chore(release): bump version to v1.0.11

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

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

.github/ISSUE_TEMPLATE/feature_request.md

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

data/supporters.json

@@ -7,9 +7,9 @@
   ],
   "allSupporters": [
     "Insomnia Art Designs",
+    "2018cfh",
     "megakirbs",
     "Brennok",
-    "2018cfh",
     "W+K+White",
     "wackop",
     "Phil",
@@ -17,55 +17,69 @@
     "Arlecchino Shion",
     "Charles Blakemore",
     "Rob Williams",
-    "$MetaSamsara",
     "stone9k",
+    "itismyelement",
+    "$MetaSamsara",
+    "onesecondinosaur",
     "Rosenthal",
     "Francisco Tatis",
+    "Tobi_Swagg",
+    "Andrew Wilson",
+    "Greybush",
+    "Ricky Carter",
+    "JongWon Han",
+    "VantAI",
     "runte3221",
+    "FreelancerZ",
+    "Edgar Tejeda",
     "Fraser Cross",
+    "Liam MacDougal",
     "Polymorphic Indeterminate",
     "Marc Whiffen",
     "Skalabananen",
     "Birdy",
     "Kiba",
     "Mozzel",
-    "itismyelement",
     "Gingko Biloba",
     "Reno Lam",
-    "onesecondinosaur",
     "sig",
     "Christian Byrne",
     "DM",
     "Sen314",
     "Estragon",
     "J\\B/ 8r0wns0n",
+    "Snaggwort",
     "Takkan",
+    "Matt+J",
     "ClockDaemon",
     "KD",
     "Omnidex",
+    "Tyler Trebuchon",
     "Release Cabrakan",
-    "Tobi_Swagg",
     "SG",
+    "carozzz",
     "James Dooley",
     "zenbound",
+    "Buzzard",
     "jmack",
-    "Andrew Wilson",
-    "Greybush",
+    "Adam Shaw",
     "Mark Corneglio",
     "SarcasticHashtag",
+    "Anthony Rizzo",
     "iamresist",
+    "RedrockVP",
     "Wolffen",
-    "Ricky Carter",
     "James Todd",
-    "JongWon Han",
-    "VantAI",
+    "Steven Pfeiffer",
     "Tim",
+    "Timmy",
+    "Johnny",
     "Lisster",
     "Michael Wong",
     "Illrigger",
+    "whudunit",
     "Tom Corrigan",
     "JackieWang",
-    "FreelancerZ",
     "fnkylove",
     "Yushio",
     "Vik71it",
@@ -73,16 +87,17 @@
     "Lilleman",
     "Robert Stacey",
     "PM",
-    "Edgar Tejeda",
+    "Todd Keck",
+    "Briton Heilbrun",
     "Jorge Hussni",
-    "Liam MacDougal",
     "Sterilized",
     "BadassArabianMofo",
+    "Pascal Dahle",
     "quarz",
     "Greg",
     "JSST",
-    "Snaggwort",
     "lmsupporter",
+    "zounic",
     "wfpearl",
     "Baekdoosixt",
     "Jonathan Ross",
@@ -91,49 +106,43 @@
     "Melville Parrish",
     "daniel dove",
     "Lustre",
-    "Tyler Trebuchon",
     "JW Sin",
     "contrite831",
     "Alex",
     "bh",
-    "carozzz",
     "Marlon Daniels",
     "Starkselle",
-    "Buzzard",
     "Aaron Bleuer",
     "LacesOut!",
     "greebles",
-    "Adam Shaw",
-    "Anthony Rizzo",
+    "M Postkasse",
     "Gooohokrbe",
-    "RedrockVP",
-    "ASLPro3D",
+    "Wicked Choices by ASLPro3D",
     "OldBones",
     "Jacob Hoehler",
     "FinalyFree",
     "Weasyl",
-    "Steven Pfeiffer",
-    "Timmy",
-    "Johnny",
+    "Lex Song",
     "Cory Paza",
     "Tak",
+    "Gonzalo Andre Allendes Lopez",
     "Zach Gonser",
     "Big Red",
-    "whudunit",
+    "Jimmy Ledbetter",
     "Luc Job",
     "dl0901dm",
     "Philip Hempel",
     "corde",
     "Nick Walker",
     "Bishoujoker",
-    "Todd Keck",
-    "Briton Heilbrun",
+    "aai",
     "Tori",
     "wildnut",
     "jean jahren",
     "Aleksander Wujczyk",
     "AM Kuro",
-    "Pascal Dahle",
+    "Ran C",
+    "ViperC",
     "Penfore",
     "Sangheili460",
     "MagnaInsomnia",
@@ -146,44 +155,49 @@
     "The Spawn",
     "graysock",
     "Greenmoustache",
-    "zounic",
     "fancypants",
     "Eldithor",
+    "Joboshy",
     "Digital",
     "JaxMax",
     "takyamtom",
+    "Bohemian Corporal",
+    "Dan",
     "Jwk0205",
+    "Bro Xie",
+    "yer fey",
     "batblue",
     "carey6409",
     "Olive",
+    "太郎 ゲーム",
     "Some Guy Named Barry",
+    "jinxedx",
     "Cosmosis",
-    "M Postkasse",
     "AELOX",
+    "Dankin",
     "Nicfit23",
     "FloPro4Sho",
     "wamekukyouzin",
     "drum matthieu",
     "Dogmaster",
     "Matt Wenzel",
-    "Lex Song",
+    "Frank Nitty",
     "Christopher Michel",
-    "Gonzalo Andre Allendes Lopez",
     "Serge Bekenkamp",
-    "Jimmy Ledbetter",
     "LeoZero",
+    "Antonio Pontes",
     "ApathyJones",
     "Julian V",
     "Steven Owens",
     "nahinahi9",
     "Dustin Chen",
     "dan",
-    "aai",
+    "Blackfish95",
     "Mouthlessman",
+    "Paul Kroll",
     "otaku fra",
-    "ViperC",
-    "Ran C",
     "MiraiKuriyamaSy",
+    "Bas Imagineer",
     "yuxz69",
     "Adam Taylor",
     "Weird_With_A_Beard",
@@ -199,89 +213,90 @@
     "Jon Sandman",
     "Ubivis",
     "CloudValley",
+    "thesoftwaredruid",
+    "wundershark",
+    "mr_dinosaur",
+    "Tyrswood",
+    "linnfrey",
     "IamAyam",
-    "Joboshy",
-    "Bohemian Corporal",
-    "Dan",
+    "skaterb949",
+    "Josef Lanzl",
     "confiscated Zyra",
-    "Bro Xie",
-    "yer fey",
     "Error_Rule34_Not_found",
-    "太郎 ゲーム",
+    "Gerald Welly",
     "Roslynd",
     "Tee Gee",
-    "jinxedx",
+    "Geolog",
     "tarek helmi",
     "Neco28",
     "Max Marklund",
     "David Ortega",
-    "Dankin",
     "Cristian Vazquez",
-    "Frank Nitty",
     "Magic Noob",
     "Pronredn",
     "DougPeterson",
-    "Antonio Pontes",
+    "Jeff",
     "Bruce",
     "lh qwe",
     "Kevin John Duck",
     "conner",
     "Kevin Christopher",
-    "Blackfish95",
     "dd",
     "Princess Bright Eyes",
-    "Paul Kroll",
+    "Dušan Ryban",
     "Felipe dos Santos",
-    "Bas Imagineer",
     "John Statham",
     "Douglas Gaspar",
+    "Metryman55",
     "AlexDuKaNa",
     "George",
     "dw",
     "decoy",
-    "thesoftwaredruid",
-    "wundershark",
-    "mr_dinosaur",
-    "Tyrswood",
     "Ray Wing",
     "Ranzitho",
     "Gus",
     "地獄の禄",
     "MJG",
     "David LaVallee",
-    "linnfrey",
     "ae",
     "Tr4shP4nda",
+    "Gamalonia",
     "WRL_SPR",
     "capn",
     "Joseph",
     "Mirko Katzula",
+    "dan",
+    "Piccio08",
+    "kumakichi",
+    "cppbel",
+    "Moon Knight",
+    "몽타주",
+    "Kland",
+    "Hailshem",
     "奚明 刘",
     "Brian M",
-    "Josef Lanzl",
     "Nerezza",
     "sanborondon",
-    "Griffin Dahlberg",
     "준희 김",
     "Taylor Funk",
     "aezin",
     "Thought2Form",
     "jcay015",
-    "Gerald Welly",
     "Kevin Picco",
     "Erik Lopez",
     "Mateo Curić",
-    "Geolog",
     "Eris3D",
     "Tomohiro Baba",
     "m",
     "Noora",
     "Pierce McBride",
+    "Joshua Gray",
     "Mattssn",
+    "Mikko Hemilä",
     "Jamie Ogletree",
     "a _",
-    "Jeff",
     "James Coleman",
+    "Martial",
     "Emil Andersson",
     "Ouro Boros",
     "Chad Idk",
@@ -289,7 +304,6 @@
     "CryptoTraderJK",
     "Yuji Kaneko",
     "Davaitamin",
-    "Dušan Ryban",
     "Rops Alot",
     "tedcor",
     "Sam",
@@ -297,20 +311,10 @@
     "sjon kreutz",
     "Ace Ventura",
     "MadSpin",
-    "Metryman55",
     "inbijiburu",
     "Nick “Loadstone” D",
-    "Gamalonia",
     "momokai",
-    "dan",
-    "Piccio08",
-    "kumakichi",
-    "cppbel",
     "starbugx",
-    "Moon Knight",
-    "몽타주",
-    "Kland",
-    "Hailshem",
     "kudari",
     "Naomi Hale Danchi",
     "dc7431",
@@ -331,12 +335,17 @@
     "JohnDoe42054",
     "BillyHill",
     "emyth",
+    "chriphost",
+    "KitKatM",
+    "socrasteeze",
+    "OrganicArtifact",
     "Vir",
     "gzmzmvp",
     "Richard",
     "Andrew",
     "Robert Wegemund",
     "Littlehuggy",
+    "Gregory Kozhemiak",
     "Draven T",
     "mrjuan",
     "Brian Buie",
@@ -347,10 +356,10 @@
     "Ivan Tadic",
     "Mike Simone",
     "ethanfel",
-    "Joshua Gray",
+    "Elliot E",
     "Morgandel",
+    "Theerat Jiramate",
     "Focuschannel",
-    "Mikko Hemilä",
     "Noah",
     "Jacob McDaniel",
     "X",
@@ -359,18 +368,18 @@
     "Artokun",
     "Michael Taylor",
     "Derek Baker",
-    "Martial",
     "Anthony Faxlandez",
     "battu",
     "Michael Anthony Scott",
     "Atilla Berke Pekduyar",
+    "Nathan",
     "Decx _",
     "Pat Hen",
     "Jordan Shaw",
-    "Thesharingbrother",
-    "ResidentDeviant",
+    "Srdb",
     "四糸凜音",
     "Nihongasuki",
+    "LarsesFPC",
     "JC",
     "Prompt Pirate",
     "uwutismxd",
@@ -378,17 +387,14 @@
     "zenobeus",
     "Crocket",
     "Jackthemind",
-    "chriphost",
-    "KitKatM",
     "ryoma",
-    "socrasteeze",
-    "OrganicArtifact",
     "Stryker",
     "ResidentDeviant",
     "MudkipMedkitz",
     "deanbrian",
     "Alex Wortman",
     "Cody",
+    "Raku",
     "smart.edge5178",
     "InformedViewz",
     "CHKeeho80",
@@ -402,6 +408,7 @@
     "moonpetal",
     "SomeDude",
     "g9p0o",
+    "Pkrsky",
     "TheHolySheep",
     "raf8osz",
     "Monte Won",
@@ -409,36 +416,38 @@
     "carsten",
     "ikok",
     "ElitaSSJ4",
+    "David Schenck",
     "Wolfe7D1",
     "blikkies",
     "Chris",
-    "Gregory Kozhemiak",
     "elleshar666",
     "Shock Shockor",
     "ACTUALLY_the_Real_Willem_Dafoe",
     "Goldwaters",
+    "Kauffy",
     "Zude",
     "John J Linehan",
     "Kyler",
-    "Elliot E",
-    "Theerat Jiramate",
     "Edward Kennedy",
     "Justin Blaylock",
     "aRtFuL_DodGeR",
+    "Nick Kage",
     "Vane Holzer",
+    "psytrax",
+    "Cyrus Fett",
     "hexxish",
     "notedfakes",
-    "DarkSunset",
-    "Nathan",
     "Billy Gladky",
     "NICHOLAS BAXLEY",
     "Michael Scott",
     "Probis",
     "Ed Wang",
+    "Wes Sims",
     "ItsGeneralButtNaked",
-    "SRDB",
+    "Donor4115",
     "g unit",
     "Distortik",
+    "Filippo Ferrari",
     "Youguang",
     "Saya",
     "andrewzpong",
@@ -452,10 +461,12 @@
     "Whitepinetrader",
     "POPPIN",
     "Ginnie",
-    "Raku",
     "emadsultan",
-    "Pkrsky",
     "nanana",
+    "g",
+    "J",
+    "Alan+Cano",
+    "FeralOpticsAI",
     "Pavlaki",
     "Doug+Rintoul",
     "Noor",
@@ -471,31 +482,27 @@
     "Duk3+Rand0m",
     "Nathen+Choi",
     "T",
-    "LarsesFPC",
     "cocona",
     "Buecyb99",
     "Welkor",
-    "David Schenck",
     "John Martin",
     "Ink Temptation",
+    "JBsuede",
     "moranqianlong",
     "Kalli Core",
     "Time Valentine",
     "Михал Михалыч",
     "Matt",
-    "Kauffy",
     "Frogmilk",
     "SPJ",
     "Kyron Mahan",
     "Bryan Rutkowski",
-    "Nick Kage",
     "TBitz33",
     "Anonym dkjglfleeoeldldldlkf",
-    "psytrax",
-    "Cyrus Fett",
     "Ezokewn",
     "SendingRavens",
     "Xenon Xue",
+    "JackJohnnyJim",
     "Edward Ten Eyck",
     "Michael Docherty",
     "Paul Hartsuyker",
@@ -504,15 +511,14 @@
     "Solixer",
     "Jacob Winter",
     "Ryan Presley Ng",
-    "Wes Sims",
     "jinksta187",
-    "Donor4115",
+    "Andrew Wilkinson",
     "Manu Thetug",
+    "Karlanx",
     "Lyavph",
     "David",
     "Meilo",
     "operationancut",
-    "Filippo Ferrari",
     "shinonomeiro",
     "Snille",
     "MaartenAlbers",
@@ -531,6 +537,10 @@
     "Scott",
     "Muratoraccio",
     "D",
+    "low9",
+    "Winged",
+    "YassineKhaled",
+    "Y",
     "MatteKey",
     "Flob",
     "ShiroSenpai",
@@ -549,10 +559,6 @@
     "redcarrot",
     "powerbot99",
     "Fthehappy",
-    "rsamerica",
-    "sfasdfasfdsa",
-    "Alan+Cano",
-    "FeralOpticsAI",
     "generic404",
     "abattoirblues",
     "zounik",
@@ -561,7 +567,8 @@
     "ahoystan",
     "Bob Barker",
     "edk",
-    "JBsuede",
+    "Tú Nguyễn Lý Hoàng",
+    "Ronan Delevacq",
     "Christian Schäfer",
     "りん あめ",
     "ja s",
@@ -579,12 +586,12 @@
     "Boba Smith",
     "Devil Lude",
     "David Murcko",
+    "MR.Bear",
     "Jack Dole",
     "max blo",
     "Sauv",
     "Steven",
     "CptNeo",
-    "JackJohnnyJim",
     "TenaciousD",
     "Dmitry Ryzhov",
     "Khánh Đặng",
@@ -593,13 +600,13 @@
     "Kevin Wallace",
     "Jimmy Borup",
     "ChicRic",
+    "Tigon",
+    "BastardSama",
     "mercur",
     "Pete Pain",
     "RHopkirk",
-    "Andrew Wilkinson",
     "Yavizu3d",
     "Maxim",
-    "Karlanx",
     "Yves Poezevara",
     "Teriak47",
     "Just me",
@@ -637,6 +644,7 @@
     "Captain_Swag",
     "obkircher",
     "gwyar",
+    "ResidentDeviant",
     "D",
     "edgecase",
     "Neoxena",
@@ -647,6 +655,9 @@
     "SelfishMedic",
     "adderleighn",
     "EnragedAntelope",
+    "SRCRCOSS",
+    "imer",
+    "Akkas+Haque",
     "Kachac",
     "tyrant2811",
     "Kevin",
@@ -678,11 +689,7 @@
     "Terraformer",
     "GDS+DEV",
     "4rt+r3d",
-    "low9",
-    "Winged",
     "you+halo9",
-    "YassineKhaled",
-    "YK12",
     "Somebody",
     "Somebody",
     "Crescent~San",
@@ -697,24 +704,25 @@
     "Coeur+de+cochon",
     "Obsidian.Studios",
     "han b",
+    "Zomba Mann",
+    "Aquaneo",
     "Nico",
     "Maximilian Krischan",
     "Banana Joe",
     "_ G3n",
     "Donovan Jenkins",
     "Hans Meier",
-    "Tú Nguyễn Lý Hoàng",
     "shira1011",
+    "sicarius",
     "Michael Eid",
     "beersandbacon",
     "Neko Desco",
     "Bob barker",
     "Ben D",
+    "Ninja Tom",
     "G",
-    "Ronan Delevacq",
     "karim ben brik",
     "Vinarus",
-    "james",
     "Michael Zhu",
     "Nemisu",
     "Seraphy",
@@ -737,15 +745,17 @@
     "AZ Party Oasis",
     "Adictedtohumping",
     "Towelie",
-    "Ryan Smith",
-    "MR.Bear",
+    "TheFusion",
     "matt",
     "dsffsdfsdfsdfsdfsdf",
     "somethingtosay8",
     "Jean-françois SEMA",
+    "3zS4QNQ4",
     "Terminuz",
     "Kurt",
     "ivistorm",
+    "Matt M.",
+    "Ivan Imes",
     "Faburizu",
     "Jack Lawfield",
     "jimyjomson",
@@ -763,12 +773,13 @@
     "Rizzi",
     "nimin",
     "OMAR LUCIANO",
+    "Somebody",
+    "CoffeeMage",
     "Ken+Suzuki",
     "hannibal",
     "Jo+Example",
     "BrentBertram",
     "inusanorthcape",
-    "Tigon",
     "eumelzocker",
     "dxjaymz",
     "L C",
@@ -776,5 +787,5 @@
     "Somebody",
     "CK"
   ],
-  "totalCount": 773
+  "totalCount": 784
 }

