fix(test): update drag interaction test to match 454210a4's renderFunction→setValue change

Commit 454210a4 replaced renderFunction() with widget.value setter +
widget.callback() in endDrag, so the test assertion should verify
callback invocation instead of the removed renderSpy call.

data/supporters.json

@@ -12,33 +12,39 @@
     "2018cfh",
     "W+K+White",
     "wackop",
-    "Takkan",
+    "Phil",
     "Carl G.",
+    "Arlecchino Shion",
+    "stone9k",
     "$MetaSamsara",
     "itismyelement",
+    "Gingko Biloba",
     "onesecondinosaur",
-    "stone9k",
+    "Takkan",
+    "Charles Blakemore",
+    "Rob Williams",
     "Rosenthal",
     "Francisco Tatis",
+    "Tobi_Swagg",
     "Andrew Wilson",
     "Greybush",
-    "Gooohokrbe",
     "Ricky Carter",
     "JongWon Han",
-    "OldBones",
     "VantAI",
     "runte3221",
+    "Illrigger",
     "FreelancerZ",
     "Edgar Tejeda",
+    "Jorge Hussni",
     "Liam MacDougal",
     "Fraser Cross",
     "Polymorphic Indeterminate",
-    "Birdy",
     "Marc Whiffen",
-    "Jorge Hussni",
+    "Birdy",
-    "Kiba",
     "Skalabananen",
+    "Kiba",
     "Reno Lam",
+    "Mozzel",
     "sig",
     "Christian Byrne",
     "DM",
@@ -46,39 +52,41 @@
     "Estragon",
     "J\\B/ 8r0wns0n",
     "Snaggwort",
-    "Arlecchino Shion",
-    "Charles Blakemore",
-    "Rob Williams",
     "ClockDaemon",
+    "Jonathan Ross",
     "KD",
     "Omnidex",
+    "Nazono_hito",
     "Tyler Trebuchon",
     "Release Cabrakan",
-    "Tobi_Swagg",
+    "contrite831",
     "SG",
     "carozzz",
     "James Dooley",
     "zenbound",
     "Buzzard",
     "jmack",
+    "Adam Shaw",
     "Mark Corneglio",
     "SarcasticHashtag",
-    "Cosmosis",
+    "Anthony Rizzo",
     "iamresist",
+    "Gooohokrbe",
     "RedrockVP",
     "Wolffen",
-    "FloPro4Sho",
     "James Todd",
+    "OldBones",
     "Steven Pfeiffer",
     "Tim",
+    "Timmy",
+    "Johnny",
     "Lisster",
     "Michael Wong",
-    "Illrigger",
+    "whudunit",
     "Tom Corrigan",
+    "dl0901dm",
     "JackieWang",
     "fnkylove",
-    "Julian V",
-    "Steven Owens",
     "Yushio",
     "Vik71it",
     "Echo",
@@ -86,147 +94,137 @@
     "Robert Stacey",
     "PM",
     "Todd Keck",
-    "Mozzel",
+    "Briton Heilbrun",
-    "Gingko Biloba",
+    "Aleksander Wujczyk",
-    "Sterilized",
     "BadassArabianMofo",
+    "Sterilized",
     "Pascal Dahle",
     "quarz",
-    "Greg",
     "Penfore",
+    "Greg",
     "JSST",
-    "esthe",
     "lmsupporter",
-    "IamAyam",
+    "zounic",
     "wfpearl",
     "Baekdoosixt",
-    "Jonathan Ross",
     "Jack B Nimble",
-    "Nazono_hito",
     "Melville Parrish",
     "daniel dove",
     "Lustre",
     "JW Sin",
-    "contrite831",
     "Alex",
     "bh",
-    "confiscated Zyra",
     "Marlon Daniels",
     "Starkselle",
     "Aaron Bleuer",
     "LacesOut!",
     "greebles",
-    "Adam Shaw",
+    "Cosmosis",
-    "Tee Gee",
-    "Anthony Rizzo",
-    "tarek helmi",
     "M Postkasse",
+    "FloPro4Sho",
     "ASLPro3D",
     "Jacob Hoehler",
     "FinalyFree",
     "Weasyl",
-    "Timmy",
+    "Lex Song",
-    "Johnny",
     "Cory Paza",
     "Tak",
     "Gonzalo Andre Allendes Lopez",
     "Zach Gonser",
     "Big Red",
-    "whudunit",
+    "Jimmy Ledbetter",
     "Luc Job",
-    "dl0901dm",
     "Philip Hempel",
     "corde",
     "Nick Walker",
-    "lh qwe",
+    "Julian V",
+    "Steven Owens",
     "Bishoujoker",
-    "conner",
     "aai",
-    "Briton Heilbrun",
     "Tori",
     "wildnut",
-    "Princess Bright Eyes",
-    "AbstractAss",
-    "Felipe dos Santos",
-    "ViperC",
     "jean jahren",
-    "Aleksander Wujczyk",
     "AM Kuro",
-    "Markus",
+    "ViperC",
-    "S Sang",
+    "Ran C",
+    "Sangheili460",
+    "MagnaInsomnia",
     "Karl P.",
     "Akira_HentAI",
-    "MagnaInsomnia",
     "Gordon Cole",
     "yuxz69",
-    "Douglas Gaspar",
+    "esthe",
-    "AlexDuKaNa",
-    "George",
     "andrew.tappan",
-    "dw",
     "N/A",
     "The Spawn",
-    "Phil",
     "graysock",
+    "Pozadine1",
     "Greenmoustache",
-    "zounic",
     "fancypants",
+    "IamAyam",
+    "Eldithor",
+    "Joboshy",
     "Digital",
     "JaxMax",
     "takyamtom",
-    "奚明 刘",
+    "Bohemian Corporal",
+    "Dan",
+    "confiscated Zyra",
     "Jwk0205",
     "Bro Xie",
-    "준희 김",
+    "yer fey",
     "batblue",
     "carey6409",
     "Olive",
     "太郎 ゲーム",
+    "Tee Gee",
     "Some Guy Named Barry",
+    "jinxedx",
+    "tarek helmi",
     "Max Marklund",
-    "Tomohiro Baba",
-    "David Ortega",
     "AELOX",
+    "Dankin",
     "Nicfit23",
-    "Noora",
     "wamekukyouzin",
     "drum matthieu",
     "Dogmaster",
     "Matt Wenzel",
-    "Mattssn",
+    "Frank Nitty",
-    "Lex Song",
+    "Pronredn",
-    "John Saveas",
     "Christopher Michel",
     "Serge Bekenkamp",
-    "Jimmy Ledbetter",
+    "DougPeterson",
     "LeoZero",
     "Antonio Pontes",
     "ApathyJones",
     "nahinahi9",
+    "lh qwe",
+    "Kevin John Duck",
+    "conner",
     "Dustin Chen",
     "dan",
-    "Yaboi",
+    "Blackfish95",
     "Mouthlessman",
-    "Steam Steam",
+    "Princess Bright Eyes",
-    "Damon Cunliffe",
+    "Paul Kroll",
-    "CryptoTraderJK",
+    "AbstractAss",
-    "Davaitamin",
     "otaku fra",
-    "Ran C",
+    "Felipe dos Santos",
-    "tedcor",
+    "Bas Imagineer",
-    "Fotek Design",
+    "Markus",
+    "MiraiKuriyamaSy",
     "Adam Taylor",
+    "Douglas Gaspar",
     "Weird_With_A_Beard",
-    "MadSpin",
+    "AlexDuKaNa",
-    "Pozadine1",
+    "George",
+    "dw",
     "Qarob",
     "AIGooner",
-    "inbijiburu",
     "Luc",
     "ProtonPrince",
     "DiffDuck",
     "elu3199",
-    "Nick “Loadstone” D",
     "Hasturkun",
     "Jon Sandman",
     "Ubivis",
@@ -234,54 +232,45 @@
     "thesoftwaredruid",
     "wundershark",
     "mr_dinosaur",
+    "Tyrswood",
     "linnfrey",
-    "Gamalonia",
-    "Vir",
     "Pkrsky",
-    "Joboshy",
+    "奚明 刘",
-    "Bohemian Corporal",
-    "Dan",
     "Josef Lanzl",
-    "Seth Christensen",
+    "Nerezza",
     "Griffin Dahlberg",
-    "Draven T",
+    "준희 김",
-    "yer fey",
     "Error_Rule34_Not_found",
     "Gerald Welly",
     "Roslynd",
     "Geolog",
-    "jinxedx",
     "Neco28",
-    "Aquatic Coffee",
+    "Tomohiro Baba",
-    "Dankin",
+    "David Ortega",
-    "ethanfel",
+    "Noora",
     "Cristian Vazquez",
-    "Frank Nitty",
+    "Mattssn",
     "Magic Noob",
-    "Focuschannel",
-    "DougPeterson",
     "Jeff",
     "Bruce",
-    "Kevin John Duck",
-    "Anthony Faxlandez",
     "Kevin Christopher",
     "Ouro Boros",
-    "Blackfish95",
+    "Chad Idk",
+    "Yaboi",
     "dd",
-    "Paul Kroll",
+    "Steam Steam",
-    "MiraiKuriyamaSy",
+    "CryptoTraderJK",
-    "semicolon drainpipe",
+    "Davaitamin",
-    "Thesharingbrother",
+    "Dušan Ryban",
-    "Bas Imagineer",
+    "tedcor",
-    "Pat Hen",
+    "Fotek Design",
+    "sjon kreutz",
     "John Statham",
-    "ResidentDeviant",
+    "MadSpin",
-    "Nihongasuki",
+    "Metryman55",
-    "JC",
+    "inbijiburu",
-    "Prompt Pirate",
-    "uwutismxd",
     "decoy",
-    "Tyrswood",
+    "Nick “Loadstone” D",
     "Ray Wing",
     "Ranzitho",
     "Gus",
@@ -290,6 +279,7 @@
     "David LaVallee",
     "ae",
     "Tr4shP4nda",
+    "Gamalonia",
     "WRL_SPR",
     "capn",
     "Joseph",
@@ -302,77 +292,60 @@
     "Moon Knight",
     "몽타주",
     "Kland",
-    "zenobeus",
+    "Hailshem",
-    "Jackthemind",
+    "kudari",
-    "ryoma",
+    "Naomi Hale Danchi",
-    "Stryker",
+    "dc7431",
-    "raf8osz",
+    "Vir",
-    "ElitaSSJ4",
-    "blikkies",
-    "Chris",
     "Brian M",
-    "Nerezza",
     "sanborondon",
+    "Seth Christensen",
+    "Draven T",
     "Taylor Funk",
     "aezin",
     "Thought2Form",
     "jcay015",
     "Kevin Picco",
     "Erik Lopez",
-    "Shock Shockor",
     "Mateo Curić",
-    "Goldwaters",
+    "Aquatic Coffee",
-    "Zude",
     "Eris3D",
     "m",
+    "ethanfel",
     "Pierce McBride",
     "Joshua Gray",
-    "Kyler",
+    "Focuschannel",
     "Mikko Hemilä",
-    "aRtFuL_DodGeR",
     "Jamie Ogletree",
     "a _",
     "James Coleman",
-    "CrimsonDX",
     "Martial",
+    "Anthony Faxlandez",
     "battu",
     "Emil Andersson",
-    "Chad Idk",
-    "DarkSunset",
-    "Billy Gladky",
     "Yuji Kaneko",
-    "Probis",
+    "Pat Hen",
-    "Dušan Ryban",
+    "semicolon drainpipe",
-    "ItsGeneralButtNaked",
     "Jordan Shaw",
     "Rops Alot",
