mirror of
https://github.com/willmiao/ComfyUI-Lora-Manager.git
synced 2026-03-25 07:05:43 -03:00
Fix null-safety issues and apply code formatting
Bug fixes: - Add null guards for base_models_roots/embeddings_roots in backup cleanup - Fix null-safety initialization of extra_unet_roots Formatting: - Apply consistent code style across Python files - Fix line wrapping, quote consistency, and trailing commas - Add type ignore comments for dynamic/platform-specific code
This commit is contained in:
Will Miao
@@ -6,23 +6,24 @@ from .parsers import (
|
||||
ComfyMetadataParser,
|
||||
MetaFormatParser,
|
||||
AutomaticMetadataParser,
|
||||
CivitaiApiMetadataParser
|
||||
CivitaiApiMetadataParser,
|
||||
)
|
||||
from .base import RecipeMetadataParser
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class RecipeParserFactory:
|
||||
"""Factory for creating recipe metadata parsers"""
|
||||
|
||||
|
||||
@staticmethod
|
||||
def create_parser(metadata) -> RecipeMetadataParser:
|
||||
def create_parser(metadata) -> RecipeMetadataParser | None:
|
||||
"""
|
||||
Create appropriate parser based on the metadata content
|
||||
|
||||
|
||||
Args:
|
||||
metadata: The metadata from the image (dict or str)
|
||||
|
||||
|
||||
Returns:
|
||||
Appropriate RecipeMetadataParser implementation
|
||||
"""
|
||||
@@ -34,17 +35,18 @@ class RecipeParserFactory:
|
||||
except Exception as e:
|
||||
logger.debug(f"CivitaiApiMetadataParser check failed: {e}")
|
||||
pass
|
||||
|
||||
|
||||
# Convert dict to string for other parsers that expect string input
|
||||
try:
|
||||
import json
|
||||
|
||||
metadata_str = json.dumps(metadata)
|
||||
except Exception as e:
|
||||
logger.debug(f"Failed to convert dict to JSON string: {e}")
|
||||
return None
|
||||
else:
|
||||
metadata_str = metadata
|
||||
|
||||
|
||||
# Try ComfyMetadataParser which requires valid JSON
|
||||
try:
|
||||
if ComfyMetadataParser().is_metadata_matching(metadata_str):
|
||||
@@ -52,7 +54,7 @@ class RecipeParserFactory:
|
||||
except Exception:
|
||||
# If JSON parsing fails, move on to other parsers
|
||||
pass
|
||||
|
||||
|
||||
# Check other parsers that expect string input
|
||||
if RecipeFormatParser().is_metadata_matching(metadata_str):
|
||||
return RecipeFormatParser()
|
||||
|
||||
@@ -9,15 +9,16 @@ from ...services.metadata_service import get_default_metadata_provider
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
"""Parser for Civitai image metadata format"""
|
||||
|
||||
|
||||
def is_metadata_matching(self, metadata) -> bool:
|
||||
"""Check if the metadata matches the Civitai image metadata format
|
||||
|
||||
|
||||
Args:
|
||||
metadata: The metadata from the image (dict)
|
||||
|
||||
|
||||
Returns:
|
||||
bool: True if this parser can handle the metadata
|
||||
"""
|
||||
@@ -28,7 +29,7 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
# Check for common CivitAI image metadata fields
|
||||
civitai_image_fields = (
|
||||
"resources",
|
||||
"civitaiResources",
|
||||
"civitaiResources",
|
||||
"additionalResources",
|
||||
"hashes",
|
||||
"prompt",
|
||||
@@ -40,7 +41,7 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
"width",
|
||||
"height",
|
||||
"Model",
|
||||
"Model hash"
|
||||
"Model hash",
|
||||
)
|
||||
return any(key in payload for key in civitai_image_fields)
|
||||
|
||||
@@ -50,7 +51,9 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
