chore(release): bump version to v1.1.6

Move NodeRegistry from a single global _nodes dict to a per-client
(_tab_nodes) structure so that multiple ComfyUI browser tabs no
longer overwrite each other's workflow node data during a
lora_registry_refresh cycle.  The merged result is a union of all
known tabs' target nodes, eliminating the non-deterministic failure
where send-to-workflow could randomly target a tab lacking valid
targets.

- NodeRegistry.register_nodes(sid, nodes) replaces per-tab data
  without affecting other tabs.
- NodeRegistry.get_merged_registry() returns the union across all
  connected clients, together with tab_count / per-tab metadata.
- prepare_for_refresh() snapshots the current active sockets; caller
  re-reads before merging so that newly-connected tabs are not pruned.
- workflow_registry.js sends api.clientId in the POST body so the
  backend can identify which tab is registering.

data/supporters.json

@@ -11,8 +11,8 @@
     "Insomnia Art Designs",
     "2018cfh",
     "Arlecchino Shion",
-    "Rob Williams",
     "Charles Blakemore",
+    "Rob Williams",
     "W+K+White",
     "$MetaSamsara",
     "wackop",
@@ -21,6 +21,8 @@
     "stone9k",
     "Rosenthal",
     "Francisco Tatis",
+    "JongWon Han",
+    "FreelancerZ",
     "Polymorphic Indeterminate",
     "Skalabananen",
     "Marc Whiffen",
@@ -38,24 +40,32 @@
     "Estragon",
     "J\\B/ 8r0wns0n",
     "ClockDaemon",
+    "KD",
+    "Omnidex",
+    "Tyler Trebuchon",
+    "Release Cabrakan",
     "Tobi_Swagg",
     "SG",
+    "James Dooley",
     "zenbound",
+    "Buzzard",
     "jmack",
     "Andrew Wilson",
     "Greybush",
+    "Mark Corneglio",
     "Ricky Carter",
     "James Todd",
-    "JongWon Han",
+    "Steven Pfeiffer",
     "VantAI",
     "レプサイ",
+    "Lisster",
     "Michael Wong",
     "runte3221",
     "Illrigger",
     "Tom Corrigan",
     "JackieWang",
-    "FreelancerZ",
     "fnkylove",
+    "Yushio",
     "Vik71it",
     "Echo",
     "Lilleman",
@@ -65,50 +75,48 @@
     "Fraser Cross",
     "Liam MacDougal",
     "Sterilized",
+    "BadassArabianMofo",
     "JORGE+LUIZ+HUSSNI+MESSIAS",
     "quarz",
     "Greg",
+    "jean jahren",
     "JSST",
     "Snaggwort",
+    "lmsupporter",
     "Takkan",
     "wfpearl",
     "Matt+J",
     "Baekdoosixt",
     "Jonathan Ross",
-    "KD",
-    "Omnidex",
+    "Jack B Nimble",
     "Nazono_hito",
     "Melville Parrish",
     "daniel dove",
     "Lustre",
-    "Tyler Trebuchon",
-    "Release Cabrakan",
     "JW Sin",
     "Alex",
     "bh",
     "carozzz",
     "Marlon Daniels",
-    "James Dooley",
-    "Buzzard",
+    "Starkselle",
     "Aaron Bleuer",
     "LacesOut!",
+    "greebles",
     "Adam Shaw",
-    "Mark Corneglio",
     "SarcasticHashtag",
     "Anthony Rizzo",
     "iamresist",
+    "M Postkasse",
     "RedrockVP",
     "Wolffen",
     "Wicked Choices by ASLPro3D",
     "Jacob Hoehler",
     "FinalyFree",
     "Weasyl",
-    "Steven Pfeiffer",
     "Timmy",
     "Johnny",
     "Cory Paza",
     "Tak",
-    "Lisster",
     "Big Red",
     "whudunit",
     "Luc Job",
@@ -116,37 +124,36 @@
     "Philip Hempel",
     "corde",
     "nwalker94",
-    "Yushio",
     "Bishoujoker",
+    "aai",
     "Todd Keck",
     "Briton Heilbrun",
     "Tori",
     "wildnut",
     "Aleksander Wujczyk",
     "AM Kuro",
-    "BadassArabianMofo",
     "Pascal Dahle",
     "Sangheili460",
     "MagnaInsomnia",
     "Akira_HentAI",
     "Karl P.",
-    "lmsupporter",
     "andrew.tappan",
     "N/A",
+    "The Spawn",
     "graysock",
     "Greenmoustache",
     "zounic",
     "fancypants",
-    "Eldithor",
-    "Jack B Nimble",
+    "Digital",
     "JaxMax",
     "contrite831",
     "Jwk0205",
-    "Starkselle",
+    "Bro Xie",
+    "batblue",
+    "carey6409",
     "Olive",
-    "greebles",
+    "太郎 ゲーム",
     "Some Guy Named Barry",
-    "M Postkasse",
     "AELOX",
     "Gooohokrbe",
     "Nicfit23",
@@ -162,12 +169,12 @@
     "Serge Bekenkamp",
     "Jimmy Ledbetter",
     "LeoZero",
+    "Antonio Pontes",
+    "nahinahi9",
     "Dustin Chen",
     "dan",
-    "aai",
     "Mouthlessman",
     "otaku fra",
-    "jean jahren",
     "MiraiKuriyamaSy",
     "Ran C",
     "ViperC",
@@ -176,7 +183,6 @@
     "Adam Taylor",
     "AbstractAss",
     "Weird_With_A_Beard",
-    "The Spawn",
     "Pozadine1",
     "Qarob",
     "AIGooner",
@@ -187,18 +193,16 @@
     "Hasturkun",
     "Jon Sandman",
     "Ubivis",
+    "CloudValley",
+    "linnfrey",
     "Jackthemind",
+    "griffin+dahlberg",
     "Joboshy",
-    "Digital",
     "takyamtom",
     "Bohemian Corporal",
     "Dan",
-    "Bro Xie",
     "yer fey",
-    "batblue",
     "Error_Rule34_Not_found",
-    "carey6409",
-    "太郎 ゲーム",
     "Roslynd",
     "jinxedx",
     "Neco28",
@@ -210,22 +214,21 @@
     "Frank Nitty",
     "Magic Noob",
     "DougPeterson",
-    "Antonio Pontes",
     "ApathyJones",
+    "Jeff",
     "Bruce",
-    "Julian V",
     "Steven Owens",
-    "nahinahi9",
     "Kevin John Duck",
     "Kevin Christopher",
     "Blackfish95",
+    "dd",
     "Paul Kroll",
     "Bas Imagineer",
     "John Statham",
     "yuxz69",
     "esthe",
+    "AlexDuKaNa",
     "decoy",
-    "CloudValley",
     "thesoftwaredruid",
     "wundershark",
     "mr_dinosaur",
@@ -233,15 +236,20 @@
     "Ray Wing",
     "Ranzitho",
     "Gus",
+    "地獄の禄",
     "MJG",
     "David LaVallee",
-    "linnfrey",
     "ae",
     "Tr4shP4nda",
     "capn",
     "Joseph",
+    "Mirko Katzula",
+    "dan",
+    "Piccio08",
+    "kumakichi",
+    "cppbel",
     "IamAyam",
-    "skaterb949",
+    "jeaness",
     "Brian M",
     "Josef Lanzl",
     "Nerezza",
@@ -261,37 +269,32 @@
     "Eris3D",
     "Max Marklund",
     "m",
+    "Pierce McBride",
     "Pronredn",
+    "Mikko Hemilä",
     "Jamie Ogletree",
     "a _",
-    "Jeff",
     "lh qwe",
     "James Coleman",
+    "Martial",
     "conner",
     "Ouro Boros",
     "Chad Idk",
-    "dd",
     "Princess Bright Eyes",
     "Yuji Kaneko",
     "Dušan Ryban",
     "Felipe dos Santos",
+    "Rops Alot",
     "Sam",
     "sjon kreutz",
     "Ace Ventura",
     "Douglas Gaspar",
     "Metryman55",
-    "AlexDuKaNa",
     "George",
     "dw",
-    "地獄の禄",
     "Gamalonia",
     "WRL_SPR",
     "momokai",
-    "Mirko Katzula",
-    "dan",
-    "Piccio08",
-    "kumakichi",
-    "cppbel",
     "Moon Knight",
     "몽타주",
     "Kland",
@@ -313,12 +316,15 @@
     "kyoumei",
     "RadStorm04",
     "JohnDoe42054",
+    "BillyHill",
+    "emyth",
     "gzmzmvp",
     "Richard",
     "奚明 刘",
     "Andrew",
     "Robert Wegemund",
     "Littlehuggy",
+    "Gregory Kozhemiak",
     "준희 김",
     "Brian Buie",
     "Sadlip",
@@ -328,16 +334,16 @@
     "Tomohiro Baba",
     "Mike Simone",
     "Noora",
-    "Pierce McBride",
     "Joshua Gray",
     "Mattssn",
-    "Mikko Hemilä",
+    "Morgandel",
     "Jacob McDaniel",
+    "X",
+    "Sloan Steddy",
     "Temikus",
     "Artokun",
     "Michael Taylor",
     "Derek Baker",
-    "Martial",
     "Michael Anthony Scott",
     "Emil Andersson",
     "Atilla Berke Pekduyar",
@@ -345,7 +351,6 @@
     "CryptoTraderJK",
     "Decx _",
     "Davaitamin",
-    "Rops Alot",
     "tedcor",
     "Fotek Design",
     "四糸凜音",
@@ -358,8 +363,6 @@
     "starbugx",
     "dc7431",
     "Crocket",
-    "BillyHill",
-    "emyth",
     "chriphost",
     "KitKatM",
     "socrasteeze",
@@ -383,35 +386,40 @@
     "g9p0o",
     "TheHolySheep",
     "Monte Won",
-    "Gregory Kozhemiak",
+    "SpringBootisTrash",
+    "carsten",
+    "ikok",
+    "Wolfe7D1",
     "Draven T",
-    "mrjuan",
     "elleshar666",
+    "ACTUALLY_the_Real_Willem_Dafoe",
     "Aquatic Coffee",
+    "Kauffy",
     "John J Linehan",
     "ethanfel",
     "Elliot E",
-    "Morgandel",
     "Theerat Jiramate",
     "Focuschannel",
     "Edward Kennedy",
     "Noah",
-    "X",
-    "Sloan Steddy",
     "Vane Holzer",
+    "psytrax",
     "hexxish",
     "Anthony Faxlandez",
     "battu",
     "notedfakes",
     "Nathan",
     "NICHOLAS BAXLEY",
+    "Michael Scott",
     "Pat Hen",
     "Xeeosat",
     "Saya",
     "Ed Wang",
     "Jordan Shaw",
+    "Wes Sims",
     "g unit",
     "Srdb",
+    "Filippo Ferrari",
     "JC",
     "Prompt Pirate",
     "uwutismxd",
@@ -427,9 +435,8 @@
     "Pkrsky",
     "nanana",
     "raf8osz",
-    "SpringBootisTrash",
-    "carsten",
-    "ikok",
+    "FeralOpticsAI",
+    "Pavlaki",
     "Doug+Rintoul",
     "Noor",
     "Yorunai",
@@ -446,36 +453,34 @@
     "cocona",
     "ElitaSSJ4",
     "David Schenck",
-    "Wolfe7D1",
     "blikkies",
     "Chris",
     "Time Valentine",
     "Shock Shockor",
-    "ACTUALLY_the_Real_Willem_Dafoe",
     "Михал Михалыч",
     "Matt",
     "Goldwaters",
-    "Kauffy",
     "Zude",
+    "Frogmilk",
     "SPJ",
     "Kyler",
+    "Bryan Rutkowski",
     "Justin Blaylock",
     "aRtFuL_DodGeR",
     "Nick Kage",
-    "psytrax",
     "Cyrus Fett",
     "Xenon Xue",
     "Edward Ten Eyck",
     "Billy Gladky",
-    "Michael Scott",
     "Probis",
     "Solixer",
-    "Wes Sims",
     "ItsGeneralButtNaked",
     "Donor4115",
+    "jinksta187",
     "Distortik",
     "Manu Thetug",
-    "Filippo Ferrari",
+    "Karlanx",
+    "operationancut",
     "Youguang",
     "andrewzpong",
     "BossGame",
@@ -486,11 +491,18 @@
     "Kevinj",
     "Mitchell Robson",
     "POPPIN",
+    "YassineKhaled",
+    "Y",
+    "MatteKey",
+    "Flob",
+    "ShiroSenpai",
+    "Inkognito",
     "G",
     "Tan+Huynh",
     "Bob+Barker",
     "D",
     "Dark_Pest",
+    "Eldithor",
     "Alex",
     "Karru",
     "ChaChanoKo",
@@ -503,13 +515,10 @@
     "g",
     "J",
     "Alan+Cano",
-    "FeralOpticsAI",
-    "Pavlaki",
     "BillyBoy84",
     "Buecyb99",
     "Welkor",
     "John Martin",
-    "Ink Temptation",
     "JBsuede",
     "moranqianlong",
     "Kalli Core",
@@ -519,13 +528,12 @@
     "Dave Abraham",
     "Joaquin Hierrezuelo",
     "Locrospiel",
-    "Frogmilk",
     "Sean voets",
+    "Jarrid Lee",
     "Kor",
     "Joseph Hanson",
     "John Rednoulf",
     "Kyron Mahan",
-    "Bryan Rutkowski",
     "Boba Smith",
     "TBitz33",
     "Anonym dkjglfleeoeldldldlkf",
@@ -544,15 +552,12 @@
     "Pete Pain",
     "Jacob Winter",
     "Ryan Presley Ng",
-    "jinksta187",
     "RHopkirk",
     "Andrew Wilkinson",
-    "Karlanx",
     "Lyavph",
     "Maxim",
     "David",
     "Meilo",
-    "operationancut",
     "shinonomeiro",
     "Snille",
     "MaartenAlbers",
@@ -571,6 +576,8 @@
     "Scott",
     "Muratoraccio",
     "D",
+    "Akkas+Haque",
+    "Kachac",
     "SAVEagleBasement",
     "Kevin+Isom",
     "Rune+Osnes",
@@ -600,12 +607,6 @@
     "Lev+Lanevskiy",
     "low9",
     "Winged",
-    "YassineKhaled",
-    "Y",
-    "MatteKey",
-    "Flob",
-    "ShiroSenpai",
-    "Inkognito",
     "Jacky+Ho",
     "generic404",
     "abattoirblues",
@@ -614,29 +615,34 @@
     "hayden",
     "Obsidian.Studios",
     "ahoystan",
+    "Zomba Mann",
     "edk",
     "Tú Nguyễn Lý Hoàng",
     "shira1011",
+    "Neko Desco",
     "Ben D",
     "G",
+    "Vinarus",
     "ja s",
     "Leslie Andrew Ridings",
     "Doug Mason",
     "scoreswazey",
     "Owen Gwosdz",
-    "Jarrid Lee",
     "Poophead27 Blyat",
     "Mythspire",
     "AZ Party Oasis",
     "Devil Lude",
     "David Murcko",
+    "TheFusion",
     "MR.Bear",
     "Jack Dole",
     "matt",
     "somethingtosay8",
+    "3zS4QNQ4",
     "Terminuz",
     "ivistorm",
     "max blo",
+    "Ivan Imes",
     "CptNeo",
     "Jack Lawfield",
     "Borte",
@@ -645,7 +651,7 @@
     "Sage Himeros",
     "Eric Ketchum",
     "Kevin Wallace",
-    "David Spearing",
+    "Zeeble",
     "ChicRic",
     "Tigon",
     "BastardSama",
@@ -706,6 +712,9 @@
     "SelfishMedic",
     "adderleighn",
     "EnragedAntelope",
+    "Somebody",
+    "Jasper",
+    "megameganck",
     "thomasand01",
     "Shiba+Sama",
     "miduzza",
@@ -730,8 +739,6 @@
     "matter",
     "SRCRCOSS",
     "imer",
-    "Akkas+Haque",
-    "Kachac",
     "jcx29",
     "Drizzly",
     "Nebuleux",
@@ -751,24 +758,23 @@
     "KUJYAKU",
     "Coeur+de+cochon",
     "han b",
-    "Zomba Mann",
     "Aquaneo",
     "Nico",
     "Maximilian Krischan",
     "Banana Joe",
     "proto merp",
     "_ G3n",
+    "Brandon Thomas",
     "Donovan Jenkins",
     "Hans Meier",
     "sicarius",
     "Michael Eid",
     "Wolf and Fox Legends",
     "beersandbacon",
-    "Neko Desco",
     "Bob barker",
     "Ninja Tom",
     "karim ben brik",
-    "Vinarus",
+    "Elemnt",
     "Josh Snyder",
     "Michael Zhu",
     "Nemisu",
@@ -792,16 +798,15 @@
     "Forbidden Atelier",
     "Thomas Sankowski",
     "DrB",
+    "Nimhloth",
     "Adictedtohumping",
     "Snorklebort",
     "vinter",
     "Towelie",
-    "TheFusion",
     "Jean-françois SEMA",
-    "3zS4QNQ4",
     "Kurt",
+    "Andrew Ly",
     "Matt M.",
-    "Ivan Imes",
     "J M",
     "Slacks",
     "Bouya shaka",
@@ -837,5 +842,5 @@
     "Somebody",
     "CK"
   ],
-  "totalCount": 834
+  "totalCount": 839
 }