+    "Thesharingbrother",
     "Sam",
-    "sjon kreutz",
-    "Nimess",
-    "SRDB",
     "Ace Ventura",
-    "g unit",
+    "ResidentDeviant",
-    "Youguang",
+    "Nihongasuki",
-    "Metryman55",
+    "JC",
-    "andrewzpong",
+    "Prompt Pirate",
-    "FrxzenSnxw",
+    "uwutismxd",
-    "BossGame",
-    "lrdchs",
     "momokai",
-    "Hailshem",
+    "zenobeus",
-    "kudari",
-    "Naomi Hale Danchi",
-    "dc7431",
     "ken",
-    "Inversity",
-    "AIVORY3D",
     "epicgamer0020690",
     "Joshua Porrata",
     "keemun",
     "SuBu",
     "RedPIXel",
-    "Kevinj",
     "Wind",
+    "Jackthemind",
     "Nexus",
     "Ramneek“Guy”Ashok",
     "squid_actually",
@@ -385,80 +358,81 @@
     "emyth",
     "chriphost",
     "KitKatM",
+    "ryoma",
     "socrasteeze",
-    "ResidentDeviant",
+    "OrganicArtifact",
+    "Stryker",
+    "MudkipMedkitz",
     "gzmzmvp",
-    "Welkor",
+    "raf8osz",
-    "John Martin",
+    "ElitaSSJ4",
     "Richard",
+    "blikkies",
     "Andrew",
+    "Chris",
     "Robert Wegemund",
     "Littlehuggy",
-    "moranqianlong",
     "Gregory Kozhemiak",
     "mrjuan",
     "Brian Buie",
+    "Shock Shockor",
     "Sadlip",
-    "Haru Yotu",
+    "Goldwaters",
     "Eric Whitney",
     "Joey Callahan",
+    "Zude",
     "Ivan Tadic",
     "Mike Simone",
+    "John J Linehan",
+    "Kyler",
+    "Elliot E",
     "Morgandel",
-    "Kyron Mahan",
+    "Theerat Jiramate",
-    "Matura Arbeit",
+    "aRtFuL_DodGeR",
     "Noah",
     "Jacob McDaniel",
     "X",
     "Sloan Steddy",
-    "TBitz33",
-    "Anonym dkjglfleeoeldldldlkf",
     "Temikus",
     "Artokun",
     "Michael Taylor",
-    "SendingRavens",
     "Derek Baker",
+    "CrimsonDX",
     "Michael Anthony Scott",
+    "DarkSunset",
     "Atilla Berke Pekduyar",
-    "Michael Docherty",
     "Nathan",
+    "Billy Gladky",
+    "NICHOLAS BAXLEY",
     "Decx _",
-    "Paul Hartsuyker",
+    "Probis",
-    "elitassj",
+    "Ed Wang",
-    "Jacob Winter",
+    "ItsGeneralButtNaked",
+    "Nimess",
+    "SRDB",
+    "g unit",
     "Distortik",
-    "David",
+    "Youguang",
-    "Meilo",
-    "Pen Bouryoung",
     "四糸凜音",
-    "shinonomeiro",
+    "Saya",
-    "Snille",
+    "andrewzpong",
-    "MaartenAlbers",
+    "FrxzenSnxw",
-    "khanh duy",
+    "BossGame",
-    "xybrightsummer",
+    "lrdchs",
-    "jreedatchison",
-    "PhilW",
     "Tree Tagger",
-    "Janik",
+    "Inversity",
     "Crocket",
-    "Cruel",
+    "AIVORY3D",
-    "MRBlack",
+    "Kevinj",
     "Mitchell Robson",
-    "Kiyoe",
-    "humptynutz",
-    "michael.isaza",
-    "Kalnei",
     "Whitepinetrader",
-    "OrganicArtifact",
+    "ResidentDeviant",
-    "Scott",
-    "MudkipMedkitz",
     "deanbrian",
     "POPPIN",
     "Alex Wortman",
     "Cody",
     "Raku",
     "smart.edge5178",
-    "emadsultan",
     "InformedViewz",
     "CHKeeho80",
     "Bubbafett",
@@ -466,76 +440,152 @@
     "Menard",
     "Skyfire83",
     "Adam Rinehart",
-    "D",
     "Pitpe11",
     "TheD1rtyD03",
     "moonpetal",
     "SomeDude",
     "g9p0o",
-    "nanana",
     "TheHolySheep",
     "Monte Won",
     "SpringBootisTrash",
     "carsten",
     "ikok",
+    "Nathen+Choi",
+    "T",
+    "LarsesFPC",
+    "cocona",
+    "sfasdfasfdsa",
     "Buecyb99",
-    "4IXplr0r3r",
+    "Welkor",
-    "dfklsjfkljslfjd",
+    "David Schenck",
-    "hayden",
+    "John Martin",
-    "ahoystan",
-    "Leland Saunders",
     "Wolfe7D1",
     "Ink Temptation",
-    "Bob Barker",
+    "moranqianlong",
-    "edk",
     "Kalli Core",
-    "Aeternyx",
     "elleshar666",
-    "YOU SINWOO",
+    "ACTUALLY_the_Real_Willem_Dafoe",
-    "ja s",
+    "Haru Yotu",
-    "Doug Mason",
     "Kauffy",
-    "Jeremy Townsend",
     "EpicElric",
-    "Sean voets",
+    "Kyron Mahan",
-    "Owen Gwosdz",
-    "John J Linehan",
-    "Elliot E",
-    "Thomas Wanner",
-    "Theerat Jiramate",
     "Edward Kennedy",
     "Justin Blaylock",
-    "Devil Lude",
+    "Matura Arbeit",
     "Nick Kage",
-    "kevin stoddard",
+    "TBitz33",
-    "Jack Dole",
+    "Anonym dkjglfleeoeldldldlkf",
     "Vane Holzer",
     "psytrax",
+    "Cyrus Fett",
     "Ezokewn",
+    "SendingRavens",
     "hexxish",
-    "CptNeo",
     "notedfakes",
-    "Maso",
+    "Michael Docherty",
-    "Eric Ketchum",
-    "NICHOLAS BAXLEY",
     "Michael Scott",
-    "Kevin Wallace",
+    "Paul Hartsuyker",
-    "Matheus Couto",
+    "elitassj",
-    "Saya",
+    "Jacob Winter",
-    "ChicRic",
-    "mercur",
-    "J C",
-    "Ed Wang",
     "Ryan Presley Ng",
     "Wes Sims",
     "Donor4115",
+    "Lyavph",
+    "David",
+    "Meilo",
+    "Filippo Ferrari",
+    "Pen Bouryoung",
+    "shinonomeiro",
+    "Snille",
+    "MaartenAlbers",
+    "khanh duy",
+    "xybrightsummer",
+    "jreedatchison",
+    "PhilW",
+    "Janik",
+    "Cruel",
+    "MRBlack",
+    "Kiyoe",
+    "humptynutz",
+    "michael.isaza",
+    "Kalnei",
+    "Scott",
+    "Muratoraccio",
+    "Ginnie",
+    "emadsultan",
+    "D",
+    "nanana",
+    "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",
+    "りん あめ",
+    "ja s",
+    "Михал Михалыч",
+    "Matt",
+    "Doug Mason",
+    "Jeremy Townsend",
+    "Frogmilk",
+    "Sean voets",
+    "Owen Gwosdz",
+    "SPJ",
+    "Thomas Wanner",
+    "Bryan Rutkowski",
+    "Devil Lude",
+    "David Murcko",
+    "kevin stoddard",
+    "Jack Dole",
+    "max blo",
+    "Xenon Xue",
+    "CptNeo",
+    "JackJohnnyJim",
+    "Dmitry Ryzhov",
+    "Maso",
+    "Edward Ten Eyck",
+    "Eric Ketchum",
+    "Kevin Wallace",
+    "Matheus Couto",
+    "ChicRic",
+    "Henrique Faiolli",
+    "mercur",
+    "Solixer",
+    "J C",
+    "jinksta187",
+    "Andrew Wilkinson",
+    "Manu Thetug",
+    "Karlanx",
     "Yves Poezevara",
+    "operationancut",
     "Teriak47",
     "Just me",
     "Raf Stahelin",
     "Вячеслав Маринин",
-    "Lyavph",
-    "Filippo Ferrari",
     "Cola Matthew",
     "OniNoKen",
     "Iain Wisely",
@@ -576,98 +626,121 @@
     "dg",
     "Maarten Harms",
     "Israel",
-    "Muratoraccio",
     "SelfishMedic",
-    "Ginnie",
     "adderleighn",
     "EnragedAntelope",
-    "Alan+Cano",
+    "lighthawke",
-    "FeralOpticsAI",
+    "Terraformer",
-    "Pavlaki",
+    "GDS+DEV",
-    "generic404",
+    "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",
-    "Doug+Rintoul",
-    "Noor",
-    "Yorunai",
     "Bula",
-    "quantenmecha",
-    "abattoirblues",
-    "Jason+Nash",
-    "BillyBoy84",
-    "DarkRoast",
-    "zounik",
-    "letzte",
-    "Nasty+Hobbit",
-    "SgtFluffles",
-    "lrdchs2",
-    "Duk3+Rand0m",
     "KUJYAKU",
-    "NathenChoi",
-    "Thomas+Reck",
-    "Larses",
-    "cocona",
     "Coeur+de+cochon",
-    "David Schenck",
     "han b",
     "Nico",
     "Banana Joe",
     "_ G3n",
     "Donovan Jenkins",
-    "JBsuede",
+    "Tú Nguyễn Lý Hoàng",
     "Michael Eid",
     "beersandbacon",
     "Maximilian Pyko",
     "Invis",
-    "Justin Houston",
+    "Bob barker",
-    "Time Valentine",
+    "Ben D",
+    "Garrett Wood",
+    "Ronan Delevacq",
     "james",
+    "Christian Schäfer",
     "OrochiNights",
     "Michael Zhu",
-    "ACTUALLY_the_Real_Willem_Dafoe",
     "gonzalo",
     "Seraphy",
-    "Михал Михалыч",
     "雨の心 落",
-    "Matt",
     "AllTimeNoobie",
     "jumpd",
     "John C",
     "Rim",
+    "Dave Abraham",
+    "Joaquin Hierrezuelo",
     "Dismem",
-    "Frogmilk",
+    "Locrospiel",
-    "SPJ",
+    "Jairus Knudsen",
+    "Jarrid Lee",
     "Xan Dionysus",
     "Nathan lee",
+    "Kor",
+    "Joseph Hanson",
     "Mewtora",
     "Middo",
     "Forbidden Atelier",
-    "Bryan Rutkowski",
+    "John Rednoulf",
+    "Spire",
     "Adictedtohumping",
+    "Boba Smith",
     "Towelie",
-    "Cyrus Fett",
+    "MR.Bear",
+    "dsffsdfsdfsdfsdfsdf",
     "Jean-françois SEMA",
     "Kurt",
-    "max blo",
+    "ivistorm",
-    "Xenon Xue",
+    "Sauv",
-    "JackJohnnyJim",
+    "Steven",
-    "Edward Ten Eyck",
+    "TenaciousD",
+    "Khánh Đặng",
     "Chase Kwon",
+    "Ted Cart",
     "Inyoshu",
     "Goober719",
     "Chad Barnes",
+    "Person Y",
+    "David Spearing",
     "James Ming",
     "vanditking",
     "kripitonga",
     "Rizzi",
     "nimin",
     "OMAR LUCIANO",
+    "Ken+Suzuki",
     "hannibal",
     "Jo+Example",
     "BrentBertram",
+    "Tigon",
     "eumelzocker",
     "dxjaymz",
     "L C",
-    "Dude"
+    "Dude",
+    "CK"
   ],
-  "totalCount": 666
+  "totalCount": 739
 }