|
||||
# Check for LoRA hash patterns
|
||||
hashes = metadata.get("hashes")
|
||||
if isinstance(hashes, dict) and any(str(key).lower().startswith("lora:") for key in hashes):
|
||||
if isinstance(hashes, dict) and any(
|
||||
str(key).lower().startswith("lora:") for key in hashes
|
||||
):
|
||||
return True
|
||||
|
||||
# Check nested meta object (common in CivitAI image responses)
|
||||
@@ -61,22 +64,28 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
|
||||
# Also check for LoRA hash patterns in nested meta
|
||||
hashes = nested_meta.get("hashes")
|
||||
if isinstance(hashes, dict) and any(str(key).lower().startswith("lora:") for key in hashes):
|
||||
if isinstance(hashes, dict) and any(
|
||||
str(key).lower().startswith("lora:") for key in hashes
|
||||
):
|
||||
return True
|
||||
|
||||
return False
|
||||
|
||||
async def parse_metadata(self, metadata, recipe_scanner=None, civitai_client=None) -> Dict[str, Any]:
|
||||
|
||||
async def parse_metadata( # type: ignore[override]
|
||||
self, user_comment, recipe_scanner=None, civitai_client=None
|
||||
) -> Dict[str, Any]:
|
||||
"""Parse metadata from Civitai image format
|
||||
|
||||
|
||||
Args:
|
||||
metadata: The metadata from the image (dict)
|
||||
user_comment: The metadata from the image (dict)
|
||||
recipe_scanner: Optional recipe scanner service
|
||||
civitai_client: Optional Civitai API client (deprecated, use metadata_provider instead)
|
||||
|
||||
|
||||
Returns:
|
||||
Dict containing parsed recipe data
|
||||
"""
|
||||
metadata: Dict[str, Any] = user_comment # type: ignore[assignment]
|
||||
metadata = user_comment
|
||||
try:
|
||||
# Get metadata provider instead of using civitai_client directly
|
||||
metadata_provider = await get_default_metadata_provider()
|
||||
@@ -100,19 +109,19 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
)
|
||||
):
|
||||
metadata = inner_meta
|
||||
|
||||
|
||||
# Initialize result structure
|
||||
result = {
|
||||
'base_model': None,
|
||||
'loras': [],
|
||||
'model': None,
|
||||
'gen_params': {},
|
||||
'from_civitai_image': True
|
||||
"base_model": None,
|
||||
"loras": [],
|
||||
"model": None,
|
||||
"gen_params": {},
|
||||
"from_civitai_image": True,
|
||||
}
|
||||
|
||||
|
||||
# Track already added LoRAs to prevent duplicates
|
||||
added_loras = {} # key: model_version_id or hash, value: index in result["loras"]
|
||||
|
||||
|
||||
# Extract hash information from hashes field for LoRA matching
|
||||
lora_hashes = {}
|
||||
if "hashes" in metadata and isinstance(metadata["hashes"], dict):
|
||||
@@ -121,14 +130,14 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
if key_str.lower().startswith("lora:"):
|
||||
lora_name = key_str.split(":", 1)[1]
|
||||
lora_hashes[lora_name] = hash_value
|
||||
|
||||
|
||||
# Extract prompt and negative prompt
|
||||
if "prompt" in metadata:
|
||||
result["gen_params"]["prompt"] = metadata["prompt"]
|
||||
|
||||
|
||||
if "negativePrompt" in metadata:
|
||||
result["gen_params"]["negative_prompt"] = metadata["negativePrompt"]
|
||||
|
||||
|
||||
# Extract other generation parameters
|
||||
param_mapping = {
|
||||
"steps": "steps",
|
||||
@@ -138,98 +147,117 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
"Size": "size",
|
||||
"clipSkip": "clip_skip",
|
||||
}
|
||||
|
||||
|
||||
for civitai_key, our_key in param_mapping.items():
|
||||