locales/de.json

@@ -689,6 +689,7 @@
             "setContentRating": "Inhaltsbewertung für alle festlegen",
             "copyAll": "Alle Syntax kopieren",
             "refreshAll": "Alle Metadaten aktualisieren",
+            "repairMetadata": "Metadaten der Auswahl reparieren",
             "checkUpdates": "Auswahl auf Updates prüfen",
             "moveAll": "Alle in Ordner verschieben",
             "autoOrganize": "Automatisch organisieren",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "Keine Ordner gefunden",
             "dragHint": "Elemente hierher ziehen, um Ordner zu erstellen"
+        },
+        "folderUpdateCheck": {
+            "label": "Auf Updates in diesem Ordner prüfen",
+            "loading": "Prüfe {type}-Updates in diesem Ordner...",
+            "success": "{count} Update(s) für {type}s in diesem Ordner gefunden",
+            "none": "Alle {type}s in diesem Ordner sind aktuell",
+            "error": "Fehler beim Prüfen des Ordners auf {type}-Updates: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "Zuvor heruntergeladen, aber derzeit nicht in Ihrer Bibliothek.",
             "alreadyInLibrary": "Bereits in Bibliothek",
             "autoOrganizedPath": "[Automatisch organisiert durch Pfadvorlage]",
+            "fileSelection": {
+                "title": "Dateiformat auswählen",
+                "files": "Dateien",
+                "select": "Datei auswählen"
+            },
             "errors": {
                 "invalidUrl": "Ungültiges Civitai URL-Format",
                 "noVersions": "Keine Versionen für dieses Modell verfügbar"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "Keine Rezept-ID verfügbar",
             "sendToWorkflowFailed": "Fehler beim Senden des Rezepts an den Workflow: {message}",
             "copyFailed": "Fehler beim Kopieren der Rezept-Syntax: {message}",
+            "createError": "Fehler beim Erstellen des Rezepts：{message}",
+            "createFailed": "Fehler beim Erstellen des Rezepts：{error}",
+            "createMissingData": "Erforderliche Daten zum Erstellen des Rezepts fehlen",
+            "created": "Rezept erfolgreich erstellt",
             "noMissingLoras": "Keine fehlenden LoRAs zum Herunterladen",
             "missingLorasInfoFailed": "Fehler beim Abrufen der Informationen für fehlende LoRAs",
             "preparingForDownloadFailed": "Fehler beim Vorbereiten der LoRAs für den Download",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "Keine Rezepte ausgewählt",
+            "repairBulkComplete": "Reparatur abgeschlossen: {repaired} repariert, {skipped} übersprungen (von {total})",
+            "repairBulkSkipped": "Keine Reparatur für die {total} ausgewählten Rezepte erforderlich",
+            "repairBulkFailed": "Reparatur der ausgewählten Rezepte fehlgeschlagen: {message}",
             "noMissingLorasInSelection": "Keine fehlenden LoRAs in ausgewählten Rezepten gefunden",
             "noLoraRootConfigured": "Kein LoRA-Stammverzeichnis konfiguriert. Bitte legen Sie ein Standard-LoRA-Stammverzeichnis in den Einstellungen fest."
         },

locales/en.json

@@ -689,6 +689,7 @@
             "setContentRating": "Set Content Rating for Selected",
             "copyAll": "Copy Selected Syntax",
             "refreshAll": "Refresh Selected Metadata",
+            "repairMetadata": "Repair Metadata for Selected",
             "checkUpdates": "Check Updates for Selected",
             "moveAll": "Move Selected to Folder",
             "autoOrganize": "Auto-Organize Selected",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "No folders found",
             "dragHint": "Drag items here to create folders"
+        },
+        "folderUpdateCheck": {
+            "label": "Check for updates in this folder",
+            "loading": "Checking {type} updates for this folder...",
+            "success": "Found {count} update(s) for {type}s in this folder",
+            "none": "All {type}s in this folder are up to date",
+            "error": "Failed to check folder for {type} updates: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "Previously downloaded, but it is not currently in your library.",
             "alreadyInLibrary": "Already in Library",
             "autoOrganizedPath": "[Auto-organized by path template]",
+            "fileSelection": {
+                "title": "Select File Format",
+                "files": "files",
+                "select": "Select File"
+            },
             "errors": {
                 "invalidUrl": "Invalid Civitai URL format",
                 "noVersions": "No versions available for this model"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "No recipe ID available",
             "sendToWorkflowFailed": "Failed to send recipe to workflow: {message}",
             "copyFailed": "Error copying recipe syntax: {message}",
+            "createError": "Error creating recipe: {message}",
+            "createFailed": "Failed to create recipe: {error}",
+            "createMissingData": "Missing required data to create recipe",
+            "created": "Recipe created successfully",
             "noMissingLoras": "No missing LoRAs to download",
             "missingLorasInfoFailed": "Failed to get information for missing LoRAs",
             "preparingForDownloadFailed": "Error preparing LoRAs for download",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "No recipes selected",
+            "repairBulkComplete": "Repair complete: {repaired} repaired, {skipped} skipped (of {total})",
+            "repairBulkSkipped": "No repair needed for any of the {total} selected recipes",
+            "repairBulkFailed": "Failed to repair selected recipes: {message}",
             "noMissingLorasInSelection": "No missing LoRAs found in selected recipes",
             "noLoraRootConfigured": "No LoRA root directory configured. Please set a default LoRA root in settings."
         },

locales/es.json

@@ -689,6 +689,7 @@
             "setContentRating": "Establecer clasificación de contenido para todos",
             "copyAll": "Copiar toda la sintaxis",
             "refreshAll": "Actualizar todos los metadatos",
+            "repairMetadata": "Reparar metadatos de la selección",
             "checkUpdates": "Comprobar actualizaciones para la selección",
             "moveAll": "Mover todos a carpeta",
             "autoOrganize": "Auto-organizar seleccionados",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "No se encontraron carpetas",
             "dragHint": "Arrastra elementos aquí para crear carpetas"
+        },
+        "folderUpdateCheck": {
+            "label": "Buscar actualizaciones en esta carpeta",
+            "loading": "Buscando actualizaciones de {type} en esta carpeta...",
+            "success": "Se encontraron {count} actualización(es) para {type}s en esta carpeta",
+            "none": "Todos los {type}s en esta carpeta están actualizados",
+            "error": "Error al buscar actualizaciones de {type} en la carpeta: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "Descargado anteriormente, pero actualmente no está en tu biblioteca.",
             "alreadyInLibrary": "Ya en la biblioteca",
             "autoOrganizedPath": "[Auto-organizado por plantilla de ruta]",
+            "fileSelection": {
+                "title": "Seleccionar formato de archivo",
+                "files": "archivos",
+                "select": "Seleccionar archivo"
+            },
             "errors": {
                 "invalidUrl": "Formato de URL de Civitai inválido",
                 "noVersions": "No hay versiones disponibles para este modelo"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "No hay ID de receta disponible",
             "sendToWorkflowFailed": "Error al enviar la receta al flujo de trabajo: {message}",
             "copyFailed": "Error copiando sintaxis de receta: {message}",
+            "createError": "Error al crear la receta：{message}",
+            "createFailed": "Error al crear la receta：{error}",
+            "createMissingData": "Faltan datos necesarios para crear la receta",
+            "created": "Receta creada exitosamente",
             "noMissingLoras": "No hay LoRAs faltantes para descargar",
             "missingLorasInfoFailed": "Error al obtener información de LoRAs faltantes",
             "preparingForDownloadFailed": "Error preparando LoRAs para descarga",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "No se han seleccionado recetas",
+            "repairBulkComplete": "Reparación completa: {repaired} reparadas, {skipped} omitidas (de {total})",
+            "repairBulkSkipped": "No se necesita reparación para ninguna de las {total} recetas seleccionadas",
+            "repairBulkFailed": "Error al reparar las recetas seleccionadas: {message}",
             "noMissingLorasInSelection": "No se encontraron LoRAs faltantes en las recetas seleccionadas",
             "noLoraRootConfigured": "No se ha configurado el directorio raíz de LoRA. Por favor, establezca un directorio raíz de LoRA predeterminado en la configuración."
         },

locales/fr.json

@@ -689,6 +689,7 @@
             "setContentRating": "Définir la classification du contenu pour tous",
             "copyAll": "Copier toute la syntaxe",
             "refreshAll": "Actualiser toutes les métadonnées",
+            "repairMetadata": "Réparer les métadonnées de la sélection",
             "checkUpdates": "Vérifier les mises à jour pour la sélection",
             "moveAll": "Déplacer tout vers un dossier",
             "autoOrganize": "Auto-organiser la sélection",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "Aucun dossier trouvé",
             "dragHint": "Faites glisser des éléments ici pour créer des dossiers"
+        },
+        "folderUpdateCheck": {
+            "label": "Vérifier les mises à jour dans ce dossier",
+            "loading": "Vérification des mises à jour {type} dans ce dossier...",
+            "success": "{count} mise(s) à jour trouvée(s) pour les {type}s dans ce dossier",
+            "none": "Tous les {type}s dans ce dossier sont à jour",
+            "error": "Échec de la vérification des mises à jour {type} dans ce dossier : {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "Déjà téléchargé, mais il n'est actuellement pas dans votre bibliothèque.",
             "alreadyInLibrary": "Déjà dans la bibliothèque",
             "autoOrganizedPath": "[Auto-organisé par modèle de chemin]",
+            "fileSelection": {
+                "title": "Choisir le format de fichier",
+                "files": "fichiers",
+                "select": "Choisir le fichier"
+            },
             "errors": {
                 "invalidUrl": "Format d'URL Civitai invalide",
                 "noVersions": "Aucune version disponible pour ce modèle"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "Aucun ID de recipe disponible",
             "sendToWorkflowFailed": "Échec de l'envoi de la recette vers le workflow : {message}",
             "copyFailed": "Erreur lors de la copie de la syntaxe de la recipe : {message}",
+            "createError": "Erreur lors de la création du Recipe ：{message}",
+            "createFailed": "Échec de la création du Recipe ：{error}",
+            "createMissingData": "Données requises manquantes pour créer le Recipe",
+            "created": "Recipe créé avec succès",
             "noMissingLoras": "Aucun LoRA manquant à télécharger",
             "missingLorasInfoFailed": "Échec de l'obtention des informations pour les LoRAs manquants",
             "preparingForDownloadFailed": "Erreur lors de la préparation des LoRAs pour le téléchargement",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "Aucune recette sélectionnée",
+            "repairBulkComplete": "Réparation terminée : {repaired} réparée(s), {skipped} ignorée(s) (sur {total})",
+            "repairBulkSkipped": "Aucune réparation nécessaire parmi les {total} recettes sélectionnées",
+            "repairBulkFailed": "Échec de la réparation des recettes sélectionnées : {message}",
             "noMissingLorasInSelection": "Aucun LoRA manquant trouvé dans les recettes sélectionnées",
             "noLoraRootConfigured": "Aucun répertoire racine LoRA configuré. Veuillez définir un répertoire racine LoRA par défaut dans les paramètres."
         },

locales/he.json

@@ -689,6 +689,7 @@
             "setContentRating": "הגדר דירוג תוכן לכל המודלים",
             "copyAll": "העתק את כל התחבירים",
             "refreshAll": "רענן את כל המטא-דאטה",
+            "repairMetadata": "תקן מטא-דאטה עבור הנבחרים",
             "checkUpdates": "בדוק עדכונים לבחירה",
             "moveAll": "העבר הכל לתיקייה",
             "autoOrganize": "ארגן אוטומטית נבחרים",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "לא נמצאו תיקיות",
             "dragHint": "גרור פריטים לכאן כדי ליצור תיקיות"
+        },
+        "folderUpdateCheck": {
+            "label": "בדוק עדכונים בתיקייה זו",
+            "loading": "בודק עדכוני {type} בתיקייה זו...",
+            "success": "נמצאו {count} עדכון/ים עבור {type}s בתיקייה זו",
+            "none": "כל ה-{type}s בתיקייה זו מעודכנים",
+            "error": "נכשל בבדיקת עדכוני {type} בתיקייה: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "הורד בעבר, אך הוא אינו נמצא כרגע בספרייה שלך.",
             "alreadyInLibrary": "כבר בספרייה",
             "autoOrganizedPath": "[מאורגן אוטומטית לפי תבנית נתיב]",
+            "fileSelection": {
+                "title": "בחר פורמט קובץ",
+                "files": "קבצים",
+                "select": "בחר קובץ"
+            },
             "errors": {
                 "invalidUrl": "פורמט URL של Civitai לא חוקי",
                 "noVersions": "אין גרסאות זמינות למודל זה"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "אין מזהה מתכון זמין",
             "sendToWorkflowFailed": "נכשל שליחת המתכון ל-workflow: {message}",
             "copyFailed": "שגיאה בהעתקת תחביר המתכון: {message}",
+            "createError": "שגיאה ביצירת המתכון：{message}",
+            "createFailed": "יצירת המתכון נכשלה：{error}",
+            "createMissingData": "חסרים נתונים נדרשים ליצירת המתכון",
+            "created": "המתכון נוצר בהצלחה",
             "noMissingLoras": "אין LoRAs חסרים להורדה",
             "missingLorasInfoFailed": "קבלת מידע עבור LoRAs חסרים נכשלה",
             "preparingForDownloadFailed": "שגיאה בהכנת LoRAs להורדה",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "לא נבחרו מתכונים",
+            "repairBulkComplete": "התיקון הושלם: {repaired} תוקנו, {skipped} דולגו (מתוך {total})",
+            "repairBulkSkipped": "אין צורך בתיקון עבור {total} המתכונים הנבחרים",
+            "repairBulkFailed": "תיקון המתכונים הנבחרים נכשל: {message}",
             "noMissingLorasInSelection": "לא נמצאו LoRAs חסרים במתכונים שנבחרו",
             "noLoraRootConfigured": "תיקיית השורש של LoRA לא מוגדרת. אנא הגדר תיקיית שורש LoRA ברירת מחדל בהגדרות."
         },

locales/ja.json

@@ -689,6 +689,7 @@
             "setContentRating": "すべてのモデルのコンテンツレーティングを設定",
             "copyAll": "すべての構文をコピー",
             "refreshAll": "すべてのメタデータを更新",
+            "repairMetadata": "選択したレシピのメタデータを修復",
             "checkUpdates": "選択項目の更新を確認",
             "moveAll": "すべてをフォルダに移動",
             "autoOrganize": "自動整理を実行",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "フォルダが見つかりません",
             "dragHint": "ここへアイテムをドラッグしてフォルダを作成します"
+        },
+        "folderUpdateCheck": {
+            "label": "このフォルダのアップデートを確認",
+            "loading": "このフォルダの{type}アップデートを確認中...",
+            "success": "このフォルダの{type}sに{count}件のアップデートが見つかりました",
+            "none": "このフォルダのすべての{type}sは最新です",
+            "error": "フォルダの{type}アップデート確認に失敗しました: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "以前にダウンロード済みですが、現在はライブラリにありません。",
             "alreadyInLibrary": "既にライブラリ内",
             "autoOrganizedPath": "[パステンプレートによる自動整理]",
+            "fileSelection": {
+                "title": "ファイル形式を選択",
+                "files": "ファイル",
+                "select": "ファイルを選択"
+            },
             "errors": {
                 "invalidUrl": "無効なCivitai URL形式",
                 "noVersions": "このモデルの利用可能なバージョンがありません"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "レシピIDが利用できません",
             "sendToWorkflowFailed": "ワークフローへのレシピ送信に失敗しました：{message}",
             "copyFailed": "レシピ構文のコピーエラー：{message}",
+            "createError": "レシピ作成中にエラーが発生しました：{message}",
+            "createFailed": "レシピの作成に失敗しました：{error}",
+            "createMissingData": "レシピ作成に必要なデータが不足しています",
+            "created": "レシピを作成しました",
             "noMissingLoras": "ダウンロードする不足LoRAがありません",
             "missingLorasInfoFailed": "不足LoRAの情報取得に失敗しました",
             "preparingForDownloadFailed": "ダウンロード用LoRAの準備中にエラーが発生しました",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "レシピが選択されていません",
+            "repairBulkComplete": "修復完了：{repaired} 件修復、{skipped} 件スキップ（合計 {total} 件）",
+            "repairBulkSkipped": "選択した {total} 件のレシピは修復不要です",
+            "repairBulkFailed": "選択したレシピの修復に失敗しました：{message}",
             "noMissingLorasInSelection": "選択したレシピに不足している LoRA が見つかりませんでした",
             "noLoraRootConfigured": "LoRA ルートディレクトリが設定されていません。設定でデフォルトの LoRA ルートを設定してください。"
         },

