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1
.gitignore
vendored
1
.gitignore
vendored
@@ -14,6 +14,7 @@ model_cache/
|
||||
|
||||
# agent
|
||||
.opencode/
|
||||
.claude/
|
||||
|
||||
# Vue widgets development cache (but keep build output)
|
||||
vue-widgets/node_modules/
|
||||
|
||||
@@ -179,6 +179,8 @@ Insomnia Art Designs, megakirbs, Brennok, wackop, 2018cfh, Takkan, stone9k, $Met
|
||||
- Context menu for quick actions
|
||||
- Custom notes and usage tips
|
||||
- Multi-folder support
|
||||
- Configurable mature blur threshold (`PG13` / `R` / `X` / `XXX`, default `R+`)
|
||||
- Example: setting threshold to `PG13` blurs `PG13`, `R`, `X`, and `XXX` previews when blur is enabled
|
||||
- Visual progress indicators during initialization
|
||||
|
||||
---
|
||||
|
||||
147
locales/de.json
147
locales/de.json
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "NSFW-Inhalte unscharf stellen",
|
||||
"blurNsfwContentHelp": "Nicht jugendfreie (NSFW) Vorschaubilder unscharf stellen",
|
||||
"showOnlySfw": "Nur SFW-Ergebnisse anzeigen",
|
||||
"showOnlySfwHelp": "Alle NSFW-Inhalte beim Durchsuchen und Suchen herausfiltern"
|
||||
"showOnlySfwHelp": "Alle NSFW-Inhalte beim Durchsuchen und Suchen herausfiltern",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "Videos bei Hover automatisch abspielen",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle überspringen",
|
||||
"resumeMetadataRefresh": "Metadaten-Aktualisierung für ausgewählte Modelle fortsetzen",
|
||||
"deleteAll": "Alle Modelle löschen",
|
||||
"downloadMissingLoras": "Fehlende LoRAs herunterladen",
|
||||
"clear": "Auswahl löschen",
|
||||
"skipMetadataRefreshCount": "Überspringen({count} Modelle)",
|
||||
"resumeMetadataRefreshCount": "Fortsetzen({count} Modelle)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "Stammverzeichnis",
|
||||
"browseFolders": "Ordner durchsuchen:",
|
||||
"downloadAndSaveRecipe": "Herunterladen & Rezept speichern",
|
||||
"importRecipeOnly": "Nur Rezept importieren",
|
||||
"importAndDownload": "Importieren & Herunterladen",
|
||||
"downloadMissingLoras": "Fehlende LoRAs herunterladen",
|
||||
"saveRecipe": "Rezept speichern",
|
||||
"loraCountInfo": "({existing}/{total} in Bibliothek)",
|
||||
@@ -732,61 +743,61 @@
|
||||
}
|
||||
},
|
||||
"batchImport": {
|
||||
"title": "[TODO: Translate] Batch Import Recipes",
|
||||
"action": "[TODO: Translate] Batch Import",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "[TODO: Translate] Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "[TODO: Translate] Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "[TODO: Translate] https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"directoryPlaceholder": "[TODO: Translate] /path/to/images/folder",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"tagsOptional": "[TODO: Translate] Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "[TODO: Translate] Skip images without metadata",
|
||||
"skipNoMetadataHelp": "[TODO: Translate] Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"startImport": "[TODO: Translate] Start Import",
|
||||
"importing": "[TODO: Translate] Importing...",
|
||||
"progress": "[TODO: Translate] Progress",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"currentItem": "[TODO: Translate] Current",
|
||||
"preparing": "[TODO: Translate] Preparing...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancelImport": "[TODO: Translate] Cancel",
|
||||
"cancelled": "[TODO: Translate] Import cancelled",
|
||||
"completed": "[TODO: Translate] Import completed",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedSuccess": "[TODO: Translate] Successfully imported {count} recipe(s)",
|
||||
"successCount": "[TODO: Translate] Successful",
|
||||
"failedCount": "[TODO: Translate] Failed",
|
||||
"skippedCount": "[TODO: Translate] Skipped",
|
||||
"totalProcessed": "[TODO: Translate] Total processed",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"title": "Batch Import Recipes",
|
||||
"action": "Batch Import",
|
||||
"urlList": "URL List",
|
||||
"directory": "Directory",
|
||||
"urlDescription": "Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "Enter one URL or path per line",
|
||||
"directoryPath": "Directory Path",
|
||||
"directoryPlaceholder": "/path/to/images/folder",
|
||||
"browse": "Browse",
|
||||
"recursive": "Include subdirectories",
|
||||
"tagsOptional": "Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "Enter tags separated by commas",
|
||||
"tagsHint": "Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "Skip images without metadata",
|
||||
"skipNoMetadataHelp": "Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "Start Import",
|
||||
"startImport": "Start Import",
|
||||
"importing": "Importing...",
|
||||
"progress": "Progress",
|
||||
"total": "Total",
|
||||
"success": "Success",
|
||||
"failed": "Failed",
|
||||
"skipped": "Skipped",
|
||||
"current": "Current",
|
||||
"currentItem": "Current",
|
||||
"preparing": "Preparing...",
|
||||
"cancel": "Cancel",
|
||||
"cancelImport": "Cancel",
|
||||
"cancelled": "Import cancelled",
|
||||
"completed": "Import completed",
|
||||
"completedWithErrors": "Completed with errors",
|
||||
"completedSuccess": "Successfully imported {count} recipe(s)",
|
||||
"successCount": "Successful",
|
||||
"failedCount": "Failed",
|
||||
"skippedCount": "Skipped",
|
||||
"totalProcessed": "Total processed",
|
||||
"viewDetails": "View Details",
|
||||
"newImport": "New Import",
|
||||
"manualPathEntry": "Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"batchImportManualEntryRequired": "File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "Back to parent directory",
|
||||
"folders": "Folders",
|
||||
"folderCount": "{count} folders",
|
||||
"imageFiles": "Image Files",
|
||||
"images": "images",
|
||||
"imageCount": "{count} images",
|
||||
"selectFolder": "Select This Folder",
|
||||
"errors": {
|
||||
"enterUrls": "[TODO: Translate] Please enter at least one URL or path",
|
||||
"enterDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"startFailed": "[TODO: Translate] Failed to start import: {message}"
|
||||
"enterUrls": "Please enter at least one URL or path",
|
||||
"enterDirectory": "Please enter a directory path",
|
||||
"startFailed": "Failed to start import: {message}"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "Basis-Modell aktualisieren",
|
||||
"cancel": "Abbrechen"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "Fehlende LoRAs herunterladen",
|
||||
"message": "{uniqueCount} einzigartige fehlende LoRAs gefunden (von insgesamt {totalCount} in ausgewählten Rezepten).",
|
||||
"previewTitle": "Zu herunterladende LoRAs:",
|
||||
"moreItems": "...und {count} weitere",
|
||||
"note": "Dateien werden mit Standard-Pfad-Vorlagen heruntergeladen. Dies kann je nach Anzahl der LoRAs eine Weile dauern.",
|
||||
"downloadButton": "{count} LoRA(s) herunterladen"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "Lokale Beispielbilder",
|
||||
"message": "Keine lokalen Beispielbilder für dieses Modell gefunden. Ansichtsoptionen:",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "Verarbeitungsfehler: {message}",
|
||||
"folderBrowserError": "Fehler beim Laden des Ordner-Browsers: {message}",
|
||||
"recipeSaveFailed": "Fehler beim Speichern des Rezepts: {error}",
|
||||
"recipeSaved": "Recipe saved successfully",
|
||||
"importFailed": "Import fehlgeschlagen: {message}",
|
||||
"folderTreeFailed": "Fehler beim Laden des Ordnerbaums",
|
||||
"folderTreeError": "Fehler beim Laden des Ordnerbaums",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "Cancelling batch import...",
|
||||
"batchImportCancelFailed": "Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "Please enter a directory path",
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "Keine Rezepte ausgewählt",
|
||||
"noMissingLorasInSelection": "Keine fehlenden LoRAs in ausgewählten Rezepten gefunden",
|
||||
"noLoraRootConfigured": "Kein LoRA-Stammverzeichnis konfiguriert. Bitte legen Sie ein Standard-LoRA-Stammverzeichnis in den Einstellungen fest."
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "Keine Modelle ausgewählt",
|
||||
|
||||
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "Blur NSFW Content",
|
||||
"blurNsfwContentHelp": "Blur mature (NSFW) content preview images",
|
||||
"showOnlySfw": "Show Only SFW Results",
|
||||
"showOnlySfwHelp": "Filter out all NSFW content when browsing and searching"
|
||||
"showOnlySfwHelp": "Filter out all NSFW content when browsing and searching",
|
||||
"matureBlurThreshold": "Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "PG13 and above",
|
||||
"r": "R and above (default)",
|
||||
"x": "X and above",
|
||||
"xxx": "XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "Autoplay Videos on Hover",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "Skip Metadata Refresh for Selected",
|
||||
"resumeMetadataRefresh": "Resume Metadata Refresh for Selected",
|
||||
"deleteAll": "Delete Selected Models",
|
||||
"downloadMissingLoras": "Download Missing LoRAs",
|
||||
"clear": "Clear Selection",
|
||||
"skipMetadataRefreshCount": "Skip ({count} models)",
|
||||
"resumeMetadataRefreshCount": "Resume ({count} models)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "Root",
|
||||
"browseFolders": "Browse Folders:",
|
||||
"downloadAndSaveRecipe": "Download & Save Recipe",
|
||||
"importRecipeOnly": "Import Recipe Only",
|
||||
"importAndDownload": "Import & Download",
|
||||
"downloadMissingLoras": "Download Missing LoRAs",
|
||||
"saveRecipe": "Save Recipe",
|
||||
"loraCountInfo": "({existing}/{total} in library)",
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "Update Base Model",
|
||||
"cancel": "Cancel"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "Download Missing LoRAs",
|
||||
"message": "Found {uniqueCount} unique missing LoRAs (from {totalCount} total across selected recipes).",
|
||||
"previewTitle": "LoRAs to download:",
|
||||
"moreItems": "...and {count} more",
|
||||
"note": "Files will be downloaded using default path templates. This may take a while depending on the number of LoRAs.",
|
||||
"downloadButton": "Download {count} LoRA(s)"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "Local Example Images",
|
||||
"message": "No local example images found for this model. View options:",
|
||||
@@ -1495,6 +1514,7 @@
|
||||
"processingError": "Processing error: {message}",
|
||||
"folderBrowserError": "Error loading folder browser: {message}",
|
||||
"recipeSaveFailed": "Failed to save recipe: {error}",
|
||||
"recipeSaved": "Recipe saved successfully",
|
||||
"importFailed": "Import failed: {message}",
|
||||
"folderTreeFailed": "Failed to load folder tree",
|
||||
"folderTreeError": "Error loading folder tree",
|
||||
@@ -1504,7 +1524,10 @@
|
||||
"batchImportNoUrls": "Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "Please enter a directory path",
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}"
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "No recipes selected",
|
||||
"noMissingLorasInSelection": "No missing LoRAs found in selected recipes",
|
||||
"noLoraRootConfigured": "No LoRA root directory configured. Please set a default LoRA root in settings."
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "No models selected",
|
||||
|
||||
147
locales/es.json
147
locales/es.json
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "Difuminar contenido NSFW",
|
||||
"blurNsfwContentHelp": "Difuminar imágenes de vista previa de contenido para adultos (NSFW)",
|
||||
"showOnlySfw": "Mostrar solo resultados SFW",
|
||||
"showOnlySfwHelp": "Filtrar todo el contenido NSFW al navegar y buscar"
|
||||
"showOnlySfwHelp": "Filtrar todo el contenido NSFW al navegar y buscar",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "Reproducir videos automáticamente al pasar el ratón",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "Omitir actualización de metadatos para seleccionados",
|
||||
"resumeMetadataRefresh": "Reanudar actualización de metadatos para seleccionados",
|
||||
"deleteAll": "Eliminar todos los modelos",
|
||||
"downloadMissingLoras": "Descargar LoRAs faltantes",
|
||||
"clear": "Limpiar selección",
|
||||
"skipMetadataRefreshCount": "Omitir({count} modelos)",
|
||||
"resumeMetadataRefreshCount": "Reanudar({count} modelos)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "Raíz",
|
||||
"browseFolders": "Explorar carpetas:",
|
||||
"downloadAndSaveRecipe": "Descargar y guardar receta",
|
||||
"importRecipeOnly": "Importar solo la receta",
|
||||
"importAndDownload": "Importar y descargar",
|
||||
"downloadMissingLoras": "Descargar LoRAs faltantes",
|
||||
"saveRecipe": "Guardar receta",
|
||||
"loraCountInfo": "({existing}/{total} en la biblioteca)",
|
||||
@@ -732,61 +743,61 @@
|
||||
}
|
||||
},
|
||||
"batchImport": {
|
||||
"title": "[TODO: Translate] Batch Import Recipes",
|
||||
"action": "[TODO: Translate] Batch Import",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "[TODO: Translate] Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "[TODO: Translate] Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "[TODO: Translate] https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"directoryPlaceholder": "[TODO: Translate] /path/to/images/folder",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"tagsOptional": "[TODO: Translate] Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "[TODO: Translate] Skip images without metadata",
|
||||
"skipNoMetadataHelp": "[TODO: Translate] Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"startImport": "[TODO: Translate] Start Import",
|
||||
"importing": "[TODO: Translate] Importing...",
|
||||
"progress": "[TODO: Translate] Progress",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"currentItem": "[TODO: Translate] Current",
|
||||
"preparing": "[TODO: Translate] Preparing...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancelImport": "[TODO: Translate] Cancel",
|
||||
"cancelled": "[TODO: Translate] Import cancelled",
|
||||
"completed": "[TODO: Translate] Import completed",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedSuccess": "[TODO: Translate] Successfully imported {count} recipe(s)",
|
||||
"successCount": "[TODO: Translate] Successful",
|
||||
"failedCount": "[TODO: Translate] Failed",
|
||||
"skippedCount": "[TODO: Translate] Skipped",
|
||||
"totalProcessed": "[TODO: Translate] Total processed",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"title": "Batch Import Recipes",
|
||||
"action": "Batch Import",
|
||||
"urlList": "URL List",
|
||||
"directory": "Directory",
|
||||
"urlDescription": "Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "Enter one URL or path per line",
|
||||
"directoryPath": "Directory Path",
|
||||
"directoryPlaceholder": "/path/to/images/folder",
|
||||
"browse": "Browse",
|
||||
"recursive": "Include subdirectories",
|
||||
"tagsOptional": "Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "Enter tags separated by commas",
|
||||
"tagsHint": "Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "Skip images without metadata",
|
||||
"skipNoMetadataHelp": "Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "Start Import",
|
||||
"startImport": "Start Import",
|
||||
"importing": "Importing...",
|
||||
"progress": "Progress",
|
||||
"total": "Total",
|
||||
"success": "Success",
|
||||
"failed": "Failed",
|
||||
"skipped": "Skipped",
|
||||
"current": "Current",
|
||||
"currentItem": "Current",
|
||||
"preparing": "Preparing...",
|
||||
"cancel": "Cancel",
|
||||
"cancelImport": "Cancel",
|
||||
"cancelled": "Import cancelled",
|
||||
"completed": "Import completed",
|
||||
"completedWithErrors": "Completed with errors",
|
||||
"completedSuccess": "Successfully imported {count} recipe(s)",
|
||||
"successCount": "Successful",
|
||||
"failedCount": "Failed",
|
||||
"skippedCount": "Skipped",
|
||||
"totalProcessed": "Total processed",
|
||||
"viewDetails": "View Details",
|
||||
"newImport": "New Import",
|
||||
"manualPathEntry": "Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"batchImportManualEntryRequired": "File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "Back to parent directory",
|
||||
"folders": "Folders",
|
||||
"folderCount": "{count} folders",
|
||||
"imageFiles": "Image Files",
|
||||
"images": "images",
|
||||
"imageCount": "{count} images",
|
||||
"selectFolder": "Select This Folder",
|
||||
"errors": {
|
||||
"enterUrls": "[TODO: Translate] Please enter at least one URL or path",
|
||||
"enterDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"startFailed": "[TODO: Translate] Failed to start import: {message}"
|
||||
"enterUrls": "Please enter at least one URL or path",
|
||||
"enterDirectory": "Please enter a directory path",
|
||||
"startFailed": "Failed to start import: {message}"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "Actualizar modelo base",
|
||||
"cancel": "Cancelar"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "Descargar LoRAs faltantes",
|
||||
"message": "Se encontraron {uniqueCount} LoRAs faltantes únicos (de {totalCount} en total entre las recetas seleccionadas).",
|
||||
"previewTitle": "LoRAs para descargar:",
|
||||
"moreItems": "...y {count} más",
|
||||
"note": "Los archivos se descargarán usando las plantillas de ruta predeterminadas. Esto puede tomar un tiempo dependiendo del número de LoRAs.",
|
||||
"downloadButton": "Descargar {count} LoRA(s)"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "Imágenes de ejemplo locales",
|
||||
"message": "No se encontraron imágenes de ejemplo locales para este modelo. Opciones de visualización:",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "Error de procesamiento: {message}",
|
||||
"folderBrowserError": "Error cargando explorador de carpetas: {message}",
|
||||
"recipeSaveFailed": "Error al guardar receta: {error}",
|
||||
"recipeSaved": "Recipe saved successfully",
|
||||
"importFailed": "Importación falló: {message}",
|
||||
"folderTreeFailed": "Error al cargar árbol de carpetas",
|
||||
"folderTreeError": "Error cargando árbol de carpetas",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "Cancelling batch import...",
|
||||
"batchImportCancelFailed": "Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "Please enter a directory path",
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "No se han seleccionado recetas",
|
||||
"noMissingLorasInSelection": "No se encontraron LoRAs faltantes en las recetas seleccionadas",
|
||||
"noLoraRootConfigured": "No se ha configurado el directorio raíz de LoRA. Por favor, establezca un directorio raíz de LoRA predeterminado en la configuración."
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "No hay modelos seleccionados",
|
||||
|
||||
147
locales/fr.json
147
locales/fr.json
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "Flouter le contenu NSFW",
|
||||
"blurNsfwContentHelp": "Flouter les images d'aperçu de contenu pour adultes (NSFW)",
|
||||
"showOnlySfw": "Afficher uniquement les résultats SFW",
|
||||
"showOnlySfwHelp": "Filtrer tout le contenu NSFW lors de la navigation et de la recherche"
|
||||
"showOnlySfwHelp": "Filtrer tout le contenu NSFW lors de la navigation et de la recherche",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "Lecture automatique vidéo au survol",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "Ignorer l'actualisation des métadonnées pour la sélection",
|
||||
"resumeMetadataRefresh": "Reprendre l'actualisation des métadonnées pour la sélection",
|
||||
"deleteAll": "Supprimer tous les modèles",
|
||||
"downloadMissingLoras": "Télécharger les LoRAs manquants",
|
||||
"clear": "Effacer la sélection",
|
||||
"skipMetadataRefreshCount": "Ignorer({count} modèles)",
|
||||
"resumeMetadataRefreshCount": "Reprendre({count} modèles)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "Racine",
|
||||
"browseFolders": "Parcourir les dossiers :",
|
||||
"downloadAndSaveRecipe": "Télécharger et sauvegarder la recipe",
|
||||
"importRecipeOnly": "Importer uniquement la recette",
|
||||
"importAndDownload": "Importer et télécharger",
|
||||
"downloadMissingLoras": "Télécharger les LoRAs manquants",
|
||||
"saveRecipe": "Sauvegarder la recipe",
|
||||
"loraCountInfo": "({existing}/{total} dans la bibliothèque)",
|
||||
@@ -732,61 +743,61 @@
|
||||
}
|
||||
},
|
||||
"batchImport": {
|
||||
"title": "[TODO: Translate] Batch Import Recipes",
|
||||
"action": "[TODO: Translate] Batch Import",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "[TODO: Translate] Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "[TODO: Translate] Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "[TODO: Translate] https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"directoryPlaceholder": "[TODO: Translate] /path/to/images/folder",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"tagsOptional": "[TODO: Translate] Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "[TODO: Translate] Skip images without metadata",
|
||||
"skipNoMetadataHelp": "[TODO: Translate] Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"startImport": "[TODO: Translate] Start Import",
|
||||
"importing": "[TODO: Translate] Importing...",
|
||||
"progress": "[TODO: Translate] Progress",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"currentItem": "[TODO: Translate] Current",
|
||||
"preparing": "[TODO: Translate] Preparing...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancelImport": "[TODO: Translate] Cancel",
|
||||
"cancelled": "[TODO: Translate] Import cancelled",
|
||||
"completed": "[TODO: Translate] Import completed",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedSuccess": "[TODO: Translate] Successfully imported {count} recipe(s)",
|
||||
"successCount": "[TODO: Translate] Successful",
|
||||
"failedCount": "[TODO: Translate] Failed",
|
||||
"skippedCount": "[TODO: Translate] Skipped",
|
||||
"totalProcessed": "[TODO: Translate] Total processed",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"title": "Batch Import Recipes",
|
||||
"action": "Batch Import",
|
||||
"urlList": "URL List",
|
||||
"directory": "Directory",
|
||||
"urlDescription": "Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "Enter one URL or path per line",
|
||||
"directoryPath": "Directory Path",
|
||||
"directoryPlaceholder": "/path/to/images/folder",
|
||||
"browse": "Browse",
|
||||
"recursive": "Include subdirectories",
|
||||
"tagsOptional": "Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "Enter tags separated by commas",
|
||||
"tagsHint": "Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "Skip images without metadata",
|
||||
"skipNoMetadataHelp": "Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "Start Import",
|
||||
"startImport": "Start Import",
|
||||
"importing": "Importing...",
|
||||
"progress": "Progress",
|
||||
"total": "Total",
|
||||
"success": "Success",
|
||||
"failed": "Failed",
|
||||
"skipped": "Skipped",
|
||||
"current": "Current",
|
||||
"currentItem": "Current",
|
||||
"preparing": "Preparing...",
|
||||
"cancel": "Cancel",
|
||||
"cancelImport": "Cancel",
|
||||
"cancelled": "Import cancelled",
|
||||
"completed": "Import completed",
|
||||
"completedWithErrors": "Completed with errors",
|
||||
"completedSuccess": "Successfully imported {count} recipe(s)",
|
||||
"successCount": "Successful",
|
||||
"failedCount": "Failed",
|
||||
"skippedCount": "Skipped",
|
||||
"totalProcessed": "Total processed",
|
||||
"viewDetails": "View Details",
|
||||
"newImport": "New Import",
|
||||
"manualPathEntry": "Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"batchImportManualEntryRequired": "File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "Back to parent directory",
|
||||
"folders": "Folders",
|
||||
"folderCount": "{count} folders",
|
||||
"imageFiles": "Image Files",
|
||||
"images": "images",
|
||||
"imageCount": "{count} images",
|
||||
"selectFolder": "Select This Folder",
|
||||
"errors": {
|
||||
"enterUrls": "[TODO: Translate] Please enter at least one URL or path",
|
||||
"enterDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"startFailed": "[TODO: Translate] Failed to start import: {message}"
|
||||
"enterUrls": "Please enter at least one URL or path",
|
||||
"enterDirectory": "Please enter a directory path",
|
||||
"startFailed": "Failed to start import: {message}"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "Mettre à jour le modèle de base",
|
||||
"cancel": "Annuler"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "Télécharger les LoRAs manquants",
|
||||
"message": "{uniqueCount} LoRAs manquants uniques trouvés (sur un total de {totalCount} dans les recettes sélectionnées).",
|
||||
"previewTitle": "LoRAs à télécharger :",
|
||||
"moreItems": "...et {count} de plus",
|
||||
"note": "Les fichiers seront téléchargés en utilisant les modèles de chemins par défaut. Cela peut prendre un certain temps selon le nombre de LoRAs.",
|
||||
"downloadButton": "Télécharger {count} LoRA(s)"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "Images d'exemple locales",
|
||||
"message": "Aucune image d'exemple locale trouvée pour ce modèle. Options d'affichage :",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "Erreur de traitement : {message}",
|
||||
"folderBrowserError": "Erreur lors du chargement du navigateur de dossiers : {message}",
|
||||
"recipeSaveFailed": "Échec de la sauvegarde de la recipe : {error}",
|
||||
"recipeSaved": "Recipe saved successfully",
|
||||
"importFailed": "Échec de l'importation : {message}",
|
||||
"folderTreeFailed": "Échec du chargement de l'arborescence des dossiers",
|
||||
"folderTreeError": "Erreur lors du chargement de l'arborescence des dossiers",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "Cancelling batch import...",
|
||||
"batchImportCancelFailed": "Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "Please enter a directory path",
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "Aucune recette sélectionnée",
|
||||
"noMissingLorasInSelection": "Aucun LoRA manquant trouvé dans les recettes sélectionnées",
|
||||
"noLoraRootConfigured": "Aucun répertoire racine LoRA configuré. Veuillez définir un répertoire racine LoRA par défaut dans les paramètres."
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "Aucun modèle sélectionné",
|
||||
|
||||
147
locales/he.json
147
locales/he.json
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "טשטש תוכן NSFW",
|
||||
"blurNsfwContentHelp": "טשטש תמונות תצוגה מקדימה של תוכן למבוגרים (NSFW)",
|
||||
"showOnlySfw": "הצג רק תוצאות SFW",
|
||||
"showOnlySfwHelp": "סנן את כל התוכן ה-NSFW בעת גלישה וחיפוש"
|
||||
"showOnlySfwHelp": "סנן את כל התוכן ה-NSFW בעת גלישה וחיפוש",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "נגן וידאו אוטומטית בריחוף",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "דילוג על רענון מטא-נתונים לנבחרים",
|
||||
"resumeMetadataRefresh": "המשך רענון מטא-נתונים לנבחרים",
|
||||
"deleteAll": "מחק את כל המודלים",
|
||||
"downloadMissingLoras": "הורדת LoRAs חסרים",
|
||||
"clear": "נקה בחירה",
|
||||
"skipMetadataRefreshCount": "דילוג({count} מודלים)",
|
||||
"resumeMetadataRefreshCount": "המשך({count} מודלים)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "שורש",
|
||||
"browseFolders": "דפדף בתיקיות:",
|
||||
"downloadAndSaveRecipe": "הורד ושמור מתכון",
|
||||
"importRecipeOnly": "יבא רק מתכון",
|
||||
"importAndDownload": "יבא והורד",
|
||||
"downloadMissingLoras": "הורד LoRAs חסרים",
|
||||
"saveRecipe": "שמור מתכון",
|
||||
"loraCountInfo": "({existing}/{total} בספרייה)",
|
||||
@@ -732,61 +743,61 @@
|
||||
}
|
||||
},
|
||||
"batchImport": {
|
||||
"title": "[TODO: Translate] Batch Import Recipes",
|
||||
"action": "[TODO: Translate] Batch Import",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "[TODO: Translate] Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "[TODO: Translate] Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "[TODO: Translate] https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"directoryPlaceholder": "[TODO: Translate] /path/to/images/folder",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"tagsOptional": "[TODO: Translate] Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "[TODO: Translate] Skip images without metadata",
|
||||
"skipNoMetadataHelp": "[TODO: Translate] Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"startImport": "[TODO: Translate] Start Import",
|
||||
"importing": "[TODO: Translate] Importing...",
|
||||
"progress": "[TODO: Translate] Progress",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"currentItem": "[TODO: Translate] Current",
|
||||
"preparing": "[TODO: Translate] Preparing...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancelImport": "[TODO: Translate] Cancel",
|
||||
"cancelled": "[TODO: Translate] Import cancelled",
|
||||
"completed": "[TODO: Translate] Import completed",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedSuccess": "[TODO: Translate] Successfully imported {count} recipe(s)",
|
||||
"successCount": "[TODO: Translate] Successful",
|
||||
"failedCount": "[TODO: Translate] Failed",
|
||||
"skippedCount": "[TODO: Translate] Skipped",
|
||||
"totalProcessed": "[TODO: Translate] Total processed",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"title": "Batch Import Recipes",
|
||||
"action": "Batch Import",
|
||||
"urlList": "URL List",
|
||||
"directory": "Directory",
|
||||
"urlDescription": "Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "Enter one URL or path per line",
|
||||
"directoryPath": "Directory Path",
|
||||
"directoryPlaceholder": "/path/to/images/folder",
|
||||
"browse": "Browse",
|
||||
"recursive": "Include subdirectories",
|
||||
"tagsOptional": "Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "Enter tags separated by commas",
|
||||
"tagsHint": "Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "Skip images without metadata",
|
||||
"skipNoMetadataHelp": "Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "Start Import",
|
||||
"startImport": "Start Import",
|
||||
"importing": "Importing...",
|
||||
"progress": "Progress",
|
||||
"total": "Total",
|
||||
"success": "Success",
|
||||
"failed": "Failed",
|
||||
"skipped": "Skipped",
|
||||
"current": "Current",
|
||||
"currentItem": "Current",
|
||||
"preparing": "Preparing...",
|
||||
"cancel": "Cancel",
|
||||
"cancelImport": "Cancel",
|
||||
"cancelled": "Import cancelled",
|
||||
"completed": "Import completed",
|
||||
"completedWithErrors": "Completed with errors",
|
||||
"completedSuccess": "Successfully imported {count} recipe(s)",
|
||||
"successCount": "Successful",
|
||||
"failedCount": "Failed",
|
||||
"skippedCount": "Skipped",
|
||||
"totalProcessed": "Total processed",
|
||||
"viewDetails": "View Details",
|
||||
"newImport": "New Import",
|
||||
"manualPathEntry": "Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"batchImportManualEntryRequired": "File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "Back to parent directory",
|
||||
"folders": "Folders",
|
||||
"folderCount": "{count} folders",
|
||||
"imageFiles": "Image Files",
|
||||
"images": "images",
|
||||
"imageCount": "{count} images",
|
||||
"selectFolder": "Select This Folder",
|
||||
"errors": {
|
||||
"enterUrls": "[TODO: Translate] Please enter at least one URL or path",
|
||||
"enterDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"startFailed": "[TODO: Translate] Failed to start import: {message}"
|
||||
"enterUrls": "Please enter at least one URL or path",
|
||||
"enterDirectory": "Please enter a directory path",
|
||||
"startFailed": "Failed to start import: {message}"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "עדכן מודל בסיס",
|
||||
"cancel": "ביטול"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "הורדת LoRAs חסרים",
|
||||
"message": "נמצאו {uniqueCount} LoRAs חסרים ייחודיים (מתוך {totalCount} בסך הכל במתכונים שנבחרו).",
|
||||
"previewTitle": "LoRAs להורדה:",
|
||||
"moreItems": "...ועוד {count}",
|
||||
"note": "הקבצים יורדו באמצעות תבניות נתיב ברירת מחדל. זה עשוי לקחת זמן בהתאם למספר ה-LoRAs.",
|
||||
"downloadButton": "הורד {count} LoRA(s)"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "תמונות דוגמה מקומיות",
|
||||
"message": "לא נמצאו תמונות דוגמה מקומיות למודל זה. אפשרויות צפייה:",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "שגיאת עיבוד: {message}",
|
||||
"folderBrowserError": "שגיאה בטעינת דפדפן התיקיות: {message}",
|
||||
"recipeSaveFailed": "שמירת המתכון נכשלה: {error}",
|
||||
"recipeSaved": "Recipe saved successfully",
|
||||
"importFailed": "הייבוא נכשל: {message}",
|
||||
"folderTreeFailed": "טעינת עץ התיקיות נכשלה",
|
||||
"folderTreeError": "שגיאה בטעינת עץ התיקיות",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "Cancelling batch import...",
|
||||
"batchImportCancelFailed": "Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "Please enter a directory path",
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "לא נבחרו מתכונים",
|
||||
"noMissingLorasInSelection": "לא נמצאו LoRAs חסרים במתכונים שנבחרו",
|
||||
"noLoraRootConfigured": "תיקיית השורש של LoRA לא מוגדרת. אנא הגדר תיקיית שורש LoRA ברירת מחדל בהגדרות."
