chore(release): bump version to v1.0.11

Build a local_cache from the scanner cache before calling the metadata
parser. When a resource hash is found in the cache, populate the entry
directly from cached civitai metadata instead of calling CivitAI's
/model-versions/by-hash endpoint.

This eliminates redundant API calls and retries for the common case
where the example image only uses the parent model plus a checkpoint.

.github/ISSUE_TEMPLATE/feature_request.md

@@ -13,8 +13,5 @@ A clear and concise description of what the problem is. Ex. I'm always frustrate
 **Describe the solution you'd like**
 A clear and concise description of what you want to happen.
 
-**Describe alternatives you've considered**
-A clear and concise description of any alternative solutions or features you've considered.
-
 **Additional context**
 Add any other context or screenshots about the feature request here.

.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/

data/supporters.json

@@ -7,22 +7,20 @@
   ],
   "allSupporters": [
     "Insomnia Art Designs",
+    "2018cfh",
     "megakirbs",
     "Brennok",
-    "2018cfh",
     "W+K+White",
     "wackop",
     "Phil",
     "Carl G.",
     "Arlecchino Shion",
-    "stone9k",
-    "$MetaSamsara",
-    "itismyelement",
-    "Gingko Biloba",
-    "onesecondinosaur",
-    "Takkan",
     "Charles Blakemore",
     "Rob Williams",
+    "stone9k",
+    "itismyelement",
+    "$MetaSamsara",
+    "onesecondinosaur",
     "Rosenthal",
     "Francisco Tatis",
     "Tobi_Swagg",
@@ -32,19 +30,18 @@
     "JongWon Han",
     "VantAI",
     "runte3221",
-    "Illrigger",
     "FreelancerZ",
     "Edgar Tejeda",
-    "Jorge Hussni",
-    "Liam MacDougal",
     "Fraser Cross",
+    "Liam MacDougal",
     "Polymorphic Indeterminate",
     "Marc Whiffen",
-    "Birdy",
     "Skalabananen",
+    "Birdy",
     "Kiba",
-    "Reno Lam",
     "Mozzel",
+    "Gingko Biloba",
+    "Reno Lam",
     "sig",
     "Christian Byrne",
     "DM",
@@ -52,14 +49,13 @@
     "Estragon",
     "J\\B/ 8r0wns0n",
     "Snaggwort",
+    "Takkan",
+    "Matt+J",
     "ClockDaemon",
-    "Jonathan Ross",
     "KD",
     "Omnidex",
-    "Nazono_hito",
     "Tyler Trebuchon",
     "Release Cabrakan",
-    "contrite831",
     "SG",
     "carozzz",
     "James Dooley",
@@ -71,20 +67,18 @@
     "SarcasticHashtag",
     "Anthony Rizzo",
     "iamresist",
-    "Gooohokrbe",
     "RedrockVP",
     "Wolffen",
     "James Todd",
-    "OldBones",
     "Steven Pfeiffer",
     "Tim",
     "Timmy",
     "Johnny",
     "Lisster",
     "Michael Wong",
+    "Illrigger",
     "whudunit",
     "Tom Corrigan",
-    "dl0901dm",
     "JackieWang",
     "fnkylove",
     "Yushio",
@@ -95,23 +89,25 @@
     "PM",
     "Todd Keck",
     "Briton Heilbrun",
-    "Aleksander Wujczyk",
-    "BadassArabianMofo",
+    "Jorge Hussni",
     "Sterilized",
+    "BadassArabianMofo",
     "Pascal Dahle",
     "quarz",
-    "Penfore",
     "Greg",
     "JSST",
     "lmsupporter",
     "zounic",
     "wfpearl",
     "Baekdoosixt",
+    "Jonathan Ross",
     "Jack B Nimble",
+    "Nazono_hito",
     "Melville Parrish",
     "daniel dove",
     "Lustre",
     "JW Sin",
+    "contrite831",
     "Alex",
     "bh",
     "Marlon Daniels",
@@ -119,10 +115,10 @@
     "Aaron Bleuer",
     "LacesOut!",
     "greebles",
-    "Cosmosis",
     "M Postkasse",
-    "FloPro4Sho",
-    "ASLPro3D",
+    "Gooohokrbe",
+    "Wicked Choices by ASLPro3D",
+    "OldBones",
     "Jacob Hoehler",
     "FinalyFree",
     "Weasyl",
@@ -134,34 +130,32 @@
     "Big Red",
     "Jimmy Ledbetter",
     "Luc Job",
+    "dl0901dm",
     "Philip Hempel",
     "corde",
     "Nick Walker",
-    "Julian V",
-    "Steven Owens",
     "Bishoujoker",
     "aai",
     "Tori",
     "wildnut",
     "jean jahren",
+    "Aleksander Wujczyk",
     "AM Kuro",
-    "ViperC",
     "Ran C",
+    "ViperC",
+    "Penfore",
     "Sangheili460",
     "MagnaInsomnia",
     "Karl P.",
     "Akira_HentAI",
     "Gordon Cole",
-    "yuxz69",
-    "esthe",
+    "AbstractAss",
     "andrew.tappan",
     "N/A",
     "The Spawn",
     "graysock",
-    "Pozadine1",
     "Greenmoustache",
     "fancypants",
-    "IamAyam",
     "Eldithor",
     "Joboshy",
     "Digital",
@@ -169,7 +163,6 @@
     "takyamtom",
     "Bohemian Corporal",
     "Dan",
-    "confiscated Zyra",
     "Jwk0205",
     "Bro Xie",
     "yer fey",
@@ -177,48 +170,39 @@
     "carey6409",
     "Olive",
     "太郎 ゲーム",
-    "Tee Gee",
     "Some Guy Named Barry",
     "jinxedx",
-    "tarek helmi",
-    "Max Marklund",
+    "Cosmosis",
     "AELOX",
     "Dankin",
     "Nicfit23",
+    "FloPro4Sho",
     "wamekukyouzin",
     "drum matthieu",
     "Dogmaster",
     "Matt Wenzel",
     "Frank Nitty",
-    "Pronredn",
     "Christopher Michel",
     "Serge Bekenkamp",
-    "DougPeterson",
     "LeoZero",
     "Antonio Pontes",
     "ApathyJones",
+    "Julian V",
+    "Steven Owens",
     "nahinahi9",
-    "lh qwe",
-    "Kevin John Duck",
-    "conner",
     "Dustin Chen",
     "dan",
     "Blackfish95",
     "Mouthlessman",
-    "Princess Bright Eyes",
     "Paul Kroll",
-    "AbstractAss",
     "otaku fra",
-    "Felipe dos Santos",
-    "Bas Imagineer",
-    "Markus",
     "MiraiKuriyamaSy",
+    "Bas Imagineer",
+    "yuxz69",
     "Adam Taylor",
-    "Douglas Gaspar",
     "Weird_With_A_Beard",
-    "AlexDuKaNa",
-    "George",
-    "dw",
+    "esthe",
+    "Pozadine1",
     "Qarob",
     "AIGooner",
     "Luc",
@@ -234,43 +218,40 @@
     "mr_dinosaur",
     "Tyrswood",
     "linnfrey",
-    "Pkrsky",
-    "奚明 刘",
+    "IamAyam",
+    "skaterb949",
     "Josef Lanzl",
-    "Nerezza",
-    "Griffin Dahlberg",
-    "준희 김",
+    "confiscated Zyra",
     "Error_Rule34_Not_found",
     "Gerald Welly",
     "Roslynd",
+    "Tee Gee",
     "Geolog",
+    "tarek helmi",
     "Neco28",
-    "Tomohiro Baba",
+    "Max Marklund",
     "David Ortega",
-    "Noora",
     "Cristian Vazquez",
-    "Mattssn",
     "Magic Noob",
+    "Pronredn",
+    "DougPeterson",
     "Jeff",
     "Bruce",
+    "lh qwe",
+    "Kevin John Duck",
+    "conner",
     "Kevin Christopher",
-    "Ouro Boros",
-    "Chad Idk",
-    "Yaboi",
     "dd",
-    "Steam Steam",
-    "CryptoTraderJK",
-    "Davaitamin",
+    "Princess Bright Eyes",
     "Dušan Ryban",
-    "tedcor",
-    "Fotek Design",
-    "sjon kreutz",
+    "Felipe dos Santos",
     "John Statham",
-    "MadSpin",
+    "Douglas Gaspar",
     "Metryman55",
-    "inbijiburu",
+    "AlexDuKaNa",
+    "George",
+    "dw",
     "decoy",
-    "Nick “Loadstone” D",
     "Ray Wing",
     "Ranzitho",
     "Gus",
@@ -288,19 +269,15 @@
     "Piccio08",
     "kumakichi",
     "cppbel",
-    "starbugx",
     "Moon Knight",
     "몽타주",
     "Kland",
     "Hailshem",
-    "kudari",
-    "Naomi Hale Danchi",
-    "dc7431",
-    "Vir",
+    "奚明 刘",
     "Brian M",
+    "Nerezza",
     "sanborondon",
-    "Seth Christensen",
-    "Draven T",
+    "준희 김",
     "Taylor Funk",
     "aezin",
     "Thought2Form",
@@ -308,36 +285,39 @@
     "Kevin Picco",
     "Erik Lopez",
     "Mateo Curić",
-    "Aquatic Coffee",
     "Eris3D",
+    "Tomohiro Baba",
     "m",
-    "ethanfel",
+    "Noora",
     "Pierce McBride",
     "Joshua Gray",
-    "Focuschannel",
+    "Mattssn",
     "Mikko Hemilä",
     "Jamie Ogletree",
     "a _",
     "James Coleman",
     "Martial",
-    "Anthony Faxlandez",
-    "battu",
     "Emil Andersson",
+    "Ouro Boros",
+    "Chad Idk",
+    "Steam Steam",
+    "CryptoTraderJK",
     "Yuji Kaneko",
-    "Pat Hen",
-    "semicolon drainpipe",
-    "Jordan Shaw",
+    "Davaitamin",
     "Rops Alot",
-    "Thesharingbrother",
+    "tedcor",
     "Sam",
+    "Fotek Design",
+    "sjon kreutz",
     "Ace Ventura",
-    "ResidentDeviant",
-    "Nihongasuki",
-    "JC",
-    "Prompt Pirate",
-    "uwutismxd",
+    "MadSpin",
+    "inbijiburu",
+    "Nick “Loadstone” D",
     "momokai",
-    "zenobeus",
+    "starbugx",
+    "kudari",
+    "Naomi Hale Danchi",
+    "dc7431",
     "ken",
     "epicgamer0020690",
     "Joshua Porrata",
@@ -345,7 +325,6 @@
     "SuBu",
     "RedPIXel",
     "Wind",
-    "Jackthemind",
     "Nexus",
     "Ramneek“Guy”Ashok",
     "squid_actually",
@@ -358,37 +337,29 @@
     "emyth",
     "chriphost",
     "KitKatM",
-    "ryoma",
     "socrasteeze",
     "OrganicArtifact",
-    "Stryker",
-    "MudkipMedkitz",
+    "Vir",
     "gzmzmvp",
-    "raf8osz",
-    "ElitaSSJ4",
     "Richard",
-    "blikkies",
     "Andrew",
-    "Chris",
     "Robert Wegemund",
     "Littlehuggy",
     "Gregory Kozhemiak",
+    "Draven T",
     "mrjuan",
     "Brian Buie",
-    "Shock Shockor",
     "Sadlip",
-    "Goldwaters",
     "Eric Whitney",
     "Joey Callahan",
-    "Zude",
+    "Aquatic Coffee",
     "Ivan Tadic",
     "Mike Simone",
-    "John J Linehan",
-    "Kyler",
+    "ethanfel",
     "Elliot E",
     "Morgandel",
     "Theerat Jiramate",
-    "aRtFuL_DodGeR",
+    "Focuschannel",
     "Noah",
     "Jacob McDaniel",
     "X",
@@ -397,38 +368,30 @@
     "Artokun",
     "Michael Taylor",
     "Derek Baker",
-    "CrimsonDX",
+    "Anthony Faxlandez",
+    "battu",
     "Michael Anthony Scott",
-    "DarkSunset",
     "Atilla Berke Pekduyar",
     "Nathan",
-    "Billy Gladky",
-    "NICHOLAS BAXLEY",
     "Decx _",
-    "Probis",
-    "Ed Wang",
-    "ItsGeneralButtNaked",
-    "Nimess",
-    "SRDB",
-    "g unit",
-    "Distortik",
-    "Youguang",
+    "Pat Hen",
+    "Jordan Shaw",
+    "Srdb",
     "四糸凜音",
-    "Saya",
-    "andrewzpong",
+    "Nihongasuki",
+    "LarsesFPC",
+    "JC",
+    "Prompt Pirate",
+    "uwutismxd",
     "FrxzenSnxw",
-    "BossGame",
-    "lrdchs",
-    "Tree Tagger",
-    "Inversity",
+    "zenobeus",
     "Crocket",
-    "AIVORY3D",
-    "Kevinj",
-    "Mitchell Robson",
-    "Whitepinetrader",
+    "Jackthemind",
+    "ryoma",
+    "Stryker",
     "ResidentDeviant",
+    "MudkipMedkitz",
     "deanbrian",
-    "POPPIN",
     "Alex Wortman",
     "Cody",
     "Raku",
@@ -445,56 +408,117 @@
     "moonpetal",
     "SomeDude",
     "g9p0o",
+    "Pkrsky",
     "TheHolySheep",
+    "raf8osz",
     "Monte Won",
     "SpringBootisTrash",
     "carsten",
     "ikok",
-    "Nathen+Choi",
-    "T",
-    "LarsesFPC",
-    "cocona",
-    "sfasdfasfdsa",
-    "Buecyb99",
-    "Welkor",
+    "ElitaSSJ4",
     "David Schenck",
-    "John Martin",
     "Wolfe7D1",
-    "Ink Temptation",
-    "moranqianlong",
-    "Kalli Core",
+    "blikkies",
+    "Chris",
     "elleshar666",
+    "Shock Shockor",
     "ACTUALLY_the_Real_Willem_Dafoe",
-    "Haru Yotu",
+    "Goldwaters",
     "Kauffy",
-    "EpicElric",
-    "Kyron Mahan",
+    "Zude",
+    "John J Linehan",
+    "Kyler",
     "Edward Kennedy",
     "Justin Blaylock",
-    "Matura Arbeit",
+    "aRtFuL_DodGeR",
     "Nick Kage",
-    "TBitz33",
-    "Anonym dkjglfleeoeldldldlkf",
     "Vane Holzer",
     "psytrax",
     "Cyrus Fett",
-    "Ezokewn",
-    "SendingRavens",
     "hexxish",
     "notedfakes",
-    "Michael Docherty",
+    "Billy Gladky",
+    "NICHOLAS BAXLEY",
     "Michael Scott",
+    "Probis",
+    "Ed Wang",
+    "Wes Sims",
+    "ItsGeneralButtNaked",
+    "Donor4115",
+    "g unit",
+    "Distortik",
+    "Filippo Ferrari",
+    "Youguang",
+    "Saya",
+    "andrewzpong",
+    "BossGame",
+    "lrdchs",
+    "Tree Tagger",
+    "Inversity",
+    "AIVORY3D",
+    "Kevinj",
+    "Mitchell Robson",
+    "Whitepinetrader",
+    "POPPIN",
+    "Ginnie",
+    "emadsultan",
+    "nanana",
+    "g",
+    "J",
+    "Alan+Cano",
+    "FeralOpticsAI",
+    "Pavlaki",
+    "Doug+Rintoul",
+    "Noor",
+    "Yorunai",
+    "quantenmecha",
+    "Jason+Nash",
+    "BillyBoy84",
+    "DarkRoast",
+    "letzte",
+    "Nasty+Hobbit",
+    "Sora+Yori",
+    "lrdchs2",
+    "Duk3+Rand0m",
+    "Nathen+Choi",
+    "T",
+    "cocona",
+    "Buecyb99",
+    "Welkor",
+    "John Martin",
+    "Ink Temptation",
+    "JBsuede",
+    "moranqianlong",
+    "Kalli Core",
+    "Time Valentine",
+    "Михал Михалыч",
+    "Matt",
+    "Frogmilk",
+    "SPJ",
+    "Kyron Mahan",
+    "Bryan Rutkowski",
+    "TBitz33",
+    "Anonym dkjglfleeoeldldldlkf",
+    "Ezokewn",
+    "SendingRavens",
+    "Xenon Xue",
+    "JackJohnnyJim",
+    "Edward Ten Eyck",
+    "Michael Docherty",
     "Paul Hartsuyker",
+    "Henrique Faiolli",
     "elitassj",
+    "Solixer",
     "Jacob Winter",
     "Ryan Presley Ng",
-    "Wes Sims",
-    "Donor4115",
+    "jinksta187",
+    "Andrew Wilkinson",
+    "Manu Thetug",
+    "Karlanx",
     "Lyavph",
     "David",
     "Meilo",
-    "Filippo Ferrari",
-    "Pen Bouryoung",
+    "operationancut",
     "shinonomeiro",
     "Snille",
     "MaartenAlbers",
@@ -502,6 +526,7 @@
     "xybrightsummer",
     "jreedatchison",
     "PhilW",
+    "Marcus thronico",
     "Janik",
     "Cruel",
     "MRBlack",
@@ -511,77 +536,78 @@
     "Kalnei",
     "Scott",
     "Muratoraccio",
-    "Ginnie",
-    "emadsultan",
     "D",
-    "nanana",
+    "low9",
+    "Winged",
+    "YassineKhaled",
+    "Y",
+    "MatteKey",
+    "Flob",
+    "ShiroSenpai",
+    "Inkognito",
+    "G",
+    "Tan+Huynh",
+    "D",
+    "Dark_Pest",
+    "Alex",
+    "Jacky+Ho",
+    "Karru",
+    "ghoulars",
+    "ChaChanoKo",
+    "null",
+    "Beau",
+    "redcarrot",
+    "powerbot99",
     "Fthehappy",
-    "rsamerica",
-    "Alan+Cano",
-    "FeralOpticsAI",
-    "Pavlaki",
     "generic404",
-    "Doug+Rintoul",
-    "Noor",
-    "Yorunai",
-    "quantenmecha",
     "abattoirblues",
-    "Jason+Nash",
-    "BillyBoy84",
     "zounik",
-    "DarkRoast",
-    "letzte",
-    "Nasty+Hobbit",
-    "Sora+Yori",
-    "lrdchs2",
-    "Duk3+Rand0m",
     "4IXplr0r3r",
     "hayden",
     "ahoystan",
-    "Leland Saunders",
     "Bob Barker",
     "edk",
-    "JBsuede",
-    "Time Valentine",
-    "Aeternyx",
-    "YOU SINWOO",
+    "Tú Nguyễn Lý Hoàng",
+    "Ronan Delevacq",
+    "Christian Schäfer",
     "りん あめ",
     "ja s",
-    "Михал Михалыч",
-    "Matt",
     "Doug Mason",
     "Jeremy Townsend",
-    "Frogmilk",
+    "Dave Abraham",
+    "Joaquin Hierrezuelo",
+    "Locrospiel",
     "Sean voets",
     "Owen Gwosdz",
-    "SPJ",
-    "Thomas Wanner",
-    "Bryan Rutkowski",
+    "Jarrid Lee",
+    "Kor",
+    "Joseph Hanson",
+    "John Rednoulf",
+    "Boba Smith",
     "Devil Lude",
     "David Murcko",
-    "kevin stoddard",
+    "MR.Bear",
     "Jack Dole",
     "max blo",
-    "Xenon Xue",
+    "Sauv",
+    "Steven",
     "CptNeo",
-    "JackJohnnyJim",
+    "TenaciousD",
     "Dmitry Ryzhov",
+    "Khánh Đặng",
     "Maso",
-    "Edward Ten Eyck",
     "Eric Ketchum",
     "Kevin Wallace",
-    "Matheus Couto",
+    "Jimmy Borup",
     "ChicRic",
-    "Henrique Faiolli",
+    "Tigon",
+    "BastardSama",
     "mercur",
-    "Solixer",
-    "J C",
-    "jinksta187",
-    "Andrew Wilkinson",
-    "Manu Thetug",
-    "Karlanx",
+    "Pete Pain",
+    "RHopkirk",
+    "Yavizu3d",
+    "Maxim",
     "Yves Poezevara",
-    "operationancut",
     "Teriak47",
     "Just me",
     "Raf Stahelin",
@@ -605,7 +631,6 @@
     "pixl",
     "Robin",
     "chahknoir",
-    "Marcus thronico",
     "nd",
     "keno94d",
     "James Melzer",
@@ -619,6 +644,7 @@
     "Captain_Swag",
     "obkircher",
     "gwyar",
+    "ResidentDeviant",
     "D",
     "edgecase",
     "Neoxena",
@@ -629,99 +655,115 @@
     "SelfishMedic",
     "adderleighn",
     "EnragedAntelope",
+    "SRCRCOSS",
+    "imer",
+    "Akkas+Haque",
+    "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",
-    "YassineKhaled",
-    "YK12",
-    "MatteKey",
-    "Flob",
-    "ShiroSenpai",
     "Somebody",
-    "Inkognito",
     "Somebody",
-    "Gramer+Gumbyte",
     "Crescent~San",
-    "Tan+Huynh",
     "AiGirlTS",
-    "D",
     "datasl4ve",
     "Somebody",
-    "Dark_Pest",
-    "Aza",
-    "Jacky+Ho",
     "koopa990",
-    "Karru",
-    "ChaChanoKo",
-    "null",
-    "bo",
     "The+Forgetful+Dev",
-    "redcarrot",
-    "powerbot99",
     "Mateusz+Kosela",
     "Bula",
     "KUJYAKU",
     "Coeur+de+cochon",
+    "Obsidian.Studios",
     "han b",
+    "Zomba Mann",
+    "Aquaneo",
     "Nico",
+    "Maximilian Krischan",
     "Banana Joe",
     "_ G3n",
     "Donovan Jenkins",
-    "Tú Nguyễn Lý Hoàng",
+    "Hans Meier",
+    "shira1011",
+    "sicarius",
     "Michael Eid",
     "beersandbacon",
-    "Maximilian Pyko",
-    "Invis",
+    "Neko Desco",
     "Bob barker",
     "Ben D",
-    "Garrett Wood",
-    "Ronan Delevacq",
-    "james",
-    "Christian Schäfer",
-    "OrochiNights",
+    "Ninja Tom",
+    "G",
+    "karim ben brik",
+    "Vinarus",
     "Michael Zhu",
-    "gonzalo",
+    "Nemisu",
     "Seraphy",
     "雨の心 落",
     "AllTimeNoobie",
+    "Leslie Andrew Ridings",
     "jumpd",
     "John C",
     "Rim",
-    "Dave Abraham",
-    "Joaquin Hierrezuelo",
-    "Dismem",
-    "Locrospiel",
     "Jairus Knudsen",
-    "Jarrid Lee",
+    "Poophead27 Blyat",
     "Xan Dionysus",
     "Nathan lee",
-    "Kor",
-    "Joseph Hanson",
-    "Mewtora",
+    "Lyle Liston",
     "Middo",
     "Forbidden Atelier",
-    "John Rednoulf",
+    "Thomas Sankowski",
     "Spire",
+    "DrB",
+    "AZ Party Oasis",
     "Adictedtohumping",
-    "Boba Smith",
     "Towelie",
-    "MR.Bear",
+    "TheFusion",
+    "matt",
     "dsffsdfsdfsdfsdfsdf",
+    "somethingtosay8",
     "Jean-françois SEMA",
+    "3zS4QNQ4",
+    "Terminuz",
     "Kurt",
     "ivistorm",
-    "Sauv",
-    "Steven",
-    "TenaciousD",
-    "Khánh Đặng",
+    "Matt M.",
+    "Ivan Imes",
+    "Faburizu",
+    "Jack Lawfield",
+    "jimyjomson",
+    "Borte",
     "Chase Kwon",
     "Ted Cart",
+    "Sage Himeros",
     "Inyoshu",
-    "Goober719",
     "Chad Barnes",
     "Person Y",
     "David Spearing",
@@ -731,16 +773,19 @@
     "Rizzi",
     "nimin",
     "OMAR LUCIANO",
+    "Somebody",
+    "CoffeeMage",
     "Ken+Suzuki",
     "hannibal",
     "Jo+Example",
     "BrentBertram",
-    "Tigon",
+    "inusanorthcape",
     "eumelzocker",
     "dxjaymz",
     "L C",
     "Dude",
+    "Somebody",
     "CK"
   ],
-  "totalCount": 739
+  "totalCount": 784
 }