locales/ko.json

@@ -689,6 +689,7 @@
             "setContentRating": "모든 모델에 콘텐츠 등급 설정",
             "copyAll": "모든 문법 복사",
             "refreshAll": "모든 메타데이터 새로고침",
+            "repairMetadata": "선택한 레시피 메타데이터 복구",
             "checkUpdates": "선택 항목 업데이트 확인",
             "moveAll": "모두 폴더로 이동",
             "autoOrganize": "자동 정리 선택",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "폴더를 찾을 수 없습니다",
             "dragHint": "항목을 여기로 드래그하여 폴더를 만듭니다"
+        },
+        "folderUpdateCheck": {
+            "label": "이 폴더의 업데이트 확인",
+            "loading": "이 폴더의 {type} 업데이트를 확인하는 중...",
+            "success": "이 폴더에서 {type}s에 대한 {count}개 업데이트를 찾았습니다",
+            "none": "이 폴더의 모든 {type}s가 최신 상태입니다",
+            "error": "폴더의 {type} 업데이트 확인 실패: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "이전에 다운로드했지만 현재 라이브러리에 없습니다.",
             "alreadyInLibrary": "이미 라이브러리에 있음",
             "autoOrganizedPath": "[경로 템플릿으로 자동 정리됨]",
+            "fileSelection": {
+                "title": "파일 형식 선택",
+                "files": "개 파일",
+                "select": "파일 선택"
+            },
             "errors": {
                 "invalidUrl": "잘못된 Civitai URL 형식",
                 "noVersions": "이 모델에 사용 가능한 버전이 없습니다"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "사용 가능한 레시피 ID가 없습니다",
             "sendToWorkflowFailed": "워크플로우에 레시피 보내기 실패: {message}",
             "copyFailed": "레시피 문법 복사 오류: {message}",
+            "createError": "레시피 생성 중 오류 발생：{message}",
+            "createFailed": "레시피 생성 실패：{error}",
+            "createMissingData": "레시피 생성에 필요한 데이터가 없습니다",
+            "created": "레시피가 생성되었습니다",
             "noMissingLoras": "다운로드할 누락된 LoRA가 없습니다",
             "missingLorasInfoFailed": "누락된 LoRA 정보를 가져오는데 실패했습니다",
             "preparingForDownloadFailed": "LoRA 다운로드 준비 오류",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "선택한 레시피가 없습니다",
+            "repairBulkComplete": "복구 완료: {repaired}개 복구, {skipped}개 건너뜀 (총 {total}개)",
+            "repairBulkSkipped": "선택한 {total}개 레시피는 복구가 필요하지 않습니다",
+            "repairBulkFailed": "선택한 레시피 복구 실패: {message}",
             "noMissingLorasInSelection": "선택한 레시피에서 누락된 LoRA를 찾을 수 없습니다",
             "noLoraRootConfigured": "LoRA 루트 디렉토리가 구성되지 않았습니다. 설정에서 기본 LoRA 루트를 설정하세요."
         },

locales/ru.json

@@ -689,6 +689,7 @@
             "setContentRating": "Установить рейтинг контента для всех",
             "copyAll": "Копировать весь синтаксис",
             "refreshAll": "Обновить все метаданные",
+            "repairMetadata": "Восстановить метаданные для выбранных",
             "checkUpdates": "Проверить обновления для выбранных",
             "moveAll": "Переместить все в папку",
             "autoOrganize": "Автоматически организовать выбранные",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "Папки не найдены",
             "dragHint": "Перетащите элементы сюда, чтобы создать папки"
+        },
+        "folderUpdateCheck": {
+            "label": "Проверить обновления в этой папке",
+            "loading": "Проверка обновлений {type} в этой папке...",
+            "success": "Найдено {count} обновление(й) для {type}s в этой папке",
+            "none": "Все {type}s в этой папке актуальны",
+            "error": "Не удалось проверить папку на наличие обновлений {type}: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "Ранее загружено, но сейчас этого нет в вашей библиотеке.",
             "alreadyInLibrary": "Уже в библиотеке",
             "autoOrganizedPath": "[Автоматически организовано по шаблону пути]",
+            "fileSelection": {
+                "title": "Выбрать формат файла",
+                "files": "файлов",
+                "select": "Выбрать файл"
+            },
             "errors": {
                 "invalidUrl": "Неверный формат URL Civitai",
                 "noVersions": "Нет доступных версий для этой модели"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "ID рецепта недоступен",
             "sendToWorkflowFailed": "Не удалось отправить рецепт в рабочий процесс: {message}",
             "copyFailed": "Ошибка копирования синтаксиса рецепта: {message}",
+            "createError": "Ошибка при создании рецепта：{message}",
+            "createFailed": "Не удалось создать рецепт：{error}",
+            "createMissingData": "Отсутствуют необходимые данные для создания рецепта",
+            "created": "Рецепт успешно создан",
             "noMissingLoras": "Нет отсутствующих LoRAs для загрузки",
             "missingLorasInfoFailed": "Не удалось получить информацию для отсутствующих LoRAs",
             "preparingForDownloadFailed": "Ошибка подготовки LoRAs для загрузки",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "Failed to browse directory: {message}",
             "batchImportDirectorySelected": "Directory selected: {path}",
             "noRecipesSelected": "Рецепты не выбраны",
+            "repairBulkComplete": "Восстановление завершено: {repaired} восстановлено, {skipped} пропущено (из {total})",
+            "repairBulkSkipped": "Ни один из {total} выбранных рецептов не требует восстановления",
+            "repairBulkFailed": "Не удалось восстановить выбранные рецепты: {message}",
             "noMissingLorasInSelection": "В выбранных рецептах не найдены отсутствующие LoRAs",
             "noLoraRootConfigured": "Корневой каталог LoRA не настроен. Пожалуйста, установите корневой каталог LoRA по умолчанию в настройках."
         },

locales/zh-CN.json

@@ -689,6 +689,7 @@
             "setContentRating": "为所选中设置内容评级",
             "copyAll": "复制所选中语法",
             "refreshAll": "刷新所选中元数据",
+            "repairMetadata": "修复所选中元数据",
             "checkUpdates": "检查所选更新",
             "moveAll": "移动所选中到文件夹",
             "autoOrganize": "自动整理所选模型",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "未找到文件夹",
             "dragHint": "拖拽项目到此处以创建文件夹"
+        },
+        "folderUpdateCheck": {
+            "label": "检查此文件夹的更新",
+            "loading": "正在检查此文件夹中的{type}更新...",
+            "success": "在此文件夹中找到 {count} 个{type}更新",
+            "none": "此文件夹中的所有{type}都是最新版本",
+            "error": "检查文件夹{type}更新失败: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "之前已下载，但当前不在你的库中。",
             "alreadyInLibrary": "已存在于库中",
             "autoOrganizedPath": "【已按路径模板自动整理】",
+            "fileSelection": {
+                "title": "选择文件格式",
+                "files": "个文件",
+                "select": "选择文件"
+            },
             "errors": {
                 "invalidUrl": "无效的 Civitai URL 格式",
                 "noVersions": "此模型没有可用版本"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "无配方 ID",
             "sendToWorkflowFailed": "发送配方到工作流失败：{message}",
             "copyFailed": "复制配方语法出错：{message}",
+            "createError": "创建配方时出错：{message}",
+            "createFailed": "创建配方失败：{error}",
+            "createMissingData": "缺少创建配方所需的数据",
+            "created": "配方创建成功",
             "noMissingLoras": "没有缺失的 LoRA 可下载",
             "missingLorasInfoFailed": "获取缺失 LoRA 信息失败",
             "preparingForDownloadFailed": "准备下载 LoRA 时出错",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "浏览目录失败：{message}",
             "batchImportDirectorySelected": "已选择目录：{path}",
             "noRecipesSelected": "未选择任何配方",
+            "repairBulkComplete": "修复完成：{repaired} 个已修复，{skipped} 个已跳过（共 {total} 个）",
+            "repairBulkSkipped": "所选 {total} 个配方无需修复",
+            "repairBulkFailed": "修复所选配方失败：{message}",
             "noMissingLorasInSelection": "在选定的配方中未找到缺失的 LoRAs",
             "noLoraRootConfigured": "未配置 LoRA 根目录。请在设置中设置默认的 LoRA 根目录。"
         },

locales/zh-TW.json

@@ -689,6 +689,7 @@
             "setContentRating": "為全部設定內容分級",
             "copyAll": "複製全部語法",
             "refreshAll": "刷新全部 metadata",
+            "repairMetadata": "修復所選中元數據",
             "checkUpdates": "檢查所選更新",
             "moveAll": "全部移動到資料夾",
             "autoOrganize": "自動整理所選模型",
@@ -962,6 +963,13 @@
         "empty": {
             "noFolders": "未找到資料夾",
             "dragHint": "將項目拖到此處以建立資料夾"
+        },
+        "folderUpdateCheck": {
+            "label": "檢查此資料夾的更新",
+            "loading": "正在檢查此資料夾中的{type}更新...",
+            "success": "在此資料夾中找到 {count} 個{type}更新",
+            "none": "此資料夾中的所有{type}都是最新版本",
+            "error": "檢查資料夾{type}更新失敗: {message}"
         }
     },
     "statistics": {
@@ -1030,6 +1038,11 @@
             "downloadedTooltip": "先前已下載，但目前不在你的庫中。",
             "alreadyInLibrary": "已在庫存",
             "autoOrganizedPath": "[依路徑範本自動整理]",
+            "fileSelection": {
+                "title": "選擇檔案格式",
+                "files": "個檔案",
+                "select": "選擇檔案"
+            },
             "errors": {
                 "invalidUrl": "Civitai 網址格式無效",
                 "noVersions": "此模型無可用版本"
@@ -1655,6 +1668,10 @@
             "noRecipeId": "無配方 ID",
             "sendToWorkflowFailed": "傳送配方到工作流失敗：{message}",
             "copyFailed": "複製配方語法錯誤：{message}",
+            "createError": "建立配方時發生錯誤：{message}",
+            "createFailed": "建立配方失敗：{error}",
+            "createMissingData": "缺少建立配方所需的資料",
+            "created": "配方建立成功",
             "noMissingLoras": "無缺少的 LoRA 可下載",
             "missingLorasInfoFailed": "取得缺少 LoRA 資訊失敗",
             "preparingForDownloadFailed": "準備下載 LoRA 時發生錯誤",
@@ -1693,6 +1710,9 @@
             "batchImportBrowseFailed": "瀏覽目錄失敗：{message}",
             "batchImportDirectorySelected": "已選擇目錄：{path}",
             "noRecipesSelected": "未選取任何食譜",
+            "repairBulkComplete": "修復完成：{repaired} 個已修復，{skipped} 個已跳過（共 {total} 個）",
+            "repairBulkSkipped": "所選 {total} 個配方無需修復",
+            "repairBulkFailed": "修復所選配方失敗：{message}",
             "noMissingLorasInSelection": "在選取的食譜中未找到缺失的 LoRAs",
             "noLoraRootConfigured": "未配置 LoRA 根目錄。請在設定中設定預設的 LoRA 根目錄。"
         },

py/recipes/base.py

@@ -7,7 +7,7 @@ import re
 from typing import Dict, List, Any, Optional, Tuple
 from abc import ABC, abstractmethod
 from ..config import config
-from ..utils.constants import VALID_LORA_TYPES
+from ..utils.constants import VALID_LORA_TYPES, VALID_CHECKPOINT_SUB_TYPES
 from ..utils.civitai_utils import rewrite_preview_url
 
 logger = logging.getLogger(__name__)
@@ -58,9 +58,52 @@ class RecipeMetadataParser(ABC):
             civitai_info, error_msg = civitai_info_tuple if isinstance(civitai_info_tuple, tuple) else (civitai_info_tuple, None)
             
             if not civitai_info or error_msg == "Model not found":
-                # Model not found or deleted
-                lora_entry['isDeleted'] = True
-                lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
+                # CivitAI may fail to resolve a hash that is still being
+                # computed (known CivitAI issue). Before marking as deleted,
+                # try to reconcile with a local model that has the same
+                # filename and matching AutoV3 hash.
+                reconciled = False
+                file_name = lora_entry.get("file_name")
+                if file_name and recipe_scanner and hash_value:
+                    lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
+                    if lora_scanner:
+                        try:
+                            # Local import to avoid circular dependency:
+                            # base.py → file_utils → settings_manager → ...
+                            #  → recipe_scanner → enrichment → base.py
+                            from ..utils.file_utils import calculate_autov3  # fmt: skip
+                            cache = await lora_scanner.get_cached_data()
+                            for item in getattr(cache, "raw_data", []):
+                                if item.get("file_name") == file_name:
+                                    local_path = item.get("file_path")
+                                    if local_path and os.path.exists(local_path):
+                                        local_autov3 = calculate_autov3(local_path)
+                                        if local_autov3 and local_autov3 == hash_value:
+                                            lora_entry["existsLocally"] = True
+                                            lora_entry["localPath"] = local_path
+                                            lora_entry["hash"] = item.get("sha256", hash_value)
+                                            if "preview_url" in item:
+                                                lora_entry["thumbnailUrl"] = config.get_preview_static_url(item["preview_url"])
+                                            civ = item.get("civitai") or {}
+                                            if isinstance(civ, dict):
+                                                if civ.get("id") is not None:
+                                                    lora_entry["id"] = civ["id"]
+                                                if civ.get("modelId") is not None:
+                                                    lora_entry["modelId"] = civ["modelId"]
+                                                if civ.get("name"):
+                                                    lora_entry["version"] = civ["name"]
+                                                # model_name is the CivitAI model display
+                                                # name stored directly in the cache column.
+                                                cached_model_name = item.get("model_name")
+                                                if cached_model_name:
+                                                    lora_entry["name"] = cached_model_name
+                                            reconciled = True
+                                            break
+                        except Exception:
+                            pass
+                if not reconciled:
+                    lora_entry['isDeleted'] = True
+                    lora_entry['thumbnailUrl'] = '/loras_static/images/no-preview.png'
                 return lora_entry
                 
             # Get model type and validate
@@ -173,6 +216,20 @@ class RecipeMetadataParser(ABC):
                 checkpoint['isDeleted'] = True
                 return checkpoint
 
+            # Validate that the model type is actually a checkpoint.
+            # Unlike populate_lora_from_civitai which has this check,
+            # this function was missing type validation — allowing LoRA
+            # version data to be saved as the recipe's checkpoint when the
+            # wrong version ID was passed downstream (fixed in v2.7+).
+            model_type = civitai_data.get('model', {}).get('type', '').lower()
+            if model_type not in VALID_CHECKPOINT_SUB_TYPES:
+                logger.warning(
+                    f"Cannot populate checkpoint: model version {civitai_data.get('id')} "
+                    f"has type '{model_type}', expected one of {VALID_CHECKPOINT_SUB_TYPES}. "
+                    f"Skipping checkpoint enrichment."
+                )
+                return checkpoint
+
             if 'model' in civitai_data and 'name' in civitai_data['model']:
                 checkpoint['name'] = civitai_data['model']['name']
 

py/recipes/enrichment.py

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

py/recipes/parsers/civitai_image.py

@@ -6,6 +6,7 @@ from typing import Dict, Any, Union
 from ..base import RecipeMetadataParser
 from ..constants import GEN_PARAM_KEYS
 from ...services.metadata_service import get_default_metadata_provider
+from ...config import config
 
 logger = logging.getLogger(__name__)
 
@@ -73,7 +74,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         return False
 
     async def parse_metadata(  # type: ignore[override]
-        self, user_comment, recipe_scanner=None, civitai_client=None
+        self, user_comment, recipe_scanner=None, civitai_client=None,
+        local_cache: dict[str, Any] | None = None,
     ) -> Dict[str, Any]:
         """Parse metadata from Civitai image format
 
@@ -81,6 +83,8 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
             user_comment: The metadata from the image (dict)
             recipe_scanner: Optional recipe scanner service
             civitai_client: Optional Civitai API client (deprecated, use metadata_provider instead)
+            local_cache: Optional dict mapping sha256/autov3 hash → scanner cache item.
+                         When provided, matching models skip CivitAI API calls.
 