py/recipes/parsers/civitai_image.py

@@ -514,11 +514,21 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
 
                         result["loras"].append(lora_entry)
 
-            # Process modelVersionIds from Civitai image API
-            # These are model version IDs returned at root level when meta doesn't contain resources
-            if "modelVersionIds" in metadata and isinstance(
-                metadata["modelVersionIds"], list
+            # Process modelVersionIds from Civitai image API.
+            # These are version IDs returned at root level of the API response.
+            # When resources or civitaiResources are already present in metadata
+            # (which they are when ?withMeta=true is passed), those sections have
+            # complete hash/type information — modelVersionIds is a fallback for
+            # when meta is null and only the flat ID list is available. Skipping
+            # it here avoids duplicates: the same file hash often resolves to
+            # different version IDs via hash lookup (resources) vs the original
+            # version ID in modelVersionIds, and both paths would create entries.
+            if (
+                "modelVersionIds" in metadata
+                and isinstance(metadata["modelVersionIds"], list)
+                and not result.get("loras")
             ):
+
                 for version_id in metadata["modelVersionIds"]:
                     version_id_str = str(version_id)
 
@@ -526,6 +536,13 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
                     if version_id_str in added_loras:
                         continue
 
+                    # Skip if this version ID is already the recipe's checkpoint
+                    # (resolved earlier from embedded resources/Model hash,
+                    # avoiding a duplicate CivitAI API call).
+                    existing_model = result.get("model")
+                    if existing_model and str(existing_model.get("id")) == version_id_str:
+                        continue
+
                     # Initialize lora entry with version ID
                     lora_entry = {
                         "id": version_id,
@@ -559,9 +576,40 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
                             )
 
                             if populated_entry is None:
-                                continue  # Skip invalid LoRA types
+                                # Not a LoRA — try as checkpoint (only if we
+                                # don't already have one).  Reuses the same
+                                # civitai_info from the API call above so no
+                                # extra query is made.
+                                if result["model"] is None:
+                                    checkpoint_entry = {
+                                        "id": version_id,
+                                        "modelId": 0,
+                                        "name": "Unknown Model",
+                                        "version": "",
+                                        "type": "checkpoint",
+                                        "existsLocally": False,
+                                        "localPath": None,
+                                        "file_name": "",
+                                        "hash": "",
+                                        "thumbnailUrl": (
+                                            "/loras_static/images/no-preview.png"
+                                        ),
+                                        "baseModel": "",
+                                        "size": 0,
+                                        "downloadUrl": "",
+                                        "isDeleted": False,
+                                    }
+                                    cp_populated = await (
+                                        self.populate_checkpoint_from_civitai(
+                                            checkpoint_entry, civitai_info
+                                        )
+                                    )
+                                    if cp_populated.get("modelId"):
+                                        result["model"] = cp_populated
+                                continue  # Not a LoRA, don't add to loras
 
                             lora_entry = populated_entry
+
                         except Exception as e:
                             logger.error(
                                 f"Error fetching Civitai info for model version {version_id}: {e}"

py/routes/handlers/misc_handlers.py

@@ -414,9 +414,10 @@ class PromptServerProtocol(Protocol):
     """Subset of PromptServer used by the handlers."""
 
     instance: "PromptServerProtocol"
+    sockets: dict  # maps clientId (sid) → WebSocketResponse
 
     def send_sync(
-        self, event: str, payload: dict
+        self, event: str, payload: dict | None = None, sid: str | None = None
     ) -> None:  # pragma: no cover - protocol
         ...
 
@@ -471,90 +472,154 @@ class BackupServiceProtocol(Protocol):
 
 
 class NodeRegistry:
-    """Thread-safe registry for tracking LoRA nodes in active workflows."""
+    """Thread-safe registry for tracking LoRA nodes across ComfyUI tabs.
+
+    Each connected ComfyUI browser tab (identified by its ``sid`` / ``clientId``)
+    registers its own set of workflow nodes.  Queries merge all known tabs into
+    a single result so that the calling LM panel always sees *every* available
+    target node, regardless of which tab responded fastest.
+    """
 
     def __init__(self) -> None:
         self._lock = asyncio.Lock()
-        self._nodes: Dict[str, dict] = {}
-        self._registry_updated = asyncio.Event()
+        # sid → {unique_id → node_info}
+        self._tab_nodes: Dict[str, Dict[str, dict]] = {}
+        self._ready = asyncio.Event()
+        self._waiting_clients: set[str] = set()
+
+    @property
+    def pending_client_count(self) -> int:
+        """Number of clients that have not yet responded in the current refresh cycle."""
+        return len(self._waiting_clients)
+
+    # ------------------------------------------------------------------
+    # Helpers to build one node dict (extracted so it's reused for each tab)
+    # ------------------------------------------------------------------
+    @staticmethod
+    def _build_node_dict(node: dict) -> dict:
+        node_id = node["node_id"]
+        graph_id = str(node["graph_id"])
+        unique_id = f"{graph_id}:{node_id}"
+        node_type = node.get("type", "")
+        type_id = NODE_TYPES.get(node_type, 0)
+        bgcolor = node.get("bgcolor") or DEFAULT_NODE_COLOR
+
+        raw_capabilities = node.get("capabilities")
+        capabilities: dict = {}
+        if isinstance(raw_capabilities, dict):
+            capabilities = dict(raw_capabilities)
+
+        raw_widget_names: list | None = node.get("widget_names")
+        if not isinstance(raw_widget_names, list):
+            capability_widget_names = capabilities.get("widget_names")
+            raw_widget_names = (
+                capability_widget_names
+                if isinstance(capability_widget_names, list)
+                else None
+            )
+
+        widget_names: list[str] = []
+        if isinstance(raw_widget_names, list):
+            widget_names = [
+                str(widget_name)
+                for widget_name in raw_widget_names
+                if isinstance(widget_name, str) and widget_name
+            ]
+
+        if widget_names:
+            capabilities["widget_names"] = widget_names
+        else:
+            capabilities.pop("widget_names", None)
+
+        if "supports_lora" in capabilities:
+            capabilities["supports_lora"] = bool(capabilities["supports_lora"])
+
+        comfy_class = node.get("comfy_class")
+        if not isinstance(comfy_class, str) or not comfy_class:
+            comfy_class = node_type if isinstance(node_type, str) else None
+
+        return {
+            "id": node_id,
+            "graph_id": graph_id,
+            "graph_name": node.get("graph_name"),
+            "unique_id": unique_id,
+            "bgcolor": bgcolor,
+            "title": node.get("title"),
+            "type": type_id,
+            "type_name": node_type,
+            "comfy_class": comfy_class,
+            "capabilities": capabilities,
+            "widget_names": widget_names,
+            "mode": node.get("mode"),
+            "marker_role": node.get("marker_role"),
+        }
+
+    # ------------------------------------------------------------------
+    # Public API
+    # ------------------------------------------------------------------
+    async def register_nodes(self, sid: str, nodes: list[dict]) -> None:
+        """Register/replace the node list for a single ComfyUI tab (identified by *sid*)."""
+        tab_nodes: dict[str, dict] = {}
+        for node in nodes:
+            nd = self._build_node_dict(node)
+            tab_nodes[nd["unique_id"]] = nd
 
-    async def register_nodes(self, nodes: list[dict]) -> None:
         async with self._lock:
-            self._nodes.clear()
-            for node in nodes:
-                node_id = node["node_id"]
-                graph_id = str(node["graph_id"])
-                unique_id = f"{graph_id}:{node_id}"
-                node_type = node.get("type", "")
-                type_id = NODE_TYPES.get(node_type, 0)
-                bgcolor = node.get("bgcolor") or DEFAULT_NODE_COLOR
-                raw_capabilities = node.get("capabilities")
-                capabilities: dict = {}
-                if isinstance(raw_capabilities, dict):
-                    capabilities = dict(raw_capabilities)
+            self._tab_nodes[sid] = tab_nodes
+            self._waiting_clients.discard(sid)
+            if not self._waiting_clients:
+                self._ready.set()
 
-                raw_widget_names: list | None = node.get("widget_names")
-                if not isinstance(raw_widget_names, list):
-                    capability_widget_names = capabilities.get("widget_names")
-                    raw_widget_names = (
-                        capability_widget_names
-                        if isinstance(capability_widget_names, list)
-                        else None
-                    )
+        logger.debug("Registered %s nodes from client %s", len(nodes), sid)
 
-                widget_names: list[str] = []
-                if isinstance(raw_widget_names, list):
-                    widget_names = [
-                        str(widget_name)
-                        for widget_name in raw_widget_names
-                        if isinstance(widget_name, str) and widget_name
-                    ]
+    def prepare_for_refresh(self, active_sids: list[str]) -> None:
+        """Set the list of client IDs we expect to hear from during the next refresh cycle."""
+        self._ready.clear()
+        self._waiting_clients = set(active_sids)
 