locales/de.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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."
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "Keine Ordner gefunden",
             "dragHint": "Elemente hierher ziehen, um Ordner zu erstellen"
+        },
+        "folderUpdateCheck": {
+            "label": "Auf Updates in diesem Ordner prüfen",
+            "loading": "Prüfe {type}-Updates in diesem Ordner...",
+            "success": "{count} Update(s) für {type}s in diesem Ordner gefunden",
+            "none": "Alle {type}s in diesem Ordner sind aktuell",
+            "error": "Fehler beim Prüfen des Ordners auf {type}-Updates: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "Zuvor heruntergeladen, aber derzeit nicht in Ihrer Bibliothek.",
             "alreadyInLibrary": "Bereits in Bibliothek",
             "autoOrganizedPath": "[Automatisch organisiert durch Pfadvorlage]",
+            "fileSelection": {
+                "title": "Dateiformat auswählen",
+                "files": "Dateien",
+                "select": "Datei auswählen"
+            },
             "errors": {
                 "invalidUrl": "Ungültiges Civitai URL-Format",
                 "noVersions": "Keine Versionen für dieses Modell verfügbar"
@@ -1080,6 +1107,12 @@
             "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.",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "Keine Rezept-ID verfügbar",
             "sendToWorkflowFailed": "Fehler beim Senden des Rezepts an den Workflow: {message}",
             "copyFailed": "Fehler beim Kopieren der Rezept-Syntax: {message}",
+            "createError": "Fehler beim Erstellen des Rezepts：{message}",
+            "createFailed": "Fehler beim Erstellen des Rezepts：{error}",
+            "createMissingData": "Erforderliche Daten zum Erstellen des Rezepts fehlen",
+            "created": "Rezept erfolgreich erstellt",
             "noMissingLoras": "Keine fehlenden LoRAs zum Herunterladen",
             "missingLorasInfoFailed": "Fehler beim Abrufen der Informationen für fehlende LoRAs",
             "preparingForDownloadFailed": "Fehler beim Vorbereiten der LoRAs für den Download",
@@ -1672,6 +1710,9 @@
             "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."
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

locales/en.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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."
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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}...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "No folders found",
             "dragHint": "Drag items here to create folders"
+        },
+        "folderUpdateCheck": {
+            "label": "Check for updates in this folder",
+            "loading": "Checking {type} updates for this folder...",
+            "success": "Found {count} update(s) for {type}s in this folder",
+            "none": "All {type}s in this folder are up to date",
+            "error": "Failed to check folder for {type} updates: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "Previously downloaded, but it is not currently in your library.",
             "alreadyInLibrary": "Already in Library",
             "autoOrganizedPath": "[Auto-organized by path template]",
+            "fileSelection": {
+                "title": "Select File Format",
+                "files": "files",
+                "select": "Select File"
+            },
             "errors": {
                 "invalidUrl": "Invalid Civitai URL format",
                 "noVersions": "No versions available for this model"
@@ -1080,6 +1107,12 @@
             "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.",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "No recipe ID available",
             "sendToWorkflowFailed": "Failed to send recipe to workflow: {message}",
             "copyFailed": "Error copying recipe syntax: {message}",
+            "createError": "Error creating recipe: {message}",
+            "createFailed": "Failed to create recipe: {error}",
+            "createMissingData": "Missing required data to create recipe",
+            "created": "Recipe created successfully",
             "noMissingLoras": "No missing LoRAs to download",
             "missingLorasInfoFailed": "Failed to get information for missing LoRAs",
             "preparingForDownloadFailed": "Error preparing LoRAs for download",
@@ -1672,6 +1710,9 @@
             "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."
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",
@@ -1952,4 +2025,4 @@
             "retry": "Retry"
         }
     }
-}
+}

locales/es.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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."
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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}...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "No se encontraron carpetas",
             "dragHint": "Arrastra elementos aquí para crear carpetas"
+        },
+        "folderUpdateCheck": {
+            "label": "Buscar actualizaciones en esta carpeta",
+            "loading": "Buscando actualizaciones de {type} en esta carpeta...",
+            "success": "Se encontraron {count} actualización(es) para {type}s en esta carpeta",
+            "none": "Todos los {type}s en esta carpeta están actualizados",
+            "error": "Error al buscar actualizaciones de {type} en la carpeta: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "Descargado anteriormente, pero actualmente no está en tu biblioteca.",
             "alreadyInLibrary": "Ya en la biblioteca",
             "autoOrganizedPath": "[Auto-organizado por plantilla de ruta]",
+            "fileSelection": {
+                "title": "Seleccionar formato de archivo",
+                "files": "archivos",
+                "select": "Seleccionar archivo"
+            },
             "errors": {
                 "invalidUrl": "Formato de URL de Civitai inválido",
                 "noVersions": "No hay versiones disponibles para este modelo"
@@ -1080,6 +1107,12 @@
             "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.",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "No hay ID de receta disponible",
             "sendToWorkflowFailed": "Error al enviar la receta al flujo de trabajo: {message}",
             "copyFailed": "Error copiando sintaxis de receta: {message}",
+            "createError": "Error al crear la receta：{message}",
+            "createFailed": "Error al crear la receta：{error}",
+            "createMissingData": "Faltan datos necesarios para crear la receta",
+            "created": "Receta creada exitosamente",
             "noMissingLoras": "No hay LoRAs faltantes para descargar",
             "missingLorasInfoFailed": "Error al obtener información de LoRAs faltantes",
             "preparingForDownloadFailed": "Error preparando LoRAs para descarga",
@@ -1672,6 +1710,9 @@
             "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."
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

locales/fr.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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."
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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}...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "Aucun dossier trouvé",
             "dragHint": "Faites glisser des éléments ici pour créer des dossiers"
+        },
+        "folderUpdateCheck": {
+            "label": "Vérifier les mises à jour dans ce dossier",
+            "loading": "Vérification des mises à jour {type} dans ce dossier...",
+            "success": "{count} mise(s) à jour trouvée(s) pour les {type}s dans ce dossier",
+            "none": "Tous les {type}s dans ce dossier sont à jour",
+            "error": "Échec de la vérification des mises à jour {type} dans ce dossier : {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "Déjà téléchargé, mais il n'est actuellement pas dans votre bibliothèque.",
             "alreadyInLibrary": "Déjà dans la bibliothèque",
             "autoOrganizedPath": "[Auto-organisé par modèle de chemin]",
+            "fileSelection": {
+                "title": "Choisir le format de fichier",
+                "files": "fichiers",
+                "select": "Choisir le fichier"
+            },
             "errors": {
                 "invalidUrl": "Format d'URL Civitai invalide",
                 "noVersions": "Aucune version disponible pour ce modèle"
@@ -1080,6 +1107,12 @@
             "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.",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "Aucun ID de recipe disponible",
             "sendToWorkflowFailed": "Échec de l'envoi de la recette vers le workflow : {message}",
             "copyFailed": "Erreur lors de la copie de la syntaxe de la recipe : {message}",
+            "createError": "Erreur lors de la création du Recipe ：{message}",
+            "createFailed": "Échec de la création du Recipe ：{error}",
+            "createMissingData": "Données requises manquantes pour créer le Recipe",
+            "created": "Recipe créé avec succès",
             "noMissingLoras": "Aucun LoRA manquant à télécharger",
             "missingLorasInfoFailed": "Échec de l'obtention des informations pour les LoRAs manquants",
             "preparingForDownloadFailed": "Erreur lors de la préparation des LoRAs pour le téléchargement",
@@ -1672,6 +1710,9 @@
             "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."
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

locales/he.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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."
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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}...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "לא נמצאו תיקיות",
             "dragHint": "גרור פריטים לכאן כדי ליצור תיקיות"
+        },
+        "folderUpdateCheck": {
+            "label": "בדוק עדכונים בתיקייה זו",
+            "loading": "בודק עדכוני {type} בתיקייה זו...",
+            "success": "נמצאו {count} עדכון/ים עבור {type}s בתיקייה זו",
+            "none": "כל ה-{type}s בתיקייה זו מעודכנים",
+            "error": "נכשל בבדיקת עדכוני {type} בתיקייה: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "הורד בעבר, אך הוא אינו נמצא כרגע בספרייה שלך.",
             "alreadyInLibrary": "כבר בספרייה",
             "autoOrganizedPath": "[מאורגן אוטומטית לפי תבנית נתיב]",
+            "fileSelection": {
+                "title": "בחר פורמט קובץ",
+                "files": "קבצים",
+                "select": "בחר קובץ"
+            },
             "errors": {
                 "invalidUrl": "פורמט URL של Civitai לא חוקי",
                 "noVersions": "אין גרסאות זמינות למודל זה"
@@ -1080,6 +1107,12 @@
             "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.",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "אין מזהה מתכון זמין",
             "sendToWorkflowFailed": "נכשל שליחת המתכון ל-workflow: {message}",
             "copyFailed": "שגיאה בהעתקת תחביר המתכון: {message}",
+            "createError": "שגיאה ביצירת המתכון：{message}",
+            "createFailed": "יצירת המתכון נכשלה：{error}",
+            "createMissingData": "חסרים נתונים נדרשים ליצירת המתכון",
+            "created": "המתכון נוצר בהצלחה",
             "noMissingLoras": "אין LoRAs חסרים להורדה",
             "missingLorasInfoFailed": "קבלת מידע עבור LoRAs חסרים נכשלה",
             "preparingForDownloadFailed": "שגיאה בהכנת LoRAs להורדה",
@@ -1672,6 +1710,9 @@
             "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."
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

locales/ja.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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。"
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "フォルダが見つかりません",
             "dragHint": "ここへアイテムをドラッグしてフォルダを作成します"
+        },
+        "folderUpdateCheck": {
+            "label": "このフォルダのアップデートを確認",
+            "loading": "このフォルダの{type}アップデートを確認中...",
+            "success": "このフォルダの{type}sに{count}件のアップデートが見つかりました",
+            "none": "このフォルダのすべての{type}sは最新です",
+            "error": "フォルダの{type}アップデート確認に失敗しました: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "以前にダウンロード済みですが、現在はライブラリにありません。",
             "alreadyInLibrary": "既にライブラリ内",
             "autoOrganizedPath": "[パステンプレートによる自動整理]",
+            "fileSelection": {
+                "title": "ファイル形式を選択",
+                "files": "ファイル",
+                "select": "ファイルを選択"
+            },
             "errors": {
                 "invalidUrl": "無効なCivitai URL形式",
                 "noVersions": "このモデルの利用可能なバージョンがありません"
@@ -1080,6 +1107,12 @@
             "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。",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "レシピIDが利用できません",
             "sendToWorkflowFailed": "ワークフローへのレシピ送信に失敗しました：{message}",
             "copyFailed": "レシピ構文のコピーエラー：{message}",
+            "createError": "レシピ作成中にエラーが発生しました：{message}",
+            "createFailed": "レシピの作成に失敗しました：{error}",
+            "createMissingData": "レシピ作成に必要なデータが不足しています",
+            "created": "レシピを作成しました",
             "noMissingLoras": "ダウンロードする不足LoRAがありません",
             "missingLorasInfoFailed": "不足LoRAの情報取得に失敗しました",
             "preparingForDownloadFailed": "ダウンロード用LoRAの準備中にエラーが発生しました",
@@ -1672,6 +1710,9 @@
             "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。"
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

locales/ko.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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."
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "폴더를 찾을 수 없습니다",
             "dragHint": "항목을 여기로 드래그하여 폴더를 만듭니다"
+        },
+        "folderUpdateCheck": {
+            "label": "이 폴더의 업데이트 확인",
+            "loading": "이 폴더의 {type} 업데이트를 확인하는 중...",
+            "success": "이 폴더에서 {type}s에 대한 {count}개 업데이트를 찾았습니다",
+            "none": "이 폴더의 모든 {type}s가 최신 상태입니다",
+            "error": "폴더의 {type} 업데이트 확인 실패: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "이전에 다운로드했지만 현재 라이브러리에 없습니다.",
             "alreadyInLibrary": "이미 라이브러리에 있음",
             "autoOrganizedPath": "[경로 템플릿으로 자동 정리됨]",
+            "fileSelection": {
+                "title": "파일 형식 선택",
+                "files": "개 파일",
+                "select": "파일 선택"
+            },
             "errors": {
                 "invalidUrl": "잘못된 Civitai URL 형식",
                 "noVersions": "이 모델에 사용 가능한 버전이 없습니다"
@@ -1080,6 +1107,12 @@
             "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.",
@@ -1160,6 +1193,7 @@
                 "editModelName": "모델명 편집",
                 "editFileName": "파일명 편집",
                 "editBaseModel": "베이스 모델 편집",
+                "editVersionName": "버전명 편집",
                 "viewOnCivitai": "Civitai에서 보기",
                 "viewOnCivitaiText": "Civitai에서 보기",
                 "viewCreatorProfile": "제작자 프로필 보기",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "사용 가능한 레시피 ID가 없습니다",
             "sendToWorkflowFailed": "워크플로우에 레시피 보내기 실패: {message}",
             "copyFailed": "레시피 문법 복사 오류: {message}",
+            "createError": "레시피 생성 중 오류 발생：{message}",
+            "createFailed": "레시피 생성 실패：{error}",
+            "createMissingData": "레시피 생성에 필요한 데이터가 없습니다",
+            "created": "레시피가 생성되었습니다",
             "noMissingLoras": "다운로드할 누락된 LoRA가 없습니다",
             "missingLorasInfoFailed": "누락된 LoRA 정보를 가져오는데 실패했습니다",
             "preparingForDownloadFailed": "LoRA 다운로드 준비 오류",
@@ -1672,6 +1710,9 @@
             "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."
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

