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civit -> civitai

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Brandon Rising 2024-01-30 22:25:23 -05:00 committed by Kent Keirsey
parent a769f93be0
commit 522ff4a042
2 changed files with 4 additions and 4 deletions
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2
invokeai/app/services/config/config_default.py
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@ -285,7 +285,7 @@ class InvokeAIAppConfig(InvokeAISettings):
node_cache_size : int = Field(default=512, description="How many cached nodes to keep in memory", json_schema_extra=Categories.Nodes) node_cache_size : int = Field(default=512, description="How many cached nodes to keep in memory", json_schema_extra=Categories.Nodes)
# MODEL IMPORT # MODEL IMPORT
civit_api_key : Optional[str] = Field(default=os.environ.get("CIVIT_API_KEY"), description="API key for Civit", json_schema_extra=Categories.Other) civitai_api_key : Optional[str] = Field(default=os.environ.get("CIVITAI_API_KEY"), description="API key for CivitAI", json_schema_extra=Categories.Other)
# DEPRECATED FIELDS - STILL HERE IN ORDER TO OBTAN VALUES FROM PRE-3.1 CONFIG FILES # DEPRECATED FIELDS - STILL HERE IN ORDER TO OBTAN VALUES FROM PRE-3.1 CONFIG FILES
always_use_cpu : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", json_schema_extra=Categories.MemoryPerformance) always_use_cpu : bool = Field(default=False, description="If true, use the CPU for rendering even if a GPU is available.", json_schema_extra=Categories.MemoryPerformance)

6
invokeai/backend/install/model_install_backend.py
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@ -104,14 +104,14 @@ class ModelInstall(object):
prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None, prediction_type_helper: Optional[Callable[[Path], SchedulerPredictionType]] = None,
model_manager: Optional[ModelManager] = None, model_manager: Optional[ModelManager] = None,
access_token: Optional[str] = None, access_token: Optional[str] = None,
civit_api_key: Optional[str] = None, civitai_api_key: Optional[str] = None,
): ):
self.config = config self.config = config
self.mgr = model_manager or ModelManager(config.model_conf_path) self.mgr = model_manager or ModelManager(config.model_conf_path)
self.datasets = OmegaConf.load(Dataset_path) self.datasets = OmegaConf.load(Dataset_path)
self.prediction_helper = prediction_type_helper self.prediction_helper = prediction_type_helper
self.access_token = access_token or HfFolder.get_token() self.access_token = access_token or HfFolder.get_token()
self.civit_api_key = civit_api_key or config.civit_api_key self.civitai_api_key = civitai_api_key or config.civitai_api_key
self.reverse_paths = self._reverse_paths(self.datasets) self.reverse_paths = self._reverse_paths(self.datasets)
def all_models(self) -> Dict[str, ModelLoadInfo]: def all_models(self) -> Dict[str, ModelLoadInfo]:
@ -330,7 +330,7 @@ class ModelInstall(object):
with TemporaryDirectory(dir=self.config.models_path) as staging: with TemporaryDirectory(dir=self.config.models_path) as staging:
CIVITAI_RE = r".*civitai.com.*" CIVITAI_RE = r".*civitai.com.*"
civit_url = re.match(CIVITAI_RE, url, re.IGNORECASE) civit_url = re.match(CIVITAI_RE, url, re.IGNORECASE)
location = download_with_resume(url, Path(staging), access_token=self.civit_api_key if civit_url else None) location = download_with_resume(url, Path(staging), access_token=self.civitai_api_key if civit_url else None)
if not location: if not location:
logger.error(f"Unable to download {url}. Skipping.") logger.error(f"Unable to download {url}. Skipping.")
info = ModelProbe().heuristic_probe(location, self.prediction_helper) info = ModelProbe().heuristic_probe(location, self.prediction_helper)