-                if widget_names:
-                    capabilities["widget_names"] = widget_names
-                else:
-                    capabilities.pop("widget_names", None)
-
-                if "supports_lora" in capabilities:
-                    capabilities["supports_lora"] = bool(capabilities["supports_lora"])
-
-                comfy_class = node.get("comfy_class")
-                if not isinstance(comfy_class, str) or not comfy_class:
-                    comfy_class = node_type if isinstance(node_type, str) else None
-
-                self._nodes[unique_id] = {
-                    "id": node_id,
-                    "graph_id": graph_id,
-                    "graph_name": node.get("graph_name"),
-                    "unique_id": unique_id,
-                    "bgcolor": bgcolor,
-                    "title": node.get("title"),
-                    "type": type_id,
-                    "type_name": node_type,
-                    "comfy_class": comfy_class,
-                    "capabilities": capabilities,
-                    "widget_names": widget_names,
-                    "mode": node.get("mode"),
-                    "marker_role": node.get("marker_role"),
-                }
-            logger.debug("Registered %s nodes in registry", len(nodes))
-            self._registry_updated.set()
-
-    async def get_registry(self) -> dict:
-        async with self._lock:
-            return {
-                "nodes": dict(self._nodes),
-                "node_count": len(self._nodes),
-            }
-
-    async def wait_for_update(self, timeout: float = 1.0) -> bool:
-        self._registry_updated.clear()
+    async def wait_for_all(self, timeout: float = 2.0) -> bool:
+        """Block until every client in the current waiting set has responded
+        (or *timeout* seconds elapse).  Returns ``True`` if all responded."""
+        if not self._waiting_clients:
+            return True
         try:
-            await asyncio.wait_for(self._registry_updated.wait(), timeout=timeout)
+            await asyncio.wait_for(self._ready.wait(), timeout=timeout)
             return True
         except asyncio.TimeoutError:
             return False
 
+    async def get_merged_registry(self, active_sids: set[str] | None = None) -> dict:
+        """Return the union of all known tab nodes, pruning any tab that is no
+        longer connected."""
+        async with self._lock:
+            # Garbage-collect stale entries (disconnected tabs)
+            if active_sids is not None:
+                for sid in list(self._tab_nodes):
+                    if sid not in active_sids:
+                        del self._tab_nodes[sid]
+
+            merged: dict[str, dict] = {}
+            tab_info: dict[str, dict] = {}
+            for sid, nodes in self._tab_nodes.items():
+                tab_info[sid] = {
+                    "node_count": len(nodes),
+                    "graph_names": list(
+                        {
+                            n.get("graph_name")
+                            for n in nodes.values()
+                            if n.get("graph_name")
+                        }
+                    ),
+                }
+                merged.update(nodes)
+
+            return {
+                "nodes": merged,
+                "node_count": len(merged),
+                "tab_count": len(self._tab_nodes),
+                "tabs": tab_info,
+            }
+
 
 class HealthCheckHandler:
     async def health_check(self, request: web.Request) -> web.Response:
@@ -2995,10 +3060,21 @@ class NodeRegistryHandler:
         try:
             data = await request.json()
             nodes = data.get("nodes", [])
+            client_id = data.get("client_id")
             if not isinstance(nodes, list):
                 return web.json_response(
                     {"success": False, "error": "nodes must be a list"}, status=400
                 )
+
+            if not isinstance(client_id, str) or not client_id:
+                return web.json_response(
+                    {
+                        "success": False,
+                        "error": "Missing client_id parameter",
+                    },
+                    status=400,
+                )
+
             for index, node in enumerate(nodes):
                 if not isinstance(node, dict):
                     return web.json_response(
@@ -3042,7 +3118,7 @@ class NodeRegistryHandler:
                 else:
                     node["graph_name"] = str(graph_name)
 
-            await self._node_registry.register_nodes(nodes)
+            await self._node_registry.register_nodes(client_id, nodes)
             return web.json_response(
                 {
                     "success": True,
@@ -3066,9 +3142,15 @@ class NodeRegistryHandler:
                     status=503,
                 )
 
+            # Snapshot of currently-connected ComfyUI tabs
+            active_sids = list(self._prompt_server.instance.sockets.keys())
+            self._node_registry.prepare_for_refresh(active_sids)
+
             try:
                 self._prompt_server.instance.send_sync("lora_registry_refresh", {})
-                logger.debug("Sent registry refresh request to frontend")
+                logger.debug(
+                    "Sent registry refresh request (expecting %s clients)", len(active_sids)
+                )
             except Exception as exc:
                 logger.error("Failed to send registry refresh message: %s", exc)
                 return web.json_response(
@@ -3080,19 +3162,31 @@ class NodeRegistryHandler:
                     status=500,
                 )
 
-            registry_updated = await self._node_registry.wait_for_update(timeout=1.0)
-            if not registry_updated:
-                logger.warning("Registry refresh timeout after 1 second")
+            if not await self._node_registry.wait_for_all(timeout=2.0):
+                logger.warning(
+                    "Registry refresh timeout after 2s (%s/%s clients responded)",
+                    len(active_sids) - self._node_registry.pending_client_count,
+                    len(active_sids),
+                )
+
+            # Re-read current sockets after the wait: a tab may have connected
+            # while we were waiting, and we don't want to garbage-collect it.
+            current_sids = set(self._prompt_server.instance.sockets.keys())
+            registry_info = await self._node_registry.get_merged_registry(
+                active_sids=current_sids
+            )
+
+            if registry_info["node_count"] == 0:
+                logger.warning("No nodes registered after refresh")
                 return web.json_response(
                     {
                         "success": False,
-                        "error": "Timeout Error",
-                        "message": "Registry refresh timeout - ComfyUI frontend may not be responsive",
+                        "error": "Empty Registry",
+                        "message": "No workflow nodes found — ensure ComfyUI is open and the extension is loaded.",
                     },
                     status=408,
                 )
 
-            registry_info = await self._node_registry.get_registry()
             return web.json_response({"success": True, "data": registry_info})
         except Exception as exc:  # pragma: no cover - defensive logging
             logger.error("Failed to get registry: %s", exc, exc_info=True)

py/routes/handlers/recipe_handlers.py

@@ -32,6 +32,7 @@ from ...utils.civitai_utils import (
     extract_civitai_image_id_from_cdn_url,
     rewrite_preview_url,
 )
+from ...utils.constants import NSFW_LEVELS
 from ...utils.exif_utils import ExifUtils
 from ...recipes.merger import GenParamsMerger
 from ...recipes.enrichment import RecipeEnricher
@@ -1120,6 +1121,13 @@ class RecipeManagementHandler:
             if parsed_embedded.get("base_model") and not metadata.get("base_model"):
                 metadata["base_model"] = parsed_embedded["base_model"]
 
+        # Extract preview_nsfw_level from the CivitAI API response
+        # (injected into civitai_meta_raw by _download_remote_media).
+        if isinstance(civitai_meta_raw, dict):
+            bl = civitai_meta_raw.get("browsingLevel")
+            if isinstance(bl, int) and bl > 0:
+                metadata["preview_nsfw_level"] = bl
+
         civitai_client = self._civitai_client_getter()
         await RecipeEnricher.enrich_recipe(
             recipe=metadata,
@@ -1515,8 +1523,31 @@ class RecipeManagementHandler:
                     # CivitAI API returns modelVersionIds at the root level of
                     # the image response, NOT inside the meta object.
                     mvids = image_info.get("modelVersionIds")
-                    if mvids and isinstance(civitai_meta_raw, dict):
-                        civitai_meta_raw["modelVersionIds"] = mvids
+                    if mvids:
+                        if isinstance(civitai_meta_raw, dict):
+                            civitai_meta_raw["modelVersionIds"] = mvids
+                        else:
+                            # meta is null but modelVersionIds exists — create a
+                            # minimal dict so downstream parsers can discover
+                            # LoRAs and checkpoints from the API response.
+                            civitai_meta_raw = {"modelVersionIds": mvids}
+
+                    # Inject browsingLevel (canonical integer) so the recipe's
+                    # preview_nsfw_level can be set, enabling proper NSFW blur
+                    # of the preview image.  Fall back to nsfwLevel (string)
+                    # when browsingLevel is absent.
+                    if isinstance(civitai_meta_raw, dict):
+                        browsing_level = image_info.get("browsingLevel")
+                        nsfw_level_str = image_info.get("nsfwLevel")
+                        if isinstance(browsing_level, int) and browsing_level > 0:
+                            civitai_meta_raw["browsingLevel"] = browsing_level
+                        elif (
+                            isinstance(nsfw_level_str, str)
+                            and nsfw_level_str in NSFW_LEVELS
+                        ):
+                            civitai_meta_raw["browsingLevel"] = NSFW_LEVELS[
+                                nsfw_level_str
+                            ]
 
                 original_url = (
                     image_info.get("url") if civitai_image_id and image_info else None
@@ -1796,6 +1827,13 @@ class RecipeManagementHandler:
             "source_path": image_url,
         }
 
+        # Extract preview_nsfw_level from the CivitAI API response
+        # (injected into civitai_meta_raw by _download_remote_media).
+        if isinstance(civitai_meta_raw, dict):
+            bl = civitai_meta_raw.get("browsingLevel")
+            if isinstance(bl, int) and bl > 0:
+                metadata["preview_nsfw_level"] = bl
+
         if civitai_parsed:
             civitai_loras = civitai_parsed.get("loras", [])
             if civitai_loras and not metadata.get("loras"):

py/services/batch_import_service.py

@@ -523,6 +523,10 @@ class BatchImportService:
                 if payload.get("checkpoint"):
                     metadata["checkpoint"] = payload["checkpoint"]
 
+                nsfw = payload.get("preview_nsfw_level")
+                if isinstance(nsfw, int) and nsfw > 0:
+                    metadata["preview_nsfw_level"] = nsfw
+
                 image_bytes = None
                 image_base64 = payload.get("image_base64")
 

py/services/civarchive_client.py

@@ -417,7 +417,7 @@ class CivArchiveClient:
 
             if version_id is not None:
                 raw_id = version_data.get("id")
-                if raw_id != version_id:
+                if raw_id is not None and str(raw_id) != str(version_id):
                     logger.warning(
                         "Requested version %s doesn't match default version %s for model %s",
                         version_id,

py/services/civitai_client.py

@@ -56,7 +56,7 @@ class CivitaiClient:
         self._MAX_CACHE_ENTRIES = 500
 
     def _build_image_info_url(self, image_id: str) -> str:
-        return f"{self.base_url}/images?imageId={image_id}&nsfw=X"
+        return f"{self.base_url}/images?imageId={image_id}&nsfw=X&withMeta=true"
 
     async def _make_request(
         self,

py/services/download_manager.py

@@ -1288,10 +1288,24 @@ class DownloadManager:
                     "download_id": download_id,
                 }
 
-            # Check if this checkpoint should be treated as a diffusion model based on baseModel
+            # Check if this checkpoint should be treated as a diffusion model
+            # Priority: (1) any file has type "UNet" or "Diffusion Model",
+            #            (2) baseModel is in DIFFUSION_MODEL_BASE_MODELS
             is_diffusion_model = False
             if model_type == "checkpoint":
-                if base_model_value in DIFFUSION_MODEL_BASE_MODELS:
+                # Check file types first (more direct signal from CivitAI)
+                version_files = version_info.get("files", [])
+                for f in version_files:
+                    f_type = f.get("type", "")
+                    if f_type in ("UNet", "Diffusion Model"):
+                        is_diffusion_model = True
+                        logger.info(
+                            f"File type '{f_type}' detected, routing checkpoint to unet folder"
+                        )
+                        break
+
+                # Fallback to baseModel name check
+                if not is_diffusion_model and base_model_value in DIFFUSION_MODEL_BASE_MODELS:
                     is_diffusion_model = True
                     logger.info(
                         f"baseModel '{base_model_value}' is a known diffusion model, routing to unet folder"
@@ -1420,7 +1434,7 @@ class DownloadManager:
                             f
                             for f in files
                             if f.get("primary")
-                            and f.get("type") in ("Model", "Negative", "Diffusion Model")
+                            and f.get("type") in ("Model", "Negative", "Diffusion Model", "UNet")
                         ),
                         None,
                     )
@@ -1451,7 +1465,7 @@ class DownloadManager:
                     (
                         f
                         for f in files
-                        if f.get("primary") and f.get("type") in ("Model", "Negative", "Diffusion Model")
+                        if f.get("primary") and f.get("type") in ("Model", "Negative", "Diffusion Model", "UNet")
                     ),
                     None,
                 )

py/services/recipes/analysis_service.py

@@ -146,11 +146,38 @@ class RecipeAnalysisService:
                 ):
                     metadata = metadata["meta"]
 