locales/ru.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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."
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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}...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "Папки не найдены",
             "dragHint": "Перетащите элементы сюда, чтобы создать папки"
+        },
+        "folderUpdateCheck": {
+            "label": "Проверить обновления в этой папке",
+            "loading": "Проверка обновлений {type} в этой папке...",
+            "success": "Найдено {count} обновление(й) для {type}s в этой папке",
+            "none": "Все {type}s в этой папке актуальны",
+            "error": "Не удалось проверить папку на наличие обновлений {type}: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "Ранее загружено, но сейчас этого нет в вашей библиотеке.",
             "alreadyInLibrary": "Уже в библиотеке",
             "autoOrganizedPath": "[Автоматически организовано по шаблону пути]",
+            "fileSelection": {
+                "title": "Выбрать формат файла",
+                "files": "файлов",
+                "select": "Выбрать файл"
+            },
             "errors": {
                 "invalidUrl": "Неверный формат URL Civitai",
                 "noVersions": "Нет доступных версий для этой модели"
@@ -1080,6 +1107,12 @@
             "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.",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "ID рецепта недоступен",
             "sendToWorkflowFailed": "Не удалось отправить рецепт в рабочий процесс: {message}",
             "copyFailed": "Ошибка копирования синтаксиса рецепта: {message}",
+            "createError": "Ошибка при создании рецепта：{message}",
+            "createFailed": "Не удалось создать рецепт：{error}",
+            "createMissingData": "Отсутствуют необходимые данные для создания рецепта",
+            "created": "Рецепт успешно создан",
             "noMissingLoras": "Нет отсутствующих LoRAs для загрузки",
             "missingLorasInfoFailed": "Не удалось получить информацию для отсутствующих LoRAs",
             "preparingForDownloadFailed": "Ошибка подготовки LoRAs для загрузки",
@@ -1672,6 +1710,9 @@
             "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."
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

locales/zh-CN.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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。"
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "未找到文件夹",
             "dragHint": "拖拽项目到此处以创建文件夹"
+        },
+        "folderUpdateCheck": {
+            "label": "检查此文件夹的更新",
+            "loading": "正在检查此文件夹中的{type}更新...",
+            "success": "在此文件夹中找到 {count} 个{type}更新",
+            "none": "此文件夹中的所有{type}都是最新版本",
+            "error": "检查文件夹{type}更新失败: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "之前已下载，但当前不在你的库中。",
             "alreadyInLibrary": "已存在于库中",
             "autoOrganizedPath": "【已按路径模板自动整理】",
+            "fileSelection": {
+                "title": "选择文件格式",
+                "files": "个文件",
+                "select": "选择文件"
+            },
             "errors": {
                 "invalidUrl": "无效的 Civitai URL 格式",
                 "noVersions": "此模型没有可用版本"
@@ -1080,6 +1107,12 @@
             "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。",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "无配方 ID",
             "sendToWorkflowFailed": "发送配方到工作流失败：{message}",
             "copyFailed": "复制配方语法出错：{message}",
+            "createError": "创建配方时出错：{message}",
+            "createFailed": "创建配方失败：{error}",
+            "createMissingData": "缺少创建配方所需的数据",
+            "created": "配方创建成功",
             "noMissingLoras": "没有缺失的 LoRA 可下载",
             "missingLorasInfoFailed": "获取缺失 LoRA 信息失败",
             "preparingForDownloadFailed": "准备下载 LoRA 时出错",
@@ -1672,6 +1710,9 @@
             "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。"
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

locales/zh-TW.json

@@ -232,7 +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",
@@ -266,10 +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": {
@@ -576,7 +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",
@@ -640,8 +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。"
             },
@@ -682,6 +689,7 @@
             "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",
@@ -692,9 +700,18 @@
             "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}...",
@@ -807,8 +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"
             },
@@ -948,6 +963,13 @@
         "empty": {
             "noFolders": "未找到資料夾",
             "dragHint": "將項目拖到此處以建立資料夾"
+        },
+        "folderUpdateCheck": {
+            "label": "檢查此資料夾的更新",
+            "loading": "正在檢查此資料夾中的{type}更新...",
+            "success": "在此資料夾中找到 {count} 個{type}更新",
+            "none": "此資料夾中的所有{type}都是最新版本",
+            "error": "檢查資料夾{type}更新失敗: {message}"
         }
     },
     "statistics": {
@@ -1016,6 +1038,11 @@
             "downloadedTooltip": "先前已下載，但目前不在你的庫中。",
             "alreadyInLibrary": "已在庫存",
             "autoOrganizedPath": "[依路徑範本自動整理]",
+            "fileSelection": {
+                "title": "選擇檔案格式",
+                "files": "個檔案",
+                "select": "選擇檔案"
+            },
             "errors": {
                 "invalidUrl": "Civitai 網址格式無效",
                 "noVersions": "此模型無可用版本"
@@ -1080,6 +1107,12 @@
             "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。",
@@ -1160,6 +1193,7 @@
                 "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",
@@ -1634,6 +1668,10 @@
             "noRecipeId": "無配方 ID",
             "sendToWorkflowFailed": "傳送配方到工作流失敗：{message}",
             "copyFailed": "複製配方語法錯誤：{message}",
+            "createError": "建立配方時發生錯誤：{message}",
+            "createFailed": "建立配方失敗：{error}",
+            "createMissingData": "缺少建立配方所需的資料",
+            "created": "配方建立成功",
             "noMissingLoras": "無缺少的 LoRA 可下載",
             "missingLorasInfoFailed": "取得缺少 LoRA 資訊失敗",
             "preparingForDownloadFailed": "準備下載 LoRA 時發生錯誤",
@@ -1672,6 +1710,9 @@
             "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。"
         },
@@ -1909,9 +1950,32 @@
             "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}",
@@ -1923,6 +1987,15 @@
             "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",

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:

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()
 

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)

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))

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):

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__)
@@ -58,9 +58,52 @@ class RecipeMetadataParser(ABC):
             civitai_info, error_msg = civitai_info_tuple if isinstance(civitai_info_tuple, tuple) else (civitai_info_tuple, None)
             
             if not civitai_info or error_msg == "Model not found":
-                # Model not found or deleted
-                lora_entry['isDeleted'] = True
-                lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
+                # CivitAI may fail to resolve a hash that is still being
+                # computed (known CivitAI issue). Before marking as deleted,
+                # try to reconcile with a local model that has the same
+                # filename and matching AutoV3 hash.
+                reconciled = False
+                file_name = lora_entry.get("file_name")
+                if file_name and recipe_scanner and hash_value:
+                    lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
+                    if lora_scanner:
+                        try:
+                            # Local import to avoid circular dependency:
+                            # base.py → file_utils → settings_manager → ...
+                            #  → recipe_scanner → enrichment → base.py
+                            from ..utils.file_utils import calculate_autov3  # fmt: skip
+                            cache = await lora_scanner.get_cached_data()
+                            for item in getattr(cache, "raw_data", []):
+                                if item.get("file_name") == file_name:
+                                    local_path = item.get("file_path")
+                                    if local_path and os.path.exists(local_path):
+                                        local_autov3 = calculate_autov3(local_path)
+                                        if local_autov3 and local_autov3 == hash_value:
+                                            lora_entry["existsLocally"] = True
+                                            lora_entry["localPath"] = local_path
+                                            lora_entry["hash"] = item.get("sha256", hash_value)
+                                            if "preview_url" in item:
+                                                lora_entry["thumbnailUrl"] = config.get_preview_static_url(item["preview_url"])
+                                            civ = item.get("civitai") or {}
+                                            if isinstance(civ, dict):
+                                                if civ.get("id") is not None:
+                                                    lora_entry["id"] = civ["id"]
+                                                if civ.get("modelId") is not None:
+                                                    lora_entry["modelId"] = civ["modelId"]
+                                                if civ.get("name"):
+                                                    lora_entry["version"] = civ["name"]
+                                                # model_name is the CivitAI model display
+                                                # name stored directly in the cache column.
+                                                cached_model_name = item.get("model_name")
+                                                if cached_model_name:
+                                                    lora_entry["name"] = cached_model_name
+                                            reconciled = True
+                                            break
+                        except Exception:
+                            pass
+                if not reconciled:
+                    lora_entry['isDeleted'] = True
+                    lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
                 return lora_entry
                 
             # Get model type and validate
@@ -173,6 +216,20 @@ 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']
 

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)
@@ -180,27 +190,42 @@ class RecipeEnricher:
             existing_cp = recipe.get("checkpoint")
             if existing_cp is None:
                 existing_cp = {}
+
+            # Extract baseModel from raw civitai_info before populate_checkpoint_from_civitai
+            # (populate may reject non-checkpoint types and lose this data)
+            base_model_from_civitai: str = ""
+            if isinstance(civitai_info, dict):
+                base_model_from_civitai = civitai_info.get("baseModel", "") or ""
+            elif isinstance(civitai_info, tuple) and len(civitai_info) > 0 and isinstance(civitai_info[0], dict):
+                base_model_from_civitai = civitai_info[0].get("baseModel", "") or ""
+
             checkpoint_data = await RecipeMetadataParser.populate_checkpoint_from_civitai(existing_cp, civitai_info)
-            # 1. First, resolve base_model using full data before we format it away
+
+            # 1. Resolve base_model from checkpoint_data first, then fall back to raw civitai_info
             current_base_model = recipe.get("base_model")
-            resolved_base_model = checkpoint_data.get("baseModel")
+            resolved_base_model = checkpoint_data.get("baseModel") or base_model_from_civitai
             if resolved_base_model:
-                # Update if empty OR if it matches our generic prefix but is less specific
                 is_generic = not current_base_model or current_base_model.lower() in ["flux", "sdxl", "sd15"]
                 if is_generic and resolved_base_model != current_base_model:
                     recipe["base_model"] = resolved_base_model
-            
-            # 2. Format according to requirements: type, modelId, modelVersionId, modelName, modelVersionName
-            formatted_checkpoint = {
-                "type": "checkpoint",
-                "modelId": checkpoint_data.get("modelId"),
-                "modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
-                "modelName": checkpoint_data.get("name"), # In base.py, 'name' is populated from civitai_data['model']['name']
-                "modelVersionName": checkpoint_data.get("version") # In base.py, 'version' is populated from civitai_data['name']
-            }
-            # Remove None values
-            recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
-            
+
+            # 2. Only format and save checkpoint if it has real data (not just type after type rejection)
+            has_checkpoint_data = any([
+                checkpoint_data.get("modelId"),
+                checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
+                checkpoint_data.get("name"),
+                checkpoint_data.get("version"),
+            ])
+            if has_checkpoint_data:
+                formatted_checkpoint = {
+                    "type": "checkpoint",
+                    "modelId": checkpoint_data.get("modelId"),
+                    "modelVersionId": checkpoint_data.get("id") or checkpoint_data.get("modelVersionId"),
+                    "modelName": checkpoint_data.get("name"),
+                    "modelVersionName": checkpoint_data.get("version"),
+                }
+                recipe["checkpoint"] = {k: v for k, v in formatted_checkpoint.items() if v is not None}
+
             return True
         else:
             # Fallback to name extraction if we don't already have one

py/recipes/parsers/civitai_image.py

@@ -6,6 +6,7 @@ from typing import Dict, Any, Union
 from ..base import RecipeMetadataParser
 from ..constants import GEN_PARAM_KEYS
 from ...services.metadata_service import get_default_metadata_provider
+from ...config import config
 
 logger = logging.getLogger(__name__)
 
@@ -73,7 +74,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         return False
 
     async def parse_metadata(  # type: ignore[override]
-        self, user_comment, recipe_scanner=None, civitai_client=None
+        self, user_comment, recipe_scanner=None, civitai_client=None,
+        local_cache: dict[str, Any] | None = None,
     ) -> Dict[str, Any]:
         """Parse metadata from Civitai image format
 
@@ -81,6 +83,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
             user_comment: The metadata from the image (dict)
             recipe_scanner: Optional recipe scanner service
             civitai_client: Optional Civitai API client (deprecated, use metadata_provider instead)
+            local_cache: Optional dict mapping sha256/autov3 hash → scanner cache item.
+                         When provided, matching models skip CivitAI API calls.
 
         Returns:
             Dict containing parsed recipe data
@@ -185,8 +189,77 @@ 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
+                        cp_hash = checkpoint_entry.get("hash")
+                        if cp_hash and metadata_provider:
+                            local_cached = local_cache.get(cp_hash) if local_cache else None
+                            if local_cached:
+                                self._populate_entry_from_cache(
+                                    checkpoint_entry, local_cached
+                                )
+                                bm = checkpoint_entry.get("baseModel", "")
+                                if bm and not result["base_model"]:
+                                    result["base_model"] = bm
+                            else:
+                                try:
+                                    civitai_info = (
+                                        await metadata_provider.get_model_by_hash(
+                                            cp_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"{cp_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
@@ -220,34 +293,45 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
                         }
 
                         # Try to get info from Civitai if hash is available
-                        if lora_entry["hash"] and metadata_provider:
-                            try:
-                                civitai_info = (
-                                    await metadata_provider.get_model_by_hash(lora_hash)
+                        if lora_hash and metadata_provider:
+                            local_cached = local_cache.get(lora_hash) if local_cache else None
+                            if local_cached:
+                                self._populate_entry_from_cache(
+                                    lora_entry, local_cached
                                 )
-
-                                populated_entry = await self.populate_lora_from_civitai(
-                                    lora_entry,
-                                    civitai_info,
-                                    recipe_scanner,
-                                    base_model_counts,
-                                    lora_hash,
-                                )
-
-                                if populated_entry is None:
-                                    continue  # Skip invalid LoRA types
-
-                                lora_entry = populated_entry
-
-                                # If we have a version ID from Civitai, track it for deduplication
-                                if "id" in lora_entry and lora_entry["id"]:
+                                # Track by version ID for deduplication
+                                if lora_entry.get("id"):
                                     added_loras[str(lora_entry["id"])] = len(
                                         result["loras"]
                                     )
-                            except Exception as e:
-                                logger.error(
-                                    f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
-                                )
+                            else:
+                                try:
+                                    civitai_info = (
+                                        await metadata_provider.get_model_by_hash(lora_hash)
+                                    )
+
+                                    populated_entry = await self.populate_lora_from_civitai(
+                                        lora_entry,
+                                        civitai_info,
+                                        recipe_scanner,
+                                        base_model_counts,
+                                        lora_hash,
+                                    )
+
+                                    if populated_entry is None:
+                                        continue  # Skip invalid LoRA types
+
+                                    lora_entry = populated_entry
+
+                                    # If we have a version ID from Civitai, track it for deduplication
+                                    if "id" in lora_entry and lora_entry["id"]:
+                                        added_loras[str(lora_entry["id"])] = len(
+                                            result["loras"]
+                                        )
+                                except Exception as e:
+                                    logger.error(
+                                        f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
+                                    )
 
                         # Track by hash if we have it
                         if lora_hash:
@@ -625,3 +709,41 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         except Exception as e:
             logger.error(f"Error parsing Civitai image metadata: {e}", exc_info=True)
             return {"error": str(e), "loras": []}
+
+    @staticmethod
+    def _populate_entry_from_cache(
+        entry: dict[str, Any],
+        cache_item: dict[str, Any],
+    ) -> None:
+        """Fill a lora/checkpoint entry from a scanner cache item.
+
+        Avoids CivitAI API calls for models that exist locally.
+        Mirrors the population logic in
+        ``RecipeMetadataParser.populate_lora_from_civitai()`` but operates
+        entirely on cached data.
+        """
+        civ = cache_item.get("civitai") or {}
+        if isinstance(civ, dict):
+            if civ.get("id") is not None:
+                entry["id"] = civ["id"]
+            if civ.get("modelId") is not None:
+                entry["modelId"] = civ["modelId"]
+            if civ.get("name"):
+                entry["version"] = civ["name"]
+            cached_name = cache_item.get("model_name")
+            if cached_name:
+                entry["name"] = cached_name
+        entry["existsLocally"] = True
+        local_path = cache_item.get("file_path")
+        if local_path:
+            entry["localPath"] = local_path
+        sha256 = cache_item.get("sha256")
+        if sha256:
+            entry["hash"] = sha256
+        if "preview_url" in cache_item:
+            entry["thumbnailUrl"] = config.get_preview_static_url(
+                cache_item["preview_url"]
+            )
+        base_model = cache_item.get("base_model", "")
+        if base_model:
+            entry["baseModel"] = base_model

py/routes/handlers/misc_handlers.py

@@ -686,6 +686,9 @@ class DoctorHandler:
         )
 
     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:
@@ -990,11 +993,29 @@ class DoctorHandler:
         }
 
     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)
@@ -1042,12 +1063,22 @@ class DoctorHandler:
                 "total_conflict_files": total_conflict_files,
             }
         ]
-        for conflict in all_conflicts:
+
+        # 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['label']}] '{conflict['filename']}' "
+                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",
@@ -1058,7 +1089,11 @@ class DoctorHandler:
                 {
                     "id": "resolve-filename-conflicts",
                     "label": "Resolve Conflicts",
-                }
+                },
+                {
+                    "id": "open-settings-syntax-format",
+                    "label": "Switch to Full Path Syntax",
+                },
             ],
         }
 