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "לא נבחרו מודלים",
|
||||
|
||||
147
locales/ja.json
147
locales/ja.json
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "NSFWコンテンツをぼかす",
|
||||
"blurNsfwContentHelp": "成人向け(NSFW)コンテンツのプレビュー画像をぼかします",
|
||||
"showOnlySfw": "SFWコンテンツのみ表示",
|
||||
"showOnlySfwHelp": "閲覧と検索時にすべてのNSFWコンテンツを除外します"
|
||||
"showOnlySfwHelp": "閲覧と検索時にすべてのNSFWコンテンツを除外します",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "ホバー時に動画を自動再生",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "選択したモデルのメタデータ更新をスキップ",
|
||||
"resumeMetadataRefresh": "選択したモデルのメタデータ更新を再開",
|
||||
"deleteAll": "すべてのモデルを削除",
|
||||
"downloadMissingLoras": "不足している LoRA をダウンロード",
|
||||
"clear": "選択をクリア",
|
||||
"skipMetadataRefreshCount": "スキップ({count}モデル)",
|
||||
"resumeMetadataRefreshCount": "再開({count}モデル)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "ルート",
|
||||
"browseFolders": "フォルダを参照:",
|
||||
"downloadAndSaveRecipe": "ダウンロード & レシピ保存",
|
||||
"importRecipeOnly": "レシピのみインポート",
|
||||
"importAndDownload": "インポートとダウンロード",
|
||||
"downloadMissingLoras": "不足しているLoRAをダウンロード",
|
||||
"saveRecipe": "レシピを保存",
|
||||
"loraCountInfo": "({existing}/{total} ライブラリ内)",
|
||||
@@ -732,61 +743,61 @@
|
||||
}
|
||||
},
|
||||
"batchImport": {
|
||||
"title": "[TODO: Translate] Batch Import Recipes",
|
||||
"action": "[TODO: Translate] Batch Import",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "[TODO: Translate] Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "[TODO: Translate] Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "[TODO: Translate] https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"directoryPlaceholder": "[TODO: Translate] /path/to/images/folder",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"tagsOptional": "[TODO: Translate] Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "[TODO: Translate] Skip images without metadata",
|
||||
"skipNoMetadataHelp": "[TODO: Translate] Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"startImport": "[TODO: Translate] Start Import",
|
||||
"importing": "[TODO: Translate] Importing...",
|
||||
"progress": "[TODO: Translate] Progress",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"currentItem": "[TODO: Translate] Current",
|
||||
"preparing": "[TODO: Translate] Preparing...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancelImport": "[TODO: Translate] Cancel",
|
||||
"cancelled": "[TODO: Translate] Import cancelled",
|
||||
"completed": "[TODO: Translate] Import completed",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedSuccess": "[TODO: Translate] Successfully imported {count} recipe(s)",
|
||||
"successCount": "[TODO: Translate] Successful",
|
||||
"failedCount": "[TODO: Translate] Failed",
|
||||
"skippedCount": "[TODO: Translate] Skipped",
|
||||
"totalProcessed": "[TODO: Translate] Total processed",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"title": "Batch Import Recipes",
|
||||
"action": "Batch Import",
|
||||
"urlList": "URL List",
|
||||
"directory": "Directory",
|
||||
"urlDescription": "Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "Enter one URL or path per line",
|
||||
"directoryPath": "Directory Path",
|
||||
"directoryPlaceholder": "/path/to/images/folder",
|
||||
"browse": "Browse",
|
||||
"recursive": "Include subdirectories",
|
||||
"tagsOptional": "Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "Enter tags separated by commas",
|
||||
"tagsHint": "Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "Skip images without metadata",
|
||||
"skipNoMetadataHelp": "Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "Start Import",
|
||||
"startImport": "Start Import",
|
||||
"importing": "Importing...",
|
||||
"progress": "Progress",
|
||||
"total": "Total",
|
||||
"success": "Success",
|
||||
"failed": "Failed",
|
||||
"skipped": "Skipped",
|
||||
"current": "Current",
|
||||
"currentItem": "Current",
|
||||
"preparing": "Preparing...",
|
||||
"cancel": "Cancel",
|
||||
"cancelImport": "Cancel",
|
||||
"cancelled": "Import cancelled",
|
||||
"completed": "Import completed",
|
||||
"completedWithErrors": "Completed with errors",
|
||||
"completedSuccess": "Successfully imported {count} recipe(s)",
|
||||
"successCount": "Successful",
|
||||
"failedCount": "Failed",
|
||||
"skippedCount": "Skipped",
|
||||
"totalProcessed": "Total processed",
|
||||
"viewDetails": "View Details",
|
||||
"newImport": "New Import",
|
||||
"manualPathEntry": "Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"batchImportManualEntryRequired": "File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "Back to parent directory",
|
||||
"folders": "Folders",
|
||||
"folderCount": "{count} folders",
|
||||
"imageFiles": "Image Files",
|
||||
"images": "images",
|
||||
"imageCount": "{count} images",
|
||||
"selectFolder": "Select This Folder",
|
||||
"errors": {
|
||||
"enterUrls": "[TODO: Translate] Please enter at least one URL or path",
|
||||
"enterDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"startFailed": "[TODO: Translate] Failed to start import: {message}"
|
||||
"enterUrls": "Please enter at least one URL or path",
|
||||
"enterDirectory": "Please enter a directory path",
|
||||
"startFailed": "Failed to start import: {message}"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "ベースモデルを更新",
|
||||
"cancel": "キャンセル"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "不足している LoRA をダウンロード",
|
||||
"message": "選択したレシピから合計 {totalCount} 個中 {uniqueCount} 個のユニークな不足している LoRA が見つかりました。",
|
||||
"previewTitle": "ダウンロードする LoRA:",
|
||||
"moreItems": "...あと {count} 個",
|
||||
"note": "ファイルはデフォルトのパステンプレートを使用してダウンロードされます。LoRA の数によっては時間がかかる場合があります。",
|
||||
"downloadButton": "{count} 個の LoRA をダウンロード"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "ローカル例画像",
|
||||
"message": "このモデルのローカル例画像が見つかりませんでした。表示オプション:",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "処理エラー:{message}",
|
||||
"folderBrowserError": "フォルダブラウザの読み込みエラー:{message}",
|
||||
"recipeSaveFailed": "レシピの保存に失敗しました:{error}",
|
||||
"recipeSaved": "Recipe saved successfully",
|
||||
"importFailed": "インポートに失敗しました:{message}",
|
||||
"folderTreeFailed": "フォルダツリーの読み込みに失敗しました",
|
||||
"folderTreeError": "フォルダツリー読み込みエラー",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "Cancelling batch import...",
|
||||
"batchImportCancelFailed": "Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "Please enter a directory path",
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "レシピが選択されていません",
|
||||
"noMissingLorasInSelection": "選択したレシピに不足している LoRA が見つかりませんでした",
|
||||
"noLoraRootConfigured": "LoRA ルートディレクトリが設定されていません。設定でデフォルトの LoRA ルートを設定してください。"
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "モデルが選択されていません",
|
||||
|
||||
147
locales/ko.json
147
locales/ko.json
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "NSFW 콘텐츠 블러 처리",
|
||||
"blurNsfwContentHelp": "성인(NSFW) 콘텐츠 미리보기 이미지를 블러 처리합니다",
|
||||
"showOnlySfw": "SFW 결과만 표시",
|
||||
"showOnlySfwHelp": "탐색 및 검색 시 모든 NSFW 콘텐츠를 필터링합니다"
|
||||
"showOnlySfwHelp": "탐색 및 검색 시 모든 NSFW 콘텐츠를 필터링합니다",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "호버 시 비디오 자동 재생",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "선택한 모델의 메타데이터 새로고침 건너뛰기",
|
||||
"resumeMetadataRefresh": "선택한 모델의 메타데이터 새로고침 재개",
|
||||
"deleteAll": "모든 모델 삭제",
|
||||
"downloadMissingLoras": "누락된 LoRA 다운로드",
|
||||
"clear": "선택 지우기",
|
||||
"skipMetadataRefreshCount": "건너뛰기({count}개 모델)",
|
||||
"resumeMetadataRefreshCount": "재개({count}개 모델)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "루트",
|
||||
"browseFolders": "폴더 탐색:",
|
||||
"downloadAndSaveRecipe": "다운로드 및 레시피 저장",
|
||||
"importRecipeOnly": "레시피만 가져오기",
|
||||
"importAndDownload": "가져오기 및 다운로드",
|
||||
"downloadMissingLoras": "누락된 LoRA 다운로드",
|
||||
"saveRecipe": "레시피 저장",
|
||||
"loraCountInfo": "({existing}/{total} 라이브러리에 있음)",
|
||||
@@ -732,61 +743,61 @@
|
||||
}
|
||||
},
|
||||
"batchImport": {
|
||||
"title": "[TODO: Translate] Batch Import Recipes",
|
||||
"action": "[TODO: Translate] Batch Import",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "[TODO: Translate] Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "[TODO: Translate] Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "[TODO: Translate] https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"directoryPlaceholder": "[TODO: Translate] /path/to/images/folder",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"tagsOptional": "[TODO: Translate] Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "[TODO: Translate] Skip images without metadata",
|
||||
"skipNoMetadataHelp": "[TODO: Translate] Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"startImport": "[TODO: Translate] Start Import",
|
||||
"importing": "[TODO: Translate] Importing...",
|
||||
"progress": "[TODO: Translate] Progress",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"currentItem": "[TODO: Translate] Current",
|
||||
"preparing": "[TODO: Translate] Preparing...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancelImport": "[TODO: Translate] Cancel",
|
||||
"cancelled": "[TODO: Translate] Import cancelled",
|
||||
"completed": "[TODO: Translate] Import completed",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedSuccess": "[TODO: Translate] Successfully imported {count} recipe(s)",
|
||||
"successCount": "[TODO: Translate] Successful",
|
||||
"failedCount": "[TODO: Translate] Failed",
|
||||
"skippedCount": "[TODO: Translate] Skipped",
|
||||
"totalProcessed": "[TODO: Translate] Total processed",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"title": "Batch Import Recipes",
|
||||
"action": "Batch Import",
|
||||
"urlList": "URL List",
|
||||
"directory": "Directory",
|
||||
"urlDescription": "Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "Enter one URL or path per line",
|
||||
"directoryPath": "Directory Path",
|
||||
"directoryPlaceholder": "/path/to/images/folder",
|
||||
"browse": "Browse",
|
||||
"recursive": "Include subdirectories",
|
||||
"tagsOptional": "Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "Enter tags separated by commas",
|
||||
"tagsHint": "Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "Skip images without metadata",
|
||||
"skipNoMetadataHelp": "Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "Start Import",
|
||||
"startImport": "Start Import",
|
||||
"importing": "Importing...",
|
||||
"progress": "Progress",
|
||||
"total": "Total",
|
||||
"success": "Success",
|
||||
"failed": "Failed",
|
||||
"skipped": "Skipped",
|
||||
"current": "Current",
|
||||
"currentItem": "Current",
|
||||
"preparing": "Preparing...",
|
||||
"cancel": "Cancel",
|
||||
"cancelImport": "Cancel",
|
||||
"cancelled": "Import cancelled",
|
||||
"completed": "Import completed",
|
||||
"completedWithErrors": "Completed with errors",
|
||||
"completedSuccess": "Successfully imported {count} recipe(s)",
|
||||
"successCount": "Successful",
|
||||
"failedCount": "Failed",
|
||||
"skippedCount": "Skipped",
|
||||
"totalProcessed": "Total processed",
|
||||
"viewDetails": "View Details",
|
||||
"newImport": "New Import",
|
||||
"manualPathEntry": "Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"batchImportManualEntryRequired": "File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "Back to parent directory",
|
||||
"folders": "Folders",
|
||||
"folderCount": "{count} folders",
|
||||
"imageFiles": "Image Files",
|
||||
"images": "images",
|
||||
"imageCount": "{count} images",
|
||||
"selectFolder": "Select This Folder",
|
||||
"errors": {
|
||||
"enterUrls": "[TODO: Translate] Please enter at least one URL or path",
|
||||
"enterDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"startFailed": "[TODO: Translate] Failed to start import: {message}"
|
||||
"enterUrls": "Please enter at least one URL or path",
|
||||
"enterDirectory": "Please enter a directory path",
|
||||
"startFailed": "Failed to start import: {message}"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "베이스 모델 업데이트",
|
||||
"cancel": "취소"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "누락된 LoRA 다운로드",
|
||||
"message": "선택한 레시피에서 총 {totalCount}개 중 {uniqueCount}개의 고유한 누락된 LoRA를 찾았습니다.",
|
||||
"previewTitle": "다운로드할 LoRA:",
|
||||
"moreItems": "...그리고 {count}개 더",
|
||||
"note": "파일은 기본 경로 템플릿을 사용하여 다운로드됩니다. LoRA의 수에 따라 다소 시간이 걸릴 수 있습니다.",
|
||||
"downloadButton": "{count}개 LoRA 다운로드"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "로컬 예시 이미지",
|
||||
"message": "이 모델의 로컬 예시 이미지를 찾을 수 없습니다. 보기 옵션:",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "처리 오류: {message}",
|
||||
"folderBrowserError": "폴더 브라우저 로딩 오류: {message}",
|
||||
"recipeSaveFailed": "레시피 저장 실패: {error}",
|
||||
"recipeSaved": "Recipe saved successfully",
|
||||
"importFailed": "가져오기 실패: {message}",
|
||||
"folderTreeFailed": "폴더 트리 로딩 실패",
|
||||
"folderTreeError": "폴더 트리 로딩 오류",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "Cancelling batch import...",
|
||||
"batchImportCancelFailed": "Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "Please enter a directory path",
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "선택한 레시피가 없습니다",
|
||||
"noMissingLorasInSelection": "선택한 레시피에서 누락된 LoRA를 찾을 수 없습니다",
|
||||
"noLoraRootConfigured": "LoRA 루트 디렉토리가 구성되지 않았습니다. 설정에서 기본 LoRA 루트를 설정하세요."
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "선택된 모델이 없습니다",
|
||||
|
||||
147
locales/ru.json
147
locales/ru.json
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "Размывать NSFW контент",
|
||||
"blurNsfwContentHelp": "Размывать превью изображений контента для взрослых (NSFW)",
|
||||
"showOnlySfw": "Показывать только SFW результаты",
|
||||
"showOnlySfwHelp": "Фильтровать весь NSFW контент при просмотре и поиске"
|
||||
"showOnlySfwHelp": "Фильтровать весь NSFW контент при просмотре и поиске",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "Автовоспроизведение видео при наведении",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "Пропустить обновление метаданных для выбранных",
|
||||
"resumeMetadataRefresh": "Возобновить обновление метаданных для выбранных",
|
||||
"deleteAll": "Удалить все модели",
|
||||
"downloadMissingLoras": "Скачать отсутствующие LoRAs",
|
||||
"clear": "Очистить выбор",
|
||||
"skipMetadataRefreshCount": "Пропустить({count} моделей)",
|
||||
"resumeMetadataRefreshCount": "Возобновить({count} моделей)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "Корень",
|
||||
"browseFolders": "Обзор папок:",
|
||||
"downloadAndSaveRecipe": "Скачать и сохранить рецепт",
|
||||
"importRecipeOnly": "Импортировать только рецепт",
|
||||
"importAndDownload": "Импорт и скачивание",
|
||||
"downloadMissingLoras": "Скачать отсутствующие LoRAs",
|
||||
"saveRecipe": "Сохранить рецепт",
|
||||
"loraCountInfo": "({existing}/{total} в библиотеке)",
|
||||
@@ -732,61 +743,61 @@
|
||||
}
|
||||
},
|
||||
"batchImport": {
|
||||
"title": "[TODO: Translate] Batch Import Recipes",
|
||||
"action": "[TODO: Translate] Batch Import",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "[TODO: Translate] Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "[TODO: Translate] Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "[TODO: Translate] https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"directoryPlaceholder": "[TODO: Translate] /path/to/images/folder",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"tagsOptional": "[TODO: Translate] Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "[TODO: Translate] Skip images without metadata",
|
||||
"skipNoMetadataHelp": "[TODO: Translate] Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"startImport": "[TODO: Translate] Start Import",
|
||||
"importing": "[TODO: Translate] Importing...",
|
||||
"progress": "[TODO: Translate] Progress",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"currentItem": "[TODO: Translate] Current",
|
||||
"preparing": "[TODO: Translate] Preparing...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancelImport": "[TODO: Translate] Cancel",
|
||||
"cancelled": "[TODO: Translate] Import cancelled",
|
||||
"completed": "[TODO: Translate] Import completed",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedSuccess": "[TODO: Translate] Successfully imported {count} recipe(s)",
|
||||
"successCount": "[TODO: Translate] Successful",
|
||||
"failedCount": "[TODO: Translate] Failed",
|
||||
"skippedCount": "[TODO: Translate] Skipped",
|
||||
"totalProcessed": "[TODO: Translate] Total processed",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"title": "Batch Import Recipes",
|
||||
"action": "Batch Import",
|
||||
"urlList": "URL List",
|
||||
"directory": "Directory",
|
||||
"urlDescription": "Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "Enter one URL or path per line",
|
||||
"directoryPath": "Directory Path",
|
||||
"directoryPlaceholder": "/path/to/images/folder",
|
||||
"browse": "Browse",
|
||||
"recursive": "Include subdirectories",
|
||||
"tagsOptional": "Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "Enter tags separated by commas",
|
||||
"tagsHint": "Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "Skip images without metadata",
|
||||
"skipNoMetadataHelp": "Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "Start Import",
|
||||
"startImport": "Start Import",
|
||||
"importing": "Importing...",
|
||||
"progress": "Progress",
|
||||
"total": "Total",
|
||||
"success": "Success",
|
||||
"failed": "Failed",
|
||||
"skipped": "Skipped",
|
||||
"current": "Current",
|
||||
"currentItem": "Current",
|
||||
"preparing": "Preparing...",
|
||||
"cancel": "Cancel",
|
||||
"cancelImport": "Cancel",
|
||||
"cancelled": "Import cancelled",
|
||||
"completed": "Import completed",
|
||||
"completedWithErrors": "Completed with errors",
|
||||
"completedSuccess": "Successfully imported {count} recipe(s)",
|
||||
"successCount": "Successful",
|
||||
"failedCount": "Failed",
|
||||
"skippedCount": "Skipped",
|
||||
"totalProcessed": "Total processed",
|
||||
"viewDetails": "View Details",
|
||||
"newImport": "New Import",
|
||||
"manualPathEntry": "Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"batchImportManualEntryRequired": "File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "Back to parent directory",
|
||||
"folders": "Folders",
|
||||
"folderCount": "{count} folders",
|
||||
"imageFiles": "Image Files",
|
||||
"images": "images",
|
||||
"imageCount": "{count} images",
|
||||
"selectFolder": "Select This Folder",
|
||||
"errors": {
|
||||
"enterUrls": "[TODO: Translate] Please enter at least one URL or path",
|
||||
"enterDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"startFailed": "[TODO: Translate] Failed to start import: {message}"
|
||||
"enterUrls": "Please enter at least one URL or path",
|
||||
"enterDirectory": "Please enter a directory path",
|
||||
"startFailed": "Failed to start import: {message}"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "Обновить базовую модель",
|
||||
"cancel": "Отмена"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "Скачать отсутствующие LoRAs",
|
||||
"message": "Найдено {uniqueCount} уникальных отсутствующих LoRAs (из {totalCount} всего в выбранных рецептах).",
|
||||
"previewTitle": "LoRAs для скачивания:",
|
||||
"moreItems": "...и еще {count}",
|
||||
"note": "Файлы будут скачаны с использованием шаблонов путей по умолчанию. Это может занять некоторое время в зависимости от количества LoRAs.",
|
||||
"downloadButton": "Скачать {count} LoRA(s)"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "Локальные примеры изображений",
|
||||
"message": "Локальные примеры изображений для этой модели не найдены. Варианты просмотра:",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "Ошибка обработки: {message}",
|
||||
"folderBrowserError": "Ошибка загрузки браузера папок: {message}",
|
||||
"recipeSaveFailed": "Не удалось сохранить рецепт: {error}",
|
||||
"recipeSaved": "Recipe saved successfully",
|
||||
"importFailed": "Импорт не удался: {message}",
|
||||
"folderTreeFailed": "Не удалось загрузить дерево папок",
|
||||
"folderTreeError": "Ошибка загрузки дерева папок",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "Cancelling batch import...",
|
||||
"batchImportCancelFailed": "Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "Please enter a directory path",
|
||||
"batchImportBrowseFailed": "Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "Directory selected: {path}",
|
||||
"noRecipesSelected": "Рецепты не выбраны",
|
||||
"noMissingLorasInSelection": "В выбранных рецептах не найдены отсутствующие LoRAs",
|
||||
"noLoraRootConfigured": "Корневой каталог LoRA не настроен. Пожалуйста, установите корневой каталог LoRA по умолчанию в настройках."
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "Модели не выбраны",
|
||||
|
||||
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "模糊 NSFW 内容",
|
||||
"blurNsfwContentHelp": "模糊成熟(NSFW)内容预览图片",
|
||||
"showOnlySfw": "仅显示 SFW 结果",
|
||||
"showOnlySfwHelp": "浏览和搜索时过滤所有 NSFW 内容"
|
||||
"showOnlySfwHelp": "浏览和搜索时过滤所有 NSFW 内容",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "悬停时自动播放视频",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "跳过所选模型的元数据刷新",
|
||||
"resumeMetadataRefresh": "恢复所选模型的元数据刷新",
|
||||
"deleteAll": "删除选中模型",
|
||||
"downloadMissingLoras": "下载缺失的 LoRAs",
|
||||
"clear": "清除选择",
|
||||
"skipMetadataRefreshCount": "跳过({count} 个模型)",
|
||||
"resumeMetadataRefreshCount": "恢复({count} 个模型)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "根目录",
|
||||
"browseFolders": "浏览文件夹:",
|
||||
"downloadAndSaveRecipe": "下载并保存配方",
|
||||
"importRecipeOnly": "仅导入配方",
|
||||
"importAndDownload": "导入并下载",
|
||||
"downloadMissingLoras": "下载缺失的 LoRA",
|
||||
"saveRecipe": "保存配方",
|
||||
"loraCountInfo": "({existing}/{total} in library)",
|
||||
@@ -734,55 +745,55 @@
|
||||
"batchImport": {
|
||||
"title": "批量导入配方",
|
||||
"action": "批量导入",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"urlList": "URL 列表",
|
||||
"directory": "目录",
|
||||
"urlDescription": "输入图像 URL 或本地文件路径(每行一个)。每个都将作为配方导入。",
|
||||
"directoryDescription": "输入目录路径以导入该文件夹中的所有图片。",
|
||||
"urlsLabel": "图片 URL 或本地路径",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"urlsHint": "每行输入一个 URL 或路径",
|
||||
"directoryPath": "目录路径",
|
||||
"directoryPlaceholder": "/图片/文件夹/路径",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"browse": "浏览",
|
||||
"recursive": "包含子目录",
|
||||
"tagsOptional": "标签(可选,应用于所有配方)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"tagsPlaceholder": "输入以逗号分隔的标签",
|
||||
"tagsHint": "标签将被添加到所有导入的配方中",
|
||||
"skipNoMetadata": "跳过无元数据的图片",
|
||||
"skipNoMetadataHelp": "没有 LoRA 元数据的图片将自动跳过。",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"start": "开始导入",
|
||||
"startImport": "开始导入",
|
||||
"importing": "正在导入配方...",
|
||||
"progress": "进度",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"total": "总计",
|
||||
"success": "成功",
|
||||
"failed": "失败",
|
||||
"skipped": "跳过",
|
||||
"current": "当前",
|
||||
"currentItem": "当前",
|
||||
"preparing": "准备中...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancel": "取消",
|
||||
"cancelImport": "取消",
|
||||
"cancelled": "批量导入已取消",
|
||||
"completed": "导入完成",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedWithErrors": "导入完成但有错误",
|
||||
"completedSuccess": "成功导入 {count} 个配方",
|
||||
"successCount": "成功",
|
||||
"failedCount": "失败",
|
||||
"skippedCount": "跳过",
|
||||
"totalProcessed": "总计处理",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"viewDetails": "查看详情",
|
||||
"newImport": "新建导入",
|
||||
"manualPathEntry": "请手动输入目录路径。此浏览器中文件浏览器不可用。",
|
||||
"batchImportDirectorySelected": "已选择目录:{path}",
|
||||
"batchImportManualEntryRequired": "文件浏览器不可用。请手动输入目录路径。",
|
||||
"backToParent": "返回上级目录",
|
||||
"folders": "文件夹",
|
||||
"folderCount": "{count} 个文件夹",
|
||||
"imageFiles": "图像文件",
|
||||
"images": "图像",
|
||||
"imageCount": "{count} 个图像",
|
||||
"selectFolder": "选择此文件夹",
|
||||
"errors": {
|
||||
"enterUrls": "请至少输入一个 URL 或路径",
|
||||
"enterDirectory": "请输入目录路径",
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "更新基础模型",
|
||||
"cancel": "取消"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "下载缺失的 LoRAs",
|
||||
"message": "发现 {uniqueCount} 个独特的缺失 LoRAs(从选定配方中的 {totalCount} 个总数)。",
|
||||
"previewTitle": "要下载的 LoRAs:",
|
||||
"moreItems": "...还有 {count} 个",
|
||||
"note": "文件将使用默认路径模板下载。根据 LoRAs 的数量,这可能需要一些时间。",
|
||||
"downloadButton": "下载 {count} 个 LoRA(s)"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "本地示例图片",
|
||||
"message": "未找到此模型的本地示例图片。可选操作:",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "处理出错:{message}",
|
||||
"folderBrowserError": "加载文件夹浏览器出错:{message}",
|
||||
"recipeSaveFailed": "保存配方失败:{error}",
|
||||
"recipeSaved": "配方保存成功",
|
||||
"importFailed": "导入失败:{message}",
|
||||
"folderTreeFailed": "加载文件夹树失败",
|
||||
"folderTreeError": "加载文件夹树出错",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "启动批量导入失败:{message}",
|
||||
"batchImportCancelling": "正在取消批量导入...",
|
||||
"batchImportCancelFailed": "取消批量导入失败:{message}",
|
||||
"batchImportNoUrls": "请输入至少一个 URL 或文件路径",
|
||||
"batchImportNoDirectory": "请输入目录路径",
|
||||
"batchImportBrowseFailed": "浏览目录失败:{message}",
|
||||
"batchImportDirectorySelected": "已选择目录:{path}",
|
||||
"noRecipesSelected": "未选择任何配方",
|
||||
"noMissingLorasInSelection": "在选定的配方中未找到缺失的 LoRAs",
|
||||
"noLoraRootConfigured": "未配置 LoRA 根目录。请在设置中设置默认的 LoRA 根目录。"
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "未选中模型",
|
||||
|
||||
@@ -291,7 +291,15 @@
|
||||
"blurNsfwContent": "模糊 NSFW 內容",
|
||||
"blurNsfwContentHelp": "模糊成熟(NSFW)內容預覽圖片",
|
||||
"showOnlySfw": "僅顯示 SFW 結果",
|
||||
"showOnlySfwHelp": "瀏覽和搜尋時過濾所有 NSFW 內容"
|
||||
"showOnlySfwHelp": "瀏覽和搜尋時過濾所有 NSFW 內容",
|
||||
"matureBlurThreshold": "[TODO: Translate] Mature Blur Threshold",
|
||||
"matureBlurThresholdHelp": "[TODO: Translate] Set which rating level starts blur filtering when NSFW blur is enabled.",
|
||||
"matureBlurThresholdOptions": {
|
||||
"pg13": "[TODO: Translate] PG13 and above",
|
||||
"r": "[TODO: Translate] R and above (default)",
|
||||
"x": "[TODO: Translate] X and above",
|
||||
"xxx": "[TODO: Translate] XXX only"
|
||||
}
|
||||
},
|
||||
"videoSettings": {
|
||||
"autoplayOnHover": "滑鼠懸停自動播放影片",
|
||||
@@ -575,6 +583,7 @@
|
||||
"skipMetadataRefresh": "跳過所選模型的元數據更新",
|
||||
"resumeMetadataRefresh": "恢復所選模型的元數據更新",
|
||||
"deleteAll": "刪除全部模型",
|
||||
"downloadMissingLoras": "下載缺失的 LoRAs",
|
||||
"clear": "清除選取",
|
||||
"skipMetadataRefreshCount": "跳過({count} 個模型)",
|
||||
"resumeMetadataRefreshCount": "恢復({count} 個模型)",
|
||||
@@ -645,6 +654,8 @@
|
||||
"root": "根目錄",
|
||||
"browseFolders": "瀏覽資料夾:",
|
||||
"downloadAndSaveRecipe": "下載並儲存配方",
|
||||
"importRecipeOnly": "僅匯入配方",
|
||||
"importAndDownload": "匯入並下載",
|
||||
"downloadMissingLoras": "下載缺少的 LoRA",
|
||||
"saveRecipe": "儲存配方",
|
||||
"loraCountInfo": "(庫存 {existing}/{total})",
|
||||
@@ -732,61 +743,61 @@
|
||||
}
|
||||
},
|
||||
"batchImport": {
|
||||
"title": "[TODO: Translate] Batch Import Recipes",
|
||||
"action": "[TODO: Translate] Batch Import",
|
||||
"urlList": "[TODO: Translate] URL List",
|
||||
"directory": "[TODO: Translate] Directory",
|
||||
"urlDescription": "[TODO: Translate] Enter image URLs or local file paths (one per line). Each will be imported as a recipe.",
|
||||
"directoryDescription": "[TODO: Translate] Enter a directory path to import all images from that folder.",
|
||||
"urlsLabel": "[TODO: Translate] Image URLs or Local Paths",
|
||||
"urlsPlaceholder": "[TODO: Translate] https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "[TODO: Translate] Enter one URL or path per line",
|
||||
"directoryPath": "[TODO: Translate] Directory Path",
|
||||
"directoryPlaceholder": "[TODO: Translate] /path/to/images/folder",
|
||||
"browse": "[TODO: Translate] Browse",
|
||||
"recursive": "[TODO: Translate] Include subdirectories",
|
||||
"tagsOptional": "[TODO: Translate] Tags (optional, applied to all recipes)",
|
||||
"tagsPlaceholder": "[TODO: Translate] Enter tags separated by commas",
|
||||
"tagsHint": "[TODO: Translate] Tags will be added to all imported recipes",
|
||||
"skipNoMetadata": "[TODO: Translate] Skip images without metadata",
|
||||
"skipNoMetadataHelp": "[TODO: Translate] Images without LoRA metadata will be skipped automatically.",
|
||||
"start": "[TODO: Translate] Start Import",
|
||||
"startImport": "[TODO: Translate] Start Import",
|
||||
"importing": "[TODO: Translate] Importing...",
|
||||
"progress": "[TODO: Translate] Progress",
|
||||
"total": "[TODO: Translate] Total",
|
||||
"success": "[TODO: Translate] Success",
|
||||
"failed": "[TODO: Translate] Failed",
|
||||
"skipped": "[TODO: Translate] Skipped",
|
||||
"current": "[TODO: Translate] Current",
|
||||
"currentItem": "[TODO: Translate] Current",
|
||||
"preparing": "[TODO: Translate] Preparing...",
|
||||
"cancel": "[TODO: Translate] Cancel",
|
||||
"cancelImport": "[TODO: Translate] Cancel",
|
||||
"cancelled": "[TODO: Translate] Import cancelled",
|
||||
"completed": "[TODO: Translate] Import completed",
|
||||
"completedWithErrors": "[TODO: Translate] Completed with errors",
|
||||
"completedSuccess": "[TODO: Translate] Successfully imported {count} recipe(s)",
|
||||
"successCount": "[TODO: Translate] Successful",
|
||||
"failedCount": "[TODO: Translate] Failed",
|
||||
"skippedCount": "[TODO: Translate] Skipped",
|
||||
"totalProcessed": "[TODO: Translate] Total processed",
|
||||
"viewDetails": "[TODO: Translate] View Details",
|
||||
"newImport": "[TODO: Translate] New Import",
|
||||
"manualPathEntry": "[TODO: Translate] Please enter the directory path manually. File browser is not available in this browser.",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {name}. You may need to enter the full path manually.",
|
||||
"batchImportManualEntryRequired": "[TODO: Translate] File browser not available. Please enter the directory path manually.",
|
||||
"backToParent": "[TODO: Translate] Back to parent directory",
|
||||
"folders": "[TODO: Translate] Folders",
|
||||
"folderCount": "[TODO: Translate] {count} folders",
|
||||
"imageFiles": "[TODO: Translate] Image Files",
|
||||
"images": "[TODO: Translate] images",
|
||||
"imageCount": "[TODO: Translate] {count} images",
|
||||
"selectFolder": "[TODO: Translate] Select This Folder",
|
||||
"title": "批量匯入配方",
|
||||
"action": "批量匯入",
|
||||
"urlList": "URL 列表",
|
||||
"directory": "目錄",
|
||||
"urlDescription": "輸入圖像 URL 或本地檔案路徑(每行一個)。每個都將作為配方匯入。",
|
||||
"directoryDescription": "輸入目錄路徑以匯入該資料夾中的所有圖像。",
|
||||
"urlsLabel": "圖像 URL 或本地路徑",
|
||||
"urlsPlaceholder": "https://civitai.com/images/...\nhttps://civitai.com/images/...\nC:/path/to/image.png\n...",
|
||||
"urlsHint": "每行輸入一個 URL 或路徑",
|
||||
"directoryPath": "目錄路徑",
|
||||
"directoryPlaceholder": "/path/to/images/folder",
|
||||
"browse": "瀏覽",
|
||||
"recursive": "包含子目錄",
|
||||
"tagsOptional": "標籤(可選,應用於所有配方)",
|
||||
"tagsPlaceholder": "輸入以逗號分隔的標籤",
|
||||
"tagsHint": "標籤將被添加到所有匯入的配方中",
|
||||
"skipNoMetadata": "跳過無元資料的圖像",
|
||||
"skipNoMetadataHelp": "沒有 LoRA 元資料的圖像將被自動跳過。",
|
||||
"start": "開始匯入",
|
||||
"startImport": "開始匯入",
|
||||
"importing": "匯入中...",
|
||||
"progress": "進度",
|
||||
"total": "總計",
|
||||
"success": "成功",
|
||||
"failed": "失敗",
|
||||
"skipped": "跳過",
|
||||
"current": "當前",
|
||||
"currentItem": "當前項目",
|
||||
"preparing": "準備中...",
|
||||
"cancel": "取消",
|
||||
"cancelImport": "取消匯入",
|
||||
"cancelled": "匯入已取消",
|
||||
"completed": "匯入完成",
|
||||
"completedWithErrors": "匯入完成但有錯誤",
|
||||
"completedSuccess": "成功匯入 {count} 個配方",
|
||||
"successCount": "成功",
|
||||
"failedCount": "失敗",
|
||||
"skippedCount": "跳過",
|
||||
"totalProcessed": "總計處理",
|
||||
"viewDetails": "查看詳情",
|
||||
"newImport": "新建匯入",
|
||||
"manualPathEntry": "請手動輸入目錄路徑。此瀏覽器中檔案瀏覽器不可用。",
|
||||
"batchImportDirectorySelected": "已選擇目錄:{path}",
|
||||
"batchImportManualEntryRequired": "檔案瀏覽器不可用。請手動輸入目錄路徑。",
|
||||
"backToParent": "返回上級目錄",
|
||||
"folders": "資料夾",
|
||||
"folderCount": "{count} 個資料夾",
|
||||
"imageFiles": "圖像檔案",
|
||||
"images": "圖像",
|
||||
"imageCount": "{count} 個圖像",
|
||||
"selectFolder": "選擇此資料夾",
|
||||
"errors": {
|
||||
"enterUrls": "[TODO: Translate] Please enter at least one URL or path",
|
||||
"enterDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"startFailed": "[TODO: Translate] Failed to start import: {message}"
|
||||
"enterUrls": "請輸入至少一個 URL 或路徑",
|
||||
"enterDirectory": "請輸入目錄路徑",
|
||||
"startFailed": "啟動匯入失敗:{message}"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -981,6 +992,14 @@
|
||||
"save": "更新基礎模型",
|
||||
"cancel": "取消"
|
||||
},
|
||||
"bulkDownloadMissingLoras": {
|
||||
"title": "下載缺失的 LoRAs",
|
||||
"message": "發現 {uniqueCount} 個獨特的缺失 LoRAs(從選取食譜中的 {totalCount} 個總數)。",
|
||||
"previewTitle": "要下載的 LoRAs:",
|
||||
"moreItems": "...還有 {count} 個",
|
||||
"note": "檔案將使用預設路徑模板下載。根據 LoRAs 的數量,這可能需要一些時間。",
|
||||
"downloadButton": "下載 {count} 個 LoRA(s)"
|
||||
},
|
||||
"exampleAccess": {
|
||||
"title": "本機範例圖片",
|
||||
"message": "此模型未找到本機範例圖片。可選擇:",
|
||||
@@ -1495,16 +1514,20 @@
|
||||
"processingError": "處理錯誤:{message}",
|
||||
"folderBrowserError": "載入資料夾瀏覽器錯誤:{message}",
|
||||
"recipeSaveFailed": "儲存配方失敗:{error}",
|
||||
"recipeSaved": "配方儲存成功",
|
||||
"importFailed": "匯入失敗:{message}",
|
||||
"folderTreeFailed": "載入資料夾樹狀結構失敗",
|
||||
"folderTreeError": "載入資料夾樹狀結構錯誤",
|
||||
"batchImportFailed": "[TODO: Translate] Failed to start batch import: {message}",
|
||||
"batchImportCancelling": "[TODO: Translate] Cancelling batch import...",
|
||||
"batchImportCancelFailed": "[TODO: Translate] Failed to cancel batch import: {message}",
|
||||
"batchImportNoUrls": "[TODO: Translate] Please enter at least one URL or file path",
|
||||
"batchImportNoDirectory": "[TODO: Translate] Please enter a directory path",
|
||||
"batchImportBrowseFailed": "[TODO: Translate] Failed to browse directory: {message}",
|
||||
"batchImportDirectorySelected": "[TODO: Translate] Directory selected: {path}"
|
||||
"batchImportFailed": "啟動批量匯入失敗:{message}",
|
||||
"batchImportCancelling": "正在取消批量匯入...",
|
||||
"batchImportCancelFailed": "取消批量匯入失敗:{message}",
|
||||
"batchImportNoUrls": "請輸入至少一個 URL 或檔案路徑",
|
||||
"batchImportNoDirectory": "請輸入目錄路徑",
|
||||
"batchImportBrowseFailed": "瀏覽目錄失敗:{message}",
|
||||
"batchImportDirectorySelected": "已選擇目錄:{path}",
|
||||
"noRecipesSelected": "未選取任何食譜",
|
||||
"noMissingLorasInSelection": "在選取的食譜中未找到缺失的 LoRAs",
|
||||
"noLoraRootConfigured": "未配置 LoRA 根目錄。請在設定中設定預設的 LoRA 根目錄。"
|
||||
},
|
||||
"models": {
|
||||
"noModelsSelected": "未選擇模型",
|
||||
|
||||
3
package-lock.json
generated
3
package-lock.json
generated
@@ -114,7 +114,6 @@
|
||||
}
|
||||
],
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"engines": {
|
||||
"node": ">=18"
|
||||
},
|
||||
@@ -138,7 +137,6 @@
|
||||
}
|
||||
],
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"engines": {
|
||||
"node": ">=18"
|
||||
}
|
||||
@@ -1613,7 +1611,6 @@
|
||||
"integrity": "sha512-MyL55p3Ut3cXbeBEG7Hcv0mVM8pp8PBNWxRqchZnSfAiES1v1mRnMeFfaHWIPULpwsYfvO+ZmMZz5tGCnjzDUQ==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"peer": true,
|
||||
"dependencies": {
|
||||
"cssstyle": "^4.0.1",
|
||||
"data-urls": "^5.0.0",
|
||||
|
||||
@@ -149,9 +149,12 @@ class MetadataHook:
|
||||
# Store the original _async_map_node_over_list function
|
||||
original_map_node_over_list = getattr(execution, map_node_func_name)
|
||||
|
||||
# Wrapped async function, compatible with both stable and nightly
|
||||
async def async_map_node_over_list_with_metadata(prompt_id, unique_id, obj, input_data_all, func, allow_interrupt=False, execution_block_cb=None, pre_execute_cb=None, *args, **kwargs):
|
||||
hidden_inputs = kwargs.get('hidden_inputs', None)
|
||||
# Wrapped async function - signature must exactly match _async_map_node_over_list
|
||||
async def async_map_node_over_list_with_metadata(
|
||||
prompt_id, unique_id, obj, input_data_all, func,
|
||||
allow_interrupt=False, execution_block_cb=None,
|
||||
pre_execute_cb=None, v3_data=None
|
||||
):
|
||||
# Only collect metadata when calling the main function of nodes
|
||||
if func == obj.FUNCTION and hasattr(obj, '__class__'):
|
||||
try:
|
||||
@@ -164,10 +167,10 @@ class MetadataHook:
|
||||
except Exception as e:
|
||||
logger.error(f"Error collecting metadata (pre-execution): {str(e)}")
|
||||
|
||||
# Call original function with all args/kwargs
|
||||
# Call original function with exact parameters
|
||||
results = await original_map_node_over_list(
|
||||
prompt_id, unique_id, obj, input_data_all, func,
|
||||
allow_interrupt, execution_block_cb, pre_execute_cb, *args, **kwargs
|
||||
allow_interrupt, execution_block_cb, pre_execute_cb, v3_data=v3_data
|
||||
)
|
||||
|
||||
if func == obj.FUNCTION and hasattr(obj, '__class__'):
|
||||
|
||||
@@ -1,8 +1,7 @@
|
||||
import logging
|
||||
import os
|
||||
from typing import List, Tuple
|
||||
import comfy.sd
|
||||
import folder_paths
|
||||
import comfy.sd # type: ignore
|
||||
import folder_paths # type: ignore
|
||||
from ..utils.utils import get_checkpoint_info_absolute, _format_model_name_for_comfyui
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -15,7 +14,7 @@ class CheckpointLoaderLM:
|
||||
extra folder paths, providing a unified interface for checkpoint loading.
|
||||
"""
|
||||
|
||||
NAME = "CheckpointLoaderLM"
|
||||
NAME = "Checkpoint Loader (LoraManager)"
|
||||
CATEGORY = "Lora Manager/loaders"
|
||||
|
||||
@classmethod
|
||||
@@ -60,7 +59,7 @@ class CheckpointLoaderLM:
|
||||
if item.get("sub_type") == "checkpoint":
|
||||
file_path = item.get("file_path", "")
|
||||
if file_path:
|
||||
# Format as ComfyUI-style: "folder/model_name.ext"
|
||||
# Format using relative path with OS-native separator
|
||||
formatted_name = _format_model_name_for_comfyui(
|
||||
file_path, model_roots
|
||||
)
|
||||
@@ -94,7 +93,7 @@ class CheckpointLoaderLM:
|
||||
"""Load a checkpoint by name, supporting extra folder paths
|
||||
|
||||
Args:
|
||||
ckpt_name: The name of the checkpoint to load (format: "folder/model_name.ext")
|
||||
ckpt_name: The name of the checkpoint to load (relative path with extension)
|
||||
|
||||
Returns:
|
||||
Tuple of (MODEL, CLIP, VAE)
|
||||
@@ -108,10 +107,6 @@ class CheckpointLoaderLM:
|
||||
"Make sure the checkpoint is indexed and try again."