-                # Include modelVersionIds from root level if available
-                # Civitai API returns modelVersionIds at root level, not in meta
+                # Include modelVersionIds from root level if available.
+                # CivitAI API returns modelVersionIds at root level, not in meta.
+                # When meta is null (None), create a minimal dict so downstream
+                # parsers can still discover LoRAs and checkpoints.
                 model_version_ids = image_info.get("modelVersionIds")
-                if model_version_ids and isinstance(metadata, dict):
-                    metadata["modelVersionIds"] = model_version_ids
+                if model_version_ids:
+                    if isinstance(metadata, dict):
+                        metadata["modelVersionIds"] = model_version_ids
+                    else:
+                        metadata = {"modelVersionIds": model_version_ids}
+
+                # Inject browsingLevel (canonical integer) so the recipe's
+                # preview_nsfw_level can be set, enabling proper NSFW blur
+                # of the preview image.  Fall back to nsfwLevel (string)
+                # when browsingLevel is absent.
+                if isinstance(metadata, dict):
+                    browsing_level = image_info.get("browsingLevel")
+                    nsfw_level_str = image_info.get("nsfwLevel")
+                    if isinstance(browsing_level, int) and browsing_level > 0:
+                        metadata["browsingLevel"] = browsing_level
+                    elif (
+                        isinstance(nsfw_level_str, str)
+                        and nsfw_level_str
+                        in (
+                            "PG", "PG13", "R", "X", "XXX", "Blocked",
+                        )
+                    ):
+                        from ...utils.constants import NSFW_LEVELS
+
+                        metadata["browsingLevel"] = NSFW_LEVELS.get(
+                            nsfw_level_str, 0
+                        )
 
                 # Validate that metadata contains meaningful recipe fields
                 # If not, treat as None to trigger EXIF extraction from downloaded image
@@ -171,12 +198,19 @@ class RecipeAnalysisService:
                 temp_path = self._create_temp_path(suffix=extension)
                 await self._download_image(url, temp_path)
 
-            if metadata is None and not is_video:
-                metadata = await asyncio.to_thread(
+            # Always extract EXIF from the downloaded image for generation
+            # params (prompt, negative prompt, sampler, steps, etc.).
+            # Previously this was gated on ``metadata is None``, but that
+            # skipped EXIF entirely when API metadata (modelVersionIds,
+            # browsingLevel) is present, losing all generation parameters.
+            exif_metadata = None
+            if not is_video:
+                exif_metadata = await asyncio.to_thread(
                     self._exif_utils.extract_image_metadata, temp_path
                 )
 
-            if not metadata and civitai_image_id and image_info:
+            # Fallback: try the original (non-optimized) image for EXIF data
+            if not exif_metadata and civitai_image_id and image_info:
                 original_url = image_info.get("url")
                 if original_url:
                     self._logger.debug(
@@ -187,15 +221,38 @@ class RecipeAnalysisService:
                     orig_temp_path = self._create_temp_path(suffix=".png")
                     try:
                         await self._download_image(original_url, orig_temp_path)
-                        metadata = await asyncio.to_thread(
+                        exif_metadata = await asyncio.to_thread(
                             self._exif_utils.extract_image_metadata,
                             orig_temp_path,
                         )
                     finally:
                         self._safe_cleanup(orig_temp_path)
 
+            # Parse EXIF data (typically a string like parameters/prompt/workflow)
+            # and API metadata (dict with modelVersionIds, browsingLevel) separately,
+            # then merge: API loras/checkpoint override, EXIF gen_params fill in gaps.
+            # This mirrors the two-pass approach in _do_import_from_url.
+            exif_parsed_result = None
+            if isinstance(exif_metadata, str):
+                exif_parser = self._recipe_parser_factory.create_parser(exif_metadata)
+                if exif_parser:
+                    exif_data = await exif_parser.parse_metadata(
+                        exif_metadata, recipe_scanner=recipe_scanner,
+                    )
+                    if exif_data and not exif_data.get("error"):
+                        exif_parsed_result = exif_data
+
+            # Merge API metadata (dict) with EXIF data (if dict) for the
+            # CivitaiApiMetadataParser.  If EXIF data is a string it was
+            # parsed above — don't try to merge a string into a dict.
+            merged = {}
+            if isinstance(exif_metadata, dict):
+                merged.update(exif_metadata)
+            if isinstance(metadata, dict):
+                merged.update(metadata)
+
             result = await self._parse_metadata(
-                metadata or {},
+                merged,
                 recipe_scanner=recipe_scanner,
                 image_path=temp_path,
                 include_image_base64=True,
@@ -203,13 +260,23 @@ class RecipeAnalysisService:
                 extension=extension,
             )
 
-            if civitai_image_id and image_info and not result.payload.get("error"):
-                mvid = image_info.get("modelVersionId")
-                if not mvid:
-                    mvids = image_info.get("modelVersionIds")
-                    if isinstance(mvids, list) and mvids:
-                        mvid = mvids[0]
+            # Merge EXIF string-parsed gen_params into the API result.
+            # API gen_params take priority (they come later via update).
+            if exif_parsed_result and not result.payload.get("error"):
+                exif_gp = exif_parsed_result.get("gen_params") or {}
+                result_gp = result.payload.get("gen_params") or {}
+                merged_gp = {**exif_gp, **result_gp}
+                if merged_gp:
+                    result.payload["gen_params"] = merged_gp
 
+            if civitai_image_id and image_info and not result.payload.get("error"):
+                # Use the metadata dict we built (may contain modelVersionIds
+                # and browsingLevel from the API root level).  Do NOT pass
+                # image_info.get("meta") — it is null for images whose meta
+                # lives at the root level only.  Also do NOT derive
+                # model_version_id from modelVersionIds[0] — that array mixes
+                # checkpoints, LoRAs, and other types without ordering
+                # guarantees; the parser already resolved them correctly.
                 recipe_for_enrich = {
                     "gen_params": result.payload.get("gen_params", {}),
                     "loras": result.payload.get("loras", []),
@@ -222,8 +289,10 @@ class RecipeAnalysisService:
                     recipe=recipe_for_enrich,
                     civitai_client=civitai_client,
                     request_params=None,
-                    prefetched_civitai_meta_raw=image_info.get("meta"),
-                    prefetched_model_version_id=mvid,
+                    prefetched_civitai_meta_raw=(
+                        metadata if isinstance(metadata, dict) else None
+                    ),
+                    prefetched_model_version_id=None,
                 )
 
                 result.payload["gen_params"] = recipe_for_enrich["gen_params"]
@@ -232,6 +301,12 @@ class RecipeAnalysisService:
                 if recipe_for_enrich.get("base_model"):
                     result.payload["base_model"] = recipe_for_enrich["base_model"]
 
+                # Extract browsingLevel from our constructed metadata for NSFW blur
+                if isinstance(metadata, dict):
+                    bl = metadata.get("browsingLevel")
+                    if isinstance(bl, int) and bl > 0:
+                        result.payload["preview_nsfw_level"] = bl
+
             return result
         finally:
             if temp_path:
@@ -314,6 +389,10 @@ class RecipeAnalysisService:
             "prompt_type",
             "positive",
             "negative",
+            # modelVersionIds is injected at the root level by CivitAI's image
+            # API when meta is null. It carries the version IDs of ALL models
+            # (checkpoint + LoRAs) used to generate the image.
+            "modelVersionIds",
         }
         return any(field in metadata for field in recipe_fields)
 

py/utils/constants.py

@@ -147,6 +147,8 @@ DIFFUSION_MODEL_BASE_MODELS = frozenset(
         "Qwen",
         "ZImageBase",
         "ZImageTurbo",
+        # Krea 2 — loaded via UNETLoader in ComfyUI
+        "Krea 2",
     ]
 )
 

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-lora-manager"
 description = "Revolutionize your workflow with the ultimate LoRA companion for ComfyUI!"
-version = "1.1.5"
+version = "1.1.6"
 license = {file = "LICENSE"}
 dependencies = [
     "aiohttp",

refs/civarc_api_model_data.json

@@ -1,134 +0,0 @@
-{
-    "id": 1746460,
-    "name": "Mixplin Style [Illustrious]",
-    "type": "LORA",
-    "description": "description",
-    "username": "Ty_Lee",
-    "downloadCount": 4207,
-    "favoriteCount": 0,
-    "commentCount": 8,
-    "ratingCount": 0,
-    "rating": 0,
-    "is_nsfw": true,
-    "nsfw_level": 31,
-    "createdAt": "2025-07-06T01:51:42.859Z",
-    "updatedAt": "2025-10-10T23:15:26.714Z",
-    "deletedAt": null,
-    "tags": [
-        "art",
-        "style",
-        "artist style",
-        "styles",
-        "mixplin",
-        "artiststyle"
-    ],
-    "creator_id": "Ty_Lee",
-    "creator_username": "Ty_Lee",
-    "creator_name": "Ty_Lee",
-    "creator_url": "/users/Ty_Lee",
-    "versions": [
-        {
-            "id": 2042594,
-            "name": "v2.0",
-            "href": "/models/1746460?modelVersionId=2042594"
-        },
-        {
-            "id": 1976567,
-            "name": "v1.0",
-            "href": "/models/1746460?modelVersionId=1976567"
-        }
-    ],
-    "version": {
-        "id": 1976567,
-        "modelId": 1746460,
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-        "baseModel": "Illustrious",
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-        "description": null,
-        "downloadCount": 437,
-        "ratingCount": 0,
-        "rating": 0,
-        "is_nsfw": true,
-        "nsfw_level": 31,
-        "createdAt": "2025-07-05T10:17:28.716Z",
-        "updatedAt": "2025-10-10T23:15:26.756Z",
-        "deletedAt": null,
-        "files": [
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-                "id": 1874043,
-                "name": "mxpln-illustrious-ty_lee.safetensors",
-                "type": "Model",
-                "sizeKB": 223124.37109375,
-                "downloadUrl": "https://civitai.com/api/download/models/1976567",
-                "modelId": 1746460,
-                "modelName": "Mixplin Style [Illustrious]",
-                "modelVersionId": 1976567,
-                "is_nsfw": true,
-                "nsfw_level": 31,
-                "sha256": "e2b7a280d6539556f23f380b3f71e4e22bc4524445c4c96526e117c6005c6ad3",
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-                "updatedAt": "2025-10-10T23:15:26.766Z",
-                "is_primary": false,
-                "mirrors": [
-                    {
-                        "filename": "mxpln-illustrious-ty_lee.safetensors",
-                        "url": "https://civitai.com/api/download/models/1976567",
-                        "source": "civitai",
-                        "model_id": 1746460,
-                        "model_version_id": 1976567,
-                        "deletedAt": null,
-                        "is_gated": false,
-                        "is_paid": false
-                    }
-                ]
-            }
-        ],
-        "images": [
-            {
-                "id": 86403595,
-                "url": "https://img.genur.art/sig/width:450/quality:85/aHR0cHM6Ly9jLmdlbnVyLmFydC9hNmE3Njc2YS0wMWQ3LTQ1YzAtOWEzYS1mNWJiYTU4MDNiMDE=",
-                "nsfwLevel": 1,
-                "width": 1560,
-                "height": 2280,
-                "hash": "U7G8Zp0w02%IA6%N00-;D]-W~VNG0nMw-.IV",
-                "type": "image",
-                "minor": false,
-                "poi": false,
-                "hasMeta": true,
-                "hasPositivePrompt": true,
-                "onSite": false,
-                "remixOfId": null,
-                "image_url": "https://img.genur.art/sig/width:450/quality:85/aHR0cHM6Ly9jLmdlbnVyLmFydC9hNmE3Njc2YS0wMWQ3LTQ1YzAtOWEzYS1mNWJiYTU4MDNiMDE=",
-                "link": "https://genur.art/posts/86403595"
-            }
-        ],
-        "trigger": [
-            "mxpln"
-        ],
-        "allow_download": true,
-        "download_url": "/api/download/models/1976567",
-        "platform_url": "https://civitai.com/models/1746460?modelVersionId=1976567",
-        "civitai_model_id": 1746460,
-        "civitai_model_version_id": 1976567,
-        "href": "/models/1746460?modelVersionId=1976567",
-        "mirrors": [
-            {
-                "platform": "tensorart",
-                "href": "/tensorart/models/904473536033245448/versions/904473536033245448",
-                "platform_url": "https://tensor.art/models/904473536033245448",
-                "name": "Mixplin Style MXP",
-                "version_name": "Mixplin",
-                "id": "904473536033245448",
-                "version_id": "904473536033245448"
-            }
-        ]
-    },
-    "platform": "civitai",
-    "platform_name": "CivitAI",
-    "meta": {
-        "title": "Mixplin Style [Illustrious] - v1.0 - CivitAI Archive",
-        "description": "Mixplin Style [Illustrious] v1.0 is a Illustrious LORA AI model created by Ty_Lee for generating images of art, style, artist style, styles, mixplin, artiststyle",
-        "image": "https://img.genur.art/sig/width:450/quality:85/aHR0cHM6Ly9jLmdlbnVyLmFydC9hNmE3Njc2YS0wMWQ3LTQ1YzAtOWEzYS1mNWJiYTU4MDNiMDE=",
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-    }
-}