         Returns:
             Dict containing parsed recipe data
@@ -185,8 +189,77 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
             # Process standard resources array
             if "resources" in metadata and isinstance(metadata["resources"], list):
                 for resource in metadata["resources"]:
+                    resource_type = resource.get("type", "lora")
+
+                    # Track resources with type "model" — these are checkpoint models.
+                    # The resources array is the most reliable source for checkpoint
+                    # identification because it has an explicit type field and hash,
+                    # unlike modelVersionIds which is a flat list with no type info.
+                    if resource_type == "model":
+                        checkpoint_entry = {
+                            "id": 0,
+                            "modelId": 0,
+                            "name": resource.get("name", "Unknown Model"),
+                            "version": "",
+                            "type": resource.get("type", "model"),
+                            "existsLocally": False,
+                            "localPath": None,
+                            "file_name": resource.get("name", ""),
+                            "hash": resource.get("hash", "") or "",
+                            "thumbnailUrl": "/loras_static/images/no-preview.png",
+                            "baseModel": "",
+                            "size": 0,
+                            "downloadUrl": "",
+                            "isDeleted": False,
+                        }
+
+                        # Try to look up base model from the checkpoint hash
+                        cp_hash = checkpoint_entry.get("hash")
+                        if cp_hash and metadata_provider:
+                            local_cached = local_cache.get(cp_hash) if local_cache else None
+                            if local_cached:
+                                self._populate_entry_from_cache(
+                                    checkpoint_entry, local_cached
+                                )
+                                bm = checkpoint_entry.get("baseModel", "")
+                                if bm and not result["base_model"]:
+                                    result["base_model"] = bm
+                            else:
+                                try:
+                                    civitai_info = (
+                                        await metadata_provider.get_model_by_hash(
+                                            cp_hash
+                                        )
+                                    )
+                                    civitai_data, error_msg = (
+                                        (civitai_info, None)
+                                        if not isinstance(civitai_info, tuple)
+                                        else civitai_info
+                                    )
+                                    if civitai_data and error_msg != "Model not found":
+                                        if 'model' in civitai_data and 'name' in civitai_data['model']:
+                                            checkpoint_entry['name'] = civitai_data['model']['name']
+                                        checkpoint_entry['id'] = civitai_data.get('id', 0)
+                                        checkpoint_entry['modelId'] = civitai_data.get('modelId', 0)
+                                        if 'name' in civitai_data:
+                                            checkpoint_entry['version'] = civitai_data['name']
+                                        base_model = civitai_data.get('baseModel', '')
+                                        if base_model:
+                                            checkpoint_entry['baseModel'] = base_model
+                                            if not result['base_model']:
+                                                result['base_model'] = base_model
+                                except Exception as e:
+                                    logger.error(
+                                        f"Error fetching checkpoint info for hash "
+                                        f"{cp_hash}: {e}"
+                                    )
+
+                        if result["model"] is None:
+                            result["model"] = checkpoint_entry
+                        continue
+
                     # Modified to process resources without a type field as potential LoRAs
-                    if resource.get("type", "lora") == "lora":
+                    if resource_type == "lora":
                         lora_hash = resource.get("hash", "")
 
                         # Try to get hash from the hashes field if not present in resource
@@ -220,34 +293,45 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
                         }
 
                         # Try to get info from Civitai if hash is available
-                        if lora_entry["hash"] and metadata_provider:
-                            try:
-                                civitai_info = (
-                                    await metadata_provider.get_model_by_hash(lora_hash)
+                        if lora_hash and metadata_provider:
+                            local_cached = local_cache.get(lora_hash) if local_cache else None
+                            if local_cached:
+                                self._populate_entry_from_cache(
+                                    lora_entry, local_cached
                                 )
-
-                                populated_entry = await self.populate_lora_from_civitai(
-                                    lora_entry,
-                                    civitai_info,
-                                    recipe_scanner,
-                                    base_model_counts,
-                                    lora_hash,
-                                )
-
-                                if populated_entry is None:
-                                    continue  # Skip invalid LoRA types
-
-                                lora_entry = populated_entry
-
-                                # If we have a version ID from Civitai, track it for deduplication
-                                if "id" in lora_entry and lora_entry["id"]:
+                                # Track by version ID for deduplication
+                                if lora_entry.get("id"):
                                     added_loras[str(lora_entry["id"])] = len(
                                         result["loras"]
                                     )
-                            except Exception as e:
-                                logger.error(
-                                    f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
-                                )
+                            else:
+                                try:
+                                    civitai_info = (
+                                        await metadata_provider.get_model_by_hash(lora_hash)
+                                    )
+
+                                    populated_entry = await self.populate_lora_from_civitai(
+                                        lora_entry,
+                                        civitai_info,
+                                        recipe_scanner,
+                                        base_model_counts,
+                                        lora_hash,
+                                    )
+
+                                    if populated_entry is None:
+                                        continue  # Skip invalid LoRA types
+
+                                    lora_entry = populated_entry
+
+                                    # If we have a version ID from Civitai, track it for deduplication
+                                    if "id" in lora_entry and lora_entry["id"]:
+                                        added_loras[str(lora_entry["id"])] = len(
+                                            result["loras"]
+                                        )
+                                except Exception as e:
+                                    logger.error(
+                                        f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
+                                    )
 
                         # Track by hash if we have it
                         if lora_hash:
@@ -625,3 +709,41 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
         except Exception as e:
             logger.error(f"Error parsing Civitai image metadata: {e}", exc_info=True)
             return {"error": str(e), "loras": []}
+
+    @staticmethod
+    def _populate_entry_from_cache(
+        entry: dict[str, Any],
+        cache_item: dict[str, Any],
+    ) -> None:
+        """Fill a lora/checkpoint entry from a scanner cache item.
+
+        Avoids CivitAI API calls for models that exist locally.
+        Mirrors the population logic in
+        ``RecipeMetadataParser.populate_lora_from_civitai()`` but operates
+        entirely on cached data.
+        """
+        civ = cache_item.get("civitai") or {}
+        if isinstance(civ, dict):
+            if civ.get("id") is not None:
+                entry["id"] = civ["id"]
+            if civ.get("modelId") is not None:
+                entry["modelId"] = civ["modelId"]
+            if civ.get("name"):
+                entry["version"] = civ["name"]
+            cached_name = cache_item.get("model_name")
+            if cached_name:
+                entry["name"] = cached_name
+        entry["existsLocally"] = True
+        local_path = cache_item.get("file_path")
+        if local_path:
+            entry["localPath"] = local_path
+        sha256 = cache_item.get("sha256")
+        if sha256:
+            entry["hash"] = sha256
+        if "preview_url" in cache_item:
+            entry["thumbnailUrl"] = config.get_preview_static_url(
+                cache_item["preview_url"]
+            )
+        base_model = cache_item.get("base_model", "")
+        if base_model:
+            entry["baseModel"] = base_model

py/routes/handlers/model_handlers.py

@@ -1472,6 +1472,21 @@ class ModelDownloadHandler:
             )
             return web.Response(status=500, text=str(exc))
 
+    async def skip_download_get(self, request: web.Request) -> web.Response:
+        try:
+            download_id = request.query.get("download_id")
+            if not download_id:
+                return web.json_response(
+                    {"success": False, "error": "Download ID is required"}, status=400
+                )
+            result = await self._download_coordinator.skip_download(download_id)
+            return web.json_response(result)
+        except Exception as exc:
+            self._logger.error(
+                "Error skipping download via GET: %s", exc, exc_info=True
+            )
+            return web.json_response({"success": False, "error": str(exc)}, status=500)
+
     async def cancel_download_get(self, request: web.Request) -> web.Response:
         try:
             download_id = request.query.get("download_id")
@@ -1960,6 +1975,10 @@ class ModelUpdateHandler:
         if target_model_ids:
             target_model_ids = sorted(set(target_model_ids))
 
+        folder_path: Optional[str] = payload.get("folder_path")
+        if folder_path is not None and not isinstance(folder_path, str):
+            folder_path = None
+
         provider = await self._get_civitai_provider()
         if provider is None:
             return web.json_response(
@@ -1974,6 +1993,7 @@ class ModelUpdateHandler:
                 provider,
                 force_refresh=force_refresh,
                 target_model_ids=target_model_ids or None,
+                folder_path=folder_path,
             )
             if self._service.scanner.is_cancelled():
                 return web.json_response(
@@ -2561,6 +2581,7 @@ class ModelHandlerSet:
             "download_model": self.download.download_model,
             "download_model_get": self.download.download_model_get,
             "cancel_download_get": self.download.cancel_download_get,
+            "skip_download_get": self.download.skip_download_get,
             "pause_download_get": self.download.pause_download_get,
             "resume_download_get": self.download.resume_download_get,
             "get_download_progress": self.download.get_download_progress,

py/routes/handlers/recipe_handlers.py

@@ -16,7 +16,7 @@ from aiohttp import web
 
 from ...config import config
 from ...services.server_i18n import server_i18n as default_server_i18n
-from ...services.settings_manager import SettingsManager
+from ...services.settings_manager import SettingsManager, get_settings_manager
 from ...services.recipes import (
     RecipeAnalysisService,
     RecipeDownloadError,
@@ -26,7 +26,12 @@ from ...services.recipes import (
     RecipeValidationError,
 )
 from ...services.metadata_service import get_default_metadata_provider
-from ...utils.civitai_utils import extract_civitai_image_id, rewrite_preview_url
+from ...utils.civitai_utils import (
+    build_civitai_image_page_url,
+    extract_civitai_image_id,
+    extract_civitai_image_id_from_cdn_url,
+    rewrite_preview_url,
+)
 from ...utils.exif_utils import ExifUtils
 from ...recipes.merger import GenParamsMerger
 from ...recipes.enrichment import RecipeEnricher
@@ -87,6 +92,7 @@ class RecipeHandlerSet:
             "repair_recipes": self.management.repair_recipes,
             "cancel_repair": self.management.cancel_repair,
             "repair_recipe": self.management.repair_recipe,
+            "repair_recipes_bulk": self.management.repair_recipes_bulk,
             "get_repair_progress": self.management.get_repair_progress,
             "start_batch_import": self.batch_import.start_batch_import,
             "get_batch_import_progress": self.batch_import.get_batch_import_progress,
@@ -95,6 +101,7 @@ class RecipeHandlerSet:
             "browse_directory": self.batch_import.browse_directory,
             "check_image_exists": self.management.check_image_exists,
             "import_from_url": self.management.import_from_url,
+            "create_from_example": self.management.create_from_example,
         }
 
 
@@ -460,7 +467,11 @@ class RecipeQueryHandler:
             if recipe_scanner is None:
                 raise RuntimeError("Recipe scanner unavailable")
 
-            self._logger.info("Manually triggering recipe cache rebuild")
+            full_rebuild = request.query.get("full_rebuild", "true").lower() == "true"
+            self._logger.info(
+                "Manually triggering recipe cache %s",
+                "full rebuild" if full_rebuild else "refresh",
+            )
             await recipe_scanner.get_cached_data(force_refresh=True)
             return web.json_response(
                 {"success": True, "message": "Recipe cache refreshed successfully"}
@@ -706,6 +717,69 @@ class RecipeManagementHandler:
             self._logger.error("Error cancelling recipe repair: %s", exc, exc_info=True)
             return web.json_response({"success": False, "error": str(exc)}, status=500)
 
+    async def repair_recipes_bulk(self, request: web.Request) -> web.Response:
+        """Bulk repair metadata for multiple recipes by their IDs.
+
+        Accepts a JSON body with a "recipe_ids" array and iterates
+        repair_recipe_by_id over each entry, collecting statistics.
+        """
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                return web.json_response(
+                    {"success": False, "error": "Recipe scanner unavailable"},
+                    status=503,
+                )
+
+            data = await request.json()
+            recipe_ids = data.get("recipe_ids", [])
+            if not recipe_ids:
+                return web.json_response(
+                    {"success": False, "error": "recipe_ids are required"},
+                    status=400,
+                )
+
+            total = len(recipe_ids)
+            repaired = 0
+            skipped = 0
+            errors = 0
+            recipes = []
+
+            for recipe_id in recipe_ids:
+                try:
+                    result = await recipe_scanner.repair_recipe_by_id(recipe_id)
+                    if result.get("success"):
+                        repaired += result.get("repaired", 0)
+                        skipped += result.get("skipped", 0)
+                        if result.get("recipe"):
+                            recipes.append(result["recipe"])
+                    else:
+                        errors += 1
+                except RecipeNotFoundError:
+                    skipped += 1
+                except Exception as exc:
+                    self._logger.error(
+                        "Error repairing recipe %s: %s", recipe_id, exc
+                    )
+                    errors += 1
+
+            return web.json_response({
+                "success": True,
+                "total": total,
+                "repaired": repaired,
+                "skipped": skipped,
+                "errors": errors,
+                "recipes": recipes,
+            })
+        except Exception as exc:
+            self._logger.error(
+                "Error performing bulk repair: %s", exc, exc_info=True
+            )
+            return web.json_response(
+                {"success": False, "error": str(exc)}, status=500
+            )
+
     async def repair_recipe(self, request: web.Request) -> web.Response:
         try:
             await self._ensure_dependencies_ready()
@@ -911,6 +985,9 @@ class RecipeManagementHandler:
             civitai_model = civitai_parsed.get("model")
             if civitai_model and not metadata.get("checkpoint"):
                 metadata["checkpoint"] = civitai_model
+            civitai_base_model = civitai_parsed.get("base_model")
+            if civitai_base_model and not metadata.get("base_model"):
+                metadata["base_model"] = civitai_base_model
         elif parsed_embedded:
             parsed_loras = parsed_embedded.get("loras")
             if parsed_loras and not metadata.get("loras"):
@@ -918,6 +995,8 @@ class RecipeManagementHandler:
             parsed_model = parsed_embedded.get("model")
             if parsed_model and not metadata.get("checkpoint"):
                 metadata["checkpoint"] = parsed_model
+            if parsed_embedded.get("base_model") and not metadata.get("base_model"):
+                metadata["base_model"] = parsed_embedded["base_model"]
 
         civitai_client = self._civitai_client_getter()
         await RecipeEnricher.enrich_recipe(
@@ -1293,11 +1372,18 @@ class RecipeManagementHandler:
                     image_info.get("meta") if civitai_image_id and image_info else None
                 )
                 if civitai_image_id and image_info:
+                    # modelVersionId (singular) — the primary version for this
+                    # image on CivitAI.  May be absent, or may *not* be the
+                    # checkpoint (e.g. when the image was generated with a LoRA
+                    # as the primary subject).  When absent, DO NOT fall back to
+                    # modelVersionIds[0] — that array mixes checkpoints, LoRAs,
+                    # and other model version IDs without ordering guarantees.
+                    # The downstream enrichment flow will find the real
+                    # checkpoint via meta.resources (type:"model" hash) or
+                    # meta.civitaiResources (type:"checkpoint" version ID), so
+                    # leaving model_ver_id as None is safe and avoids the bug
+                    # where a LoRA version ID was treated as the checkpoint.
                     model_ver_id = image_info.get("modelVersionId")
-                    if not model_ver_id:
-                        ids = image_info.get("modelVersionIds")
-                        if isinstance(ids, list) and ids:
-                            model_ver_id = ids[0]
 
                     # Inject root-level modelVersionIds into meta so downstream
                     # parsers (CivitaiApiMetadataParser) can discover ALL resources
@@ -1418,25 +1504,28 @@ class RecipeManagementHandler:
             if not image_url:
                 raise RecipeValidationError("Missing required field: image_url")
 
+            force = request.query.get("force", "false").lower() == "true"
+
             image_id = extract_civitai_image_id(image_url)
             if not image_id:
                 raise RecipeValidationError(
                     "Could not extract Civitai image ID from URL"
                 )
 
-            # Check for duplicate (fast, before acquiring semaphore)
-            cache = await recipe_scanner.get_cached_data()
-            for recipe in getattr(cache, "raw_data", []):
-                source = recipe.get("source_path")
-                if source:
-                    existing_id = extract_civitai_image_id(source)
-                    if existing_id == image_id:
-                        return web.json_response({
-                            "success": True,
-                            "recipe_id": recipe.get("id"),
-                            "name": recipe.get("title", ""),
-                            "already_exists": True,
-                        })
+            # Check for duplicate (fast, before acquiring semaphore), unless force
+            if not force:
+                cache = await recipe_scanner.get_cached_data()
+                for recipe in getattr(cache, "raw_data", []):
+                    source = recipe.get("source_path")
+                    if source:
+                        existing_id = extract_civitai_image_id(source)
+                        if existing_id == image_id:
+                            return web.json_response({
+                                "success": True,
+                                "recipe_id": recipe.get("id"),
+                                "name": recipe.get("title", ""),
+                                "already_exists": True,
+                            })
 
             async with self._import_semaphore:
                 return await self._do_import_from_url(image_url, recipe_scanner)
@@ -1542,6 +1631,9 @@ class RecipeManagementHandler:
             civitai_model = civitai_parsed.get("model")
             if civitai_model and not metadata.get("checkpoint"):
                 metadata["checkpoint"] = civitai_model
+            civitai_base_model = civitai_parsed.get("base_model")
+            if civitai_base_model and not metadata.get("base_model"):
+                metadata["base_model"] = civitai_base_model
         elif parsed_embedded:
             parsed_loras = parsed_embedded.get("loras")
             if parsed_loras and not metadata.get("loras"):
@@ -1549,6 +1641,8 @@ class RecipeManagementHandler:
             parsed_model = parsed_embedded.get("model")
             if parsed_model and not metadata.get("checkpoint"):
                 metadata["checkpoint"] = parsed_model
+            if parsed_embedded.get("base_model") and not metadata.get("base_model"):
+                metadata["base_model"] = parsed_embedded["base_model"]
 
         civitai_client = self._civitai_client_getter()
         await RecipeEnricher.enrich_recipe(
@@ -1580,6 +1674,272 @@ class RecipeManagementHandler:
         )
         return web.json_response(result.payload, status=result.status)
 
