增加环绕侦察场景适配

backend_service/venv/lib/python3.13/site-packages/huggingface_hub/cli/_cli_utils.py

@@ -96,7 +96,7 @@ TokenOpt = Annotated[
 ]
 
 PrivateOpt = Annotated[
-    bool,
+    Optional[bool],
     typer.Option(
         help="Whether to create a private repo if repo doesn't exist on the Hub. Ignored if the repo already exists.",
     ),
@@ -144,6 +144,7 @@ def _check_cli_update() -> None:
             return
 
     # Touch the file to mark that we did the check now
+    Path(constants.CHECK_FOR_UPDATE_DONE_PATH).parent.mkdir(parents=True, exist_ok=True)
     Path(constants.CHECK_FOR_UPDATE_DONE_PATH).touch()
 
     # Check latest version from PyPI

backend_service/venv/lib/python3.13/site-packages/huggingface_hub/cli/hf.py

@@ -13,6 +13,7 @@
 # limitations under the License.
 
 
+from huggingface_hub import constants
 from huggingface_hub.cli._cli_utils import check_cli_update, typer_factory
 from huggingface_hub.cli.auth import auth_cli
 from huggingface_hub.cli.cache import cache_cli
@@ -51,7 +52,8 @@ app.add_typer(ie_cli, name="endpoints")
 
 
 def main():
-    logging.set_verbosity_info()
+    if not constants.HF_DEBUG:
+        logging.set_verbosity_info()
     check_cli_update()
     app()
 

backend_service/venv/lib/python3.13/site-packages/huggingface_hub/cli/inference_endpoints.py

@@ -5,7 +5,7 @@ from typing import Annotated, Optional
 
 import typer
 
-from huggingface_hub._inference_endpoints import InferenceEndpoint
+from huggingface_hub._inference_endpoints import InferenceEndpoint, InferenceEndpointScalingMetric
 from huggingface_hub.errors import HfHubHTTPError
 
 from ._cli_utils import TokenOpt, get_hf_api, typer_factory
@@ -112,6 +112,36 @@ def deploy(
         ),
     ] = None,
     token: TokenOpt = None,
+    min_replica: Annotated[
+        int,
+        typer.Option(
+            help="The minimum number of replicas (instances) to keep running for the Inference Endpoint.",
+        ),
+    ] = 1,
+    max_replica: Annotated[
+        int,
+        typer.Option(
+            help="The maximum number of replicas (instances) to scale to for the Inference Endpoint.",
+        ),
+    ] = 1,
+    scale_to_zero_timeout: Annotated[
+        Optional[int],
+        typer.Option(
+            help="The duration in minutes before an inactive endpoint is scaled to zero.",
+        ),
+    ] = None,
+    scaling_metric: Annotated[
+        Optional[InferenceEndpointScalingMetric],
+        typer.Option(
+            help="The metric reference for scaling.",
+        ),
+    ] = None,
+    scaling_threshold: Annotated[
+        Optional[float],
+        typer.Option(
+            help="The scaling metric threshold used to trigger a scale up. Ignored when scaling metric is not provided.",
+        ),
+    ] = None,
 ) -> None:
     """Deploy an Inference Endpoint from a Hub repository."""
     api = get_hf_api(token=token)
@@ -127,6 +157,11 @@ def deploy(
         namespace=namespace,
         task=task,
         token=token,
+        min_replica=min_replica,
+        max_replica=max_replica,
+        scaling_metric=scaling_metric,
+        scaling_threshold=scaling_threshold,
+        scale_to_zero_timeout=scale_to_zero_timeout,
     )
 
     _print_endpoint(endpoint)
@@ -262,6 +297,18 @@ def update(
             help="The duration in minutes before an inactive endpoint is scaled to zero.",
         ),
     ] = None,
+    scaling_metric: Annotated[
+        Optional[InferenceEndpointScalingMetric],
+        typer.Option(
+            help="The metric reference for scaling.",
+        ),
+    ] = None,
+    scaling_threshold: Annotated[
+        Optional[float],
+        typer.Option(
+            help="The scaling metric threshold used to trigger a scale up. Ignored when scaling metric is not provided.",
+        ),
+    ] = None,
     token: TokenOpt = None,
 ) -> None:
     """Update an existing endpoint."""
@@ -280,6 +327,8 @@ def update(
             min_replica=min_replica,
             max_replica=max_replica,
             scale_to_zero_timeout=scale_to_zero_timeout,
+            scaling_metric=scaling_metric,
+            scaling_threshold=scaling_threshold,
             token=token,
         )
     except HfHubHTTPError as error:

backend_service/venv/lib/python3.13/site-packages/huggingface_hub/cli/repo.py

@@ -66,7 +66,7 @@ def repo_create(
             help="Hugging Face Spaces SDK type. Required when --type is set to 'space'.",
         ),
     ] = None,
-    private: PrivateOpt = False,
+    private: PrivateOpt = None,
     token: TokenOpt = None,
     exist_ok: Annotated[
         bool,

backend_service/venv/lib/python3.13/site-packages/huggingface_hub/cli/upload.py

@@ -80,7 +80,7 @@ def upload(
     ] = None,
     repo_type: RepoTypeOpt = RepoType.model,
     revision: RevisionOpt = None,
-    private: PrivateOpt = False,
+    private: PrivateOpt = None,
     include: Annotated[
         Optional[list[str]],
         typer.Option(

backend_service/venv/lib/python3.13/site-packages/huggingface_hub/cli/upload_large_folder.py

@@ -38,7 +38,7 @@ def upload_large_folder(
     ],
     repo_type: RepoTypeOpt = RepoType.model,
     revision: RevisionOpt = None,
-    private: PrivateOpt = False,
+    private: PrivateOpt = None,
     include: Annotated[
         Optional[list[str]],
         typer.Option(