refs/civitai.sql

@@ -1,38 +0,0 @@
-CREATE TABLE models (
-            id         INTEGER PRIMARY KEY,
-            name       TEXT NOT NULL,
-            type       TEXT NOT NULL,
-            username   TEXT,
-            data       TEXT NOT NULL,
-            created_at INTEGER NOT NULL,
-            updated_at INTEGER NOT NULL
-        ) STRICT;
-CREATE TABLE model_versions (
-            id           INTEGER PRIMARY KEY,
-            model_id     INTEGER NOT NULL,
-            position     INTEGER NOT NULL,
-            name         TEXT NOT NULL,
-            base_model   TEXT NOT NULL,
-            published_at INTEGER,
-            data         TEXT NOT NULL,
-            created_at   INTEGER NOT NULL,
-            updated_at   INTEGER NOT NULL
-        ) STRICT;
-CREATE INDEX model_versions_model_id_idx ON model_versions (model_id);
-CREATE TABLE model_files (
-            id               INTEGER PRIMARY KEY,
-            model_id         INTEGER NOT NULL,
-            version_id       INTEGER NOT NULL,
-            type             TEXT NOT NULL,
-            sha256           TEXT,
-            data             TEXT NOT NULL,
-            created_at       INTEGER NOT NULL,
-            updated_at       INTEGER NOT NULL
-        ) STRICT;
-CREATE INDEX model_files_model_id_idx ON model_files (model_id);
-CREATE INDEX model_files_version_id_idx ON model_files (version_id);
-CREATE TABLE archived_model_files (
-            file_id INTEGER PRIMARY KEY,
-            model_id INTEGER NOT NULL,
-            version_id INTEGER NOT NULL
-        ) STRICT;

refs/civitai_api_model_by_modelId.json

@@ -1,110 +0,0 @@
-{
-    "id": 1231067,
-    "name": "Vivid Impressions Storybook Style",
-    "description": "<h3 id=\"if-you'd-like-to-support-me-feel-free-to-visit-my-ko-fi-page.-please-share-your-images-using-the-&quot;+add-post&quot;-button-below.-it-supports-the-creators.-thanks!-nnfwkvfly\">If you'd like to support me, feel free to visit my <a target=\"_blank\" rel=\"ugc\" href=\"https://ko-fi.com/pixelpawsai\">Ko-Fi</a> page. ❤️<br /><br />Please share your images using the \"<span style=\"color:rgb(250, 82, 82)\">+add post</span>\" button below. It supports the creators. Thanks! 💕</h3><h3 id=\"if-you-like-my-lora-please-like-comment-or-donate-some-buzz.-much-appreciated!-vyeqok3go\">If you like my LoRA, please<span style=\"color:rgb(230, 73, 128)\"> </span><span style=\"color:rgb(250, 82, 82)\">like</span>, <span style=\"color:rgb(250, 82, 82)\">comment</span>, or <span style=\"color:#fa5252\">donate some Buzz</span>. Much appreciated! ❤️</h3><h3 id=\"-lo912t8rj\"></h3><h3 id=\"trigger-word:-ppstorybook-wlggllim2\"><strong><span style=\"color:rgb(253, 126, 20)\">Trigger word: </span></strong>ppstorybook</h3><h3 id=\"strength:-0.8-experiment-as-you-like-luvhks6za\"><strong><span style=\"color:rgb(253, 126, 20)\">Strength: </span></strong>0.8, experiment as you like</h3>",
-    "allowNoCredit": true,
-    "allowCommercialUse": [
-        "Image",
-        "RentCivit",
-        "Rent",
-        "Sell"
-    ],
-    "allowDerivatives": true,
-    "allowDifferentLicense": true,
-    "type": "LORA",
-    "minor": false,
-    "sfwOnly": false,
-    "poi": false,
-    "nsfw": false,
-    "nsfwLevel": 1,
-    "availability": "Public",
-    "cosmetic": null,
-    "supportsGeneration": true,
-    "stats": {
-        "downloadCount": 2183,
-        "favoriteCount": 0,
-        "thumbsUpCount": 416,
-        "thumbsDownCount": 0,
-        "commentCount": 12,
-        "ratingCount": 0,
-        "rating": 0,
-        "tippedAmountCount": 360
-    },
-    "creator": {
-        "username": "PixelPawsAI",
-        "image": "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/f3a1aa7c-0159-4dd8-884a-1e7ceb350f96/width=96/PixelPawsAI.jpeg"
-    },
-    "tags": [
-        "style",
-        "illustration",
-        "storybook"
-    ],
-    "modelVersions": [
-        {
-            "id": 1387174,
-            "index": 0,
-            "name": "v1.0",
-            "baseModel": "Flux.1 D",
-            "baseModelType": "Standard",
-            "createdAt": "2025-02-08T11:15:47.197Z",
-            "publishedAt": "2025-02-08T11:29:04.487Z",
-            "status": "Published",
-            "availability": "Public",
-            "nsfwLevel": 1,
-            "trainedWords": [
-                "ppstorybook"
-            ],
-            "covered": true,
-            "stats": {
-                "downloadCount": 2183,
-                "ratingCount": 0,
-                "rating": 0,
-                "thumbsUpCount": 416,
-                "thumbsDownCount": 0
-            },
-            "files": [
-                {
-                    "id": 1289799,
-                    "sizeKB": 18829.1484375,
-                    "name": "pp-storybook_rank2_bf16.safetensors",
-                    "type": "Model",
-                    "pickleScanResult": "Success",
-                    "pickleScanMessage": "No Pickle imports",
-                    "virusScanResult": "Success",
-                    "virusScanMessage": null,
-                    "scannedAt": "2025-02-08T11:21:04.247Z",
-                    "metadata": {
-                        "format": "SafeTensor"
-                    },
-                    "hashes": {
-                        "AutoV1": "F414C813",
-                        "AutoV2": "9753338AB6",
-                        "SHA256": "9753338AB693CA82BF89ED77A5D1912879E40051463EC6E330FB9866CE798668",
-                        "CRC32": "A65AE7B3",
-                        "BLAKE3": "A5F8AB95AC2486345E4ACCAE541FF19D97ED53EFB0A7CC9226636975A0437591",
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-                    },
-                    "downloadUrl": "https://civitai.com/api/download/models/1387174",
-                    "primary": true
-                }
-            ],
-            "images": [
-                {
-                    "url": "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/42b875cf-c62b-41fa-a349-383b7f074351/original=true/56547310.jpeg",
-                    "nsfwLevel": 1,
-                    "width": 832,
-                    "height": 1216,
-                    "hash": "U5IiO6s-4Vn+0~EO^5xa00VsL#IU_O?E7yWC",
-                    "type": "image",
-                    "minor": false,
-                    "poi": false,
-                    "hasMeta": true,
-                    "hasPositivePrompt": true,
-                    "onSite": false,
-                    "remixOfId": null
-                }
-            ],
-            "downloadUrl": "https://civitai.com/api/download/models/1387174"
-        }
-    ]
-}

refs/civitai_api_model_by_versionId.json

@@ -1,100 +0,0 @@
-{
-    "id": 1387174,
-    "modelId": 1231067,
-    "name": "v1.0",
-    "createdAt": "2025-02-08T11:15:47.197Z",
-    "updatedAt": "2025-02-08T11:29:04.526Z",
-    "status": "Published",
-    "publishedAt": "2025-02-08T11:29:04.487Z",
-    "trainedWords": [
-        "ppstorybook"
-    ],
-    "trainingStatus": null,
-    "trainingDetails": null,
-    "baseModel": "Flux.1 D",
-    "baseModelType": null,
-    "earlyAccessEndsAt": null,
-    "earlyAccessConfig": null,
-    "description": null,
-    "uploadType": "Created",
-    "usageControl": "Download",
-    "air": "urn:air:flux1:lora:civitai:1231067@1387174",
-    "stats": {
-        "downloadCount": 1436,
-        "ratingCount": 0,
-        "rating": 0,
-        "thumbsUpCount": 316
-    },
-    "model": {
-        "name": "Vivid Impressions Storybook Style",
-        "type": "LORA",
-        "nsfw": false,
-        "poi": false
-    },
-    "files": [
-        {
-            "id": 1289799,
-            "sizeKB": 18829.1484375,
-            "name": "pp-storybook_rank2_bf16.safetensors",
-            "type": "Model",
-            "pickleScanResult": "Success",
-            "pickleScanMessage": "No Pickle imports",
-            "virusScanResult": "Success",
-            "virusScanMessage": null,
-            "scannedAt": "2025-02-08T11:21:04.247Z",
-            "metadata": {
-                "format": "SafeTensor",
-                "size": null,
-                "fp": null
-            },
-            "hashes": {
-                "AutoV1": "F414C813",
-                "AutoV2": "9753338AB6",
-                "SHA256": "9753338AB693CA82BF89ED77A5D1912879E40051463EC6E330FB9866CE798668",
-                "CRC32": "A65AE7B3",
-                "BLAKE3": "A5F8AB95AC2486345E4ACCAE541FF19D97ED53EFB0A7CC9226636975A0437591",
-                "AutoV3": "34A22376739D"
-            },
-            "primary": true,
-            "downloadUrl": "https://civitai.com/api/download/models/1387174"
-        }
-    ],
-    "images": [
-        {
-            "url": "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/42b875cf-c62b-41fa-a349-383b7f074351/width=832/56547310.jpeg",
-            "nsfwLevel": 1,
-            "width": 832,
-            "height": 1216,
-            "hash": "U5IiO6s-4Vn+0~EO^5xa00VsL#IU_O?E7yWC",
-            "type": "image",
-            "metadata": {
-                "hash": "U5IiO6s-4Vn+0~EO^5xa00VsL#IU_O?E7yWC",
-                "size": 1361590,
-                "width": 832,
-                "height": 1216
-            },
-            "meta": {
-                "Size": "832x1216",
-                "seed": 1116375220995209,
-                "Model": "flux_dev_fp8",
-                "steps": 23,
-                "hashes": {
-                    "model": ""
-                },
-                "prompt": "ppstorybook,A dreamy bunny hopping across a rainbow bridge, with fluffy clouds surrounding it and tiny birds flying alongside, rendered in a magical, soft-focus style with pastel hues and glowing accents.",
-                "Version": "ComfyUI",
-                "sampler": "DPM++ 2M",
-                "cfgScale": 3.5,
-                "clipSkip": 1,
-                "resources": [],
-                "Model hash": ""
-            },
-            "availability": "Public",
-            "hasMeta": true,
-            "hasPositivePrompt": true,
-            "onSite": false,
-            "remixOfId": null
-        }
-    ],
-    "downloadUrl": "https://civitai.com/api/download/models/1387174"
-}