@@ -2065,7 +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(
                 {
@@ -2139,8 +2174,19 @@ class ModelLibraryHandler:
                 ]
                 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_not_downloaded(found_type, model_version_id)
+            await history_service.mark_as_deleted(found_type, model_version_id)
 
             return web.json_response(
                 {

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()
@@ -1449,6 +1472,21 @@ class ModelDownloadHandler:
             )
             return web.Response(status=500, text=str(exc))
 
+    async def skip_download_get(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "Download ID is required"}, status=400
+                )
+            result = await self._download_coordinator.skip_download(download_id)
+            return web.json_response(result)
+        except Exception as exc:
+            self._logger.error(
+                "Error skipping download via GET: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def cancel_download_get(self, request: web.Request) -> web.Response:
         try:
             download_id = request.query.get("download_id")
@@ -1937,6 +1975,10 @@ class ModelUpdateHandler:
         if target_model_ids:
             target_model_ids = sorted(set(target_model_ids))
 
+        folder_path: Optional[str] = payload.get("folder_path")
+        if folder_path is not None and not isinstance(folder_path, str):
+            folder_path = None
+
         provider = await self._get_civitai_provider()
         if provider is None:
             return web.json_response(
@@ -1951,6 +1993,7 @@ class ModelUpdateHandler:
                 provider,
                 force_refresh=force_refresh,
                 target_model_ids=target_model_ids or None,
+                folder_path=folder_path,
             )
             if self._service.scanner.is_cancelled():
                 return web.json_response(
@@ -2538,6 +2581,7 @@ class ModelHandlerSet:
             "download_model": self.download.download_model,
             "download_model_get": self.download.download_model_get,
             "cancel_download_get": self.download.cancel_download_get,
+            "skip_download_get": self.download.skip_download_get,
             "pause_download_get": self.download.pause_download_get,
             "resume_download_get": self.download.resume_download_get,
             "get_download_progress": self.download.get_download_progress,

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"]

py/routes/handlers/recipe_handlers.py

@@ -16,7 +16,7 @@ from aiohttp import web
 
 from ...config import config
 from ...services.server_i18n import server_i18n as default_server_i18n
-from ...services.settings_manager import SettingsManager
+from ...services.settings_manager import SettingsManager, get_settings_manager
 from ...services.recipes import (
     RecipeAnalysisService,
     RecipeDownloadError,
@@ -26,7 +26,12 @@ from ...services.recipes import (
     RecipeValidationError,
 )
 from ...services.metadata_service import get_default_metadata_provider
-from ...utils.civitai_utils import extract_civitai_image_id, rewrite_preview_url
+from ...utils.civitai_utils import (
+    build_civitai_image_page_url,
+    extract_civitai_image_id,
+    extract_civitai_image_id_from_cdn_url,
+    rewrite_preview_url,
+)
 from ...utils.exif_utils import ExifUtils
 from ...recipes.merger import GenParamsMerger
 from ...recipes.enrichment import RecipeEnricher
@@ -87,12 +92,16 @@ 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,
+            "create_from_example": self.management.create_from_example,
         }
 
 
@@ -458,7 +467,11 @@ class RecipeQueryHandler:
             if recipe_scanner is None:
                 raise RuntimeError("Recipe scanner unavailable")
 
-            self._logger.info("Manually triggering recipe cache rebuild")
+            full_rebuild = request.query.get("full_rebuild", "true").lower() == "true"
+            self._logger.info(
+                "Manually triggering recipe cache %s",
+                "full rebuild" if full_rebuild else "refresh",
+            )
             await recipe_scanner.get_cached_data(force_refresh=True)
             return web.json_response(
                 {"success": True, "message": "Recipe cache refreshed successfully"}
@@ -541,7 +554,7 @@ class RecipeQueryHandler:
                     )
                     response_data.append(
                         {
-                            "type": "source_url",
+                            "type": "source_path",
                             "fingerprint": url,
                             "count": len(recipes),
                             "recipes": recipes,
@@ -607,6 +620,7 @@ 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 +717,69 @@ 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 +837,28 @@ 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 +869,155 @@ 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
+            civitai_base_model = civitai_parsed.get("base_model")
+            if civitai_base_model and not metadata.get("base_model"):
+                metadata["base_model"] = civitai_base_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
+            if parsed_embedded.get("base_model") and not metadata.get("base_model"):
+                metadata["base_model"] = parsed_embedded["base_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 +1319,7 @@ 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 +1367,38 @@ 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 +1446,500 @@ 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")
+
+            force = request.query.get("force", "false").lower() == "true"
+
+            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), unless force
+            if not force:
+                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
+            civitai_base_model = civitai_parsed.get("base_model")
+            if civitai_base_model and not metadata.get("base_model"):
+                metadata["base_model"] = civitai_base_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
+            if parsed_embedded.get("base_model") and not metadata.get("base_model"):
+                metadata["base_model"] = parsed_embedded["base_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)
+
+    async def create_from_example(self, request: web.Request) -> web.Response:
+        """Create a recipe from a model's example image using cached metadata.
+
+        Uses the image's meta data (already cached in .metadata.json from the
+        CivitAI model-versions API) to create a recipe without additional
+        CivitAI API calls.
+
+        If the image metadata doesn't contain any resources of the parent
+        model's type (LoRA-type or Checkpoint), the parent model is
+        auto-populated as a fallback.
+
+        Request body:
+            image_data (dict): The full image object from model-versions API
+                (includes meta, additionalResources, url, etc.)
+            model_hash (str): SHA256 hash of the parent model
+            model_name (str): Filename of the parent model
+            model_type (str): Page type (``"loras"``, ``"checkpoints"``, etc.)
+            local_image_path (str, optional): Local filesystem path to read
+                the image bytes for the recipe preview
+        """
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            data = await request.json()
+            image_data = data.get("image_data")
+            model_hash = data.get("model_hash")
+            model_name = data.get("model_name")
+            model_type = data.get("model_type", "")
+
+            if not image_data or not model_hash or not model_name:
+                raise RecipeValidationError(
+                    "Missing required fields: image_data, model_hash, model_name"
+                )
+
+            # Merge nested meta into top level so the parser finds everything.
+            # CivitaiApiMetadataParser expects prompt, seed, resources, etc.
+            # at the top level or wrapped under a "meta" key.
+            inner_meta = image_data.get("meta") or {}
+            parsed_input = {**image_data, **inner_meta}
+            parsed_input.pop("meta", None)
+
+            # Build a local cache of {hash → cache_item} so the parser can
+            # skip CivitAI API calls for models that exist on disk.
+            local_cache: Dict[str, Dict[str, Any]] = {}
+            lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
+            if lora_scanner and model_hash:
+                try:
+                    parent_cache_data = await lora_scanner.get_cached_data()
+                    for item in getattr(parent_cache_data, "raw_data", []):
+                        if item.get("sha256", "").lower() == model_hash.lower():
+                            local_cache[model_hash.lower()] = item
+                            # Compute AutoV3 so the parser can also match on
+                            # that hash type (CivitAI metadata resources use
+                            # AutoV3).
+                            file_path = item.get("file_path")
+                            if file_path and os.path.exists(file_path):
+                                try:
+                                    from ...utils.file_utils import (
+                                        calculate_autov3,
+                                    )
+                                    autov3 = calculate_autov3(file_path)
+                                    if autov3:
+                                        local_cache[autov3.lower()] = item
+                                except Exception:
+                                    pass
+                            break
+                except Exception:
+                    pass
+
+            parser = self._analysis_service._recipe_parser_factory.create_parser(
+                parsed_input
+            )
+            if not parser:
+                raise RecipeValidationError("Unable to parse image metadata")
+
+            from ...recipes.parsers.civitai_image import CivitaiApiMetadataParser
+
+            if isinstance(parser, CivitaiApiMetadataParser):
+                parsed = await parser.parse_metadata(
+                    parsed_input,
+                    recipe_scanner=recipe_scanner,
+                    local_cache=local_cache,
+                )
+            else:
+                parsed = await parser.parse_metadata(
+                    parsed_input, recipe_scanner=recipe_scanner
+                )
+
+            loras = list(parsed.get("loras") or [])
+            checkpoint = parsed.get("model")
+            is_lora_type = model_type.startswith("lora")
+            is_ckpt_type = model_type.startswith("checkpoint")
+
+            # Extract parent model metadata from local_cache (used below to
+            # reconcile isDeleted entries and enrich auto-populated ones).
+            parent_civitai_id: int | None = None
+            parent_model_id: int | None = None
+            parent_version_name: str | None = None
+            parent_model_name: str | None = None
+            # Prefer sha256 key; fall back to any cached entry.
+            parent_item = local_cache.get(model_hash.lower()) if model_hash else None
+            if parent_item is None and local_cache:
+                parent_item = next(iter(local_cache.values()))
+            if parent_item:
+                civ = parent_item.get("civitai") or {}
+                if isinstance(civ, dict):
+                    parent_civitai_id = civ.get("id")
+                    parent_model_id = civ.get("modelId")
+                    parent_version_name = civ.get("name")
+                parent_model_name = parent_item.get("model_name")
+
+            # Reconcile isDeleted entries against the parent model.
+            # When the CivitAI hash lookup fails (known issue — hashes not
+            # yet computed), the parser marks the entry isDeleted even though
+            # the model exists locally.
+            if is_lora_type:
+                for lora in loras:
+                    if lora.get("isDeleted") and lora.get("file_name") == model_name:
+                        lora["isDeleted"] = False
+                        lora["existsLocally"] = True
+                        lora["hash"] = model_hash
+                        if parent_civitai_id is not None:
+                            lora["id"] = parent_civitai_id
+                        if parent_model_id is not None:
+                            lora["modelId"] = parent_model_id
+                        if parent_version_name is not None:
+                            lora["version"] = parent_version_name
+                        if parent_model_name is not None:
+                            lora["name"] = parent_model_name
+            elif is_ckpt_type and checkpoint and checkpoint.get("isDeleted"):
+                if checkpoint.get("file_name") == model_name:
+                    checkpoint["isDeleted"] = False
+                    checkpoint["existsLocally"] = True
+                    checkpoint["hash"] = model_hash
+                    if parent_civitai_id is not None:
+                        checkpoint["id"] = parent_civitai_id
+                    if parent_model_id is not None:
+                        checkpoint["modelId"] = parent_model_id
+                    if parent_version_name is not None:
+                        checkpoint["version"] = parent_version_name
+
+            # Auto-populate parent model only when the image metadata didn't
+            # contain any resources of that type.
+            if is_lora_type and not loras:
+                lora_entry = {
+                    "name": model_name,
+                    "type": "lora",
+                    "weight": 1.0,
+                    "hash": model_hash,
+                    "existsLocally": True,
+                    "localPath": None,
+                    "file_name": model_name,
+                    "thumbnailUrl": "/loras_static/images/no-preview.png",
+                    "baseModel": parsed.get("base_model", ""),
+                    "size": 0,
+                    "downloadUrl": "",
+                    "isDeleted": False,
+                }
+                if parent_civitai_id is not None:
+                    lora_entry["id"] = parent_civitai_id
+                if parent_model_id is not None:
+                    lora_entry["modelId"] = parent_model_id
+                if parent_version_name is not None:
+                    lora_entry["version"] = parent_version_name
+                if parent_model_name is not None:
+                    lora_entry["name"] = parent_model_name
+                loras.insert(0, lora_entry)
+            elif is_ckpt_type and not checkpoint:
+                checkpoint = {
+                    "name": model_name,
+                    "type": "checkpoint",
+                    "hash": model_hash,
+                    "file_name": model_name,
+                    "existsLocally": True,
+                    "baseModel": parsed.get("base_model", ""),
+                    "isDeleted": False,
+                }
+                if parent_civitai_id is not None:
+                    checkpoint["id"] = parent_civitai_id
+                if parent_model_id is not None:
+                    checkpoint["modelId"] = parent_model_id
+                if parent_version_name is not None:
+                    checkpoint["version"] = parent_version_name
+                if parent_model_name is not None:
+                    checkpoint["name"] = parent_model_name
+
+            image_url = image_data.get("url") or ""
+            image_id = extract_civitai_image_id_from_cdn_url(image_url)
+            settings_mgr = get_settings_manager()
+            civitai_host = settings_mgr.get("civitai_host") if settings_mgr else None
+            page_url = build_civitai_image_page_url(image_id, host=civitai_host) or image_url
+
+            recipe_metadata: dict[str, Any] = {
+                "base_model": parsed.get("base_model") or "",
+                "loras": loras,
+                "gen_params": parsed.get("gen_params") or {},
+                "source_path": page_url,
+            }
+            nsfw_level = image_data.get("nsfwLevel")
+            if isinstance(nsfw_level, int):
+                recipe_metadata["preview_nsfw_level"] = nsfw_level
+            if checkpoint:
+                recipe_metadata["checkpoint"] = checkpoint
+
+            image_bytes: bytes | None = None
+            extension: str | None = None
+            local_image_path = data.get("local_image_path")
+            if local_image_path and os.path.exists(local_image_path):
+                with open(local_image_path, "rb") as f:
+                    image_bytes = f.read()
+                ext = os.path.splitext(local_image_path)[1].lower()
+                if ext in (".jpg", ".jpeg", ".png", ".webp", ".gif"):
+                    extension = ext
+            elif image_data.get("url"):
+                try:
+                    downloader = await self._downloader_factory()
+                    url = image_data["url"]
+                    tmp = tempfile.NamedTemporaryFile(delete=False)
+                    tmp.close()
+                    success, result = await downloader.download_file(
+                        url, tmp.name, use_auth=False
+                    )
+                    if success:
+                        with open(tmp.name, "rb") as f:
+                            image_bytes = f.read()
+                        url_path = url.split("?")[0].split("#")[0]
+                        ext = os.path.splitext(url_path)[1].lower()
+                        if ext:
+                            extension = ext
+                    if os.path.exists(tmp.name):
+                        os.unlink(tmp.name)
+                except Exception as exc:
+                    self._logger.warning(
+                        "Failed to download image for recipe: %s", exc
+                    )
+
+            prompt = (
+                (parsed.get("gen_params") or {}).get("prompt") or ""
+            )
+            if prompt:
+                name = " ".join(str(prompt).split()[:10])
+            else:
+                name = f"Recipe from {model_name}"
+
+            save_result = await self._persistence_service.save_recipe(
+                recipe_scanner=recipe_scanner,
+                image_bytes=image_bytes,
+                image_base64=None,
+                name=name,
+                tags=[],
+                metadata=recipe_metadata,
+                extension=extension,
+            )
+            return web.json_response(save_result.payload, status=save_result.status)
+
+        except RecipeValidationError as exc:
+            return web.json_response({"error": str(exc)}, status=400)
+        except Exception as exc:
+            self._logger.error(
+                "Error creating recipe from example: %s", exc, exc_info=True
+            )
+            return web.json_response({"error": str(exc)}, status=500)
+
 
 class RecipeAnalysisHandler:
     """Analyze images to extract recipe metadata."""

py/routes/model_route_registrar.py

@@ -101,6 +101,7 @@ COMMON_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("POST", "/api/lm/download-model", "download_model"),
     RouteDefinition("GET", "/api/lm/download-model-get", "download_model_get"),
     RouteDefinition("GET", "/api/lm/cancel-download-get", "cancel_download_get"),
+    RouteDefinition("GET", "/api/lm/skip-download", "skip_download_get"),
     RouteDefinition("GET", "/api/lm/pause-download", "pause_download_get"),
     RouteDefinition("GET", "/api/lm/resume-download", "resume_download_get"),
     RouteDefinition(

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 +71,13 @@ 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"),
+    RouteDefinition(
+        "POST", "/api/lm/recipes/create-from-example", "create_from_example"
+    ),
 )
 
 

py/routes/update_routes.py

@@ -11,6 +11,7 @@ from typing import Dict, List
 
 from ..utils.settings_paths import ensure_settings_file
 from ..services.downloader import get_downloader
+from ..services.service_registry import ServiceRegistry
 
 logger = logging.getLogger(__name__)
 
@@ -212,8 +213,19 @@ class UpdateRoutes:
 
             zip_path = tmp_zip_path
 
-            # Skip both settings.json, civitai and model cache folder
-            UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai', 'model_cache'])
+            # Close the downloaded-versions SQLite connection before cleaning,
+            # so that shutil.rmtree() does not fail on Windows (the process
+            # cannot delete a file with an outstanding open handle).
+            try:
+                history_svc = ServiceRegistry._services.get("downloaded_version_history_service")
+                if history_svc is not None:
+                    history_svc.close()
+                    logger.info("Closed downloaded-version history database connection")
+            except Exception:
+                logger.debug("Could not close downloaded-version history database", exc_info=True)
+
+            # Skip settings.json, civitai, model cache and runtime cache folders
+            UpdateRoutes._clean_plugin_folder(plugin_root, skip_files=['settings.json', 'civitai', 'model_cache', 'cache', 'wildcards', 'backups'])
 
             # Extract ZIP to temp dir
             with tempfile.TemporaryDirectory() as tmp_dir:
@@ -222,16 +234,17 @@ class UpdateRoutes:
                     # Find extracted folder (GitHub ZIP contains a root folder)
                     extracted_root = next(os.scandir(tmp_dir)).path
 
-                    # Copy files, skipping settings.json and civitai folder
+                    # Copy files, skipping user data that should be preserved
+                    skip_items = {'settings.json', 'civitai', 'wildcards', 'backups'}
                     for item in os.listdir(extracted_root):
-                        if item == 'settings.json' or item == 'civitai':
+                        if item in skip_items:
                             continue
                         src = os.path.join(extracted_root, item)
                         dst = os.path.join(plugin_root, item)
                         if os.path.isdir(src):
                             if os.path.exists(dst):
                                 shutil.rmtree(dst)
-                            shutil.copytree(src, dst, ignore=shutil.ignore_patterns('settings.json', 'civitai'))
+                            shutil.copytree(src, dst, ignore=shutil.ignore_patterns(*skip_items))
                         else:
                             shutil.copy2(src, dst)
 
