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feat(download): add configurable base model download exclusions

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Will Miao
2026-03-26 23:06:14 +08:00
parent 5b065b47d4
commit a5191414cc
22 changed files with 988 additions and 4 deletions
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51
py/services/download_manager.py
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@@ -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(