+    async def create_from_example(self, request: web.Request) -> web.Response:
+        """Create a recipe from a model's example image using cached metadata.
+
+        Uses the image's meta data (already cached in .metadata.json from the
+        CivitAI model-versions API) to create a recipe without additional
+        CivitAI API calls.
+
+        If the image metadata doesn't contain any resources of the parent
+        model's type (LoRA-type or Checkpoint), the parent model is
+        auto-populated as a fallback.
+
+        Request body:
+            image_data (dict): The full image object from model-versions API
+                (includes meta, additionalResources, url, etc.)
+            model_hash (str): SHA256 hash of the parent model
+            model_name (str): Filename of the parent model
+            model_type (str): Page type (``"loras"``, ``"checkpoints"``, etc.)
+            local_image_path (str, optional): Local filesystem path to read
+                the image bytes for the recipe preview
+        """
+        try:
+            await self._ensure_dependencies_ready()
+            recipe_scanner = self._recipe_scanner_getter()
+            if recipe_scanner is None:
+                raise RuntimeError("Recipe scanner unavailable")
+
+            data = await request.json()
+            image_data = data.get("image_data")
+            model_hash = data.get("model_hash")
+            model_name = data.get("model_name")
+            model_type = data.get("model_type", "")
+
+            if not image_data or not model_hash or not model_name:
+                raise RecipeValidationError(
+                    "Missing required fields: image_data, model_hash, model_name"
+                )
+
+            # Merge nested meta into top level so the parser finds everything.
+            # CivitaiApiMetadataParser expects prompt, seed, resources, etc.
+            # at the top level or wrapped under a "meta" key.
+            inner_meta = image_data.get("meta") or {}
+            parsed_input = {**image_data, **inner_meta}
+            parsed_input.pop("meta", None)
+
+            # Build a local cache of {hash → cache_item} so the parser can
+            # skip CivitAI API calls for models that exist on disk.
+            local_cache: Dict[str, Dict[str, Any]] = {}
+            lora_scanner = getattr(recipe_scanner, "_lora_scanner", None)
+            if lora_scanner and model_hash:
+                try:
+                    parent_cache_data = await lora_scanner.get_cached_data()
+                    for item in getattr(parent_cache_data, "raw_data", []):
+                        if item.get("sha256", "").lower() == model_hash.lower():
+                            local_cache[model_hash.lower()] = item
+                            # Compute AutoV3 so the parser can also match on
+                            # that hash type (CivitAI metadata resources use
+                            # AutoV3).
+                            file_path = item.get("file_path")
+                            if file_path and os.path.exists(file_path):
+                                try:
+                                    from ...utils.file_utils import (
+                                        calculate_autov3,
+                                    )
+                                    autov3 = calculate_autov3(file_path)
+                                    if autov3:
+                                        local_cache[autov3.lower()] = item
+                                except Exception:
+                                    pass
+                            break
+                except Exception:
+                    pass
+
+            parser = self._analysis_service._recipe_parser_factory.create_parser(
+                parsed_input
+            )
+            if not parser:
+                raise RecipeValidationError("Unable to parse image metadata")
+
+            from ...recipes.parsers.civitai_image import CivitaiApiMetadataParser
+
+            if isinstance(parser, CivitaiApiMetadataParser):
+                parsed = await parser.parse_metadata(
+                    parsed_input,
+                    recipe_scanner=recipe_scanner,
+                    local_cache=local_cache,
+                )
+            else:
+                parsed = await parser.parse_metadata(
+                    parsed_input, recipe_scanner=recipe_scanner
+                )
+
+            loras = list(parsed.get("loras") or [])
+            checkpoint = parsed.get("model")
+            is_lora_type = model_type.startswith("lora")
+            is_ckpt_type = model_type.startswith("checkpoint")
+
+            # Extract parent model metadata from local_cache (used below to
+            # reconcile isDeleted entries and enrich auto-populated ones).
+            parent_civitai_id: int | None = None
+            parent_model_id: int | None = None
+            parent_version_name: str | None = None
+            parent_model_name: str | None = None
+            # Prefer sha256 key; fall back to any cached entry.
+            parent_item = local_cache.get(model_hash.lower()) if model_hash else None
+            if parent_item is None and local_cache:
+                parent_item = next(iter(local_cache.values()))
+            if parent_item:
+                civ = parent_item.get("civitai") or {}
+                if isinstance(civ, dict):
+                    parent_civitai_id = civ.get("id")
+                    parent_model_id = civ.get("modelId")
+                    parent_version_name = civ.get("name")
+                parent_model_name = parent_item.get("model_name")
+
+            # Reconcile isDeleted entries against the parent model.
+            # When the CivitAI hash lookup fails (known issue — hashes not
+            # yet computed), the parser marks the entry isDeleted even though
+            # the model exists locally.
+            if is_lora_type:
+                for lora in loras:
+                    if lora.get("isDeleted") and lora.get("file_name") == model_name:
+                        lora["isDeleted"] = False
+                        lora["existsLocally"] = True
+                        lora["hash"] = model_hash
+                        if parent_civitai_id is not None:
+                            lora["id"] = parent_civitai_id
+                        if parent_model_id is not None:
+                            lora["modelId"] = parent_model_id
+                        if parent_version_name is not None:
+                            lora["version"] = parent_version_name
+                        if parent_model_name is not None:
+                            lora["name"] = parent_model_name
+            elif is_ckpt_type and checkpoint and checkpoint.get("isDeleted"):
+                if checkpoint.get("file_name") == model_name:
+                    checkpoint["isDeleted"] = False
+                    checkpoint["existsLocally"] = True
+                    checkpoint["hash"] = model_hash
+                    if parent_civitai_id is not None:
+                        checkpoint["id"] = parent_civitai_id
+                    if parent_model_id is not None:
+                        checkpoint["modelId"] = parent_model_id
+                    if parent_version_name is not None:
+                        checkpoint["version"] = parent_version_name
+
+            # Auto-populate parent model only when the image metadata didn't
+            # contain any resources of that type.
+            if is_lora_type and not loras:
+                lora_entry = {
+                    "name": model_name,
+                    "type": "lora",
+                    "weight": 1.0,
+                    "hash": model_hash,
+                    "existsLocally": True,
+                    "localPath": None,
+                    "file_name": model_name,
+                    "thumbnailUrl": "/loras_static/images/no-preview.png",
+                    "baseModel": parsed.get("base_model", ""),
+                    "size": 0,
+                    "downloadUrl": "",
+                    "isDeleted": False,
+                }
+                if parent_civitai_id is not None:
+                    lora_entry["id"] = parent_civitai_id
+                if parent_model_id is not None:
+                    lora_entry["modelId"] = parent_model_id
+                if parent_version_name is not None:
+                    lora_entry["version"] = parent_version_name
+                if parent_model_name is not None:
+                    lora_entry["name"] = parent_model_name
+                loras.insert(0, lora_entry)
+            elif is_ckpt_type and not checkpoint:
+                checkpoint = {
+                    "name": model_name,
+                    "type": "checkpoint",
+                    "hash": model_hash,
+                    "file_name": model_name,
+                    "existsLocally": True,
+                    "baseModel": parsed.get("base_model", ""),
+                    "isDeleted": False,
+                }
+                if parent_civitai_id is not None:
+                    checkpoint["id"] = parent_civitai_id
+                if parent_model_id is not None:
+                    checkpoint["modelId"] = parent_model_id
+                if parent_version_name is not None:
+                    checkpoint["version"] = parent_version_name
+                if parent_model_name is not None:
+                    checkpoint["name"] = parent_model_name
+
+            image_url = image_data.get("url") or ""
+            image_id = extract_civitai_image_id_from_cdn_url(image_url)
+            settings_mgr = get_settings_manager()
+            civitai_host = settings_mgr.get("civitai_host") if settings_mgr else None
+            page_url = build_civitai_image_page_url(image_id, host=civitai_host) or image_url
+
+            recipe_metadata: dict[str, Any] = {
+                "base_model": parsed.get("base_model") or "",
+                "loras": loras,
+                "gen_params": parsed.get("gen_params") or {},
+                "source_path": page_url,
+            }
+            nsfw_level = image_data.get("nsfwLevel")
+            if isinstance(nsfw_level, int):
+                recipe_metadata["preview_nsfw_level"] = nsfw_level
+            if checkpoint:
+                recipe_metadata["checkpoint"] = checkpoint
+
+            image_bytes: bytes | None = None
+            extension: str | None = None
+            local_image_path = data.get("local_image_path")
+            if local_image_path and os.path.exists(local_image_path):
+                with open(local_image_path, "rb") as f:
+                    image_bytes = f.read()
+                ext = os.path.splitext(local_image_path)[1].lower()
+                if ext in (".jpg", ".jpeg", ".png", ".webp", ".gif"):
+                    extension = ext
+            elif image_data.get("url"):
+                try:
+                    downloader = await self._downloader_factory()
+                    url = image_data["url"]
+                    tmp = tempfile.NamedTemporaryFile(delete=False)
+                    tmp.close()
+                    success, result = await downloader.download_file(
+                        url, tmp.name, use_auth=False
+                    )
+                    if success:
+                        with open(tmp.name, "rb") as f:
+                            image_bytes = f.read()
+                        url_path = url.split("?")[0].split("#")[0]
+                        ext = os.path.splitext(url_path)[1].lower()
+                        if ext:
+                            extension = ext
+                    if os.path.exists(tmp.name):
+                        os.unlink(tmp.name)
+                except Exception as exc:
+                    self._logger.warning(
+                        "Failed to download image for recipe: %s", exc
+                    )
+
+            prompt = (
+                (parsed.get("gen_params") or {}).get("prompt") or ""
+            )
+            if prompt:
+                name = " ".join(str(prompt).split()[:10])
+            else:
+                name = f"Recipe from {model_name}"
+
+            save_result = await self._persistence_service.save_recipe(
+                recipe_scanner=recipe_scanner,
+                image_bytes=image_bytes,
+                image_base64=None,
+                name=name,
+                tags=[],
+                metadata=recipe_metadata,
+                extension=extension,
+            )
+            return web.json_response(save_result.payload, status=save_result.status)
+
+        except RecipeValidationError as exc:
+            return web.json_response({"error": str(exc)}, status=400)
+        except Exception as exc:
+            self._logger.error(
+                "Error creating recipe from example: %s", exc, exc_info=True
+            )
+            return web.json_response({"error": str(exc)}, status=500)
+
 
 class RecipeAnalysisHandler:
     """Analyze images to extract recipe metadata."""

py/routes/model_route_registrar.py

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

py/routes/recipe_route_registrar.py

@@ -58,6 +58,7 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
     RouteDefinition("POST", "/api/lm/recipes/repair", "repair_recipes"),
     RouteDefinition("POST", "/api/lm/recipes/cancel-repair", "cancel_repair"),
     RouteDefinition("POST", "/api/lm/recipe/{recipe_id}/repair", "repair_recipe"),
+    RouteDefinition("POST", "/api/lm/recipes/repair-bulk", "repair_recipes_bulk"),
     RouteDefinition("GET", "/api/lm/recipes/repair-progress", "get_repair_progress"),
     RouteDefinition("POST", "/api/lm/recipes/batch-import/start", "start_batch_import"),
     RouteDefinition(
@@ -74,6 +75,9 @@ ROUTE_DEFINITIONS: tuple[RouteDefinition, ...] = (
         "GET", "/api/lm/recipes/check-image-exists", "check_image_exists"
     ),
     RouteDefinition("GET", "/api/lm/recipes/import-from-url", "import_from_url"),
+    RouteDefinition(
+        "POST", "/api/lm/recipes/create-from-example", "create_from_example"
+    ),
 )
 
 

py/routes/update_routes.py

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

py/services/aria2_downloader.py

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

py/services/civarchive_client.py

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

py/services/civitai_client.py

@@ -410,6 +410,25 @@ class CivitaiClient:
             return None
 
         target_version = self._select_target_version(model_data, model_id, version_id)
+
+        # If modelVersions is empty (e.g. CivitAI cache lag for newly published
+        # models) but a specific version_id is known, fall back to fetching the
+        # version directly via the individual model-versions endpoint, then
+        # enrich it with the model-level data we already have.
+        if target_version is None and version_id is not None:
+            logger.info(
+                "modelVersions empty for model %s; falling back to direct "
+                "version lookup for %s",
+                model_id,
+                version_id,
+            )
+            version = await self._fetch_version_by_id(version_id)
+            if version:
+                self._enrich_version_with_model_data(version, model_data)
+                self._remove_comfy_metadata(version)
+                return version
+            return None
+
         if target_version is None:
             return None
 

py/services/download_coordinator.py

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

py/services/download_manager.py

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

py/services/downloaded_version_history_service.py

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

py/services/downloader.py

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

py/services/model_hash_index.py

@@ -7,6 +7,7 @@ class ModelHashIndex:
     def __init__(self):
         self._hash_to_path: Dict[str, str] = {}
         self._filename_to_hash: Dict[str, str] = {}
+        self._autov2_to_path: Dict[str, str] = {}
         # New data structures for tracking duplicates
         self._duplicate_hashes: Dict[str, List[str]] = {}  # sha256 -> list of paths
         self._duplicate_filenames: Dict[str, List[str]] = {}  # filename -> list of paths
@@ -63,6 +64,9 @@ class ModelHashIndex:
         # Add new mappings
         self._hash_to_path[sha256] = file_path
         self._filename_to_hash[filename] = sha256
+        # AutoV2 = first 10 chars of SHA256
+        if len(sha256) >= 10:
+            self._autov2_to_path[sha256[:10]] = file_path
     
     def _get_filename_from_path(self, file_path: str) -> str:
         """Extract filename without extension from path"""
@@ -157,7 +161,12 @@ class ModelHashIndex:
                 del self._duplicate_filenames[filename]
                 if filename in self._filename_to_hash:
                     del self._filename_to_hash[filename]
-    
+
+        # Remove from AutoV2 index
+        autov2_keys_to_remove = [k for k, v in self._autov2_to_path.items() if v == file_path]
+        for k in autov2_keys_to_remove:
+            del self._autov2_to_path[k]
+
     def remove_by_hash(self, sha256: str) -> None:
         """Remove entry by hash"""
         sha256 = sha256.lower()
@@ -177,6 +186,10 @@ class ModelHashIndex:
         # Remove hash-to-path mapping
         del self._hash_to_path[sha256]
         
+        autov2_key = sha256[:10]
+        if autov2_key in self._autov2_to_path:
+            del self._autov2_to_path[autov2_key]
+        
         # Update filename-to-hash and duplicate filenames for all paths
         for path_to_remove in paths_to_remove:
             fname = self._get_filename_from_path(path_to_remove)
@@ -195,13 +208,24 @@ class ModelHashIndex:
                     # If only one entry remains, it's no longer a duplicate
                     del self._duplicate_filenames[fname]
     
-    def has_hash(self, sha256: str) -> bool:
-        """Check if hash exists in index"""
-        return sha256.lower() in self._hash_to_path
-    
-    def get_path(self, sha256: str) -> Optional[str]:
-        """Get file path for a hash"""
-        return self._hash_to_path.get(sha256.lower())
+    def has_hash(self, hash_value: str) -> bool:
+        """Check if hash exists in index (SHA256 or AutoV2)"""
+        normalized = hash_value.lower()
+        if normalized in self._hash_to_path:
+            return True
+        if len(normalized) == 10:
+            return normalized in self._autov2_to_path
+        return False
+
+    def get_path(self, hash_value: str) -> Optional[str]:
+        """Get file path for a hash (SHA256 or AutoV2)"""
+        normalized = hash_value.lower()
+        path = self._hash_to_path.get(normalized)
+        if path is not None:
+            return path
+        if len(normalized) == 10:
+            return self._autov2_to_path.get(normalized)
+        return None
     
     def get_hash(self, file_path: str) -> Optional[str]:
         """Get hash for a file path"""
@@ -218,6 +242,7 @@ class ModelHashIndex:
         """Clear all entries"""
         self._hash_to_path.clear()
         self._filename_to_hash.clear()
+        self._autov2_to_path.clear()
         self._duplicate_hashes.clear()
         self._duplicate_filenames.clear()
     

py/services/model_metadata_provider.py

@@ -5,7 +5,7 @@ import logging
 import random
 from typing import Optional, Dict, Tuple, Any, List, Sequence
 from .downloader import get_downloader
-from .errors import RateLimitError
+from .errors import RateLimitError, ResourceNotFoundError
 
 try:
     from bs4 import BeautifulSoup
@@ -482,6 +482,7 @@ class FallbackMetadataProvider(ModelMetadataProvider):
         return None, "Model not found"
 
     async def get_model_versions(self, model_id: str) -> Optional[Dict]:
+        not_found_confirmed = False
         for provider, label in self._iter_providers():
             try:
                 result = await self._call_with_rate_limit(
@@ -492,8 +493,24 @@ class FallbackMetadataProvider(ModelMetadataProvider):
                 if result:
                     return result
             except RateLimitError as exc:
+                if not_found_confirmed:
+                    logger.debug(
+                        "Suppressing rate limit from %s for model %s: "
+                        "already confirmed as not found by another provider",
+                        label,
+                        model_id,
+                    )
+                    return None
                 exc.provider = exc.provider or label
                 raise exc
+            except ResourceNotFoundError:
+                not_found_confirmed = True
+                logger.debug(
+                    "Provider %s reports model %s as not found",
+                    label,
+                    model_id,
+                )
+                continue
             except Exception as e:
                 logger.debug("Provider %s failed for get_model_versions: %s", label, e)
                 continue

py/services/model_update_service.py

@@ -689,6 +689,7 @@ class ModelUpdateService:
         *,
         force_refresh: bool = False,
         target_model_ids: Optional[Sequence[int]] = None,
+        folder_path: Optional[str] = None,
     ) -> Dict[int, ModelUpdateRecord]:
         """Refresh update information for every model present in the cache."""
         scanner.reset_cancellation()
@@ -703,6 +704,7 @@ class ModelUpdateService:
         local_versions = await self._collect_local_versions(
             scanner,
             target_model_ids=target_filter,
+            folder_path=folder_path,
         )
         total_models = len(local_versions)
         if total_models == 0:
@@ -1276,6 +1278,7 @@ class ModelUpdateService:
         scanner,
         *,
         target_model_ids: Optional[Sequence[int]] = None,
+        folder_path: Optional[str] = None,
     ) -> Dict[int, List[int]]:
         cache = await scanner.get_cached_data()
         mapping: Dict[int, set[int]] = {}
@@ -1288,7 +1291,19 @@ class ModelUpdateService:
             if not target_set:
                 return {}
 
+        normalized_folder = None
+        if folder_path is not None:
+            normalized_folder = folder_path.replace("\\", "/").strip("/")
+
         for item in cache.raw_data:
+            # Apply folder filter first (cheapest check)
+            if normalized_folder is not None:
+                if not isinstance(item, dict):
+                    continue
+                item_folder = (item.get("folder") or "").replace("\\", "/").strip("/")
+                if item_folder != normalized_folder and not item_folder.startswith(normalized_folder + "/"):
+                    continue
+
             civitai = item.get("civitai") if isinstance(item, dict) else None
             if not isinstance(civitai, dict):
                 continue

py/services/recipe_scanner.py

@@ -65,7 +65,7 @@ class RecipeScanner:
             cls._instance._civitai_client = None  # Will be lazily initialized
         return cls._instance
 
-    REPAIR_VERSION = 3
+    REPAIR_VERSION = 4
 
     def __init__(
         self,
@@ -292,6 +292,32 @@ class RecipeScanner:
         if recipe.get("repair_version", 0) >= self.REPAIR_VERSION:
             return False
 