if civitai_key in metadata and our_key in GEN_PARAM_KEYS:
|
||||
result["gen_params"][our_key] = metadata[civitai_key]
|
||||
|
||||
|
||||
# Extract base model information - directly if available
|
||||
if "baseModel" in metadata:
|
||||
result["base_model"] = metadata["baseModel"]
|
||||
elif "Model hash" in metadata and metadata_provider:
|
||||
model_hash = metadata["Model hash"]
|
||||
model_info, error = await metadata_provider.get_model_by_hash(model_hash)
|
||||
model_info, error = await metadata_provider.get_model_by_hash(
|
||||
model_hash
|
||||
)
|
||||
if model_info:
|
||||
result["base_model"] = model_info.get("baseModel", "")
|
||||
elif "Model" in metadata and isinstance(metadata.get("resources"), list):
|
||||
# Try to find base model in resources
|
||||
for resource in metadata.get("resources", []):
|
||||
if resource.get("type") == "model" and resource.get("name") == metadata.get("Model"):
|
||||
if resource.get("type") == "model" and resource.get(
|
||||
"name"
|
||||
) == metadata.get("Model"):
|
||||
# This is likely the checkpoint model
|
||||
if metadata_provider and resource.get("hash"):
|
||||
model_info, error = await metadata_provider.get_model_by_hash(resource.get("hash"))
|
||||
(
|
||||
model_info,
|
||||
error,
|
||||
) = await metadata_provider.get_model_by_hash(
|
||||
resource.get("hash")
|
||||
)
|
||||
if model_info:
|
||||
result["base_model"] = model_info.get("baseModel", "")
|
||||
|
||||
|
||||
base_model_counts = {}
|
||||
|
||||
|
||||
# Process standard resources array
|
||||
if "resources" in metadata and isinstance(metadata["resources"], list):
|
||||
for resource in metadata["resources"]:
|
||||
# Modified to process resources without a type field as potential LoRAs
|
||||
if resource.get("type", "lora") == "lora":
|
||||
lora_hash = resource.get("hash", "")
|
||||
|
||||
|
||||
# Try to get hash from the hashes field if not present in resource
|
||||
if not lora_hash and resource.get("name"):
|
||||
lora_hash = lora_hashes.get(resource["name"], "")
|
||||
|
||||
|
||||
# Skip LoRAs without proper identification (hash or modelVersionId)
|
||||
if not lora_hash and not resource.get("modelVersionId"):
|
||||
logger.debug(f"Skipping LoRA resource '{resource.get('name', 'Unknown')}' - no hash or modelVersionId")
|
||||
logger.debug(
|
||||
f"Skipping LoRA resource '{resource.get('name', 'Unknown')}' - no hash or modelVersionId"
|
||||
)
|
||||
continue
|
||||
|
||||
|
||||
# Skip if we've already added this LoRA by hash
|
||||
if lora_hash and lora_hash in added_loras:
|
||||
continue
|
||||
|
||||
|
||||
lora_entry = {
|
||||
'name': resource.get("name", "Unknown LoRA"),
|
||||
'type': "lora",
|
||||
'weight': float(resource.get("weight", 1.0)),
|
||||
'hash': lora_hash,
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': resource.get("name", "Unknown"),
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
"name": resource.get("name", "Unknown LoRA"),
|
||||
"type": "lora",
|
||||
"weight": float(resource.get("weight", 1.0)),
|
||||
"hash": lora_hash,
|
||||
"existsLocally": False,
|
||||
"localPath": None,
|
||||
"file_name": resource.get("name", "Unknown"),
|
||||
"thumbnailUrl": "/loras_static/images/no-preview.png",
|
||||
"baseModel": "",
|
||||
"size": 0,
|
||||
"downloadUrl": "",
|
||||
"isDeleted": False,
|
||||
}
|
||||
|
||||
|
||||
# Try to get info from Civitai if hash is available
|
||||