docs/LM-Extension-Wiki.md

@@ -1,183 +0,0 @@
-## Overview
-
-The **LoRA Manager Civitai Extension** is a Browser extension designed to work seamlessly with [LoRA Manager](https://github.com/willmiao/ComfyUI-Lora-Manager) to significantly enhance your browsing experience on [Civitai](https://civitai.com). With this extension, you can:
-
-✅ Instantly see which models are already present in your local library  
-✅ Download new models with a single click  
-✅ Manage downloads efficiently with queue and parallel download support  
-✅ Keep your downloaded models automatically organized according to your custom settings    
-
-![Civitai Models page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-models-page.png) 
-
-**Update:** It now also supports browsing on [CivArchive](https://civarchive.com/) (formerly CivitaiArchive). 
-
-![CivArchive Models page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civarchive-models-page.png)  
-
----
-
-## Why Supporter Access?
-
-LoRA Manager is built with love for the Stable Diffusion and ComfyUI communities. Your support makes it possible for me to keep improving and maintaining the tool full-time.
-
-Supporter-exclusive features help ensure the long-term sustainability of LoRA Manager, allowing continuous updates, new features, and better performance for everyone.
-
-Every contribution directly fuels development and keeps the core LoRA Manager free and open-source. In addition to monthly supporters, one-time donation supporters will also receive a license key, with the duration scaling according to the contribution amount. Thank you for helping keep this project alive and growing. ❤️
-
-
----
-
-## Installation
-
-### Supported Browsers & Installation Methods
-
-| Browser            | Installation Method                                                                 |
-|--------------------|-------------------------------------------------------------------------------------|
-| **Google Chrome**   | [Chrome Web Store link](https://chromewebstore.google.com/detail/capigligggeijgmocnaflanlbghnamgm?utm_source=item-share-cb) |
-| **Microsoft Edge**  | Install via Chrome Web Store (compatible)                                          |
-| **Brave Browser**   | Install via Chrome Web Store (compatible)                                          |
-| **Opera**           | Install via Chrome Web Store (compatible)                                          |
-| **Firefox**         | <div id="firefox-install" class="install-ok"><a href="https://github.com/willmiao/lm-civitai-extension-firefox/releases/latest/download/extension.xpi">📦 Install Firefox Extension (reviewed and verified by Mozilla)</a></div>             |
-
-For non-Chrome browsers (e.g., Microsoft Edge), you can typically install extensions from the Chrome Web Store by following these steps: open the extension’s Chrome Web Store page, click 'Get extension', then click 'Allow' when prompted to enable installations from other stores, and finally click 'Add extension' to complete the installation.
-
----
-
-## Privacy & Security
-
-I understand concerns around browser extensions and privacy, and I want to be fully transparent about how the **LM Civitai Extension** works:
-
-- **Reviewed and Verified**  
-  This extension has been **manually reviewed and approved by the Chrome Web Store**. The Firefox version uses the **exact same code** (only the packaging format differs) and has passed **Mozilla’s Add-on review**.
-
-- **Minimal Network Access**  
-  The only external server this extension connects to is:  
-  **`https://willmiao.shop`** — used solely for **license validation**.
-
-  It does **not collect, transmit, or store any personal or usage data**.  
-  No browsing history, no user IDs, no analytics, no hidden trackers.
-
-- **Local-Only Model Detection**  
-  Model detection and LoRA Manager communication all happen **locally** within your browser, directly interacting with your local LoRA Manager backend.
-
-I value your trust and are committed to keeping your local setup private and secure. If you have any questions, feel free to reach out!
-
----
-
-## How to Use
-
-After installing the extension, you'll automatically receive a **7-day trial** to explore all features.
-
-When the extension is correctly installed and your license is valid:
-
-- Open **Civitai**, and you'll see visual indicators added by the extension on model cards, showing:
-  - ✅ Models already present in your local library  
-  - ⬇️ A download button for models not in your library  
-
-Clicking the download button adds the corresponding model version to the download queue, waiting to be downloaded. You can set up to **5 models to download simultaneously**.
-
-### Visual Indicators Appear On:
-
-- **Home Page** — Featured models  
-- **Models Page**  
-- **Creator Profiles** — If the creator has set their models to be visible  
-- **Recommended Resources** — On individual model pages  
-
-### Version Buttons on Model Pages
-
-On a specific model page, visual indicators also appear on version buttons, showing which versions are already in your local library.
-
-**Starting from v0.4.8**, model pages use a dedicated download button for better compatibility. When switching to a specific version by clicking a version button:
-
-- The new **dedicated download button** directly triggers download via **LoRA Manager**
-- The **original download button** remains unchanged for standard browser downloads
-
-![Civitai Model Page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-model-page.png)
-
-### Hide Models Already in Library (Beta)
-
-**New in v0.4.8**: A new **Hide models already in library (Beta)** option makes it easier to focus on models you haven't added yet. It can be enabled from Settings, or toggled quickly using **Ctrl + Shift + H** (macOS: **Command + Shift + H**).
-
-### Resources on Image Pages — now shows in-library indicators for image resources plus one-click recipe import
-
-- **One-Click Import Civitai Image as Recipe** — Import any Civitai image as a recipe with a single click in the Resources Used panel.
-- **Auto-Queue Missing Assets** — In Settings you can decide if LoRAs or checkpoints referenced by that image should automatically be added to your download queue.
-- **More Accurate Metadata** — Importing directly from the page is faster than copying inside LM and keeps on-site tags and other metadata perfectly aligned.
-
-![Civitai Image Page](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/civitai-image-page.jpg)
-
-[![alt](url)](https://github.com/user-attachments/assets/41fd4240-c949-4f83-bde7-8f3124c09494)
-
----
-
-## Model Download Location & LoRA Manager Settings
-
-To use the **one-click download function**, you must first set:
-
-- Your **Default LoRAs Root**  
-- Your **Default Checkpoints Root**  
-
-These are set within LoRA Manager's settings.
-
-When everything is configured, downloaded model files will be placed in:  
-
-`<Default_Models_Root>/<Base_Model_of_the_Model>/<First_Tag_of_the_Model>`
-
-
-### Update: Default Path Customization (2025-07-21)  
-
-A new setting to customize the default download path has been added in the nightly version. You can now personalize where models are saved when downloading via the LM Civitai Extension.
-
-![Default Path Customization](https://github.com/willmiao/ComfyUI-Lora-Manager/blob/main/wiki-images/default-path-customization.png)
-
-The previous YAML path mapping file will be deprecated—settings will now be unified in settings.json to simplify configuration.
-
----
-
-## Backend Port Configuration
-
-If your **ComfyUI** or **LoRA Manager** backend is running on a port **other than the default 8188**, you must configure the backend port in the extension's settings.
-
-After correctly setting and saving the port, you'll see in the extension's header area:  
-- A **Healthy** status with the tooltip:  `Connected to LoRA Manager on port xxxx`
-
-
----
-
-## Advanced Usage
-
-### Connecting to a Remote LoRA Manager
-
-If your LoRA Manager is running on another computer, you can still connect from your browser using port forwarding.
-
-> **Why can't you set a remote IP directly?**
->
-> For privacy and security, the extension only requests access to `http://127.0.0.1/*`. Supporting remote IPs would require much broader permissions, which may be rejected by browser stores and could raise user concerns.
-
-**Solution: Port Forwarding with `socat`**
-
-On your browser computer, run:
-
-`socat TCP-LISTEN:8188,bind=127.0.0.1,fork TCP:REMOTE.IP.ADDRESS.HERE:8188`
-
-- Replace `REMOTE.IP.ADDRESS.HERE` with the IP of the machine running LoRA Manager.
-- Adjust the port if needed.
-
-This lets the extension connect to `127.0.0.1:8188` as usual, with traffic forwarded to your remote server.
-
-_Thanks to user **Temikus** for sharing this solution!_
-
----
-
-## Roadmap
-
-The extension will evolve alongside **LoRA Manager** improvements. Planned features include:
-
-- [x] Support for **additional model types** (e.g., embeddings)
-- [x] One-click **Recipe Import**
-- [x] Display of in-library status for all resources in the **Resources Used** section of the image page
-- [x] One-click **Auto-organize Models**
-- [x] **Hide models already in library (Beta)** - Focus on models you haven't added yet
-
-**Stay tuned — and thank you for your support!**
-
----

locales/de.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Automatisch organisieren",
             "skipMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle überspringen",
             "resumeMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle fortsetzen",
+            "setFavorite": "Als Favorit setzen",
+            "setFavoriteCount": "Als Favorit setzen ({favorited}/{total})",
+            "unfavorite": "Aus Favoriten entfernen",
             "deleteAll": "Ausgewählte löschen",
             "downloadMissingLoras": "Fehlende LoRAs herunterladen",
             "clear": "Auswahl löschen",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Inhaltsbewertung auf {level} für {count} Modell(e) gesetzt",
             "bulkContentRatingPartial": "Inhaltsbewertung auf {level} für {success} Modell(e) gesetzt, {failed} fehlgeschlagen",
             "bulkContentRatingFailed": "Inhaltsbewertung für ausgewählte Modelle konnte nicht aktualisiert werden",
+            "bulkFavoriteUpdating": "Füge {count} Modell(e) zu Favoriten hinzu...",
+            "bulkUnfavoriteUpdating": "Entferne {count} Modell(e) aus Favoriten...",
+            "bulkFavoritePartialAdded": "{success} Modell(e) zu Favoriten hinzugefügt, {failed} fehlgeschlagen",
+            "bulkFavoritePartialRemoved": "{success} Modell(e) aus Favoriten entfernt, {failed} fehlgeschlagen",
+            "bulkFavoriteFailed": "Fehler beim Aktualisieren des Favoritenstatus",
             "bulkUpdatesChecking": "Ausgewählte {type}-Modelle werden auf Updates geprüft...",
             "bulkUpdatesSuccess": "Updates für {count} ausgewählte {type}-Modelle verfügbar",
             "bulkUpdatesNone": "Keine Updates für ausgewählte {type}-Modelle gefunden",

locales/en.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Auto-Organize Selected",
             "skipMetadataRefresh": "Skip Metadata Refresh for Selected",
             "resumeMetadataRefresh": "Resume Metadata Refresh for Selected",
+            "setFavorite": "Set as Favorite",
+            "setFavoriteCount": "Set as Favorite ({favorited}/{total})",
+            "unfavorite": "Remove from Favorites",
             "deleteAll": "Delete Selected",
             "downloadMissingLoras": "Download Missing LoRAs",
             "clear": "Clear Selection",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Set content rating to {level} for {count} model(s)",
             "bulkContentRatingPartial": "Set content rating to {level} for {success} model(s), {failed} failed",
             "bulkContentRatingFailed": "Failed to update content rating for selected models",
+            "bulkFavoriteUpdating": "Adding {count} model(s) to favorites...",
+            "bulkUnfavoriteUpdating": "Removing {count} model(s) from favorites...",
+            "bulkFavoritePartialAdded": "Added {success} model(s) to favorites, {failed} failed",
+            "bulkFavoritePartialRemoved": "Removed {success} model(s) from favorites, {failed} failed",
+            "bulkFavoriteFailed": "Failed to update favorite status for selected models",
             "bulkUpdatesChecking": "Checking selected {type}(s) for updates...",
             "bulkUpdatesSuccess": "Updates available for {count} selected {type}(s)",
             "bulkUpdatesNone": "No updates found for selected {type}(s)",

locales/es.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Auto-organizar seleccionados",
             "skipMetadataRefresh": "Omitir actualización de metadatos para seleccionados",
             "resumeMetadataRefresh": "Reanudar actualización de metadatos para seleccionados",
+            "setFavorite": "Marcar como favorito",
+            "setFavoriteCount": "Marcar como favorito ({favorited}/{total})",
+            "unfavorite": "Quitar de favoritos",
             "deleteAll": "Eliminar seleccionados",
             "downloadMissingLoras": "Descargar LoRAs faltantes",
             "clear": "Limpiar selección",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Clasificación de contenido establecida en {level} para {count} modelo(s)",
             "bulkContentRatingPartial": "Clasificación de contenido establecida en {level} para {success} modelo(s), {failed} fallaron",
             "bulkContentRatingFailed": "No se pudo actualizar la clasificación de contenido para los modelos seleccionados",
+            "bulkFavoriteUpdating": "Añadiendo {count} modelo(s) a favoritos...",
+            "bulkUnfavoriteUpdating": "Eliminando {count} modelo(s) de favoritos...",
+            "bulkFavoritePartialAdded": "{success} modelo(s) añadido(s) a favoritos, {failed} fallido(s)",
+            "bulkFavoritePartialRemoved": "{success} modelo(s) eliminado(s) de favoritos, {failed} fallido(s)",
+            "bulkFavoriteFailed": "Error al actualizar el estado de favorito",
             "bulkUpdatesChecking": "Comprobando actualizaciones para {type} seleccionados...",
             "bulkUpdatesSuccess": "Actualizaciones disponibles para {count} {type} seleccionados",
             "bulkUpdatesNone": "No se encontraron actualizaciones para los {type} seleccionados",