+        # 1.5 Detect and clear corrupted checkpoint (LoRA data saved as checkpoint).
+        #     A checkpoint whose modelVersionId also appears in a LoRA entry is
+        #     definitely wrong — the CivitAI import code used to pick
+        #     modelVersionIds[0] as the checkpoint, which was often a LoRA.
+        #     Clearing it lets the enrichment flow re-resolve the correct
+        #     checkpoint from CivitAI image metadata.
+        cp = recipe.get("checkpoint")
+        lora_mvids = {
+            l.get("modelVersionId")
+            for l in recipe.get("loras", [])
+            if l.get("modelVersionId")
+        }
+        if cp and cp.get("modelVersionId") and cp["modelVersionId"] in lora_mvids:
+            cp_mvid = cp["modelVersionId"]
+            logger.info(
+                "Recipe %s: checkpoint modelVersionId %s matches a LoRA — "
+                "clearing corrupted checkpoint and removing matching LoRA entry",
+                recipe.get("id"),
+                cp_mvid,
+            )
+            recipe["checkpoint"] = None
+            recipe["loras"] = [
+                l for l in recipe.get("loras", [])
+                if l.get("modelVersionId") != cp_mvid
+            ]
+
         # 2. Identification: Is repair needed?
         has_checkpoint = (
             "checkpoint" in recipe

py/services/recipes/persistence_service.py

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

py/utils/civitai_utils.py

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

py/utils/constants.py

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

py/utils/example_images_download_manager.py

@@ -397,13 +397,12 @@ class DownloadManager:
 
             models_with_hash = len(all_models_with_hash)
 
-            # Calculate pending count: check which models actually need processing
-            # A model is pending if it has a hash, is not in processed_models,
-            # and its folder doesn't exist or is empty
+            # Calculate pending count: check which models actually need processing.
+            # A model is pending if it has a hash, is not already processed or known-failed,
+            # and its folder doesn't exist or is empty.
             pending_hashes = set()
             for model_hash, model_name in all_models_with_hash:
-                if model_hash not in processed_models:
-                    # Check if model folder exists with files
+                if model_hash not in processed_models and model_hash not in failed_models:
                     model_dir = ExampleImagePathResolver.get_model_folder(
                         model_hash, active_library
                     )

py/utils/file_utils.py

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

py/utils/session_logging.py

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

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.0.8"
+version = "1.0.11"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

scripts/restore_suffixed_filenames.py

@@ -0,0 +1,404 @@
+#!/usr/bin/env python3
+"""
+Restore original filenames by removing leftover 4-char hash suffixes.
+
+When LoRA Manager's old duplicate filename resolver ran, it appended
+``-{first4ofSHA256}`` to duplicate filenames, e.g.::
+
+    my_lora.safetensors  →  my_lora-a3f7.safetensors
+
+With full-path LoRA syntax now available (``<lora:subfolder/name:1.0>``),
+these suffixes are unnecessary.  This script detects such files and, with
+your confirmation, restores their original names.
+
+The same suffix pattern is also used by the download conflict handler
+(``{name}-{hash}.{ext}``).  To avoid false positives, this script skips
+any file whose original name already exists in the same directory — those
+were likely added by a download conflict, not the old resolver.
+
+Usage::
+
+    # Detect only (dry-run, default)
+    python scripts/restore_suffixed_filenames.py
+
+    # Detect + restore (with confirmation prompt)
+    python scripts/restore_suffixed_filenames.py --apply
+
+After restoring filenames, run **Rebuild Cache** in the LoRA Manager
+Doctor panel to refresh the model cache.
+"""
+
+from __future__ import annotations
+
+import argparse
+import json
+import logging
+import os
+import re
+import sys
+from pathlib import Path
+from typing import Any
+
+logging.basicConfig(
+    level=logging.INFO,
+    format="%(message)s",
+)
+logger = logging.getLogger(__name__)
+
+APP_NAME = "ComfyUI-LoRA-Manager"
+MODEL_EXTENSIONS = {".safetensors", ".ckpt", ".pt", ".pth", ".bin"}
+PREVIEW_EXTENSIONS = {
+    ".png", ".jpg", ".jpeg", ".webp", ".gif", ".bmp",
+    ".mp4", ".webm", ".mov",
+}
+
+# Matches filenames like "my_lora-a3f7.safetensors"
+# Groups: (base_name, 4-char-hex, extension)
+_SUFFIX_RE = re.compile(r"^(.+)-([0-9a-f]{4})(\.[^.]+)$")
+
+
+# ── helpers (copied from migrate_legacy_metadata.py for consistency) ──────────
+
+
+def resolve_settings_path() -> Path:
+    repo_root = Path(__file__).parent.parent.resolve()
+    portable = repo_root / "settings.json"
+    if portable.exists():
+        payload = _load_json(portable)
+        if isinstance(payload, dict) and payload.get("use_portable_settings") is True:
+            return portable
+
+    config_home = os.environ.get("XDG_CONFIG_HOME")
+    if config_home:
+        return Path(config_home).expanduser() / APP_NAME / "settings.json"
+    return Path.home() / ".config" / APP_NAME / "settings.json"
+
+
+def _load_json(path: Path) -> dict[str, Any]:
+    try:
+        with path.open("r", encoding="utf-8") as f:
+            return json.load(f)
+    except (FileNotFoundError, json.JSONDecodeError, OSError):
+        return {}
+
+
+def _expand_path(value: str) -> str:
+    return str(Path(value).expanduser().resolve(strict=False))
+
+
+def _normalize_path_list(value: Any) -> list[str]:
+    if isinstance(value, str):
+        return [_expand_path(value)] if value else []
+    if isinstance(value, list):
+        return [_expand_path(item) for item in value if isinstance(item, str) and item]
+    return []
+
+
+def _dedupe(values: list[str]) -> list[str]:
+    seen: set[str] = set()
+    result: list[str] = []
+    for value in values:
+        if value not in seen:
+            result.append(value)
+            seen.add(value)
+    return result
+
+
+def get_model_roots(settings: dict[str, Any]) -> dict[str, list[str]]:
+    """Extract model folder roots from LoRA Manager settings.
+
+    Returns ``{model_type: [path, ...]}`` where *model_type* is one of
+    ``loras``, ``checkpoints``, ``embeddings``, ``unet``, etc.
+
+    Both primary (``folder_paths``) and extra (``extra_folder_paths``)
+    paths are included.  Extra paths can be configured via the UI at
+    Settings → Model Libraries → Extra Folder Paths.
+    """
+    roots: dict[str, list[str]] = {}
+    active_library = settings.get("active_library") or "default"
+    sources = [settings]
+    library = settings.get("libraries", {}).get(active_library)
+    if isinstance(library, dict):
+        sources.insert(0, library)
+    for source in sources:
+        # Primary folder paths.
+        folder_paths = source.get("folder_paths")
+        if isinstance(folder_paths, dict):
+            for key, value in folder_paths.items():
+                roots.setdefault(key, []).extend(_normalize_path_list(value))
+        # Extra folder paths (Settings → Model Libraries → Extra Folder Paths).
+        extra_folder_paths = source.get("extra_folder_paths")
+        if isinstance(extra_folder_paths, dict):
+            for key, value in extra_folder_paths.items():
+                roots.setdefault(key, []).extend(_normalize_path_list(value))
+    for default_key, folder_key in (
+        ("default_lora_root", "loras"),
+        ("default_checkpoint_root", "checkpoints"),
+        ("default_unet_root", "unet"),
+        ("default_embedding_root", "embeddings"),
+    ):
+        value = settings.get(default_key)
+        if isinstance(value, str) and value:
+            roots.setdefault(folder_key, []).append(_expand_path(value))
+    return {key: _dedupe(values) for key, values in roots.items()}
+
+
+def find_model_files(directory: Path) -> list[Path]:
+    """Recursively find all model files in *directory*."""
+    files: list[Path] = []
+    for ext in MODEL_EXTENSIONS:
+        files.extend(directory.rglob(f"*{ext}"))
+    return files
+
+
+# ── core detection logic ──────────────────────────────────────────────────────
+
+
+def check_file(path: Path) -> tuple[str, str, str] | None:
+    """If *path* matches the suffix pattern, return ``(base_name, hex, ext)``.
+
+    Returns ``None`` when:
+    * The filename does not match the pattern, or
+    * The original name (without the suffix) already exists in the same
+      directory (likely a download-conflict rename, not a doctor rename).
+    """
+    match = _SUFFIX_RE.match(path.name)
+    if not match:
+        return None
+
+    base_name = match.group(1)
+    hex_part = match.group(2)
+    extension = match.group(3)
+    orig_name = base_name + extension
+    orig_path = path.with_name(orig_name)
+
+    # Safety: skip if the original name already exists.
+    if orig_path.exists():
+        return None
+
+    return base_name, hex_part, extension
+
+
+def scan_roots(
+    roots: dict[str, list[str]],
+) -> dict[str, list[tuple[Path, str, str, str]]]:
+    """Scan all model roots and return detected files grouped by model type.
+
+    Returns ``{model_type: [(full_path, base_name, hex, ext), ...]}``.
+    """
+    results: dict[str, list[tuple[Path, str, str, str]]] = {}
+
+    for model_type, root_list in roots.items():
+        type_results: list[tuple[Path, str, str, str]] = []
+        for root in root_list:
+            root_path = Path(root)
+            if not root_path.is_dir():
+                continue
+            for model_file in find_model_files(root_path):
+                match = check_file(model_file)
+                if match:
+                    type_results.append((model_file, *match))
+        if type_results:
+            results[model_type] = type_results
+
+    return results
+
+
+def rename_file(
+    path: Path, base_name: str, extension: str, dry_run: bool
+) -> bool:
+    """Rename *path* to ``{base_name}{extension}``.
+
+    Also renames sidecar files (``.metadata.json``, ``.civitai.info``) and
+    preview images.  Returns ``True`` on success.
+    """
+    new_path = path.with_name(base_name + extension)
+    old_stem = path.with_suffix("")  # /dir/base_name-hex  (no ext)
+    new_stem = new_path.with_suffix("")  # /dir/base_name  (no ext)
+
+    if dry_run:
+        logger.info("  would rename:  %s", path.name)
+        logger.info("             ->  %s", new_path.name)
+        return True
+
+    try:
+        os.rename(path, new_path)
+    except OSError as exc:
+        logger.error("  FAILED to rename %s: %s", path.name, exc)
+        return False
+
+    # Rename sidecar metadata files.
+    for suffix in (".metadata.json", ".civitai.info"):
+        old_sidecar = old_stem.with_name(old_stem.name + suffix)
+        new_sidecar = new_stem.with_name(new_stem.name + suffix)
+        if old_sidecar.exists():
+            try:
+                os.rename(old_sidecar, new_sidecar)
+            except OSError as exc:
+                logger.warning("  could not rename sidecar %s: %s", old_sidecar.name, exc)
+
+    # Rename preview images.
+    for preview_ext in PREVIEW_EXTENSIONS:
+        old_preview = old_stem.with_name(old_stem.name + preview_ext)
+        new_preview = new_stem.with_name(new_stem.name + preview_ext)
+        if old_preview.exists():
+            try:
+                os.rename(old_preview, new_preview)
+            except OSError as exc:
+                logger.warning("  could not rename preview %s: %s", old_preview.name, exc)
+
+    logger.info("  renamed: %s  ->  %s", path.name, new_path.name)
+    return True
+
+
+# ── report helpers ────────────────────────────────────────────────────────────
+
+
+def print_report(results: dict[str, list[tuple[Path, str, str, str]]]) -> int:
+    """Print a human-readable report of detected files.  Returns total count."""
+    if not results:
+        logger.info("No leftover suffixed filenames detected.")
+        return 0
+
+    total = 0
+    for model_type in sorted(results):
+        entries = results[model_type]
+        total += len(entries)
+        label = model_type.capitalize()
+        logger.info("")
+        logger.info("─" * 50)
+        logger.info("  %s  (%d file(s))", label, len(entries))
+        logger.info("─" * 50)
+        for path, base_name, hex_part, ext in sorted(entries):
+            logger.info("  %s  →  %s%s", path.name, base_name, ext)
+
+    logger.info("")
+    logger.info("=" * 50)
+    logger.info("  Total: %d file(s) with leftover suffixes.", total)
+    logger.info("=" * 50)
+    return total
+
+
+def prompt_user(count: int) -> bool:
+    """Ask the user whether to proceed with the rename."""
+    try:
+        answer = input(
+            f"\nRestore {count} file(s) to their original names? [y/N] "
+        ).strip().lower()
+    except (EOFError, KeyboardInterrupt):
+        print()
+        return False
+    return answer in ("y", "yes")
+
+
+# ── main ──────────────────────────────────────────────────────────────────────
+
+
+def main() -> int:
+    parser = argparse.ArgumentParser(
+        description=(
+            "Detect and restore model filenames that have leftover "
+            "4-character hash suffixes from the old conflict resolver."
+        ),
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+        epilog=(
+            "Examples:\n"
+            "  python scripts/restore_suffixed_filenames.py\n"
+            "  python scripts/restore_suffixed_filenames.py --apply\n"
+            "  python scripts/restore_suffixed_filenames.py --apply --yes\n"
+        ),
+    )
+    parser.add_argument(
+        "--apply",
+        action="store_true",
+        help="Actually rename files (with confirmation prompt unless --yes is given)",
+    )
+    parser.add_argument(
+        "--yes", "-y",
+        action="store_true",
+        help="Skip confirmation prompt (implies --apply)",
+    )
+    parser.add_argument(
+        "--dry-run",
+        action="store_true",
+        help="Detect only — show what would be renamed without making changes",
+    )
+    parser.add_argument(
+        "-v", "--verbose",
+        action="store_true",
+        help="Enable debug-level logging",
+    )
+    args = parser.parse_args()
+
+    if args.verbose:
+        logging.getLogger().setLevel(logging.DEBUG)
+
+    # Resolve settings.
+    settings_path = resolve_settings_path()
+    logger.info("Settings: %s", settings_path)
+    settings = _load_json(settings_path)
+    if not settings:
+        logger.error("Could not load settings.json.  Is LoRA Manager configured?")
+        return 1
+
+    roots = get_model_roots(settings)
+    if not roots:
+        logger.error("No model folders found in settings.")
+        return 1
+
+    # Log which roots are being scanned.
+    for model_type, root_list in roots.items():
+        for root in root_list:
+            logger.info("Scanning %s: %s", model_type, root)
+
+    # Detect.
+    results = scan_roots(roots)
+    total = print_report(results)
+
+    if total == 0:
+        return 0
+
+    # Determine mode.
+    dry_run = not args.apply and not args.yes
+
+    if dry_run:
+        logger.info("\n[Dry-run mode — no files modified]")
+        logger.info("Run with --apply to restore filenames.")
+        return 0
+
+    # Confirm unless --yes.
+    if not args.yes:
+        if not prompt_user(total):
+            logger.info("Aborted.")
+            return 0
+
+    # Rename.
+    logger.info("")
+    success = 0
+    fail = 0
+    for model_type in sorted(results):
+        entries = results[model_type]
+        logger.info("")
+        logger.info("─" * 50)
+        logger.info("  Restoring %s  (%d file(s))", model_type, len(entries))
+        logger.info("─" * 50)
+        for path, base_name, hex_part, ext in sorted(entries):
+            ok = rename_file(path, base_name, ext, dry_run=False)
+            if ok:
+                success += 1
+            else:
+                fail += 1
+
+    logger.info("")
+    logger.info("=" * 50)
+    logger.info("  Done: %d restored, %d failed.", success, fail)
+    logger.info("=" * 50)
+    logger.info("")
+    logger.info("  ⚠  Please run Rebuild Cache in the LoRA Manager")
+    logger.info("     Doctor panel to refresh the model cache.")
+
+    return 0 if fail == 0 else 1
+
+
+if __name__ == "__main__":
+    sys.exit(main())

settings.json.example

@@ -10,13 +10,14 @@
       "C:/path/to/your/checkpoints_folder",
       "C:/path/to/another/checkpoints_folder"
     ],
+    "unet": [
+      "C:/path/to/your/diffusion_models_folder",
+      "C:/path/to/another/diffusion_models_folder"
+    ],
     "embeddings": [
       "C:/path/to/your/embeddings_folder",
       "C:/path/to/another/embeddings_folder"
     ]
   },
-  "example_images_open_mode": "system",
-  "example_images_local_root": "",
-  "example_images_open_uri_template": "",
   "auto_organize_exclusions": []
 }

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

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

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

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

static/css/components/sidebar.css

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

static/js/api/baseModelApi.js

@@ -766,6 +766,49 @@ export class BaseModelApiClient {
         }
     }
 
+    async refreshUpdatesForFolder(folderPath, { force = false } = {}) {
+        if (!folderPath) {
+            throw new Error('No folder path provided');
+        }
+
+        try {
+            state.loadingManager.show('Checking for updates...', 0);
+            state.loadingManager.showCancelButton(() => this.cancelTask());
+
+            const response = await fetch(this.apiConfig.endpoints.refreshUpdates, {
+                method: 'POST',
+                headers: { 'Content-Type': 'application/json' },
+                body: JSON.stringify({
+                    folder_path: folderPath,
+                    force
+                })
+            });
+
+            let payload = {};
+            try {
+                payload = await response.json();
+            } catch (error) {
+                console.warn('Unable to parse refresh updates response as JSON', error);
+            }
+
+            if (!response.ok || payload?.success !== true) {
+                if (payload?.status === 'cancelled') {
+                    showToast('toast.api.operationCancelled', {}, 'info');
+                    return null;
+                }
+                const message = payload?.error || response.statusText || 'Failed to refresh updates';
+                throw new Error(message);
+            }
+
+            return payload;
+        } catch (error) {
+            console.error('Error refreshing updates for folder:', error);
+            throw error;
+        } finally {
+            state.loadingManager.hide();
+        }
+    }
+
     async fetchCivitaiVersions(modelId, source = null) {
         try {
             let requestUrl = `${this.apiConfig.endpoints.civitaiVersions}/${modelId}`;
@@ -909,7 +952,7 @@ export class BaseModelApiClient {
         }
     }
 