@@ -239,15 +252,17 @@ class UpdateRoutes:
                     # for ComfyUI Manager to work properly
                     tracking_info_file = os.path.join(plugin_root, '.tracking')
                     tracking_files = []
+                    skip_tracked = {'civitai', 'wildcards', 'backups'}
                     for root, dirs, files in os.walk(extracted_root):
-                        # Skip civitai folder and its contents
+                        # Skip user data directories and their contents
                         rel_root = os.path.relpath(root, extracted_root)
-                        if rel_root == 'civitai' or rel_root.startswith('civitai' + os.sep):
+                        top_dir = rel_root.split(os.sep)[0] if rel_root != '.' else ''
+                        if top_dir in skip_tracked:
                             continue
                         for file in files:
                             rel_path = os.path.relpath(os.path.join(root, file), extracted_root)
-                            # Skip settings.json and any file under civitai
-                            if rel_path == 'settings.json' or rel_path.startswith('civitai' + os.sep):
+                            # Skip settings.json and any file under user data dirs
+                            if rel_path == 'settings.json' or rel_path.split(os.sep)[0] in skip_tracked:
                                 continue
                             tracking_files.append(rel_path.replace("\\", "/"))
                     with open(tracking_info_file, "w", encoding='utf-8') as file:

py/services/aria2_downloader.py

@@ -14,12 +14,30 @@ from typing import Any, Dict, Optional, Tuple
 
 import aiohttp
 
-from .downloader import DownloadProgress, get_downloader
+from .downloader import DownloadProgress, get_downloader, is_ssl_cert_verify_error
 from .aria2_transfer_state import Aria2TransferStateStore
 from .settings_manager import get_settings_manager
 
 logger = logging.getLogger(__name__)
 
+def _try_certifi_ca_path() -> str | None:
+    """Return the certifi CA bundle path if available, else None."""
+    try:
+        import certifi  # type: ignore[import-untyped]
+
+        path = certifi.where()
+        if os.path.isfile(path):
+            logger.debug(
+                "aria2 --ca-certificate: using certifi CA bundle at %s", path
+            )
+            return path
+    except ImportError:
+        pass
+
+    logger.debug("aria2 --ca-certificate: certifi not available")
+    return None
+
+
 CIVITAI_DOWNLOAD_URL_PREFIXES = (
     "https://civitai.com/api/download/",
     "https://civitai.red/api/download/",
@@ -39,7 +57,7 @@ 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()
@@ -391,6 +409,15 @@ class Aria2Downloader:
                     f"Failed to resolve authenticated Civitai redirect: status={response.status} body={body[:300]}"
                 )
         except aiohttp.ClientError as exc:
+            if is_ssl_cert_verify_error(exc):
+                logger.error(
+                    "SSL certificate verification failed during Civitai redirect "
+                    "resolution for %s. This is usually caused by an outdated CA "
+                    "certificate bundle. Recommended fixes:\n"
+                    "  1. pip install --upgrade certifi\n"
+                    "  2. pip install pip-system-certs",
+                    url,
+                )
             raise Aria2Error(
                 f"Failed to resolve authenticated Civitai redirect: {exc}"
             ) from exc
@@ -414,6 +441,11 @@ class Aria2Downloader:
                 f"--rpc-listen-port={self._rpc_port}",
                 f"--rpc-secret={self._rpc_secret}",
                 "--check-certificate=true",
+                # Point aria2 at certifi's CA bundle when available so it uses
+                # the same certificate store as Python downloads.
+                *((
+                    f"--ca-certificate={ca_cert}",
+                ) if (ca_cert := _try_certifi_ca_path()) else ()),
                 "--allow-overwrite=true",
                 "--auto-file-renaming=false",
                 "--file-allocation=none",

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)

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]:

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

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:

py/services/civarchive_client.py

@@ -186,6 +186,22 @@ class CivArchiveClient:
         if "metadata" in file_data:
             transformed["metadata"] = file_data["metadata"]
 
+        # Infer metadata.format from filename extension
+        name = transformed.get("name")
+        if name and isinstance(name, str):
+            lower_name = name.lower()
+            if lower_name.endswith(".safetensors"):
+                inferred_format = "SafeTensor"
+            elif lower_name.endswith(".ckpt"):
+                inferred_format = "PickleTensor"
+            else:
+                inferred_format = None
+            if inferred_format:
+                if "metadata" not in transformed:
+                    transformed["metadata"] = {}
+                if isinstance(transformed["metadata"], dict):
+                    transformed["metadata"].setdefault("format", inferred_format)
+
         if file_data.get("modelVersionId") is not None:
             transformed["modelVersionId"] = file_data.get("modelVersionId")
         elif file_data.get("model_version_id") is not None:
@@ -213,6 +229,20 @@ class CivArchiveClient:
         for file_data in candidates:
             if isinstance(file_data, dict):
                 transformed_files.append(self._transform_file_entry(file_data))
+
+        # Sort: .safetensors first, .ckpt second, others last
+        # so the backend fallback (no file_params) prefers safetensors
+        def _sort_key(f: Dict) -> int:
+            fname = f.get("name") or ""
+            if isinstance(fname, str):
+                lower = fname.lower()
+                if lower.endswith(".safetensors"):
+                    return 0
+                elif lower.endswith(".ckpt"):
+                    return 1
+            return 2
+
+        transformed_files.sort(key=_sort_key)
         return transformed_files
 
     def _transform_version(

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,
@@ -640,7 +753,7 @@ class CivitaiClient:
                 "GET",
                 f"{self.base_url}/models",
                 use_auth=True,
-                params={"username": username},
+                params={"username": username, "nsfw": "true"},
             )
 
             if not success:

py/services/download_coordinator.py

@@ -110,6 +110,23 @@ class DownloadCoordinator:
 
         return result
 
+    async def skip_download(self, download_id: str) -> Dict[str, Any]:
+        """Skip a download while preserving all partial files on disk."""
+        download_manager = await self._download_manager_factory()
+        result = await download_manager.skip_download(download_id)
+
+        await self._ws_manager.broadcast_download_progress(
+            download_id,
+            {
+                "status": "skipped",
+                "progress": 0,
+                "download_id": download_id,
+                "message": "Download skipped by user (partial files preserved)",
+            },
+        )
+
+        return result
+
     async def pause_download(self, download_id: str) -> Dict[str, Any]:
         """Pause an active download and notify listeners."""
 

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
@@ -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
@@ -2400,6 +2404,89 @@ class DownloadManager:
                 self._download_tasks.pop(download_id, None)
                 await self._aria2_state_store.remove(download_id)
 
+    async def skip_download(self, download_id: str) -> Dict:
+        """Skip a download while preserving all partial files on disk.
+
+        Removes all in-memory tracking (asyncio task, semaphore, active/pause
+        state) but keeps partial files (.part / .aria2) on disk so that a
+        subsequent download-model-get request for the same save path can
+        auto-resume from the preserved partial download.
+
+        Args:
+            download_id: The unique identifier of the download task
+
+        Returns:
+            Dict: Status of the skip operation
+        """
+        await self._restore_persisted_downloads()
+
+        if download_id not in self._download_tasks and download_id not in self._active_downloads:
+            return {"success": False, "error": "Download task not found"}
+
+        download_info = self._active_downloads.get(download_id)
+        task = self._download_tasks.get(download_id)
+        active_statuses = {"queued", "waiting", "downloading", "paused", "cancelling"}
+        if task is None and (
+            not isinstance(download_info, dict)
+            or download_info.get("status") not in active_statuses
+        ):
+            return {"success": False, "error": "Download task not found"}
+
+        backend = (
+            self._active_downloads.get(download_id, {}).get("transfer_backend")
+            or "python"
+        )
+
+        try:
+            # For aria2: pause the transfer rather than force-removing it, so
+            # the .aria2 control file stays on disk for future resume
+            if backend == "aria2":
+                try:
+                    aria2_downloader = await get_aria2_downloader()
+                    pause_result = await aria2_downloader.pause_download(download_id)
+                    if not pause_result.get("success"):
+                        logger.warning(
+                            "Failed to pause aria2 transfer for %s during skip: %s",
+                            download_id,
+                            pause_result.get("error"),
+                        )
+                except Exception as exc:
+                    logger.warning(
+                        "Failed to pause aria2 transfer for %s during skip: %s",
+                        download_id,
+                        exc,
+                    )
+
+            # Cancel the asyncio task so the semaphore slot is released
+            if task is not None:
+                task.cancel()
+
+            # Resume pause event so the task can exit cleanly
+            pause_control = self._pause_events.get(download_id)
+            if pause_control is not None:
+                pause_control.resume()
+
+            # Wait briefly for task to acknowledge cancellation
+            if task is not None:
+                try:
+                    await asyncio.wait_for(asyncio.shield(task), timeout=2.0)
+                except (asyncio.CancelledError, asyncio.TimeoutError):
+                    pass
+
+            logger.info(f"Download skipped for task {download_id} (partial files preserved)")
+            return {"success": True, "message": "Download skipped successfully"}
+        except Exception as e:
+            logger.error(f"Error skipping download: {e}", exc_info=True)
+            return {"success": False, "error": str(e)}
+        finally:
+            # Clean up local in-memory tracking only - NO file deletion
+            self._pause_events.pop(download_id, None)
+            self._download_tasks.pop(download_id, None)
+            if download_id in self._active_downloads:
+                del self._active_downloads[download_id]
+            # Preserve aria2 state store entry so the partial download
+            # info survives restarts and can be resumed later
+
     async def pause_download(self, download_id: str) -> Dict:
         """Pause an active download without losing progress."""
 

py/services/downloaded_version_history_service.py

@@ -96,6 +96,21 @@ class DownloadedVersionHistoryService:
     def get_database_path(self) -> str:
         return self._db_path
 
+    def close(self) -> None:
+        """Close the persistent SQLite connection, if open.
+
+        This is called before plugin update operations to release the
+        database file lock on Windows, allowing ``shutil.rmtree()`` to
+        succeed when the cache resides inside the plugin directory.
+        """
+        if self._conn is not None:
+            try:
+                self._conn.close()
+            except Exception:
+                pass
+            finally:
+                self._conn = None
+
     def _get_active_library_name(self) -> str | None:
         try:
             value = self._settings.get_active_library_name()
@@ -206,7 +221,7 @@ class DownloadedVersionHistoryService:
             )
             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:

py/services/downloader.py

@@ -13,6 +13,7 @@ This module provides a centralized download service with:
 import os
 import logging
 import asyncio
+import ssl
 import aiohttp
 from collections import deque
 from dataclasses import dataclass
@@ -31,6 +32,20 @@ from .errors import RateLimitError
 logger = logging.getLogger(__name__)
 
 
+def is_ssl_cert_verify_error(exc: BaseException) -> bool:
+    """Check if an exception represents an SSL certificate verification failure.
+
+    Matches ``ssl.SSLCertVerificationError``, ``aiohttp.ClientConnectorCertificateError``
+    (which wraps the former), and falls back to the standard OpenSSL error text.
+    """
+    if isinstance(exc, ssl.SSLCertVerificationError):
+        return True
+    cert_error = getattr(exc, "certificate_error", None)
+    if isinstance(cert_error, ssl.SSLCertVerificationError):
+        return True
+    return "CERTIFICATE_VERIFY_FAILED" in str(exc)
+
+
 @dataclass(frozen=True)
 class DownloadProgress:
     """Snapshot of a download transfer at a moment in time."""
@@ -265,9 +280,22 @@ class Downloader:
             logger.debug(
                 "Proxy mode: system-level proxy (trust_env) will be used if configured in environment."
             )
+        # Build SSL context: prefer certifi's CA bundle for broader
+        # CA coverage across different Python environments (especially
+        # embedded/compatibility Python builds).
+        try:
+            import certifi  # type: ignore[import-untyped]
+
+            ca_path = certifi.where()
+            ssl_context = ssl.create_default_context(cafile=ca_path)
+            logger.debug("SSL: using certifi CA bundle at %s", ca_path)
+        except (ImportError, FileNotFoundError, ValueError, OSError):
+            ssl_context = ssl.create_default_context()
+            logger.debug("SSL: certifi unavailable; using system default CA bundle")
+
         # Optimize TCP connection parameters
         connector = aiohttp.TCPConnector(
-            ssl=True,
+            ssl=ssl_context,
             limit=8,  # Concurrent connections
             ttl_dns_cache=300,  # DNS cache timeout
             force_close=False,  # Keep connections for reuse
@@ -736,6 +764,17 @@ class Downloader:
                 DownloadRestartRequested,
             ) as e:
                 retry_count += 1
+
+                if is_ssl_cert_verify_error(e):
+                    logger.error(
+                        "SSL certificate verification failed when connecting to %s. "
+                        "This is usually caused by an outdated CA certificate bundle "
+                        "in the Python environment. Recommended fixes:\n"
+                        "  1. pip install --upgrade certifi\n"
+                        "  2. pip install pip-system-certs",
+                        url,
+                    )
+
                 logger.warning(
                     f"Network error during download (attempt {retry_count}/{self.max_retries + 1}): {e}"
                 )

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:

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
         ]

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"""
@@ -157,7 +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()
@@ -177,6 +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)
@@ -195,13 +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"""
@@ -209,13 +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()
     

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

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
@@ -482,6 +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(
@@ -492,8 +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

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),
             )

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
@@ -1067,6 +1067,19 @@ 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'])
@@ -1101,7 +1114,15 @@ class ModelScanner:
 
     def _log_duplicate_filename_summary(self) -> None:
         """Log a batched summary of duplicate filename conflicts once per scan."""
-        if self._hash_index is None:
+        # 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()
@@ -1473,6 +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)
 
@@ -1572,12 +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

py/services/model_update_service.py

@@ -689,6 +689,7 @@ class ModelUpdateService:
         *,
         force_refresh: bool = False,
         target_model_ids: Optional[Sequence[int]] = None,
+        folder_path: Optional[str] = None,
     ) -> Dict[int, ModelUpdateRecord]:
         """Refresh update information for every model present in the cache."""
         scanner.reset_cancellation()
@@ -703,6 +704,7 @@ class ModelUpdateService:
         local_versions = await self._collect_local_versions(
             scanner,
             target_model_ids=target_filter,
+            folder_path=folder_path,
         )
         total_models = len(local_versions)
         if total_models == 0:
@@ -1000,12 +1002,11 @@ class ModelUpdateService:
                     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:
@@ -1277,6 +1278,7 @@ class ModelUpdateService:
         scanner,
         *,
         target_model_ids: Optional[Sequence[int]] = None,
+        folder_path: Optional[str] = None,
     ) -> Dict[int, List[int]]:
         cache = await scanner.get_cached_data()
         mapping: Dict[int, set[int]] = {}
@@ -1289,7 +1291,19 @@ class ModelUpdateService:
             if not target_set:
                 return {}
 
+        normalized_folder = None
+        if folder_path is not None:
+            normalized_folder = folder_path.replace("\\", "/").strip("/")
+
         for item in cache.raw_data:
+            # Apply folder filter first (cheapest check)
+            if normalized_folder is not None:
+                if not isinstance(item, dict):
+                    continue
+                item_folder = (item.get("folder") or "").replace("\\", "/").strip("/")
+                if item_folder != normalized_folder and not item_folder.startswith(normalized_folder + "/"):
+                    continue
+
             civitai = item.get("civitai") if isinstance(item, dict) else None
             if not isinstance(civitai, dict):
                 continue

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,

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
 

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)
 

py/services/recipes/persistence_service.py

@@ -115,6 +115,10 @@ class RecipePersistenceService:
         if metadata.get("source_path"):
             recipe_data["source_path"] = metadata.get("source_path")
 
+        nsfw_level = metadata.get("preview_nsfw_level")
+        if nsfw_level is not None and isinstance(nsfw_level, int):
+            recipe_data["preview_nsfw_level"] = nsfw_level
+
         json_filename = f"{recipe_id}.recipe.json"
         json_path = os.path.join(recipes_dir, json_filename)
         json_path = os.path.normpath(json_path)

py/services/settings_manager.py

@@ -96,6 +96,7 @@ 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",

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
 

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] = {
@@ -66,6 +66,46 @@ def build_civitai_model_page_url(
     return None
 
 
+_RE_CDN_IMAGE_ID = re.compile(r"/(\d+)\.(?:jpeg|jpg|png|webp|gif)(?:\?|#|$)")
+
+
+def extract_civitai_image_id_from_cdn_url(url: str | None) -> str | None:
+    """Extract the numeric image ID from a Cloudflare CDN image URL.
+
+    CivitAI image CDN URLs follow the pattern::
+
+        https://image.civitai.com/{cf_uuid}/{params}/{image_id}.{ext}
+
+    The image database ID is always the last path segment (minus extension)
+    because ``getEdgeUrl(…, name=id.toString())`` embeds it explicitly
+    in the model-versions REST API response.
+    """
+    if not url:
+        return None
+    match = _RE_CDN_IMAGE_ID.search(url)
+    return match.group(1) if match else None
+
+
+def build_civitai_image_page_url(
+    image_id: str | int | None,
+    *,
+    host: str | None = None,
+) -> str | None:
+    """Build a Civitai image page URL.
+
+    Returns something like ``https://civitai.com/images/12345``.
+    The host is resolved through :func:`normalize_civitai_page_host` and
+    therefore respects the user's ``civitai_host`` setting.
+    """
+    if not image_id:
+        return None
+    normalized_host = normalize_civitai_page_host(host)
+    normalized_id = str(image_id).strip()
+    if not normalized_id:
+        return None
+    return urlunparse(("https", normalized_host, f"/images/{normalized_id}", "", "", ""))
+
+
 def _parse_supported_civitai_page_url(url: str | None):
     if not url:
         return None
@@ -239,9 +279,9 @@ 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
@@ -328,8 +368,10 @@ def rewrite_preview_url(
 
 
 __all__ = [
+    "build_civitai_image_page_url",
     "build_license_flags",
     "extract_civitai_image_id",
+    "extract_civitai_image_id_from_cdn_url",
     "extract_civitai_page_host",
     "extract_civitai_model_url_parts",
     "is_supported_civitai_page_host",

py/utils/constants.py

@@ -101,8 +101,34 @@ DEFAULT_PRIORITY_TAG_CONFIG = {
 DIFFUSION_MODEL_BASE_MODELS = frozenset(
     [
         "Anima",
-        "ZImageTurbo",
-        "ZImageBase",
+        # Flux series — DiT architecture, loaded via UNETLoader in ComfyUI
+        "Flux.1 D",
+        "Flux.1 S",
+        "Flux.1 Krea",
+        "Flux.1 Kontext",
+        "Flux.2 D",
+        "Flux.2 Klein 9B",
+        "Flux.2 Klein 9B-base",
+        "Flux.2 Klein 4B",
+        "Flux.2 Klein 4B-base",
+        # Non-UNet / DiT image diffusion models
+        "AuraFlow",
+        "Chroma",
+        "HiDream",
+        "Hunyuan 1",
+        "Kolors",
+        "Lumina",
+        "PixArt a",
+        "PixArt E",
+        # Video diffusion models
+        "CogVideoX",
+        "Hunyuan Video",
+        "LTXV",
+        "LTXV2",
+        "LTXV 2.3",
+        "Mochi",
+        "SVD",
+        "Wan Video",
         "Wan Video 1.3B t2v",
         "Wan Video 14B t2v",
         "Wan Video 14B i2v 480p",
@@ -112,9 +138,13 @@ DIFFUSION_MODEL_BASE_MODELS = frozenset(
         "Wan Video 2.2 T2V-A14B",
         "Wan Video 2.5 T2V",
         "Wan Video 2.5 I2V",
-        "CogVideoX",
-        "Mochi",
+        # Other diffusion models
+        "Ernie",
+        "Ernie Turbo",
+        "Nucleus",
         "Qwen",
+        "ZImageBase",
+        "ZImageTurbo",
     ]
 )
 