locales/fr.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Auto-organiser la sélection",
             "skipMetadataRefresh": "Ignorer l'actualisation des métadonnées pour la sélection",
             "resumeMetadataRefresh": "Reprendre l'actualisation des métadonnées pour la sélection",
+            "setFavorite": "Définir comme favori",
+            "setFavoriteCount": "Définir comme favori ({favorited}/{total})",
+            "unfavorite": "Retirer des favoris",
             "deleteAll": "Supprimer la sélection",
             "downloadMissingLoras": "Télécharger les LoRAs manquants",
             "clear": "Effacer la sélection",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Classification du contenu définie sur {level} pour {count} modèle(s)",
             "bulkContentRatingPartial": "Classification du contenu définie sur {level} pour {success} modèle(s), {failed} échec(s)",
             "bulkContentRatingFailed": "Impossible de mettre à jour la classification du contenu pour les modèles sélectionnés",
+            "bulkFavoriteUpdating": "Ajout de {count} modèle(s) aux favoris...",
+            "bulkUnfavoriteUpdating": "Suppression de {count} modèle(s) des favoris...",
+            "bulkFavoritePartialAdded": "{success} modèle(s) ajouté(s) aux favoris, {failed} échec(s)",
+            "bulkFavoritePartialRemoved": "{success} modèle(s) retiré(s) des favoris, {failed} échec(s)",
+            "bulkFavoriteFailed": "Échec de la mise à jour du statut de favori",
             "bulkUpdatesChecking": "Vérification des mises à jour pour les {type} sélectionnés...",
             "bulkUpdatesSuccess": "Mises à jour disponibles pour {count} {type} sélectionnés",
             "bulkUpdatesNone": "Aucune mise à jour trouvée pour les {type} sélectionnés",

locales/he.json

@@ -687,6 +687,9 @@
             "autoOrganize": "ארגן אוטומטית נבחרים",
             "skipMetadataRefresh": "דילוג על רענון מטא-נתונים לנבחרים",
             "resumeMetadataRefresh": "המשך רענון מטא-נתונים לנבחרים",
+            "setFavorite": "הגדר כמועדף",
+            "setFavoriteCount": "הגדר כמועדף ({favorited}/{total})",
+            "unfavorite": "הסר ממועדפים",
             "deleteAll": "מחק נבחרים",
             "downloadMissingLoras": "הורדת LoRAs חסרים",
             "clear": "נקה בחירה",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "דירוג התוכן הוגדר ל-{level} עבור {count} מודלים",
             "bulkContentRatingPartial": "דירוג התוכן הוגדר ל-{level} עבור {success} מודלים, {failed} נכשלו",
             "bulkContentRatingFailed": "עדכון דירוג התוכן עבור המודלים שנבחרו נכשל",
+            "bulkFavoriteUpdating": "מוסיף {count} דגמים למועדפים...",
+            "bulkUnfavoriteUpdating": "מסיר {count} דגמים ממועדפים...",
+            "bulkFavoritePartialAdded": "{success} דגמים נוספו למועדפים, {failed} נכשלו",
+            "bulkFavoritePartialRemoved": "{success} דגמים הוסרו ממועדפים, {failed} נכשלו",
+            "bulkFavoriteFailed": "עדכון סטטוס מועדפים נכשל",
             "bulkUpdatesChecking": "בודק עדכונים עבור {type} שנבחרו...",
             "bulkUpdatesSuccess": "יש עדכונים עבור {count} {type} שנבחרו",
             "bulkUpdatesNone": "לא נמצאו עדכונים עבור {type} שנבחרו",

locales/ja.json

@@ -687,6 +687,9 @@
             "autoOrganize": "自動整理を実行",
             "skipMetadataRefresh": "選択したモデルのメタデータ更新をスキップ",
             "resumeMetadataRefresh": "選択したモデルのメタデータ更新を再開",
+            "setFavorite": "お気に入りに設定",
+            "setFavoriteCount": "お気に入りに設定 ({favorited}/{total})",
+            "unfavorite": "お気に入りから削除",
             "deleteAll": "選択したものを削除",
             "downloadMissingLoras": "不足している LoRA をダウンロード",
             "clear": "選択をクリア",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "{count} 件のモデルのコンテンツレーティングを {level} に設定しました",
             "bulkContentRatingPartial": "{success} 件のモデルのコンテンツレーティングを {level} に設定、{failed} 件は失敗しました",
             "bulkContentRatingFailed": "選択したモデルのコンテンツレーティングを更新できませんでした",
+            "bulkFavoriteUpdating": "{count} 個のモデルをお気に入りに追加中...",
+            "bulkUnfavoriteUpdating": "{count} 個のモデルをお気に入りから削除中...",
+            "bulkFavoritePartialAdded": "{success} 個のモデルをお気に入りに追加、{failed} 個失敗",
+            "bulkFavoritePartialRemoved": "{success} 個のモデルをお気に入りから削除、{failed} 個失敗",
+            "bulkFavoriteFailed": "お気に入り状態の更新に失敗しました",
             "bulkUpdatesChecking": "選択された{type}の更新を確認しています...",
             "bulkUpdatesSuccess": "{count} 件の選択された{type}に利用可能な更新があります",
             "bulkUpdatesNone": "選択された{type}には更新が見つかりませんでした",

locales/ko.json

@@ -687,6 +687,9 @@
             "autoOrganize": "자동 정리 선택",
             "skipMetadataRefresh": "선택한 모델의 메타데이터 새로고침 건너뛰기",
             "resumeMetadataRefresh": "선택한 모델의 메타데이터 새로고침 재개",
+            "setFavorite": "즐겨찾기로 설정",
+            "setFavoriteCount": "즐겨찾기로 설정 ({favorited}/{total})",
+            "unfavorite": "즐겨찾기 해제",
             "deleteAll": "선택된 항목 삭제",
             "downloadMissingLoras": "누락된 LoRA 다운로드",
             "clear": "선택 지우기",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "{count}개 모델의 콘텐츠 등급을 {level}(으)로 설정했습니다",
             "bulkContentRatingPartial": "{success}개 모델의 콘텐츠 등급을 {level}(으)로 설정했고, {failed}개는 실패했습니다",
             "bulkContentRatingFailed": "선택한 모델의 콘텐츠 등급을 업데이트하지 못했습니다",
+            "bulkFavoriteUpdating": "{count}개 모델을 즐겨찾기에 추가 중...",
+            "bulkUnfavoriteUpdating": "{count}개 모델을 즐겨찾기에서 제거 중...",
+            "bulkFavoritePartialAdded": "{success}개 모델을 즐겨찾기에 추가, {failed}개 실패",
+            "bulkFavoritePartialRemoved": "{success}개 모델을 즐겨찾기에서 제거, {failed}개 실패",
+            "bulkFavoriteFailed": "즐겨찾기 상태 업데이트 실패",
             "bulkUpdatesChecking": "선택한 {type}의 업데이트를 확인하는 중...",
             "bulkUpdatesSuccess": "선택한 {count}개의 {type}에 사용할 수 있는 업데이트가 있습니다",
             "bulkUpdatesNone": "선택한 {type}에 대한 업데이트가 없습니다",

locales/ru.json

@@ -687,6 +687,9 @@
             "autoOrganize": "Автоматически организовать выбранные",
             "skipMetadataRefresh": "Пропустить обновление метаданных для выбранных",
             "resumeMetadataRefresh": "Возобновить обновление метаданных для выбранных",
+            "setFavorite": "Добавить в избранное",
+            "setFavoriteCount": "Добавить в избранное ({favorited}/{total})",
+            "unfavorite": "Удалить из избранного",
             "deleteAll": "Удалить выбранные",
             "downloadMissingLoras": "Скачать отсутствующие LoRAs",
             "clear": "Очистить выбор",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "Рейтинг контента установлен на {level} для {count} модель(ей)",
             "bulkContentRatingPartial": "Рейтинг контента {level} установлен для {success} модель(ей), {failed} не удалось",
             "bulkContentRatingFailed": "Не удалось обновить рейтинг контента для выбранных моделей",
+            "bulkFavoriteUpdating": "Добавление {count} моделей в избранное...",
+            "bulkUnfavoriteUpdating": "Удаление {count} моделей из избранного...",
+            "bulkFavoritePartialAdded": "{success} моделей добавлено в избранное, {failed} не удалось",
+            "bulkFavoritePartialRemoved": "{success} моделей удалено из избранного, {failed} не удалось",
+            "bulkFavoriteFailed": "Не удалось обновить статус избранного",
             "bulkUpdatesChecking": "Проверка обновлений для выбранных {type}...",
             "bulkUpdatesSuccess": "Доступны обновления для {count} выбранных {type}",
             "bulkUpdatesNone": "Обновления для выбранных {type} не найдены",

locales/zh-CN.json

@@ -687,6 +687,9 @@
             "autoOrganize": "自动整理所选模型",
             "skipMetadataRefresh": "跳过所选模型的元数据刷新",
             "resumeMetadataRefresh": "恢复所选模型的元数据刷新",
+            "setFavorite": "设为收藏",
+            "setFavoriteCount": "设为收藏 ({favorited}/{total})",
+            "unfavorite": "取消收藏",
             "deleteAll": "删除已选",
             "downloadMissingLoras": "下载缺失的 LoRAs",
             "clear": "清除选择",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "已将 {count} 个模型的内容评级设置为 {level}",
             "bulkContentRatingPartial": "已将 {success} 个模型的内容评级设置为 {level}，{failed} 个失败",
             "bulkContentRatingFailed": "未能更新所选模型的内容评级",
+            "bulkFavoriteUpdating": "正在将 {count} 个模型添加到收藏...",
+            "bulkUnfavoriteUpdating": "正在将 {count} 个模型从收藏移除...",
+            "bulkFavoritePartialAdded": "已将 {success} 个模型添加到收藏，{failed} 个失败",
+            "bulkFavoritePartialRemoved": "已将 {success} 个模型从收藏移除，{failed} 个失败",
+            "bulkFavoriteFailed": "更新收藏状态失败",
             "bulkUpdatesChecking": "正在检查所选 {type} 的更新...",
             "bulkUpdatesSuccess": "{count} 个所选 {type} 有可用更新",
             "bulkUpdatesNone": "所选 {type} 未发现更新",

locales/zh-TW.json

@@ -687,6 +687,9 @@
             "autoOrganize": "自動整理所選模型",
             "skipMetadataRefresh": "跳過所選模型的元數據更新",
             "resumeMetadataRefresh": "恢復所選模型的元數據更新",
+            "setFavorite": "設為收藏",
+            "setFavoriteCount": "設為收藏 ({favorited}/{total})",
+            "unfavorite": "取消收藏",
             "deleteAll": "刪除所選",
             "downloadMissingLoras": "下載缺失的 LoRAs",
             "clear": "清除選取",
@@ -1699,6 +1702,11 @@
             "bulkContentRatingSet": "已將 {count} 個模型的內容分級設定為 {level}",
             "bulkContentRatingPartial": "已將 {success} 個模型的內容分級設定為 {level}，{failed} 個失敗",
             "bulkContentRatingFailed": "無法更新所選模型的內容分級",
+            "bulkFavoriteUpdating": "正在將 {count} 個模型加入收藏...",
+            "bulkUnfavoriteUpdating": "正在將 {count} 個模型從收藏移除...",
+            "bulkFavoritePartialAdded": "已將 {success} 個模型加入收藏，{failed} 個失敗",
+            "bulkFavoritePartialRemoved": "已將 {success} 個模型從收藏移除，{failed} 個失敗",
+            "bulkFavoriteFailed": "更新收藏狀態失敗",
             "bulkUpdatesChecking": "正在檢查所選 {type} 的更新...",
             "bulkUpdatesSuccess": "{count} 個所選 {type} 有可用更新",
             "bulkUpdatesNone": "所選 {type} 未找到更新",

py/metadata_collector/metadata_processor.py

@@ -560,8 +560,14 @@ class MetadataProcessor:
         
         params["loras"] = " ".join(lora_parts)
         