refs/civitai_comfy_metadata.json

@@ -1,153 +0,0 @@
-{
-    "resource-stack": {
-      "class_type": "CheckpointLoaderSimple",
-      "inputs": { "ckpt_name": "urn:air:sdxl:checkpoint:civitai:827184@1410435" }
-    },
-    "resource-stack-1": {
-      "class_type": "LoraLoader",
-      "inputs": {
-        "lora_name": "urn:air:sdxl:lora:civitai:1107767@1253442",
-        "strength_model": 1,
-        "strength_clip": 1,
-        "model": ["resource-stack", 0],
-        "clip": ["resource-stack", 1]
-      }
-    },
-    "resource-stack-2": {
-      "class_type": "LoraLoader",
-      "inputs": {
-        "lora_name": "urn:air:sdxl:lora:civitai:1342708@1516344",
-        "strength_model": 1,
-        "strength_clip": 1,
-        "model": ["resource-stack-1", 0],
-        "clip": ["resource-stack-1", 1]
-      }
-    },
-    "resource-stack-3": {
-      "class_type": "LoraLoader",
-      "inputs": {
-        "lora_name": "urn:air:sdxl:lora:civitai:122359@135867",
-        "strength_model": 1.55,
-        "strength_clip": 1,
-        "model": ["resource-stack-2", 0],
-        "clip": ["resource-stack-2", 1]
-      }
-    },
-    "6": {
-      "class_type": "smZ CLIPTextEncode",
-      "inputs": {
-        "text": "masterpiece, best quality, amazing quality, detailed setting, detailed background, 1girl, yunyun (konosuba), nude, red eyes, hair ornament, braid, hair between eyes,low twintails, pink ribbon, bow, hair bow, pussy, frilled skirt, layered skirt, belt, pink thighhighs, (pussy juice), large insertion, vaginal tugging, pussy grip, detailed skin, detailed soles, stretched pussy, feet in stockings, ass, nipples, medium breasts, french kiss, anus, shocked, nervous, penis awe,  BREAK Professor\u0027s office, college student, pornographic, 1boy, close eyes, (musscular male, detailed large cock), vaginal sex, college office setting, ass grab, fucking, riding, cowgirl, erotic, side view, deep fucking",
-        "parser": "comfy",
-        "text_g": "",
-        "text_l": "",
-        "ascore": 2.5,
-        "width": 0,
-        "height": 0,
-        "crop_w": 0,
-        "crop_h": 0,
-        "target_width": 0,
-        "target_height": 0,
-        "smZ_steps": 1,
-        "mean_normalization": true,
-        "multi_conditioning": true,
-        "use_old_emphasis_implementation": false,
-        "with_SDXL": false,
-        "clip": ["resource-stack-3", 1]
-      },
-      "_meta": { "title": "Positive" }
-    },
-    "7": {
-      "class_type": "smZ CLIPTextEncode",
-      "inputs": {
-        "text": "bad quality,worst quality,worst detail,sketch,censor",
-        "parser": "comfy",
-        "text_g": "",
-        "text_l": "",
-        "ascore": 2.5,
-        "width": 0,
-        "height": 0,
-        "crop_w": 0,
-        "crop_h": 0,
-        "target_width": 0,
-        "target_height": 0,
-        "smZ_steps": 1,
-        "mean_normalization": true,
-        "multi_conditioning": true,
-        "use_old_emphasis_implementation": false,
-        "with_SDXL": false,
-        "clip": ["resource-stack-3", 1]
-      },
-      "_meta": { "title": "Negative" }
-    },
-    "20": {
-      "class_type": "UpscaleModelLoader",
-      "inputs": { "model_name": "urn:air:other:upscaler:civitai:147759@164821" },
-      "_meta": { "title": "Load Upscale Model" }
-    },
-    "17": {
-      "class_type": "LoadImage",
-      "inputs": {
-        "image": "https://orchestration.civitai.com/v2/consumer/blobs/5KZ6358TW8CNEGPZKD08NVDB30",
-        "upload": "image"
-      },
-      "_meta": { "title": "Image Load" }
-    },
-    "19": {
-      "class_type": "ImageUpscaleWithModel",
-      "inputs": { "upscale_model": ["20", 0], "image": ["17", 0] },
-      "_meta": { "title": "Upscale Image (using Model)" }
-    },
-    "23": {
-      "class_type": "ImageScale",
-      "inputs": {
-        "upscale_method": "nearest-exact",
-        "crop": "disabled",
-        "width": 1280,
-        "height": 1856,
-        "image": ["19", 0]
-      },
-      "_meta": { "title": "Upscale Image" }
-    },
-    "21": {
-      "class_type": "VAEEncode",
-      "inputs": { "pixels": ["23", 0], "vae": ["resource-stack", 2] },
-      "_meta": { "title": "VAE Encode" }
-    },
-    "11": {
-      "class_type": "KSampler",
-      "inputs": {
-        "sampler_name": "euler_ancestral",
-        "scheduler": "normal",
-        "seed": 2088370631,
-        "steps": 47,
-        "cfg": 6.5,
-        "denoise": 0.3,
-        "model": ["resource-stack-3", 0],
-        "positive": ["6", 0],
-        "negative": ["7", 0],
-        "latent_image": ["21", 0]
-      },
-      "_meta": { "title": "KSampler" }
-    },
-    "13": {
-      "class_type": "VAEDecode",
-      "inputs": { "samples": ["11", 0], "vae": ["resource-stack", 2] },
-      "_meta": { "title": "VAE Decode" }
-    },
-    "12": {
-      "class_type": "SaveImage",
-      "inputs": { "filename_prefix": "ComfyUI", "images": ["13", 0] },
-      "_meta": { "title": "Save Image" }
-    },
-    "extra": {
-      "airs": [
-        "urn:air:other:upscaler:civitai:147759@164821",
-        "urn:air:sdxl:checkpoint:civitai:827184@1410435",
-        "urn:air:sdxl:lora:civitai:1107767@1253442",
-        "urn:air:sdxl:lora:civitai:1342708@1516344",
-        "urn:air:sdxl:lora:civitai:122359@135867"
-      ]
-    },
-    "extraMetadata": "{\u0022prompt\u0022:\u0022masterpiece, best quality, amazing quality, detailed setting, detailed background, 1girl, yunyun (konosuba), nude, red eyes, hair ornament, braid, hair between eyes,low twintails, pink ribbon, bow, hair bow, pussy, frilled skirt, layered skirt, belt, pink thighhighs, (pussy juice), large insertion, vaginal tugging, pussy grip, detailed skin, detailed soles, stretched pussy, feet in stockings, ass, nipples, medium breasts, french kiss, anus, shocked, nervous, penis awe,  BREAK Professor\u0027s office, college student, pornographic, 1boy, close eyes, (musscular male, detailed large cock), vaginal sex, college office setting, ass grab, fucking, riding, cowgirl, erotic, side view, deep fucking\u0022,\u0022negativePrompt\u0022:\u0022bad quality,worst quality,worst detail,sketch,censor\u0022,\u0022steps\u0022:47,\u0022cfgScale\u0022:6.5,\u0022sampler\u0022:\u0022euler_ancestral\u0022,\u0022workflowId\u0022:\u0022img2img-hires\u0022,\u0022resources\u0022:[{\u0022modelVersionId\u0022:1410435,\u0022strength\u0022:1},{\u0022modelVersionId\u0022:1410435,\u0022strength\u0022:1},{\u0022modelVersionId\u0022:1253442,\u0022strength\u0022:1},{\u0022modelVersionId\u0022:1516344,\u0022strength\u0022:1},{\u0022modelVersionId\u0022:135867,\u0022strength\u0022:1.55}],\u0022remixOfId\u0022:32140259}"
-  }
-  

refs/jpeg_civitai_exif_userComment_example

@@ -1,18 +0,0 @@
-a dynamic and dramatic digital artwork featuring a stylized anthropomorphic white tiger with striking yellow eyes. The tiger is depicted in a powerful stance, wielding a katana with one hand raised above its head. Its fur is detailed with black stripes, and its mane flows wildly, blending with the stormy background. The scene is set amidst swirling dark clouds and flashes of lightning, enhancing the sense of movement and energy. The composition is vertical, with the tiger positioned centrally, creating a sense of depth and intensity. The color palette is dominated by shades of blue, gray, and white, with bright highlights from the lightning. The overall style is reminiscent of fantasy or manga art, with a focus on dynamic action and dramatic lighting.
-Negative prompt:
-Steps: 30, Sampler: Undefined, CFG scale: 3.5, Seed: 90300501, Size: 832x1216, Clip skip: 2, Created Date: 2025-03-05T13:51:18.1770234Z, Civitai resources: [{"type":"checkpoint","modelVersionId":691639,"modelName":"FLUX","modelVersionName":"Dev"},{"type":"lora","weight":0.4,"modelVersionId":1202162,"modelName":"Velvet\u0027s Mythic Fantasy Styles | Flux \u002B Pony \u002B illustrious","modelVersionName":"Flux Gothic Lines"},{"type":"lora","weight":0.8,"modelVersionId":1470588,"modelName":"Velvet\u0027s Mythic Fantasy Styles | Flux \u002B Pony \u002B illustrious","modelVersionName":"Flux Retro"},{"type":"lora","weight":0.75,"modelVersionId":746484,"modelName":"Elden Ring - Yoshitaka Amano","modelVersionName":"V1"},{"type":"lora","weight":0.2,"modelVersionId":914935,"modelName":"Ink-style","modelVersionName":"ink-dynamic"},{"type":"lora","weight":0.2,"modelVersionId":1189379,"modelName":"Painterly Fantasy by ChronoKnight - [FLUX \u0026 IL]","modelVersionName":"FLUX"},{"type":"lora","weight":0.2,"modelVersionId":757030,"modelName":"Mezzotint Artstyle for Flux - by Ethanar","modelVersionName":"V1"}], Civitai metadata: {}
-
-masterpiece, best quality, good quality, very aesthetic, absurdres, newest, 8K, depth of field, focused subject,
-dynamic angle, dutch angle, from below, epic half body portrait, gritty, wabi sabi, looking at viewer, woman is a geisha, parted lips,
-holographic skin, holofoil glitter, faint, glowing, ethereal, neon hair, glowing hair, otherworldly glow, she is dangerous
-<lora:ck-shadow-circuit-IL:0.78>, <lora:ck-nc-cyberpunk-IL-000011:0.4>, <lora:ck-neon-retrowave-IL:0.2>, <lora:ck-yoneyama-mai-IL-000014:0.4>
-Negative prompt: score_6, score_5, score_4, bad quality, worst quality, worst detail, sketch, censorship, furry, window, headphones,
-Steps: 30, Sampler: Euler a, Schedule type: Simple, CFG scale: 7, Seed: 1405717592, Size: 832x1216, Model hash: 1ad6ca7f70, Model: waiNSFWIllustrious_v100, Denoising strength: 0.35, Hires CFG Scale: 5, Hires upscale: 1.3, Hires steps: 20, Hires upscaler: 4x-AnimeSharp, Lora hashes: "ck-shadow-circuit-IL: 88e247aa8c3d, ck-nc-cyberpunk-IL-000011: 935e6755554c, ck-neon-retrowave-IL: edafb9df7da1, ck-yoneyama-mai-IL-000014: 1b9305692a2e", Version: f2.0.1v1.10.1-1.10.1, Diffusion in Low Bits: Automatic (fp16 LoRA)
-
-Masterpiece, best quality, high quality, newest, highres, 8K, HDR, absurdres, 1girl, solo, futuristic warrior, sleek exosuit with glowing energy cores, long braided hair flowing behind, gripping a high-tech bow with an energy arrow drawn, standing on a floating platform overlooking a massive space station, planets and nebulae in the distance, soft glow from distant stars, cinematic depth, foreshortening, dynamic pose, dramatic sci-fi lighting.
-Negative prompt: worst quality, normal quality, anatomical nonsense, bad anatomy,interlocked fingers, extra fingers,watermark,simple background, loli,
-Steps: 20, Sampler: euler_ancestral_karras, CFG scale: 8.0, Seed: 691121152183439, Model: il\waiNSFWIllustrious_v110.safetensors, Model hash: c3688ee04c, Lora_0 Model name: iLLMythAn1m3Style.safetensors, Lora_0 Model hash: ba7a040786, Lora_0 Strength model: 1.0, Lora_0 Strength clip: 1.0, Hashes: {"model": "c3688ee04c", "lora:iLLMythAn1m3Style": "ba7a040786"}
-
-Immerse yourself in the enchanting journey, where harmonious transmutation of Bauhaus art unites photographic precision and contemporary illustration, capturing an enthralling blend between vivid abstract nature and urban landscapes. Let your eyes be captivated by a kaleidoscope of rich, deep reds and yellows, entwined with intriguing shades that beckon a somber atmosphere. As your spirit ventures along this haunting path, witness the mysterious, high-angle perspective dominated by scattered clouds – granting you a mesmerizing glimpse into the ever-transforming realm of metamorphosing environments. ,<lora:flux/fav/ck-charcoal-drawing-000014.safetensors:1.0:1.0>   
-Negative prompt:
-Steps: 20, Sampler: Euler, CFG scale: 3.5, Seed: 885491426361006, Size: 832x1216, Model hash: 4610115bb0, Model: flux_dev, Hashes: {"LORA:flux/fav/ck-charcoal-drawing-000014.safetensors": "34d36c17c1", "model": "4610115bb0"}, Version: ComfyUI

refs/meta_format.txt

@@ -1,3 +0,0 @@
-In this ethereal masterpiece, metallic sculptures juxtapose effortlessly against a subtle backdrop of misty neutral hues. Exquisite curvatures and geometric shapes converge harmoniously, creating an illuminating realm of polished metallic surfaces. Shimmering copper, gleaming silver, and lustrous gold hues dance in perfect balance, highlighting the intricate play of light and shadow cast upon these celestial forms.  A halo of diffused radiance envelops each piece, enhancing their textured depths and metallic brilliance while allowing delicate details to emerge from obscurity. The composition conveys a serene yet mesmerizing atmosphere, as if suspended in a dreamlike limbo between reality and fantasy. The tantalizing interplay of colors within this transcendent realm creates a profound sense of depth and grandeur that invites the viewer into an enchanting voyage through abstract metallic beauty.  This captivating artwork evokes emotions of boundless curiosity and reverence reminiscent of the timeless works by artists such as Giorgio de Chirico or Paul Klee, while asserting a unique, modern artistic sensibility. With every observation, a new nuance unfolds, as if a never-ending story waiting to be discovered through the lens of metallic artistry.
-Negative prompt:
-Steps: 25, Sampler: dpmpp_2m_sgm_uniform, Seed: 471889513588087, Model: Fluxmania V5P.safetensors, Model hash: 8ae0583b06, VAE: ae.sft, VAE hash: afc8e28272, Lora_0 Model name: ArtVador I.safetensors, Lora_0 Model hash: 08f7133a58, Lora_0 Strength model: 0.65, Lora_0 Strength clip: 0.65, Lora_1 Model name: Kaoru Yamada.safetensors, Lora_1 Model hash: d4893f7202, Lora_1 Strength model: 0.75, Lora_1 Strength clip: 0.75, Hashes: {"model": "8ae0583b06", "vae": "afc8e28272", "lora:ArtVador I": "08f7133a58", "lora:Kaoru Yamada": "d4893f7202"}

refs/recipe.json

@@ -1,33 +0,0 @@
-{
-    "id": "42803a29-02dc-49e1-b798-27da70e8b408",
-    "file_path": "/home/miao/workspace/ComfyUI/models/loras/recipes/test/42803a29-02dc-49e1-b798-27da70e8b408.webp",
-    "title": "masterpiece, best quality, amazing quality, very aesthetic, detailed eyes, perfect",
-    "modified": 1754897325.0507245,
-    "created_date": 1754897325.0507245,
-    "base_model": "Illustrious",
-    "loras": [
-        {
-            "file_name": "",
-            "hash": "1b5b763d83961bb5745f3af8271ba83f1d4fd69c16278dae6d5b4e194bdde97a",
-            "strength": 1.0,
-            "modelVersionId": 2007092,
-            "modelName": "Pony: People's Works +",
-            "modelVersionName": "v8_Illusv1.0",
-            "isDeleted": false,
-            "exclude": false
-        }
-    ],
-    "gen_params": {
-        "prompt": "masterpiece, best quality, amazing quality, very aesthetic, detailed eyes, perfect eyes, realistic eyes,\n(flat colors:1.5), (anime:1.5), (lineart:1.5),\nclose-up, solo, tongue, 1girl, food, (saliva:0.1), open mouth, candy, simple background, blue background, large lollipop, tongue out, fade background, lips, hand up, holding, looking at viewer, licking, seductive, half-closed eyes,",
-        "negative_prompt": "shiny skin,",
-        "steps": 19,
-        "sampler": "Euler a",
-        "cfg_scale": 5,
-        "seed": 1765271748,
-        "size": "832x1216",
-        "clip_skip": 2
-    },
-    "fingerprint": "1b5b763d83961bb5745f3af8271ba83f1d4fd69c16278dae6d5b4e194bdde97a:1.0",
-    "source_path": "https://civitai.com/images/92427432",
-    "folder": "test"
-}