|
||||
)
|
||||
|
||||
# Check if it's a GGUF model
|
||||
if ckpt_path.endswith(".gguf"):
|
||||
return self._load_gguf_checkpoint(ckpt_path, ckpt_name)
|
||||
|
||||
# Load regular checkpoint using ComfyUI's API
|
||||
logger.info(f"Loading checkpoint from: {ckpt_path}")
|
||||
out = comfy.sd.load_checkpoint_guess_config(
|
||||
@@ -121,64 +116,3 @@ class CheckpointLoaderLM:
|
||||
embedding_directory=folder_paths.get_folder_paths("embeddings"),
|
||||
)
|
||||
return out[:3]
|
||||
|
||||
def _load_gguf_checkpoint(self, ckpt_path: str, ckpt_name: str) -> Tuple:
|
||||
"""Load a GGUF format checkpoint
|
||||
|
||||
Args:
|
||||
ckpt_path: Absolute path to the GGUF file
|
||||
ckpt_name: Name of the checkpoint for error messages
|
||||
|
||||
Returns:
|
||||
Tuple of (MODEL, CLIP, VAE) - CLIP and VAE may be None for GGUF
|
||||
"""
|
||||
try:
|
||||
# Try to import ComfyUI-GGUF modules
|
||||
from custom_nodes.ComfyUI_GGUF.loader import gguf_sd_loader
|
||||
from custom_nodes.ComfyUI_GGUF.ops import GGMLOps
|
||||
from custom_nodes.ComfyUI_GGUF.nodes import GGUFModelPatcher
|
||||
except ImportError:
|
||||
raise RuntimeError(
|
||||
f"Cannot load GGUF model '{ckpt_name}'. "
|
||||
"ComfyUI-GGUF is not installed. "
|
||||
"Please install ComfyUI-GGUF from https://github.com/city96/ComfyUI-GGUF "
|
||||
"to load GGUF format models."
|
||||
)
|
||||
|
||||
logger.info(f"Loading GGUF checkpoint from: {ckpt_path}")
|
||||
|
||||
try:
|
||||
# Load GGUF state dict
|
||||
sd, extra = gguf_sd_loader(ckpt_path)
|
||||
|
||||
# Prepare kwargs for metadata if supported
|
||||
kwargs = {}
|
||||
import inspect
|
||||
|
||||
valid_params = inspect.signature(
|
||||
comfy.sd.load_diffusion_model_state_dict
|
||||
).parameters
|
||||
if "metadata" in valid_params:
|
||||
kwargs["metadata"] = extra.get("metadata", {})
|
||||
|
||||
# Load the model
|
||||
model = comfy.sd.load_diffusion_model_state_dict(
|
||||
sd, model_options={"custom_operations": GGMLOps()}, **kwargs
|
||||
)
|
||||
|
||||
if model is None:
|
||||
raise RuntimeError(
|
||||
f"Could not detect model type for GGUF checkpoint: {ckpt_path}"
|
||||
)
|
||||
|
||||
# Wrap with GGUFModelPatcher
|
||||
model = GGUFModelPatcher.clone(model)
|
||||
|
||||
# GGUF checkpoints typically don't include CLIP/VAE
|
||||
return (model, None, None)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error loading GGUF checkpoint '{ckpt_name}': {e}")
|
||||
raise RuntimeError(
|
||||
f"Failed to load GGUF checkpoint '{ckpt_name}': {str(e)}"
|
||||
)
|
||||
|
||||
161
py/nodes/gguf_import_helper.py
Normal file
161
py/nodes/gguf_import_helper.py
Normal file
@@ -0,0 +1,161 @@
|
||||
"""
|
||||
Helper module to safely import ComfyUI-GGUF modules.
|
||||
|
||||
This module provides a robust way to import ComfyUI-GGUF functionality
|
||||
regardless of how ComfyUI loaded it.
|
||||
"""
|
||||
|
||||
import sys
|
||||
import os
|
||||
import importlib.util
|
||||
import logging
|
||||
from typing import Optional, Tuple, Any
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def _get_gguf_path() -> str:
|
||||
"""Get the path to ComfyUI-GGUF based on this file's location.
|
||||
|
||||
Since ComfyUI-Lora-Manager and ComfyUI-GGUF are both in custom_nodes/,
|
||||
we can derive the GGUF path from our own location.
|
||||
"""
|
||||
# This file is at: custom_nodes/ComfyUI-Lora-Manager/py/nodes/gguf_import_helper.py
|
||||
# ComfyUI-GGUF is at: custom_nodes/ComfyUI-GGUF
|
||||
current_file = os.path.abspath(__file__)
|
||||
# Go up 4 levels: nodes -> py -> ComfyUI-Lora-Manager -> custom_nodes
|
||||
custom_nodes_dir = os.path.dirname(
|
||||
os.path.dirname(os.path.dirname(os.path.dirname(current_file)))
|
||||
)
|
||||
return os.path.join(custom_nodes_dir, "ComfyUI-GGUF")
|
||||
|
||||
|
||||
def _find_gguf_module() -> Optional[Any]:
|
||||
"""Find ComfyUI-GGUF module in sys.modules.
|
||||
|
||||
ComfyUI registers modules using the full path with dots replaced by _x_.
|
||||
"""
|
||||
gguf_path = _get_gguf_path()
|
||||
sys_module_name = gguf_path.replace(".", "_x_")
|
||||
|
||||
logger.debug(f"[GGUF Import] Looking for module '{sys_module_name}' in sys.modules")
|
||||
if sys_module_name in sys.modules:
|
||||
logger.info(f"[GGUF Import] Found module: '{sys_module_name}'")
|
||||
return sys.modules[sys_module_name]
|
||||
|
||||
logger.debug(f"[GGUF Import] Module not found: '{sys_module_name}'")
|
||||
return None
|
||||
|
||||
|
||||
def _load_gguf_modules_directly() -> Optional[Any]:
|
||||
"""Load ComfyUI-GGUF modules directly from file paths."""
|
||||
gguf_path = _get_gguf_path()
|
||||
|
||||
logger.info(f"[GGUF Import] Direct Load: Attempting to load from '{gguf_path}'")
|
||||
|
||||
if not os.path.exists(gguf_path):
|
||||
logger.warning(f"[GGUF Import] Path does not exist: {gguf_path}")
|
||||
return None
|
||||
|
||||
try:
|
||||
namespace = "ComfyUI_GGUF_Dynamic"
|
||||
init_path = os.path.join(gguf_path, "__init__.py")
|
||||
|
||||
if not os.path.exists(init_path):
|
||||
logger.warning(f"[GGUF Import] __init__.py not found at '{init_path}'")
|
||||
return None
|
||||
|
||||
logger.debug(f"[GGUF Import] Loading from '{init_path}'")
|
||||
spec = importlib.util.spec_from_file_location(namespace, init_path)
|
||||
if not spec or not spec.loader:
|
||||
logger.error(f"[GGUF Import] Failed to create spec for '{init_path}'")
|
||||
return None
|
||||
|
||||
package = importlib.util.module_from_spec(spec)
|
||||
package.__path__ = [gguf_path]
|
||||
sys.modules[namespace] = package
|
||||
spec.loader.exec_module(package)
|
||||
logger.debug(f"[GGUF Import] Loaded main package '{namespace}'")
|
||||
|
||||
# Load submodules
|
||||
loaded = []
|
||||
for submod_name in ["loader", "ops", "nodes"]:
|
||||
submod_path = os.path.join(gguf_path, f"{submod_name}.py")
|
||||
if os.path.exists(submod_path):
|
||||
submod_spec = importlib.util.spec_from_file_location(
|
||||
f"{namespace}.{submod_name}", submod_path
|
||||
)
|
||||
if submod_spec and submod_spec.loader:
|
||||
submod = importlib.util.module_from_spec(submod_spec)
|
||||
submod.__package__ = namespace
|
||||
sys.modules[f"{namespace}.{submod_name}"] = submod
|
||||
submod_spec.loader.exec_module(submod)
|
||||
setattr(package, submod_name, submod)
|
||||
loaded.append(submod_name)
|
||||
logger.debug(f"[GGUF Import] Loaded submodule '{submod_name}'")
|
||||
|
||||
logger.info(f"[GGUF Import] Direct Load success: {loaded}")
|
||||
return package
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[GGUF Import] Direct Load failed: {e}", exc_info=True)
|
||||
return None
|
||||
|
||||
|
||||
def get_gguf_modules() -> Tuple[Any, Any, Any]:
|
||||
"""Get ComfyUI-GGUF modules (loader, ops, nodes).
|
||||
|
||||
Returns:
|
||||
Tuple of (loader_module, ops_module, nodes_module)
|
||||
|
||||
Raises:
|
||||
RuntimeError: If ComfyUI-GGUF cannot be found or loaded.
|
||||
"""
|
||||
logger.debug("[GGUF Import] Starting module search...")
|
||||
|
||||
# Try to find already loaded module first
|
||||
gguf_module = _find_gguf_module()
|
||||
|
||||
if gguf_module is None:
|
||||
logger.info("[GGUF Import] Not found in sys.modules, trying direct load...")
|
||||
gguf_module = _load_gguf_modules_directly()
|
||||
|
||||
if gguf_module is None:
|
||||
raise RuntimeError(
|
||||
"ComfyUI-GGUF is not installed. "
|
||||
"Please install from https://github.com/city96/ComfyUI-GGUF"
|
||||
)
|
||||
|
||||
# Extract submodules
|
||||
loader = getattr(gguf_module, "loader", None)
|
||||
ops = getattr(gguf_module, "ops", None)
|
||||
nodes = getattr(gguf_module, "nodes", None)
|
||||
|
||||
if loader is None or ops is None or nodes is None:
|
||||
missing = [
|
||||
name
|
||||
for name, mod in [("loader", loader), ("ops", ops), ("nodes", nodes)]
|
||||
if mod is None
|
||||
]
|
||||
raise RuntimeError(f"ComfyUI-GGUF missing submodules: {missing}")
|
||||
|
||||
logger.debug("[GGUF Import] All modules loaded successfully")
|
||||
return loader, ops, nodes
|
||||
|
||||
|
||||
def get_gguf_sd_loader():
|
||||
"""Get the gguf_sd_loader function from ComfyUI-GGUF."""
|
||||
loader, _, _ = get_gguf_modules()
|
||||
return getattr(loader, "gguf_sd_loader")
|
||||
|
||||
|
||||
def get_ggml_ops():
|
||||
"""Get the GGMLOps class from ComfyUI-GGUF."""
|
||||
_, ops, _ = get_gguf_modules()
|
||||
return getattr(ops, "GGMLOps")
|
||||
|
||||
|
||||
def get_gguf_model_patcher():
|
||||
"""Get the GGUFModelPatcher class from ComfyUI-GGUF."""
|
||||
_, _, nodes = get_gguf_modules()
|
||||
return getattr(nodes, "GGUFModelPatcher")
|
||||
@@ -56,6 +56,9 @@ class LoraCyclerLM:
|
||||
clip_strength = float(cycler_config.get("clip_strength", 1.0))
|
||||
sort_by = "filename"
|
||||
|
||||
# Include "no lora" option
|
||||
include_no_lora = cycler_config.get("include_no_lora", False)
|
||||
|
||||
# Dual-index mechanism for batch queue synchronization
|
||||
execution_index = cycler_config.get("execution_index") # Can be None
|
||||
# next_index_from_config = cycler_config.get("next_index") # Not used on backend
|
||||
@@ -71,7 +74,10 @@ class LoraCyclerLM:
|
||||
|
||||
total_count = len(lora_list)
|
||||
|
||||
if total_count == 0:
|
||||
# Calculate effective total count (includes no lora option if enabled)
|
||||
effective_total_count = total_count + 1 if include_no_lora else total_count
|
||||
|
||||
if total_count == 0 and not include_no_lora:
|
||||
logger.warning("[LoraCyclerLM] No LoRAs available in pool")
|
||||
return {
|
||||
"result": ([],),
|
||||
@@ -93,42 +99,66 @@ class LoraCyclerLM:
|
||||
else:
|
||||
actual_index = current_index
|
||||
|
||||
# Clamp index to valid range (1-based)
|
||||
clamped_index = max(1, min(actual_index, total_count))
|
||||
# Clamp index to valid range (1-based, includes no lora if enabled)
|
||||
clamped_index = max(1, min(actual_index, effective_total_count))
|
||||
|
||||
# Get LoRA at current index (convert to 0-based for list access)
|
||||
current_lora = lora_list[clamped_index - 1]
|
||||
# Check if current index is the "no lora" option (last position when include_no_lora is True)
|
||||
is_no_lora = include_no_lora and clamped_index == effective_total_count
|
||||
|
||||
# Build LORA_STACK with single LoRA
|
||||
lora_path, _ = get_lora_info(current_lora["file_name"])
|
||||
if not lora_path:
|
||||
logger.warning(
|
||||
f"[LoraCyclerLM] Could not find path for LoRA: {current_lora['file_name']}"
|
||||
)
|
||||
if is_no_lora:
|
||||
# "No LoRA" option - return empty stack
|
||||
lora_stack = []
|
||||
current_lora_name = "No LoRA"
|
||||
current_lora_filename = "No LoRA"
|
||||
else:
|
||||
# Normalize path separators
|
||||
lora_path = lora_path.replace("/", os.sep)
|
||||
lora_stack = [(lora_path, model_strength, clip_strength)]
|
||||
# Get LoRA at current index (convert to 0-based for list access)
|
||||
current_lora = lora_list[clamped_index - 1]
|
||||
current_lora_name = current_lora["file_name"]
|
||||
current_lora_filename = current_lora["file_name"]
|
||||
|
||||
# Build LORA_STACK with single LoRA
|
||||
if current_lora["file_name"] == "None":
|
||||
lora_path = None
|
||||
else:
|
||||
lora_path, _ = get_lora_info(current_lora["file_name"])
|
||||
|
||||
if not lora_path:
|
||||
if current_lora["file_name"] != "None":
|
||||
logger.warning(
|
||||
f"[LoraCyclerLM] Could not find path for LoRA: {current_lora['file_name']}"
|
||||
)
|
||||
lora_stack = []
|
||||
else:
|
||||
# Normalize path separators
|
||||
lora_path = lora_path.replace("/", os.sep)
|
||||
lora_stack = [(lora_path, model_strength, clip_strength)]
|
||||
|
||||
# Calculate next index (wrap to 1 if at end)
|
||||
next_index = clamped_index + 1
|
||||
if next_index > total_count:
|
||||
if next_index > effective_total_count:
|
||||
next_index = 1
|
||||
|
||||
# Get next LoRA for UI display (what will be used next generation)
|
||||
next_lora = lora_list[next_index - 1]
|
||||
next_display_name = next_lora["file_name"]
|
||||
is_next_no_lora = include_no_lora and next_index == effective_total_count
|
||||
if is_next_no_lora:
|
||||
next_display_name = "No LoRA"
|
||||
next_lora_filename = "No LoRA"
|
||||
else:
|
||||
next_lora = lora_list[next_index - 1]
|
||||
next_display_name = next_lora["file_name"]
|
||||
next_lora_filename = next_lora["file_name"]
|
||||
|
||||
return {
|
||||
"result": (lora_stack,),
|
||||
"ui": {
|
||||
"current_index": [clamped_index],
|
||||
"next_index": [next_index],
|
||||
"total_count": [total_count],
|
||||
"current_lora_name": [current_lora["file_name"]],
|
||||
"current_lora_filename": [current_lora["file_name"]],
|
||||
"total_count": [
|
||||
total_count
|
||||
], # Return actual LoRA count, not effective_total_count
|
||||
"current_lora_name": [current_lora_name],
|
||||
"current_lora_filename": [current_lora_filename],
|
||||
"next_lora_name": [next_display_name],
|
||||
"next_lora_filename": [next_lora["file_name"]],
|
||||
"next_lora_filename": [next_lora_filename],
|
||||
},
|
||||
}
|
||||
|
||||
@@ -82,6 +82,7 @@ class LoraPoolLM:
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"favoritesOnly": False,
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
"namePatterns": {"include": [], "exclude": [], "useRegex": False},
|
||||
},
|
||||
"preview": {"matchCount": 0, "lastUpdated": 0},
|
||||
}
|
||||
|
||||
@@ -7,10 +7,8 @@ and tracks the last used combination for reuse.
|
||||
"""
|
||||
|
||||
import logging
|
||||
import random
|
||||
import os
|
||||
from ..utils.utils import get_lora_info
|
||||
from .utils import extract_lora_name
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@@ -1,8 +1,7 @@
|
||||
import logging
|
||||
import os
|
||||
from typing import List, Tuple
|
||||
import torch
|
||||
import comfy.sd
|
||||
import comfy.sd # type: ignore
|
||||
from ..utils.utils import get_checkpoint_info_absolute, _format_model_name_for_comfyui
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -16,7 +15,7 @@ class UNETLoaderLM:
|
||||
Supports both regular diffusion models and GGUF format models.
|
||||
"""
|
||||
|
||||
NAME = "UNETLoaderLM"
|
||||
NAME = "Unet Loader (LoraManager)"
|
||||
CATEGORY = "Lora Manager/loaders"
|
||||
|
||||
@classmethod
|
||||
@@ -61,7 +60,7 @@ class UNETLoaderLM:
|
||||
if item.get("sub_type") == "diffusion_model":
|
||||
file_path = item.get("file_path", "")
|
||||
if file_path:
|
||||
# Format as ComfyUI-style: "folder/model_name.ext"
|
||||
# Format using relative path with OS-native separator
|
||||
formatted_name = _format_model_name_for_comfyui(
|
||||
file_path, model_roots
|
||||
)
|
||||
@@ -95,12 +94,14 @@ class UNETLoaderLM:
|
||||
"""Load a diffusion model by name, supporting extra folder paths
|
||||
|
||||
Args:
|
||||
unet_name: The name of the diffusion model to load (format: "folder/model_name.ext")
|
||||
unet_name: The name of the diffusion model to load (relative path with extension)
|
||||
weight_dtype: The dtype to use for model weights
|
||||
|
||||
Returns:
|
||||
Tuple of (MODEL,)
|
||||
"""
|
||||
import torch
|
||||
|
||||
# Get absolute path from cache using ComfyUI-style name
|
||||
unet_path, metadata = get_checkpoint_info_absolute(unet_name)
|
||||
|
||||
@@ -143,18 +144,17 @@ class UNETLoaderLM:
|
||||
Returns:
|
||||
Tuple of (MODEL,)
|
||||
"""
|
||||
import torch
|
||||
from .gguf_import_helper import get_gguf_modules
|
||||
|
||||
# Get ComfyUI-GGUF modules using helper (handles various import scenarios)
|
||||
try:
|
||||
# Try to import ComfyUI-GGUF modules
|
||||
from custom_nodes.ComfyUI_GGUF.loader import gguf_sd_loader
|
||||
from custom_nodes.ComfyUI_GGUF.ops import GGMLOps
|
||||
from custom_nodes.ComfyUI_GGUF.nodes import GGUFModelPatcher
|
||||
except ImportError:
|
||||
raise RuntimeError(
|
||||
f"Cannot load GGUF model '{unet_name}'. "
|
||||
"ComfyUI-GGUF is not installed. "
|
||||
"Please install ComfyUI-GGUF from https://github.com/city96/ComfyUI-GGUF "
|
||||
"to load GGUF format models."
|
||||
)
|
||||
loader_module, ops_module, nodes_module = get_gguf_modules()
|
||||
gguf_sd_loader = getattr(loader_module, "gguf_sd_loader")
|
||||
GGMLOps = getattr(ops_module, "GGMLOps")
|
||||
GGUFModelPatcher = getattr(nodes_module, "GGUFModelPatcher")
|
||||
except RuntimeError as e:
|
||||
raise RuntimeError(f"Cannot load GGUF model '{unet_name}'. {str(e)}")
|
||||
|
||||
logger.info(f"Loading GGUF diffusion model from: {unet_path}")
|
||||
|
||||
|
||||
@@ -7,6 +7,7 @@ from .parsers import (
|
||||
MetaFormatParser,
|
||||
AutomaticMetadataParser,
|
||||
CivitaiApiMetadataParser,
|
||||
SuiImageParamsParser,
|
||||
)
|
||||
from .base import RecipeMetadataParser
|
||||
|
||||
@@ -55,6 +56,13 @@ class RecipeParserFactory:
|
||||
# If JSON parsing fails, move on to other parsers
|
||||
pass
|
||||
|
||||
# Try SuiImageParamsParser for SuiImage metadata format
|
||||
try:
|
||||
if SuiImageParamsParser().is_metadata_matching(metadata_str):
|
||||
return SuiImageParamsParser()
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
# Check other parsers that expect string input
|
||||
if RecipeFormatParser().is_metadata_matching(metadata_str):
|
||||
return RecipeFormatParser()
|
||||
|
||||
@@ -5,6 +5,7 @@ from .comfy import ComfyMetadataParser
|
||||
from .meta_format import MetaFormatParser
|
||||
from .automatic import AutomaticMetadataParser
|
||||
from .civitai_image import CivitaiApiMetadataParser
|
||||
from .sui_image_params import SuiImageParamsParser
|
||||
|
||||
__all__ = [
|
||||
'RecipeFormatParser',
|
||||
@@ -12,4 +13,5 @@ __all__ = [
|
||||
'MetaFormatParser',
|
||||
'AutomaticMetadataParser',
|
||||
'CivitaiApiMetadataParser',
|
||||
'SuiImageParamsParser',
|
||||
]
|
||||
|
||||
188
py/recipes/parsers/sui_image_params.py
Normal file
188
py/recipes/parsers/sui_image_params.py
Normal file
@@ -0,0 +1,188 @@
|
||||
"""Parser for SuiImage (Stable Diffusion WebUI) metadata format."""
|
||||
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any, Optional, List
|
||||
from ..base import RecipeMetadataParser
|
||||
from ...services.metadata_service import get_default_metadata_provider
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class SuiImageParamsParser(RecipeMetadataParser):
|
||||
"""Parser for SuiImage metadata JSON format.
|
||||
|
||||
This format is used by some Stable Diffusion WebUI variants.
|
||||
Structure:
|
||||
{
|
||||
"sui_image_params": {
|
||||
"prompt": "...",
|
||||
"negativeprompt": "...",
|
||||
"model": "...",
|
||||
"seed": ...,
|
||||
"steps": ...,
|
||||
...
|
||||
},
|
||||
"sui_models": [
|
||||
{"name": "...", "param": "model", "hash": "..."},
|
||||
...
|
||||
],
|
||||
"sui_extra_data": {...}
|
||||
}
|
||||
"""
|
||||
|
||||
def is_metadata_matching(self, user_comment: str) -> bool:
|
||||
"""Check if the user comment matches the SuiImage metadata format"""
|
||||
try:
|
||||
data = json.loads(user_comment)
|
||||
return isinstance(data, dict) and 'sui_image_params' in data
|
||||
except (json.JSONDecodeError, TypeError):
|
||||
return False
|
||||
|
||||
async def parse_metadata(self, user_comment: str, recipe_scanner=None, civitai_client=None) -> Dict[str, Any]:
|
||||
"""Parse metadata from SuiImage metadata format"""
|
||||
try:
|
||||
metadata_provider = await get_default_metadata_provider()
|
||||
|
||||
data = json.loads(user_comment)
|
||||
params = data.get('sui_image_params', {})
|
||||
models = data.get('sui_models', [])
|
||||
|
||||
# Extract prompt and negative prompt
|
||||
prompt = params.get('prompt', '')
|
||||
negative_prompt = params.get('negativeprompt', '') or params.get('negative_prompt', '')
|
||||
|
||||
# Extract generation parameters
|
||||
gen_params = {}
|
||||
if prompt:
|
||||
gen_params['prompt'] = prompt
|
||||
if negative_prompt:
|
||||
gen_params['negative_prompt'] = negative_prompt
|
||||
|
||||
# Map standard parameters
|
||||
param_mapping = {
|
||||
'steps': 'steps',
|
||||
'seed': 'seed',
|
||||
'cfgscale': 'cfg_scale',
|
||||
'cfg_scale': 'cfg_scale',
|
||||
'width': 'width',
|
||||
'height': 'height',
|
||||
'sampler': 'sampler',
|
||||
'scheduler': 'scheduler',
|
||||
'model': 'model',
|
||||
'vae': 'vae',
|
||||
}
|
||||
|
||||
for src_key, dest_key in param_mapping.items():
|
||||
if src_key in params and params[src_key] is not None:
|
||||
gen_params[dest_key] = params[src_key]
|
||||
|
||||
# Add size info if available
|
||||
if 'width' in gen_params and 'height' in gen_params:
|
||||
gen_params['size'] = f"{gen_params['width']}x{gen_params['height']}"
|
||||
|
||||
# Process models - extract checkpoint and loras
|
||||
loras: List[Dict[str, Any]] = []
|
||||
checkpoint: Optional[Dict[str, Any]] = None
|
||||
|
||||
for model in models:
|
||||
model_name = model.get('name', '')
|
||||
param_type = model.get('param', '')
|
||||
model_hash = model.get('hash', '')
|
||||
|
||||
# Remove .safetensors extension for cleaner name
|
||||
clean_name = model_name.replace('.safetensors', '') if model_name else ''
|
||||
|
||||
# Check if this is a LoRA by looking at the name or param type
|
||||
is_lora = 'lora' in model_name.lower() or param_type.lower().startswith('lora')
|
||||
|
||||
if is_lora:
|
||||
lora_entry = {
|
||||
'id': 0,
|
||||
'modelId': 0,
|
||||
'name': clean_name,
|
||||
'version': '',
|
||||
'type': 'lora',
|
||||
'weight': 1.0,
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': model_name,
|
||||
'hash': model_hash.replace('0x', '') if model_hash.startswith('0x') else model_hash,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
# Try to get additional info from metadata provider
|
||||
if metadata_provider and model_hash:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(
|
||||
model_hash.replace('0x', '') if model_hash.startswith('0x') else model_hash
|
||||
)
|
||||
if civitai_info:
|
||||
lora_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry, civitai_info, recipe_scanner
|
||||
)
|
||||
except Exception as e:
|
||||
logger.debug(f"Error fetching info for LoRA {clean_name}: {e}")
|
||||
|
||||
if lora_entry:
|
||||
loras.append(lora_entry)
|
||||
elif param_type == 'model' or 'lora' not in model_name.lower():
|
||||
# This is likely a checkpoint
|
||||
checkpoint_entry = {
|
||||
'id': 0,
|
||||
'modelId': 0,
|
||||
'name': clean_name,
|
||||
'version': '',
|
||||
'type': 'checkpoint',
|
||||
'hash': model_hash.replace('0x', '') if model_hash.startswith('0x') else model_hash,
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': model_name,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
}
|
||||
|
||||
# Try to get additional info from metadata provider
|
||||
if metadata_provider and model_hash:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(
|
||||
model_hash.replace('0x', '') if model_hash.startswith('0x') else model_hash
|
||||
)
|
||||
if civitai_info:
|
||||
checkpoint_entry = await self.populate_checkpoint_from_civitai(
|
||||
checkpoint_entry, civitai_info
|
||||
)
|
||||
except Exception as e:
|
||||
logger.debug(f"Error fetching info for checkpoint {clean_name}: {e}")
|
||||
|
||||
checkpoint = checkpoint_entry
|
||||
|
||||
# Determine base model from loras or checkpoint
|
||||
base_model = None
|
||||
if loras:
|
||||
base_models = [lora.get('baseModel') for lora in loras if lora.get('baseModel')]
|
||||
if base_models:
|
||||
from collections import Counter
|
||||
base_model_counts = Counter(base_models)
|
||||
base_model = base_model_counts.most_common(1)[0][0]
|
||||
elif checkpoint and checkpoint.get('baseModel'):
|
||||
base_model = checkpoint['baseModel']
|
||||
|
||||
return {
|
||||
'base_model': base_model,
|
||||
'loras': loras,
|
||||
'checkpoint': checkpoint,
|
||||
'gen_params': gen_params,
|
||||
'from_sui_image_params': True
|
||||
}
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error parsing SuiImage metadata: {e}", exc_info=True)
|
||||
return {"error": str(e), "loras": []}
|
||||
@@ -309,6 +309,13 @@ class ModelListingHandler:
|
||||
else:
|
||||
allow_selling_generated_content = None # None means no filter applied
|
||||
|
||||
# Name pattern filters for LoRA Pool
|
||||
name_pattern_include = request.query.getall("name_pattern_include", [])
|
||||
name_pattern_exclude = request.query.getall("name_pattern_exclude", [])
|
||||
name_pattern_use_regex = (
|
||||
request.query.get("name_pattern_use_regex", "false").lower() == "true"
|
||||
)
|
||||
|
||||
return {
|
||||
"page": page,
|
||||
"page_size": page_size,
|
||||
@@ -328,6 +335,9 @@ class ModelListingHandler:
|
||||
"credit_required": credit_required,
|
||||
"allow_selling_generated_content": allow_selling_generated_content,
|
||||
"model_types": model_types,
|
||||
"name_pattern_include": name_pattern_include,
|
||||
"name_pattern_exclude": name_pattern_exclude,
|
||||
"name_pattern_use_regex": name_pattern_use_regex,
|
||||
**self._parse_specific_params(request),
|
||||
}
|
||||
|
||||
|
||||
@@ -58,6 +58,7 @@ class CacheEntryValidator:
|
||||
'preview_nsfw_level': (0, False),
|
||||
'notes': ('', False),
|
||||
'usage_tips': ('', False),
|
||||
'hash_status': ('completed', False),
|
||||
}
|
||||
|
||||
@classmethod
|
||||
@@ -90,13 +91,31 @@ class CacheEntryValidator:
|
||||
|
||||
errors: List[str] = []
|
||||
repaired = False
|
||||
|
||||
# If auto_repair is on, we work on a copy. If not, we still need a safe way to check fields.
|
||||
working_entry = dict(entry) if auto_repair else entry
|
||||
|
||||
# Determine effective hash_status for validation logic
|
||||
hash_status = entry.get('hash_status')
|
||||
if hash_status is None:
|
||||
if auto_repair:
|
||||
working_entry['hash_status'] = 'completed'
|
||||
repaired = True
|
||||
hash_status = 'completed'
|
||||
|
||||
for field_name, (default_value, is_required) in cls.CORE_FIELDS.items():
|
||||
value = working_entry.get(field_name)
|
||||
# Get current value from the original entry to avoid side effects during validation
|
||||
value = entry.get(field_name)
|
||||
|
||||
# Check if field is missing or None
|
||||
if value is None:
|
||||
# Special case: sha256 can be None/empty if hash_status is pending
|
||||
if field_name == 'sha256' and hash_status == 'pending':
|
||||
if auto_repair:
|
||||
working_entry[field_name] = ''
|
||||
repaired = True
|
||||
continue
|
||||
|
||||
if is_required:
|
||||
errors.append(f"Required field '{field_name}' is missing or None")
|
||||
if auto_repair:
|
||||
@@ -107,6 +126,10 @@ class CacheEntryValidator:
|
||||
# Validate field type and value
|
||||
field_error = cls._validate_field(field_name, value, default_value)
|
||||
if field_error:
|
||||
# Special case: allow empty string for sha256 if pending
|
||||
if field_name == 'sha256' and hash_status == 'pending' and value == '':
|
||||
continue
|
||||
|
||||
errors.append(field_error)
|
||||
if auto_repair:
|
||||
working_entry[field_name] = cls._get_default_copy(default_value)
|
||||
@@ -127,7 +150,7 @@ class CacheEntryValidator:
|
||||
# Special validation: sha256 must not be empty for required field
|
||||
# BUT allow empty sha256 when hash_status is pending (lazy hash calculation)
|
||||
sha256 = working_entry.get('sha256', '')
|
||||
hash_status = working_entry.get('hash_status', 'completed')
|
||||
# Use the effective hash_status we determined earlier
|
||||
if not sha256 or (isinstance(sha256, str) and not sha256.strip()):
|
||||
# Allow empty sha256 for lazy hash calculation (checkpoints)
|
||||
if hash_status != 'pending':
|
||||
@@ -144,8 +167,13 @@ class CacheEntryValidator:
|
||||
if isinstance(sha256, str):
|
||||
normalized_sha = sha256.lower().strip()
|
||||
if normalized_sha != sha256:
|
||||
working_entry['sha256'] = normalized_sha
|
||||
repaired = True
|
||||
if auto_repair:
|
||||
working_entry['sha256'] = normalized_sha
|
||||
repaired = True
|
||||
else:
|
||||
# If not auto-repairing, we don't consider case difference as a "critical error"
|
||||
# that invalidates the entry, but we also don't mark it repaired.
|
||||
pass
|
||||
|
||||
# Determine if entry is valid
|
||||
# Entry is valid if no critical required field errors remain after repair
|
||||
|
||||
@@ -490,14 +490,33 @@ class CivitaiClient:
|
||||
"""
|
||||
try:
|
||||
url = f"{self.base_url}/images?imageId={image_id}&nsfw=X"
|
||||
requested_id = int(image_id)
|
||||
|
||||
logger.debug(f"Fetching image info for ID: {image_id}")
|
||||
success, result = await self._make_request("GET", url, use_auth=True)
|
||||
|
||||
if success:
|
||||
if result and "items" in result and len(result["items"]) > 0:
|
||||
logger.debug(f"Successfully fetched image info for ID: {image_id}")
|
||||
return result["items"][0]
|
||||
if result and "items" in result and isinstance(result["items"], list):
|
||||
items = result["items"]
|
||||
|
||||
# First, try to find the item with matching ID
|
||||
for item in items:
|
||||
if isinstance(item, dict) and item.get("id") == requested_id:
|
||||
logger.debug(f"Successfully fetched image info for ID: {image_id}")
|
||||
return item
|
||||
|
||||
# No matching ID found - log warning with details about returned items
|
||||
returned_ids = [
|
||||
item.get("id") for item in items
|
||||
if isinstance(item, dict) and "id" in item
|
||||
]
|
||||
logger.warning(
|
||||
f"CivitAI API returned no matching image for requested ID {image_id}. "
|
||||
f"Returned {len(items)} item(s) with IDs: {returned_ids}. "
|
||||
f"This may indicate the image was deleted, hidden, or there is a database lag."