-        # Set default clip_skip value
+        # Extract clip_skip from any SAMPLING node that provides it
-        params["clip_skip"] = "1"  # Common default
+        for sampler_info in metadata.get(SAMPLING, {}).values():
+            clip_skip = sampler_info.get("parameters", {}).get("clip_skip")
+            if clip_skip is not None:
+                params["clip_skip"] = clip_skip
+                break
+        if params["clip_skip"] is None:
+            params["clip_skip"] = "1"
         
         return params
     

py/metadata_collector/node_extractors.py

@@ -144,6 +144,118 @@ class TSCCheckpointLoaderExtractor(NodeMetadataExtractor):
                 metadata[PROMPTS][node_id]["positive_encoded"] = positive_conditioning
                 metadata[PROMPTS][node_id]["negative_encoded"] = negative_conditioning
 
+
+class EasyComfyLoaderExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        if "ckpt_name" in inputs:
+            _store_checkpoint_metadata(metadata, node_id, inputs["ckpt_name"])
+
+        # Only extract from optional_lora_stack — skip the single lora_name to
+        # avoid double-counting LoRAs that come through the LORA_STACK path.
+        active_loras = []
+        optional_lora_stack = inputs.get("optional_lora_stack")
+        if optional_lora_stack is not None and isinstance(optional_lora_stack, (list, tuple)):
+            for item in optional_lora_stack:
+                if isinstance(item, (list, tuple)) and len(item) >= 2:
+                    lora_path = item[0]
+                    model_strength = item[1]
+                    lora_name = os.path.splitext(os.path.basename(lora_path))[0]
+                    active_loras.append({
+                        "name": lora_name,
+                        "strength": model_strength
+                    })
+
+        if active_loras:
+            metadata[LORAS][node_id] = {
+                "lora_list": active_loras,
+                "node_id": node_id
+            }
+
+        positive_text = inputs.get("positive", "")
+        negative_text = inputs.get("negative", "")
+
+        if positive_text or negative_text:
+            if node_id not in metadata[PROMPTS]:
+                metadata[PROMPTS][node_id] = {"node_id": node_id}
+            metadata[PROMPTS][node_id]["positive_text"] = positive_text
+            metadata[PROMPTS][node_id]["negative_text"] = negative_text
+
+        if "clip_skip" in inputs:
+            clip_skip = inputs["clip_skip"]
+            if node_id not in metadata[SAMPLING]:
+                metadata[SAMPLING][node_id] = {"parameters": {}, "node_id": node_id}
+            metadata[SAMPLING][node_id]["parameters"]["clip_skip"] = clip_skip
+
+        width = inputs.get("empty_latent_width")
+        height = inputs.get("empty_latent_height")
+        if width is not None and height is not None:
+            if SIZE not in metadata:
+                metadata[SIZE] = {}
+            metadata[SIZE][node_id] = {
+                "width": int(width),
+                "height": int(height),
+                "node_id": node_id
+            }
+
+    @staticmethod
+    def update(node_id, outputs, metadata):
+        # outputs: [(pipe_dict, model, vae), ...]
+        if not outputs or not isinstance(outputs, list) or len(outputs) == 0:
+            return
+        first_output = outputs[0]
+        if not isinstance(first_output, tuple) or len(first_output) < 1:
+            return
+        pipe = first_output[0]
+        if not isinstance(pipe, dict):
+            return
+
+        positive_conditioning = pipe.get("positive")
+        negative_conditioning = pipe.get("negative")
+
+        if positive_conditioning is not None or negative_conditioning is not None:
+            if node_id not in metadata[PROMPTS]:
+                metadata[PROMPTS][node_id] = {"node_id": node_id}
+            if positive_conditioning is not None:
+                metadata[PROMPTS][node_id]["positive_encoded"] = positive_conditioning
+            if negative_conditioning is not None:
+                metadata[PROMPTS][node_id]["negative_encoded"] = negative_conditioning
+
+
+class EasyPreSamplingExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs:
+            return
+
+        sampling_params = {}
+        for key in ("steps", "cfg", "sampler_name", "scheduler", "denoise", "seed"):
+            if key in inputs:
+                sampling_params[key] = inputs[key]
+
+        metadata[SAMPLING][node_id] = {
+            "parameters": sampling_params,
+            "node_id": node_id,
+            IS_SAMPLER: True
+        }
+
+
+class EasySeedExtractor(NodeMetadataExtractor):
+    @staticmethod
+    def extract(node_id, inputs, outputs, metadata):
+        if not inputs or "seed" not in inputs:
+            return
+
+        metadata[SAMPLING][node_id] = {
+            "parameters": {"seed": inputs["seed"]},
+            "node_id": node_id,
+            IS_SAMPLER: False
+        }
+
+
 class CLIPTextEncodeExtractor(NodeMetadataExtractor):
     @staticmethod
     def extract(node_id, inputs, outputs, metadata):
@@ -1013,9 +1125,12 @@ NODE_EXTRACTORS = {
     "KSamplerSelect": KSamplerSelectExtractor,  # Add KSamplerSelect
     "BasicScheduler": BasicSchedulerExtractor,  # Add BasicScheduler
     "AlignYourStepsScheduler": BasicSchedulerExtractor,  # Add AlignYourStepsScheduler
+    # ComfyUI-Easy-Use pre-sampling / seed
+    "samplerSettings": EasyPreSamplingExtractor,  # easy preSampling
+    "easySeed": EasySeedExtractor,  # easy seed
     # Loaders
     "CheckpointLoaderSimple": CheckpointLoaderExtractor,
-    "comfyLoader": CheckpointLoaderExtractor,  # easy comfyLoader
+    "comfyLoader": EasyComfyLoaderExtractor,  # ComfyUI-Easy-Use easy comfyLoader
     "CheckpointLoaderSimpleWithImages": CheckpointLoaderExtractor,  # CheckpointLoader|pysssss
     "TSC_EfficientLoader": TSCCheckpointLoaderExtractor,  # Efficient Nodes
     "NunchakuFluxDiTLoader": NunchakuFluxDiTLoaderExtractor,  # ComfyUI-Nunchaku

py/nodes/wanvideo_lora_select.py

@@ -1,10 +1,22 @@
-import folder_paths # type: ignore
+import os
-from ..utils.utils import get_lora_info
+from ..utils.utils import get_lora_info_absolute
+from ..config import config
 from .utils import FlexibleOptionalInputType, any_type, get_loras_list
 import logging
 
 logger = logging.getLogger(__name__)
 
+
+def _relpath_within_loras(abs_path):
+    """Return abs_path relative to the first matching lora root, or basename as fallback."""
+    all_roots = list(config.loras_roots or []) + list(config.extra_loras_roots or [])
+    for root in all_roots:
+        try:
+            return os.path.relpath(abs_path, root)
+        except ValueError:
+            continue
+    return os.path.basename(abs_path)
+
 class WanVideoLoraSelectLM:
     NAME = "WanVideo Lora Select (LoraManager)"
     CATEGORY = "Lora Manager/stackers"
@@ -56,13 +68,13 @@ class WanVideoLoraSelectLM:
             clip_strength = float(lora.get('clipStrength', model_strength))
             
             # Get lora path and trigger words
-            lora_path, trigger_words = get_lora_info(lora_name)
+            lora_path, trigger_words = get_lora_info_absolute(lora_name)
             
             # Create lora item for WanVideo format
             lora_item = {
-                "path": folder_paths.get_full_path("loras", lora_path),
+                "path": lora_path,
                 "strength": model_strength,
-                "name": lora_path.split(".")[0],
+                "name": os.path.splitext(_relpath_within_loras(lora_path))[0],
                 "blocks": selected_blocks,
                 "layer_filter": layer_filter,
                 "low_mem_load": low_mem_load,

py/nodes/wanvideo_lora_select_from_text.py

@@ -1,11 +1,23 @@
-import folder_paths # type: ignore
+import os
-from ..utils.utils import get_lora_info
+from ..utils.utils import get_lora_info_absolute
+from ..config import config
 from .utils import any_type 
 import logging
 
 # 初始化日志记录器
 logger = logging.getLogger(__name__)
 
+
+def _relpath_within_loras(abs_path):
+    """Return abs_path relative to the first matching lora root, or basename as fallback."""
+    all_roots = list(config.loras_roots or []) + list(config.extra_loras_roots or [])
+    for root in all_roots:
+        try:
+            return os.path.relpath(abs_path, root)
+        except ValueError:
+            continue
+    return os.path.basename(abs_path)
+
 # 定义新节点的类
 class WanVideoLoraTextSelectLM:
     # 节点在UI中显示的名称
@@ -87,12 +99,12 @@ class WanVideoLoraTextSelectLM:
             else:
                 continue
 
-            lora_path, trigger_words = get_lora_info(lora_name_raw)
+            lora_path, trigger_words = get_lora_info_absolute(lora_name_raw)
 
             lora_item = {
-                "path": folder_paths.get_full_path("loras", lora_path),
+                "path": lora_path,
                 "strength": model_strength,
-                "name": lora_path.split(".")[0],
+                "name": os.path.splitext(_relpath_within_loras(lora_path))[0],
                 "blocks": selected_blocks,
                 "layer_filter": layer_filter,
                 "low_mem_load": low_mem_load,

py/routes/handlers/misc_handlers.py

@@ -33,6 +33,7 @@ from ...services.metadata_service import (
     update_metadata_providers,
 )
 from ...services.service_registry import ServiceRegistry
+from ...services.model_lifecycle_service import delete_model_artifacts
 from ...services.settings_manager import get_settings_manager
 from ...services.websocket_manager import ws_manager
 from ...services.downloader import get_downloader
@@ -1791,15 +1792,19 @@ class ModelLibraryHandler:
                     exists = True
                     model_type = "embedding"
 