-    async downloadModel(modelId, versionId, modelRoot, relativePath, useDefaultPaths = false, downloadId, source = null) {
+    async downloadModel(modelId, versionId, modelRoot, relativePath, useDefaultPaths = false, downloadId, source = null, fileParams = null) {
         try {
             const response = await fetch(DOWNLOAD_ENDPOINTS.download, {
                 method: 'POST',
@@ -921,7 +964,8 @@ export class BaseModelApiClient {
                     relative_path: relativePath,
                     use_default_paths: useDefaultPaths,
                     download_id: downloadId,
-                    ...(source ? { source } : {})
+                    ...(source ? { source } : {}),
+                    ...(fileParams ? { file_params: fileParams } : {})
                 })
             });
 

static/js/api/recipeApi.js

@@ -15,6 +15,7 @@ const RECIPE_ENDPOINTS = {
     move: '/api/lm/recipe/move',
     moveBulk: '/api/lm/recipes/move-bulk',
     bulkDelete: '/api/lm/recipes/bulk-delete',
+    repairBulk: '/api/lm/recipes/repair-bulk',
 };
 
 const RECIPE_SIDEBAR_CONFIG = {
@@ -196,8 +197,8 @@ export async function resetAndReloadWithVirtualScroll(options = {}) {
         // Reset page counter
         pageState.currentPage = 1;
 
-        // Fetch the first page
-        const result = await fetchPageFunction(1, pageState.pageSize || 50);
+        const pageSize = state.virtualScroller?.pageSize || pageState.pageSize || 100;
+        const result = await fetchPageFunction(1, pageSize);
 
         // Update the virtual scroller
         state.virtualScroller.refreshWithData(
@@ -250,8 +251,8 @@ export async function loadMoreWithVirtualScroll(options = {}) {
             pageState.currentPage = 1;
         }
 
-        // Fetch the first page of data
-        const result = await fetchPageFunction(pageState.currentPage, pageState.pageSize || 50);
+        const pageSize = state.virtualScroller?.pageSize || pageState.pageSize || 100;
+        const result = await fetchPageFunction(pageState.currentPage, pageSize);
 
         // Update virtual scroller with the new data
         state.virtualScroller.refreshWithData(
@@ -293,47 +294,41 @@ export async function resetAndReload(updateFolders = false, options = {}) {
 }
 
 /**
- * Sync changes - quick refresh without rebuilding cache (similar to models page)
+ * Refreshes the recipe list by triggering a backend scan, then reloading.
+ * @param {boolean} fullRebuild - If true, fully rebuild the cache; if false, incremental scan
  */
 export async function syncChanges() {
-    try {
-        state.loadingManager.showSimpleLoading('Syncing changes...');
-
-        // Simply reload the recipes without rebuilding cache
-        await resetAndReload(false, { preserveScroll: true });
-
-        showToast('toast.recipes.syncComplete', {}, 'success');
-    } catch (error) {
-        console.error('Error syncing recipes:', error);
-        showToast('toast.recipes.syncFailed', { message: error.message }, 'error');
-    } finally {
-        state.loadingManager.hide();
-        state.loadingManager.restoreProgressBar();
-    }
+    return refreshRecipes(false);
 }
 
-/**
- * Refreshes the recipe list by first rebuilding the cache and then loading recipes
- */
-export async function refreshRecipes() {
-    try {
-        state.loadingManager.showSimpleLoading('Refreshing recipes...');
+export async function refreshRecipes(fullRebuild = true) {
+    const actionLabel = fullRebuild ? 'Rebuilding recipe cache' : 'Refreshing recipes';
+    const actionToast = fullRebuild ? 'Full rebuild' : 'Refresh';
 
-        // Call the API endpoint to rebuild the recipe cache
-        const response = await fetch(RECIPE_ENDPOINTS.scan);
+    try {
+        state.loadingManager.show(`${actionLabel}...`, 0);
+
+        const url = new URL(RECIPE_ENDPOINTS.scan, window.location.origin);
+        url.searchParams.append('full_rebuild', fullRebuild);
+
+        const response = await fetch(url);
 
         if (!response.ok) {
-            const data = await response.json();
-            throw new Error(data.error || 'Failed to refresh recipe cache');
+            throw new Error(`Failed to refresh recipe cache: ${response.status} ${response.statusText}`);
         }
 
-        // After successful cache rebuild, reload the recipes
-        await resetAndReload(false, { preserveScroll: true });
+        const data = await response.json();
+        if (data.status === 'cancelled') {
+            showToast('toast.api.operationCancelled', {}, 'info');
+            return;
+        }
 
-        showToast('toast.recipes.refreshComplete', {}, 'success');
+        await resetAndReload(false);
+
+        showToast('toast.api.refreshComplete', { action: actionToast }, 'success');
     } catch (error) {
         console.error('Error refreshing recipes:', error);
-        showToast('toast.recipes.refreshFailed', { message: error.message }, 'error');
+        showToast('toast.api.refreshFailed', { action: fullRebuild ? 'rebuild' : 'refresh', type: 'recipe' }, 'error');
     } finally {
         state.loadingManager.hide();
         state.loadingManager.restoreProgressBar();
@@ -557,6 +552,38 @@ export class RecipeSidebarApiClient {
         };
     }
 
+    async repairBulkModels(filePaths) {
+        if (!filePaths || filePaths.length === 0) {
+            throw new Error('No file paths provided');
+        }
+
+        const recipeIds = filePaths
+            .map((path) => extractRecipeId(path))
+            .filter((id) => !!id);
+
+        if (recipeIds.length === 0) {
+            throw new Error('No recipe IDs could be derived from file paths');
+        }
+
+        const response = await fetch(this.apiConfig.endpoints.repairBulk, {
+            method: 'POST',
+            headers: {
+                'Content-Type': 'application/json',
+            },
+            body: JSON.stringify({
+                recipe_ids: recipeIds,
+            }),
+        });
+
+        const result = await response.json();
+
+        if (!response.ok || !result.success) {
+            throw new Error(result.error || 'Failed to repair recipes');
+        }
+
+        return result;
+    }
+
     async bulkDeleteModels(filePaths) {
         if (!filePaths || filePaths.length === 0) {
             throw new Error('No file paths provided');

static/js/components/ContextMenu/BulkContextMenu.js

@@ -41,6 +41,11 @@ export class BulkContextMenu extends BaseContextMenu {
         const autoOrganizeItem = this.menu.querySelector('[data-action="auto-organize"]');
         const deleteAllItem = this.menu.querySelector('[data-action="delete-all"]');
         const downloadMissingLorasItem = this.menu.querySelector('[data-action="download-missing-loras"]');
+        const repairMetadataItem = this.menu.querySelector('[data-action="repair-metadata"]');
+
+        if (repairMetadataItem) {
+            repairMetadataItem.style.display = config.repairMetadata ? 'flex' : 'none';
+        }
 
         if (sendToWorkflowAppendItem) {
             sendToWorkflowAppendItem.style.display = config.sendToWorkflow ? 'flex' : 'none';
@@ -127,33 +132,38 @@ export class BulkContextMenu extends BaseContextMenu {
         const resumeMetadataRefreshItem = this.menu.querySelector('[data-action="resume-metadata-refresh"]');
 
         if (skipMetadataRefreshItem && resumeMetadataRefreshItem) {
-            const skipCount = this.countSkipStatus(true);
-            const resumeCount = this.countSkipStatus(false);
-            const totalCount = skipCount + resumeCount;
-
-            if (skipCount === totalCount) {
+            if (!config.skipMetadataRefresh) {
                 skipMetadataRefreshItem.style.display = 'none';
-                resumeMetadataRefreshItem.style.display = 'flex';
-                resumeMetadataRefreshItem.querySelector('span').textContent = translate(
-                    'loras.bulkOperations.resumeMetadataRefresh'
-                );
-            } else if (resumeCount === totalCount) {
-                skipMetadataRefreshItem.style.display = 'flex';
                 resumeMetadataRefreshItem.style.display = 'none';
-                skipMetadataRefreshItem.querySelector('span').textContent = translate(
-                    'loras.bulkOperations.skipMetadataRefresh'
-                );
             } else {
-                skipMetadataRefreshItem.style.display = 'flex';
-                resumeMetadataRefreshItem.style.display = 'flex';
-                skipMetadataRefreshItem.querySelector('span').textContent = translate(
-                    'loras.bulkOperations.skipMetadataRefreshCount',
-                    { count: resumeCount }
-                );
-                resumeMetadataRefreshItem.querySelector('span').textContent = translate(
-                    'loras.bulkOperations.resumeMetadataRefreshCount',
-                    { count: skipCount }
-                );
+                const skipCount = this.countSkipStatus(true);
+                const resumeCount = this.countSkipStatus(false);
+                const totalCount = skipCount + resumeCount;
+
+                if (skipCount === totalCount) {
+                    skipMetadataRefreshItem.style.display = 'none';
+                    resumeMetadataRefreshItem.style.display = 'flex';
+                    resumeMetadataRefreshItem.querySelector('span').textContent = translate(
+                        'loras.bulkOperations.resumeMetadataRefresh'
+                    );
+                } else if (resumeCount === totalCount) {
+                    skipMetadataRefreshItem.style.display = 'flex';
+                    resumeMetadataRefreshItem.style.display = 'none';
+                    skipMetadataRefreshItem.querySelector('span').textContent = translate(
+                        'loras.bulkOperations.skipMetadataRefresh'
+                    );
+                } else {
+                    skipMetadataRefreshItem.style.display = 'flex';
+                    resumeMetadataRefreshItem.style.display = 'flex';
+                    skipMetadataRefreshItem.querySelector('span').textContent = translate(
+                        'loras.bulkOperations.skipMetadataRefreshCount',
+                        { count: resumeCount }
+                    );
+                    resumeMetadataRefreshItem.querySelector('span').textContent = translate(
+                        'loras.bulkOperations.resumeMetadataRefreshCount',
+                        { count: skipCount }
+                    );
+                }
             }
         }
 
@@ -251,6 +261,9 @@ export class BulkContextMenu extends BaseContextMenu {
             case 'delete-all':
                 bulkManager.showBulkDeleteModal();
                 break;
+            case 'repair-metadata':
+                bulkManager.repairSelectedRecipes();
+                break;
             case 'set-favorite': {
                 const allFavorited = this.countFavoritedInSelection() === state.selectedModels.size;
                 bulkManager.setBulkFavorites(!allFavorited);

static/js/components/ContextMenu/RecipeContextMenu.js

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

static/js/components/RecipeCard.js

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

static/js/components/SidebarManager.js

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

static/js/components/shared/ModelModal.js

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

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

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

static/js/components/shared/showcase/ShowcaseView.js

@@ -183,6 +183,9 @@ function renderMediaItem(img, index, exampleFiles) {
         Math.min(maxHeightPercent, aspectRatio)
     );
     
+    // Extract CivitAI image ID from CDN URL for import status check
+    const cdnImageId = (img.url || '').match(/\/(\d+)\.(?:jpeg|jpg|png|webp|gif)(?:\?|#|$)/)?.[1] || '';
+
     // Check if media should be blurred
     const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
     const matureBlurThreshold = getMatureBlurThreshold(state.settings);
@@ -224,12 +227,25 @@ function renderMediaItem(img, index, exampleFiles) {
     // Determine if this is a custom image (has id property)
     const isCustomImage = Boolean(typeof img.id === 'string' && img.id);
     
+    const hasGenMeta = img.hasMeta || (img.meta && (img.meta.prompt || img.meta.seed || img.meta.resources));
+
     // Create the media control buttons HTML
     const mediaControlsHtml = `
         <div class="media-controls">
             <button class="media-control-btn set-preview-btn" title="Set as preview">
                 <i class="fas fa-image"></i>
             </button>
+            ${hasGenMeta ? `
+            <button class="media-control-btn create-recipe-btn"
+                    title="Create As Recipe"
+                    data-image-meta="${encodeURIComponent(JSON.stringify(img.meta || {}))}"
+                    data-image-url="${img.url || ''}"
+                    data-image-nsfw="${img.nsfwLevel ?? ''}"
+                    data-image-id="${cdnImageId}"
+                    data-local-path="${localFile ? localFile.path : ''}">
+                <i class="fas fa-book-open"></i>
+            </button>
+            ` : ''}
             <button class="media-control-btn set-nsfw-btn" 
                     title="Set content rating"
                     data-media-index="${index}"
@@ -240,7 +256,7 @@ function renderMediaItem(img, index, exampleFiles) {
             <button class="media-control-btn example-delete-btn ${!isCustomImage ? 'disabled' : ''}" 
                     title="${isCustomImage ? 'Delete this example' : 'Only custom images can be deleted'}" 
                     data-short-id="${img.id || ''}" 
-                    ${!isCustomImage ? 'disabled' : ''}>
+                    ${!isCustomImage ? 'aria-disabled="true"' : ''}>
                 <i class="fas fa-trash-alt"></i>
                 <i class="fas fa-check confirm-icon"></i>
             </button>

static/js/managers/BatchImportManager.js

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

static/js/managers/BulkManager.js

@@ -85,7 +85,8 @@ export class BulkManager {
                 setContentRating: false,
                 skipMetadataRefresh: false,
                 setFavorite: true,
-                unfavorite: true
+                unfavorite: true,
+                repairMetadata: true
             }
         };
 
@@ -656,6 +657,76 @@ export class BulkManager {
         }
     }
 
+    async repairSelectedRecipes() {
+        if (state.selectedModels.size === 0) {
+            showToast('toast.recipes.noRecipesSelected', {}, 'warning');
+            return;
+        }
+
+        if (state.currentPageType !== 'recipes') {
+            showToast('This operation is only available for recipes', {}, 'warning');
+            return;
+        }
+
+        try {
+            const apiClient = this.getActiveApiClient();
+            const filePaths = Array.from(state.selectedModels);
+
+            if (typeof apiClient.repairBulkModels !== 'function') {
+                showToast('Bulk repair is not supported for this model type', {}, 'error');
+                return;
+            }
+
+            state.loadingManager.showSimpleLoading('Repairing recipe metadata...');
+
+            const result = await apiClient.repairBulkModels(filePaths);
+
+            if (result.success) {
+                const total = result.total || filePaths.length;
+                const repaired = result.repaired || 0;
+                const skipped = result.skipped || 0;
+
+                const recipes = result.recipes || [];
+                for (const recipe of recipes) {
+                    if (recipe.file_path) {
+                        state.virtualScroller.updateSingleItem(
+                            recipe.file_path,
+                            recipe
+                        );
+                    }
+                }
+
+                if (repaired > 0) {
+                    showToast(
+                        'toast.recipes.repairBulkComplete',
+                        { repaired, skipped, total },
+                        'success'
+                    );
+                } else {
+                    showToast(
+                        'toast.recipes.repairBulkSkipped',
+                        { total },
+                        'info'
+                    );
+                }
+
+                this.clearSelection();
+            } else {
+                throw new Error(result.error || 'Bulk repair failed');
+            }
+        } catch (error) {
+            console.error('Error during bulk recipe repair:', error);
+            showToast('toast.recipes.repairBulkFailed', { message: error.message }, 'error');
+        } finally {
+            if (state.loadingManager?.hide) {
+                state.loadingManager.hide();
+            }
+            if (typeof state.loadingManager?.restoreProgressBar === 'function') {
+                state.loadingManager.restoreProgressBar();
+            }
+        }
+    }
+
     async refreshAllMetadata() {
         if (state.selectedModels.size === 0) {
             showToast('toast.models.noModelsSelected', {}, 'warning');

static/js/managers/BulkMissingLoraDownloadManager.js

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

static/js/managers/DownloadManager.js

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

static/js/managers/FilterManager.js

@@ -662,7 +662,7 @@ export class FilterManager {
 
         // Call the appropriate manager's load method based on page type
         if (this.currentPage === 'recipes' && window.recipeManager) {
-            await window.recipeManager.loadRecipes({ preserveScroll: true });
+            await window.recipeManager.loadRecipes(true);
         } else if (this.currentPage === 'loras' || this.currentPage === 'embeddings' || this.currentPage === 'checkpoints') {
             // For models page, reset the page and reload
             await getModelApiClient().loadMoreWithVirtualScroll(true, false);
@@ -746,7 +746,7 @@ export class FilterManager {
 
         // Reload data using the appropriate method for the current page
         if (this.currentPage === 'recipes' && window.recipeManager) {
-            await window.recipeManager.loadRecipes({ preserveScroll: true });
+            await window.recipeManager.loadRecipes(true);
         } else if (this.currentPage === 'loras' || this.currentPage === 'checkpoints' || this.currentPage === 'embeddings') {
             await getModelApiClient().loadMoreWithVirtualScroll(true, true);
         }

static/js/managers/SearchManager.js

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

static/js/managers/SettingsManager.js

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

static/js/managers/UpdateService.js

@@ -731,9 +731,16 @@ export class UpdateService {
     }
     
     // Simple markdown parser for changelog items
+    // Simple markdown parser for changelog items
+    // Escape HTML entities first so angle brackets in content (e.g. `<lora:x>`)
+    // aren't swallowed by innerHTML's HTML parser as invalid tags
     parseMarkdown(text) {
         if (!text) return '';
         
+        text = text.replace(/&/g, '&amp;');
+        text = text.replace(/</g, '&lt;');
+        text = text.replace(/>/g, '&gt;');
+        
         // Handle bold text (**text**)
         text = text.replace(/\*\*(.*?)\*\*/g, '<strong>$1</strong>');
         

static/js/managers/import/DownloadManager.js

@@ -122,7 +122,7 @@ export class DownloadManager {
             modalManager.closeModal('importModal');
 
             // Refresh the recipe
-            window.recipeManager.loadRecipes({ preserveScroll: true });
+            window.recipeManager.loadRecipes(true);
 