|
||||
)
|
||||
return None
|
||||
|
||||
logger.warning(f"No image found with ID: {image_id}")
|
||||
return None
|
||||
|
||||
@@ -505,6 +524,10 @@ class CivitaiClient:
|
||||
return None
|
||||
except RateLimitError:
|
||||
raise
|
||||
except ValueError as e:
|
||||
error_msg = f"Invalid image ID format: {image_id}"
|
||||
logger.error(error_msg)
|
||||
return None
|
||||
except Exception as e:
|
||||
error_msg = f"Error fetching image info: {e}"
|
||||
logger.error(error_msg)
|
||||
|
||||
@@ -16,10 +16,9 @@ from ..utils.constants import (
|
||||
VALID_LORA_TYPES,
|
||||
)
|
||||
from ..utils.civitai_utils import rewrite_preview_url
|
||||
from ..utils.preview_selection import select_preview_media
|
||||
from ..utils.preview_selection import resolve_mature_threshold, select_preview_media
|
||||
from ..utils.utils import sanitize_folder_name
|
||||
from ..utils.exif_utils import ExifUtils
|
||||
from ..utils.file_utils import calculate_sha256
|
||||
from ..utils.metadata_manager import MetadataManager
|
||||
from .service_registry import ServiceRegistry
|
||||
from .settings_manager import get_settings_manager
|
||||
@@ -847,9 +846,13 @@ class DownloadManager:
|
||||
blur_mature_content = bool(
|
||||
settings_manager.get("blur_mature_content", True)
|
||||
)
|
||||
mature_threshold = resolve_mature_threshold(
|
||||
{"mature_blur_level": settings_manager.get("mature_blur_level", "R")}
|
||||
)
|
||||
selected_image, nsfw_level = select_preview_media(
|
||||
images,
|
||||
blur_mature_content=blur_mature_content,
|
||||
mature_threshold=mature_threshold,
|
||||
)
|
||||
|
||||
preview_url = selected_image.get("url") if selected_image else None
|
||||
@@ -965,11 +968,12 @@ class DownloadManager:
|
||||
for download_url in download_urls:
|
||||
use_auth = download_url.startswith("https://civitai.com/api/download/")
|
||||
download_kwargs = {
|
||||
"progress_callback": lambda progress,
|
||||
snapshot=None: self._handle_download_progress(
|
||||
progress,
|
||||
progress_callback,
|
||||
snapshot,
|
||||
"progress_callback": lambda progress, snapshot=None: (
|
||||
self._handle_download_progress(
|
||||
progress,
|
||||
progress_callback,
|
||||
snapshot,
|
||||
)
|
||||
),
|
||||
"use_auth": use_auth, # Only use authentication for Civitai downloads
|
||||
}
|
||||
@@ -1238,7 +1242,8 @@ class DownloadManager:
|
||||
entry.file_name = os.path.splitext(os.path.basename(file_path))[0]
|
||||
# Update size to actual downloaded file size
|
||||
entry.size = os.path.getsize(file_path)
|
||||
entry.sha256 = await calculate_sha256(file_path)
|
||||
# Use SHA256 from API metadata (already set in from_civitai_info)
|
||||
# Do not recalculate to avoid blocking during ComfyUI execution
|
||||
entries.append(entry)
|
||||
|
||||
return entries
|
||||
|
||||
@@ -44,7 +44,9 @@ class DownloadStreamControl:
|
||||
self._event.set()
|
||||
self._reconnect_requested = False
|
||||
self.last_progress_timestamp: Optional[float] = None
|
||||
self.stall_timeout: float = float(stall_timeout) if stall_timeout is not None else 120.0
|
||||
self.stall_timeout: float = (
|
||||
float(stall_timeout) if stall_timeout is not None else 120.0
|
||||
)
|
||||
|
||||
def is_set(self) -> bool:
|
||||
return self._event.is_set()
|
||||
@@ -85,7 +87,9 @@ class DownloadStreamControl:
|
||||
self.last_progress_timestamp = timestamp or datetime.now().timestamp()
|
||||
self._reconnect_requested = False
|
||||
|
||||
def time_since_last_progress(self, *, now: Optional[float] = None) -> Optional[float]:
|
||||
def time_since_last_progress(
|
||||
self, *, now: Optional[float] = None
|
||||
) -> Optional[float]:
|
||||
if self.last_progress_timestamp is None:
|
||||
return None
|
||||
reference = now if now is not None else datetime.now().timestamp()
|
||||
@@ -120,7 +124,7 @@ class Downloader:
|
||||
def __init__(self):
|
||||
"""Initialize the downloader with optimal settings"""
|
||||
# Check if already initialized for singleton pattern
|
||||
if hasattr(self, '_initialized'):
|
||||
if hasattr(self, "_initialized"):
|
||||
return
|
||||
self._initialized = True
|
||||
|
||||
@@ -131,7 +135,9 @@ class Downloader:
|
||||
self._session_lock = asyncio.Lock()
|
||||
|
||||
# Configuration
|
||||
self.chunk_size = 4 * 1024 * 1024 # 4MB chunks for better throughput
|
||||
self.chunk_size = (
|
||||
16 * 1024 * 1024
|
||||
) # 16MB chunks to balance I/O reduction and memory usage
|
||||
self.max_retries = 5
|
||||
self.base_delay = 2.0 # Base delay for exponential backoff
|
||||
self.session_timeout = 300 # 5 minutes
|
||||
@@ -139,10 +145,10 @@ class Downloader:
|
||||
|
||||
# Default headers
|
||||
self.default_headers = {
|
||||
'User-Agent': 'ComfyUI-LoRA-Manager/1.0',
|
||||
"User-Agent": "ComfyUI-LoRA-Manager/1.0",
|
||||
# Explicitly request uncompressed payloads so aiohttp doesn't need optional
|
||||
# decoders (e.g. zstandard) that may be missing in runtime environments.
|
||||
'Accept-Encoding': 'identity',
|
||||
"Accept-Encoding": "identity",
|
||||
}
|
||||
|
||||
@property
|
||||
@@ -158,7 +164,7 @@ class Downloader:
|
||||
@property
|
||||
def proxy_url(self) -> Optional[str]:
|
||||
"""Get the current proxy URL (initialize if needed)"""
|
||||
if not hasattr(self, '_proxy_url'):
|
||||
if not hasattr(self, "_proxy_url"):
|
||||
self._proxy_url = None
|
||||
return self._proxy_url
|
||||
|
||||
@@ -169,14 +175,14 @@ class Downloader:
|
||||
|
||||
try:
|
||||
settings_manager = get_settings_manager()
|
||||
settings_timeout = settings_manager.get('download_stall_timeout_seconds')
|
||||
settings_timeout = settings_manager.get("download_stall_timeout_seconds")
|
||||
except Exception as exc: # pragma: no cover - defensive guard
|
||||
logger.debug("Failed to read stall timeout from settings: %s", exc)
|
||||
|
||||
raw_value = (
|
||||
settings_timeout
|
||||
if settings_timeout not in (None, "")
|
||||
else os.environ.get('COMFYUI_DOWNLOAD_STALL_TIMEOUT')
|
||||
else os.environ.get("COMFYUI_DOWNLOAD_STALL_TIMEOUT")
|
||||
)
|
||||
|
||||
try:
|
||||
@@ -191,11 +197,13 @@ class Downloader:
|
||||
if self._session is None:
|
||||
return True
|
||||
|
||||
if not hasattr(self, '_session_created_at') or self._session_created_at is None:
|
||||
if not hasattr(self, "_session_created_at") or self._session_created_at is None:
|
||||
return True
|
||||
|
||||
# Refresh if session is older than timeout
|
||||
if (datetime.now() - self._session_created_at).total_seconds() > self.session_timeout:
|
||||
if (
|
||||
datetime.now() - self._session_created_at
|
||||
).total_seconds() > self.session_timeout:
|
||||
return True
|
||||
|
||||
return False
|
||||
@@ -209,7 +217,7 @@ class Downloader:
|
||||
if self._session is not None:
|
||||
try:
|
||||
await self._session.close()
|
||||
except Exception as e: # pragma: no cover
|
||||
except Exception as e: # pragma: no cover
|
||||
logger.warning(f"Error closing previous session: {e}")
|
||||
finally:
|
||||
self._session = None
|
||||
@@ -217,12 +225,12 @@ class Downloader:
|
||||
# Check for app-level proxy settings
|
||||
proxy_url = None
|
||||
settings_manager = get_settings_manager()
|
||||
if settings_manager.get('proxy_enabled', False):
|
||||
proxy_host = settings_manager.get('proxy_host', '').strip()
|
||||
proxy_port = settings_manager.get('proxy_port', '').strip()
|
||||
proxy_type = settings_manager.get('proxy_type', 'http').lower()
|
||||
proxy_username = settings_manager.get('proxy_username', '').strip()
|
||||
proxy_password = settings_manager.get('proxy_password', '').strip()
|
||||
if settings_manager.get("proxy_enabled", False):
|
||||
proxy_host = settings_manager.get("proxy_host", "").strip()
|
||||
proxy_port = settings_manager.get("proxy_port", "").strip()
|
||||
proxy_type = settings_manager.get("proxy_type", "http").lower()
|
||||
proxy_username = settings_manager.get("proxy_username", "").strip()
|
||||
proxy_password = settings_manager.get("proxy_password", "").strip()
|
||||
|
||||
if proxy_host and proxy_port:
|
||||
# Build proxy URL
|
||||
@@ -231,37 +239,46 @@ class Downloader:
|
||||
else:
|
||||
proxy_url = f"{proxy_type}://{proxy_host}:{proxy_port}"
|
||||
|
||||
logger.debug(f"Using app-level proxy: {proxy_type}://{proxy_host}:{proxy_port}")
|
||||
logger.debug(
|
||||
f"Using app-level proxy: {proxy_type}://{proxy_host}:{proxy_port}"
|
||||
)
|
||||
logger.debug("Proxy mode: app-level proxy is active.")
|
||||
else:
|
||||
logger.debug("Proxy mode: system-level proxy (trust_env) will be used if configured in environment.")
|
||||
logger.debug(
|
||||
"Proxy mode: system-level proxy (trust_env) will be used if configured in environment."
|
||||
)
|
||||
# Optimize TCP connection parameters
|
||||
connector = aiohttp.TCPConnector(
|
||||
ssl=True,
|
||||
limit=8, # Concurrent connections
|
||||
ttl_dns_cache=300, # DNS cache timeout
|
||||
force_close=False, # Keep connections for reuse
|
||||
enable_cleanup_closed=True
|
||||
enable_cleanup_closed=True,
|
||||
)
|
||||
|
||||
# Configure timeout parameters
|
||||
timeout = aiohttp.ClientTimeout(
|
||||
total=None, # No total timeout for large downloads
|
||||
connect=60, # Connection timeout
|
||||
sock_read=300 # 5 minute socket read timeout
|
||||
sock_read=300, # 5 minute socket read timeout
|
||||
)
|
||||
|
||||
self._session = aiohttp.ClientSession(
|
||||
connector=connector,
|
||||
trust_env=proxy_url is None, # Only use system proxy if no app-level proxy is set
|
||||
timeout=timeout
|
||||
trust_env=proxy_url
|
||||
is None, # Only use system proxy if no app-level proxy is set
|
||||
timeout=timeout,
|
||||
)
|
||||
|
||||
# Store proxy URL for use in requests
|
||||
self._proxy_url = proxy_url
|
||||
self._session_created_at = datetime.now()
|
||||
|
||||
logger.debug("Created new HTTP session with proxy settings. App-level proxy: %s, System-level proxy (trust_env): %s", bool(proxy_url), proxy_url is None)
|
||||
logger.debug(
|
||||
"Created new HTTP session with proxy settings. App-level proxy: %s, System-level proxy (trust_env): %s",
|
||||
bool(proxy_url),
|
||||
proxy_url is None,
|
||||
)
|
||||
|
||||
def _get_auth_headers(self, use_auth: bool = False) -> Dict[str, str]:
|
||||
"""Get headers with optional authentication"""
|
||||
@@ -270,10 +287,10 @@ class Downloader:
|
||||
if use_auth:
|
||||
# Add CivitAI API key if available
|
||||
settings_manager = get_settings_manager()
|
||||
api_key = settings_manager.get('civitai_api_key')
|
||||
api_key = settings_manager.get("civitai_api_key")
|
||||
if api_key:
|
||||
headers['Authorization'] = f'Bearer {api_key}'
|
||||
headers['Content-Type'] = 'application/json'
|
||||
headers["Authorization"] = f"Bearer {api_key}"
|
||||
headers["Content-Type"] = "application/json"
|
||||
|
||||
return headers
|
||||
|
||||
@@ -303,7 +320,7 @@ class Downloader:
|
||||
Tuple[bool, str]: (success, save_path or error message)
|
||||
"""
|
||||
retry_count = 0
|
||||
part_path = save_path + '.part' if allow_resume else save_path
|
||||
part_path = save_path + ".part" if allow_resume else save_path
|
||||
|
||||
# Prepare headers
|
||||
headers = self._get_auth_headers(use_auth)
|
||||
@@ -323,50 +340,71 @@ class Downloader:
|
||||
session = await self.session
|
||||
# Debug log for proxy mode at request time
|
||||
if self.proxy_url:
|
||||
logger.debug(f"[download_file] Using app-level proxy: {self.proxy_url}")
|
||||
logger.debug(
|
||||
f"[download_file] Using app-level proxy: {self.proxy_url}"
|
||||
)
|
||||
else:
|
||||
logger.debug("[download_file] Using system-level proxy (trust_env) if configured.")
|
||||
logger.debug(
|
||||
"[download_file] Using system-level proxy (trust_env) if configured."
|
||||
)
|
||||
|
||||
# Add Range header for resume if we have partial data
|
||||
request_headers = headers.copy()
|
||||
if allow_resume and resume_offset > 0:
|
||||
request_headers['Range'] = f'bytes={resume_offset}-'
|
||||
request_headers["Range"] = f"bytes={resume_offset}-"
|
||||
|
||||
# Disable compression for better chunked downloads
|
||||
request_headers['Accept-Encoding'] = 'identity'
|
||||
request_headers["Accept-Encoding"] = "identity"
|
||||
|
||||
logger.debug(f"Download attempt {retry_count + 1}/{self.max_retries + 1} from: {url}")
|
||||
logger.debug(
|
||||
f"Download attempt {retry_count + 1}/{self.max_retries + 1} from: {url}"
|
||||
)
|
||||
if resume_offset > 0:
|
||||
logger.debug(f"Requesting range from byte {resume_offset}")
|
||||
|
||||
async with session.get(url, headers=request_headers, allow_redirects=True, proxy=self.proxy_url) as response:
|
||||
async with session.get(
|
||||
url,
|
||||
headers=request_headers,
|
||||
allow_redirects=True,
|
||||
proxy=self.proxy_url,
|
||||
) as response:
|
||||
# Handle different response codes
|
||||
if response.status == 200:
|
||||
# Full content response
|
||||
if resume_offset > 0:
|
||||
# Server doesn't support ranges, restart from beginning
|
||||
logger.warning("Server doesn't support range requests, restarting download")
|
||||
logger.warning(
|
||||
"Server doesn't support range requests, restarting download"
|
||||
)
|
||||
resume_offset = 0
|
||||
if os.path.exists(part_path):
|
||||
os.remove(part_path)
|
||||
elif response.status == 206:
|
||||
# Partial content response (resume successful)
|
||||
content_range = response.headers.get('Content-Range')
|
||||
content_range = response.headers.get("Content-Range")
|
||||
if content_range:
|
||||
# Parse total size from Content-Range header (e.g., "bytes 1024-2047/2048")
|
||||
range_parts = content_range.split('/')
|
||||
range_parts = content_range.split("/")
|
||||
if len(range_parts) == 2:
|
||||
total_size = int(range_parts[1])
|
||||
logger.info(f"Successfully resumed download from byte {resume_offset}")
|
||||
logger.info(
|
||||
f"Successfully resumed download from byte {resume_offset}"
|
||||
)
|
||||
elif response.status == 416:
|
||||
# Range not satisfiable - file might be complete or corrupted
|
||||
if allow_resume and os.path.exists(part_path):
|
||||
part_size = os.path.getsize(part_path)
|
||||
logger.warning(f"Range not satisfiable. Part file size: {part_size}")
|
||||
logger.warning(
|
||||
f"Range not satisfiable. Part file size: {part_size}"
|
||||
)
|
||||
# Try to get actual file size
|
||||
head_response = await session.head(url, headers=headers, proxy=self.proxy_url)
|
||||
head_response = await session.head(
|
||||
url, headers=headers, proxy=self.proxy_url
|
||||
)
|
||||
if head_response.status == 200:
|
||||
actual_size = int(head_response.headers.get('content-length', 0))
|
||||
actual_size = int(
|
||||
head_response.headers.get("content-length", 0)
|
||||
)
|
||||
if part_size == actual_size:
|
||||
# File is complete, just rename it
|
||||
if allow_resume:
|
||||
@@ -388,21 +426,36 @@ class Downloader:
|
||||
resume_offset = 0
|
||||
continue
|
||||
elif response.status == 401:
|
||||
logger.warning(f"Unauthorized access to resource: {url} (Status 401)")
|
||||
return False, "Invalid or missing API key, or early access restriction."
|
||||
logger.warning(
|
||||
f"Unauthorized access to resource: {url} (Status 401)"
|
||||
)
|
||||
return (
|
||||
False,
|
||||
"Invalid or missing API key, or early access restriction.",
|
||||
)
|
||||
elif response.status == 403:
|
||||
logger.warning(f"Forbidden access to resource: {url} (Status 403)")
|
||||
return False, "Access forbidden: You don't have permission to download this file."
|
||||
logger.warning(
|
||||
f"Forbidden access to resource: {url} (Status 403)"
|
||||
)
|
||||
return (
|
||||
False,
|
||||
"Access forbidden: You don't have permission to download this file.",
|
||||
)
|
||||
elif response.status == 404:
|
||||
logger.warning(f"Resource not found: {url} (Status 404)")
|
||||
return False, "File not found - the download link may be invalid or expired."
|
||||
return (
|
||||
False,
|
||||
"File not found - the download link may be invalid or expired.",
|
||||
)
|
||||
else:
|
||||
logger.error(f"Download failed for {url} with status {response.status}")
|
||||
logger.error(
|
||||
f"Download failed for {url} with status {response.status}"
|
||||
)
|
||||
return False, f"Download failed with status {response.status}"
|
||||
|
||||
# Get total file size for progress calculation (if not set from Content-Range)
|
||||
if total_size == 0:
|
||||
total_size = int(response.headers.get('content-length', 0))
|
||||
total_size = int(response.headers.get("content-length", 0))
|
||||
if response.status == 206:
|
||||
# For partial content, add the offset to get total file size
|
||||
total_size += resume_offset
|
||||
@@ -417,7 +470,7 @@ class Downloader:
|
||||
|
||||
# Stream download to file with progress updates
|
||||
loop = asyncio.get_running_loop()
|
||||
mode = 'ab' if (allow_resume and resume_offset > 0) else 'wb'
|
||||
mode = "ab" if (allow_resume and resume_offset > 0) else "wb"
|
||||
control = pause_event
|
||||
|
||||
if control is not None:
|
||||
@@ -425,7 +478,9 @@ class Downloader:
|
||||
|
||||
with open(part_path, mode) as f:
|
||||
while True:
|
||||
active_stall_timeout = control.stall_timeout if control else self.stall_timeout
|
||||
active_stall_timeout = (
|
||||
control.stall_timeout if control else self.stall_timeout
|
||||
)
|
||||
|
||||
if control is not None:
|
||||
if control.is_paused():
|
||||
@@ -437,7 +492,9 @@ class Downloader:
|
||||
"Reconnect requested after resume"
|
||||
)
|
||||
elif control.consume_reconnect_request():
|
||||
raise DownloadRestartRequested("Reconnect requested")
|
||||
raise DownloadRestartRequested(
|
||||
"Reconnect requested"
|
||||
)
|
||||
|
||||
try:
|
||||
chunk = await asyncio.wait_for(
|
||||
@@ -466,22 +523,32 @@ class Downloader:
|
||||
control.mark_progress(timestamp=now.timestamp())
|
||||
|
||||
# Limit progress update frequency to reduce overhead
|
||||
time_diff = (now - last_progress_report_time).total_seconds()
|
||||
time_diff = (
|
||||
now - last_progress_report_time
|
||||
).total_seconds()
|
||||
|
||||
if progress_callback and time_diff >= 1.0:
|
||||
progress_samples.append((now, current_size))
|
||||
cutoff = now - timedelta(seconds=5)
|
||||
while progress_samples and progress_samples[0][0] < cutoff:
|
||||
while (
|
||||
progress_samples and progress_samples[0][0] < cutoff
|
||||
):
|
||||
progress_samples.popleft()
|
||||
|
||||
percent = (current_size / total_size) * 100 if total_size else 0.0
|
||||
percent = (
|
||||
(current_size / total_size) * 100
|
||||
if total_size
|
||||
else 0.0
|
||||
)
|
||||
bytes_per_second = 0.0
|
||||
if len(progress_samples) >= 2:
|
||||
first_time, first_bytes = progress_samples[0]
|
||||
last_time, last_bytes = progress_samples[-1]
|
||||
elapsed = (last_time - first_time).total_seconds()
|
||||
if elapsed > 0:
|
||||
bytes_per_second = (last_bytes - first_bytes) / elapsed
|
||||
bytes_per_second = (
|
||||
last_bytes - first_bytes
|
||||
) / elapsed
|
||||
|
||||
progress_snapshot = DownloadProgress(
|
||||
percent_complete=percent,
|
||||
@@ -491,21 +558,23 @@ class Downloader:
|
||||
timestamp=now.timestamp(),
|
||||
)
|
||||
|
||||
await self._dispatch_progress_callback(progress_callback, progress_snapshot)
|
||||
await self._dispatch_progress_callback(
|
||||
progress_callback, progress_snapshot
|
||||
)
|
||||
last_progress_report_time = now
|
||||
|
||||
# Download completed successfully
|
||||
# Verify file size integrity before finalizing
|
||||
final_size = os.path.getsize(part_path) if os.path.exists(part_path) else 0
|
||||
final_size = (
|
||||
os.path.getsize(part_path) if os.path.exists(part_path) else 0
|
||||
)
|
||||
expected_size = total_size if total_size > 0 else None
|
||||
|
||||
integrity_error: Optional[str] = None
|
||||
if final_size <= 0:
|
||||
integrity_error = "Downloaded file is empty"
|
||||
elif expected_size is not None and final_size != expected_size:
|
||||
integrity_error = (
|
||||
f"File size mismatch. Expected: {expected_size}, Got: {final_size}"
|
||||
)
|
||||
integrity_error = f"File size mismatch. Expected: {expected_size}, Got: {final_size}"
|
||||
|
||||
if integrity_error is not None:
|
||||
logger.error(
|
||||
@@ -555,7 +624,9 @@ class Downloader:
|
||||
rename_attempt = 0
|
||||
rename_success = False
|
||||
|
||||
while rename_attempt < max_rename_attempts and not rename_success:
|
||||
while (
|
||||
rename_attempt < max_rename_attempts and not rename_success
|
||||
):
|
||||
try:
|
||||
# If the destination file exists, remove it first (Windows safe)
|
||||
if os.path.exists(save_path):
|
||||
@@ -566,11 +637,18 @@ class Downloader:
|
||||
except PermissionError as e:
|
||||
rename_attempt += 1
|
||||
if rename_attempt < max_rename_attempts:
|
||||
logger.info(f"File still in use, retrying rename in 2 seconds (attempt {rename_attempt}/{max_rename_attempts})")
|
||||
logger.info(
|
||||
f"File still in use, retrying rename in 2 seconds (attempt {rename_attempt}/{max_rename_attempts})"
|
||||
)
|
||||
await asyncio.sleep(2)
|
||||
else:
|
||||
logger.error(f"Failed to rename file after {max_rename_attempts} attempts: {e}")
|
||||
return False, f"Failed to finalize download: {str(e)}"
|
||||
logger.error(
|
||||
f"Failed to rename file after {max_rename_attempts} attempts: {e}"
|
||||
)
|
||||
return (
|
||||
False,
|
||||
f"Failed to finalize download: {str(e)}",
|
||||
)
|
||||
|
||||
final_size = os.path.getsize(save_path)
|
||||
|
||||
@@ -583,8 +661,9 @@ class Downloader:
|
||||
bytes_per_second=0.0,
|
||||
timestamp=datetime.now().timestamp(),
|
||||
)
|
||||
await self._dispatch_progress_callback(progress_callback, final_snapshot)
|
||||
|
||||
await self._dispatch_progress_callback(
|
||||
progress_callback, final_snapshot
|
||||
)
|
||||
|
||||
return True, save_path
|
||||
|
||||
@@ -597,7 +676,9 @@ class Downloader:
|
||||
DownloadRestartRequested,
|
||||
) as e:
|
||||
retry_count += 1
|
||||
logger.warning(f"Network error during download (attempt {retry_count}/{self.max_retries + 1}): {e}")
|
||||
logger.warning(
|
||||
f"Network error during download (attempt {retry_count}/{self.max_retries + 1}): {e}"
|
||||
)
|
||||
|
||||
if retry_count <= self.max_retries:
|
||||
# Calculate delay with exponential backoff
|
||||
@@ -615,7 +696,10 @@ class Downloader:
|
||||
continue
|
||||
else:
|
||||
logger.error(f"Max retries exceeded for download: {e}")
|
||||
return False, f"Network error after {self.max_retries + 1} attempts: {str(e)}"
|
||||
return (
|
||||
False,
|
||||
f"Network error after {self.max_retries + 1} attempts: {str(e)}",
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Unexpected download error: {e}")
|
||||
@@ -645,7 +729,7 @@ class Downloader:
|
||||
url: str,
|
||||
use_auth: bool = False,
|
||||
custom_headers: Optional[Dict[str, str]] = None,
|
||||
return_headers: bool = False
|
||||
return_headers: bool = False,
|
||||
) -> Tuple[bool, Union[bytes, str], Optional[Dict]]:
|
||||
"""
|
||||
Download a file to memory (for small files like preview images)
|
||||
@@ -663,16 +747,22 @@ class Downloader:
|
||||
session = await self.session
|
||||
# Debug log for proxy mode at request time
|
||||
if self.proxy_url:
|
||||
logger.debug(f"[download_to_memory] Using app-level proxy: {self.proxy_url}")
|
||||
logger.debug(
|
||||
f"[download_to_memory] Using app-level proxy: {self.proxy_url}"
|
||||
)
|
||||
else:
|
||||
logger.debug("[download_to_memory] Using system-level proxy (trust_env) if configured.")
|
||||
logger.debug(
|
||||
"[download_to_memory] Using system-level proxy (trust_env) if configured."
|
||||
)
|
||||
|
||||
# Prepare headers
|
||||
headers = self._get_auth_headers(use_auth)
|
||||
if custom_headers:
|
||||
headers.update(custom_headers)
|
||||
|
||||
async with session.get(url, headers=headers, proxy=self.proxy_url) as response:
|
||||
async with session.get(
|
||||
url, headers=headers, proxy=self.proxy_url
|
||||
) as response:
|
||||
if response.status == 200:
|
||||
content = await response.read()
|
||||
if return_headers:
|
||||
@@ -700,7 +790,7 @@ class Downloader:
|
||||
self,
|
||||
url: str,
|
||||
use_auth: bool = False,
|
||||
custom_headers: Optional[Dict[str, str]] = None
|
||||
custom_headers: Optional[Dict[str, str]] = None,
|
||||
) -> Tuple[bool, Union[Dict, str]]:
|
||||
"""
|
||||
Get response headers without downloading the full content
|
||||
@@ -717,16 +807,22 @@ class Downloader:
|
||||
session = await self.session
|
||||
# Debug log for proxy mode at request time
|
||||
if self.proxy_url:
|
||||
logger.debug(f"[get_response_headers] Using app-level proxy: {self.proxy_url}")
|
||||
logger.debug(
|
||||
f"[get_response_headers] Using app-level proxy: {self.proxy_url}"
|
||||
)
|
||||
else:
|
||||
logger.debug("[get_response_headers] Using system-level proxy (trust_env) if configured.")
|
||||
logger.debug(
|
||||
"[get_response_headers] Using system-level proxy (trust_env) if configured."
|
||||
)
|
||||
|
||||
# Prepare headers
|
||||
headers = self._get_auth_headers(use_auth)
|
||||
if custom_headers:
|
||||
headers.update(custom_headers)
|
||||
|
||||
async with session.head(url, headers=headers, proxy=self.proxy_url) as response:
|
||||
async with session.head(
|
||||
url, headers=headers, proxy=self.proxy_url
|
||||
) as response:
|
||||
if response.status == 200:
|
||||
return True, dict(response.headers)
|
||||
else:
|
||||
@@ -742,7 +838,7 @@ class Downloader:
|
||||
url: str,
|
||||
use_auth: bool = False,
|
||||
custom_headers: Optional[Dict[str, str]] = None,
|
||||
**kwargs
|
||||
**kwargs,
|
||||
) -> Tuple[bool, Union[Dict, str]]:
|
||||
"""
|
||||
Make a generic HTTP request and return JSON response
|
||||
@@ -763,7 +859,9 @@ class Downloader:
|
||||
if self.proxy_url:
|
||||
logger.debug(f"[make_request] Using app-level proxy: {self.proxy_url}")
|
||||
else:
|
||||
logger.debug("[make_request] Using system-level proxy (trust_env) if configured.")
|
||||
logger.debug(
|
||||
"[make_request] Using system-level proxy (trust_env) if configured."
|
||||
)
|
||||
|
||||
# Prepare headers
|
||||
headers = self._get_auth_headers(use_auth)
|
||||
@@ -771,10 +869,12 @@ class Downloader:
|
||||
headers.update(custom_headers)
|
||||
|
||||
# Add proxy to kwargs if not already present
|
||||
if 'proxy' not in kwargs:
|
||||
kwargs['proxy'] = self.proxy_url
|
||||
if "proxy" not in kwargs:
|
||||
kwargs["proxy"] = self.proxy_url
|
||||
|
||||
async with session.request(method, url, headers=headers, **kwargs) as response:
|
||||
async with session.request(
|
||||
method, url, headers=headers, **kwargs
|
||||
) as response:
|
||||
if response.status == 200:
|
||||
# Try to parse as JSON, fall back to text
|
||||
try:
|
||||
|
||||
@@ -48,7 +48,9 @@ class LoraService(BaseModelService):
|
||||
"notes": lora_data.get("notes", ""),
|
||||
"favorite": lora_data.get("favorite", False),
|
||||
"update_available": bool(lora_data.get("update_available", False)),
|
||||
"skip_metadata_refresh": bool(lora_data.get("skip_metadata_refresh", False)),
|
||||
"skip_metadata_refresh": bool(
|
||||
lora_data.get("skip_metadata_refresh", False)
|
||||
),
|
||||
"sub_type": sub_type,
|
||||
"civitai": self.filter_civitai_data(
|
||||
lora_data.get("civitai", {}), minimal=True
|
||||
@@ -62,6 +64,68 @@ class LoraService(BaseModelService):
|
||||
if first_letter:
|
||||
data = self._filter_by_first_letter(data, first_letter)
|
||||
|
||||
# Handle name pattern filters
|
||||
name_pattern_include = kwargs.get("name_pattern_include", [])
|
||||
name_pattern_exclude = kwargs.get("name_pattern_exclude", [])
|
||||
name_pattern_use_regex = kwargs.get("name_pattern_use_regex", False)
|
||||
|
||||
if name_pattern_include or name_pattern_exclude:
|
||||
import re
|
||||
|
||||
def matches_pattern(name, pattern, use_regex):
|
||||
"""Check if name matches pattern (regex or substring)"""
|
||||
if not name:
|
||||
return False
|
||||
if use_regex:
|
||||
try:
|
||||
return bool(re.search(pattern, name, re.IGNORECASE))
|
||||
except re.error:
|
||||
# Invalid regex, fall back to substring match
|
||||
return pattern.lower() in name.lower()
|
||||
else:
|
||||
return pattern.lower() in name.lower()
|
||||
|
||||
def matches_any_pattern(name, patterns, use_regex):
|
||||
"""Check if name matches any of the patterns"""
|
||||
if not patterns:
|
||||
return True
|
||||
return any(matches_pattern(name, p, use_regex) for p in patterns)
|
||||
|
||||
filtered = []
|
||||
for lora in data:
|
||||
model_name = lora.get("model_name", "")
|
||||
file_name = lora.get("file_name", "")
|
||||
names_to_check = [n for n in [model_name, file_name] if n]
|
||||
|
||||
# Check exclude patterns first
|
||||
excluded = False
|
||||
if name_pattern_exclude:
|
||||
for name in names_to_check:
|
||||
if matches_any_pattern(
|
||||
name, name_pattern_exclude, name_pattern_use_regex
|
||||
):
|
||||
excluded = True
|
||||
break
|
||||
|
||||
if excluded:
|
||||
continue
|
||||
|
||||
# Check include patterns
|
||||
if name_pattern_include:
|
||||
included = False
|
||||
for name in names_to_check:
|
||||
if matches_any_pattern(
|
||||
name, name_pattern_include, name_pattern_use_regex
|
||||
):
|
||||
included = True
|
||||
break
|
||||
if not included:
|
||||
continue
|
||||
|
||||
filtered.append(lora)
|
||||
|
||||
data = filtered
|
||||
|
||||
return data
|
||||
|
||||
def _filter_by_first_letter(self, data: List[Dict], letter: str) -> List[Dict]:
|
||||
@@ -368,9 +432,7 @@ class LoraService(BaseModelService):
|
||||
rng.uniform(clip_strength_min, clip_strength_max), 2
|
||||
)
|
||||
else:
|
||||
clip_str = round(
|
||||
rng.uniform(clip_strength_min, clip_strength_max), 2
|
||||
)
|
||||
clip_str = round(rng.uniform(clip_strength_min, clip_strength_max), 2)
|
||||
|
||||
result_loras.append(
|
||||
{
|
||||
@@ -485,12 +547,69 @@ class LoraService(BaseModelService):
|
||||
if bool(lora.get("license_flags", 127) & (1 << 1))
|
||||
]
|
||||
|
||||
# Apply name pattern filters
|
||||
name_patterns = filter_section.get("namePatterns", {})
|
||||
include_patterns = name_patterns.get("include", [])
|
||||
exclude_patterns = name_patterns.get("exclude", [])
|
||||
use_regex = name_patterns.get("useRegex", False)
|
||||
|
||||
if include_patterns or exclude_patterns:
|
||||
import re
|
||||
|
||||
def matches_pattern(name, pattern, use_regex):
|
||||
"""Check if name matches pattern (regex or substring)"""
|
||||
if not name:
|
||||
return False
|
||||
if use_regex:
|
||||
try:
|
||||
return bool(re.search(pattern, name, re.IGNORECASE))
|
||||
except re.error:
|
||||
# Invalid regex, fall back to substring match
|
||||
return pattern.lower() in name.lower()
|
||||
else:
|
||||
return pattern.lower() in name.lower()
|
||||
|
||||
def matches_any_pattern(name, patterns, use_regex):
|
||||
"""Check if name matches any of the patterns"""
|
||||
if not patterns:
|
||||
return True
|
||||
return any(matches_pattern(name, p, use_regex) for p in patterns)
|
||||
|
||||
filtered = []
|
||||
for lora in available_loras:
|
||||
model_name = lora.get("model_name", "")
|
||||
file_name = lora.get("file_name", "")
|
||||
names_to_check = [n for n in [model_name, file_name] if n]
|
||||
|
||||
# Check exclude patterns first
|
||||
excluded = False
|
||||
if exclude_patterns:
|
||||
for name in names_to_check:
|
||||
if matches_any_pattern(name, exclude_patterns, use_regex):
|
||||
excluded = True
|
||||
break
|
||||
|
||||
if excluded:
|
||||
continue
|
||||
|
||||
# Check include patterns
|
||||
if include_patterns:
|
||||
included = False
|
||||
for name in names_to_check:
|
||||
if matches_any_pattern(name, include_patterns, use_regex):
|
||||
included = True
|
||||
break
|
||||
if not included:
|
||||
continue
|
||||
|
||||
filtered.append(lora)
|
||||
|
||||
available_loras = filtered
|
||||
|
||||
return available_loras
|
||||
|
||||
async def get_cycler_list(
|
||||
self,
|
||||
pool_config: Optional[Dict] = None,
|
||||
sort_by: str = "filename"
|
||||
self, pool_config: Optional[Dict] = None, sort_by: str = "filename"
|
||||
) -> List[Dict]:
|
||||
"""
|
||||
Get filtered and sorted LoRA list for cycling.
|
||||
@@ -518,16 +637,16 @@ class LoraService(BaseModelService):
|
||||
available_loras,
|
||||
key=lambda x: (
|
||||
(x.get("model_name") or x.get("file_name", "")).lower(),
|
||||
x.get("file_path", "").lower()
|
||||
)
|
||||
x.get("file_path", "").lower(),
|
||||
),
|
||||
)
|
||||
else: # Default to filename
|
||||
available_loras = sorted(
|
||||
available_loras,
|
||||
key=lambda x: (
|
||||
x.get("file_name", "").lower(),
|
||||
x.get("file_path", "").lower()
|
||||
)
|
||||
x.get("file_path", "").lower(),
|
||||
),
|
||||
)
|
||||
|
||||
# Return minimal data needed for cycling
|
||||
|
||||
@@ -122,11 +122,25 @@ async def get_metadata_provider(provider_name: str = None):
|
||||
|
||||
provider_manager = await ModelMetadataProviderManager.get_instance()
|
||||
|
||||
provider = (
|
||||
provider_manager._get_provider(provider_name)
|
||||
if provider_name
|
||||
else provider_manager._get_provider()
|
||||
)
|
||||
try:
|
||||
provider = (
|
||||
provider_manager._get_provider(provider_name)
|
||||
if provider_name
|
||||
else provider_manager._get_provider()
|
||||
)
|
||||
except ValueError as e:
|
||||
# Provider not initialized, attempt to initialize
|
||||
if "No default provider set" in str(e) or "not registered" in str(e):
|
||||
logger.warning(f"Metadata provider not initialized ({e}), initializing now...")
