add route payload to deploy Inference Endpoints

src/huggingface_hub/hf_api.py

@@ -7566,6 +7566,10 @@ def create_inference_endpoint(
         custom_image: Optional[Dict] = None,
         secrets: Optional[Dict[str, str]] = None,
         type: InferenceEndpointType = InferenceEndpointType.PROTECTED,
+        domain: Optional[str] = None,
+        path: Optional[str] = None,
+        cache_http_responses: Optional[bool] = None,
+        tags: Optional[List[str]] = None,
         namespace: Optional[str] = None,
         token: Union[bool, str, None] = None,
     ) -> InferenceEndpoint:
@@ -7607,6 +7611,14 @@ def create_inference_endpoint(
                 Secret values to inject in the container environment.
             type ([`InferenceEndpointType]`, *optional*):
                 The type of the Inference Endpoint, which can be `"protected"` (default), `"public"` or `"private"`.
+            domain (`str`, *optional*):
+                The custom domain for the Inference Endpoint deployment, if setup the inference endpoint will be available at this domain (e.g. `"my-new-domain.cool-website.woof"`).
+            path (`str`, *optional*):
+                The custom path to the deployed model, should start with a `/` (e.g. `"/models/google-bert/bert-base-uncased"`).
+            cache_http_responses (`bool`, *optional*):
+                Whether to cache HTTP responses from the Inference Endpoint. Defaults to `False`.
+            tags (`List[str]`, *optional*):
+                A list of tags to associate with the Inference Endpoint.
             namespace (`str`, *optional*):
                 The namespace where the Inference Endpoint will be created. Defaults to the current user's namespace.
             token (Union[bool, str, None], optional):
@@ -7668,6 +7680,7 @@ def create_inference_endpoint(
             ...         "url": "ghcr.io/huggingface/text-generation-inference:1.1.0",
             ...     },
             ...    secrets={"MY_SECRET_KEY": "secret_value"},
+            ...    tags=["dev", "text-generation"],
             ... )
 
             ```
@@ -7703,6 +7716,17 @@ def create_inference_endpoint(
         }
         if secrets:
             payload["model"]["secrets"] = secrets
+        if domain is not None or path is not None:
+            payload["route"] = {}
+            if domain is not None:
+                payload["route"]["domain"] = domain
+            if path is not None:
+                payload["route"]["path"] = path
+        if cache_http_responses is not None:
+            payload["cacheHttpResponses"] = cache_http_responses
+        if tags is not None:
+            payload["tags"] = tags
+
         response = get_session().post(
             f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}",
             headers=self._build_hf_headers(token=token),
@@ -7865,14 +7889,19 @@ def update_inference_endpoint(
         task: Optional[str] = None,
         custom_image: Optional[Dict] = None,
         secrets: Optional[Dict[str, str]] = None,
+        # Route update
+        domain: Optional[str] = None,
+        path: Optional[str] = None,
         # Other
+        cache_http_responses: Optional[bool] = None,
+        tags: Optional[List[str]] = None,
         namespace: Optional[str] = None,
         token: Union[bool, str, None] = None,
     ) -> InferenceEndpoint:
         """Update an Inference Endpoint.
 
-        This method allows the update of either the compute configuration, the deployed model, or both. All arguments are
-        optional but at least one must be provided.
+        This method allows the update of either the compute configuration, the deployed model, the route, or any combination.
+        All arguments are optional but at least one must be provided.
 
         For convenience, you can also update an Inference Endpoint using [`InferenceEndpoint.update`].
 
@@ -7906,6 +7935,17 @@ def update_inference_endpoint(
                 Inference Endpoint running on the `text-generation-inference` (TGI) framework (see examples).
             secrets (`Dict[str, str]`, *optional*):
                 Secret values to inject in the container environment.
+
+            domain (`str`, *optional*):
+                The custom domain for the Inference Endpoint deployment, if setup the inference endpoint will be available at this domain (e.g. `"my-new-domain.cool-website.woof"`).
+            path (`str`, *optional*):
+                The custom path to the deployed model, should start with a `/` (e.g. `"/models/google-bert/bert-base-uncased"`).
+
+            cache_http_responses (`bool`, *optional*):
+                Whether to cache HTTP responses from the Inference Endpoint.
+            tags (`List[str]`, *optional*):
+                A list of tags to associate with the Inference Endpoint.
+
             namespace (`str`, *optional*):
                 The namespace where the Inference Endpoint will be updated. Defaults to the current user's namespace.
             token (Union[bool, str, None], optional):
@@ -7945,6 +7985,14 @@ def update_inference_endpoint(
             payload["model"]["image"] = {"custom": custom_image}
         if secrets is not None:
             payload["model"]["secrets"] = secrets
+        if domain is not None:
+            payload["route"]["domain"] = domain
+        if path is not None:
+            payload["route"]["path"] = path
+        if cache_http_responses is not None:
+            payload["cacheHttpResponses"] = cache_http_responses
+        if tags is not None:
+            payload["tags"] = tags
 
         response = get_session().put(
             f"{constants.INFERENCE_ENDPOINTS_ENDPOINT}/endpoint/{namespace}/{name}",