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
                     )

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

py/utils/file_utils.py

@@ -1,7 +1,10 @@
 
 import hashlib
+import json
 import logging
 import os
+import struct
+from typing import Any
 
 from .constants import (
     CARD_PREVIEW_WIDTH,
@@ -31,7 +34,7 @@ def _get_hash_chunk_size_bytes() -> int:
 
 
 async def calculate_sha256(file_path: str) -> str:
-    """Calculate SHA256 hash of a file"""
+    """Calculate SHA256 hash of a file (full file content)."""
     sha256_hash = hashlib.sha256()
     chunk_size = _get_hash_chunk_size_bytes()
     with open(file_path, "rb") as f:
@@ -39,6 +42,79 @@ async def calculate_sha256(file_path: str) -> str:
             sha256_hash.update(byte_block)
     return sha256_hash.hexdigest()
 
+
+def calculate_autov2(file_path: str) -> str:
+    """Calculate CivitAI AutoV2 hash.
+
+    AutoV2 is the first 10 characters of the full file SHA256.
+    Used by CivitAI as a shortened file identifier.
+
+    Reference: https://developer.civitai.com/site/reference/model-versions
+    """
+    full_hash = hashlib.sha256()
+    chunk_size = _get_hash_chunk_size_bytes()
+    with open(file_path, "rb") as f:
+        for byte_block in iter(lambda: f.read(chunk_size), b""):
+            full_hash.update(byte_block)
+    return full_hash.hexdigest()[:10]
+
+
+def read_safetensors_metadata(file_path: str) -> dict[str, Any]:
+    """Read the ``__metadata__`` dict from a safetensors file header.
+
+    Safetensors file format:
+      - 8 bytes: header length (little-endian 64-bit)
+      - N bytes: UTF-8 JSON header
+      - The header JSON contains a ``__metadata__`` key holding arbitrary metadata.
+
+    Returns an empty dict if the file is not a valid safetensors file or has no
+    metadata.
+    """
+    try:
+        with open(file_path, "rb") as f:
+            header_len_bytes = f.read(8)
+            if len(header_len_bytes) < 8:
+                return {}
+            header_len = struct.unpack("<Q", header_len_bytes)[0]
+            header_bytes = f.read(header_len)
+            if len(header_bytes) < header_len:
+                return {}
+            header = json.loads(header_bytes.decode("utf-8"))
+            return header.get("__metadata__", {})
+    except (OSError, json.JSONDecodeError, UnicodeDecodeError, struct.error):
+        return {}
+
+
+def calculate_autov3(file_path: str) -> str | None:
+    """Calculate CivitAI AutoV3 hash from a safetensors file.
+
+    AutoV3 is extracted from the safetensors file's embedded metadata, not
+    computed from the file bytes directly. The orchestrator reads the
+    ``sshs_model_hash`` (kohya-ss format) or ``modelspec.hash_sha256`` field
+    from the safetensors header and stores the first 12 characters.
+
+    The embedded hash itself is the SHA256 of the file after skipping the
+    8-byte header length + JSON header (a.k.a. the addnet hash / tensor-only
+    hash).
+
+    Reference:
+      - CivitAI DB trigger: ``SUBSTRING(NEW.hash FROM 1 FOR 12)``
+      - https://developer.civitai.com/site/reference/model-versions
+
+    Returns ``None`` when no AutoV3 hash can be determined (e.g. the file is
+    not safetensors, or the metadata doesn't contain a recognised hash field).
+    """
+    metadata = read_safetensors_metadata(file_path)
+    if not metadata:
+        return None
+
+    embedded_hash = metadata.get("sshs_model_hash") or metadata.get("modelspec.hash_sha256")
+    if embedded_hash and isinstance(embedded_hash, str) and len(embedded_hash) >= 12:
+        return embedded_hash[:12]
+
+    return None
+
+
 def find_preview_file(base_name: str, dir_path: str) -> str:
     """Find preview file for given base name in directory.
 

py/utils/session_logging.py

@@ -64,6 +64,27 @@ def _build_log_file_path(settings_file: str | None, started_at: datetime) -> str
     return os.path.join(log_dir, f"standalone-session-{timestamp}.log")
 
 
+_KEEP_LOG_COUNT = 3
+
+
+def _prune_old_logs(log_dir: str) -> None:
+    """Remove older session log files, keeping only the ``_KEEP_LOG_COUNT`` newest."""
+    try:
+        files = [
+            os.path.join(log_dir, name)
+            for name in os.listdir(log_dir)
+            if name.startswith("standalone-session-") and name.endswith(".log")
+        ]
+    except OSError:
+        return
+    files.sort(key=os.path.getmtime, reverse=True)
+    for path in files[_KEEP_LOG_COUNT:]:
+        try:
+            os.remove(path)
+        except OSError:
+            pass
+
+
 def setup_standalone_session_logging(settings_file: str | None) -> StandaloneSessionLogState:
     global _session_state
 
@@ -90,6 +111,7 @@ def setup_standalone_session_logging(settings_file: str | None) -> StandaloneSes
             file_handler.set_name(_FILE_HANDLER_NAME)
             file_handler.setFormatter(formatter)
             root_logger.addHandler(file_handler)
+            _prune_old_logs(os.path.dirname(log_file_path))
 
         _session_state = StandaloneSessionLogState(
             started_at=started_at,

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:

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.0.6"
+version = "1.0.11"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

scripts/restore_suffixed_filenames.py

@@ -0,0 +1,404 @@
+#!/usr/bin/env python3
+"""
+Restore original filenames by removing leftover 4-char hash suffixes.
+
+When LoRA Manager's old duplicate filename resolver ran, it appended
+``-{first4ofSHA256}`` to duplicate filenames, e.g.::
+
+    my_lora.safetensors  →  my_lora-a3f7.safetensors
+
+With full-path LoRA syntax now available (``<lora:subfolder/name:1.0>``),
+these suffixes are unnecessary.  This script detects such files and, with
+your confirmation, restores their original names.
+
+The same suffix pattern is also used by the download conflict handler
+(``{name}-{hash}.{ext}``).  To avoid false positives, this script skips
+any file whose original name already exists in the same directory — those
+were likely added by a download conflict, not the old resolver.
+
+Usage::
+
+    # Detect only (dry-run, default)
+    python scripts/restore_suffixed_filenames.py
+
+    # Detect + restore (with confirmation prompt)
+    python scripts/restore_suffixed_filenames.py --apply
+
+After restoring filenames, run **Rebuild Cache** in the LoRA Manager
+Doctor panel to refresh the model cache.
+"""
+
+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="%(message)s",
+)
+logger = logging.getLogger(__name__)
+
+APP_NAME = "ComfyUI-LoRA-Manager"
+MODEL_EXTENSIONS = {".safetensors", ".ckpt", ".pt", ".pth", ".bin"}
+PREVIEW_EXTENSIONS = {
+    ".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp",
+    ".mp4", ".webm", ".mov",
+}
+
+# Matches filenames like "my_lora-a3f7.safetensors"
+# Groups: (base_name, 4-char-hex, extension)
+_SUFFIX_RE = re.compile(r"^(.+)-([0-9a-f]{4})(\.[^.]+)$")
+
+
+# ── helpers (copied from migrate_legacy_metadata.py for consistency) ──────────
+
+
+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, json.JSONDecodeError, OSError):
+        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]]:
+    """Extract model folder roots from LoRA Manager settings.
+
+    Returns ``{model_type: [path, ...]}`` where *model_type* is one of
+    ``loras``, ``checkpoints``, ``embeddings``, ``unet``, etc.
+
+    Both primary (``folder_paths``) and extra (``extra_folder_paths``)
+    paths are included.  Extra paths can be configured via the UI at
+    Settings → Model Libraries → Extra Folder Paths.
+    """
+    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:
+        # Primary folder paths.
+        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))
+        # Extra folder paths (Settings → Model Libraries → Extra Folder Paths).
+        extra_folder_paths = source.get("extra_folder_paths")
+        if isinstance(extra_folder_paths, dict):
+            for key, value in extra_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_unet_root", "unet"),
+        ("default_embedding_root", "embeddings"),
+    ):
+        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]:
+    """Recursively find all model files in *directory*."""
+    files: list[Path] = []
+    for ext in MODEL_EXTENSIONS:
+        files.extend(directory.rglob(f"*{ext}"))
+    return files
+
+
+# ── core detection logic ──────────────────────────────────────────────────────
+
+
+def check_file(path: Path) -> tuple[str, str, str] | None:
+    """If *path* matches the suffix pattern, return ``(base_name, hex, ext)``.
+
+    Returns ``None`` when:
+    * The filename does not match the pattern, or
+    * The original name (without the suffix) already exists in the same
+      directory (likely a download-conflict rename, not a doctor rename).
+    """
+    match = _SUFFIX_RE.match(path.name)
+    if not match:
+        return None
+
+    base_name = match.group(1)
+    hex_part = match.group(2)
+    extension = match.group(3)
+    orig_name = base_name + extension
+    orig_path = path.with_name(orig_name)
+
+    # Safety: skip if the original name already exists.
+    if orig_path.exists():
+        return None
+
+    return base_name, hex_part, extension
+
+
+def scan_roots(
+    roots: dict[str, list[str]],
+) -> dict[str, list[tuple[Path, str, str, str]]]:
+    """Scan all model roots and return detected files grouped by model type.
+
+    Returns ``{model_type: [(full_path, base_name, hex, ext), ...]}``.
+    """
+    results: dict[str, list[tuple[Path, str, str, str]]] = {}
+
+    for model_type, root_list in roots.items():
+        type_results: list[tuple[Path, str, str, str]] = []
+        for root in root_list:
+            root_path = Path(root)
+            if not root_path.is_dir():
+                continue
+            for model_file in find_model_files(root_path):
+                match = check_file(model_file)
+                if match:
+                    type_results.append((model_file, *match))
+        if type_results:
+            results[model_type] = type_results
+
+    return results
+
+
+def rename_file(
+    path: Path, base_name: str, extension: str, dry_run: bool
+) -> bool:
+    """Rename *path* to ``{base_name}{extension}``.
+
+    Also renames sidecar files (``.metadata.json``, ``.civitai.info``) and
+    preview images.  Returns ``True`` on success.
+    """
+    new_path = path.with_name(base_name + extension)
+    old_stem = path.with_suffix("")  # /dir/base_name-hex  (no ext)
+    new_stem = new_path.with_suffix("")  # /dir/base_name  (no ext)
+
+    if dry_run:
+        logger.info("  would rename:  %s", path.name)
+        logger.info("             ->  %s", new_path.name)
+        return True
+
+    try:
+        os.rename(path, new_path)
+    except OSError as exc:
+        logger.error("  FAILED to rename %s: %s", path.name, exc)
+        return False
+
+    # Rename sidecar metadata files.
+    for suffix in (".metadata.json", ".civitai.info"):
+        old_sidecar = old_stem.with_name(old_stem.name + suffix)
+        new_sidecar = new_stem.with_name(new_stem.name + suffix)
+        if old_sidecar.exists():
+            try:
+                os.rename(old_sidecar, new_sidecar)
+            except OSError as exc:
+                logger.warning("  could not rename sidecar %s: %s", old_sidecar.name, exc)
+
+    # Rename preview images.
+    for preview_ext in PREVIEW_EXTENSIONS:
+        old_preview = old_stem.with_name(old_stem.name + preview_ext)
+        new_preview = new_stem.with_name(new_stem.name + preview_ext)
+        if old_preview.exists():
+            try:
+                os.rename(old_preview, new_preview)
+            except OSError as exc:
+                logger.warning("  could not rename preview %s: %s", old_preview.name, exc)
+
+    logger.info("  renamed: %s  ->  %s", path.name, new_path.name)
+    return True
+
+
+# ── report helpers ────────────────────────────────────────────────────────────
+
+
+def print_report(results: dict[str, list[tuple[Path, str, str, str]]]) -> int:
+    """Print a human-readable report of detected files.  Returns total count."""
+    if not results:
+        logger.info("No leftover suffixed filenames detected.")
+        return 0
+
+    total = 0
+    for model_type in sorted(results):
+        entries = results[model_type]
+        total += len(entries)
+        label = model_type.capitalize()
+        logger.info("")
+        logger.info("─" * 50)
+        logger.info("  %s  (%d file(s))", label, len(entries))
+        logger.info("─" * 50)
+        for path, base_name, hex_part, ext in sorted(entries):
+            logger.info("  %s  →  %s%s", path.name, base_name, ext)
+
+    logger.info("")
+    logger.info("=" * 50)
+    logger.info("  Total: %d file(s) with leftover suffixes.", total)
+    logger.info("=" * 50)
+    return total
+
+
+def prompt_user(count: int) -> bool:
+    """Ask the user whether to proceed with the rename."""
+    try:
+        answer = input(
+            f"\nRestore {count} file(s) to their original names? [y/N] "
+        ).strip().lower()
+    except (EOFError, KeyboardInterrupt):
+        print()
+        return False
+    return answer in ("y", "yes")
+
+
+# ── main ──────────────────────────────────────────────────────────────────────
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description=(
+            "Detect and restore model filenames that have leftover "
+            "4-character hash suffixes from the old conflict resolver."
+        ),
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=(
+            "Examples:\n"
+            "  python scripts/restore_suffixed_filenames.py\n"
+            "  python scripts/restore_suffixed_filenames.py --apply\n"
+            "  python scripts/restore_suffixed_filenames.py --apply --yes\n"
+        ),
+    )
+    parser.add_argument(
+        "--apply",
+        action="store_true",
+        help="Actually rename files (with confirmation prompt unless --yes is given)",
+    )
+    parser.add_argument(
+        "--yes", "-y",
+        action="store_true",
+        help="Skip confirmation prompt (implies --apply)",
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="Detect only — show what would be renamed without making changes",
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        action="store_true",
+        help="Enable debug-level logging",
+    )
+    args = parser.parse_args()
+
+    if args.verbose:
+        logging.getLogger().setLevel(logging.DEBUG)
+
+    # Resolve settings.
+    settings_path = resolve_settings_path()
+    logger.info("Settings: %s", settings_path)
+    settings = _load_json(settings_path)
+    if not settings:
+        logger.error("Could not load settings.json.  Is LoRA Manager configured?")
+        return 1
+
+    roots = get_model_roots(settings)
+    if not roots:
+        logger.error("No model folders found in settings.")
+        return 1
+
+    # Log which roots are being scanned.
+    for model_type, root_list in roots.items():
+        for root in root_list:
+            logger.info("Scanning %s: %s", model_type, root)
+
+    # Detect.
+    results = scan_roots(roots)
+    total = print_report(results)
+
+    if total == 0:
+        return 0
+
+    # Determine mode.
+    dry_run = not args.apply and not args.yes
+
+    if dry_run:
+        logger.info("\n[Dry-run mode — no files modified]")
+        logger.info("Run with --apply to restore filenames.")
+        return 0
+
+    # Confirm unless --yes.
+    if not args.yes:
+        if not prompt_user(total):
+            logger.info("Aborted.")
+            return 0
+
+    # Rename.
+    logger.info("")
+    success = 0
+    fail = 0
+    for model_type in sorted(results):
+        entries = results[model_type]
+        logger.info("")
+        logger.info("─" * 50)
+        logger.info("  Restoring %s  (%d file(s))", model_type, len(entries))
+        logger.info("─" * 50)
+        for path, base_name, hex_part, ext in sorted(entries):
+            ok = rename_file(path, base_name, ext, dry_run=False)
+            if ok:
+                success += 1
+            else:
+                fail += 1
+
+    logger.info("")
+    logger.info("=" * 50)
+    logger.info("  Done: %d restored, %d failed.", success, fail)
+    logger.info("=" * 50)
+    logger.info("")
+    logger.info("  ⚠  Please run Rebuild Cache in the LoRA Manager")
+    logger.info("     Doctor panel to refresh the model cache.")
+
+    return 0 if fail == 0 else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

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": []
 }

static/css/components/card.css

@@ -507,21 +507,96 @@
     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;
 }
 
-/* Hide civitai version name when setting is disabled */
-body.hide-card-version .civitai-version {
+.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;
+}
+
 /* Prevent text selection on cards and interactive elements */
 .model-card,
 .model-card *,

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);

static/css/components/lora-modal/showcase.css

@@ -141,8 +141,9 @@
   border-color: var(--lora-error);
 }
 
-/* Disabled state for delete button */
-.media-control-btn.example-delete-btn.disabled {
+/* Disabled state for delete and create-recipe buttons */
+.media-control-btn.example-delete-btn.disabled,
+.media-control-btn.create-recipe-btn.disabled {
   opacity: 0.5;
   cursor: not-allowed;
 }

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;
+}

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;