|
||||
await initialize_metadata_providers()
|
||||
provider_manager = await ModelMetadataProviderManager.get_instance()
|
||||
provider = (
|
||||
provider_manager._get_provider(provider_name)
|
||||
if provider_name
|
||||
else provider_manager._get_provider()
|
||||
)
|
||||
else:
|
||||
raise
|
||||
|
||||
return _wrap_provider_with_rate_limit(provider_name, provider)
|
||||
|
||||
|
||||
@@ -14,7 +14,6 @@ from ..utils.metadata_manager import MetadataManager
|
||||
from ..utils.civitai_utils import resolve_license_info
|
||||
from .model_cache import ModelCache
|
||||
from .model_hash_index import ModelHashIndex
|
||||
from ..utils.constants import PREVIEW_EXTENSIONS
|
||||
from .model_lifecycle_service import delete_model_artifacts
|
||||
from .service_registry import ServiceRegistry
|
||||
from .websocket_manager import ws_manager
|
||||
@@ -1443,12 +1442,11 @@ class ModelScanner:
|
||||
if not file_path:
|
||||
return None
|
||||
|
||||
base_name = os.path.splitext(file_path)[0]
|
||||
|
||||
for ext in PREVIEW_EXTENSIONS:
|
||||
preview_path = f"{base_name}{ext}"
|
||||
if os.path.exists(preview_path):
|
||||
return config.get_preview_static_url(preview_path)
|
||||
dir_path = os.path.dirname(file_path)
|
||||
base_name = os.path.splitext(os.path.basename(file_path))[0]
|
||||
preview_path = find_preview_file(base_name, dir_path)
|
||||
if preview_path:
|
||||
return config.get_preview_static_url(preview_path)
|
||||
|
||||
return None
|
||||
|
||||
|
||||
@@ -13,7 +13,7 @@ from typing import Any, Dict, Iterable, List, Mapping, Optional, Sequence
|
||||
from .errors import RateLimitError, ResourceNotFoundError
|
||||
from .settings_manager import get_settings_manager
|
||||
from ..utils.civitai_utils import rewrite_preview_url
|
||||
from ..utils.preview_selection import select_preview_media
|
||||
from ..utils.preview_selection import resolve_mature_threshold, select_preview_media
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
@@ -1252,14 +1252,23 @@ class ModelUpdateService:
|
||||
return None
|
||||
|
||||
blur_mature_content = True
|
||||
mature_threshold = resolve_mature_threshold({"mature_blur_level": "R"})
|
||||
settings = getattr(self, "_settings", None)
|
||||
if settings is not None and hasattr(settings, "get"):
|
||||
try:
|
||||
blur_mature_content = bool(settings.get("blur_mature_content", True))
|
||||
mature_threshold = resolve_mature_threshold(
|
||||
{"mature_blur_level": settings.get("mature_blur_level", "R")}
|
||||
)
|
||||
except Exception: # pragma: no cover - defensive guard
|
||||
blur_mature_content = True
|
||||
mature_threshold = resolve_mature_threshold({"mature_blur_level": "R"})
|
||||
|
||||
selected, _ = select_preview_media(candidates, blur_mature_content=blur_mature_content)
|
||||
selected, _ = select_preview_media(
|
||||
candidates,
|
||||
blur_mature_content=blur_mature_content,
|
||||
mature_threshold=mature_threshold,
|
||||
)
|
||||
if not selected:
|
||||
return None
|
||||
|
||||
|
||||
@@ -56,6 +56,7 @@ class PersistentModelCache:
|
||||
"exclude",
|
||||
"db_checked",
|
||||
"last_checked_at",
|
||||
"hash_status",
|
||||
)
|
||||
_MODEL_UPDATE_COLUMNS: Tuple[str, ...] = _MODEL_COLUMNS[2:]
|
||||
_instances: Dict[str, "PersistentModelCache"] = {}
|
||||
@@ -186,6 +187,7 @@ class PersistentModelCache:
|
||||
"civitai_deleted": bool(row["civitai_deleted"]),
|
||||
"skip_metadata_refresh": bool(row["skip_metadata_refresh"]),
|
||||
"license_flags": int(license_value),
|
||||
"hash_status": row["hash_status"] or "completed",
|
||||
}
|
||||
raw_data.append(item)
|
||||
|
||||
@@ -449,6 +451,7 @@ class PersistentModelCache:
|
||||
exclude INTEGER,
|
||||
db_checked INTEGER,
|
||||
last_checked_at REAL,
|
||||
hash_status TEXT,
|
||||
PRIMARY KEY (model_type, file_path)
|
||||
);
|
||||
|
||||
@@ -496,6 +499,7 @@ class PersistentModelCache:
|
||||
"skip_metadata_refresh": "INTEGER DEFAULT 0",
|
||||
# Persisting without explicit flags should assume CivitAI's documented defaults (0b111001 == 57).
|
||||
"license_flags": f"INTEGER DEFAULT {DEFAULT_LICENSE_FLAGS}",
|
||||
"hash_status": "TEXT DEFAULT 'completed'",
|
||||
}
|
||||
|
||||
for column, definition in required_columns.items():
|
||||
@@ -570,6 +574,7 @@ class PersistentModelCache:
|
||||
1 if item.get("exclude") else 0,
|
||||
1 if item.get("db_checked") else 0,
|
||||
float(item.get("last_checked_at") or 0.0),
|
||||
item.get("hash_status", "completed"),
|
||||
)
|
||||
|
||||
def _insert_model_sql(self) -> str:
|
||||
|
||||
@@ -9,7 +9,7 @@ from urllib.parse import urlparse
|
||||
|
||||
from ..utils.constants import CARD_PREVIEW_WIDTH, PREVIEW_EXTENSIONS
|
||||
from ..utils.civitai_utils import rewrite_preview_url
|
||||
from ..utils.preview_selection import select_preview_media
|
||||
from ..utils.preview_selection import resolve_mature_threshold, select_preview_media
|
||||
from .settings_manager import get_settings_manager
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
@@ -49,9 +49,13 @@ class PreviewAssetService:
|
||||
blur_mature_content = bool(
|
||||
settings_manager.get("blur_mature_content", True)
|
||||
)
|
||||
mature_threshold = resolve_mature_threshold(
|
||||
{"mature_blur_level": settings_manager.get("mature_blur_level", "R")}
|
||||
)
|
||||
first_preview, nsfw_level = select_preview_media(
|
||||
images,
|
||||
blur_mature_content=blur_mature_content,
|
||||
mature_threshold=mature_threshold,
|
||||
)
|
||||
|
||||
if not first_preview:
|
||||
@@ -216,4 +220,3 @@ class PreviewAssetService:
|
||||
if "webm" in content_type:
|
||||
return ".webm"
|
||||
return ".mp4"
|
||||
|
||||
|
||||
@@ -1,4 +1,5 @@
|
||||
"""Services responsible for recipe metadata analysis."""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import base64
|
||||
@@ -69,7 +70,9 @@ class RecipeAnalysisService:
|
||||
try:
|
||||
metadata = self._exif_utils.extract_image_metadata(temp_path)
|
||||
if not metadata:
|
||||
return AnalysisResult({"error": "No metadata found in this image", "loras": []})
|
||||
return AnalysisResult(
|
||||
{"error": "No metadata found in this image", "loras": []}
|
||||
)
|
||||
|
||||
return await self._parse_metadata(
|
||||
metadata,
|
||||
@@ -105,7 +108,9 @@ class RecipeAnalysisService:
|
||||
if civitai_match:
|
||||
image_info = await civitai_client.get_image_info(civitai_match.group(1))
|
||||
if not image_info:
|
||||
raise RecipeDownloadError("Failed to fetch image information from Civitai")
|
||||
raise RecipeDownloadError(
|
||||
"Failed to fetch image information from Civitai"
|
||||
)
|
||||
|
||||
image_url = image_info.get("url")
|
||||
if not image_url:
|
||||
@@ -114,13 +119,15 @@ class RecipeAnalysisService:
|
||||
is_video = image_info.get("type") == "video"
|
||||
|
||||
# Use optimized preview URLs if possible
|
||||
rewritten_url, _ = rewrite_preview_url(image_url, media_type=image_info.get("type"))
|
||||
rewritten_url, _ = rewrite_preview_url(
|
||||
image_url, media_type=image_info.get("type")
|
||||
)
|
||||
if rewritten_url:
|
||||
image_url = rewritten_url
|
||||
|
||||
if is_video:
|
||||
# Extract extension from URL
|
||||
url_path = image_url.split('?')[0].split('#')[0]
|
||||
url_path = image_url.split("?")[0].split("#")[0]
|
||||
extension = os.path.splitext(url_path)[1].lower() or ".mp4"
|
||||
else:
|
||||
extension = ".jpg"
|
||||
@@ -135,9 +142,17 @@ class RecipeAnalysisService:
|
||||
and isinstance(metadata["meta"], dict)
|
||||
):
|
||||
metadata = metadata["meta"]
|
||||
|
||||
# Validate that metadata contains meaningful recipe fields
|
||||
# If not, treat as None to trigger EXIF extraction from downloaded image
|
||||
if isinstance(metadata, dict) and not self._has_recipe_fields(metadata):
|
||||
self._logger.debug(
|
||||
"Civitai API metadata lacks recipe fields, will extract from EXIF"
|
||||
)
|
||||
metadata = None
|
||||
else:
|
||||
# Basic extension detection for non-Civitai URLs
|
||||
url_path = url.split('?')[0].split('#')[0]
|
||||
url_path = url.split("?")[0].split("#")[0]
|
||||
extension = os.path.splitext(url_path)[1].lower()
|
||||
if extension in [".mp4", ".webm"]:
|
||||
is_video = True
|
||||
@@ -211,7 +226,9 @@ class RecipeAnalysisService:
|
||||
|
||||
image_bytes = self._convert_tensor_to_png_bytes(latest_image)
|
||||
if image_bytes is None:
|
||||
raise RecipeValidationError("Cannot handle this data shape from metadata registry")
|
||||
raise RecipeValidationError(
|
||||
"Cannot handle this data shape from metadata registry"
|
||||
)
|
||||
|
||||
return AnalysisResult(
|
||||
{
|
||||
@@ -222,6 +239,22 @@ class RecipeAnalysisService:
|
||||
|
||||
# Internal helpers -------------------------------------------------
|
||||
|
||||
def _has_recipe_fields(self, metadata: dict[str, Any]) -> bool:
|
||||
"""Check if metadata contains meaningful recipe-related fields."""
|
||||
recipe_fields = {
|
||||
"prompt",
|
||||
"negative_prompt",
|
||||
"resources",
|
||||
"hashes",
|
||||
"params",
|
||||
"generationData",
|
||||
"Workflow",
|
||||
"prompt_type",
|
||||
"positive",
|
||||
"negative",
|
||||
}
|
||||
return any(field in metadata for field in recipe_fields)
|
||||
|
||||
async def _parse_metadata(
|
||||
self,
|
||||
metadata: dict[str, Any],
|
||||
@@ -234,7 +267,12 @@ class RecipeAnalysisService:
|
||||
) -> AnalysisResult:
|
||||
parser = self._recipe_parser_factory.create_parser(metadata)
|
||||
if parser is None:
|
||||
payload = {"error": "No parser found for this image", "loras": []}
|
||||
# Provide more specific error message based on metadata source
|
||||
if not metadata:
|
||||
error_msg = "This image does not contain any generation metadata (prompt, models, or parameters)"
|
||||
else:
|
||||
error_msg = "No parser found for this image"
|
||||
payload = {"error": error_msg, "loras": []}
|
||||
if include_image_base64 and image_path:
|
||||
payload["image_base64"] = self._encode_file(image_path)
|
||||
payload["is_video"] = is_video
|
||||
@@ -257,7 +295,9 @@ class RecipeAnalysisService:
|
||||
|
||||
matching_recipes: list[str] = []
|
||||
if fingerprint:
|
||||
matching_recipes = await recipe_scanner.find_recipes_by_fingerprint(fingerprint)
|
||||
matching_recipes = await recipe_scanner.find_recipes_by_fingerprint(
|
||||
fingerprint
|
||||
)
|
||||
result["matching_recipes"] = matching_recipes
|
||||
|
||||
return AnalysisResult(result)
|
||||
@@ -269,7 +309,10 @@ class RecipeAnalysisService:
|
||||
raise RecipeDownloadError(f"Failed to download image from URL: {result}")
|
||||
|
||||
def _metadata_not_found_response(self, path: str) -> AnalysisResult:
|
||||
payload: dict[str, Any] = {"error": "No metadata found in this image", "loras": []}
|
||||
payload: dict[str, Any] = {
|
||||
"error": "No metadata found in this image",
|
||||
"loras": [],
|
||||
}
|
||||
if os.path.exists(path):
|
||||
payload["image_base64"] = self._encode_file(path)
|
||||
return AnalysisResult(payload)
|
||||
@@ -305,7 +348,9 @@ class RecipeAnalysisService:
|
||||
|
||||
if hasattr(tensor_image, "shape"):
|
||||
self._logger.debug(
|
||||
"Tensor shape: %s, dtype: %s", tensor_image.shape, getattr(tensor_image, "dtype", None)
|
||||
"Tensor shape: %s, dtype: %s",
|
||||
tensor_image.shape,
|
||||
getattr(tensor_image, "dtype", None),
|
||||
)
|
||||
|
||||
import torch # type: ignore[import-not-found]
|
||||
|
||||
@@ -12,6 +12,7 @@ from typing import Any, Awaitable, Dict, Iterable, List, Mapping, Optional, Sequ
|
||||
from platformdirs import user_config_dir
|
||||
|
||||
from ..utils.constants import DEFAULT_HASH_CHUNK_SIZE_MB, DEFAULT_PRIORITY_TAG_CONFIG
|
||||
from ..utils.preview_selection import VALID_MATURE_BLUR_LEVELS
|
||||
from ..utils.settings_paths import APP_NAME, ensure_settings_file, get_legacy_settings_path
|
||||
from ..utils.tag_priorities import (
|
||||
PriorityTagEntry,
|
||||
@@ -59,6 +60,7 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
|
||||
"optimize_example_images": True,
|
||||
"auto_download_example_images": False,
|
||||
"blur_mature_content": True,
|
||||
"mature_blur_level": "R",
|
||||
"autoplay_on_hover": False,
|
||||
"display_density": "default",
|
||||
"card_info_display": "always",
|
||||
@@ -274,6 +276,16 @@ class SettingsManager:
|
||||
self.settings["metadata_refresh_skip_paths"] = []
|
||||
inserted_defaults = True
|
||||
|
||||
had_mature_level = "mature_blur_level" in self.settings
|
||||
raw_mature_level = self.settings.get("mature_blur_level")
|
||||
normalized_mature_level = self.normalize_mature_blur_level(raw_mature_level)
|
||||
if normalized_mature_level != raw_mature_level:
|
||||
self.settings["mature_blur_level"] = normalized_mature_level
|
||||
if had_mature_level:
|
||||
updated_existing = True
|
||||
else:
|
||||
inserted_defaults = True
|
||||
|
||||
for key, value in defaults.items():
|
||||
if key == "priority_tags":
|
||||
continue
|
||||
@@ -608,6 +620,7 @@ class SettingsManager:
|
||||
'optimizeExampleImages': 'optimize_example_images',
|
||||
'autoDownloadExampleImages': 'auto_download_example_images',
|
||||
'blurMatureContent': 'blur_mature_content',
|
||||
'matureBlurLevel': 'mature_blur_level',
|
||||
'autoplayOnHover': 'autoplay_on_hover',
|
||||
'displayDensity': 'display_density',
|
||||
'cardInfoDisplay': 'card_info_display',
|
||||
@@ -860,6 +873,13 @@ class SettingsManager:
|
||||
|
||||
return normalized
|
||||
|
||||
def normalize_mature_blur_level(self, value: Any) -> str:
|
||||
if isinstance(value, str):
|
||||
normalized = value.strip().upper()
|
||||
if normalized in VALID_MATURE_BLUR_LEVELS:
|
||||
return normalized
|
||||
return "R"
|
||||
|
||||
def normalize_auto_organize_exclusions(self, value: Any) -> List[str]:
|
||||
if value is None:
|
||||
return []
|
||||
@@ -1012,6 +1032,8 @@ class SettingsManager:
|
||||
value = self.normalize_auto_organize_exclusions(value)
|
||||
elif key == "metadata_refresh_skip_paths":
|
||||
value = self.normalize_metadata_refresh_skip_paths(value)
|
||||
elif key == "mature_blur_level":
|
||||
value = self.normalize_mature_blur_level(value)
|
||||
self.settings[key] = value
|
||||
portable_switch_pending = False
|
||||
if key == "use_portable_settings" and isinstance(value, bool):
|
||||
|
||||
@@ -40,49 +40,39 @@ async def calculate_sha256(file_path: str) -> str:
|
||||
return sha256_hash.hexdigest()
|
||||
|
||||
def find_preview_file(base_name: str, dir_path: str) -> str:
|
||||
"""Find preview file for given base name in directory"""
|
||||
"""Find preview file for given base name in directory.
|
||||
|
||||
Performs an exact-case check first (fast path), then falls back to a
|
||||
case-insensitive scan so that files like ``model.WEBP`` or ``model.Png``
|
||||
are discovered on case-sensitive filesystems.
|
||||
"""
|
||||
|
||||
temp_extensions = PREVIEW_EXTENSIONS.copy()
|
||||
# Add example extension for compatibility
|
||||
# https://github.com/willmiao/ComfyUI-Lora-Manager/issues/225
|
||||
# The preview image will be optimized to lora-name.webp, so it won't affect other logic
|
||||
temp_extensions.append(".example.0.jpeg")
|
||||
|
||||
# Fast path: exact-case match
|
||||
for ext in temp_extensions:
|
||||
full_pattern = os.path.join(dir_path, f"{base_name}{ext}")
|
||||
if os.path.exists(full_pattern):
|
||||
# Check if this is an image and not already webp
|
||||
# TODO: disable the optimization for now, maybe add a config option later
|
||||
# if ext.lower().endswith(('.jpg', '.jpeg', '.png')) and not ext.lower().endswith('.webp'):
|
||||
# try:
|
||||
# # Optimize the image to webp format
|
||||
# webp_path = os.path.join(dir_path, f"{base_name}.webp")
|
||||
|
||||
# # Use ExifUtils to optimize the image
|
||||
# with open(full_pattern, 'rb') as f:
|
||||
# image_data = f.read()
|
||||
|
||||
# optimized_data, _ = ExifUtils.optimize_image(
|
||||
# image_data=image_data,
|
||||
# target_width=CARD_PREVIEW_WIDTH,
|
||||
# format='webp',
|
||||
# quality=85,
|
||||
# preserve_metadata=False
|
||||
# )
|
||||
|
||||
# # Save the optimized webp file
|
||||
# with open(webp_path, 'wb') as f:
|
||||
# f.write(optimized_data)
|
||||
|
||||
# logger.debug(f"Optimized preview image from {full_pattern} to {webp_path}")
|
||||
# return webp_path.replace(os.sep, "/")
|
||||
# except Exception as e:
|
||||
# logger.error(f"Error optimizing preview image {full_pattern}: {e}")
|
||||
# # Fall back to original file if optimization fails
|
||||
# return full_pattern.replace(os.sep, "/")
|
||||
|
||||
# Return the original path for webp images or non-image files
|
||||
return full_pattern.replace(os.sep, "/")
|
||||
|
||||
# Slow path: case-insensitive match for systems with mixed-case extensions
|
||||
# (e.g. .WEBP, .Png, .JPG placed manually or by external tools)
|
||||
try:
|
||||
dir_entries = os.listdir(dir_path)
|
||||
except OSError:
|
||||
return ""
|
||||
|
||||
base_lower = base_name.lower()
|
||||
for ext in temp_extensions:
|
||||
target = f"{base_lower}{ext}" # ext is already lowercase
|
||||
for entry in dir_entries:
|
||||
if entry.lower() == target:
|
||||
return os.path.join(dir_path, entry).replace(os.sep, "/")
|
||||
|
||||
return ""
|
||||
|
||||
def get_preview_extension(preview_path: str) -> str:
|
||||
|
||||
@@ -2,11 +2,12 @@
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
from typing import Mapping, Optional, Sequence, Tuple
|
||||
from typing import Any, Mapping, Optional, Sequence, Tuple
|
||||
|
||||
from .constants import NSFW_LEVELS
|
||||
|
||||
PreviewMedia = Mapping[str, object]
|
||||
VALID_MATURE_BLUR_LEVELS = ("PG13", "R", "X", "XXX")
|
||||
|
||||
|
||||
def _extract_nsfw_level(entry: Mapping[str, object]) -> int:
|
||||
@@ -19,17 +20,36 @@ def _extract_nsfw_level(entry: Mapping[str, object]) -> int:
|
||||
return 0
|
||||
|
||||
|
||||
def resolve_mature_threshold(settings: Mapping[str, Any] | None) -> int:
|
||||
"""Resolve the configured mature blur threshold from settings.
|
||||
|
||||
Allowed values are ``PG13``, ``R``, ``X``, and ``XXX``. Any invalid or
|
||||
missing value falls back to ``R``.
|
||||
"""
|
||||
|
||||
if not isinstance(settings, Mapping):
|
||||
return NSFW_LEVELS.get("R", 4)
|
||||
|
||||
raw_level = settings.get("mature_blur_level", "R")
|
||||
normalized = str(raw_level).strip().upper()
|
||||
if normalized not in VALID_MATURE_BLUR_LEVELS:
|
||||
normalized = "R"
|
||||
return NSFW_LEVELS.get(normalized, NSFW_LEVELS.get("R", 4))
|
||||
|
||||
|
||||
def select_preview_media(
|
||||
images: Sequence[Mapping[str, object]] | None,
|
||||
*,
|
||||
blur_mature_content: bool,
|
||||
mature_threshold: int | None = None,
|
||||
) -> Tuple[Optional[PreviewMedia], int]:
|
||||
"""Select the most appropriate preview media entry.
|
||||
|
||||
When ``blur_mature_content`` is enabled we first try to return the first media
|
||||
item with an ``nsfwLevel`` lower than :pydata:`NSFW_LEVELS["R"]`. If none are
|
||||
available we return the media entry with the lowest NSFW level. When the
|
||||
setting is disabled we simply return the first entry.
|
||||
item with an ``nsfwLevel`` lower than the configured mature threshold
|
||||
(defaults to :pydata:`NSFW_LEVELS["R"]`). If none are available we return
|
||||
the media entry with the lowest NSFW level. When the setting is disabled we
|
||||
simply return the first entry.
|
||||
"""
|
||||
|
||||
if not images:
|
||||
@@ -45,7 +65,9 @@ def select_preview_media(
|
||||
if not blur_mature_content:
|
||||
return selected, selected_level
|
||||
|
||||
safe_threshold = NSFW_LEVELS.get("R", 4)
|
||||
safe_threshold = (
|
||||
mature_threshold if isinstance(mature_threshold, int) else NSFW_LEVELS.get("R", 4)
|
||||
)
|
||||
for candidate in candidates:
|
||||
level = _extract_nsfw_level(candidate)
|
||||
if level < safe_threshold:
|
||||
@@ -60,4 +82,4 @@ def select_preview_media(
|
||||
return selected, selected_level
|
||||
|
||||
|
||||
__all__ = ["select_preview_media"]
|
||||
__all__ = ["resolve_mature_threshold", "select_preview_media", "VALID_MATURE_BLUR_LEVELS"]
|
||||
|
||||
@@ -148,8 +148,8 @@ def get_checkpoint_info_absolute(checkpoint_name):
|
||||
# Format the stored path as ComfyUI-style name
|
||||
formatted_name = _format_model_name_for_comfyui(file_path, model_roots)
|
||||
|
||||
# Match by formatted name
|
||||
if formatted_name == normalized_name or formatted_name == checkpoint_name:
|
||||
# Match by formatted name (normalize separators for robust comparison)
|
||||
if formatted_name.replace(os.sep, "/") == normalized_name or formatted_name == checkpoint_name:
|
||||
return file_path, item
|
||||
|
||||
# Also try matching by basename only (for backward compatibility)
|
||||
@@ -200,19 +200,22 @@ def _format_model_name_for_comfyui(file_path: str, model_roots: list) -> str:
|
||||
Returns:
|
||||
ComfyUI-style model name with relative path and extension
|
||||
"""
|
||||
# Normalize path separators
|
||||
normalized_path = file_path.replace(os.sep, "/")
|
||||
|
||||
# Find the matching root and get relative path
|
||||
for root in model_roots:
|
||||
normalized_root = root.replace(os.sep, "/")
|
||||
# Ensure root ends with / for proper matching
|
||||
if not normalized_root.endswith("/"):
|
||||
normalized_root += "/"
|
||||
try:
|
||||
# Normalize paths for comparison
|
||||
norm_file = os.path.normcase(os.path.abspath(file_path))
|
||||
norm_root = os.path.normcase(os.path.abspath(root))
|
||||
|
||||
if normalized_path.startswith(normalized_root):
|
||||
rel_path = normalized_path[len(normalized_root) :]
|
||||
return rel_path
|
||||
# Add trailing separator for prefix check
|
||||
if not norm_root.endswith(os.sep):
|
||||
norm_root += os.sep
|
||||
|
||||
if norm_file.startswith(norm_root):
|
||||
# Use os.path.relpath to get relative path with OS-native separator
|
||||
return os.path.relpath(file_path, root)
|
||||
except (ValueError, TypeError):
|
||||
continue
|
||||
|
||||
# If no root matches, just return the basename with extension
|
||||
return os.path.basename(file_path)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
[pytest]
|
||||
addopts = -v --import-mode=importlib -m "not performance"
|
||||
addopts = -v --import-mode=importlib -m "not performance" --ignore=__init__.py
|
||||
testpaths = tests
|
||||
python_files = test_*.py
|
||||
python_classes = Test*
|
||||
|
||||
@@ -687,7 +687,7 @@
|
||||
padding: 12px 16px;
|
||||
background: oklch(var(--lora-warning) / 0.1);
|
||||
border: 1px solid var(--lora-warning);
|
||||
border-radius: var(--border-radius-sm) var(--border-radius-sm) 0 0;
|
||||
border-radius: var(--border-radius-sm);
|
||||
color: var(--text-color);
|
||||
}
|
||||
|
||||
|
||||
@@ -151,7 +151,8 @@ body.modal-open {
|
||||
[data-theme="dark"] .changelog-section,
|
||||
[data-theme="dark"] .update-info,
|
||||
[data-theme="dark"] .info-item,
|
||||
[data-theme="dark"] .path-preview {
|
||||
[data-theme="dark"] .path-preview,
|
||||
[data-theme="dark"] #bulkDownloadMissingLorasModal .bulk-download-loras-preview {
|
||||
background: rgba(255, 255, 255, 0.03);
|
||||
border: 1px solid var(--lora-border);
|
||||
}
|
||||
@@ -349,3 +350,87 @@ button:disabled,
|
||||
margin-top: var(--space-1);
|
||||
text-align: center;
|
||||
}
|
||||
|
||||
/* Bulk Download Missing LoRAs Modal */
|
||||
#bulkDownloadMissingLorasModal .modal-body {
|
||||
padding: var(--space-3);
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .confirmation-message {
|
||||
color: var(--text-color);
|
||||
margin-bottom: var(--space-3);
|
||||
font-size: 1em;
|
||||
line-height: 1.5;
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .bulk-download-loras-preview {
|
||||
background: rgba(0, 0, 0, 0.03);
|
||||
border: 1px solid rgba(0, 0, 0, 0.1);
|
||||
border-radius: var(--border-radius-sm);
|
||||
padding: var(--space-3);
|
||||
margin-bottom: var(--space-3);
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .preview-title {
|
||||
font-weight: 600;
|
||||
margin-bottom: var(--space-2);
|
||||
color: var(--text-color);
|
||||
font-size: 0.95em;
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .bulk-download-loras-list {
|
||||
list-style: none;
|
||||
padding: 0;
|
||||
margin: 0;
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .bulk-download-loras-list li {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
padding: var(--space-1) 0;
|
||||
border-bottom: 1px solid var(--border-color);
|
||||
font-size: 0.9em;
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .bulk-download-loras-list li:last-child {
|
||||
border-bottom: none;
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .bulk-download-loras-list li.more-items {
|
||||
font-style: italic;
|
||||
opacity: 0.7;
|
||||
text-align: center;
|
||||
justify-content: center;
|
||||
padding: var(--space-2) 0;
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .lora-name {
|
||||
font-weight: 500;
|
||||
color: var(--text-color);
|
||||
flex: 1;
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .lora-version {
|
||||
font-size: 0.85em;
|
||||
opacity: 0.7;
|
||||
margin-left: var(--space-1);
|
||||
color: var(--text-muted);
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .confirmation-note {
|
||||
display: flex;
|
||||
align-items: flex-start;
|
||||
gap: var(--space-2);
|
||||
padding: var(--space-2);
|
||||
background: rgba(59, 130, 246, 0.1);
|
||||
border-radius: var(--border-radius-sm);
|
||||
font-size: 0.9em;
|
||||
color: var(--text-color);
|
||||
}
|
||||
|
||||
#bulkDownloadMissingLorasModal .confirmation-note i {
|
||||
color: var(--lora-accent);
|
||||
margin-top: 2px;
|
||||
flex-shrink: 0;
|
||||
}
|
||||
|
||||
@@ -251,7 +251,7 @@ export class BaseModelApiClient {
|
||||
replaceModelPreview(filePath) {
|
||||
const input = document.createElement('input');
|
||||
input.type = 'file';
|
||||
input.accept = 'image/*,video/mp4';
|
||||
input.accept = 'image/*,image/webp,video/mp4';
|
||||
|
||||
input.onchange = async () => {
|
||||
if (!input.files || !input.files[0]) return;
|
||||
|
||||
@@ -2,6 +2,8 @@ import { BaseContextMenu } from './BaseContextMenu.js';
|
||||
import { state } from '../../state/index.js';
|
||||
import { bulkManager } from '../../managers/BulkManager.js';
|
||||
import { updateElementText, translate } from '../../utils/i18nHelpers.js';
|
||||
import { bulkMissingLoraDownloadManager } from '../../managers/BulkMissingLoraDownloadManager.js';
|
||||
import { showToast } from '../../utils/uiHelpers.js';
|
||||
|
||||
export class BulkContextMenu extends BaseContextMenu {
|
||||
constructor() {
|
||||
@@ -37,6 +39,7 @@ export class BulkContextMenu extends BaseContextMenu {
|
||||
const moveAllItem = this.menu.querySelector('[data-action="move-all"]');
|
||||
const autoOrganizeItem = this.menu.querySelector('[data-action="auto-organize"]');
|
||||
const deleteAllItem = this.menu.querySelector('[data-action="delete-all"]');
|
||||
const downloadMissingLorasItem = this.menu.querySelector('[data-action="download-missing-loras"]');
|
||||
|
||||
if (sendToWorkflowAppendItem) {
|
||||
sendToWorkflowAppendItem.style.display = config.sendToWorkflow ? 'flex' : 'none';
|
||||
@@ -71,6 +74,10 @@ export class BulkContextMenu extends BaseContextMenu {
|
||||
if (setContentRatingItem) {
|
||||
setContentRatingItem.style.display = config.setContentRating ? 'flex' : 'none';
|
||||
}
|
||||
if (downloadMissingLorasItem) {
|
||||
// Only show for recipes page
|
||||
downloadMissingLorasItem.style.display = currentModelType === 'recipes' ? 'flex' : 'none';
|
||||
}
|
||||
|
||||
const skipMetadataRefreshItem = this.menu.querySelector('[data-action="skip-metadata-refresh"]');
|
||||
const resumeMetadataRefreshItem = this.menu.querySelector('[data-action="resume-metadata-refresh"]');
|
||||
@@ -178,6 +185,9 @@ export class BulkContextMenu extends BaseContextMenu {
|
||||
case 'delete-all':
|
||||
bulkManager.showBulkDeleteModal();
|
||||
break;
|
||||
case 'download-missing-loras':
|
||||
this.handleDownloadMissingLoras();
|
||||
break;
|
||||
case 'clear':
|
||||
bulkManager.clearSelection();
|
||||
break;
|
||||
@@ -185,4 +195,39 @@ export class BulkContextMenu extends BaseContextMenu {
|
||||
console.warn(`Unknown bulk action: ${action}`);
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Handle downloading missing LoRAs for selected recipes
|
||||
*/
|
||||
async handleDownloadMissingLoras() {
|
||||
if (state.selectedModels.size === 0) {
|
||||
return;
|
||||
}
|
||||
|
||||
// Get selected recipes from the virtual scroller
|
||||
const selectedRecipes = [];
|
||||
state.selectedModels.forEach(filePath => {
|
||||
const card = document.querySelector(`.model-card[data-filepath="${CSS.escape(filePath)}"]`);
|
||||
if (card && card.recipeData) {
|
||||
selectedRecipes.push(card.recipeData);
|
||||
}
|
||||
});
|
||||
|
||||
if (selectedRecipes.length === 0) {
|
||||
// Try to get recipes from virtual scroller state
|
||||
const items = state.virtualScroller?.items || [];
|
||||
items.forEach(recipe => {
|
||||
if (recipe.file_path && state.selectedModels.has(recipe.file_path)) {
|
||||
selectedRecipes.push(recipe);
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
if (selectedRecipes.length === 0) {
|
||||
showToast('toast.recipes.noRecipesSelected', {}, 'warning');
|
||||
return;
|
||||
}
|
||||
|
||||
await bulkMissingLoraDownloadManager.downloadMissingLoras(selectedRecipes);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -6,7 +6,7 @@ import { modalManager } from '../managers/ModalManager.js';
|
||||
import { getCurrentPageState } from '../state/index.js';
|
||||
import { state } from '../state/index.js';
|
||||
import { bulkManager } from '../managers/BulkManager.js';
|
||||
import { NSFW_LEVELS, getBaseModelAbbreviation } from '../utils/constants.js';
|
||||
import { NSFW_LEVELS, getBaseModelAbbreviation, getMatureBlurThreshold } from '../utils/constants.js';
|
||||
|
||||
class RecipeCard {
|
||||
constructor(recipe, clickHandler) {
|
||||
@@ -74,7 +74,8 @@ class RecipeCard {
|
||||
|
||||
// NSFW blur logic - similar to LoraCard
|
||||
const nsfwLevel = this.recipe.preview_nsfw_level !== undefined ? this.recipe.preview_nsfw_level : 0;
|
||||
const shouldBlur = state.settings.blur_mature_content && nsfwLevel > NSFW_LEVELS.PG13;
|
||||
const matureBlurThreshold = getMatureBlurThreshold(state.settings);
|
||||
const shouldBlur = state.settings.blur_mature_content && nsfwLevel >= matureBlurThreshold;
|
||||
|
||||
if (shouldBlur) {
|
||||
card.classList.add('nsfw-content');
|
||||
|
||||
@@ -1299,7 +1299,6 @@ class RecipeModal {
|
||||
|
||||
// New method to navigate to the LoRAs page
|
||||
navigateToLorasPage(specificLoraIndex = null) {
|
||||
debugger;
|
||||
// Close the current modal
|
||||
modalManager.closeModal('recipeModal');
|
||||
|
||||
|
||||
@@ -4,7 +4,7 @@ import { showModelModal } from './ModelModal.js';
|
||||
import { toggleShowcase } from './showcase/ShowcaseView.js';
|
||||
import { bulkManager } from '../../managers/BulkManager.js';
|
||||
import { modalManager } from '../../managers/ModalManager.js';
|
||||
import { NSFW_LEVELS, getBaseModelAbbreviation, getSubTypeAbbreviation, MODEL_SUBTYPE_DISPLAY_NAMES } from '../../utils/constants.js';
|
||||
import { NSFW_LEVELS, getBaseModelAbbreviation, getSubTypeAbbreviation, getMatureBlurThreshold, MODEL_SUBTYPE_DISPLAY_NAMES } from '../../utils/constants.js';
|
||||
import { MODEL_TYPES } from '../../api/apiConfig.js';
|
||||
import { getModelApiClient } from '../../api/modelApiFactory.js';
|
||||
import { showDeleteModal } from '../../utils/modalUtils.js';
|
||||
@@ -478,7 +478,8 @@ export function createModelCard(model, modelType) {
|
||||
card.dataset.nsfwLevel = nsfwLevel;
|
||||
|
||||
// Determine if the preview should be blurred based on NSFW level and user settings
|
||||
const shouldBlur = state.settings.blur_mature_content && nsfwLevel > NSFW_LEVELS.PG13;
|
||||
const matureBlurThreshold = getMatureBlurThreshold(state.settings);
|
||||
const shouldBlur = state.settings.blur_mature_content && nsfwLevel >= matureBlurThreshold;
|
||||
if (shouldBlur) {
|
||||
card.classList.add('nsfw-content');
|
||||
}
|
||||
|
||||
@@ -6,7 +6,7 @@
|
||||
import { showToast, copyToClipboard, getNSFWLevelName } from '../../../utils/uiHelpers.js';
|
||||
import { state } from '../../../state/index.js';
|
||||
import { getModelApiClient } from '../../../api/modelApiFactory.js';
|
||||
import { NSFW_LEVELS } from '../../../utils/constants.js';
|
||||
import { NSFW_LEVELS, getMatureBlurThreshold } from '../../../utils/constants.js';
|
||||
import { getNsfwLevelSelector } from '../NsfwLevelSelector.js';
|
||||
|
||||
/**
|
||||
@@ -607,7 +607,8 @@ function applyNsfwLevelChange(mediaWrapper, nsfwLevel) {
|
||||
}
|
||||
mediaWrapper.dataset.nsfwLevel = String(nsfwLevel);
|
||||
|
||||
const shouldBlur = state.settings.blur_mature_content && nsfwLevel > NSFW_LEVELS.PG13;
|
||||
const matureBlurThreshold = getMatureBlurThreshold(state.settings);
|
||||
const shouldBlur = state.settings.blur_mature_content && nsfwLevel >= matureBlurThreshold;
|
||||
let overlay = mediaWrapper.querySelector('.nsfw-overlay');
|
||||
let toggleBtn = mediaWrapper.querySelector('.toggle-blur-btn');
|
||||
|
||||
|
||||
@@ -6,7 +6,7 @@ import { showToast } from '../../../utils/uiHelpers.js';
|
||||
import { state } from '../../../state/index.js';
|
||||
import { modalManager } from '../../../managers/ModalManager.js';
|
||||
import { translate } from '../../../utils/i18nHelpers.js';
|
||||
import { NSFW_LEVELS } from '../../../utils/constants.js';
|
||||
import { NSFW_LEVELS, getMatureBlurThreshold } from '../../../utils/constants.js';
|
||||
import {
|
||||
initLazyLoading,
|
||||
initNsfwBlurHandlers,
|
||||
@@ -184,7 +184,8 @@ function renderMediaItem(img, index, exampleFiles) {
|
||||
|
||||
// Check if media should be blurred
|
||||
const nsfwLevel = img.nsfwLevel !== undefined ? img.nsfwLevel : 0;
|
||||
const shouldBlur = state.settings.blur_mature_content && nsfwLevel > NSFW_LEVELS.PG13;
|
||||
const matureBlurThreshold = getMatureBlurThreshold(state.settings);
|
||||
const shouldBlur = state.settings.blur_mature_content && nsfwLevel >= matureBlurThreshold;