if lora_entry['hash'] and metadata_provider:
|
||||
if lora_entry["hash"] and metadata_provider:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(lora_hash)
|
||||
|
||||
civitai_info = (
|
||||
await metadata_provider.get_model_by_hash(lora_hash)
|
||||
)
|
||||
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info,
|
||||
recipe_scanner,
|
||||
base_model_counts,
|
||||
lora_hash
|
||||
lora_hash,
|
||||
)
|
||||
|
||||
|
||||
if populated_entry is None:
|
||||
continue # Skip invalid LoRA types
|
||||
|
||||
|
||||
lora_entry = populated_entry
|
||||
|
||||
|
||||
# If we have a version ID from Civitai, track it for deduplication
|
||||
if 'id' in lora_entry and lora_entry['id']:
|
||||
added_loras[str(lora_entry['id'])] = len(result["loras"])
|
||||
if "id" in lora_entry and lora_entry["id"]:
|
||||
added_loras[str(lora_entry["id"])] = len(
|
||||
result["loras"]
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}")
|
||||
|
||||
logger.error(
|
||||
f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
|
||||
)
|
||||
|
||||
# Track by hash if we have it
|
||||
if lora_hash:
|
||||
added_loras[lora_hash] = len(result["loras"])
|
||||
|
||||
|
||||
result["loras"].append(lora_entry)
|
||||
|
||||
|
||||
# Process civitaiResources array
|
||||
if "civitaiResources" in metadata and isinstance(metadata["civitaiResources"], list):
|
||||
if "civitaiResources" in metadata and isinstance(
|
||||
metadata["civitaiResources"], list
|
||||
):
|
||||
for resource in metadata["civitaiResources"]:
|
||||
# Get resource type and identifier
|
||||
resource_type = str(resource.get("type") or "").lower()
|
||||
@@ -237,32 +265,39 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
|
||||
if resource_type == "checkpoint":
|
||||
checkpoint_entry = {
|
||||
'id': resource.get("modelVersionId", 0),
|
||||
'modelId': resource.get("modelId", 0),
|
||||
'name': resource.get("modelName", "Unknown Checkpoint"),
|
||||
'version': resource.get("modelVersionName", ""),
|
||||
'type': resource.get("type", "checkpoint"),
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': resource.get("modelName", ""),
|
||||
'hash': resource.get("hash", "") or "",
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
"id": resource.get("modelVersionId", 0),
|
||||
"modelId": resource.get("modelId", 0),
|
||||
"name": resource.get("modelName", "Unknown Checkpoint"),
|
||||
"version": resource.get("modelVersionName", ""),
|
||||
"type": resource.get("type", "checkpoint"),
|
||||
"existsLocally": False,
|
||||
"localPath": None,
|
||||
"file_name": resource.get("modelName", ""),
|
||||
"hash": resource.get("hash", "") or "",
|
||||
"thumbnailUrl": "/loras_static/images/no-preview.png",
|
||||
"baseModel": "",
|
||||
"size": 0,
|
||||
"downloadUrl": "",
|
||||
"isDeleted": False,
|
||||
}
|
||||
|
||||
if version_id and metadata_provider:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_version_info(version_id)
|
||||
civitai_info = (
|
||||
await metadata_provider.get_model_version_info(
|
||||
version_id
|
||||
)
|
||||
)
|
||||
|
||||
checkpoint_entry = await self.populate_checkpoint_from_civitai(
|
||||
checkpoint_entry,
|
||||
civitai_info
|
||||
checkpoint_entry = (
|
||||
await self.populate_checkpoint_from_civitai(
|
||||
checkpoint_entry, civitai_info
|
||||
)
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for checkpoint version {version_id}: {e}")
|
||||
logger.error(