refs/target_version.json

@@ -1,42 +0,0 @@
-{
-  "id": 2269146,
-  "modelId": 2004760,
-  "name": "v1.0 Illustrious",
-  "nsfwLevel": 1,
-  "trainedWords": ["PencilSketchDaal"],
-  "baseModel": "Illustrious",
-  "description": "<p>Illustrious. Your pencil may vary with your checkpoint. </p>",
-  "model": {
-    "name": "Pencil Sketch Anime",
-    "type": "LORA",
-    "nsfw": false,
-    "description": "description",
-    "tags": ["style"],
-    "allowNoCredit": true,
-    "allowCommercialUse": ["Sell"],
-    "allowDerivatives": true,
-    "allowDifferentLicense": true
-  },
-  "files": [
-    {
-      "id": 2161260,
-      "sizeKB": 223106.37890625,
-      "name": "Pencil-Sketch-Illustrious.safetensors",
-      "type": "Model",
-      "hashes": {
-        "SHA256": "2C70479CD673B0FE056EAF4FD97C7F33A39F14853805431AC9AB84226ECE3B82"
-      },
-      "primary": true,
-      "downloadUrl": "https://civitai.com/api/download/models/2269146",
-      "mirrors": {}
-    }
-  ],
-  "images": [
-    {},
-    {}
-  ],
-  "creator": {
-    "username": "Daalis",
-    "image": "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/eb245b49-edc8-4ed6-ad7b-6d61eb8c51de/width=96/Daalis.jpeg"
-  }
-}

refs/version.json

@@ -1,91 +0,0 @@
-{
-  "id": 1255556,
-  "modelId": 1117241,
-  "name": "v1.0",
-  "createdAt": "2025-01-08T06:13:08.839Z",
-  "updatedAt": "2025-01-08T06:28:54.156Z",
-  "status": "Published",
-  "publishedAt": "2025-01-08T06:28:54.155Z",
-  "trainedWords": ["in the style of ppWhimsy"],
-  "trainingStatus": null,
-  "trainingDetails": null,
-  "baseModel": "Flux.1 D",
-  "baseModelType": "Standard",
-  "earlyAccessEndsAt": null,
-  "earlyAccessConfig": null,
-  "description": null,
-  "uploadType": "Created",
-  "usageControl": "Download",
-  "air": "urn:air:flux1:lora:civitai:1117241@1255556",
-  "stats": {
-    "downloadCount": 210,
-    "ratingCount": 0,
-    "rating": 0,
-    "thumbsUpCount": 26
-  },
-  "model": {
-    "name": "Enchanted Whimsy style (Flux)",
-    "type": "LORA",
-    "nsfw": false,
-    "poi": false
-  },
-  "files": [
-    {
-      "id": 1160774,
-      "sizeKB": 38828.8125,
-      "name": "pp-enchanted-whimsy.safetensors",
-      "type": "Model",
-      "pickleScanResult": "Success",
-      "pickleScanMessage": "No Pickle imports",
-      "virusScanResult": "Success",
-      "virusScanMessage": null,
-      "scannedAt": "2025-01-08T06:16:27.731Z",
-      "metadata": {
-        "format": "SafeTensor",
-        "size": null,
-        "fp": null
-      },
-      "hashes": {
-        "AutoV1": "40CAF049",
-        "AutoV2": "3202778C3E",
-        "SHA256": "3202778C3EBE5CF7EBE5FC51561DEAE8611F4362036EB7C02EFA033C705E6240",
-        "CRC32": "69DCD953",
-        "BLAKE3": "ED04580DDB1AD36D8B87F4B0800F5930C7E5D4A7269BDC2BE26ED77EA1A34697",
-        "AutoV3": "BF82986F8597"
-      },
-      "primary": true,
-      "downloadUrl": "https://civitai.com/api/download/models/1255556"
-    }
-  ],
-  "images": [
-    {
-      "url": "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/707aef9b-36fb-46c2-ac41-adcab539d3a6/width=832/50270101.jpeg",
-      "nsfwLevel": 1,
-      "width": 832,
-      "height": 1216,
-      "hash": "U7Am@@$^J3%100R;pLR.M]tQ-ps+?wRiVrof",
-      "type": "image",
-      "metadata": {
-        "hash": "U7Am@@$^J3%100R;pLR.M]tQ-ps+?wRiVrof",
-        "size": 702313,
-        "width": 832,
-        "height": 1216
-      },
-      "minor": false,
-      "poi": false,
-      "meta": {
-        "prompt": "in the style of ppWhimsy, a close-up of a boy with a crown of ferns and tiny horns, his eyes wide with wonder as a family of glowing hedgehogs nestle in his hands, their spines shimmering with soft pastel colors"
-      },
-      "availability": "Public",
-      "hasMeta": true,
-      "hasPositivePrompt": true,
-      "onSite": false,
-      "remixOfId": null
-    }
-  ],
-  "downloadUrl": "https://civitai.com/api/download/models/1255556",
-  "creator": {
-    "username": "PixelPawsAI",
-    "image": "https://image.civitai.com/xG1nkqKTMzGDvpLrqFT7WA/f3a1aa7c-0159-4dd8-884a-1e7ceb350f96/width=96/PixelPawsAI.jpeg"
-  }
-}

static/js/managers/BulkManager.js

@@ -21,6 +21,7 @@ export class BulkManager {
         this.isMarqueeActive = false;
         this.isDragging = false;
         this.marqueeStart = { x: 0, y: 0 };
+        this.marqueeStartDoc = { x: 0, y: 0 }; // Marquee start in document coordinates
         this.marqueeElement = null;
         this.initialSelectedModels = new Set();
 
@@ -29,6 +30,11 @@ export class BulkManager {
         this.mouseDownTime = 0;
         this.mouseDownPosition = { x: 0, y: 0 };
 
+        // Auto-scroll properties for marquee
+        this.lastClientX = 0;
+        this.lastClientY = 0;
+        this.autoScrollRaf = null;
+
         // Model type specific action configurations
         this.actionConfig = {
             [MODEL_TYPES.LORA]: {
@@ -168,7 +174,10 @@ export class BulkManager {
 
         eventManager.addHandler('mousemove', 'bulkManager-marquee-move', (e) => {
             if (this.isMarqueeActive) {
+                this.lastClientX = e.clientX;
+                this.lastClientY = e.clientY;
                 this.updateMarqueeSelection(e);
+                this.startAutoScroll();
             } else if (this.mouseDownTime && !this.isDragging) {
                 // Check if we've moved enough to consider it a drag
                 const dx = e.clientX - this.mouseDownPosition.x;
@@ -237,6 +246,7 @@ export class BulkManager {
      * Clean up event handlers
      */
     cleanup() {
+        this.stopAutoScroll();
         eventManager.removeAllHandlersForSource('bulkManager-keyboard');
         eventManager.removeAllHandlersForSource('bulkManager-marquee-start');
         eventManager.removeAllHandlersForSource('bulkManager-marquee-move');
@@ -1727,10 +1737,15 @@ export class BulkManager {
      * @param {boolean} isDragging - Whether this is triggered from a drag operation
      */
     startMarqueeSelection(e, isDragging = false) {
-        // Store initial mouse position
+        // Store initial mouse position (viewport coordinates for visual element)
         this.marqueeStart.x = this.mouseDownPosition.x;
         this.marqueeStart.y = this.mouseDownPosition.y;
 
+        // Store initial mouse position in document coordinates (for logical selection)
+        const container = document.querySelector('.page-content');
+        this.marqueeStartDoc.x = this.mouseDownPosition.x + (container?.scrollLeft || 0);
+        this.marqueeStartDoc.y = this.mouseDownPosition.y + (container?.scrollTop || 0);
+
         // Store initial selection state
         this.initialSelectedModels = new Set(state.selectedModels);
 
@@ -1776,46 +1791,67 @@ export class BulkManager {
      */
     updateMarqueeSelection(e) {
         if (!this.marqueeElement) return;
-
-        const currentX = e.clientX;
-        const currentY = e.clientY;
-
-        // Calculate rectangle bounds
-        const left = Math.min(this.marqueeStart.x, currentX);
-        const top = Math.min(this.marqueeStart.y, currentY);
-        const width = Math.abs(currentX - this.marqueeStart.x);
-        const height = Math.abs(currentY - this.marqueeStart.y);
-
-        // Update marquee element position and size
-        this.marqueeElement.style.left = left + 'px';
-        this.marqueeElement.style.top = top + 'px';
-        this.marqueeElement.style.width = width + 'px';
-        this.marqueeElement.style.height = height + 'px';
-
-        // Check which cards intersect with marquee
-        this.updateCardSelection(left, top, left + width, top + height);
+        this.updateMarqueeSelectionFromPosition(e.clientX, e.clientY);
     }
 
     /**
-     * Update card selection based on marquee bounds
+     * Update marquee from raw client coordinates (used by both mousemove and auto-scroll loop)
      */
-    updateCardSelection(left, top, right, bottom) {
-        const cards = document.querySelectorAll('.model-card');
+    updateMarqueeSelectionFromPosition(clientX, clientY) {
+        if (!this.marqueeElement) return;
+
+        const container = document.querySelector('.page-content');
+        const scrollX = container?.scrollLeft || 0;
+        const scrollY = container?.scrollTop || 0;
+
+        // Current position in document coordinates
+        const currentDocX = clientX + scrollX;
+        const currentDocY = clientY + scrollY;
+
+        // Calculate marquee rectangle in document coordinates
+        const docLeft = Math.min(this.marqueeStartDoc.x, currentDocX);
+        const docTop = Math.min(this.marqueeStartDoc.y, currentDocY);
+        const docRight = Math.max(this.marqueeStartDoc.x, currentDocX);
+        const docBottom = Math.max(this.marqueeStartDoc.y, currentDocY);
+
+        // Update visual marquee element (position: fixed, so subtract scroll offset)
+        this.marqueeElement.style.left = (docLeft - scrollX) + 'px';
+        this.marqueeElement.style.top = (docTop - scrollY) + 'px';
+        this.marqueeElement.style.width = (docRight - docLeft) + 'px';
+        this.marqueeElement.style.height = (docBottom - docTop) + 'px';
+
+        // Check which cards intersect with marquee
+        this.updateCardSelection(docLeft, docTop, docRight, docBottom);
+    }
+
+    /**
+     * Update card selection based on marquee bounds (document coordinates).
+     * Uses dual detection: DOM cards for visible ones + VirtualScroller layout for off-screen cards.
+     */
+    updateCardSelection(docLeft, docTop, docRight, docBottom) {
+        const vs = state.virtualScroller;
+        const container = document.querySelector('.page-content');
+        const scrollX = container?.scrollLeft || 0;
+        const scrollY = container?.scrollTop || 0;
         const newSelection = new Set(this.initialSelectedModels);
+        const visibleFilepaths = new Set();
 
-        cards.forEach(card => {
-            const rect = card.getBoundingClientRect();
-
-            // Check if card intersects with marquee rectangle
-            const intersects = !(rect.right < left ||
-                rect.left > right ||
-                rect.bottom < top ||
-                rect.top > bottom);
-
+        // Step 1: Process visible DOM cards using getBoundingClientRect + scroll offset
+        document.querySelectorAll('.model-card').forEach(card => {
             const filepath = card.dataset.filepath;
+            if (!filepath) return;
+            visibleFilepaths.add(filepath);
+
+            const rect = card.getBoundingClientRect();
+            const cardLeft = rect.left + scrollX;
+            const cardTop = rect.top + scrollY;
+            const cardRight = rect.right + scrollX;
+            const cardBottom = rect.bottom + scrollY;
+
+            const intersects = !(cardRight < docLeft || cardLeft > docRight ||
+                                 cardBottom < docTop || cardTop > docBottom);
 
             if (intersects) {
-                // Add to selection if intersecting
                 newSelection.add(filepath);
                 card.classList.add('selected');
 
@@ -1825,12 +1861,43 @@ export class BulkManager {
                     this.updateMetadataCacheFromCard(filepath, card);
                 }
             } else if (!this.initialSelectedModels.has(filepath)) {
-                // Remove from selection if not intersecting and wasn't initially selected
                 newSelection.delete(filepath);
                 card.classList.remove('selected');
             }
         });
 