|
||||
|
||||
// Determine NSFW warning text based on level
|
||||
let nsfwText = "Mature Content";
|
||||
|
||||
@@ -104,6 +104,14 @@ export class BatchImportManager {
|
||||
|
||||
// Clean up any existing connections
|
||||
this.cleanupConnections();
|
||||
|
||||
// Focus on the URL input field for better UX
|
||||
setTimeout(() => {
|
||||
const urlInput = document.getElementById('batchUrlInput');
|
||||
if (urlInput) {
|
||||
urlInput.focus();
|
||||
}
|
||||
}, 100);
|
||||
}
|
||||
|
||||
/**
|
||||
|
||||
357
static/js/managers/BulkMissingLoraDownloadManager.js
Normal file
357
static/js/managers/BulkMissingLoraDownloadManager.js
Normal file
@@ -0,0 +1,357 @@
|
||||
import { showToast } from '../utils/uiHelpers.js';
|
||||
import { translate } from '../utils/i18nHelpers.js';
|
||||
import { getModelApiClient } from '../api/modelApiFactory.js';
|
||||
import { MODEL_TYPES } from '../api/apiConfig.js';
|
||||
import { state } from '../state/index.js';
|
||||
import { modalManager } from './ModalManager.js';
|
||||
|
||||
/**
|
||||
* Manager for downloading missing LoRAs for selected recipes in bulk
|
||||
*/
|
||||
export class BulkMissingLoraDownloadManager {
|
||||
constructor() {
|
||||
this.loraApiClient = getModelApiClient(MODEL_TYPES.LORA);
|
||||
this.pendingLoras = [];
|
||||
this.pendingRecipes = [];
|
||||
}
|
||||
|
||||
/**
|
||||
* Collect missing LoRAs from selected recipes with deduplication
|
||||
* @param {Array} selectedRecipes - Array of selected recipe objects
|
||||
* @returns {Object} - Object containing unique missing LoRAs and statistics
|
||||
*/
|
||||
collectMissingLoras(selectedRecipes) {
|
||||
const uniqueLoras = new Map(); // key: hash or modelVersionId, value: lora object
|
||||
const missingLorasByRecipe = new Map();
|
||||
let totalMissingCount = 0;
|
||||
|
||||
selectedRecipes.forEach(recipe => {
|
||||
const missingLoras = [];
|
||||
|
||||
if (recipe.loras && Array.isArray(recipe.loras)) {
|
||||
recipe.loras.forEach(lora => {
|
||||
// Only include LoRAs not in library and not deleted
|
||||
if (!lora.inLibrary && !lora.isDeleted) {
|
||||
const uniqueKey = lora.hash || lora.id || lora.modelVersionId;
|
||||
|
||||
if (uniqueKey && !uniqueLoras.has(uniqueKey)) {
|
||||
// Store the LoRA info
|
||||
uniqueLoras.set(uniqueKey, {
|
||||
...lora,
|
||||
modelId: lora.modelId || lora.model_id,
|
||||
id: lora.id || lora.modelVersionId,
|
||||
});
|
||||
}
|
||||
|
||||
missingLoras.push(lora);
|
||||
totalMissingCount++;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
if (missingLoras.length > 0) {
|
||||
missingLorasByRecipe.set(recipe.id || recipe.file_path, {
|
||||
recipe,
|
||||
missingLoras
|
||||
});
|
||||
}
|
||||
});
|
||||
|
||||
return {
|
||||
uniqueLoras: Array.from(uniqueLoras.values()),
|
||||
uniqueCount: uniqueLoras.size,
|
||||
totalMissingCount,
|
||||
missingLorasByRecipe
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Show confirmation modal for downloading missing LoRAs
|
||||
* @param {Object} stats - Statistics about missing LoRAs
|
||||
* @returns {Promise<boolean>} - Whether user confirmed
|
||||
*/
|
||||
async showConfirmationModal(stats) {
|
||||
const { uniqueCount, totalMissingCount, uniqueLoras } = stats;
|
||||
|
||||
if (uniqueCount === 0) {
|
||||
showToast('toast.recipes.noMissingLoras', {}, 'info');
|
||||
return false;
|
||||
}
|
||||
|
||||
// Store pending data for confirmation
|
||||
this.pendingLoras = uniqueLoras;
|
||||
|
||||
// Update modal content
|
||||
const messageEl = document.getElementById('bulkDownloadMissingLorasMessage');
|
||||
const listEl = document.getElementById('bulkDownloadMissingLorasList');
|
||||
const confirmBtn = document.getElementById('bulkDownloadMissingLorasConfirmBtn');
|
||||
|
||||
if (messageEl) {
|
||||
messageEl.textContent = translate('modals.bulkDownloadMissingLoras.message', {
|
||||
uniqueCount,
|
||||
totalCount: totalMissingCount
|
||||
}, `Found ${uniqueCount} unique missing LoRAs (from ${totalMissingCount} total across selected recipes).`);
|
||||
}
|
||||
|
||||
if (listEl) {
|
||||
listEl.innerHTML = uniqueLoras.slice(0, 10).map(lora => `
|
||||
<li>
|
||||
<span class="lora-name">${lora.name || lora.file_name || 'Unknown'}</span>
|
||||
${lora.version ? `<span class="lora-version">${lora.version}</span>` : ''}
|
||||
</li>
|
||||
`).join('') +
|
||||
(uniqueLoras.length > 10 ? `
|
||||
<li class="more-items">${translate('modals.bulkDownloadMissingLoras.moreItems', { count: uniqueLoras.length - 10 }, `...and ${uniqueLoras.length - 10} more`)}</li>
|
||||
` : '');
|
||||
}
|
||||
|
||||
if (confirmBtn) {
|
||||
confirmBtn.innerHTML = `
|
||||
<i class="fas fa-download"></i>
|
||||
${translate('modals.bulkDownloadMissingLoras.downloadButton', { count: uniqueCount }, `Download ${uniqueCount} LoRA(s)`)}
|
||||
`;
|
||||
}
|
||||
|
||||
// Show modal
|
||||
modalManager.showModal('bulkDownloadMissingLorasModal');
|
||||
|
||||
// Return a promise that will be resolved when user confirms or cancels
|
||||
return new Promise((resolve) => {
|
||||
this.confirmResolve = resolve;
|
||||
});
|
||||
}
|
||||
|
||||
/**
|
||||
* Called when user confirms download in modal
|
||||
*/
|
||||
async confirmDownload() {
|
||||
modalManager.closeModal('bulkDownloadMissingLorasModal');
|
||||
|
||||
if (this.confirmResolve) {
|
||||
this.confirmResolve(true);
|
||||
this.confirmResolve = null;
|
||||
}
|
||||
|
||||
// Execute download
|
||||
await this.executeDownload(this.pendingLoras);
|
||||
this.pendingLoras = [];
|
||||
}
|
||||
|
||||
/**
|
||||
* Download missing LoRAs for selected recipes
|
||||
* @param {Array} selectedRecipes - Array of selected recipe objects
|
||||
*/
|
||||
async downloadMissingLoras(selectedRecipes) {
|
||||
if (!selectedRecipes || selectedRecipes.length === 0) {
|
||||
showToast('toast.recipes.noRecipesSelected', {}, 'warning');
|
||||
return;
|
||||
}
|
||||
|
||||
// Store selected recipes
|
||||
this.pendingRecipes = selectedRecipes;
|
||||
|
||||
// Collect missing LoRAs with deduplication
|
||||
const stats = this.collectMissingLoras(selectedRecipes);
|
||||
|
||||
if (stats.uniqueCount === 0) {
|
||||
showToast('toast.recipes.noMissingLorasInSelection', {}, 'info');
|
||||
return;
|
||||
}
|
||||
|
||||
// Show confirmation modal
|
||||
const confirmed = await this.showConfirmationModal(stats);
|
||||
if (!confirmed) {
|
||||
return;
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Execute the download process
|
||||
* @param {Array} lorasToDownload - Array of unique LoRAs to download
|
||||
*/
|
||||
async executeDownload(lorasToDownload) {
|
||||
const totalLoras = lorasToDownload.length;
|
||||
|
||||
// Get LoRA root directory
|
||||
const loraRoot = await this.getLoraRoot();
|
||||
if (!loraRoot) {
|
||||
showToast('toast.recipes.noLoraRootConfigured', {}, 'error');
|
||||
return;
|
||||
}
|
||||
|
||||
// Generate batch download ID
|
||||
const batchDownloadId = Date.now().toString();
|
||||
|
||||
// Use default paths
|
||||
const useDefaultPaths = true;
|
||||
|
||||
// Set up WebSocket for progress updates
|
||||
const wsProtocol = window.location.protocol === 'https:' ? 'wss://' : 'ws://';
|
||||
const ws = new WebSocket(`${wsProtocol}${window.location.host}/ws/download-progress?id=${batchDownloadId}`);
|
||||
|
||||
// Show download progress UI
|
||||
const loadingManager = state.loadingManager;
|
||||
const updateProgress = loadingManager.showDownloadProgress(totalLoras);
|
||||
|
||||
let completedDownloads = 0;
|
||||
let failedDownloads = 0;
|
||||
let currentLoraProgress = 0;
|
||||
|
||||
// Set up WebSocket message handler
|
||||
ws.onmessage = (event) => {
|
||||
const data = JSON.parse(event.data);
|
||||
|
||||
// Handle download ID confirmation
|
||||
if (data.type === 'download_id') {
|
||||
console.log(`Connected to batch download progress with ID: ${data.download_id}`);
|
||||
return;
|
||||
}
|
||||
|
||||
// Process progress updates
|
||||
if (data.status === 'progress' && data.download_id && data.download_id.startsWith(batchDownloadId)) {
|
||||
currentLoraProgress = data.progress;
|
||||
|
||||
const currentLora = lorasToDownload[completedDownloads + failedDownloads];
|
||||
const loraName = currentLora ? (currentLora.name || currentLora.file_name || 'Unknown') : '';
|
||||
|
||||
const metrics = {
|
||||
bytesDownloaded: data.bytes_downloaded,
|
||||
totalBytes: data.total_bytes,
|
||||
bytesPerSecond: data.bytes_per_second
|
||||
};
|
||||
|
||||
updateProgress(currentLoraProgress, completedDownloads, loraName, metrics);
|
||||
|
||||
// Update status message
|
||||
if (currentLoraProgress < 3) {
|
||||
loadingManager.setStatus(
|
||||
translate('recipes.controls.import.startingDownload',
|
||||
{ current: completedDownloads + failedDownloads + 1, total: totalLoras },
|
||||
`Starting download for LoRA ${completedDownloads + failedDownloads + 1}/${totalLoras}`
|
||||
)
|
||||
);
|
||||
} else if (currentLoraProgress > 3 && currentLoraProgress < 100) {
|
||||
loadingManager.setStatus(
|
||||
translate('recipes.controls.import.downloadingLoras', {}, `Downloading LoRAs...`)
|
||||
);
|
||||
}
|
||||
}
|
||||
};
|
||||
|
||||
// Wait for WebSocket to connect
|
||||
await new Promise((resolve, reject) => {
|
||||
ws.onopen = resolve;
|
||||
ws.onerror = (error) => {
|
||||
console.error('WebSocket error:', error);
|
||||
reject(error);
|
||||
};
|
||||
});
|
||||
|
||||
// Download each LoRA sequentially
|
||||
for (let i = 0; i < lorasToDownload.length; i++) {
|
||||
const lora = lorasToDownload[i];
|
||||
|
||||
currentLoraProgress = 0;
|
||||
|
||||
loadingManager.setStatus(
|
||||
translate('recipes.controls.import.startingDownload',
|
||||
{ current: i + 1, total: totalLoras },
|
||||
`Starting download for LoRA ${i + 1}/${totalLoras}`
|
||||
)
|
||||
);
|
||||
updateProgress(0, completedDownloads, lora.name || lora.file_name || 'Unknown');
|
||||
|
||||
try {
|
||||
const modelId = lora.modelId || lora.model_id;
|
||||
const versionId = lora.id || lora.modelVersionId;
|
||||
|
||||
if (!modelId && !versionId) {
|
||||
console.warn(`Skipping LoRA without model/version ID:`, lora);
|
||||
failedDownloads++;
|
||||
continue;
|
||||
}
|
||||
|
||||
const response = await this.loraApiClient.downloadModel(
|
||||
modelId,
|
||||
versionId,
|
||||
loraRoot,
|
||||
'', // Empty relative path, use default paths
|
||||
useDefaultPaths,
|
||||
batchDownloadId
|
||||
);
|
||||
|
||||
if (!response.success) {
|
||||
console.error(`Failed to download LoRA ${lora.name || lora.file_name}: ${response.error}`);
|
||||
failedDownloads++;
|
||||
} else {
|
||||
completedDownloads++;
|
||||
updateProgress(100, completedDownloads, '');
|
||||
}
|
||||
} catch (error) {
|
||||
console.error(`Error downloading LoRA ${lora.name || lora.file_name}:`, error);
|
||||
failedDownloads++;
|
||||
}
|
||||
}
|
||||
|
||||
// Close WebSocket
|
||||
ws.close();
|
||||
|
||||
// Hide loading UI
|
||||
loadingManager.hide();
|
||||
|
||||
// Show completion message
|
||||
if (failedDownloads === 0) {
|
||||
showToast('toast.loras.allDownloadSuccessful', { count: completedDownloads }, 'success');
|
||||
} else {
|
||||
showToast('toast.loras.downloadPartialSuccess', {
|
||||
completed: completedDownloads,
|
||||
total: totalLoras
|
||||
}, 'warning');
|
||||
}
|
||||
|
||||
// Refresh the recipes list to update LoRA status
|
||||
if (window.recipeManager) {
|
||||
window.recipeManager.loadRecipes();
|
||||
}
|
||||
}
|
||||
|
||||
/**
|
||||
* Get LoRA root directory from API
|
||||
* @returns {Promise<string|null>} - LoRA root directory or null
|
||||
*/
|
||||
async getLoraRoot() {
|
||||
try {
|
||||
// Fetch available LoRA roots from API
|
||||
const rootsData = await this.loraApiClient.fetchModelRoots();
|
||||
|
||||
if (!rootsData || !rootsData.roots || rootsData.roots.length === 0) {
|
||||
console.error('No LoRA roots available');
|
||||
return null;
|
||||
}
|
||||
|
||||
// Try to get default root from settings
|
||||
const defaultRootKey = 'default_lora_root';
|
||||
const defaultRoot = state.global?.settings?.[defaultRootKey];
|
||||
|
||||
// If default root is set and exists in available roots, use it
|
||||
if (defaultRoot && rootsData.roots.includes(defaultRoot)) {
|
||||
return defaultRoot;
|
||||
}
|
||||
|
||||
// Otherwise, return the first available root
|
||||
return rootsData.roots[0];
|
||||
|
||||
} catch (error) {
|
||||
console.error('Error getting LoRA root:', error);
|
||||
return null;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
// Export singleton instance
|
||||
export const bulkMissingLoraDownloadManager = new BulkMissingLoraDownloadManager();
|
||||
|
||||
// Make available globally for HTML onclick handlers
|
||||
if (typeof window !== 'undefined') {
|
||||
window.bulkMissingLoraDownloadManager = bulkMissingLoraDownloadManager;
|
||||
}
|
||||
@@ -142,6 +142,28 @@ export class ImportManager {
|
||||
|
||||
// Reset duplicate related properties
|
||||
this.duplicateRecipes = [];
|
||||
|
||||
// Reset button visibility in location step
|
||||
this.resetLocationStepButtons();
|
||||
}
|
||||
|
||||
resetLocationStepButtons() {
|
||||
// Reset buttons to default state
|
||||
const locationStep = document.getElementById('locationStep');
|
||||
if (!locationStep) return;
|
||||
|
||||
const backBtn = locationStep.querySelector('.secondary-btn');
|
||||
const primaryBtn = locationStep.querySelector('.primary-btn');
|
||||
|
||||
// Back button - show
|
||||
if (backBtn) {
|
||||
backBtn.style.display = 'inline-block';
|
||||
}
|
||||
|
||||
// Primary button - reset text
|
||||
if (primaryBtn) {
|
||||
primaryBtn.textContent = translate('recipes.controls.import.downloadAndSaveRecipe', {}, 'Download & Save Recipe');
|
||||
}
|
||||
}
|
||||
|
||||
toggleImportMode(mode) {
|
||||
@@ -261,11 +283,57 @@ export class ImportManager {
|
||||
this.loadDefaultPathSetting();
|
||||
|
||||
this.updateTargetPath();
|
||||
|
||||
// Update download button with missing LoRA count (if any)
|
||||
if (this.missingLoras && this.missingLoras.length > 0) {
|
||||
this.updateDownloadButtonCount();
|
||||
this.updateImportButtonsVisibility(true);
|
||||
} else {
|
||||
this.updateImportButtonsVisibility(false);
|
||||
}
|
||||
} catch (error) {
|
||||
showToast('toast.recipes.importFailed', { message: error.message }, 'error');
|
||||
}
|
||||
}
|
||||
|
||||
updateImportButtonsVisibility(hasMissingLoras) {
|
||||
// Update primary button text based on whether there are missing LoRAs
|
||||
const locationStep = document.getElementById('locationStep');
|
||||
if (!locationStep) return;
|
||||
|
||||
const backBtn = locationStep.querySelector('.secondary-btn');
|
||||
const primaryBtn = locationStep.querySelector('.primary-btn');
|
||||
|
||||
// Back button - always show
|
||||
if (backBtn) {
|
||||
backBtn.style.display = 'inline-block';
|
||||
}
|
||||
|
||||
// Update primary button text
|
||||
if (primaryBtn) {
|
||||
const downloadCountSpan = locationStep.querySelector('#downloadLoraCount');
|
||||
if (hasMissingLoras) {
|
||||
// Rebuild button content to ensure proper structure
|
||||
const buttonText = translate('recipes.controls.import.importAndDownload', {}, 'Import & Download');
|
||||
primaryBtn.innerHTML = `${buttonText} <span id="downloadLoraCount"></span>`;
|
||||
} else {
|
||||
primaryBtn.textContent = translate('recipes.controls.import.downloadAndSaveRecipe', {}, 'Download & Save Recipe');
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
updateDownloadButtonCount() {
|
||||
// Update the download count badge on the primary button
|
||||
const locationStep = document.getElementById('locationStep');
|
||||
if (!locationStep) return;
|
||||
|
||||
const downloadCountSpan = locationStep.querySelector('#downloadLoraCount');
|
||||
if (downloadCountSpan) {
|
||||
const missingCount = this.missingLoras?.length || 0;
|
||||
downloadCountSpan.textContent = missingCount > 0 ? `(${missingCount})` : '';
|
||||
}
|
||||
}
|
||||
|
||||
backToUpload() {
|
||||
this.stepManager.showStep('uploadStep');
|
||||
|
||||
@@ -426,12 +494,54 @@ export class ImportManager {
|
||||
const modalTitle = document.querySelector('#importModal h2');
|
||||
if (modalTitle) modalTitle.textContent = translate('recipes.controls.import.downloadMissingLoras', {}, 'Download Missing LoRAs');
|
||||
|
||||
// Update the save button text
|
||||
const saveButton = document.querySelector('#locationStep .primary-btn');
|
||||
if (saveButton) saveButton.textContent = translate('recipes.controls.import.downloadMissingLoras', {}, 'Download Missing LoRAs');
|
||||
// Update button texts and show download count
|
||||
const locationStep = document.getElementById('locationStep');
|
||||
if (!locationStep) return;
|
||||
|
||||
// Hide the back button
|
||||
const backButton = document.querySelector('#locationStep .secondary-btn');
|
||||
if (backButton) backButton.style.display = 'none';
|
||||
const primaryBtn = locationStep.querySelector('.primary-btn');
|
||||
const backBtn = locationStep.querySelector('.secondary-btn');
|
||||
|
||||
// primaryBtn should be the "Import & Download" button
|
||||
if (primaryBtn) {
|
||||
const buttonText = translate('recipes.controls.import.importAndDownload', {}, 'Import & Download');
|
||||
primaryBtn.innerHTML = `${buttonText} <span id="downloadLoraCount">(${recipeData.loras?.length || 0})</span>`;
|
||||
}
|
||||
|
||||
// Hide the "Back" button in download-only mode
|
||||
if (backBtn) {
|
||||
backBtn.style.display = 'none';
|
||||
}
|
||||
}
|
||||
|
||||
saveRecipeWithoutDownload() {
|
||||
// Call save recipe with skip download flag
|
||||
return this.downloadManager.saveRecipe(true);
|
||||
}
|
||||
|
||||
async saveRecipeOnlyFromDetails() {
|
||||
// Validate recipe name first
|
||||
if (!this.recipeName) {
|
||||
showToast('toast.recipes.enterRecipeName', {}, 'error');
|
||||
return;
|
||||
}
|
||||
|
||||
// Mark deleted LoRAs as excluded
|
||||
if (this.recipeData && this.recipeData.loras) {
|
||||
this.recipeData.loras.forEach(lora => {
|
||||
if (lora.isDeleted) {
|
||||
lora.exclude = true;
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
// Update missing LoRAs list
|
||||
this.missingLoras = this.recipeData.loras.filter(lora =>
|
||||
!lora.existsLocally && !lora.isDeleted);
|
||||
|
||||
// For import only, we don't need downloadableLoRAs
|
||||
this.downloadableLoRAs = [];
|
||||
|
||||
// Save recipe without downloading
|
||||
await this.downloadManager.saveRecipe(true);
|
||||
}
|
||||
}
|
||||
|
||||
@@ -291,6 +291,19 @@ export class ModalManager {
|
||||
});
|
||||
}
|
||||
|
||||
// Register bulkDownloadMissingLorasModal
|
||||
const bulkDownloadMissingLorasModal = document.getElementById('bulkDownloadMissingLorasModal');
|
||||
if (bulkDownloadMissingLorasModal) {
|
||||
this.registerModal('bulkDownloadMissingLorasModal', {
|
||||
element: bulkDownloadMissingLorasModal,
|
||||
onClose: () => {
|
||||
this.getModal('bulkDownloadMissingLorasModal').element.style.display = 'none';
|
||||
document.body.classList.remove('modal-open');
|
||||
},
|
||||
closeOnOutsideClick: true
|
||||
});
|
||||
}
|
||||
|
||||
document.addEventListener('keydown', this.boundHandleEscape);
|
||||
this.initialized = true;
|
||||
}
|
||||
|
||||
@@ -10,6 +10,8 @@ import { validatePriorityTagString, getPriorityTagSuggestionsMap, invalidatePrio
|
||||
import { bannerService } from './BannerService.js';
|
||||
import { sidebarManager } from '../components/SidebarManager.js';
|
||||
|
||||
const VALID_MATURE_BLUR_LEVELS = new Set(['PG13', 'R', 'X', 'XXX']);
|
||||
|
||||
export class SettingsManager {
|
||||
constructor() {
|
||||
this.initialized = false;
|
||||
@@ -137,11 +139,25 @@ export class SettingsManager {
|
||||
backendSettings?.metadata_refresh_skip_paths ?? defaults.metadata_refresh_skip_paths
|
||||
);
|
||||
|
||||
merged.mature_blur_level = this.normalizeMatureBlurLevel(
|
||||
backendSettings?.mature_blur_level ?? defaults.mature_blur_level
|
||||
);
|
||||
|
||||
Object.keys(merged).forEach(key => this.backendSettingKeys.add(key));
|
||||
|
||||
return merged;
|
||||
}
|
||||
|
||||
normalizeMatureBlurLevel(value) {
|
||||
if (typeof value === 'string') {
|
||||
const normalized = value.trim().toUpperCase();
|
||||
if (VALID_MATURE_BLUR_LEVELS.has(normalized)) {
|
||||
return normalized;
|
||||
}
|
||||
}
|
||||
return 'R';
|
||||
}
|
||||
|
||||
normalizePatternList(value) {
|
||||
if (Array.isArray(value)) {
|
||||
const sanitized = value
|
||||
@@ -682,6 +698,13 @@ export class SettingsManager {
|
||||
showOnlySFWCheckbox.checked = state.global.settings.show_only_sfw ?? false;
|
||||
}
|
||||
|
||||
const matureBlurLevelSelect = document.getElementById('matureBlurLevel');
|
||||
if (matureBlurLevelSelect) {
|
||||
matureBlurLevelSelect.value = this.normalizeMatureBlurLevel(
|
||||
state.global.settings.mature_blur_level
|
||||
);
|
||||
}
|
||||
|
||||
const usePortableCheckbox = document.getElementById('usePortableSettings');
|
||||
if (usePortableCheckbox) {
|
||||
usePortableCheckbox.checked = !!state.global.settings.use_portable_settings;
|
||||
@@ -1811,7 +1834,9 @@ export class SettingsManager {
|
||||
const element = document.getElementById(elementId);
|
||||
if (!element) return;
|
||||
|
||||
const value = element.value;
|
||||
const value = settingKey === 'mature_blur_level'
|
||||
? this.normalizeMatureBlurLevel(element.value)
|
||||
: element.value;
|
||||
|
||||
try {
|
||||
// Update frontend state with mapped keys
|
||||
@@ -1834,7 +1859,12 @@ export class SettingsManager {
|
||||
|
||||
showToast('toast.settings.settingsUpdated', { setting: settingKey.replace(/_/g, ' ') }, 'success');
|
||||
|
||||
if (settingKey === 'model_name_display' || settingKey === 'model_card_footer_action' || settingKey === 'update_flag_strategy') {
|
||||
if (
|
||||
settingKey === 'model_name_display'
|
||||
|| settingKey === 'model_card_footer_action'
|
||||
|| settingKey === 'update_flag_strategy'
|
||||
|| settingKey === 'mature_blur_level'
|
||||
) {
|
||||
this.reloadContent();
|
||||
}
|
||||
} catch (error) {
|
||||
|
||||
@@ -9,7 +9,7 @@ export class DownloadManager {
|
||||
this.importManager = importManager;
|
||||
}
|
||||
|
||||
async saveRecipe() {
|
||||
async saveRecipe(skipDownload = false) {
|
||||
// Check if we're in download-only mode (for existing recipe)
|
||||
const isDownloadOnly = !!this.importManager.recipeId;
|
||||
|
||||
@@ -20,7 +20,10 @@ export class DownloadManager {
|
||||
|
||||
try {
|
||||
// Show progress indicator
|
||||
this.importManager.loadingManager.showSimpleLoading(isDownloadOnly ? translate('recipes.controls.import.downloadingLoras', {}, 'Downloading LoRAs...') : translate('recipes.controls.import.savingRecipe', {}, 'Saving recipe...'));
|
||||
const loadingMessage = skipDownload
|
||||
? translate('recipes.controls.import.savingRecipe', {}, 'Saving recipe...')
|
||||
: (isDownloadOnly ? translate('recipes.controls.import.downloadingLoras', {}, 'Downloading LoRAs...') : translate('recipes.controls.import.savingRecipe', {}, 'Saving recipe...'));
|
||||
this.importManager.loadingManager.showSimpleLoading(loadingMessage);
|
||||
|
||||
// Only send the complete recipe to save if not in download-only mode
|
||||
if (!isDownloadOnly) {
|
||||
@@ -98,15 +101,17 @@ export class DownloadManager {
|
||||
}
|
||||
}
|
||||
|
||||
// Check if we need to download LoRAs
|
||||
// Check if we need to download LoRAs (skip if skipDownload is true)
|
||||
let failedDownloads = 0;
|
||||
if (this.importManager.downloadableLoRAs && this.importManager.downloadableLoRAs.length > 0) {
|
||||
if (!skipDownload && this.importManager.downloadableLoRAs && this.importManager.downloadableLoRAs.length > 0) {
|
||||
await this.downloadMissingLoras();
|
||||
}
|
||||
|
||||
// Show success message
|
||||
if (isDownloadOnly) {
|
||||
if (failedDownloads === 0) {
|
||||
if (skipDownload) {
|
||||
showToast('toast.recipes.recipeSaved', {}, 'success');
|
||||
} else if (failedDownloads === 0) {
|
||||
showToast('toast.loras.downloadSuccessful', {}, 'success');
|
||||
}
|
||||
} else {
|
||||
|
||||
@@ -325,7 +325,8 @@ export class RecipeDataManager {
|
||||
}
|
||||
|
||||
updateNextButtonState() {
|
||||
const nextButton = document.querySelector('#detailsStep .primary-btn');
|
||||
const nextButton = document.getElementById('nextBtn');
|
||||
const importOnlyBtn = document.getElementById('importOnlyBtn');
|
||||
const actionsContainer = document.querySelector('#detailsStep .modal-actions');
|
||||
if (!nextButton || !actionsContainer) return;
|
||||
|
||||
@@ -365,7 +366,7 @@ export class RecipeDataManager {
|
||||
buttonsContainer.parentNode.insertBefore(warningContainer, buttonsContainer);
|
||||
}
|
||||
|
||||
// Check for duplicates but don't change button actions
|
||||
// Check for downloadable missing LoRAs
|
||||
const missingNotDeleted = this.importManager.recipeData.loras.filter(
|
||||
lora => !lora.existsLocally && !lora.isDeleted
|
||||
).length;
|
||||
@@ -374,8 +375,16 @@ export class RecipeDataManager {
|
||||
nextButton.classList.remove('warning-btn');
|
||||
|
||||
if (missingNotDeleted > 0) {
|
||||
nextButton.textContent = translate('recipes.controls.import.downloadMissingLoras', {}, 'Download Missing LoRAs');
|
||||
// Show import only button and update primary button
|
||||
if (importOnlyBtn) {
|
||||
importOnlyBtn.style.display = 'inline-block';
|
||||
}
|
||||
nextButton.textContent = translate('recipes.controls.import.importAndDownload', {}, 'Import & Download') + ` (${missingNotDeleted})`;
|
||||
} else {
|
||||
// Hide import only button and show save recipe
|
||||
if (importOnlyBtn) {
|
||||
importOnlyBtn.style.display = 'none';
|
||||
}
|
||||
nextButton.textContent = translate('recipes.controls.import.saveRecipe', {}, 'Save Recipe');
|
||||
}
|
||||
}
|
||||
@@ -440,8 +449,11 @@ export class RecipeDataManager {
|
||||
// Store only downloadable LoRAs for the download step
|
||||
this.importManager.downloadableLoRAs = this.importManager.missingLoras;
|
||||
this.importManager.proceedToLocation();
|
||||
} else if (this.importManager.missingLoras.length === 0 && this.importManager.recipeData.loras.some(l => !l.existsLocally)) {
|
||||
// All missing LoRAs are deleted, save recipe without download
|
||||
this.importManager.saveRecipe();
|
||||
} else {
|
||||
// Otherwise, save the recipe directly
|
||||
// No missing LoRAs at all, save the recipe directly
|
||||
this.importManager.saveRecipe();
|
||||
}
|
||||
}
|
||||
|
||||
@@ -24,6 +24,7 @@ const DEFAULT_SETTINGS_BASE = Object.freeze({
|
||||
optimize_example_images: true,
|
||||
auto_download_example_images: false,
|
||||
blur_mature_content: true,
|
||||
mature_blur_level: 'R',
|
||||
autoplay_on_hover: false,
|
||||
display_density: 'default',
|
||||
card_info_display: 'always',
|
||||
|
||||
@@ -309,6 +309,15 @@ export const NSFW_LEVELS = {
|
||||
BLOCKED: 32
|
||||
};
|
||||
|
||||
export const VALID_MATURE_BLUR_LEVELS = ['PG13', 'R', 'X', 'XXX'];
|
||||
|
||||
export function getMatureBlurThreshold(settings = {}) {
|
||||
const rawValue = settings?.mature_blur_level;
|
||||
const normalizedValue = typeof rawValue === 'string' ? rawValue.trim().toUpperCase() : '';
|
||||
const levelName = VALID_MATURE_BLUR_LEVELS.includes(normalizedValue) ? normalizedValue : 'R';
|
||||
return NSFW_LEVELS[levelName] ?? NSFW_LEVELS.R;
|
||||
}
|
||||
|
||||
// Node type constants
|
||||
export const NODE_TYPES = {
|
||||
LORA_LOADER: 1,
|
||||
|
||||
@@ -87,6 +87,9 @@
|
||||
<i class="fas fa-redo"></i> <span>{{ t('loras.bulkOperations.resumeMetadataRefresh') }}</span>
|
||||
</div>
|
||||
<div class="context-menu-separator"></div>
|
||||
<div class="context-menu-item" data-action="download-missing-loras">
|
||||
<i class="fas fa-download"></i> <span>{{ t('loras.bulkOperations.downloadMissingLoras') }}</span>
|
||||
</div>
|
||||
<div class="context-menu-item" data-action="move-all">
|
||||
<i class="fas fa-folder-open"></i> <span>{{ t('loras.bulkOperations.moveAll') }}</span>
|
||||
</div>
|
||||
|
||||
@@ -92,9 +92,10 @@
|
||||
<!-- Duplicate recipes will be populated here -->
|
||||
</div>
|
||||
|
||||
<div class="modal-actions">
|
||||
<div class="modal-actions" id="detailsStepActions">
|
||||
<button class="secondary-btn" onclick="importManager.backToUpload()">{{ t('common.actions.back') }}</button>
|
||||
<button class="primary-btn" onclick="importManager.proceedFromDetails()">{{ t('common.actions.next') }}</button>
|
||||
<button class="secondary-btn" id="importOnlyBtn" onclick="importManager.saveRecipeOnlyFromDetails()" style="display: none;">{{ t('recipes.controls.import.importRecipeOnly') }}</button>
|
||||
<button class="primary-btn" id="nextBtn" onclick="importManager.proceedFromDetails()">{{ t('common.actions.next') }}</button>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -159,7 +160,7 @@
|
||||
|
||||
<div class="modal-actions">
|
||||
<button class="secondary-btn" onclick="importManager.backToDetails()">{{ t('common.actions.back') }}</button>
|
||||
<button class="primary-btn" onclick="importManager.saveRecipe()">{{ t('recipes.controls.import.downloadAndSaveRecipe') }}</button>
|
||||
<button class="primary-btn" onclick="importManager.saveRecipe()">{{ t('recipes.controls.import.importAndDownload') }} <span id="downloadLoraCount"></span></button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
@@ -81,3 +81,31 @@
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Bulk Download Missing LoRAs Confirmation Modal -->
|
||||
<div id="bulkDownloadMissingLorasModal" class="modal">
|
||||
<div class="modal-content">
|
||||
<div class="modal-header">
|
||||
<h2>{{ t('modals.bulkDownloadMissingLoras.title') }}</h2>
|
||||
<span class="close" onclick="modalManager.closeModal('bulkDownloadMissingLorasModal')">×</span>
|
||||
</div>
|
||||
<div class="modal-body">
|
||||
<p class="confirmation-message" id="bulkDownloadMissingLorasMessage"></p>
|
||||
<div class="bulk-download-loras-preview" id="bulkDownloadMissingLorasPreview">
|
||||
<p class="preview-title">{{ t('modals.bulkDownloadMissingLoras.previewTitle') }}</p>
|
||||
<ul class="bulk-download-loras-list" id="bulkDownloadMissingLorasList"></ul>
|
||||
</div>
|
||||
<p class="confirmation-note">
|
||||
<i class="fas fa-info-circle"></i>
|
||||
{{ t('modals.bulkDownloadMissingLoras.note') }}
|
||||
</p>
|
||||
</div>
|
||||
<div class="modal-actions">
|
||||
<button class="secondary-btn" onclick="modalManager.closeModal('bulkDownloadMissingLorasModal')">{{ t('common.actions.cancel') }}</button>
|
||||
<button class="primary-btn" id="bulkDownloadMissingLorasConfirmBtn" onclick="bulkMissingLoraDownloadManager.confirmDownload()">
|
||||
<i class="fas fa-download"></i>
|
||||
{{ t('modals.bulkDownloadMissingLoras.downloadButton') }}
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
@@ -281,6 +281,26 @@
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<div class="setting-item">
|
||||
<div class="setting-row">
|
||||
<div class="setting-info">
|
||||
<label for="matureBlurLevel">
|
||||
{{ t('settings.contentFiltering.matureBlurThreshold') }}
|
||||
<i class="fas fa-info-circle info-icon" data-tooltip="{{ t('settings.contentFiltering.matureBlurThresholdHelp') }}"></i>
|
||||
</label>
|
||||
</div>
|
||||
<div class="setting-control select-control">
|
||||
<select id="matureBlurLevel"
|
||||
onchange="settingsManager.saveSelectSetting('matureBlurLevel', 'mature_blur_level')">
|
||||
<option value="PG13">{{ t('settings.contentFiltering.matureBlurThresholdOptions.pg13') }}</option>
|
||||
<option value="R">{{ t('settings.contentFiltering.matureBlurThresholdOptions.r') }}</option>
|
||||
<option value="X">{{ t('settings.contentFiltering.matureBlurThresholdOptions.x') }}</option>
|
||||
<option value="XXX">{{ t('settings.contentFiltering.matureBlurThresholdOptions.xxx') }}</option>
|
||||
</select>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Video Settings -->
|
||||
|
||||
@@ -15,7 +15,8 @@ describe('state module', () => {
|
||||
expect(defaultSettings).toMatchObject({
|
||||
civitai_api_key: '',
|
||||
language: 'en',
|
||||
blur_mature_content: true
|
||||
blur_mature_content: true,
|
||||
mature_blur_level: 'R'
|
||||
});
|
||||
|
||||
expect(defaultSettings.download_path_templates).toEqual(DEFAULT_PATH_TEMPLATES);
|
||||
|
||||
18
tests/frontend/utils/constants.matureBlurThreshold.test.js
Normal file
18
tests/frontend/utils/constants.matureBlurThreshold.test.js
Normal file
@@ -0,0 +1,18 @@
|
||||
import { describe, expect, it } from 'vitest';
|
||||
|
||||
import { NSFW_LEVELS, getMatureBlurThreshold } from '../../../static/js/utils/constants.js';
|
||||
|
||||
describe('getMatureBlurThreshold', () => {
|
||||
it('returns configured PG13 threshold', () => {
|
||||
expect(getMatureBlurThreshold({ mature_blur_level: 'PG13' })).toBe(NSFW_LEVELS.PG13);
|
||||
});
|
||||
|
||||
it('normalizes lowercase values', () => {
|
||||
expect(getMatureBlurThreshold({ mature_blur_level: 'x' })).toBe(NSFW_LEVELS.X);
|
||||
});
|
||||
|
||||
it('falls back to R when value is invalid or missing', () => {
|
||||
expect(getMatureBlurThreshold({ mature_blur_level: 'invalid' })).toBe(NSFW_LEVELS.R);
|
||||
expect(getMatureBlurThreshold({})).toBe(NSFW_LEVELS.R);
|
||||
});
|
||||
});
|
||||
@@ -194,6 +194,7 @@ class TestCacheHealthMonitor:
|
||||
'preview_nsfw_level': 0,
|
||||
'notes': '',
|
||||
'usage_tips': '',
|
||||
'hash_status': 'completed',
|
||||
}
|
||||
incomplete_entry = {
|
||||
'file_path': '/models/test2.safetensors',
|
||||
|
||||
@@ -484,9 +484,11 @@ async def test_get_model_version_info_success(monkeypatch, downloader):
|
||||
assert result["images"][0]["meta"]["other"] == "keep"
|
||||
|
||||
|
||||
async def test_get_image_info_returns_first_item(monkeypatch, downloader):
|
||||
async def test_get_image_info_returns_matching_item(monkeypatch, downloader):
|
||||
"""When API returns multiple items, return the one matching the requested ID."""