+                if exists:
+                    return web.json_response(
+                        {
+                            "success": True,
+                            "exists": True,
+                            "modelType": model_type,
+                            "hasBeenDownloaded": False,
+                        }
+                    )
+
                 history_service = await self._get_download_history_service()
                 has_been_downloaded = False
-                history_type = model_type
+                history_type = None
-                if history_type:
-                    has_been_downloaded = await history_service.has_been_downloaded(
-                        history_type,
-                        model_version_id,
-                    )
-                else:
                 for candidate_type in ("lora", "checkpoint", "embedding"):
                     if await history_service.has_been_downloaded(
                         candidate_type,
@@ -1812,8 +1817,8 @@ class ModelLibraryHandler:
                 return web.json_response(
                     {
                         "success": True,
-                        "exists": exists,
+                        "exists": False,
-                        "modelType": model_type if exists else history_type,
+                        "modelType": history_type,
                         "hasBeenDownloaded": has_been_downloaded,
                     }
                 )
@@ -1833,29 +1838,35 @@ class ModelLibraryHandler:
             model_type = None
             versions = []
             downloaded_version_ids = []
-            history_service = await self._get_download_history_service()
             if lora_versions:
-                model_type = "lora"
+                return web.json_response(
-                versions = self._with_downloaded_flag(lora_versions)
+                    {
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
+                        "success": True,
-                    model_type,
+                        "modelType": "lora",
-                    model_id,
+                        "versions": self._with_downloaded_flag(lora_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            elif checkpoint_versions:
+            if checkpoint_versions:
-                model_type = "checkpoint"
+                return web.json_response(
-                versions = self._with_downloaded_flag(checkpoint_versions)
+                    {
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
+                        "success": True,
-                    model_type,
+                        "modelType": "checkpoint",
-                    model_id,
+                        "versions": self._with_downloaded_flag(checkpoint_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            elif embedding_versions:
+            if embedding_versions:
-                model_type = "embedding"
+                return web.json_response(
-                versions = self._with_downloaded_flag(embedding_versions)
+                    {
-                downloaded_version_ids = await history_service.get_downloaded_version_ids(
+                        "success": True,
-                    model_type,
+                        "modelType": "embedding",
-                    model_id,
+                        "versions": self._with_downloaded_flag(embedding_versions),
+                        "downloadedVersionIds": [],
+                    }
                 )
-            else:
+
+            history_service = await self._get_download_history_service()
             for candidate_type in ("lora", "checkpoint", "embedding"):
                 candidate_downloaded_version_ids = (
                     await history_service.get_downloaded_version_ids(
@@ -1880,6 +1891,86 @@ class ModelLibraryHandler:
             logger.error("Failed to check model existence: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    async def check_models_exist(self, request: web.Request) -> web.Response:
+        try:
+            model_ids_raw = request.query.get("modelIds", "")
+            if not model_ids_raw:
+                return web.json_response(
+                    {"success": True, "results": []}
+                )
+
+            raw_ids = model_ids_raw.split(",")
+            seen: set[int] = set()
+            model_ids: list[int] = []
+            for raw in raw_ids:
+                stripped = raw.strip()
+                if not stripped:
+                    continue
+                try:
+                    mid = int(stripped)
+                except ValueError:
+                    continue
+                if mid not in seen:
+                    seen.add(mid)
+                    model_ids.append(mid)
+
+            if not model_ids:
+                return web.json_response(
+                    {"success": True, "results": []}
+                )
+
+            lora_scanner = await self._service_registry.get_lora_scanner()
+            checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
+            embedding_scanner = await self._service_registry.get_embedding_scanner()
+
+            results: list[dict] = []
+            for model_id in model_ids:
+                lora_versions = await lora_scanner.get_model_versions_by_id(model_id)
+                if lora_versions:
+                    results.append({
+                        "modelId": model_id,
+                        "modelType": "lora",
+                        "versions": self._with_downloaded_flag(lora_versions),
+                        "downloadedVersionIds": [],
+                    })
+                    continue
+
+                if checkpoint_scanner:
+                    checkpoint_versions = await checkpoint_scanner.get_model_versions_by_id(model_id)
+                    if checkpoint_versions:
+                        results.append({
+                            "modelId": model_id,
+                            "modelType": "checkpoint",
+                            "versions": self._with_downloaded_flag(checkpoint_versions),
+                            "downloadedVersionIds": [],
+                        })
+                        continue
+
+                if embedding_scanner:
+                    embedding_versions = await embedding_scanner.get_model_versions_by_id(model_id)
+                    if embedding_versions:
+                        results.append({
+                            "modelId": model_id,
+                            "modelType": "embedding",
+                            "versions": self._with_downloaded_flag(embedding_versions),
+                            "downloadedVersionIds": [],
+                        })
+                        continue
+
+                results.append({
+                    "modelId": model_id,
+                    "modelType": None,
+                    "versions": [],
+                    "downloadedVersionIds": [],
+                })
+
+            return web.json_response(
+                {"success": True, "results": results}
+            )
+        except Exception as exc:
+            logger.error("Failed to check models existence: %s", exc, exc_info=True)
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def get_model_version_download_status(
         self, request: web.Request
     ) -> web.Response:
@@ -1992,6 +2083,78 @@ class ModelLibraryHandler:
             )
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    async def delete_model_version(self, request: web.Request) -> web.Response:
+        try:
+            model_version_id_str = request.query.get("modelVersionId")
+            if not model_version_id_str:
+                return web.json_response(
+                    {"success": False, "error": "Missing required parameter: modelVersionId"},
+                    status=400,
+                )
+            try:
+                model_version_id = int(model_version_id_str)
+            except ValueError:
+                return web.json_response(
+                    {"success": False, "error": "Parameter modelVersionId must be an integer"},
+                    status=400,
+                )
+
+            lora_scanner = await self._service_registry.get_lora_scanner()
+            checkpoint_scanner = await self._service_registry.get_checkpoint_scanner()
+            embedding_scanner = await self._service_registry.get_embedding_scanner()
+
+            found_type = None
+            file_path = None
+            found_cache = None
+
+            for model_type, scanner in (
+                ("lora", lora_scanner),
+                ("checkpoint", checkpoint_scanner),
+                ("embedding", embedding_scanner),
+            ):
+                cache = await scanner.get_cached_data()
+                if cache and model_version_id in cache.version_index:
+                    found_type = model_type
+                    found_cache = cache
+                    entry = cache.version_index[model_version_id]
+                    file_path = entry.get("file_path")
+                    break
+
+            if not file_path:
+                return web.json_response(
+                    {"success": False, "error": "Model version not found in any scanner cache"},
+                    status=404,
+                )
+
+            target_dir = os.path.dirname(file_path)
+            base_name = os.path.basename(file_path)
+            file_name, extension = os.path.splitext(base_name)
+            await delete_model_artifacts(target_dir, file_name, main_extension=extension)
+
+            if found_cache:
+                found_cache.raw_data = [
+                    item
+                    for item in found_cache.raw_data
+                    if item.get("file_path") != file_path
+                ]
+                await found_cache.resort()
+
+            history_service = await self._get_download_history_service()
+            await history_service.mark_not_downloaded(found_type, model_version_id)
+
+            return web.json_response(
+                {
+                    "success": True,
+                    "modelType": found_type,
+                    "modelVersionId": model_version_id,
+                }
+            )
+        except Exception as exc:
+            logger.error(
+                "Failed to delete model version: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def get_model_versions_status(self, request: web.Request) -> web.Response:
         try:
             model_id_str = request.query.get("modelId")
@@ -3025,8 +3188,10 @@ class MiscHandlerSet:
             "update_node_widget": self.node_registry.update_node_widget,
             "get_registry": self.node_registry.get_registry,
             "check_model_exists": self.model_library.check_model_exists,
+            "check_models_exist": self.model_library.check_models_exist,
             "get_model_version_download_status": self.model_library.get_model_version_download_status,
             "set_model_version_download_status": self.model_library.set_model_version_download_status,
+            "delete_model_version": self.model_library.delete_model_version,
             "get_civitai_user_models": self.model_library.get_civitai_user_models,
             "download_metadata_archive": self.metadata_archive.download_metadata_archive,
             "remove_metadata_archive": self.metadata_archive.remove_metadata_archive,

py/routes/misc_route_registrar.py

@@ -43,6 +43,7 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("POST", "/api/lm/update-node-widget", "update_node_widget"),
     RouteDefinition("GET", "/api/lm/get-registry", "get_registry"),
     RouteDefinition("GET", "/api/lm/check-model-exists", "check_model_exists"),
+    RouteDefinition("GET", "/api/lm/check-models-exist", "check_models_exist"),
     RouteDefinition(
         "GET",
         "/api/lm/model-version-download-status",
@@ -90,6 +91,9 @@ MISC_ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition(
         "GET", "/api/lm/base-models/cache-status", "get_base_model_cache_status"
     ),
+    RouteDefinition(
+        "GET", "/api/lm/delete-model-version", "delete_model_version"
+    ),
 )
 
 

py/services/civitai_base_model_service.py

@@ -193,6 +193,9 @@ class CivitaiBaseModelService:
             "zimageturbo": "ZIT",
             "zimagebase": "ZIB",
             "anima": "ANI",
+            "ernie": "ERNI",
+            "ernie turbo": "ETRB",
+            "nucleus": "NUCL",
             "svd": "SVD",
             "ltxv": "LTXV",
             "ltxv2": "LTV2",
@@ -418,6 +421,9 @@ class CivitaiBaseModelService:
                 "Kolors",
                 "NoobAI",
                 "Anima",
+                "Ernie",
+                "Ernie Turbo",
+                "Nucleus",
             ],
         }
 

py/services/civitai_client.py

@@ -577,6 +577,59 @@ class CivitaiClient:
             logger.error(error_msg)
             return None
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        """Fetch full version details for up to 100 SHA256 hashes via the batch endpoint.
+
+        Uses POST /api/v1/model-versions/by-hash which returns full version
+        details including ``usageControl`` and ``earlyAccessEndsAt`` that are
+        not available from the model-level API.
+
+        Args:
+            hashes: List of SHA256 hashes (max 100 per batch; auto-split).
+
+        Returns:
+            List of version dicts or None on failure.
+        """
+        if not hashes:
+            return []
+
+        BATCH_SIZE = 100
+        all_versions: List[Dict] = []
+
+        for start in range(0, len(hashes), BATCH_SIZE):
+            batch = hashes[start : start + BATCH_SIZE]
+            try:
+                success, result = await self._make_request(
+                    "POST",
+                    f"{self.base_url}/model-versions/by-hash",
+                    use_auth=True,
+                    json=batch,
+                )
+                if not success:
+                    logger.warning(
+                        "Batch by-hash request failed for %d hashes: %s",
+                        len(batch),
+                        result,
+                    )
+                    continue
+
+                if isinstance(result, list):
+                    all_versions.extend(result)
+                else:
+                    logger.debug(
+                        "Unexpected by-hash response type: %s", type(result)
+                    )
+            except RateLimitError:
+                raise
+            except Exception as exc:  # pragma: no cover - defensive logging
+                logger.error(
+                    "Error fetching model versions by hashes: %s", exc
+                )
+
+        return all_versions if all_versions else None
+
     async def get_user_models(self, username: str) -> Optional[List[Dict]]:
         """Fetch all models for a specific Civitai user."""
         if not username:

py/services/downloaded_version_history_service.py

@@ -64,6 +64,7 @@ class DownloadedVersionHistoryService:
         self._db_path = db_path or _resolve_database_path()
         self._settings = settings_manager or get_settings_manager()
         self._lock = asyncio.Lock()
+        self._conn: sqlite3.Connection | None = None
         self._schema_initialized = False
         self._ensure_directory()
         self._initialize_schema()
@@ -78,6 +79,12 @@ class DownloadedVersionHistoryService:
         conn.row_factory = sqlite3.Row
         return conn
 
+    def _get_conn(self) -> sqlite3.Connection:
+        if self._conn is None:
+            self._conn = sqlite3.connect(self._db_path, check_same_thread=False)
+            self._conn.row_factory = sqlite3.Row
+        return self._conn
+
     def _initialize_schema(self) -> None:
         if self._schema_initialized:
             return
@@ -116,7 +123,7 @@ class DownloadedVersionHistoryService:
         timestamp = time.time()
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             conn.execute(
                 """
                 INSERT INTO downloaded_model_versions (
@@ -180,7 +187,7 @@ class DownloadedVersionHistoryService:
             return
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             conn.executemany(
                 """
                 INSERT INTO downloaded_model_versions (
@@ -208,7 +215,7 @@ class DownloadedVersionHistoryService:
         timestamp = time.time()
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             conn.execute(
                 """
                 INSERT INTO downloaded_model_versions (
@@ -238,7 +245,7 @@ class DownloadedVersionHistoryService:
             return False
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             row = conn.execute(
                 """
                 SELECT is_deleted_override
@@ -258,7 +265,7 @@ class DownloadedVersionHistoryService:
             return []
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             rows = conn.execute(
                 """
                 SELECT version_id
@@ -291,7 +298,7 @@ class DownloadedVersionHistoryService:
         params: list[object] = [normalized_type, *normalized_model_ids]
 
         async with self._lock:
-            with self._connect() as conn:
+            conn = self._get_conn()
             rows = conn.execute(
                 f"""
                 SELECT model_id, version_id

py/services/model_metadata_provider.py

@@ -109,6 +109,18 @@ class ModelMetadataProvider(ABC):
         """Fetch model versions for multiple model ids when supported."""
         raise NotImplementedError
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        """Fetch full version details for multiple SHA256 hashes.
+
+        Used specifically to retrieve ``usageControl`` which is only
+        available from the per-version / by-hash API, not from model-level
+        responses.  Providers that cannot resolve hashes should let the
+        default ``NotImplementedError`` propagate.
+        """
+        raise NotImplementedError
+        
     @abstractmethod
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
         """Get specific model version with additional metadata"""
@@ -141,6 +153,11 @@ class CivitaiModelMetadataProvider(ModelMetadataProvider):
     ) -> Optional[Dict[int, Dict]]:
         return await self.client.get_model_versions_bulk(model_ids)
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        return await self.client.get_model_versions_by_hashes(hashes)
+        
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
         return await self.client.get_model_version(model_id, version_id)
         
