true,
    backup_retention_count: 5,
+    strip_lora_on_copy: false,
 });

 export function createDefaultSettings() {
--- a/Show More
+++ b/Show More