|
||||
async def fake_make_request(method, url, use_auth=True, **kwargs):
|
||||
return True, {"items": [{"id": 1}, {"id": 2}]}
|
||||
# Requested ID is 42, but it's the second item in the response
|
||||
return True, {"items": [{"id": 41}, {"id": 42, "name": "target"}, {"id": 43}]}
|
||||
|
||||
downloader.make_request = fake_make_request
|
||||
|
||||
@@ -494,7 +496,25 @@ async def test_get_image_info_returns_first_item(monkeypatch, downloader):
|
||||
|
||||
result = await client.get_image_info("42")
|
||||
|
||||
assert result == {"id": 1}
|
||||
assert result == {"id": 42, "name": "target"}
|
||||
|
||||
|
||||
async def test_get_image_info_returns_none_when_id_mismatch(monkeypatch, downloader, caplog):
|
||||
"""When API returns items but none match the requested ID, return None and log warning."""
|
||||
async def fake_make_request(method, url, use_auth=True, **kwargs):
|
||||
# Requested ID is 999, but API returns different IDs (simulating deleted/hidden image)
|
||||
return True, {"items": [{"id": 1}, {"id": 2}, {"id": 3}]}
|
||||
|
||||
downloader.make_request = fake_make_request
|
||||
|
||||
client = await CivitaiClient.get_instance()
|
||||
|
||||
result = await client.get_image_info("999")
|
||||
|
||||
assert result is None
|
||||
# Verify warning was logged
|
||||
assert "CivitAI API returned no matching image for requested ID 999" in caplog.text
|
||||
assert "Returned 3 item(s) with IDs: [1, 2, 3]" in caplog.text
|
||||
|
||||
|
||||
async def test_get_image_info_handles_missing(monkeypatch, downloader):
|
||||
@@ -508,3 +528,13 @@ async def test_get_image_info_handles_missing(monkeypatch, downloader):
|
||||
result = await client.get_image_info("42")
|
||||
|
||||
assert result is None
|
||||
|
||||
|
||||
async def test_get_image_info_handles_invalid_id(monkeypatch, downloader, caplog):
|
||||
"""When given a non-numeric image ID, return None and log error."""
|
||||
client = await CivitaiClient.get_instance()
|
||||
|
||||
result = await client.get_image_info("not-a-number")
|
||||
|
||||
assert result is None
|
||||
assert "Invalid image ID format" in caplog.text
|
||||
|
||||
@@ -281,8 +281,6 @@ async def test_execute_download_extracts_zip_single_model(monkeypatch, tmp_path)
|
||||
DownloadManager, "_get_lora_scanner", AsyncMock(return_value=dummy_scanner)
|
||||
)
|
||||
monkeypatch.setattr(MetadataManager, "save_metadata", AsyncMock(return_value=True))
|
||||
hash_calculator = AsyncMock(return_value="hash-single")
|
||||
monkeypatch.setattr(download_manager, "calculate_sha256", hash_calculator)
|
||||
|
||||
result = await manager._execute_download(
|
||||
download_urls=download_urls,
|
||||
@@ -299,10 +297,10 @@ async def test_execute_download_extracts_zip_single_model(monkeypatch, tmp_path)
|
||||
assert not zip_path.exists()
|
||||
extracted = save_dir / "model.safetensors"
|
||||
assert extracted.exists()
|
||||
assert hash_calculator.await_args.args[0] == str(extracted)
|
||||
saved_call = MetadataManager.save_metadata.await_args
|
||||
assert saved_call.args[0] == str(extracted)
|
||||
assert saved_call.args[1].sha256 == "hash-single"
|
||||
# SHA256 comes from metadata (API value), not recalculated
|
||||
assert saved_call.args[1].sha256 == "sha256"
|
||||
assert dummy_scanner.add_model_to_cache.await_count == 1
|
||||
|
||||
|
||||
@@ -351,8 +349,6 @@ async def test_execute_download_extracts_zip_multiple_models(monkeypatch, tmp_pa
|
||||
DownloadManager, "_get_lora_scanner", AsyncMock(return_value=dummy_scanner)
|
||||
)
|
||||
monkeypatch.setattr(MetadataManager, "save_metadata", AsyncMock(return_value=True))
|
||||
hash_calculator = AsyncMock(side_effect=["hash-one", "hash-two"])
|
||||
monkeypatch.setattr(download_manager, "calculate_sha256", hash_calculator)
|
||||
|
||||
result = await manager._execute_download(
|
||||
download_urls=download_urls,
|
||||
@@ -372,15 +368,15 @@ async def test_execute_download_extracts_zip_multiple_models(monkeypatch, tmp_pa
|
||||
assert extracted_one.exists()
|
||||
assert extracted_two.exists()
|
||||
|
||||
assert hash_calculator.await_count == 2
|
||||
assert MetadataManager.save_metadata.await_count == 2
|
||||
assert dummy_scanner.add_model_to_cache.await_count == 2
|
||||
|
||||
metadata_calls = MetadataManager.save_metadata.await_args_list
|
||||
assert metadata_calls[0].args[0] == str(extracted_one)
|
||||
assert metadata_calls[0].args[1].sha256 == "hash-one"
|
||||
# SHA256 comes from metadata (API value), not recalculated
|
||||
assert metadata_calls[0].args[1].sha256 == "sha256"
|
||||
assert metadata_calls[1].args[0] == str(extracted_two)
|
||||
assert metadata_calls[1].args[1].sha256 == "hash-two"
|
||||
assert metadata_calls[1].args[1].sha256 == "sha256"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@@ -427,8 +423,6 @@ async def test_execute_download_extracts_zip_pt_embedding(monkeypatch, tmp_path)
|
||||
ServiceRegistry, "get_embedding_scanner", AsyncMock(return_value=dummy_scanner)
|
||||
)
|
||||
monkeypatch.setattr(MetadataManager, "save_metadata", AsyncMock(return_value=True))
|
||||
hash_calculator = AsyncMock(return_value="hash-pt")
|
||||
monkeypatch.setattr(download_manager, "calculate_sha256", hash_calculator)
|
||||
|
||||
result = await manager._execute_download(
|
||||
download_urls=download_urls,
|
||||
@@ -445,10 +439,10 @@ async def test_execute_download_extracts_zip_pt_embedding(monkeypatch, tmp_path)
|
||||
assert not zip_path.exists()
|
||||
extracted = save_dir / "embedding.pt"
|
||||
assert extracted.exists()
|
||||
assert hash_calculator.await_args.args[0] == str(extracted)
|
||||
saved_call = MetadataManager.save_metadata.await_args
|
||||
assert saved_call.args[0] == str(extracted)
|
||||
assert saved_call.args[1].sha256 == "hash-pt"
|
||||
# SHA256 comes from metadata (API value), not recalculated
|
||||
assert saved_call.args[1].sha256 == "sha256"
|
||||
assert dummy_scanner.add_model_to_cache.await_count == 1
|
||||
|
||||
|
||||
|
||||
@@ -9,7 +9,11 @@ from unittest.mock import AsyncMock, patch, MagicMock
|
||||
|
||||
import aiohttp
|
||||
|
||||
from py.services.downloader import Downloader, DownloadStalledError, DownloadRestartRequested
|
||||
from py.services.downloader import (
|
||||
Downloader,
|
||||
DownloadStalledError,
|
||||
DownloadRestartRequested,
|
||||
)
|
||||
|
||||
|
||||
class TestDownloadStreamControl:
|
||||
@@ -118,6 +122,7 @@ class TestDownloaderConfiguration:
|
||||
return instance1, instance2
|
||||
|
||||
import asyncio
|
||||
|
||||
instance1, instance2 = asyncio.run(get_instances())
|
||||
|
||||
assert instance1 is instance2
|
||||
@@ -131,7 +136,7 @@ class TestDownloaderConfiguration:
|
||||
|
||||
downloader = Downloader()
|
||||
|
||||
assert downloader.chunk_size == 4 * 1024 * 1024 # 4MB
|
||||
assert downloader.chunk_size == 16 * 1024 * 1024 # 16MB
|
||||
assert downloader.max_retries == 5
|
||||
assert downloader.base_delay == 2.0
|
||||
assert downloader.session_timeout == 300
|
||||
@@ -145,9 +150,9 @@ class TestDownloaderConfiguration:
|
||||
|
||||
downloader = Downloader()
|
||||
|
||||
assert 'User-Agent' in downloader.default_headers
|
||||
assert 'ComfyUI-LoRA-Manager' in downloader.default_headers['User-Agent']
|
||||
assert downloader.default_headers['Accept-Encoding'] == 'identity'
|
||||
assert "User-Agent" in downloader.default_headers
|
||||
assert "ComfyUI-LoRA-Manager" in downloader.default_headers["User-Agent"]
|
||||
assert downloader.default_headers["Accept-Encoding"] == "identity"
|
||||
|
||||
# Cleanup
|
||||
Downloader._instance = None
|
||||
@@ -204,7 +209,10 @@ class TestDownloaderExceptions:
|
||||
with pytest.raises(DownloadRestartRequested) as exc_info:
|
||||
raise DownloadRestartRequested("Reconnect requested after resume")
|
||||
|
||||
assert "reconnect" in str(exc_info.value).lower() or "restart" in str(exc_info.value).lower()
|
||||
assert (
|
||||
"reconnect" in str(exc_info.value).lower()
|
||||
or "restart" in str(exc_info.value).lower()
|
||||
)
|
||||
|
||||
|
||||
class TestDownloaderAuthHeaders:
|
||||
@@ -217,8 +225,8 @@ class TestDownloaderAuthHeaders:
|
||||
|
||||
headers = downloader._get_auth_headers(use_auth=False)
|
||||
|
||||
assert 'User-Agent' in headers
|
||||
assert 'Authorization' not in headers
|
||||
assert "User-Agent" in headers
|
||||
assert "Authorization" not in headers
|
||||
|
||||
Downloader._instance = None
|
||||
|
||||
@@ -231,12 +239,14 @@ class TestDownloaderAuthHeaders:
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.get.return_value = None
|
||||
|
||||
with patch('py.services.downloader.get_settings_manager', return_value=mock_settings):
|
||||
with patch(
|
||||
"py.services.downloader.get_settings_manager", return_value=mock_settings
|
||||
):
|
||||
headers = downloader._get_auth_headers(use_auth=True)
|
||||
|
||||
# Should still have User-Agent but no Authorization
|
||||
assert 'User-Agent' in headers
|
||||
assert 'Authorization' not in headers
|
||||
assert "User-Agent" in headers
|
||||
assert "Authorization" not in headers
|
||||
|
||||
Downloader._instance = None
|
||||
|
||||
@@ -249,14 +259,16 @@ class TestDownloaderAuthHeaders:
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.get.return_value = "test-api-key-12345"
|
||||
|
||||
with patch('py.services.downloader.get_settings_manager', return_value=mock_settings):
|
||||
with patch(
|
||||
"py.services.downloader.get_settings_manager", return_value=mock_settings
|
||||
):
|
||||
headers = downloader._get_auth_headers(use_auth=True)
|
||||
|
||||
# Should have both User-Agent and Authorization
|
||||
assert 'User-Agent' in headers
|
||||
assert 'Authorization' in headers
|
||||
assert 'test-api-key-12345' in headers['Authorization']
|
||||
assert headers['Content-Type'] == 'application/json'
|
||||
assert "User-Agent" in headers
|
||||
assert "Authorization" in headers
|
||||
assert "test-api-key-12345" in headers["Authorization"]
|
||||
assert headers["Content-Type"] == "application/json"
|
||||
|
||||
Downloader._instance = None
|
||||
|
||||
@@ -286,6 +298,7 @@ class TestDownloaderSessionManagement:
|
||||
|
||||
# Mock datetime to return current time
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
current_time = datetime.now()
|
||||
downloader._session_created_at = current_time
|
||||
|
||||
@@ -301,6 +314,7 @@ class TestDownloaderSessionManagement:
|
||||
|
||||
# Simulate an old session (older than timeout)
|
||||
from datetime import datetime, timedelta
|
||||
|
||||
old_time = datetime.now() - timedelta(seconds=downloader.session_timeout + 1)
|
||||
downloader._session_created_at = old_time
|
||||
downloader._session = MagicMock()
|
||||
|
||||
@@ -369,3 +369,289 @@ async def test_pool_filter_combined_all_filters(lora_service):
|
||||
# - tags: tag1 ✓
|
||||
assert len(filtered) == 1
|
||||
assert filtered[0]["file_name"] == "match_all.safetensors"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_pool_filter_name_patterns_include_text(lora_service):
|
||||
"""Test filtering by name patterns with text matching (useRegex=False)."""
|
||||
sample_loras = [
|
||||
{
|
||||
"file_name": "character_anime_v1.safetensors",
|
||||
"model_name": "Anime Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "character_realistic_v1.safetensors",
|
||||
"model_name": "Realistic Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "style_watercolor_v1.safetensors",
|
||||
"model_name": "Watercolor Style",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
]
|
||||
|
||||
# Test include patterns with text matching
|
||||
pool_config = {
|
||||
"baseModels": [],
|
||||
"tags": {"include": [], "exclude": []},
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
"namePatterns": {"include": ["character"], "exclude": [], "useRegex": False},
|
||||
}
|
||||
|
||||
filtered = await lora_service._apply_pool_filters(sample_loras, pool_config)
|
||||
assert len(filtered) == 2
|
||||
file_names = {lora["file_name"] for lora in filtered}
|
||||
assert file_names == {
|
||||
"character_anime_v1.safetensors",
|
||||
"character_realistic_v1.safetensors",
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_pool_filter_name_patterns_exclude_text(lora_service):
|
||||
"""Test excluding by name patterns with text matching (useRegex=False)."""
|
||||
sample_loras = [
|
||||
{
|
||||
"file_name": "character_anime_v1.safetensors",
|
||||
"model_name": "Anime Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "character_realistic_v1.safetensors",
|
||||
"model_name": "Realistic Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "style_watercolor_v1.safetensors",
|
||||
"model_name": "Watercolor Style",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
]
|
||||
|
||||
# Test exclude patterns with text matching
|
||||
pool_config = {
|
||||
"baseModels": [],
|
||||
"tags": {"include": [], "exclude": []},
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
"namePatterns": {"include": [], "exclude": ["anime"], "useRegex": False},
|
||||
}
|
||||
|
||||
filtered = await lora_service._apply_pool_filters(sample_loras, pool_config)
|
||||
assert len(filtered) == 2
|
||||
file_names = {lora["file_name"] for lora in filtered}
|
||||
assert file_names == {
|
||||
"character_realistic_v1.safetensors",
|
||||
"style_watercolor_v1.safetensors",
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_pool_filter_name_patterns_include_regex(lora_service):
|
||||
"""Test filtering by name patterns with regex matching (useRegex=True)."""
|
||||
sample_loras = [
|
||||
{
|
||||
"file_name": "character_anime_v1.safetensors",
|
||||
"model_name": "Anime Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "character_realistic_v1.safetensors",
|
||||
"model_name": "Realistic Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "style_watercolor_v1.safetensors",
|
||||
"model_name": "Watercolor Style",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
]
|
||||
|
||||
# Test include patterns with regex matching - match files starting with "character_"
|
||||
pool_config = {
|
||||
"baseModels": [],
|
||||
"tags": {"include": [], "exclude": []},
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
"namePatterns": {"include": ["^character_"], "exclude": [], "useRegex": True},
|
||||
}
|
||||
|
||||
filtered = await lora_service._apply_pool_filters(sample_loras, pool_config)
|
||||
assert len(filtered) == 2
|
||||
file_names = {lora["file_name"] for lora in filtered}
|
||||
assert file_names == {
|
||||
"character_anime_v1.safetensors",
|
||||
"character_realistic_v1.safetensors",
|
||||
}
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_pool_filter_name_patterns_exclude_regex(lora_service):
|
||||
"""Test excluding by name patterns with regex matching (useRegex=True)."""
|
||||
sample_loras = [
|
||||
{
|
||||
"file_name": "character_anime_v1.safetensors",
|
||||
"model_name": "Anime Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "character_realistic_v1.safetensors",
|
||||
"model_name": "Realistic Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "style_watercolor_v1.safetensors",
|
||||
"model_name": "Watercolor Style",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
]
|
||||
|
||||
# Test exclude patterns with regex matching - exclude files ending with "_v1.safetensors"
|
||||
pool_config = {
|
||||
"baseModels": [],
|
||||
"tags": {"include": [], "exclude": []},
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
"namePatterns": {
|
||||
"include": [],
|
||||
"exclude": ["_v1\\.safetensors$"],
|
||||
"useRegex": True,
|
||||
},
|
||||
}
|
||||
|
||||
filtered = await lora_service._apply_pool_filters(sample_loras, pool_config)
|
||||
assert len(filtered) == 0 # All files match the exclude pattern
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_pool_filter_name_patterns_combined(lora_service):
|
||||
"""Test combining include and exclude name patterns."""
|
||||
sample_loras = [
|
||||
{
|
||||
"file_name": "character_anime_v1.safetensors",
|
||||
"model_name": "Anime Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "character_realistic_v1.safetensors",
|
||||
"model_name": "Realistic Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "style_watercolor_v1.safetensors",
|
||||
"model_name": "Watercolor Style",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
]
|
||||
|
||||
# Test include "character" but exclude "anime"
|
||||
pool_config = {
|
||||
"baseModels": [],
|
||||
"tags": {"include": [], "exclude": []},
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
"namePatterns": {
|
||||
"include": ["character"],
|
||||
"exclude": ["anime"],
|
||||
"useRegex": False,
|
||||
},
|
||||
}
|
||||
|
||||
filtered = await lora_service._apply_pool_filters(sample_loras, pool_config)
|
||||
assert len(filtered) == 1
|
||||
assert filtered[0]["file_name"] == "character_realistic_v1.safetensors"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_pool_filter_name_patterns_model_name_fallback(lora_service):
|
||||
"""Test that name pattern filtering falls back to model_name when file_name doesn't match."""
|
||||
sample_loras = [
|
||||
{
|
||||
"file_name": "abc123.safetensors",
|
||||
"model_name": "Super Anime Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
{
|
||||
"file_name": "def456.safetensors",
|
||||
"model_name": "Realistic Portrait",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
]
|
||||
|
||||
# Should match model_name even if file_name doesn't contain the pattern
|
||||
pool_config = {
|
||||
"baseModels": [],
|
||||
"tags": {"include": [], "exclude": []},
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
"namePatterns": {"include": ["anime"], "exclude": [], "useRegex": False},
|
||||
}
|
||||
|
||||
filtered = await lora_service._apply_pool_filters(sample_loras, pool_config)
|
||||
assert len(filtered) == 1
|
||||
assert filtered[0]["file_name"] == "abc123.safetensors"
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_pool_filter_name_patterns_invalid_regex(lora_service):
|
||||
"""Test that invalid regex falls back to substring matching."""
|
||||
sample_loras = [
|
||||
{
|
||||
"file_name": "character_anime[test]_v1.safetensors",
|
||||
"model_name": "Anime Character",
|
||||
"base_model": "Illustrious",
|
||||
"folder": "",
|
||||
"license_flags": build_license_flags(None),
|
||||
},
|
||||
]
|
||||
|
||||
# Invalid regex pattern (unclosed character class) should fall back to substring matching
|
||||
# The pattern "anime[" is invalid regex but valid substring - it exists in the filename
|
||||
pool_config = {
|
||||
"baseModels": [],
|
||||
"tags": {"include": [], "exclude": []},
|
||||
"folders": {"include": [], "exclude": []},
|
||||
"license": {"noCreditRequired": False, "allowSelling": False},
|
||||
"namePatterns": {"include": ["anime["], "exclude": [], "useRegex": True},
|
||||
}
|
||||
|
||||
# Should not crash and should match using substring fallback
|
||||
filtered = await lora_service._apply_pool_filters(sample_loras, pool_config)
|
||||
assert len(filtered) == 1 # Substring match works even with invalid regex
|
||||
|
||||
@@ -492,7 +492,7 @@ async def test_analyze_remote_video(tmp_path):
|
||||
|
||||
class DummyFactory:
|
||||
def create_parser(self, metadata):
|
||||
async def parse_metadata(m, recipe_scanner):
|
||||
async def parse_metadata(m, recipe_scanner=None, civitai_client=None):
|
||||
return {"loras": []}
|
||||
return SimpleNamespace(parse_metadata=parse_metadata)
|
||||
|
||||
|
||||
@@ -265,6 +265,32 @@ def test_delete_setting(manager):
|
||||
assert manager.get("example") is None
|
||||
|
||||
|
||||
def test_missing_mature_blur_level_defaults_to_r(tmp_path, monkeypatch):
|
||||
manager = _create_manager_with_settings(
|
||||
tmp_path,
|
||||
monkeypatch,
|
||||
{
|
||||
"blur_mature_content": True,
|
||||
"folder_paths": {},
|
||||
},
|
||||
)
|
||||
|
||||
assert manager.get("mature_blur_level") == "R"
|
||||
|
||||
|
||||
def test_invalid_mature_blur_level_is_normalized_to_r(tmp_path, monkeypatch):
|
||||
manager = _create_manager_with_settings(
|
||||
tmp_path,
|
||||
monkeypatch,
|
||||
{
|
||||
"mature_blur_level": "unsafe",
|
||||
"folder_paths": {},
|
||||
},
|
||||
)
|
||||
|
||||
assert manager.get("mature_blur_level") == "R"
|
||||
|
||||
|
||||
def test_model_name_display_setting_notifies_scanners(tmp_path, monkeypatch):
|
||||
initial = {
|
||||
"libraries": {"default": {"folder_paths": {}, "default_lora_root": "", "default_checkpoint_root": "", "default_embedding_root": ""}},
|
||||
|
||||
202
tests/services/test_sui_image_params_parser.py
Normal file
202
tests/services/test_sui_image_params_parser.py
Normal file
@@ -0,0 +1,202 @@
|
||||
"""Tests for SuiImageParamsParser."""
|
||||
|
||||
import pytest
|
||||
import json
|
||||
from py.recipes.parsers import SuiImageParamsParser
|
||||
|
||||
|
||||
class TestSuiImageParamsParser:
|
||||
"""Test cases for SuiImageParamsParser."""
|
||||
|
||||
def setup_method(self):
|
||||
"""Set up test fixtures."""
|
||||
self.parser = SuiImageParamsParser()
|
||||
|
||||
def test_is_metadata_matching_positive(self):
|
||||
"""Test that parser correctly identifies SuiImage metadata format."""
|
||||
metadata = {
|
||||
"sui_image_params": {
|
||||
"prompt": "test prompt",
|
||||
"model": "test_model"
|
||||
}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
assert self.parser.is_metadata_matching(metadata_str) is True
|
||||
|
||||
def test_is_metadata_matching_negative(self):
|
||||
"""Test that parser rejects non-SuiImage metadata."""
|
||||
# Missing sui_image_params key
|
||||
metadata = {
|
||||
"other_params": {
|
||||
"prompt": "test prompt"
|
||||
}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
assert self.parser.is_metadata_matching(metadata_str) is False
|
||||
|
||||
def test_is_metadata_matching_invalid_json(self):
|
||||
"""Test that parser handles invalid JSON gracefully."""
|
||||
metadata_str = "not valid json"
|
||||
assert self.parser.is_metadata_matching(metadata_str) is False
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_parse_metadata_extracts_basic_fields(self):
|
||||
"""Test parsing basic fields from SuiImage metadata."""
|
||||
metadata = {
|
||||
"sui_image_params": {
|
||||
"prompt": "beautiful landscape",
|
||||
"negativeprompt": "ugly, blurry",
|
||||
"steps": 30,
|
||||
"seed": 12345,
|
||||
"cfgscale": 7.5,
|
||||
"width": 512,
|
||||
"height": 768,
|
||||
"sampler": "Euler a",
|
||||
"scheduler": "normal"
|
||||
},
|
||||
"sui_models": [],
|
||||
"sui_extra_data": {}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
result = await self.parser.parse_metadata(metadata_str)
|
||||
|
||||
assert result.get('gen_params', {}).get('prompt') == "beautiful landscape"
|
||||
assert result.get('gen_params', {}).get('negative_prompt') == "ugly, blurry"
|
||||
assert result.get('gen_params', {}).get('steps') == 30
|
||||
assert result.get('gen_params', {}).get('seed') == 12345
|
||||
assert result.get('gen_params', {}).get('cfg_scale') == 7.5
|
||||
assert result.get('gen_params', {}).get('width') == 512
|
||||
assert result.get('gen_params', {}).get('height') == 768
|
||||
assert result.get('gen_params', {}).get('size') == "512x768"
|
||||
assert result.get('loras') == []
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_parse_metadata_extracts_checkpoint(self):
|
||||
"""Test parsing checkpoint from sui_models."""
|
||||
metadata = {
|
||||
"sui_image_params": {
|
||||
"prompt": "test prompt",
|
||||
"model": "checkpoint_model"
|
||||
},
|
||||
"sui_models": [
|
||||
{
|
||||
"name": "test_checkpoint.safetensors",
|
||||
"param": "model",
|
||||
"hash": "0x1234567890abcdef"
|
||||
}
|
||||
],
|
||||
"sui_extra_data": {}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
result = await self.parser.parse_metadata(metadata_str)
|
||||
|
||||
checkpoint = result.get('checkpoint')
|
||||
assert checkpoint is not None
|
||||
assert checkpoint['type'] == 'checkpoint'
|
||||
assert checkpoint['name'] == 'test_checkpoint'
|
||||
assert checkpoint['hash'] == '1234567890abcdef'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_parse_metadata_extracts_lora(self):
|
||||
"""Test parsing LoRA from sui_models."""
|
||||
metadata = {
|
||||
"sui_image_params": {
|
||||
"prompt": "test prompt"
|
||||
},
|
||||
"sui_models": [
|
||||
{
|
||||
"name": "test_lora.safetensors",
|
||||
"param": "lora",
|
||||
"hash": "0xabcdef1234567890"
|
||||
}
|
||||
],
|
||||
"sui_extra_data": {}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
result = await self.parser.parse_metadata(metadata_str)
|
||||
|
||||
loras = result.get('loras')
|
||||
assert len(loras) == 1
|
||||
assert loras[0]['type'] == 'lora'
|
||||
assert loras[0]['name'] == 'test_lora'
|
||||
assert loras[0]['file_name'] == 'test_lora.safetensors'
|
||||
assert loras[0]['hash'] == 'abcdef1234567890'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_parse_metadata_handles_lora_in_name(self):
|
||||
"""Test that LoRA is detected by 'lora' in name."""
|
||||
metadata = {
|
||||
"sui_image_params": {
|
||||
"prompt": "test prompt"
|
||||
},
|
||||
"sui_models": [
|
||||
{
|
||||
"name": "style_lora_v2.safetensors",
|
||||
"param": "some_other_param",
|
||||
"hash": "0x1111111111111111"
|
||||
}
|
||||
],
|
||||
"sui_extra_data": {}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
result = await self.parser.parse_metadata(metadata_str)
|
||||
|
||||
loras = result.get('loras')
|
||||
assert len(loras) == 1
|
||||
assert loras[0]['type'] == 'lora'
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_parse_metadata_empty_models(self):
|
||||
"""Test parsing with empty sui_models array."""
|
||||
metadata = {
|
||||
"sui_image_params": {
|
||||
"prompt": "test prompt",
|
||||
"steps": 20
|
||||
},
|
||||
"sui_models": [],
|
||||
"sui_extra_data": {
|
||||
"date": "2024-01-01"
|
||||
}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
result = await self.parser.parse_metadata(metadata_str)
|
||||
|
||||
assert result.get('loras') == []
|
||||
assert result.get('checkpoint') is None
|
||||
assert result.get('gen_params', {}).get('prompt') == "test prompt"
|
||||
assert result.get('gen_params', {}).get('steps') == 20
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_parse_metadata_alternative_field_names(self):
|
||||
"""Test parsing with alternative field names."""
|
||||
metadata = {
|
||||
"sui_image_params": {
|
||||
"prompt": "test prompt",
|
||||
"negative_prompt": "bad quality", # Using underscore variant
|
||||
"cfg_scale": 6.0 # Using underscore variant
|
||||
},
|
||||
"sui_models": [],
|
||||
"sui_extra_data": {}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
result = await self.parser.parse_metadata(metadata_str)
|
||||
|
||||
assert result.get('gen_params', {}).get('negative_prompt') == "bad quality"
|
||||
assert result.get('gen_params', {}).get('cfg_scale') == 6.0
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_parse_metadata_error_handling(self):
|
||||
"""Test that parser handles malformed data gracefully."""