|
||||
f"Error fetching Civitai info for checkpoint version {version_id}: {e}"
|
||||
)
|
||||
|
||||
if result["model"] is None:
|
||||
result["model"] = checkpoint_entry
|
||||
@@ -275,31 +310,35 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
|
||||
# Initialize lora entry
|
||||
lora_entry = {
|
||||
'id': resource.get("modelVersionId", 0),
|
||||
'modelId': resource.get("modelId", 0),
|
||||
'name': resource.get("modelName", "Unknown LoRA"),
|
||||
'version': resource.get("modelVersionName", ""),
|
||||
'type': resource.get("type", "lora"),
|
||||
'weight': round(float(resource.get("weight", 1.0)), 2),
|
||||
'existsLocally': False,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
"id": resource.get("modelVersionId", 0),
|
||||
"modelId": resource.get("modelId", 0),
|
||||
"name": resource.get("modelName", "Unknown LoRA"),
|
||||
"version": resource.get("modelVersionName", ""),
|
||||
"type": resource.get("type", "lora"),
|
||||
"weight": round(float(resource.get("weight", 1.0)), 2),
|
||||
"existsLocally": False,
|
||||
"thumbnailUrl": "/loras_static/images/no-preview.png",
|
||||
"baseModel": "",
|
||||
"size": 0,
|
||||
"downloadUrl": "",
|
||||
"isDeleted": False,
|
||||
}
|
||||
|
||||
# Try to get info from Civitai if modelVersionId is available
|
||||
if version_id and metadata_provider:
|
||||
try:
|
||||
# Use get_model_version_info instead of get_model_version
|
||||
civitai_info = await metadata_provider.get_model_version_info(version_id)
|
||||
civitai_info = (
|
||||
await metadata_provider.get_model_version_info(
|
||||
version_id
|
||||
)
|
||||
)
|
||||
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info,
|
||||
recipe_scanner,
|
||||
base_model_counts
|
||||
base_model_counts,
|
||||
)
|
||||
|
||||
if populated_entry is None:
|
||||
@@ -307,74 +346,87 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
|
||||
lora_entry = populated_entry
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for model version {version_id}: {e}")
|
||||
logger.error(
|
||||
f"Error fetching Civitai info for model version {version_id}: {e}"
|
||||
)
|
||||
|
||||
# Track this LoRA in our deduplication dict
|
||||
if version_id:
|
||||
added_loras[version_id] = len(result["loras"])
|
||||
|
||||
result["loras"].append(lora_entry)
|
||||
|
||||
|
||||
# Process additionalResources array
|
||||
if "additionalResources" in metadata and isinstance(metadata["additionalResources"], list):
|
||||
if "additionalResources" in metadata and isinstance(
|
||||
metadata["additionalResources"], list
|
||||
):
|
||||
for resource in metadata["additionalResources"]:
|
||||
# Skip resources that aren't LoRAs or LyCORIS
|
||||
if resource.get("type") not in ["lora", "lycoris"] and "type" not in resource:
|
||||
if (
|
||||
resource.get("type") not in ["lora", "lycoris"]
|
||||
and "type" not in resource
|
||||
):
|
||||
continue
|
||||
|
||||
|
||||
lora_type = resource.get("type", "lora")
|
||||
name = resource.get("name", "")
|
||||
|
||||
|
||||
# Extract ID from URN format if available
|
||||
version_id = None
|
||||
if name and "civitai:" in name:
|
||||
parts = name.split("@")
|
||||
if len(parts) > 1:
|
||||
version_id = parts[1]
|
||||
|
||||
|
||||
# Skip if we've already added this LoRA
|
||||
if version_id in added_loras:
|
||||
continue
|
||||
|
||||
|
||||
lora_entry = {
|
||||
'name': name,
|
||||
'type': lora_type,
|
||||