+        // Step 2: Process off-screen cards via VirtualScroller layout calculation.
+        // Since VirtualScroller removes off-screen DOM elements, we compute
+        // each card's position from its index and the VS layout parameters.
+        if (vs?.gridElement && vs.items && vs.columnsCount > 0) {
+            const gridRect = vs.gridElement.getBoundingClientRect();
+            // Grid origin in scroll-container content coordinates
+            const originX = gridRect.left + scrollX;
+            const originY = gridRect.top + scrollY;
+
+            for (let i = 0; i < vs.items.length; i++) {
+                const filepath = vs.items[i]?.file_path;
+                if (!filepath || visibleFilepaths.has(filepath)) continue;
+
+                const row = Math.floor(i / vs.columnsCount);
+                const col = i % vs.columnsCount;
+
+                const cLeft = originX + col * (vs.itemWidth + vs.columnGap);
+                const cTop = originY + (vs.containerPaddingTop || 0) + row * (vs.itemHeight + (vs.rowGap || 0));
+                const cRight = cLeft + vs.itemWidth;
+                const cBottom = cTop + vs.itemHeight;
+
+                const intersects = !(cRight < docLeft || cLeft > docRight ||
+                                     cBottom < docTop || cTop > docBottom);
+
+                if (intersects) {
+                    newSelection.add(filepath);
+                } else if (!this.initialSelectedModels.has(filepath)) {
+                    newSelection.delete(filepath);
+                }
+            }
+        }
+
         // Update global selection state
         state.selectedModels = newSelection;
 
@@ -1849,6 +1916,9 @@ export class BulkManager {
         this.isDragging = false;
         this.mouseDownTime = 0;
 
+        // Stop any active auto-scroll
+        this.stopAutoScroll();
+
         // Update event manager state
         eventManager.setState('marqueeActive', false);
 
@@ -1874,6 +1944,79 @@ export class BulkManager {
         // Clear initial selection state
         this.initialSelectedModels.clear();
     }
+
+    /**
+     * Start auto-scroll loop when mouse approaches viewport edge during marquee
+     */
+    startAutoScroll() {
+        if (this.autoScrollRaf) return;
+        this.autoScrollLoop();
+    }
+
+    /**
+     * Stop auto-scroll loop
+     */
+    stopAutoScroll() {
+        if (this.autoScrollRaf) {
+            cancelAnimationFrame(this.autoScrollRaf);
+            this.autoScrollRaf = null;
+        }
+    }
+
+    /**
+     * Auto-scroll loop: scrolls the page when mouse is near viewport edges
+     * and re-evaluates marquee selection after each scroll.
+     */
+    autoScrollLoop() {
+        if (!this.isMarqueeActive) {
+            this.autoScrollRaf = null;
+            return;
+        }
+
+        const container = document.querySelector('.page-content');
+        if (!container) {
+            this.autoScrollRaf = null;
+            return;
+        }
+
+        const MARGIN = 30;      // Px from edge to trigger scroll
+        const BASE_SPEED = 12;   // Pixels per frame at edge boundary
+        const MAX_SPEED = 40;    // Maximum scroll speed
+        const rect = container.getBoundingClientRect();
+        let dx = 0;
+        let dy = 0;
+
+        // Vertical auto-scroll - speed increases the further the cursor is past the edge
+        if (this.lastClientY !== undefined) {
+            if (this.lastClientY < rect.top + MARGIN) {
+                const dist = Math.max(0, (rect.top + MARGIN) - this.lastClientY);
+                dy = -Math.min(BASE_SPEED + dist * 0.5, MAX_SPEED);
+            } else if (this.lastClientY > rect.bottom - MARGIN) {
+                const dist = Math.max(0, this.lastClientY - (rect.bottom - MARGIN));
+                dy = Math.min(BASE_SPEED + dist * 0.5, MAX_SPEED);
+            }
+        }
+
+        // Horizontal auto-scroll
+        if (this.lastClientX !== undefined) {
+            if (this.lastClientX < rect.left + MARGIN) {
+                const dist = Math.max(0, (rect.left + MARGIN) - this.lastClientX);
+                dx = -Math.min(BASE_SPEED + dist * 0.5, MAX_SPEED);
+            } else if (this.lastClientX > rect.right - MARGIN) {
+                const dist = Math.max(0, this.lastClientX - (rect.right - MARGIN));
+                dx = Math.min(BASE_SPEED + dist * 0.5, MAX_SPEED);
+            }
+        }
+
+        if (dx !== 0 || dy !== 0) {
+            container.scrollBy(dx, dy);
+            // Re-evaluate marquee selection with the new scroll position
+            this.updateMarqueeSelectionFromPosition(this.lastClientX, this.lastClientY);
+            this.autoScrollRaf = requestAnimationFrame(() => this.autoScrollLoop());
+        } else {
+            this.autoScrollRaf = null;
+        }
+    }
 }
 
 export const bulkManager = new BulkManager();

static/js/managers/DownloadManager.js

@@ -351,7 +351,7 @@ export class DownloadManager {
             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 modelFiles = (version.files || []).filter(f => f.type === 'Model' || f.type === 'UNet' || f.type === 'Diffusion Model');
             const primaryFile = modelFiles.find(f => f.primary) || modelFiles[0] || {};
             const fileSize = version.modelSizeKB ?
                 (version.modelSizeKB / 1024).toFixed(2) :
@@ -478,7 +478,7 @@ export class DownloadManager {
         if (!version) return;
 
         this.currentVersion = version;
-        const modelFiles = (version.files || []).filter(f => f.type === 'Model');
+        const modelFiles = (version.files || []).filter(f => f.type === 'Model' || f.type === 'UNet' || f.type === 'Diffusion Model');
 
         document.getElementById('versionStep').style.display = 'none';
         document.getElementById('fileSelectionStep').style.display = 'block';
@@ -534,7 +534,7 @@ export class DownloadManager {
         const version = this.currentVersion;
         if (!version) return;
 
-        const modelFiles = (version.files || []).filter(f => f.type === 'Model');
+        const modelFiles = (version.files || []).filter(f => f.type === 'Model' || f.type === 'UNet' || f.type === 'Diffusion Model');
         this.selectedFile = modelFiles.find(f => f.id.toString() === selectedRadio.value);
 
         document.getElementById('fileSelectionStep').style.display = 'none';
@@ -954,7 +954,7 @@ export class DownloadManager {
         }
         if (!this.isBatchMode) {
             const fileParams = this.selectedFile ? {
-                type: 'Model',
+                type: this.selectedFile.type || 'Model',
                 format: this.selectedFile.metadata?.format || 'SafeTensor',
                 size: this.selectedFile.metadata?.size || 'full',
                 fp: this.selectedFile.metadata?.fp,

static/js/managers/import/DownloadManager.js

@@ -57,9 +57,16 @@ export class DownloadManager {
                     base_model: this.importManager.recipeData.base_model || "",
                     loras: this.importManager.recipeData.loras || [],
                     gen_params: this.importManager.recipeData.gen_params || {},
-                    raw_metadata: this.importManager.recipeData.raw_metadata || {}
+                    raw_metadata: this.importManager.recipeData.raw_metadata || {},
                 };
 
+                // Preserve preview_nsfw_level from analysis so the saved
+                // recipe applies the correct NSFW blur on the preview image.
+                const nsfwLevel = this.importManager.recipeData.preview_nsfw_level;
+                if (nsfwLevel !== undefined && nsfwLevel !== null) {
+                    completeMetadata.preview_nsfw_level = nsfwLevel;
+                }
+
                 const checkpointMetadata =
                     this.importManager.recipeData.checkpoint ||
                     this.importManager.recipeData.model ||

tests/routes/test_api_snapshots.py

@@ -60,7 +60,9 @@ class FakePromptServer:
     sent = []
 
     class Instance:
-        def send_sync(self, event, payload):
+        sockets: dict = {}
+
+        def send_sync(self, event, payload, sid=None):
             FakePromptServer.sent.append((event, payload))
 
     instance = Instance()
@@ -148,7 +150,8 @@ class TestNodeRegistryHandlerSnapshots:
                         "type": "Lora Loader (LoraManager)",
                         "title": "Test Loader",
                     }
-                ]
+                ],
+                "client_id": "test-client-1",
             }
         )
 
@@ -167,7 +170,7 @@ class TestNodeRegistryHandlerSnapshots:
             standalone_mode=False,
         )
 
-        request = FakeRequest(json_data={"nodes": []})
+        request = FakeRequest(json_data={"nodes": [], "client_id": "test-client-1"})
         response = await handler.register_nodes(request)
         payload = json.loads(response.text)
 

tests/routes/test_misc_routes.py

@@ -586,7 +586,9 @@ class FakePromptServer:
     sent = []
 
     class Instance:
-        def send_sync(self, event, payload):
+        sockets: dict = {}
+
+        def send_sync(self, event, payload, sid=None):
             FakePromptServer.sent.append((event, payload))
 
     instance = Instance()
@@ -601,7 +603,12 @@ async def test_register_nodes_requires_graph_id():
         standalone_mode=False,
     )
 
-    request = FakeRequest(json_data={"nodes": [{"node_id": 1}]})
+    request = FakeRequest(
+        json_data={
+            "nodes": [{"node_id": 1}],
+            "client_id": "test-client-1",
+        }
+    )
     response = await handler.register_nodes(request)
     payload = json.loads(response.text)
 
@@ -629,7 +636,8 @@ async def test_register_nodes_stores_graph_identifier():
                     "type": "Lora Loader (LoraManager)",
                     "title": "Loader",
                 }
-            ]
+            ],
+            "client_id": "test-client-1",
         }
     )
 
@@ -638,7 +646,7 @@ async def test_register_nodes_stores_graph_identifier():
 
     assert payload["success"] is True
 
-    registry = await node_registry.get_registry()
+    registry = await node_registry.get_merged_registry()
     assert registry["node_count"] == 1
     stored_node = next(iter(registry["nodes"].values()))
     assert stored_node["graph_id"] == "graph-123"
@@ -664,7 +672,8 @@ async def test_register_nodes_defaults_graph_name_to_none():
                     "type": "Lora Loader (LoraManager)",
                     "title": "Root Loader",
                 }
-            ]
+            ],
+            "client_id": "test-client-1",
         }
     )
 
@@ -673,7 +682,7 @@ async def test_register_nodes_defaults_graph_name_to_none():
 
     assert payload["success"] is True
 
-    registry = await node_registry.get_registry()
+    registry = await node_registry.get_merged_registry()
     stored_node = next(iter(registry["nodes"].values()))
     assert stored_node["graph_name"] is None
 
@@ -700,7 +709,8 @@ async def test_register_nodes_includes_capabilities():
                         "widget_names": ["ckpt_name", "", 42],
                     },
                 }
-            ]
+            ],
+            "client_id": "test-client-1",
         }
     )
 
@@ -709,7 +719,7 @@ async def test_register_nodes_includes_capabilities():
 
     assert payload["success"] is True
 
-    registry = await node_registry.get_registry()
+    registry = await node_registry.get_merged_registry()
     stored_node = next(iter(registry["nodes"].values()))
     assert stored_node["capabilities"] == {
         "supports_lora": False,
@@ -724,7 +734,9 @@ async def test_update_node_widget_sends_payload():
 
     class RecordingPromptServer:
         class Instance:
-            def send_sync(self, event, payload):
+            sockets: dict = {}
+
+            def send_sync(self, event, payload, sid=None):
                 send_calls.append((event, payload))
 
         instance = Instance()
@@ -768,7 +780,9 @@ async def test_update_lora_code_includes_graph_identifier():
 
     class RecordingPromptServer:
         class Instance:
-            def send_sync(self, event, payload):
+            sockets: dict = {}
+
+            def send_sync(self, event, payload, sid=None):
                 send_calls.append((event, payload))
 
         instance = Instance()

tests/services/test_civitai_client.py

@@ -568,7 +568,7 @@ async def test_get_image_info_prefers_red_host_for_red_source(monkeypatch, downl
 
     assert result == {"id": 124950237, "name": "target"}
     assert requested_urls == [
-        "https://civitai.red/api/v1/images?imageId=124950237&nsfw=X"
+        "https://civitai.red/api/v1/images?imageId=124950237&nsfw=X&withMeta=true"
     ]
 
 
@@ -589,7 +589,7 @@ async def test_get_image_info_uses_red_host_even_for_red_source(monkeypatch, dow
 
     assert result == {"id": 124950237, "name": "target"}
     assert requested_urls == [
-        "https://civitai.red/api/v1/images?imageId=124950237&nsfw=X",
+        "https://civitai.red/api/v1/images?imageId=124950237&nsfw=X&withMeta=true",
     ]
 
 
@@ -610,7 +610,7 @@ async def test_get_image_info_does_not_fall_back_after_request_failure(monkeypat
 
     assert result is None
     assert requested_urls == [
-        "https://civitai.red/api/v1/images?imageId=124950237&nsfw=X",
+        "https://civitai.red/api/v1/images?imageId=124950237&nsfw=X&withMeta=true",
     ]
 
 

web/comfyui/workflow_registry.js

@@ -151,7 +151,10 @@ app.registerExtension({
                 headers: {
                     "Content-Type": "application/json",
                 },
-                body: JSON.stringify({ nodes: workflowNodes }),
+                body: JSON.stringify({
+                    nodes: workflowNodes,
+                    client_id: api.clientId ?? api.initialClientId ?? "",
+                }),
             });
 
             if (!response.ok) {