|
||||
# Missing required fields
|
||||
metadata = {
|
||||
"sui_image_params": {},
|
||||
"sui_models": [],
|
||||
"sui_extra_data": {}
|
||||
}
|
||||
metadata_str = json.dumps(metadata)
|
||||
result = await self.parser.parse_metadata(metadata_str)
|
||||
|
||||
assert 'error' not in result
|
||||
assert result.get('loras') == []
|
||||
# Empty params result in empty gen_params dict
|
||||
assert result.get('gen_params') == {}
|
||||
@@ -1,30 +1,7 @@
|
||||
from py.utils.preview_selection import select_preview_media
|
||||
import pytest
|
||||
|
||||
|
||||
def test_select_preview_prefers_safe_media_when_blurred():
|
||||
images = [
|
||||
{"url": "nsfw", "type": "image", "nsfwLevel": 8},
|
||||
{"url": "mid", "type": "image", "nsfwLevel": 4},
|
||||
{"url": "safe", "type": "image", "nsfwLevel": 1},
|
||||
]
|
||||
|
||||
selected, level = select_preview_media(images, blur_mature_content=True)
|
||||
|
||||
assert selected["url"] == "safe"
|
||||
assert level == 1
|
||||
|
||||
|
||||
def test_select_preview_returns_lowest_when_no_safe_media():
|
||||
images = [
|
||||
{"url": "x", "type": "image", "nsfwLevel": 16},
|
||||
{"url": "r", "type": "image", "nsfwLevel": 4},
|
||||
{"url": "xx", "type": "image", "nsfwLevel": 8},
|
||||
]
|
||||
|
||||
selected, level = select_preview_media(images, blur_mature_content=True)
|
||||
|
||||
assert selected["url"] == "r"
|
||||
assert level == 4
|
||||
from py.utils.constants import NSFW_LEVELS
|
||||
from py.utils.preview_selection import resolve_mature_threshold, select_preview_media
|
||||
|
||||
|
||||
def test_select_preview_returns_first_when_blur_disabled():
|
||||
@@ -37,3 +14,36 @@ def test_select_preview_returns_first_when_blur_disabled():
|
||||
|
||||
assert selected["url"] == "nsfw"
|
||||
assert level == 32
|
||||
|
||||
|
||||
@pytest.mark.parametrize(
|
||||
("threshold_name", "expected_url"),
|
||||
[
|
||||
("PG13", "pg"),
|
||||
("R", "pg13"),
|
||||
("X", "r"),
|
||||
("XXX", "x"),
|
||||
],
|
||||
)
|
||||
def test_select_preview_respects_configurable_threshold(threshold_name, expected_url):
|
||||
images = [
|
||||
{"url": "xxx", "type": "image", "nsfwLevel": NSFW_LEVELS["XXX"]},
|
||||
{"url": "x", "type": "image", "nsfwLevel": NSFW_LEVELS["X"]},
|
||||
{"url": "r", "type": "image", "nsfwLevel": NSFW_LEVELS["R"]},
|
||||
{"url": "pg13", "type": "image", "nsfwLevel": NSFW_LEVELS["PG13"]},
|
||||
{"url": "pg", "type": "image", "nsfwLevel": NSFW_LEVELS["PG"]},
|
||||
]
|
||||
|
||||
selected, level = select_preview_media(
|
||||
images,
|
||||
blur_mature_content=True,
|
||||
mature_threshold=NSFW_LEVELS[threshold_name],
|
||||
)
|
||||
|
||||
assert selected["url"] == expected_url
|
||||
assert level == next(item["nsfwLevel"] for item in images if item["url"] == expected_url)
|
||||
|
||||
|
||||
def test_resolve_mature_threshold_falls_back_to_r_for_invalid_value():
|
||||
assert resolve_mature_threshold({"mature_blur_level": "invalid"}) == NSFW_LEVELS["R"]
|
||||
assert resolve_mature_threshold({}) == NSFW_LEVELS["R"]
|
||||
|
||||
@@ -2,8 +2,8 @@
|
||||
<div class="lora-cycler-widget">
|
||||
<LoraCyclerSettingsView
|
||||
:current-index="state.currentIndex.value"
|
||||
:total-count="state.totalCount.value"
|
||||
:current-lora-name="state.currentLoraName.value"
|
||||
:total-count="displayTotalCount"
|
||||
:current-lora-name="displayLoraName"
|
||||
:current-lora-filename="state.currentLoraFilename.value"
|
||||
:model-strength="state.modelStrength.value"
|
||||
:clip-strength="state.clipStrength.value"
|
||||
@@ -16,11 +16,14 @@
|
||||
:is-pause-disabled="hasQueuedPrompts"
|
||||
:is-workflow-executing="state.isWorkflowExecuting.value"
|
||||
:executing-repeat-step="state.executingRepeatStep.value"
|
||||
:include-no-lora="state.includeNoLora.value"
|
||||
:is-no-lora="isNoLora"
|
||||
@update:current-index="handleIndexUpdate"
|
||||
@update:model-strength="state.modelStrength.value = $event"
|
||||
@update:clip-strength="state.clipStrength.value = $event"
|
||||
@update:use-custom-clip-range="handleUseCustomClipRangeChange"
|
||||
@update:repeat-count="handleRepeatCountChange"
|
||||
@update:include-no-lora="handleIncludeNoLoraChange"
|
||||
@toggle-pause="handleTogglePause"
|
||||
@reset-index="handleResetIndex"
|
||||
@open-lora-selector="isModalOpen = true"
|
||||
@@ -30,6 +33,7 @@
|
||||
:visible="isModalOpen"
|
||||
:lora-list="cachedLoraList"
|
||||
:current-index="state.currentIndex.value"
|
||||
:include-no-lora="state.includeNoLora.value"
|
||||
@close="isModalOpen = false"
|
||||
@select="handleModalSelect"
|
||||
/>
|
||||
@@ -37,7 +41,7 @@
|
||||
</template>
|
||||
|
||||
<script setup lang="ts">
|
||||
import { onMounted, ref } from 'vue'
|
||||
import { onMounted, ref, computed } from 'vue'
|
||||
import LoraCyclerSettingsView from './lora-cycler/LoraCyclerSettingsView.vue'
|
||||
import LoraListModal from './lora-cycler/LoraListModal.vue'
|
||||
import { useLoraCyclerState } from '../composables/useLoraCyclerState'
|
||||
@@ -102,6 +106,31 @@ const isModalOpen = ref(false)
|
||||
// Cache for LoRA list (used by modal)
|
||||
const cachedLoraList = ref<LoraItem[]>([])
|
||||
|
||||
// Computed: display total count (includes no lora option if enabled)
|
||||
const displayTotalCount = computed(() => {
|
||||
const baseCount = state.totalCount.value
|
||||
return state.includeNoLora.value ? baseCount + 1 : baseCount
|
||||
})
|
||||
|
||||
// Computed: display LoRA name (shows "No LoRA" if on the last index and includeNoLora is enabled)
|
||||
const displayLoraName = computed(() => {
|
||||
const currentIndex = state.currentIndex.value
|
||||
const totalCount = state.totalCount.value
|
||||
|
||||
// If includeNoLora is enabled and we're on the last position (no lora slot)
|
||||
if (state.includeNoLora.value && currentIndex === totalCount + 1) {
|
||||
return 'No LoRA'
|
||||
}
|
||||
|
||||
// Otherwise show the normal LoRA name
|
||||
return state.currentLoraName.value
|
||||
})
|
||||
|
||||
// Computed: check if currently on "No LoRA" option
|
||||
const isNoLora = computed(() => {
|
||||
return state.includeNoLora.value && state.currentIndex.value === state.totalCount.value + 1
|
||||
})
|
||||
|
||||
// Get pool config from connected node
|
||||
const getPoolConfig = (): LoraPoolConfig | null => {
|
||||
// Check if getPoolConfig method exists on node (added by main.ts)
|
||||
@@ -113,7 +142,17 @@ const getPoolConfig = (): LoraPoolConfig | null => {
|
||||
|
||||
// Update display from LoRA list and index
|
||||
const updateDisplayFromLoraList = (loraList: LoraItem[], index: number) => {
|
||||
if (loraList.length > 0 && index > 0 && index <= loraList.length) {
|
||||
const actualLoraCount = loraList.length
|
||||
|
||||
// If index is beyond actual LoRA count, it means we're on the "no lora" option
|
||||
if (state.includeNoLora.value && index === actualLoraCount + 1) {
|
||||
state.currentLoraName.value = 'No LoRA'
|
||||
state.currentLoraFilename.value = 'No LoRA'
|
||||
return
|
||||
}
|
||||
|
||||
// Otherwise, show normal LoRA info
|
||||
if (actualLoraCount > 0 && index > 0 && index <= actualLoraCount) {
|
||||
const currentLora = loraList[index - 1]
|
||||
if (currentLora) {
|
||||
state.currentLoraName.value = currentLora.file_name
|
||||
@@ -124,6 +163,14 @@ const updateDisplayFromLoraList = (loraList: LoraItem[], index: number) => {
|
||||
|
||||
// Handle index update from user
|
||||
const handleIndexUpdate = async (newIndex: number) => {
|
||||
// Calculate max valid index (includes no lora slot if enabled)
|
||||
const maxIndex = state.includeNoLora.value
|
||||
? state.totalCount.value + 1
|
||||
: state.totalCount.value
|
||||
|
||||
// Clamp index to valid range
|
||||
const clampedIndex = Math.max(1, Math.min(newIndex, maxIndex || 1))
|
||||
|
||||
// Reset execution state when user manually changes index
|
||||
// This ensures the next execution starts from the user-set index
|
||||
;(props.widget as any)[HAS_EXECUTED] = false
|
||||
@@ -134,14 +181,14 @@ const handleIndexUpdate = async (newIndex: number) => {
|
||||
executionQueue.length = 0
|
||||
hasQueuedPrompts.value = false
|
||||
|
||||
state.setIndex(newIndex)
|
||||
state.setIndex(clampedIndex)
|
||||
|
||||
// Refresh list to update current LoRA display
|
||||
try {
|
||||
const poolConfig = getPoolConfig()
|
||||
const loraList = await state.fetchCyclerList(poolConfig)
|
||||
cachedLoraList.value = loraList
|
||||
updateDisplayFromLoraList(loraList, newIndex)
|
||||
updateDisplayFromLoraList(loraList, clampedIndex)
|
||||
} catch (error) {
|
||||
console.error('[LoraCyclerWidget] Error updating index:', error)
|
||||
}
|
||||
@@ -169,6 +216,17 @@ const handleRepeatCountChange = (newValue: number) => {
|
||||
state.displayRepeatUsed.value = 0
|
||||
}
|
||||
|
||||
// Handle include no lora toggle
|
||||
const handleIncludeNoLoraChange = (newValue: boolean) => {
|
||||
state.includeNoLora.value = newValue
|
||||
|
||||
// If turning off and current index is beyond the actual LoRA count,
|
||||
// clamp it to the last valid LoRA index
|
||||
if (!newValue && state.currentIndex.value > state.totalCount.value) {
|
||||
state.currentIndex.value = Math.max(1, state.totalCount.value)
|
||||
}
|
||||
}
|
||||
|
||||
// Handle pause toggle
|
||||
const handleTogglePause = () => {
|
||||
state.togglePause()
|
||||
|
||||
@@ -8,6 +8,9 @@
|
||||
:exclude-tags="state.excludeTags.value"
|
||||
:include-folders="state.includeFolders.value"
|
||||
:exclude-folders="state.excludeFolders.value"
|
||||
:include-patterns="state.includePatterns.value"
|
||||
:exclude-patterns="state.excludePatterns.value"
|
||||
:use-regex="state.useRegex.value"
|
||||
:no-credit-required="state.noCreditRequired.value"
|
||||
:allow-selling="state.allowSelling.value"
|
||||
:preview-items="state.previewItems.value"
|
||||
@@ -16,6 +19,9 @@
|
||||
@open-modal="openModal"
|
||||
@update:include-folders="state.includeFolders.value = $event"
|
||||
@update:exclude-folders="state.excludeFolders.value = $event"
|
||||
@update:include-patterns="state.includePatterns.value = $event"
|
||||
@update:exclude-patterns="state.excludePatterns.value = $event"
|
||||
@update:use-regex="state.useRegex.value = $event"
|
||||
@update:no-credit-required="state.noCreditRequired.value = $event"
|
||||
@update:allow-selling="state.allowSelling.value = $event"
|
||||
@refresh="state.refreshPreview"
|
||||
|
||||
@@ -13,7 +13,9 @@
|
||||
@click="handleOpenSelector"
|
||||
>
|
||||
<span class="progress-label">{{ isWorkflowExecuting ? 'Using LoRA:' : 'Next LoRA:' }}</span>
|
||||
<span class="progress-name clickable" :class="{ disabled: isPauseDisabled }" :title="currentLoraFilename">
|
||||
<span class="progress-name clickable"
|
||||
:class="{ disabled: isPauseDisabled, 'no-lora': isNoLora }"
|
||||
:title="currentLoraFilename">
|
||||
{{ currentLoraName || 'None' }}
|
||||
<svg class="selector-icon" viewBox="0 0 24 24" fill="currentColor">
|
||||
<path d="M7 10l5 5 5-5z"/>
|
||||
@@ -160,6 +162,27 @@
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Include No LoRA Toggle -->
|
||||
<div class="setting-section">
|
||||
<div class="section-header-with-toggle">
|
||||
<label class="setting-label">
|
||||
Add "No LoRA" step
|
||||
</label>
|
||||
<button
|
||||
type="button"
|
||||
class="toggle-switch"
|
||||
:class="{ 'toggle-switch--active': includeNoLora }"
|
||||
@click="$emit('update:includeNoLora', !includeNoLora)"
|
||||
role="switch"
|
||||
:aria-checked="includeNoLora"
|
||||
title="Add an iteration without LoRA for comparison"
|
||||
>
|
||||
<span class="toggle-switch__track"></span>
|
||||
<span class="toggle-switch__thumb"></span>
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
@@ -182,6 +205,8 @@ const props = defineProps<{
|
||||
isPauseDisabled: boolean
|
||||
isWorkflowExecuting: boolean
|
||||
executingRepeatStep: number
|
||||
includeNoLora: boolean
|
||||
isNoLora?: boolean
|
||||
}>()
|
||||
|
||||
const emit = defineEmits<{
|
||||
@@ -190,6 +215,7 @@ const emit = defineEmits<{
|
||||
'update:clipStrength': [value: number]
|
||||
'update:useCustomClipRange': [value: boolean]
|
||||
'update:repeatCount': [value: number]
|
||||
'update:includeNoLora': [value: boolean]
|
||||
'toggle-pause': []
|
||||
'reset-index': []
|
||||
'open-lora-selector': []
|
||||
@@ -346,6 +372,16 @@ const onRepeatBlur = (event: Event) => {
|
||||
color: rgba(191, 219, 254, 1);
|
||||
}
|
||||
|
||||
.progress-name.no-lora {
|
||||
font-style: italic;
|
||||
color: rgba(226, 232, 240, 0.6);
|
||||
}
|
||||
|
||||
.progress-name.clickable.no-lora:hover:not(.disabled) {
|
||||
background: rgba(160, 174, 192, 0.2);
|
||||
color: rgba(226, 232, 240, 0.8);
|
||||
}
|
||||
|
||||
.progress-name.clickable.disabled {
|
||||
cursor: not-allowed;
|
||||
opacity: 0.5;
|
||||
|
||||
@@ -35,7 +35,10 @@
|
||||
v-for="item in filteredList"
|
||||
:key="item.index"
|
||||
class="lora-item"
|
||||
:class="{ active: currentIndex === item.index }"
|
||||
:class="{
|
||||
active: currentIndex === item.index,
|
||||
'no-lora-item': item.lora.file_name === 'No LoRA'
|
||||
}"
|
||||
@mouseenter="showPreview(item.lora.file_name, $event)"
|
||||
@mouseleave="hidePreview"
|
||||
@click="selectLora(item.index)"
|
||||
@@ -65,6 +68,7 @@ const props = defineProps<{
|
||||
visible: boolean
|
||||
loraList: LoraItem[]
|
||||
currentIndex: number
|
||||
includeNoLora?: boolean
|
||||
}>()
|
||||
|
||||
const emit = defineEmits<{
|
||||
@@ -79,7 +83,8 @@ const searchInputRef = ref<HTMLInputElement | null>(null)
|
||||
let previewTooltip: any = null
|
||||
|
||||
const subtitleText = computed(() => {
|
||||
const total = props.loraList.length
|
||||
const baseTotal = props.loraList.length
|
||||
const total = props.includeNoLora ? baseTotal + 1 : baseTotal
|
||||
const filtered = filteredList.value.length
|
||||
if (filtered === total) {
|
||||
return `Total: ${total} LoRA${total !== 1 ? 's' : ''}`
|
||||
@@ -88,11 +93,19 @@ const subtitleText = computed(() => {
|
||||
})
|
||||
|
||||
const filteredList = computed<LoraListItem[]>(() => {
|
||||
const list = props.loraList.map((lora, idx) => ({
|
||||
const list: LoraListItem[] = props.loraList.map((lora, idx) => ({
|
||||
index: idx + 1,
|
||||
lora
|
||||
}))
|
||||
|
||||
// Add "No LoRA" option at the end if includeNoLora is enabled
|
||||
if (props.includeNoLora) {
|
||||
list.push({
|
||||
index: list.length + 1,
|
||||
lora: { file_name: 'No LoRA' } as LoraItem
|
||||
})
|
||||
}
|
||||
|
||||
if (!searchQuery.value.trim()) {
|
||||
return list
|
||||
}
|
||||
@@ -303,6 +316,15 @@ onUnmounted(() => {
|
||||
font-weight: 500;
|
||||
}
|
||||
|
||||
.lora-item.no-lora-item .lora-name {
|
||||
font-style: italic;
|
||||
color: rgba(226, 232, 240, 0.6);
|
||||
}
|
||||
|
||||
.lora-item.no-lora-item:hover .lora-name {
|
||||
color: rgba(226, 232, 240, 0.8);
|
||||
}
|
||||
|
||||
.no-results {
|
||||
padding: 32px 20px;
|
||||
text-align: center;
|
||||
|
||||
@@ -24,6 +24,15 @@
|
||||
@edit-exclude="$emit('open-modal', 'excludeFolders')"
|
||||
/>
|
||||
|
||||
<NamePatternsSection
|
||||
:include-patterns="includePatterns"
|
||||
:exclude-patterns="excludePatterns"
|
||||
:use-regex="useRegex"
|
||||
@update:include-patterns="$emit('update:includePatterns', $event)"
|
||||
@update:exclude-patterns="$emit('update:excludePatterns', $event)"
|
||||
@update:use-regex="$emit('update:useRegex', $event)"
|
||||
/>
|
||||
|
||||
<LicenseSection
|
||||
:no-credit-required="noCreditRequired"
|
||||
:allow-selling="allowSelling"
|
||||
@@ -46,6 +55,7 @@
|
||||
import BaseModelSection from './sections/BaseModelSection.vue'
|
||||
import TagsSection from './sections/TagsSection.vue'
|
||||
import FoldersSection from './sections/FoldersSection.vue'
|
||||
import NamePatternsSection from './sections/NamePatternsSection.vue'
|
||||
import LicenseSection from './sections/LicenseSection.vue'
|
||||
import LoraPoolPreview from './LoraPoolPreview.vue'
|
||||
import type { BaseModelOption, LoraItem } from '../../composables/types'
|
||||
@@ -61,6 +71,10 @@ defineProps<{
|
||||
// Folders
|
||||
includeFolders: string[]
|
||||
excludeFolders: string[]
|
||||
// Name patterns
|
||||
includePatterns: string[]
|
||||
excludePatterns: string[]
|
||||
useRegex: boolean
|
||||
// License
|
||||
noCreditRequired: boolean
|
||||
allowSelling: boolean
|
||||
@@ -74,6 +88,9 @@ defineEmits<{
|
||||
'open-modal': [modal: ModalType]
|
||||
'update:includeFolders': [value: string[]]
|
||||
'update:excludeFolders': [value: string[]]
|
||||
'update:includePatterns': [value: string[]]
|
||||
'update:excludePatterns': [value: string[]]
|
||||
'update:useRegex': [value: boolean]
|
||||
'update:noCreditRequired': [value: boolean]
|
||||
'update:allowSelling': [value: boolean]
|
||||
refresh: []
|
||||
|
||||
@@ -0,0 +1,255 @@
|
||||
<template>
|
||||
<div class="section">
|
||||
<div class="section__header">
|
||||
<span class="section__title">NAME PATTERNS</span>
|
||||
<label class="section__toggle">
|
||||
<input
|
||||
type="checkbox"
|
||||
:checked="useRegex"
|
||||
@change="$emit('update:useRegex', ($event.target as HTMLInputElement).checked)"
|
||||
/>
|
||||
<span class="section__toggle-label">Use Regex</span>
|
||||
</label>
|
||||
</div>
|
||||
<div class="section__columns">
|
||||
<!-- Include column -->
|
||||
<div class="section__column">
|
||||
<div class="section__column-header">
|
||||
<span class="section__column-title section__column-title--include">INCLUDE</span>
|
||||
</div>
|
||||
<div class="section__input-wrapper">
|
||||
<input
|
||||
type="text"
|
||||
v-model="includeInput"
|
||||
:placeholder="useRegex ? 'Add regex pattern...' : 'Add text pattern...'"
|
||||
class="section__input"
|
||||
@keydown.enter="addInclude"
|
||||
/>
|
||||
<button type="button" class="section__add-btn" @click="addInclude">+</button>
|
||||
</div>
|
||||
<div class="section__patterns">
|
||||
<FilterChip
|
||||
v-for="pattern in includePatterns"
|
||||
:key="pattern"
|
||||
:label="pattern"
|
||||
variant="include"
|
||||
removable
|
||||
@remove="removeInclude(pattern)"
|
||||
/>
|
||||
<div v-if="includePatterns.length === 0" class="section__empty">
|
||||
{{ useRegex ? 'No regex patterns' : 'No text patterns' }}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<!-- Exclude column -->
|
||||
<div class="section__column">
|
||||
<div class="section__column-header">
|
||||
<span class="section__column-title section__column-title--exclude">EXCLUDE</span>
|
||||
</div>
|
||||
<div class="section__input-wrapper">
|
||||
<input
|
||||
type="text"
|
||||
v-model="excludeInput"
|
||||
:placeholder="useRegex ? 'Add regex pattern...' : 'Add text pattern...'"
|
||||
class="section__input"
|
||||
@keydown.enter="addExclude"
|
||||
/>
|
||||
<button type="button" class="section__add-btn" @click="addExclude">+</button>
|
||||
</div>
|
||||
<div class="section__patterns">
|
||||
<FilterChip
|
||||
v-for="pattern in excludePatterns"
|
||||
:key="pattern"
|
||||
:label="pattern"
|
||||
variant="exclude"
|
||||
removable
|
||||
@remove="removeExclude(pattern)"
|
||||
/>
|
||||
<div v-if="excludePatterns.length === 0" class="section__empty">
|
||||
{{ useRegex ? 'No regex patterns' : 'No text patterns' }}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</template>
|
||||
|
||||
<script setup lang="ts">
|
||||
import { ref } from 'vue'
|
||||
import FilterChip from '../shared/FilterChip.vue'
|
||||
|
||||
const props = defineProps<{
|
||||
includePatterns: string[]
|
||||
excludePatterns: string[]
|
||||
useRegex: boolean
|
||||
}>()
|
||||
|
||||
const emit = defineEmits<{
|
||||
'update:includePatterns': [value: string[]]
|
||||
'update:excludePatterns': [value: string[]]
|
||||
'update:useRegex': [value: boolean]
|
||||
}>()
|
||||
|
||||
const includeInput = ref('')
|
||||
const excludeInput = ref('')
|
||||
|
||||
const addInclude = () => {
|
||||
const pattern = includeInput.value.trim()
|
||||
if (pattern && !props.includePatterns.includes(pattern)) {
|
||||
emit('update:includePatterns', [...props.includePatterns, pattern])
|
||||
includeInput.value = ''
|
||||
}
|
||||
}
|
||||
|
||||
const addExclude = () => {
|
||||
const pattern = excludeInput.value.trim()
|
||||
if (pattern && !props.excludePatterns.includes(pattern)) {
|
||||
emit('update:excludePatterns', [...props.excludePatterns, pattern])
|
||||
excludeInput.value = ''
|
||||
}
|
||||
}
|
||||
|
||||
const removeInclude = (pattern: string) => {
|
||||
emit('update:includePatterns', props.includePatterns.filter(p => p !== pattern))
|
||||
}
|
||||
|
||||
const removeExclude = (pattern: string) => {
|
||||
emit('update:excludePatterns', props.excludePatterns.filter(p => p !== pattern))
|
||||
}
|
||||
</script>
|
||||
|
||||
<style scoped>
|
||||
.section {
|
||||
margin-bottom: 16px;
|
||||
}
|
||||
|
||||
.section__header {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
margin-bottom: 8px;
|
||||
}
|
||||
|
||||
.section__title {
|
||||
font-size: 10px;
|
||||
font-weight: 600;
|
||||
text-transform: uppercase;
|
||||
letter-spacing: 0.05em;
|
||||
color: var(--fg-color, #fff);
|
||||
opacity: 0.6;
|
||||
}
|
||||
|
||||
.section__toggle {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
gap: 6px;
|
||||
cursor: pointer;
|
||||
font-size: 11px;
|
||||
color: var(--fg-color, #fff);
|
||||
opacity: 0.7;
|
||||
}
|
||||
|
||||
.section__toggle input[type="checkbox"] {
|
||||
margin: 0;
|
||||
width: 14px;
|
||||
height: 14px;
|
||||
cursor: pointer;
|
||||
}
|
||||
|
||||
.section__toggle-label {
|
||||
font-weight: 500;
|
||||
}
|
||||
|
||||
.section__columns {
|
||||
display: grid;
|
||||
grid-template-columns: 1fr 1fr;
|
||||
gap: 12px;
|
||||
}
|
||||
|
||||
.section__column {
|
||||
min-width: 0;
|
||||
}
|
||||
|
||||
.section__column-header {
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: space-between;
|
||||
margin-bottom: 6px;
|
||||
}
|
||||
|
||||
.section__column-title {
|
||||
font-size: 9px;
|
||||
font-weight: 500;
|
||||
text-transform: uppercase;
|
||||
letter-spacing: 0.03em;
|
||||
}
|
||||
|
||||
.section__column-title--include {
|
||||
color: #4299e1;
|
||||
}
|
||||
|
||||
.section__column-title--exclude {
|
||||
color: #ef4444;
|
||||
}
|
||||
|
||||
.section__input-wrapper {
|
||||
display: flex;
|
||||
gap: 4px;
|
||||
margin-bottom: 8px;
|
||||
}
|
||||
|
||||
.section__input {
|
||||
flex: 1;
|
||||
min-width: 0;
|
||||
padding: 6px 8px;
|
||||
background: var(--comfy-input-bg, #333);
|
||||
border: 1px solid var(--comfy-input-border, #444);
|
||||
border-radius: 4px;
|
||||
color: var(--fg-color, #fff);
|
||||
font-size: 12px;
|
||||
outline: none;
|
||||
}
|
||||
|
||||
.section__input:focus {
|
||||
border-color: #4299e1;
|
||||
}
|
||||
|
||||
.section__add-btn {
|
||||
width: 28px;
|
||||
height: 28px;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
justify-content: center;
|
||||
background: var(--comfy-input-bg, #333);
|
||||
border: 1px solid var(--comfy-input-border, #444);
|
||||
border-radius: 4px;
|
||||
color: var(--fg-color, #fff);
|
||||
font-size: 16px;
|
||||
font-weight: 500;
|
||||
cursor: pointer;
|
||||
transition: all 0.15s;
|
||||
}
|
||||
|
||||
.section__add-btn:hover {
|
||||
background: var(--comfy-input-bg-hover, #444);
|
||||
border-color: #4299e1;
|
||||
}
|
||||
|
||||
.section__patterns {
|
||||
display: flex;
|
||||
flex-wrap: wrap;
|
||||
gap: 4px;
|
||||
min-height: 22px;
|
||||
}
|
||||
|
||||
.section__empty {
|
||||
font-size: 10px;
|
||||
color: var(--fg-color, #fff);
|
||||
opacity: 0.3;
|
||||
font-style: italic;
|
||||
min-height: 22px;
|
||||
display: flex;
|
||||
align-items: center;
|
||||
}
|
||||
</style>
|
||||
@@ -10,6 +10,12 @@ export interface LoraPoolConfig {
|
||||
noCreditRequired: boolean
|
||||
allowSelling: boolean
|
||||
}
|
||||
namePatterns: {
|
||||
include: string[]
|
||||
exclude: string[]
|
||||
useRegex: boolean
|
||||
}
|
||||
includeEmptyLora?: boolean // Optional, deprecated (moved to Cycler)
|
||||
}
|
||||
preview: { matchCount: number; lastUpdated: number }
|
||||
}
|
||||
@@ -84,6 +90,8 @@ export interface CyclerConfig {
|
||||
repeat_count: number // How many times each LoRA should repeat (default: 1)
|
||||
repeat_used: number // How many times current index has been used
|
||||
is_paused: boolean // Whether iteration is paused
|
||||
// Include "no LoRA" option in cycle
|
||||
include_no_lora: boolean // Whether to include empty LoRA option
|
||||
}
|
||||
|
||||
// Widget config union type
|
||||
|
||||
@@ -4,6 +4,7 @@ import type { ComponentWidget, CyclerConfig, LoraPoolConfig } from './types'
|
||||
export interface CyclerLoraItem {
|
||||
file_name: string
|
||||
model_name: string
|
||||
file_path: string
|
||||
}
|
||||
|
||||
export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
@@ -34,6 +35,7 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
const repeatUsed = ref(0) // How many times current index has been used (internal tracking)
|
||||
const displayRepeatUsed = ref(0) // For UI display, deferred updates like currentIndex
|
||||
const isPaused = ref(false) // Whether iteration is paused
|
||||
const includeNoLora = ref(false) // Whether to include empty LoRA option in cycle
|
||||
|
||||
// Execution progress tracking (visual feedback)
|
||||
const isWorkflowExecuting = ref(false) // Workflow is currently running
|
||||
@@ -58,6 +60,7 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
repeat_count: repeatCount.value,
|
||||
repeat_used: repeatUsed.value,
|
||||
is_paused: isPaused.value,
|
||||
include_no_lora: includeNoLora.value,
|
||||
}
|
||||
}
|
||||
return {
|
||||
@@ -75,6 +78,7 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
repeat_count: repeatCount.value,
|
||||
repeat_used: repeatUsed.value,
|
||||
is_paused: isPaused.value,
|
||||
include_no_lora: includeNoLora.value,
|
||||
}
|
||||
}
|
||||
|
||||
@@ -93,12 +97,13 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
sortBy.value = config.sort_by || 'filename'
|
||||
currentLoraName.value = config.current_lora_name || ''
|
||||
currentLoraFilename.value = config.current_lora_filename || ''
|
||||
// Advanced index control features
|
||||
repeatCount.value = config.repeat_count ?? 1
|
||||
repeatUsed.value = config.repeat_used ?? 0
|
||||
isPaused.value = config.is_paused ?? false
|
||||
// Note: execution_index and next_index are not restored from config
|
||||
// as they are transient values used only during batch execution
|
||||
// Advanced index control features
|
||||
repeatCount.value = config.repeat_count ?? 1
|
||||
repeatUsed.value = config.repeat_used ?? 0
|
||||
isPaused.value = config.is_paused ?? false
|
||||
includeNoLora.value = config.include_no_lora ?? false
|
||||
// Note: execution_index and next_index are not restored from config
|
||||
// as they are transient values used only during batch execution
|
||||
} finally {
|
||||
isRestoring = false
|
||||
}
|
||||
@@ -111,7 +116,9 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
// Calculate the next index (wrap to 1 if at end)
|
||||
const current = executionIndex.value ?? currentIndex.value
|
||||
let next = current + 1
|
||||
if (totalCount.value > 0 && next > totalCount.value) {
|
||||
// Total count includes no lora option if enabled
|
||||
const effectiveTotalCount = includeNoLora.value ? totalCount.value + 1 : totalCount.value
|
||||
if (effectiveTotalCount > 0 && next > effectiveTotalCount) {
|
||||
next = 1
|
||||
}
|
||||
nextIndex.value = next
|
||||
@@ -122,7 +129,9 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
if (nextIndex.value === null) {
|
||||
// First execution uses current_index, so next is current + 1
|
||||
let next = currentIndex.value + 1
|
||||
if (totalCount.value > 0 && next > totalCount.value) {
|
||||
// Total count includes no lora option if enabled
|
||||
const effectiveTotalCount = includeNoLora.value ? totalCount.value + 1 : totalCount.value
|
||||
if (effectiveTotalCount > 0 && next > effectiveTotalCount) {
|
||||
next = 1
|
||||
}
|
||||
nextIndex.value = next
|
||||
@@ -230,7 +239,9 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
|
||||
// Set index manually
|
||||
const setIndex = (index: number) => {
|
||||
if (index >= 1 && index <= totalCount.value) {
|
||||
// Total count includes no lora option if enabled
|
||||
const effectiveTotalCount = includeNoLora.value ? totalCount.value + 1 : totalCount.value
|
||||
if (index >= 1 && index <= effectiveTotalCount) {
|
||||
currentIndex.value = index
|
||||
}
|
||||
}
|
||||
@@ -272,6 +283,7 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
repeatCount,
|
||||
repeatUsed,
|
||||
isPaused,
|
||||
includeNoLora,
|
||||
], () => {
|
||||
widget.value = buildConfig()
|
||||
}, { deep: true })
|
||||
@@ -294,6 +306,7 @@ export function useLoraCyclerState(widget: ComponentWidget<CyclerConfig>) {
|
||||
repeatUsed,
|
||||
displayRepeatUsed,
|
||||
isPaused,
|
||||
includeNoLora,
|
||||
isWorkflowExecuting,
|
||||
executingRepeatStep,
|
||||
|
||||
|
||||
@@ -62,6 +62,9 @@ export function useLoraPoolApi() {
|
||||
foldersExclude?: string[]
|
||||
noCreditRequired?: boolean
|
||||
allowSelling?: boolean
|
||||
namePatternsInclude?: string[]
|
||||
namePatternsExclude?: string[]
|
||||
namePatternsUseRegex?: boolean
|
||||
page?: number
|
||||
pageSize?: number
|
||||
}
|
||||
@@ -92,6 +95,13 @@ export function useLoraPoolApi() {
|
||||
urlParams.set('allow_selling_generated_content', String(params.allowSelling))
|
||||
}
|
||||
|
||||
// Name pattern filters
|
||||
params.namePatternsInclude?.forEach(pattern => urlParams.append('name_pattern_include', pattern))
|
||||
params.namePatternsExclude?.forEach(pattern => urlParams.append('name_pattern_exclude', pattern))
|
||||
if (params.namePatternsUseRegex !== undefined) {
|
||||
urlParams.set('name_pattern_use_regex', String(params.namePatternsUseRegex))
|
||||
}
|
||||
|
||||
const response = await fetch(`/api/lm/loras/list?${urlParams}`)
|
||||
const data = await response.json()
|
||||
|
||||
|
||||
@@ -24,6 +24,9 @@ export function useLoraPoolState(widget: ComponentWidget<LoraPoolConfig>) {
|
||||
const excludeFolders = ref<string[]>([])
|
||||
const noCreditRequired = ref(false)
|
||||
const allowSelling = ref(false)
|
||||
const includePatterns = ref<string[]>([])
|
||||
const excludePatterns = ref<string[]>([])
|
||||
const useRegex = ref(false)
|
||||
|
||||
// Available options from API
|
||||
const availableBaseModels = ref<BaseModelOption[]>([])
|
||||
@@ -52,6 +55,11 @@ export function useLoraPoolState(widget: ComponentWidget<LoraPoolConfig>) {
|
||||
license: {
|
||||
noCreditRequired: noCreditRequired.value,
|
||||
allowSelling: allowSelling.value
|
||||
},
|
||||
namePatterns: {
|
||||
include: includePatterns.value,
|
||||
exclude: excludePatterns.value,
|
||||
useRegex: useRegex.value
|
||||
}
|
||||
},
|
||||
preview: {
|
||||
@@ -94,6 +102,9 @@ export function useLoraPoolState(widget: ComponentWidget<LoraPoolConfig>) {
|
||||
updateIfChanged(excludeFolders, filters.folders?.exclude || [])
|
||||
updateIfChanged(noCreditRequired, filters.license?.noCreditRequired ?? false)
|
||||
updateIfChanged(allowSelling, filters.license?.allowSelling ?? false)
|
||||
updateIfChanged(includePatterns, filters.namePatterns?.include || [])
|
||||
updateIfChanged(excludePatterns, filters.namePatterns?.exclude || [])
|
||||
updateIfChanged(useRegex, filters.namePatterns?.useRegex ?? false)
|
||||
|
||||
// matchCount doesn't trigger watchers, so direct assignment is fine
|
||||
matchCount.value = preview?.matchCount || 0
|
||||
@@ -125,6 +136,9 @@ export function useLoraPoolState(widget: ComponentWidget<LoraPoolConfig>) {
|
||||
foldersExclude: excludeFolders.value,
|
||||
noCreditRequired: noCreditRequired.value || undefined,
|
||||
allowSelling: allowSelling.value || undefined,
|
||||
namePatternsInclude: includePatterns.value,
|
||||
namePatternsExclude: excludePatterns.value,
|
||||
namePatternsUseRegex: useRegex.value,
|
||||
pageSize: 6
|
||||
})
|
||||
|
||||
@@ -150,7 +164,10 @@ export function useLoraPoolState(widget: ComponentWidget<LoraPoolConfig>) {
|
||||
includeFolders,
|
||||
excludeFolders,
|
||||
noCreditRequired,
|
||||
allowSelling
|
||||
allowSelling,
|
||||
includePatterns,
|
||||
excludePatterns,
|
||||
useRegex
|
||||
], onFilterChange, { deep: true })
|
||||
|
||||
return {
|
||||
@@ -162,6 +179,9 @@ export function useLoraPoolState(widget: ComponentWidget<LoraPoolConfig>) {
|
||||
excludeFolders,
|
||||
noCreditRequired,
|
||||
allowSelling,
|
||||
includePatterns,
|
||||
excludePatterns,
|
||||
useRegex,
|
||||
|
||||
// Available options
|
||||
availableBaseModels,
|
||||
|
||||
@@ -13,12 +13,12 @@ import {
|
||||
} from './mode-change-handler'
|
||||
|
||||
const LORA_POOL_WIDGET_MIN_WIDTH = 500
|
||||
const LORA_POOL_WIDGET_MIN_HEIGHT = 400
|
||||
const LORA_POOL_WIDGET_MIN_HEIGHT = 520
|
||||
const LORA_RANDOMIZER_WIDGET_MIN_WIDTH = 500
|
||||
const LORA_RANDOMIZER_WIDGET_MIN_HEIGHT = 448
|
||||
const LORA_RANDOMIZER_WIDGET_MAX_HEIGHT = LORA_RANDOMIZER_WIDGET_MIN_HEIGHT
|
||||
const LORA_CYCLER_WIDGET_MIN_WIDTH = 380
|
||||
const LORA_CYCLER_WIDGET_MIN_HEIGHT = 314
|
||||
const LORA_CYCLER_WIDGET_MIN_HEIGHT = 344
|
||||
const LORA_CYCLER_WIDGET_MAX_HEIGHT = LORA_CYCLER_WIDGET_MIN_HEIGHT
|
||||
const JSON_DISPLAY_WIDGET_MIN_WIDTH = 300
|
||||
const JSON_DISPLAY_WIDGET_MIN_HEIGHT = 200
|
||||
|
||||
@@ -84,7 +84,8 @@ describe('useLoraCyclerState', () => {
|
||||
current_lora_filename: '',
|
||||
repeat_count: 1,
|
||||
repeat_used: 0,
|
||||
is_paused: false
|
||||
is_paused: false,
|
||||
include_no_lora: false
|
||||
})
|
||||
|
||||
expect(state.currentIndex.value).toBe(5)
|
||||
|
||||
4
vue-widgets/tests/fixtures/mockConfigs.ts
vendored
4
vue-widgets/tests/fixtures/mockConfigs.ts
vendored
@@ -24,6 +24,7 @@ export function createMockCyclerConfig(overrides: Partial<CyclerConfig> = {}): C
|
||||
repeat_count: 1,
|
||||
repeat_used: 0,
|
||||
is_paused: false,
|
||||
include_no_lora: false,
|
||||
...overrides
|
||||
}
|
||||
}
|
||||
@@ -54,7 +55,8 @@ export function createMockPoolConfig(overrides: Partial<LoraPoolConfig> = {}): L
|
||||
export function createMockLoraList(count: number = 5): CyclerLoraItem[] {
|
||||
return Array.from({ length: count }, (_, i) => ({
|
||||
file_name: `lora${i + 1}.safetensors`,
|
||||
model_name: `LoRA Model ${i + 1}`
|
||||
model_name: `LoRA Model ${i + 1}`,
|
||||
file_path: `/models/loras/lora${i + 1}.safetensors`
|
||||
}))
|
||||
}
|
||||
|
||||
|
||||
@@ -14,6 +14,7 @@ import { initDrag, createContextMenu, initHeaderDrag, initReorderDrag, handleKey
|
||||
import { forwardMiddleMouseToCanvas } from "./utils.js";
|
||||
import { PreviewTooltip } from "./preview_tooltip.js";
|
||||
import { ensureLmStyles } from "./lm_styles_loader.js";
|
||||
import { getStrengthStepPreference } from "./settings.js";
|
||||
|
||||
export function addLorasWidget(node, name, opts, callback) {
|
||||
ensureLmStyles();
|
||||
@@ -416,7 +417,7 @@ export function addLorasWidget(node, name, opts, callback) {
|
||||
const loraIndex = lorasData.findIndex(l => l.name === name);
|
||||
|
||||
if (loraIndex >= 0) {
|
||||
lorasData[loraIndex].strength = (parseFloat(lorasData[loraIndex].strength) - 0.05).toFixed(2);
|
||||
lorasData[loraIndex].strength = (parseFloat(lorasData[loraIndex].strength) - getStrengthStepPreference()).toFixed(2);
|
||||
// Sync clipStrength if collapsed
|
||||
syncClipStrengthIfCollapsed(lorasData[loraIndex]);
|
||||
|
||||
@@ -488,7 +489,7 @@ export function addLorasWidget(node, name, opts, callback) {
|
||||
const loraIndex = lorasData.findIndex(l => l.name === name);
|
||||
|
||||
if (loraIndex >= 0) {
|
||||
lorasData[loraIndex].strength = (parseFloat(lorasData[loraIndex].strength) + 0.05).toFixed(2);
|
||||
lorasData[loraIndex].strength = (parseFloat(lorasData[loraIndex].strength) + getStrengthStepPreference()).toFixed(2);
|
||||
// Sync clipStrength if collapsed
|
||||
syncClipStrengthIfCollapsed(lorasData[loraIndex]);
|
||||
|
||||
@@ -541,7 +542,7 @@ export function addLorasWidget(node, name, opts, callback) {
|
||||
const loraIndex = lorasData.findIndex(l => l.name === name);
|
||||
|
||||
if (loraIndex >= 0) {
|
||||
lorasData[loraIndex].clipStrength = (parseFloat(lorasData[loraIndex].clipStrength) - 0.05).toFixed(2);
|
||||
lorasData[loraIndex].clipStrength = (parseFloat(lorasData[loraIndex].clipStrength) - getStrengthStepPreference()).toFixed(2);
|
||||
|
||||
const newValue = formatLoraValue(lorasData);
|
||||
updateWidgetValue(newValue);
|
||||
@@ -611,7 +612,7 @@ export function addLorasWidget(node, name, opts, callback) {
|
||||
const loraIndex = lorasData.findIndex(l => l.name === name);
|
||||
|
||||
if (loraIndex >= 0) {
|
||||
lorasData[loraIndex].clipStrength = (parseFloat(lorasData[loraIndex].clipStrength) + 0.05).toFixed(2);
|
||||
lorasData[loraIndex].clipStrength = (parseFloat(lorasData[loraIndex].clipStrength) + getStrengthStepPreference()).toFixed(2);
|
||||
|
||||
const newValue = formatLoraValue(lorasData);
|
||||
updateWidgetValue(newValue);
|
||||
|
||||
@@ -24,6 +24,9 @@ const NEW_TAB_TEMPLATE_DEFAULT = "Default";
|
||||
|
||||
const NEW_TAB_ZOOM_LEVEL = 0.8;
|
||||
|
||||
const STRENGTH_STEP_SETTING_ID = "loramanager.strength_step";
|
||||
const STRENGTH_STEP_DEFAULT = 0.05;
|
||||
|
||||
// ============================================================================
|
||||
// Helper Functions
|
||||
// ============================================================================
|
||||
@@ -232,6 +235,32 @@ const getNewTabTemplatePreference = (() => {
|
||||
};
|
||||
})();
|
||||
|
||||
const getStrengthStepPreference = (() => {
|
||||
let settingsUnavailableLogged = false;
|
||||
|
||||
return () => {
|
||||
const settingManager = app?.extensionManager?.setting;
|
||||
if (!settingManager || typeof settingManager.get !== "function") {
|
||||
if (!settingsUnavailableLogged) {
|
||||
console.warn("LoRA Manager: settings API unavailable, using default strength step.");
|
||||
settingsUnavailableLogged = true;
|
||||
}
|
||||
return STRENGTH_STEP_DEFAULT;
|
||||
}
|
||||
|
||||
try {
|
||||
const value = settingManager.get(STRENGTH_STEP_SETTING_ID);
|
||||
return value ?? STRENGTH_STEP_DEFAULT;
|
||||
} catch (error) {
|
||||
if (!settingsUnavailableLogged) {
|
||||
console.warn("LoRA Manager: unable to read strength step setting, using default.", error);
|
||||
settingsUnavailableLogged = true;
|
||||
}
|
||||
return STRENGTH_STEP_DEFAULT;
|
||||
}
|
||||
};
|
||||
})();
|
||||
|
||||
// ============================================================================
|
||||
// Register Extension with All Settings
|
||||
// ============================================================================
|
||||
@@ -293,6 +322,19 @@ app.registerExtension({
|
||||
tooltip: "Choose a template workflow to load when creating a new workflow tab. 'Default (Blank)' keeps ComfyUI's original blank workflow behavior.",
|
||||
category: ["LoRA Manager", "Workflow", "New Tab Template"],
|
||||
},
|
||||
{
|
||||
id: STRENGTH_STEP_SETTING_ID,
|
||||
name: "Strength Adjustment Step",
|
||||
type: "slider",
|
||||
attrs: {
|
||||
min: 0.01,
|
||||
max: 0.1,
|
||||
step: 0.01,
|
||||
},
|
||||
defaultValue: STRENGTH_STEP_DEFAULT,
|
||||
tooltip: "Step size for adjusting LoRA strength via arrow buttons or keyboard (default: 0.05)",
|
||||
category: ["LoRA Manager", "LoRA Widget", "Strength Step"],
|
||||
},
|
||||
],
|
||||
async setup() {
|
||||
await loadWorkflowOptions();
|
||||
@@ -375,4 +417,5 @@ export {
|
||||
getTagSpaceReplacementPreference,
|
||||
getUsageStatisticsPreference,
|
||||
getNewTabTemplatePreference,
|
||||
getStrengthStepPreference,
|
||||
};
|
||||
|
||||
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Load Diff
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Reference in New Issue
Block a user