         } catch (error) {
             console.error('Error:', error);

static/js/recipes.js

@@ -8,7 +8,7 @@ import { getSessionItem, removeSessionItem } from './utils/storageHelpers.js';
 import { RecipeContextMenu } from './components/ContextMenu/index.js';
 import { DuplicatesManager } from './components/DuplicatesManager.js';
 import { refreshVirtualScroll } from './utils/infiniteScroll.js';
-import { refreshRecipes, syncChanges, RecipeSidebarApiClient } from './api/recipeApi.js';
+import { refreshRecipes, RecipeSidebarApiClient } from './api/recipeApi.js';
 import { sidebarManager } from './components/SidebarManager.js';
 
 class RecipePageControls {
@@ -19,16 +19,13 @@ class RecipePageControls {
     }
 
     async resetAndReload() {
-        await refreshVirtualScroll({ preserveScroll: true });
+        await refreshVirtualScroll();
     }
 
     async refreshModels(fullRebuild = false) {
-        if (fullRebuild) {
-            await refreshRecipes();
-            return;
-        }
+        await refreshRecipes(fullRebuild);
 
-        await syncChanges();
+        await sidebarManager.refresh();
     }
 
     getSidebarApiClient() {

static/js/utils/updateCheckHelpers.js

@@ -100,6 +100,90 @@ export async function performModelUpdateCheck({ onStart, onComplete } = {}) {
     return { status, displayName, records, error };
 }
 
+/**
+ * Perform a model update check scoped to a specific folder.
+ * @param {string} folderPath - The relative folder path to check.
+ * @param {Object} [options]
+ * @param {Function} [options.onComplete] - Callback invoked after the request settles.
+ * @returns {Promise<{status: string, records: Array, error: Error | null}>}
+ */
+export async function performFolderUpdateCheck(folderPath, { onComplete } = {}) {
+    const modelType = getCurrentModelType();
+    const apiConfig = getCompleteApiConfig(modelType);
+    const apiClient = getModelApiClient(modelType);
+    const displayName = apiConfig?.config?.displayName ?? 'Model';
+
+    if (!apiConfig?.endpoints?.refreshUpdates) {
+        console.warn('Refresh updates endpoint not configured for model type:', modelType);
+        onComplete?.({ status: 'unsupported', records: [], error: null });
+        return { status: 'unsupported', records: [], error: null };
+    }
+
+    const loadingMessage = translate(
+        'sidebar.folderUpdateCheck.loading',
+        { type: displayName },
+        `Checking ${displayName} updates for this folder...`
+    );
+
+    state.loadingManager?.showSimpleLoading?.(loadingMessage);
+    state.loadingManager?.showCancelButton?.(() => apiClient.cancelTask());
+
+    let status = 'success';
+    let records = [];
+    let error = null;
+
+    try {
+        const response = await fetch(apiConfig.endpoints.refreshUpdates, {
+            method: 'POST',
+            headers: { 'Content-Type': 'application/json' },
+            body: JSON.stringify({ folder_path: folderPath, force: false })
+        });
+
+        let payload = {};
+        try {
+            payload = await response.json();
+        } catch {
+            payload = {};
+        }
+
+        if (!response.ok || payload.success !== true) {
+            if (payload?.status === 'cancelled') {
+                showToast('toast.api.operationCancelled', {}, 'info');
+                return { status: 'cancelled', records: [], error: null };
+            }
+            const errorMessage = payload?.error || response.statusText || 'Unknown error';
+            throw new Error(errorMessage);
+        }
+
+        records = Array.isArray(payload.records) ? payload.records : [];
+
+        if (records.length > 0) {
+            showToast('sidebar.folderUpdateCheck.success', { count: records.length, type: displayName }, 'success');
+        } else {
+            showToast('sidebar.folderUpdateCheck.none', { type: displayName }, 'info');
+        }
+
+        await resetAndReload(false);
+    } catch (err) {
+        status = 'error';
+        error = err instanceof Error ? err : new Error(String(err));
+        console.error('Error checking folder model updates:', error);
+        showToast(
+            'sidebar.folderUpdateCheck.error',
+            { message: error?.message ?? 'Unknown error', type: displayName },
+            'error'
+        );
+    } finally {
+        state.loadingManager?.hide?.();
+        if (typeof state.loadingManager?.restoreProgressBar === 'function') {
+            state.loadingManager.restoreProgressBar();
+        }
+        onComplete?.({ status, records, error });
+    }
+
+    return { status, records, error };
+}
+
 function getTypePlural(displayName) {
     if (!displayName) {
         return 'models';

templates/components/context_menu.html

@@ -80,6 +80,9 @@
         <div class="context-menu-item" data-action="check-updates">
             <i class="fas fa-bell"></i> <span>{{ t('loras.bulkOperations.checkUpdates') }}</span>
         </div>
+        <div class="context-menu-item" data-action="repair-metadata">
+            <i class="fas fa-tools"></i> <span>{{ t('loras.bulkOperations.repairMetadata') }}</span>
+        </div>
         <div class="context-menu-item" data-action="skip-metadata-refresh">
             <i class="fas fa-ban"></i> <span>{{ t('loras.bulkOperations.skipMetadataRefresh') }}</span>
         </div>
@@ -147,6 +150,13 @@
     </div>
 </div>
 
+<!-- Sidebar Folder Context Menu -->
+<div id="sidebarFolderContextMenu" class="context-menu">
+    <div class="context-menu-item" data-action="check-folder-updates">
+        <i class="fas fa-bell"></i> <span>{{ t('sidebar.folderUpdateCheck.label') }}</span>
+    </div>
+</div>
+
 <div id="nsfwLevelSelector" class="nsfw-level-selector">
     <div class="nsfw-level-header">
         <h3>{{ t('modals.contentRating.title') }}</h3>

templates/components/modals/download_modal.html

@@ -29,6 +29,21 @@
             </div>
         </div>
 
+        <!-- Step 2.5: File Selection (optional - only when version has multiple model files) -->
+        <div class="download-step" id="fileSelectionStep" style="display: none;">
+            <div class="file-selection-header">
+                <h3 id="fileSelectionTitle">{{ t('modals.download.fileSelection.title') }}</h3>
+                <div class="file-selection-version-name" id="fileSelectionVersionName"></div>
+            </div>
+            <div class="file-selection-list" id="fileSelectionList">
+                <!-- File options will be rendered here dynamically -->
+            </div>
+            <div class="modal-actions">
+                <button class="secondary-btn" id="backToVersionFromFilesBtn">{{ t('common.actions.back') }}</button>
+                <button class="primary-btn" id="confirmFileSelection">{{ t('modals.download.fileSelection.select') }}</button>
+            </div>
+        </div>
+
         <!-- Step 3: Location Selection -->
         <div class="download-step" id="locationStep" style="display: none;">
             <div class="location-selection">

tests/frontend/api/recipeApi.bulk.test.js

@@ -3,6 +3,7 @@ import { describe, it, beforeEach, afterEach, expect, vi } from 'vitest';
 const showToastMock = vi.hoisted(() => vi.fn());
 const loadingManagerMock = vi.hoisted(() => ({
   showSimpleLoading: vi.fn(),
+  show: vi.fn(),
   hide: vi.fn(),
   restoreProgressBar: vi.fn(),
 }));
@@ -177,9 +178,7 @@ describe('RecipeSidebarApiClient bulk operations', () => {
     );
   });
 
-  it('preserves scroll position for recipe reloads when requested', async () => {
-    const scrollSnapshot = { scrollContainer: { scrollTop: 480 }, scrollTop: 480 };
-    captureScrollPositionMock.mockReturnValue(scrollSnapshot);
+  it('reloads recipes without preserving scroll', async () => {
     global.fetch.mockResolvedValue({
       ok: true,
       json: async () => ({
@@ -189,18 +188,18 @@ describe('RecipeSidebarApiClient bulk operations', () => {
       }),
     });
 
-    await resetAndReload(false, { preserveScroll: true });
+    await resetAndReload(false);
 
-    expect(captureScrollPositionMock).toHaveBeenCalledTimes(1);
+    expect(captureScrollPositionMock).not.toHaveBeenCalled();
     expect(virtualScrollerMock.refreshWithData).toHaveBeenCalledWith(
       [{ id: 'recipe-1' }],
       1,
       false
     );
-    expect(restoreScrollPositionMock).toHaveBeenCalledWith(scrollSnapshot);
+    expect(restoreScrollPositionMock).not.toHaveBeenCalled();
   });
 
-  it('uses scroll-preserving reloads for syncChanges', async () => {
+  it('uses scroll-free reloads for syncChanges', async () => {
     global.fetch.mockResolvedValue({
       ok: true,
       json: async () => ({
@@ -212,8 +211,8 @@ describe('RecipeSidebarApiClient bulk operations', () => {
 
     await syncChanges();
 
-    expect(captureScrollPositionMock).toHaveBeenCalledTimes(1);
-    expect(restoreScrollPositionMock).toHaveBeenCalledTimes(1);
+    expect(captureScrollPositionMock).not.toHaveBeenCalled();
+    expect(restoreScrollPositionMock).not.toHaveBeenCalled();
     expect(loadingManagerMock.restoreProgressBar).toHaveBeenCalledTimes(1);
   });
 });

tests/routes/test_model_update_handler.py

@@ -46,6 +46,7 @@ class DummyUpdateService:
         *,
         force_refresh=False,
         target_model_ids=None,
+        folder_path=None,
     ):
         self.calls.append(
             {
@@ -54,6 +55,7 @@ class DummyUpdateService:
                 "provider": provider,
                 "force_refresh": force_refresh,
                 "target_model_ids": target_model_ids,
+                "folder_path": folder_path,
             }
         )
         return self.records

tests/routes/test_recipe_routes.py

@@ -467,7 +467,10 @@ async def test_import_remote_recipe(monkeypatch, tmp_path: Path) -> None:
     class Provider:
         async def get_model_version_info(self, model_version_id):
             provider_calls.append(model_version_id)
-            return {"baseModel": "Flux Provider"}, None
+            return {
+                "baseModel": "Flux Provider",
+                "model": {"type": "Checkpoint", "name": "Flux"},
+            }, None
 
     async def fake_get_default_metadata_provider():
         return Provider()

tests/services/test_civitai_image_parser.py

@@ -298,3 +298,113 @@ async def test_parse_metadata_handles_modelVersionIds(monkeypatch):
     assert lora2["type"] == "lora"
     assert lora2["hash"] == "aabbccdd0022"
     assert lora2["baseModel"] == "SDXL"
+
+
+@pytest.mark.asyncio
+async def test_parse_metadata_extracts_checkpoint_from_resources_model_type(monkeypatch):
+    """resources entries with type:"model" should be captured as the checkpoint,
+    not skipped (which was the old buggy behavior), and not mixed into loras."""
+    captured_hashes = []
+
+    async def fake_metadata_provider():
+        class Provider:
+            async def get_model_by_hash(self, model_hash):
+                captured_hashes.append(model_hash)
+                if model_hash == "a1b2c3d4e5":
+                    return ({
+                        "id": 999,
+                        "modelId": 888,
+                        "name": "v1.0",
+                        "model": {"name": "Real Checkpoint", "type": "Checkpoint"},
+                        "baseModel": "SDXL 1.0",
+                        "images": [{"url": "https://image.civitai.com/cp/original=true"}],
+                        "files": [{"type": "Model", "primary": True, "sizeKB": 1024, "name": "cp.safetensors"}]
+                    }, None)
+                return None, "Model not found"
+
+        return Provider()
+
+    monkeypatch.setattr(
+        "py.recipes.parsers.civitai_image.get_default_metadata_provider",
+        fake_metadata_provider,
+    )
+
+    parser = CivitaiApiMetadataParser()
+
+    metadata = {
+        "prompt": "test",
+        "resources": [
+            {"hash": "a1b2c3d4e5", "name": "Real Checkpoint", "type": "model"},
+            {"hash": "f6g7h8i9j0", "name": "Some LoRA", "type": "lora", "weight": 0.8},
+        ],
+        "Model hash": "a1b2c3d4e5",
+    }
+
+    result = await parser.parse_metadata(metadata)
+
+    # The type:"model" resource should be in result["model"], not in result["loras"]
+    assert result["model"] is not None, "checkpoint model should be extracted"
+    assert result["model"]["name"] == "Real Checkpoint"
+    assert result["model"]["hash"] == "a1b2c3d4e5"
+    assert result["model"]["type"] == "model"
+
+    # The LoRA resource should be in result["loras"]
+    assert len(result["loras"]) == 1
+    assert result["loras"][0]["name"] == "Some LoRA"
+
+    # The checkpoint hash should have triggered a lookup
+    assert "a1b2c3d4e5" in captured_hashes
+
+
+@pytest.mark.asyncio
+async def test_parse_metadata_resources_model_type_does_not_duplicate_checkpoint_in_loras(monkeypatch):
+    """When a resources entry has type:"model", it should NOT also appear in loras.
+    Regression test for the bug where the checkpoint model appeared in both places."""
+    async def fake_metadata_provider():
+        class Provider:
+            async def get_model_by_hash(self, model_hash):
+                if model_hash == "cp123hash":
+                    return ({
+                        "id": 100,
+                        "modelId": 200,
+                        "name": "v2",
+                        "model": {"name": "My Checkpoint", "type": "Checkpoint"},
+                        "baseModel": "SDXL",
+                        "files": [{"type": "Model", "primary": True, "sizeKB": 1024, "name": "cp.safetensors"}]
+                    }, None)
+                if model_hash == "lora1hash":
+                    return ({
+                        "id": 300,
+                        "modelId": 400,
+                        "name": "v1",
+                        "model": {"name": "Style LoRA", "type": "LORA"},
+                        "baseModel": "SDXL",
+                        "files": [{"type": "Model", "primary": True, "sizeKB": 512, "name": "style.safetensors"}]
+                    }, None)
+                return None, "Model not found"
+
+        return Provider()
+
+    monkeypatch.setattr(
+        "py.recipes.parsers.civitai_image.get_default_metadata_provider",
+        fake_metadata_provider,
+    )
+
+    parser = CivitaiApiMetadataParser()
+    metadata = {
+        "resources": [
+            {"hash": "cp123hash", "name": "My Checkpoint", "type": "model"},
+            {"hash": "lora1hash", "name": "Style LoRA", "type": "lora", "weight": 0.5},
+        ],
+    }
+
+    result = await parser.parse_metadata(metadata)
+
+    # Checkpoint must NOT appear in loras
+    lora_names = {l["name"] for l in result["loras"]}
+    assert "My Checkpoint" not in lora_names
+    assert "Style LoRA" in lora_names
+
+    # Checkpoint must be in result["model"]
+    assert result["model"] is not None
+    assert result["model"]["name"] == "My Checkpoint"

tests/services/test_recipe_repair.py

@@ -94,7 +94,7 @@ async def test_repair_all_recipes_with_enriched_checkpoint_id(setup_scanner):
         "id": 5678,
         "modelId": 1234,
         "name": "v1.0",
-        "model": {"name": "Full Model Name"},
+        "model": {"name": "Full Model Name", "type": "Checkpoint"},
         "baseModel": "SDXL 1.0",
         "images": [{"url": "https://image.url/thumb.jpg"}],
         "files": [{"type": "Model", "hashes": {"SHA256": "ABCDEF"}, "name": "full_filename.safetensors"}]
@@ -142,7 +142,7 @@ async def test_repair_all_recipes_supports_civitai_red_source_url(setup_scanner)
             "id": 5678,
             "modelId": 1234,
             "name": "v1.0",
-            "model": {"name": "Full Model Name"},
+            "model": {"name": "Full Model Name", "type": "Checkpoint"},
             "baseModel": "SDXL 1.0",
             "images": [{"url": "https://image.url/thumb.jpg"}],
             "files": [
@@ -183,7 +183,7 @@ async def test_repair_all_recipes_with_enriched_checkpoint_hash(setup_scanner):
         "id": 999,
         "modelId": 888,
         "name": "v2.0",
-        "model": {"name": "Hashed Model"},
+        "model": {"name": "Hashed Model", "type": "Checkpoint"},
         "baseModel": "SD 1.5",
         "files": [{"type": "Model", "hashes": {"SHA256": "hash123"}, "name": "hashed.safetensors"}]
     }, None)

web/comfyui/autocomplete.js

@@ -183,6 +183,13 @@ function parseSearchTokens(term = '') {
     return { include, exclude };
 }
 
+function escapePromptParentheses(text) {
+    // In ComfyUI's CLIP text encoder, bare parentheses are weight adjustment syntax.
+    // Tags containing literal parentheses must be escaped with backslash to prevent
+    // them from being interpreted as weight modifiers. e.g. "foo (bar)" → "foo \(bar\)"
+    return text.replace(/\(/g, '\\(').replace(/\)/g, '\\)');
+}
+
 function formatAutocompleteInsertion(text = '') {
     const trimmed = typeof text === 'string' ? text.trim() : '';
     if (!trimmed) {
@@ -253,7 +260,7 @@ function createDefaultBehavior(modelType) {
             if (!trimmed) {
                 return '';
             }
-            return formatAutocompleteInsertion(trimmed);
+            return formatAutocompleteInsertion(escapePromptParentheses(trimmed));
         },
     };
 }
@@ -352,7 +359,7 @@ const MODEL_BEHAVIORS = {
     custom_words: {
         enablePreview: false,
         async getInsertText(_instance, relativePath) {
-            return formatAutocompleteInsertion(relativePath);
+            return formatAutocompleteInsertion(escapePromptParentheses(relativePath));
         },
     },
     prompt: {
@@ -399,6 +406,8 @@ const MODEL_BEHAVIORS = {
                     tagText = tagText.replace(/_/g, ' ');
                 }
 
+                tagText = escapePromptParentheses(tagText);
+
                 return formatAutocompleteInsertion(tagText);
             }
         },