@@ -519,6 +536,32 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 continue
         return None, "No provider could retrieve the data"
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        for provider, label in self._iter_providers():
+            try:
+                result = await self._call_with_rate_limit(
+                    label,
+                    provider.get_model_versions_by_hashes,
+                    hashes,
+                )
+                if result is not None:
+                    return result
+            except NotImplementedError:
+                continue
+            except RateLimitError as exc:
+                exc.provider = exc.provider or label
+                raise exc
+            except Exception as e:
+                logger.debug(
+                    "Provider %s failed for get_model_versions_by_hashes: %s",
+                    label,
+                    e,
+                )
+                continue
+        return None
+
     async def get_user_models(self, username: str) -> Optional[List[Dict]]:
         for provider, label in self._iter_providers():
             try:
@@ -593,6 +636,15 @@ class RateLimitRetryingProvider(ModelMetadataProvider):
             model_ids,
         )
 
+    async def get_model_versions_by_hashes(
+        self, hashes: List[str]
+    ) -> Optional[List[Dict]]:
+        return await self._rate_limit_helper.run(
+            self._label,
+            self._provider.get_model_versions_by_hashes,
+            hashes,
+        )
+
     async def get_model_version(self, model_id: int = None, version_id: int = None) -> Optional[Dict]:
         return await self._rate_limit_helper.run(
             self._label,
@@ -669,6 +721,17 @@ class ModelMetadataProviderManager:
         provider = self._get_provider(provider_name)
         return await provider.get_model_version_info(version_id)
 
+    async def get_model_versions_by_hashes(
+        self,
+        hashes: List[str],
+        provider_name: str = None,
+    ) -> Optional[List[Dict]]:
+        provider = self._get_provider(provider_name)
+        try:
+            return await provider.get_model_versions_by_hashes(hashes)
+        except NotImplementedError:
+            return None
+
     async def get_user_models(self, username: str, provider_name: str = None) -> Optional[List[Dict]]:
         """Fetch models owned by the specified user"""
         provider = self._get_provider(provider_name)

py/services/model_update_service.py

@@ -989,6 +989,11 @@ class ModelUpdateService:
                 fallback_attempted = True
                 try:
                     response = await metadata_provider.get_model_versions(model_id)
+                    if response is not None:
+                        await self._enrich_version_entries(
+                            metadata_provider,
+                            {model_id: response},
+                        )
                 except RateLimitError:
                     raise
                 except ResourceNotFoundError as exc:
@@ -1083,6 +1088,136 @@ class ModelUpdateService:
             self._upsert_record(record)
             return record
 
+    async def _enrich_version_entries(
+        self,
+        metadata_provider,
+        responses_by_model_id: Dict[int, Mapping],
+    ) -> None:
+        """Enrich version entries with ``usageControl`` via batch hash endpoint.
+
+        The model-level API does not include ``usageControl`` on version
+        entries. This method collects SHA256 hashes from every version's
+        primary model file, calls ``POST /api/v1/model-versions/by-hash``
+        (up to 100 hashes per request), and injects ``usageControl`` +
+        ``earlyAccessEndsAt`` into each version entry dict in-place.
+        """
+        if not metadata_provider or not responses_by_model_id:
+            return
+
+        hashes_by_version: Dict[int, str] = {}
+        for response in responses_by_model_id.values():
+            hashes_by_version.update(
+                self._collect_hashes_from_response(response)
+            )
+
+        if not hashes_by_version:
+            return
+
+        version_ids_by_hash: Dict[str, List[int]] = {}
+        for version_id, sha256 in hashes_by_version.items():
+            version_ids_by_hash.setdefault(sha256, []).append(version_id)
+
+        all_hashes = list(version_ids_by_hash.keys())
+        BATCH_SIZE = 100
+
+        enrichment: Dict[int, Dict] = {}
+        try:
+            for start in range(0, len(all_hashes), BATCH_SIZE):
+                batch = all_hashes[start : start + BATCH_SIZE]
+                try:
+                    enriched = await metadata_provider.get_model_versions_by_hashes(
+                        batch
+                    )
+                except NotImplementedError:
+                    return
+                except RateLimitError:
+                    raise
+                except Exception:
+                    continue
+
+                if not enriched:
+                    continue
+
+                for entry in enriched:
+                    if not isinstance(entry, dict):
+                        continue
+                    version_id = entry.get("id")
+                    if version_id is None:
+                        continue
+                    enrichment[version_id] = {
+                        "usageControl": _normalize_string(
+                            entry.get("usageControl")
+                        ),
+                        "earlyAccessEndsAt": _normalize_string(
+                            entry.get("earlyAccessEndsAt")
+                        ),
+                    }
+        except RateLimitError:
+            raise
+
+        if not enrichment:
+            return
+
+        for response in responses_by_model_id.values():
+            versions = response.get("modelVersions")
+            if not isinstance(versions, list):
+                continue
+            for version in versions:
+                if not isinstance(version, dict):
+                    continue
+                version_id = version.get("id")
+                if version_id not in enrichment:
+                    continue
+                extra = enrichment[version_id]
+                if extra.get("usageControl") and not version.get("usageControl"):
+                    version["usageControl"] = extra["usageControl"]
+                if extra.get("earlyAccessEndsAt") and not version.get(
+                    "earlyAccessEndsAt"
+                ):
+                    version["earlyAccessEndsAt"] = extra["earlyAccessEndsAt"]
+
+    @staticmethod
+    def _collect_hashes_from_response(response: Mapping) -> Dict[int, str]:
+        """Extract ``{version_id: sha256}`` from a model-level API response.
+
+        Returns an empty dict if the response structure is unexpected.
+        """
+        result: Dict[int, str] = {}
+        versions = response.get("modelVersions")
+        if not isinstance(versions, list):
+            return result
+        for entry in versions:
+            if not isinstance(entry, dict):
+                continue
+            version_id = _normalize_int(entry.get("id"))
+            if version_id is None:
+                continue
+            sha256 = ModelUpdateService._extract_sha256_from_version_entry(entry)
+            if sha256:
+                result[version_id] = sha256
+        return result
+
+    @staticmethod
+    def _extract_sha256_from_version_entry(entry: Mapping) -> Optional[str]:
+        """Return the SHA256 hash from the primary model file of a version entry."""
+        files = entry.get("files")
+        if not isinstance(files, list):
+            return None
+        for file_info in files:
+            if not isinstance(file_info, dict):
+                continue
+            if file_info.get("type") != "Model":
+                continue
+            primary = file_info.get("primary")
+            if primary is not True and str(primary).strip().lower() != "true":
+                continue
+            hashes = file_info.get("hashes")
+            if isinstance(hashes, dict):
+                sha256 = hashes.get("SHA256")
+                if sha256:
+                    return sha256
+        return None
+
     async def _fetch_model_versions_bulk(
         self,
         metadata_provider,
@@ -1134,6 +1269,7 @@ class ModelUpdateService:
             len(aggregated),
             provider_name,
         )
+        await self._enrich_version_entries(metadata_provider, aggregated)
         return aggregated
 
     async def _collect_local_versions(
@@ -1261,6 +1397,7 @@ class ModelUpdateService:
                     sort_index=sort_map.get(version_id, index),
                     early_access_ends_at=remote_version.early_access_ends_at,
                     is_early_access=remote_version.is_early_access,
+                    usage_control=remote_version.usage_control,
                 )
             )
 

py/utils/constants.py

@@ -178,5 +178,8 @@ SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS = frozenset(
         "Wan Video 2.5 I2V",
         "Hunyuan Video",
         "Anima",
+        "Ernie",
+        "Ernie Turbo",
+        "Nucleus",
     ]
 )

static/css/components/batch-import-modal.css

@@ -87,7 +87,7 @@
 
 .checkbox-label input[type="checkbox"]:checked + .checkmark::after {
     content: '\f00c';
-    font-family: 'Font Awesome 6 Free';
+    font-family: 'Font Awesome 6 Free', sans-serif;
     font-weight: 900;
     color: var(--lora-text);
     font-size: 12px;

static/css/components/card.css

@@ -329,7 +329,6 @@
 }
 
 .card-actions i {
-    margin-left: var(--space-1);
     cursor: pointer;
     color: white;
     transition: opacity 0.2s, transform 0.15s ease;

static/css/components/header.css

@@ -141,8 +141,7 @@
 
 .header-search .search-container:focus-within {
   border-color: var(--lora-accent);
-  box-shadow: 0 4px 16px rgba(0, 0, 0, 0.12), 0 0 0 1px var(--lora-accent);
+  box-shadow: 0 2px 8px rgba(0, 0, 0, 0.08), 0 0 0 1px var(--lora-accent);
-  transform: translateY(-1px);
 }
 
 .header-search input {

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

@@ -387,6 +387,10 @@
     cursor: not-allowed;
 }
 
+.version-action-disabled-wrapper {
+    display: inline-flex;
+}
+
 .versions-loading-state,
 .versions-empty,
 .versions-error {

static/css/components/shared.css

@@ -67,7 +67,6 @@
 
 .early-access-info {
     display: none;
-    position: absolute;
     top: 100%;
     right: 0;
     background: var(--card-bg);
@@ -97,7 +96,6 @@
 
 .local-path {
     display: none;
-    position: absolute;
     top: 100%;
     right: 0;
     background: var(--card-bg);

static/css/layout.css

@@ -371,6 +371,14 @@
     display: block;
 }
 
+/* Elevate the controls stacking context above breadcrumb nav when a dropdown is open,
+   so the dropdown menu isn't obscured. Only active when dropdown is shown to avoid
+   the entire controls bar (which can wrap to 2 rows on narrow viewports) covering
+   the sticky breadcrumb. */
+.controls:has(.dropdown-group.active) {
+    z-index: var(--z-header);
+}
+
 .dropdown-item {
     display: block;
     padding: 6px 15px;

static/js/components/ContextMenu/BulkContextMenu.js

@@ -74,6 +74,34 @@ export class BulkContextMenu extends BaseContextMenu {
         if (setContentRatingItem) {
             setContentRatingItem.style.display = config.setContentRating ? 'flex' : 'none';
         }
+
+        const setFavoriteItem = this.menu.querySelector('[data-action="set-favorite"]');
+
+        if (setFavoriteItem && config.setFavorite) {
+            setFavoriteItem.style.display = 'flex';
+
+            const total = state.selectedModels.size;
+            const favoritedCount = this.countFavoritedInSelection();
+            const allFavorited = total > 0 && favoritedCount === total;
+
+            const icon = setFavoriteItem.querySelector('i');
+            const label = setFavoriteItem.querySelector('span');
+
+            if (allFavorited) {
+                if (icon) { icon.className = 'far fa-star'; }
+                if (label) { label.textContent = translate('loras.bulkOperations.unfavorite'); }
+            } else {
+                if (icon) { icon.className = 'fas fa-star'; }
+                if (label) {
+                    label.textContent = favoritedCount > 0
+                        ? translate('loras.bulkOperations.setFavoriteCount', { favorited: favoritedCount, total })
+                        : translate('loras.bulkOperations.setFavorite');
+                }
+            }
+        } else if (setFavoriteItem) {
+            setFavoriteItem.style.display = 'none';
+        }
+
         if (downloadMissingLorasItem) {
             // Only show for recipes page
             downloadMissingLorasItem.style.display = currentModelType === 'recipes' ? 'flex' : 'none';
@@ -138,6 +166,20 @@ export class BulkContextMenu extends BaseContextMenu {
         return count;
     }
 