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 */

static/css/components/modal/download-modal.css

@@ -502,4 +502,170 @@
     opacity: 0.5;
     pointer-events: none;
     user-select: none;
+}
+
+/* File Count Badge on Version Items */
+.file-select-badge {
+    display: inline-flex;
+    align-items: center;
+    gap: 4px;
+    padding: 2px 8px;
+    border-radius: 10px;
+    background: oklch(var(--lora-accent) / 0.18);
+    color: var(--lora-accent);
+    font-size: inherit;
+    font-weight: 600;
+    cursor: pointer;
+    transition: all 0.2s ease;
+    border: 1px solid oklch(var(--lora-accent) / 0.35);
+    user-select: none;
+    box-shadow: 0 1px 2px oklch(var(--lora-accent) / 0.1);
+}
+
+.file-select-badge:hover {
+    background: oklch(var(--lora-accent) / 0.3);
+    border-color: var(--lora-accent);
+    transform: scale(1.05);
+    box-shadow: 0 2px 6px oklch(var(--lora-accent) / 0.2);
+}
+
+.file-select-badge:active {
+    transform: scale(0.98);
+}
+
+.file-select-badge i {
+    font-size: 0.9em;
+}
+
+.file-select-badge .badge-arrow {
+    margin-left: 2px;
+    font-size: 0.65em;
+    opacity: 0.7;
+}
+
+/* File Selection Step */
+.file-selection-header {
+    margin-bottom: var(--space-3);
+}
+
+.file-selection-header h3 {
+    margin: 0 0 4px 0;
+    font-size: 1.1em;
+    color: var(--text-color);
+}
+
+.file-selection-version-name {
+    font-size: 0.9em;
+    color: var(--text-color);
+    opacity: 0.7;
+}
+
+.file-selection-list {
+    max-height: 360px;
+    overflow-y: auto;
+    margin: var(--space-2) 0;
+    display: flex;
+    flex-direction: column;
+    gap: 8px;
+}
+
+.file-option {
+    display: flex;
+    align-items: center;
+    gap: 12px;
+    padding: 12px;
+    border: 1px solid var(--border-color);
+    border-radius: var(--border-radius-sm);
+    cursor: pointer;
+    transition: all 0.2s ease;
+    background: var(--bg-color);
+}
+
+.file-option:hover {
+    border-color: var(--lora-accent);
+    box-shadow: 0 1px 4px rgba(0, 0, 0, 0.08);
+}
+
+.file-option.selected {
+    border: 2px solid var(--lora-accent);
+    background: oklch(var(--lora-accent) / 0.05);
+}
+
+.file-option-radio {
+    flex-shrink: 0;
+}
+
+.file-option-radio input[type="radio"] {
+    width: 16px;
+    height: 16px;
+    accent-color: var(--lora-accent);
+    cursor: pointer;
+}
+
+.file-option-info {
+    flex: 1;
+    min-width: 0;
+}
+
+.file-option-tags {
+    display: flex;
+    flex-wrap: wrap;
+    gap: 6px;
+    margin-bottom: 4px;
+}
+
+.file-tag {
+    display: inline-block;
+    padding: 2px 7px;
+    border-radius: 4px;
+    font-size: 0.8em;
+    font-weight: 500;
+    line-height: 1.4;
+}
+
+.file-tag.format {
+    background: oklch(var(--lora-accent) / 0.1);
+    color: var(--lora-accent);
+}
+
+.file-tag.fp {
+    background: oklch(0.6 0.15 250 / 0.1);
+    color: oklch(0.55 0.15 250);
+}
+
+.file-tag.size {
+    background: oklch(0.55 0.1 160 / 0.1);
+    color: oklch(0.5 0.12 160);
+}
+
+.file-option-name {
+    font-size: 0.8em;
+    color: var(--text-color);
+    opacity: 0.6;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    margin-top: 2px;
+}
+
+.file-option-size {
+    font-size: 0.9em;
+    color: var(--text-color);
+    white-space: nowrap;
+    font-variant-numeric: tabular-nums;
+}
+
+/* Dark theme adjustments */
+[data-theme="dark"] .file-option {
+    background: var(--lora-surface);
+}
+
+[data-theme="dark"] .file-tag.fp {
+    background: oklch(0.55 0.12 250 / 0.15);
+    color: oklch(0.7 0.12 250);
+}
+
+[data-theme="dark"] .file-tag.size {
+    background: oklch(0.5 0.08 160 / 0.15);
+    color: oklch(0.65 0.08 160);
 }

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);
+}

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 {

static/css/components/sidebar.css

@@ -745,3 +745,8 @@
 .sidebar-tree-container {
     position: relative;
 }
+
+/* Folder context menu - positioned relative to sidebar */
+#sidebarFolderContextMenu {
+    z-index: var(--z-modal, 1002);
+}

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;

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;
@@ -759,6 +766,49 @@ export class BaseModelApiClient {
         }
     }
 
+    async refreshUpdatesForFolder(folderPath, { force = false } = {}) {
+        if (!folderPath) {
+            throw new Error('No folder path provided');
+        }
+
+        try {
+            state.loadingManager.show('Checking for updates...', 0);
+            state.loadingManager.showCancelButton(() => this.cancelTask());
+
+            const response = await fetch(this.apiConfig.endpoints.refreshUpdates, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({
+                    folder_path: folderPath,
+                    force
+                })
+            });
+
+            let payload = {};
+            try {
+                payload = await response.json();
+            } catch (error) {
+                console.warn('Unable to parse refresh updates response as JSON', error);
+            }
+
+            if (!response.ok || payload?.success !== true) {
+                if (payload?.status === 'cancelled') {
+                    showToast('toast.api.operationCancelled', {}, 'info');
+                    return null;
+                }
+                const message = payload?.error || response.statusText || 'Failed to refresh updates';
+                throw new Error(message);
+            }
+
+            return payload;
+        } catch (error) {
+            console.error('Error refreshing updates for folder:', error);
+            throw error;
+        } finally {
+            state.loadingManager.hide();
+        }
+    }
+
     async fetchCivitaiVersions(modelId, source = null) {
         try {
             let requestUrl = `${this.apiConfig.endpoints.civitaiVersions}/${modelId}`;
@@ -902,7 +952,7 @@ export class BaseModelApiClient {
         }
     }
 
-    async downloadModel(modelId, versionId, modelRoot, relativePath, useDefaultPaths = false, downloadId, source = null) {
+    async downloadModel(modelId, versionId, modelRoot, relativePath, useDefaultPaths = false, downloadId, source = null, fileParams = null) {
         try {
             const response = await fetch(DOWNLOAD_ENDPOINTS.download, {
                 method: 'POST',
@@ -914,7 +964,8 @@ export class BaseModelApiClient {
                     relative_path: relativePath,
                     use_default_paths: useDefaultPaths,
                     download_id: downloadId,
-                    ...(source ? { source } : {})
+                    ...(source ? { source } : {}),
+                    ...(fileParams ? { file_params: fileParams } : {})
                 })
             });
 
@@ -978,6 +1029,16 @@ 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__';

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 = {
@@ -196,8 +197,8 @@ export async function resetAndReloadWithVirtualScroll(options = {}) {
         // Reset page counter
         pageState.currentPage = 1;
 
-        // Fetch the first page
-        const result = await fetchPageFunction(1, pageState.pageSize || 50);
+        const pageSize = state.virtualScroller?.pageSize || pageState.pageSize || 100;
+        const result = await fetchPageFunction(1, pageSize);
 
         // Update the virtual scroller
         state.virtualScroller.refreshWithData(
@@ -250,8 +251,8 @@ export async function loadMoreWithVirtualScroll(options = {}) {
             pageState.currentPage = 1;
         }
 
-        // Fetch the first page of data
-        const result = await fetchPageFunction(pageState.currentPage, pageState.pageSize || 50);
+        const pageSize = state.virtualScroller?.pageSize || pageState.pageSize || 100;
+        const result = await fetchPageFunction(pageState.currentPage, pageSize);
 
         // Update virtual scroller with the new data
         state.virtualScroller.refreshWithData(
@@ -293,47 +294,41 @@ export async function resetAndReload(updateFolders = false, options = {}) {
 }
 
 /**
- * Sync changes - quick refresh without rebuilding cache (similar to models page)
+ * Refreshes the recipe list by triggering a backend scan, then reloading.
+ * @param {boolean} fullRebuild - If true, fully rebuild the cache; if false, incremental scan
  */
 export async function syncChanges() {
-    try {
-        state.loadingManager.showSimpleLoading('Syncing changes...');
-
-        // Simply reload the recipes without rebuilding cache
-        await resetAndReload(false, { preserveScroll: true });
-
-        showToast('toast.recipes.syncComplete', {}, 'success');
-    } catch (error) {
-        console.error('Error syncing recipes:', error);
-        showToast('toast.recipes.syncFailed', { message: error.message }, 'error');
-    } finally {
-        state.loadingManager.hide();
-        state.loadingManager.restoreProgressBar();
-    }
+    return refreshRecipes(false);
 }
 
-/**
- * Refreshes the recipe list by first rebuilding the cache and then loading recipes
- */
-export async function refreshRecipes() {
-    try {
-        state.loadingManager.showSimpleLoading('Refreshing recipes...');
+export async function refreshRecipes(fullRebuild = true) {
+    const actionLabel = fullRebuild ? 'Rebuilding recipe cache' : 'Refreshing recipes';
+    const actionToast = fullRebuild ? 'Full rebuild' : 'Refresh';
 
-        // Call the API endpoint to rebuild the recipe cache
-        const response = await fetch(RECIPE_ENDPOINTS.scan);
+    try {
+        state.loadingManager.show(`${actionLabel}...`, 0);
+
+        const url = new URL(RECIPE_ENDPOINTS.scan, window.location.origin);
+        url.searchParams.append('full_rebuild', fullRebuild);
+
+        const response = await fetch(url);
 
         if (!response.ok) {
-            const data = await response.json();
-            throw new Error(data.error || 'Failed to refresh recipe cache');
+            throw new Error(`Failed to refresh recipe cache: ${response.status} ${response.statusText}`);
         }
 
-        // After successful cache rebuild, reload the recipes
-        await resetAndReload(false, { preserveScroll: true });
+        const data = await response.json();
+        if (data.status === 'cancelled') {
+            showToast('toast.api.operationCancelled', {}, 'info');
+            return;
+        }
 
-        showToast('toast.recipes.refreshComplete', {}, 'success');
+        await resetAndReload(false);
+
+        showToast('toast.api.refreshComplete', { action: actionToast }, 'success');
     } catch (error) {
         console.error('Error refreshing recipes:', error);
-        showToast('toast.recipes.refreshFailed', { message: error.message }, 'error');
+        showToast('toast.api.refreshFailed', { action: fullRebuild ? 'rebuild' : 'refresh', type: 'recipe' }, 'error');
     } finally {
         state.loadingManager.hide();
         state.loadingManager.restoreProgressBar();
@@ -557,6 +552,38 @@ 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');

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;
     }
-}
+}

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';
         }
@@ -107,39 +121,59 @@ export class BulkContextMenu extends BaseContextMenu {
             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() {
@@ -227,6 +261,9 @@ 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);
@@ -235,6 +272,9 @@ export class BulkContextMenu extends BaseContextMenu {
             case 'download-missing-loras':
                 this.handleDownloadMissingLoras();
                 break;
+            case 'download-example-images':
+                this.handleDownloadExampleImages();
+                break;
             case 'clear':
                 bulkManager.clearSelection();
                 break;
@@ -277,4 +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);
+        }
+    }
 }

static/js/components/ContextMenu/RecipeContextMenu.js

@@ -306,8 +306,14 @@ export class RecipeContextMenu extends BaseContextMenu {
             if (result.success) {
                 if (result.repaired > 0) {
                     showToast('recipes.contextMenu.repair.success', {}, 'success');
-                    // Refresh the current card or reload
-                    this.resetAndReload();
+                    const detailResponse = await fetch(`/api/lm/recipe/${recipeId}`);
+                    if (detailResponse.ok) {
+                        const updatedRecipe = await detailResponse.json();
+                        const filePath = this.currentCard?.dataset?.filepath;
+                        if (filePath && state.virtualScroller) {
+                            state.virtualScroller.updateSingleItem(filePath, updatedRecipe);
+                        }
+                    }
                 } else {
                     showToast('recipes.contextMenu.repair.skipped', {}, 'info');
                 }

static/js/components/RecipeCard.js

@@ -28,6 +28,7 @@ class RecipeCard {
         card.dataset.created = this.recipe.created_date;
         card.dataset.id = this.recipe.id || '';
         card.dataset.folder = this.recipe.folder || '';
+        card.dataset.favorite = this.recipe.favorite ? 'true' : 'false';
 
         // Get base model with fallback
         const baseModelLabel = (this.recipe.base_model || '').trim() || 'Unknown';
@@ -161,6 +162,7 @@ class RecipeCard {
 
         // Update early to provide instant feedback and avoid race conditions with re-renders
         this.recipe.favorite = newFavoriteState;
+        card.dataset.favorite = newFavoriteState ? 'true' : 'false';
 
         // Function to update icon state
         const updateIconUI = (icon, state) => {

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) {

static/js/components/SidebarManager.js

@@ -7,6 +7,7 @@ import { translate } from '../utils/i18nHelpers.js';
 import { state } from '../state/index.js';
 import { bulkManager } from '../managers/BulkManager.js';
 import { showToast } from '../utils/uiHelpers.js';
+import { performFolderUpdateCheck } from '../utils/updateCheckHelpers.js';
 import { escapeHtml, escapeAttribute } from './shared/utils.js';
 
 export class SidebarManager {
@@ -41,6 +42,7 @@ export class SidebarManager {
 
         // Bind methods
         this.handleTreeClick = this.handleTreeClick.bind(this);
+        this.handleTreeContextMenu = this.handleTreeContextMenu.bind(this);
         this.handleBreadcrumbClick = this.handleBreadcrumbClick.bind(this);
         this.handleDocumentClick = this.handleDocumentClick.bind(this);
         this.handleSidebarHeaderClick = this.handleSidebarHeaderClick.bind(this);
@@ -185,6 +187,8 @@ export class SidebarManager {
         }
         if (folderTree) {
             folderTree.removeEventListener('click', this.handleTreeClick);
+            folderTree.removeEventListener('contextmenu', this.handleTreeContextMenu);
+            folderTree.removeEventListener('dragover', this.handleFolderDragOver);
         }
         if (sidebarBreadcrumbNav) {
             sidebarBreadcrumbNav.removeEventListener('click', this.handleBreadcrumbClick);
@@ -977,6 +981,7 @@ export class SidebarManager {
         const folderTree = document.getElementById('sidebarFolderTree');
         if (folderTree) {
             folderTree.addEventListener('click', this.handleTreeClick);
+            folderTree.addEventListener('contextmenu', this.handleTreeContextMenu);
         }
 
         // Breadcrumb click handler
@@ -1027,6 +1032,19 @@ export class SidebarManager {
         if (displayModeToggleBtn) {
             displayModeToggleBtn.addEventListener('click', this.handleDisplayModeToggle);
         }
+
+        // Sidebar folder context menu click handler
+        const sidebarFolderMenu = document.getElementById('sidebarFolderContextMenu');
+        if (sidebarFolderMenu) {
+            sidebarFolderMenu.addEventListener('click', (e) => {
+                const item = e.target.closest('.context-menu-item');
+                if (!item) return;
+                const action = item.dataset.action;
+                if (action) {
+                    this.handleFolderContextMenuAction(action);
+                }
+            });
+        }
     }
 
     handleDocumentClick(event) {
@@ -1398,6 +1416,82 @@ export class SidebarManager {
         }
     }
 
+    handleTreeContextMenu(event) {
+        const nodeContent = event.target.closest('.sidebar-tree-node, .sidebar-folder-item');
+        if (!nodeContent) return;
+
+        event.preventDefault();
+        event.stopPropagation();
+
+        const path = nodeContent.dataset.path;
+        if (path === undefined || path === null || path === '') return;
+
+        this._showFolderContextMenu(event.clientX, event.clientY, path);
+    }
+
+    _showFolderContextMenu(x, y, path) {
+        this._closeFolderContextMenu();
+
+        const menu = document.getElementById('sidebarFolderContextMenu');
+        if (!menu) return;
+
+        menu.style.left = `${x}px`;
+        menu.style.top = `${y}px`;
+        menu.style.display = 'block';
+        menu.dataset.folderPath = path;
+
+        this._folderContextOpen = true;
+
+        // Close on next click outside
+        this._folderContextCloseHandler = (e) => {
+            if (!menu.contains(e.target)) {
+                this._closeFolderContextMenu();
+            }
+        };
+        setTimeout(() => {
+            document.addEventListener('click', this._folderContextCloseHandler);
+        }, 0);
+    }
+
+    _closeFolderContextMenu() {
+        const menu = document.getElementById('sidebarFolderContextMenu');
+        if (menu) {
+            menu.style.display = 'none';
+            delete menu.dataset.folderPath;
+        }
+        if (this._folderContextCloseHandler) {
+            document.removeEventListener('click', this._folderContextCloseHandler);
+            this._folderContextCloseHandler = null;
+        }
+        this._folderContextOpen = false;
+    }
+
+    handleFolderContextMenuAction(action) {
+        const menu = document.getElementById('sidebarFolderContextMenu');
+        if (!menu) return;
+
+        const path = menu.dataset.folderPath;
+        this._closeFolderContextMenu();
+
+        if (!path) return;
+
+        this._performFolderAction(action, path);
+    }
+
+    async _performFolderAction(action, path) {
+        switch (action) {
+            case 'check-folder-updates':
+                try {
+                    await performFolderUpdateCheck(path);
+                } catch (error) {
+                    console.error('Folder update check failed:', error);
+                }
+                break;
+            default:
+                console.warn('Unknown folder action:', action);
+        }
+    }
+
     handleBreadcrumbClick(event) {
         const breadcrumbItem = event.target.closest('.sidebar-breadcrumb-item');
         const dropdownItem = event.target.closest('.breadcrumb-dropdown-item');

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();
         }
     }
-}
+}

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;
+}

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>
-                        ${model.civitai?.name ? `<span class="version-name civitai-version">${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>

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');
+    }
+}

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>
@@ -516,7 +522,7 @@ export async function showModelModal(model, modelType) {
                     </div>
                 </div>
 
-                <div class="showcase-section" data-model-hash="${modelWithFullData.sha256 || ''}" data-filepath="${escapedFilePathAttr}">
+                <div class="showcase-section" data-model-hash="${modelWithFullData.sha256 || ''}" data-model-name="${escapeAttribute(modelWithFullData.file_name || modelWithFullData.model_name || '')}" data-model-type="${modelType}" data-filepath="${escapedFilePathAttr}">
                     <div class="showcase-tabs">
                         ${tabsContent}
                     </div>
@@ -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);

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();

static/js/components/shared/showcase/MediaUtils.js

@@ -135,6 +135,39 @@ export function initLazyLoading(container) {
     lazyElements.forEach(element => observer.observe(element));
 }
 
+/**
+ * Check which Create As Recipe buttons correspond to already-imported
+ * images and disable them.
+ */
+async function checkImportedRecipes(container) {
+    const recipeButtons = container.querySelectorAll('.create-recipe-btn');
+    if (!recipeButtons.length) return;
+
+    const imageIds = [];
+    recipeButtons.forEach(btn => {
+        const id = btn.dataset.imageId;
+        if (id) imageIds.push(id);
+    });
+    if (!imageIds.length) return;
+
+    try {
+        const response = await fetch(`/api/lm/recipes/check-image-exists?image_ids=${imageIds.join(',')}`);
+        const data = await response.json();
+        if (!data.success || !data.results) return;
+        recipeButtons.forEach(btn => {
+            const id = btn.dataset.imageId;
+            if (id && data.results[id]?.in_library) {
+                btn.title = 'Already imported as recipe';
+                btn.classList.add('disabled');
+                btn.setAttribute('aria-disabled', 'true');
+            }
+        });
+    } catch (err) {
+        console.error('Failed to check imported recipes:', err);
+    }
+}
+
+
 /**
  * Get the actual rendered rectangle of a media element with object-fit: contain
  * @param {HTMLElement} mediaElement - The img or video element
@@ -471,6 +504,75 @@ export function initMediaControlHandlers(container) {
         });
     });
     
