feat(download): add configurable base model download exclusions

py/services/download_manager.py

@@ -13,6 +13,7 @@ from ..utils.models import LoraMetadata, CheckpointMetadata, EmbeddingMetadata
 from ..utils.constants import (
     CARD_PREVIEW_WIDTH,
     DIFFUSION_MODEL_BASE_MODELS,
+    SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS,
     VALID_LORA_TYPES,
 )
 from ..utils.civitai_utils import rewrite_preview_url
@@ -228,7 +229,9 @@ class DownloadManager:
                     # Update status based on result
                     if task_id in self._active_downloads:
                         self._active_downloads[task_id]["status"] = (
-                            "completed" if result["success"] else "failed"
+                            result.get("status", "completed")
+                            if result["success"]
+                            else "failed"
                         )
                         if not result["success"]:
                             self._active_downloads[task_id]["error"] = result.get(
@@ -352,10 +355,54 @@ class DownloadManager:
                     "error": f'Model type "{model_type_from_info}" is not supported for download',
                 }
 
+            excluded_base_models = get_settings_manager().get_download_skip_base_models()
+            base_model_value = version_info.get("baseModel", "")
+            if (
+                isinstance(base_model_value, str)
+                and base_model_value in SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS
+                and base_model_value in excluded_base_models
+            ):
+                file_name = ""
+                files = version_info.get("files")
+                if isinstance(files, list):
+                    primary_file = next(
+                        (
+                            file_info
+                            for file_info in files
+                            if isinstance(file_info, dict) and file_info.get("primary")
+                        ),
+                        None,
+                    )
+                    selected_file = primary_file
+                    if selected_file is None:
+                        selected_file = next(
+                            (file_info for file_info in files if isinstance(file_info, dict)),
+                            None,
+                        )
+                    if isinstance(selected_file, dict):
+                        raw_file_name = selected_file.get("name", "")
+                        if isinstance(raw_file_name, str):
+                            file_name = raw_file_name.strip()
+
+                message = (
+                    f"Skipped download for '{file_name or version_info.get('name') or f'model_version:{model_version_id or model_id}'}' "
+                    f"because base model '{base_model_value}' is excluded in settings"
+                )
+                logger.info(message)
+                return {
+                    "success": True,
+                    "skipped": True,
+                    "status": "skipped",
+                    "reason": "base_model_excluded",
+                    "message": message,
+                    "base_model": base_model_value,
+                    "file_name": file_name,
+                    "download_id": download_id,
+                }
+
             # Check if this checkpoint should be treated as a diffusion model based on baseModel
             is_diffusion_model = False
             if model_type == "checkpoint":
-                base_model_value = version_info.get("baseModel", "")
                 if base_model_value in DIFFUSION_MODEL_BASE_MODELS:
                     is_diffusion_model = True
                     logger.info(

py/services/settings_manager.py

@@ -11,7 +11,11 @@ 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.constants import (
+    DEFAULT_HASH_CHUNK_SIZE_MB,
+    DEFAULT_PRIORITY_TAG_CONFIG,
+    SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS,
+)
 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 (
@@ -73,6 +77,7 @@ DEFAULT_SETTINGS: Dict[str, Any] = {
     "update_flag_strategy": "same_base",
     "auto_organize_exclusions": [],
     "metadata_refresh_skip_paths": [],
+    "download_skip_base_models": [],
 }
 
 
@@ -276,6 +281,21 @@ class SettingsManager:
             self.settings["metadata_refresh_skip_paths"] = []
             inserted_defaults = True
 
+        if "download_skip_base_models" in self.settings:
+            normalized_skip_base_models = self.normalize_download_skip_base_models(
+                self.settings.get("download_skip_base_models")
+            )
+            if normalized_skip_base_models != self.settings.get(
+                "download_skip_base_models"
+            ):
+                self.settings["download_skip_base_models"] = (
+                    normalized_skip_base_models
+                )
+                updated_existing = True
+        else:
+            self.settings["download_skip_base_models"] = []
+            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)
@@ -964,6 +984,45 @@ class SettingsManager:
             self._save_settings()
         return skip_paths
 
+    def normalize_download_skip_base_models(self, value: Any) -> List[str]:
+        if value is None:
+            return []
+
+        if isinstance(value, str):
+            candidates: Iterable[str] = (
+                value.replace("\n", ",").replace(";", ",").split(",")
+            )
+        elif isinstance(value, Sequence) and not isinstance(
+            value, (bytes, bytearray, str)
+        ):
+            candidates = value
+        else:
+            return []
+
+        base_models: List[str] = []
+        seen = set()
+        for raw in candidates:
+            if not isinstance(raw, str):
+                continue
+            token = raw.strip()
+            if not token or token not in SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS:
+                continue
+            if token in seen:
+                continue
+            seen.add(token)
+            base_models.append(token)
+
+        return base_models
+
+    def get_download_skip_base_models(self) -> List[str]:
+        base_models = self.normalize_download_skip_base_models(
+            self.settings.get("download_skip_base_models")
+        )
+        if base_models != self.settings.get("download_skip_base_models"):
+            self.settings["download_skip_base_models"] = base_models
+            self._save_settings()
+        return base_models
+
     def get_extra_folder_paths(self) -> Dict[str, List[str]]:
         """Get extra folder paths for the active library.
 
@@ -1032,6 +1091,8 @@ 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 == "download_skip_base_models":
+            value = self.normalize_download_skip_base_models(value)
         elif key == "mature_blur_level":
             value = self.normalize_mature_blur_level(value)
         self.settings[key] = value

py/utils/constants.py

@@ -113,3 +113,59 @@ DIFFUSION_MODEL_BASE_MODELS = frozenset(
         "Qwen",
     ]
 )
+
+# Supported baseModel values for download exclusion settings.
+# Keep this aligned with static/js/utils/constants.js, excluding the generic "Other" value.
+SUPPORTED_DOWNLOAD_SKIP_BASE_MODELS = frozenset(
+    [
+        "SD 1.4",
+        "SD 1.5",
+        "SD 1.5 LCM",
+        "SD 1.5 Hyper",
+        "SD 2.0",
+        "SD 2.1",
+        "SD 3",
+        "SD 3.5",
+        "SD 3.5 Medium",
+        "SD 3.5 Large",
+        "SD 3.5 Large Turbo",
+        "SDXL 1.0",
+        "SDXL Lightning",
+        "SDXL Hyper",
+        "Flux.1 D",
+        "Flux.1 S",
+        "Flux.1 Krea",
+        "Flux.1 Kontext",
+        "Flux.2 D",
+        "Flux.2 Klein 9B",
+        "Flux.2 Klein 9B-base",
+        "Flux.2 Klein 4B",
+        "Flux.2 Klein 4B-base",
+        "AuraFlow",
+        "Chroma",
+        "PixArt a",
+        "PixArt E",
+        "Hunyuan 1",
+        "Lumina",
+        "Kolors",
+        "NoobAI",
+        "Illustrious",
+        "Pony",
+        "HiDream",
+        "Qwen",
+        "ZImageTurbo",
+        "ZImageBase",
+        "SVD",
+        "LTXV",
+        "LTXV2",
+        "Wan Video",
+        "Wan Video 1.3B t2v",
+        "Wan Video 14B t2v",
+        "Wan Video 14B i2v 480p",
+        "Wan Video 14B i2v 720p",
+        "Wan Video 2.2 TI2V-5B",
+        "Wan Video 2.2 T2V-A14B",
+        "Wan Video 2.2 I2V-A14B",
+        "Hunyuan Video",
+    ]
+)