+    countFavoritedInSelection() {
+        let count = 0;
+        for (const filePath of state.selectedModels) {
+            const escapedPath = window.CSS && typeof window.CSS.escape === 'function'
+                ? window.CSS.escape(filePath)
+                : filePath.replace(/["\\]/g, '\\$&');
+            const card = document.querySelector(`.model-card[data-filepath="${escapedPath}"]`);
+            if (card && card.dataset.favorite === 'true') {
+                count++;
+            }
+        }
+        return count;
+    }
+
     showMenu(x, y, card) {
         this.updateMenuItemsForModelType();
         this.updateSelectedCountHeader();
@@ -185,6 +227,11 @@ export class BulkContextMenu extends BaseContextMenu {
             case 'delete-all':
                 bulkManager.showBulkDeleteModal();
                 break;
+            case 'set-favorite': {
+                const allFavorited = this.countFavoritedInSelection() === state.selectedModels.size;
+                bulkManager.setBulkFavorites(!allFavorited);
+                break;
+            }
             case 'download-missing-loras':
                 this.handleDownloadMissingLoras();
                 break;

static/js/components/shared/ModelVersionsTab.js

@@ -241,7 +241,7 @@ function buildActionButton(label, variant, action, options = {}) {
     if (action) {
         attributes.push(`data-version-action="${escapeHtml(action)}"`);
     }
-    if (options.title) {
+    if (!options.disabled && options.title) {
         attributes.push(`title="${escapeHtml(options.title)}"`);
         attributes.push(`aria-label="${escapeHtml(options.title)}"`);
     }
@@ -251,7 +251,11 @@ function buildActionButton(label, variant, action, options = {}) {
     if (options.extraAttributes) {
         attributes.push(options.extraAttributes);
     }
-    return `<button ${attributes.join(' ')}>${options.iconMarkup || ''}${escapeHtml(label)}</button>`;
+    const buttonHtml = `<button ${attributes.join(' ')}>${options.iconMarkup || ''}${escapeHtml(label)}</button>`;
+    if (options.disabled && options.title) {
+        return `<span class="version-action-disabled-wrapper" title="${escapeHtml(options.title)}" aria-label="${escapeHtml(options.title)}">${buttonHtml}</span>`;
+    }
+    return buttonHtml;
 }
 
 const DISPLAY_FILTER_MODES = Object.freeze({

static/js/managers/BulkManager.js

@@ -3,7 +3,7 @@ import { showToast, copyToClipboard, sendLoraToWorkflow, buildLoraSyntax, getNSF
 import { updateCardsForBulkMode } from '../components/shared/ModelCard.js';
 import { modalManager } from './ModalManager.js';
 import { getModelApiClient, resetAndReload } from '../api/modelApiFactory.js';
-import { RecipeSidebarApiClient } from '../api/recipeApi.js';
+import { RecipeSidebarApiClient, updateRecipeMetadata } from '../api/recipeApi.js';
 import { MODEL_TYPES, MODEL_CONFIG } from '../api/apiConfig.js';
 import { BASE_MODEL_CATEGORIES } from '../utils/constants.js';
 import { getPriorityTagSuggestions } from '../utils/priorityTagHelpers.js';
@@ -41,7 +41,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: true,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             [MODEL_TYPES.EMBEDDING]: {
                 addTags: true,
@@ -53,7 +55,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: false,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             [MODEL_TYPES.CHECKPOINT]: {
                 addTags: true,
@@ -65,7 +69,9 @@ export class BulkManager {
                 autoOrganize: true,
                 deleteAll: true,
                 setContentRating: true,
-                skipMetadataRefresh: true
+                skipMetadataRefresh: true,
+                setFavorite: true,
+                unfavorite: true
             },
             recipes: {
                 addTags: false,
@@ -77,7 +83,9 @@ export class BulkManager {
                 autoOrganize: false,
                 deleteAll: true,
                 setContentRating: false,
-                skipMetadataRefresh: false
+                skipMetadataRefresh: false,
+                setFavorite: true,
+                unfavorite: true
             }
         };
 
@@ -1090,6 +1098,60 @@ export class BulkManager {
         }
     }
 
+    async setBulkFavorites(value) {
+        if (state.selectedModels.size === 0) {
+            showToast('toast.models.noModelsSelected', {}, 'warning');
+            return;
+        }
+
+        const totalCount = state.selectedModels.size;
+        const isRecipesPage = state.currentPageType === 'recipes';
+
+        state.loadingManager.showSimpleLoading(
+            translate(value ? 'toast.models.bulkFavoriteUpdating' : 'toast.models.bulkUnfavoriteUpdating', { count: totalCount })
+        );
+        let cancelled = false;
+        state.loadingManager.showCancelButton(() => {
+            cancelled = true;
+        });
+
+        let successCount = 0;
+        let failureCount = 0;
+
+        try {
+            for (const filePath of state.selectedModels) {
+                if (cancelled) {
+                    showToast('toast.api.operationCancelled', {}, 'info');
+                    break;
+                }
+                try {
+                    if (isRecipesPage) {
+                        await updateRecipeMetadata(filePath, { favorite: value });
+                    } else {
+                        const apiClient = getModelApiClient();
+                        await apiClient.saveModelMetadata(filePath, { favorite: value });
+                    }
+                    successCount++;
+                } catch (error) {
+                    failureCount++;
+                    console.error(`Failed to set favorite=${value} for ${filePath}:`, error);
+                }
+            }
+        } finally {
+            state.loadingManager?.hide?.();
+        }
+
+        if (successCount === totalCount) {
+            const toastKey = value ? 'modelCard.favorites.added' : 'modelCard.favorites.removed';
+            showToast(toastKey, {}, 'success');
+        } else if (successCount > 0) {
+            const toastKey = value ? 'toast.models.bulkFavoritePartialAdded' : 'toast.models.bulkFavoritePartialRemoved';
+            showToast(toastKey, { success: successCount, failed: failureCount }, 'warning');
+        } else {
+            showToast('toast.models.bulkFavoriteFailed', {}, 'error');
+        }
+    }
+
     /**
      * Show bulk base model modal
      */

static/js/managers/FilterManager.js

@@ -599,7 +599,7 @@ export class FilterManager {
 
         // Call the appropriate manager's load method based on page type
         if (this.currentPage === 'recipes' && window.recipeManager) {
-            await window.recipeManager.loadRecipes(true);
+            await window.recipeManager.loadRecipes({ preserveScroll: true });
         } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints') {
             // For models page, reset the page and reload
             await getModelApiClient().loadMoreWithVirtualScroll(true, false);
@@ -682,7 +682,7 @@ export class FilterManager {
 
         // Reload data using the appropriate method for the current page
         if (this.currentPage === 'recipes' && window.recipeManager) {
-            await window.recipeManager.loadRecipes(true);
+            await window.recipeManager.loadRecipes({ preserveScroll: true });
         } else if (this.currentPage === 'loras' || this.currentPage === 'checkpoints' || this.currentPage === 'embeddings') {
             await getModelApiClient().loadMoreWithVirtualScroll(true, true);
         }

static/js/managers/SearchManager.js

@@ -301,7 +301,7 @@ export class SearchManager {
       
       // Call the appropriate manager's load method based on page type
       if (this.currentPage === 'recipes' && window.recipeManager) {
-        window.recipeManager.loadRecipes(true); // true to reset pagination
+        window.recipeManager.loadRecipes({ preserveScroll: true });
       } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints') {
         // For models page, reset the page and reload
         getModelApiClient().loadMoreWithVirtualScroll(true, false);

static/js/managers/SettingsManager.js

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

static/js/recipes.js

@@ -19,7 +19,7 @@ class RecipePageControls {
     }
 
     async resetAndReload() {
-        refreshVirtualScroll();
+        await refreshVirtualScroll({ preserveScroll: true });
     }
 
     async refreshModels(fullRebuild = false) {

static/js/utils/constants.js

@@ -66,6 +66,9 @@ export const BASE_MODELS = {
     HUNYUAN_VIDEO: "Hunyuan Video",
     // Other models
     ANIMA: "Anima",
+    ERNIE: "Ernie",
+    ERNIE_TURBO: "Ernie Turbo",
+    NUCLEUS: "Nucleus",
     PONY_V7: "Pony V7",
     // Default
     UNKNOWN: "Other"
@@ -191,6 +194,9 @@ export const BASE_MODEL_ABBREVIATIONS = {
     [BASE_MODELS.ZIMAGE_TURBO]: 'ZIT',
     [BASE_MODELS.ZIMAGE_BASE]: 'ZIB',
     [BASE_MODELS.ANIMA]: 'ANI',
+    [BASE_MODELS.ERNIE]: 'ERNI',
+    [BASE_MODELS.ERNIE_TURBO]: 'ETRB',
+    [BASE_MODELS.NUCLEUS]: 'NUCL',
 
     // Default
     [BASE_MODELS.UNKNOWN]: 'OTH'
@@ -394,6 +400,7 @@ export const BASE_MODEL_CATEGORIES = {
         BASE_MODELS.QWEN, BASE_MODELS.AURAFLOW, BASE_MODELS.CHROMA, BASE_MODELS.ZIMAGE_TURBO, BASE_MODELS.ZIMAGE_BASE,
         BASE_MODELS.PIXART_A, BASE_MODELS.PIXART_E, BASE_MODELS.HUNYUAN_1,
         BASE_MODELS.LUMINA, BASE_MODELS.KOLORS, BASE_MODELS.NOOBAI, BASE_MODELS.ANIMA,
+        BASE_MODELS.ERNIE, BASE_MODELS.ERNIE_TURBO, BASE_MODELS.NUCLEUS,
         BASE_MODELS.UNKNOWN
     ]
 };

templates/components/context_menu.html

@@ -77,6 +77,9 @@
     <div class="context-menu-item" data-action="set-base-model">
         <i class="fas fa-layer-group"></i> <span>{{ t('loras.bulkOperations.setBaseModel') }}</span>
     </div>
+    <div class="context-menu-item" data-action="set-favorite">
+        <i class="fas fa-star"></i> <span>{{ t('loras.bulkOperations.setFavorite') }}</span>
+    </div>
     <div class="context-menu-item" data-action="set-content-rating">
         <i class="fas fa-exclamation-triangle"></i> <span>{{ t('loras.bulkOperations.setContentRating') }}</span>
     </div>

tests/frontend/components/lorasWidgetEvents.interactions.test.js

@@ -114,7 +114,8 @@ describe('LoRA widget drag interactions', () => {
     dragEl.dispatchEvent(new PointerEvent('pointerup', { pointerId: 1 }));
     expect(document.body.classList.contains('lm-lora-strength-dragging')).toBe(false);
     expect(onDragEnd).toHaveBeenCalledTimes(1);
-    expect(renderSpy).toHaveBeenCalledWith(widget.value, widget);
+    // 454210a4 replaced renderFunction() with widget.value setter + widget.callback()
+    expect(widget.callback).toHaveBeenCalledWith(widget.value);
   });
 
   it('deletes the selected LoRA when backspace is pressed outside of strength inputs', async () => {

web/comfyui/loras_widget_events.js

@@ -232,9 +232,13 @@ export function initDrag(
         onDragEnd();
       }
 
-      // Now do the re-render after drag is complete
+      // Commit final value through options.setValue so external observers are notified.
-      if (renderFunction) {
+      // During drag, handleStrengthDrag mutates widgetValue in-place (updateWidget=false),
-        renderFunction(widget.value, widget);
+      // bypassing widget.value setter and options.setValue entirely. This assignment
+      // flushes the in-place mutation through the setter so any setValue wrappers fire.
+      widget.value = widget.value;
+      if (typeof widget.callback === 'function') {
+        widget.callback(widget.value);
       }
     }
   };
@@ -349,8 +353,12 @@ export function initHeaderDrag(headerEl, widget, renderFunction) {
     document.body.classList.remove('lm-lora-strength-dragging');
 
     // Only re-render if we actually dragged
-    if (wasDragging && renderFunction) {
+    if (wasDragging) {
-      renderFunction(widget.value, widget);
+      // Commit final value through options.setValue so external observers are notified.
+      widget.value = widget.value;
+      if (typeof widget.callback === 'function') {
+        widget.callback(widget.value);
+      }
     }
   };
 

web/comfyui/trigger_word_toggle.js

@@ -413,7 +413,7 @@ app.registerExtension({
           const savedItem = consumeQueuedState(itemState, itemText);
           return {
             text: itemText,
-            active: savedItem ? savedItem.active : defaultActive,
+            active: savedItem ? savedItem.active : true,
             highlighted: false,
             strength: null,
           };