+    // Create As Recipe buttons
+    const recipeButtons = container.querySelectorAll('.create-recipe-btn');
+    recipeButtons.forEach(btn => {
+        btn.addEventListener('click', async function(e) {
+            e.stopPropagation();
+            
+            // Ignore clicks when disabled
+            if (this.classList.contains('disabled')) {
+                return;
+            }
+            
+            const imageMetaRaw = this.dataset.imageMeta;
+            const imageUrl = this.dataset.imageUrl;
+            const imageNsfw = this.dataset.imageNsfw;
+            const localPath = this.dataset.localPath || '';
+            const showcaseSection = this.closest('.showcase-section');
+            const modelHash = showcaseSection ? showcaseSection.dataset.modelHash : '';
+            const modelName = showcaseSection ? showcaseSection.dataset.modelName : '';
+            const modelType = showcaseSection ? showcaseSection.dataset.modelType : '';
+            
+            if (!imageMetaRaw || !modelHash) {
+                showToast('toast.recipes.createMissingData', {}, 'error');
+                return;
+            }
+            
+            // Show loading state
+            const originalHtml = this.innerHTML;
+            this.innerHTML = '<i class="fas fa-spinner fa-spin"></i>';
+            this.disabled = true;
+            
+            try {
+                const imageMeta = JSON.parse(decodeURIComponent(imageMetaRaw));
+                
+                const response = await fetch('/api/lm/recipes/create-from-example', {
+                    method: 'POST',
+                    headers: { 'Content-Type': 'application/json' },
+                    body: JSON.stringify({
+                        image_data: {
+                            meta: imageMeta,
+                            url: imageUrl,
+                            nsfwLevel: imageNsfw ? parseInt(imageNsfw, 10) : undefined,
+                        },
+                        model_hash: modelHash,
+                        model_name: modelName || modelHash,
+                        model_type: modelType,
+                        local_image_path: localPath,
+                    }),
+                });
+                
+                const result = await response.json();
+                
+                if (result.success && result.recipe_id) {
+                    showToast('toast.recipes.created', { recipeId: result.recipe_id }, 'success');
+                } else {
+                    showToast('toast.recipes.createFailed', { error: result.error || 'Unknown error' }, 'error');
+                }
+            } catch (error) {
+                console.error('Failed to create recipe:', error);
+                showToast('toast.recipes.createError', { message: error.message }, 'error');
+            } finally {
+                this.innerHTML = originalHtml;
+                this.disabled = false;
+            }
+        });
+    });
+    
+    // Check which images are already imported as recipes → disable button
+    checkImportedRecipes(container);
+    
     // Initialize set preview buttons
     initSetPreviewHandlers(container);
 

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,
@@ -182,6 +183,9 @@ function renderMediaItem(img, index, exampleFiles) {
         Math.min(maxHeightPercent, aspectRatio)
     );
     
+    // Extract CivitAI image ID from CDN URL for import status check
+    const cdnImageId = (img.url || '').match(/\/(\d+)\.(?:jpeg|jpg|png|webp|gif)(?:\?|#|$)/)?.[1] || '';
+
     // Check if media should be blurred
     const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
     const matureBlurThreshold = getMatureBlurThreshold(state.settings);
@@ -223,12 +227,25 @@ function renderMediaItem(img, index, exampleFiles) {
     // Determine if this is a custom image (has id property)
     const isCustomImage = Boolean(typeof img.id === 'string' && img.id);
     
+    const hasGenMeta = img.hasMeta || (img.meta && (img.meta.prompt || img.meta.seed || img.meta.resources));
+
     // Create the media control buttons HTML
     const mediaControlsHtml = `
         <div class="media-controls">
             <button class="media-control-btn set-preview-btn" title="Set as preview">
                 <i class="fas fa-image"></i>
             </button>
+            ${hasGenMeta ? `
+            <button class="media-control-btn create-recipe-btn"
+                    title="Create As Recipe"
+                    data-image-meta="${encodeURIComponent(JSON.stringify(img.meta || {}))}"
+                    data-image-url="${img.url || ''}"
+                    data-image-nsfw="${img.nsfwLevel ?? ''}"
+                    data-image-id="${cdnImageId}"
+                    data-local-path="${localFile ? localFile.path : ''}">
+                <i class="fas fa-book-open"></i>
+            </button>
+            ` : ''}
             <button class="media-control-btn set-nsfw-btn" 
                     title="Set content rating"
                     data-media-index="${index}"
@@ -239,7 +256,7 @@ function renderMediaItem(img, index, exampleFiles) {
             <button class="media-control-btn example-delete-btn ${!isCustomImage ? 'disabled' : ''}" 
                     title="${isCustomImage ? 'Delete this example' : 'Only custom images can be deleted'}" 
                     data-short-id="${img.id || ''}" 
-                    ${!isCustomImage ? 'disabled' : ''}>
+                    ${!isCustomImage ? 'aria-disabled="true"' : ''}>
                 <i class="fas fa-trash-alt"></i>
                 <i class="fas fa-check confirm-icon"></i>
             </button>
@@ -640,6 +657,27 @@ 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);
     

static/js/managers/BatchImportManager.js

@@ -432,7 +432,7 @@ export class BatchImportManager {
         
         // Refresh recipes list to show newly imported recipes
         if (window.recipeManager && typeof window.recipeManager.loadRecipes === 'function') {
-            window.recipeManager.loadRecipes({ preserveScroll: true });
+            window.recipeManager.loadRecipes(true);
         }
         
         // Show results step

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, updateRecipeMetadata } 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';
@@ -74,7 +74,7 @@ export class BulkManager {
                 unfavorite: true
             },
             recipes: {
-                addTags: false,
+                addTags: true,
                 sendToWorkflow: false,
                 copyAll: false,
                 refreshAll: false,
@@ -85,7 +85,8 @@ export class BulkManager {
                 setContentRating: false,
                 skipMetadataRefresh: false,
                 setFavorite: true,
-                unfavorite: true
+                unfavorite: true,
+                repairMetadata: true
             }
         };
 
@@ -546,9 +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');
@@ -642,6 +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');
@@ -771,6 +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();
@@ -994,7 +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');
@@ -1018,6 +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) {
@@ -1025,7 +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 });
@@ -1064,6 +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');

static/js/managers/BulkMissingLoraDownloadManager.js

@@ -309,9 +309,22 @@ export class BulkMissingLoraDownloadManager {
             }, 'warning');
         }
 
-        // Refresh the recipes list to update LoRA status
-        if (window.recipeManager) {
-            window.recipeManager.loadRecipes({ preserveScroll: true });
+        // Update each affected recipe card with fresh data (LoRA inLibrary flags changed)
+        if (state.virtualScroller) {
+            const { extractRecipeId } = await import('../api/recipeApi.js');
+            for (const recipe of this.pendingRecipes) {
+                const recipeId = extractRecipeId(recipe.file_path);
+                if (!recipeId) continue;
+                try {
+                    const detailRes = await fetch(`/api/lm/recipe/${encodeURIComponent(recipeId)}`);
+                    if (detailRes.ok) {
+                        const updated = await detailRes.json();
+                        state.virtualScroller.updateSingleItem(recipe.file_path, updated);
+                    }
+                } catch (e) {
+                    console.warn('Failed to update recipe card after LoRA download:', e);
+                }
+            }
         }
     }
 

static/js/managers/DoctorManager.js

@@ -225,6 +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.${status}`;
+        const displaySummary = translate(summaryKey, {}, item.summary || '');
+
         const details = Array.isArray(item.details) ? item.details : [];
         const listItems = details
             .filter((detail) => typeof detail === 'string')
@@ -235,19 +242,22 @@ export class DoctorManager {
             .map((detail) => this.renderInlineDetail(detail))
             .join('');
         const actions = (item.actions || [])
-            .map((action) => `
+            .map((action) => {
+                const actionLabel = translate(`doctor.actions.${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">${escapeHtml(tagLabel)}</span>
                 </div>
@@ -262,7 +272,7 @@ export class DoctorManager {
         if (detail.conflict_groups || detail.total_conflict_files) {
             return `
                 <div class="doctor-inline-detail">
-                    <strong>${escapeHtml(translate('doctor.status.warning', {}, 'Conflicts'))}</strong>
+                    <strong>${escapeHtml(translate('doctor.labels.conflicts', {}, 'Conflicts'))}</strong>
                     <div>${escapeHtml(`${detail.conflict_groups || 0} filenames, ${detail.total_conflict_files || 0} files`)}</div>
                 </div>
             `;
@@ -324,11 +334,42 @@ 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.resolveFilenameConflicts();
+                await this.promptResolveConflicts();
                 break;
             case 'reload-page':
                 this.reloadUi();
@@ -358,6 +399,62 @@ 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);
@@ -449,3 +546,8 @@ export class DoctorManager {
 }
 
 export const doctorManager = new DoctorManager();
+
+// Make available globally for HTML onclick handlers
+if (typeof window !== 'undefined') {
+    window.doctorManager = doctorManager;
+}

static/js/managers/DownloadManager.js

@@ -33,6 +33,8 @@ export class DownloadManager {
         this.handleStartDownload = this.startDownload.bind(this);
         this.handleBackToUrl = this.backToUrl.bind(this);
         this.handleBackToVersions = this.backToVersions.bind(this);
+        this.handleBackToVersionFromFiles = this.backToVersionFromFiles.bind(this);
+        this.handleConfirmFileSelection = this.confirmFileSelection.bind(this);
         this.handleCloseModal = this.closeModal.bind(this);
         this.handleToggleDefaultPath = this.toggleDefaultPath.bind(this);
     }
@@ -80,6 +82,10 @@ export class DownloadManager {
         document.getElementById('backToVersionsBtn').addEventListener('click', this.handleBackToVersions);
         document.getElementById('closeDownloadModal').addEventListener('click', this.handleCloseModal);
 
+        // File selection step buttons
+        document.getElementById('backToVersionFromFilesBtn').addEventListener('click', this.handleBackToVersionFromFiles);
+        document.getElementById('confirmFileSelection').addEventListener('click', this.handleConfirmFileSelection);
+
         // Default path toggle handler
         document.getElementById('useDefaultPath').addEventListener('change', this.handleToggleDefaultPath);
     }
@@ -129,6 +135,7 @@ export class DownloadManager {
         this.modelId = null;
         this.modelVersionId = null;
         this.source = null;
+        this.selectedFile = null;
 
         this.selectedFolder = '';
 
@@ -247,9 +254,12 @@ export class DownloadManager {
             const firstImage = version.images?.find(img => !img.url.endsWith('.mp4'));
             const thumbnailUrl = firstImage ? firstImage.url : '/loras_static/images/no-preview.png';
 
+            // Count model-type files per version
+            const modelFiles = (version.files || []).filter(f => f.type === 'Model');
+            const primaryFile = modelFiles.find(f => f.primary) || modelFiles[0] || {};
             const fileSize = version.modelSizeKB ?
                 (version.modelSizeKB / 1024).toFixed(2) :
-                (version.files[0]?.sizeKB / 1024).toFixed(2);
+                ((primaryFile.sizeKB || 0) / 1024).toFixed(2);
 
             const existsLocally = version.existsLocally;
             const hasBeenDownloaded = version.hasBeenDownloaded && !existsLocally;
@@ -282,6 +292,12 @@ export class DownloadManager {
                  </div>`;
             }
 
+            const fileBadge = modelFiles.length > 1 && !existsLocally
+                ? `<span class="file-select-badge" data-version-id="${version.id}">
+                     <i class="fas fa-th-list"></i> ${modelFiles.length} ${translate('modals.download.fileSelection.files')} <i class="fas fa-chevron-right badge-arrow"></i>
+                   </span>`
+                : '';
+
             return `
                 <div class="version-item ${this.currentVersion?.id === version.id ? 'selected' : ''} 
                      ${existsLocally ? 'exists-locally' : ''} 
@@ -302,14 +318,23 @@ export class DownloadManager {
                         <div class="version-meta">
                             <span><i class="fas fa-calendar"></i> ${new Date(version.createdAt).toLocaleDateString()}</span>
                             <span><i class="fas fa-file-archive"></i> ${fileSize} MB</span>
+                            ${fileBadge}
                         </div>
                     </div>
                 </div>
             `;
         }).join('');
 
-        // Add click handlers for version selection
+        // Add click handlers for version selection and file badge
         versionList.addEventListener('click', (event) => {
+            const badge = event.target.closest('.file-select-badge');
+            if (badge) {
+                event.stopPropagation();
+                const versionId = badge.dataset.versionId;
+                this.selectVersion(versionId);
+                this.showFileSelectionStep(versionId);
+                return;
+            }
             const versionItem = event.target.closest('.version-item');
             if (versionItem) {
                 this.selectVersion(versionItem.dataset.versionId);
@@ -352,6 +377,80 @@ export class DownloadManager {
         }
     }
 
+    showFileSelectionStep(versionId) {
+        const version = this.versions.find(v => v.id.toString() === versionId.toString());
+        if (!version) return;
+
+        this.currentVersion = version;
+        const modelFiles = (version.files || []).filter(f => f.type === 'Model');
+
+        document.getElementById('versionStep').style.display = 'none';
+        document.getElementById('fileSelectionStep').style.display = 'block';
+
+        const nameEl = document.getElementById('fileSelectionVersionName');
+        if (nameEl) {
+            nameEl.textContent = `${version.name} · ${version.baseModel || ''}`;
+        }
+
+        const container = document.getElementById('fileSelectionList');
+        container.innerHTML = modelFiles.map(file => {
+            const meta = file.metadata || {};
+            const sizeGB = file.sizeKB ? (file.sizeKB / (1024 * 1024)).toFixed(2) : '--';
+            const isSelected = this.selectedFile?.id === file.id;
+
+            const tags = [];
+            if (meta.size) tags.push(`<span class="file-tag size">${meta.size}</span>`);
+            if (meta.format) tags.push(`<span class="file-tag format">${meta.format}</span>`);
+            if (meta.fp) tags.push(`<span class="file-tag fp">${meta.fp}</span>`);
+
+            const fileName = file.name || '';
+
+            return `
+                <div class="file-option ${isSelected ? 'selected' : ''}" data-file-id="${file.id}">
+                    <div class="file-option-radio">
+                        <input type="radio" name="fileSelection" value="${file.id}" ${isSelected ? 'checked' : ''}>
+                    </div>
+                    <div class="file-option-info">
+                        <div class="file-option-tags">
+                            ${tags.join(' ')}
+                        </div>
+                        <div class="file-option-name">${fileName}</div>
+                    </div>
+                    <div class="file-option-size">${sizeGB} GB</div>
+                </div>
+            `;
+        }).join('');
+
+        container.querySelectorAll('.file-option').forEach(el => {
+            el.addEventListener('click', () => {
+                container.querySelectorAll('.file-option').forEach(o => o.classList.remove('selected'));
+                el.classList.add('selected');
+                const radio = el.querySelector('input[type="radio"]');
+                if (radio) radio.checked = true;
+            });
+        });
+    }
+
+    confirmFileSelection() {
+        const selectedRadio = document.querySelector('#fileSelectionList input[type="radio"]:checked');
+        if (!selectedRadio) return;
+
+        const version = this.currentVersion;
+        if (!version) return;
+
+        const modelFiles = (version.files || []).filter(f => f.type === 'Model');
+        this.selectedFile = modelFiles.find(f => f.id.toString() === selectedRadio.value);
+
+        document.getElementById('fileSelectionStep').style.display = 'none';
+        document.getElementById('locationStep').style.display = 'block';
+        this.proceedToLocationContent();
+    }
+
+    backToVersionFromFiles() {
+        document.getElementById('fileSelectionStep').style.display = 'none';
+        document.getElementById('versionStep').style.display = 'block';
+    }
+
     async proceedToLocation() {
         if (!this.currentVersion) {
             showToast('toast.loras.pleaseSelectVersion', {}, 'error');
@@ -366,6 +465,10 @@ export class DownloadManager {
 
         document.getElementById('versionStep').style.display = 'none';
         document.getElementById('locationStep').style.display = 'block';
+        await this.proceedToLocationContent();
+    }
+
+    async proceedToLocationContent() {
 
         try {
             // Fetch model roots
@@ -450,6 +553,7 @@ export class DownloadManager {
         targetFolder = '',
         useDefaultPaths = false,
         source = null,
+        fileParams = null,
         closeModal = false,
     }) {
         const config = this.apiClient?.apiConfig?.config;
@@ -513,7 +617,8 @@ export class DownloadManager {
                 targetFolder,
                 useDefaultPaths,
                 downloadId,
-                source
+                source,
+                fileParams
             );
 
             if (response?.skipped) {
@@ -632,6 +737,13 @@ export class DownloadManager {
         } else {
             targetFolder = this.folderTreeManager.getSelectedPath();
         }
+        const fileParams = this.selectedFile ? {
+            type: 'Model',
+            format: this.selectedFile.metadata?.format || 'SafeTensor',
+            size: this.selectedFile.metadata?.size || 'full',
+            fp: this.selectedFile.metadata?.fp,
+        } : null;
+
         return this.executeDownloadWithProgress({
             modelId: this.modelId,
             versionId: this.currentVersion.id,
@@ -640,6 +752,7 @@ export class DownloadManager {
             targetFolder,
             useDefaultPaths,
             source: this.source,
+            fileParams,
             closeModal: true,
         });
     }

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({ preserveScroll: true });
+            await window.recipeManager.loadRecipes(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({ preserveScroll: true });
+            await window.recipeManager.loadRecipes(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'

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 {

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({ preserveScroll: true });
+        window.recipeManager.loadRecipes(true);
       } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints') {
         // For models page, reset the page and reload
         getModelApiClient().loadMoreWithVirtualScroll(true, false);

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;
         }
@@ -949,6 +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();
 
@@ -2863,7 +2876,7 @@ export class SettingsManager {
             await resetAndReload(false);
         } else if (this.currentPage === 'recipes') {
             // Reload the recipes without updating folders
-            await window.recipeManager.loadRecipes({ preserveScroll: true });
+            await window.recipeManager.loadRecipes(true);
         } else if (this.currentPage === 'checkpoints') {
             // Reload the checkpoints without updating folders
             await resetAndReload(false);