'weight': float(resource.get("strength", 1.0)),
|
||||
'hash': "",
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': name,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
"name": name,
|
||||
"type": lora_type,
|
||||
"weight": float(resource.get("strength", 1.0)),
|
||||
"hash": "",
|
||||
"existsLocally": False,
|
||||
"localPath": None,
|
||||
"file_name": name,
|
||||
"thumbnailUrl": "/loras_static/images/no-preview.png",
|
||||
"baseModel": "",
|
||||
"size": 0,
|
||||
"downloadUrl": "",
|
||||
"isDeleted": False,
|
||||
}
|
||||
|
||||
|
||||
# If we have a version ID and metadata provider, try to get more info
|
||||
if version_id and metadata_provider:
|
||||
try:
|
||||
# Use get_model_version_info with the version ID
|
||||
civitai_info = await metadata_provider.get_model_version_info(version_id)
|
||||
|
||||
civitai_info = (
|
||||
await metadata_provider.get_model_version_info(
|
||||
version_id
|
||||
)
|
||||
)
|
||||
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info,
|
||||
recipe_scanner,
|
||||
base_model_counts
|
||||
base_model_counts,
|
||||
)
|
||||
|
||||
|
||||
if populated_entry is None:
|
||||
continue # Skip invalid LoRA types
|
||||
|
||||
|
||||
lora_entry = populated_entry
|
||||
|
||||
|
||||
# Track this LoRA for deduplication
|
||||
if version_id:
|
||||
added_loras[version_id] = len(result["loras"])
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for model ID {version_id}: {e}")
|
||||
|
||||
logger.error(
|
||||
f"Error fetching Civitai info for model ID {version_id}: {e}"
|
||||
)
|
||||
|
||||
result["loras"].append(lora_entry)
|
||||
|
||||
# If we found LoRA hashes in the metadata but haven't already
|
||||
@@ -390,30 +442,32 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
continue
|
||||
|
||||
lora_entry = {
|
||||
'name': lora_name,
|
||||
'type': "lora",
|
||||
'weight': 1.0,
|
||||
'hash': lora_hash,
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': lora_name,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
"name": lora_name,
|
||||
"type": "lora",
|
||||
"weight": 1.0,
|
||||
"hash": lora_hash,
|
||||
"existsLocally": False,
|
||||
"localPath": None,
|
||||
"file_name": lora_name,
|
||||
"thumbnailUrl": "/loras_static/images/no-preview.png",
|
||||
"baseModel": "",
|
||||
"size": 0,
|
||||
"downloadUrl": "",
|
||||
"isDeleted": False,
|
||||
}
|
||||
|
||||
if metadata_provider:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(lora_hash)
|
||||
civitai_info = await metadata_provider.get_model_by_hash(
|
||||
lora_hash
|
||||
)
|
||||
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info,
|
||||
recipe_scanner,
|
||||
base_model_counts,
|
||||
lora_hash
|
||||
lora_hash,
|
||||
)
|
||||
|
||||
if populated_entry is None:
|
||||
@@ -421,80 +475,93 @@ class CivitaiApiMetadataParser(RecipeMetadataParser):
|
||||
|
||||
lora_entry = populated_entry
|
||||
|
||||
if 'id' in lora_entry and lora_entry['id']:
|
||||
added_loras[str(lora_entry['id'])] = len(result["loras"])
|
||||
if "id" in lora_entry and lora_entry["id"]:
|
||||
added_loras[str(lora_entry["id"])] = len(result["loras"])
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for LoRA hash {lora_hash}: {e}")
|
||||
logger.error(
|
||||
f"Error fetching Civitai info for LoRA hash {lora_hash}: {e}"
|
||||
)
|
||||
|
||||
added_loras[lora_hash] = len(result["loras"])
|
||||
result["loras"].append(lora_entry)
