PR review comments

Author: agrimk

ads/aqua/client/client.py

@@ -582,13 +582,13 @@ def embeddings(
         payload = {**(payload or {}), "input": input}
         return self._request(payload=payload, headers=headers)
 
-    def list_models(self) -> Union[Dict[str, Any], Iterator[Mapping[str, Any]]]:
-        """Generate embeddings by sending a request to the endpoint.
+    def fetch_data(self) -> Union[Dict[str, Any], Iterator[Mapping[str, Any]]]:
+        """Fetch Data in json format by sending a request to the endpoint.
 
         Args:
 
         Returns:
-            Union[Dict[str, Any], Iterator[Mapping[str, Any]]]: The server's response, typically including the generated embeddings.
+            Union[Dict[str, Any], Iterator[Mapping[str, Any]]]: The server's response, typically including the data in JSON format.
         """
         # headers = {"Content-Type", "application/json"}
         response = self._client.get(self.endpoint)

ads/aqua/extension/deployment_handler.py

@@ -385,7 +385,7 @@ class AquaModelListHandler(AquaAPIhandler):
     @handle_exceptions
     def get(self, model_deployment_id):
         """
-        Handles streaming inference request for the Active Model Deployments
+        Handles get model list for the Active Model Deployment
         Raises
         ------
         HTTPError
@@ -395,10 +395,7 @@ def get(self, model_deployment_id):
         self.set_header("Content-Type", "application/json")
         endpoint: str = ""
         model_deployment = AquaDeploymentApp().get(model_deployment_id)
-        if model_deployment.endpoint.endswith("/"):
-            endpoint = model_deployment.endpoint + "predict/v1/models"
-        else:
-            endpoint = model_deployment.endpoint + "/predict/v1/models"
+        endpoint = model_deployment.endpoint.rstrip("/") + "/predict/v1/models"       
         aqua_client = Client(endpoint=endpoint)
         try:
             list_model_result = aqua_client.list_models()