|
||||
|
||||
# Check for LoRA info in the format "Lora_0 Model hash", "Lora_0 Model name", etc.
|
||||
lora_index = 0
|
||||
while f"Lora_{lora_index} Model hash" in metadata and f"Lora_{lora_index} Model name" in metadata:
|
||||
while (
|
||||
f"Lora_{lora_index} Model hash" in metadata
|
||||
and f"Lora_{lora_index} Model name" in metadata
|
||||
):
|
||||
lora_hash = metadata[f"Lora_{lora_index} Model hash"]
|
||||
lora_name = metadata[f"Lora_{lora_index} Model name"]
|
||||
lora_strength_model = float(metadata.get(f"Lora_{lora_index} Strength model", 1.0))
|
||||
|
||||
lora_strength_model = float(
|
||||
metadata.get(f"Lora_{lora_index} Strength model", 1.0)
|
||||
)
|
||||
|
||||
# Skip if we've already added this LoRA by hash
|
||||
if lora_hash and lora_hash in added_loras:
|
||||
lora_index += 1
|
||||
continue
|
||||
|
||||
|
||||
lora_entry = {
|
||||
'name': lora_name,
|
||||
'type': "lora",
|
||||
'weight': lora_strength_model,
|
||||
'hash': lora_hash,
|
||||
'existsLocally': False,
|
||||
'localPath': None,
|
||||
'file_name': lora_name,
|
||||
'thumbnailUrl': '/loras_static/images/no-preview.png',
|
||||
'baseModel': '',
|
||||
'size': 0,
|
||||
'downloadUrl': '',
|
||||
'isDeleted': False
|
||||
"name": lora_name,
|
||||
"type": "lora",
|
||||
"weight": lora_strength_model,
|
||||
"hash": lora_hash,
|
||||
"existsLocally": False,
|
||||
"localPath": None,
|
||||
"file_name": lora_name,
|
||||
"thumbnailUrl": "/loras_static/images/no-preview.png",
|
||||
"baseModel": "",
|
||||
"size": 0,
|
||||
"downloadUrl": "",
|
||||
"isDeleted": False,
|
||||
}
|
||||
|
||||
|
||||
# Try to get info from Civitai if hash is available
|
||||
if lora_entry['hash'] and metadata_provider:
|
||||
if lora_entry["hash"] and metadata_provider:
|
||||
try:
|
||||
civitai_info = await metadata_provider.get_model_by_hash(lora_hash)
|
||||
|
||||
civitai_info = await metadata_provider.get_model_by_hash(
|
||||
lora_hash
|
||||
)
|
||||
|
||||
populated_entry = await self.populate_lora_from_civitai(
|
||||
lora_entry,
|
||||
civitai_info,
|
||||
recipe_scanner,
|
||||
base_model_counts,
|
||||
lora_hash
|
||||
lora_hash,
|
||||
)
|
||||
|
||||
|
||||
if populated_entry is None:
|
||||
lora_index += 1
|
||||
continue # Skip invalid LoRA types
|
||||
|
||||
|
||||
lora_entry = populated_entry
|
||||
|
||||
|
||||
# If we have a version ID from Civitai, track it for deduplication
|
||||
if 'id' in lora_entry and lora_entry['id']:
|
||||
added_loras[str(lora_entry['id'])] = len(result["loras"])
|
||||
if "id" in lora_entry and lora_entry["id"]:
|
||||
added_loras[str(lora_entry["id"])] = len(result["loras"])
|
||||
except Exception as e:
|
||||
logger.error(f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}")
|
||||
|
||||
logger.error(
|
||||
f"Error fetching Civitai info for LoRA hash {lora_entry['hash']}: {e}"
|
||||
)
|
||||
|
||||
# Track by hash if we have it
|
||||
if lora_hash:
|
||||
added_loras[lora_hash] = len(result["loras"])
|
||||
|
||||
|
||||
result["loras"].append(lora_entry)
|
||||
|
||||
|
||||
lora_index += 1
|
||||
|
||||
|
||||
# If base model wasn't found earlier, use the most common one from LoRAs
|
||||
if not result["base_model"] and base_model_counts:
|
||||
result["base_model"] = max(base_model_counts.items(), key=lambda x: x[1])[0]
|
||||
|
||||
result["base_model"] = max(
|
||||
base_model_counts.items(), key=lambda x: x[1]
|
||||
)[0]
|
||||
|
||||
return result
|
||||
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Error parsing Civitai image metadata: {e}", exc_info=True)
|
||||
return {"error": str(e), "loras": []}
|
||||
|
||||
Reference in New Issue
Block a user