diff --git a/src/backend/base/langflow/components/prompts/LangChainHubPrompt.py b/src/backend/base/langflow/components/prompts/LangChainHubPrompt.py
index a4c4c6d5a..5048abc04 100644
--- a/src/backend/base/langflow/components/prompts/LangChainHubPrompt.py
+++ b/src/backend/base/langflow/components/prompts/LangChainHubPrompt.py
@@ -21,13 +21,14 @@ class LangChainHubPromptComponent(Component):
             name="langchain_api_key",
             display_name="Your LangChain API Key",
             info="The LangChain API Key to use.",
+            required=True,
         ),
         StrInput(
             name="langchain_hub_prompt",
             display_name="LangChain Hub Prompt",
-            info="The LangChain Hub prompt to use.",
-            value="efriis/my-first-prompt",
+            info="The LangChain Hub prompt to use, i.e., 'efriis/my-first-prompt'",
             refresh_button=True,
+            required=True,
         ),
     ]
 
@@ -36,63 +37,70 @@ class LangChainHubPromptComponent(Component):
     ]
 
     def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):
-        if field_name == "langchain_hub_prompt":
-            template = self._fetch_langchain_hub_template()
+        # If the field is not langchain_hub_prompt or the value is empty, return the build config as is
+        if field_name != "langchain_hub_prompt" or not field_value:
+            return build_config
 
-            # Get the template's messages
-            if hasattr(template, "messages"):
-                template_messages = template.messages
-            else:
-                template_messages = [HumanMessagePromptTemplate(prompt=template)]
+        # Fetch the template
+        template = self._fetch_langchain_hub_template()
 
-            # Extract the messages from the prompt data
-            prompt_template = []
-            for message_data in template_messages:
-                prompt_template.append(message_data.prompt)
+        # Get the template's messages
+        if hasattr(template, "messages"):
+            template_messages = template.messages
+        else:
+            template_messages = [HumanMessagePromptTemplate(prompt=template)]
 
-            # Regular expression to find all instances of {<string>}
-            pattern = r"\{(.*?)\}"
+        # Extract the messages from the prompt data
+        prompt_template = []
+        for message_data in template_messages:
+            prompt_template.append(message_data.prompt)
 
-            # Get all the custom fields
-            custom_fields: list[str] = []
-            full_template = ""
-            for message in prompt_template:
-                # Find all matches
-                matches = re.findall(pattern, message.template)
-                custom_fields = custom_fields + matches
+        # Regular expression to find all instances of {<string>}
+        pattern = r"\{(.*?)\}"
 
-                # Create a string version of the full template
-                full_template = full_template + "\n" + message.template
+        # Get all the custom fields
+        custom_fields: list[str] = []
+        full_template = ""
+        for message in prompt_template:
+            # Find all matches
+            matches = re.findall(pattern, message.template)
+            custom_fields = custom_fields + matches
 
-            # No need to reprocess if we have them already
-            if all("param_" + custom_field in build_config for custom_field in custom_fields):
-                return build_config
+            # Create a string version of the full template
+            full_template = full_template + "\n" + message.template
 
-            # Easter egg: Show template in info popup
-            build_config["langchain_hub_prompt"]["info"] = full_template
+        # No need to reprocess if we have them already
+        if all("param_" + custom_field in build_config for custom_field in custom_fields):
+            return build_config
 
-            # Remove old parameter inputs if any
-            for key, _ in build_config.copy().items():
-                if key.startswith("param_"):
-                    del build_config[key]
+        # Easter egg: Show template in info popup
+        build_config["langchain_hub_prompt"]["info"] = full_template
 
-            # Now create inputs for each
-            for custom_field in custom_fields:
-                new_parameter = DefaultPromptField(
-                    name=f"param_{custom_field}",
-                    display_name=custom_field,
-                    info="Fill in the value for {" + custom_field + "}",
-                ).to_dict()
+        # Remove old parameter inputs if any
+        for key, _ in build_config.copy().items():
+            if key.startswith("param_"):
+                del build_config[key]
 
-                build_config[f"param_{custom_field}"] = new_parameter
+        # Now create inputs for each
+        for custom_field in custom_fields:
+            new_parameter = DefaultPromptField(
+                name=f"param_{custom_field}",
+                display_name=custom_field,
+                info="Fill in the value for {" + custom_field + "}",
+            ).to_dict()
+
+            # Add the new parameter to the build config
+            build_config[f"param_{custom_field}"] = new_parameter
 
         return build_config
 
     async def build_prompt(
         self,
     ) -> Message:
-        # Get the parameters that
-        template = self._fetch_langchain_hub_template()  # TODO: doing this twice
+        # Fetch the template
+        template = self._fetch_langchain_hub_template()
+
+        # Get the parameters from the attributes
         original_params = {k[6:] if k.startswith("param_") else k: v for k, v in self._attributes.items()}
         prompt_value = template.invoke(original_params)
 
@@ -111,6 +119,7 @@ class LangChainHubPromptComponent(Component):
         # Check if the api key is provided
         if not self.langchain_api_key:
             msg = "Please provide a LangChain API Key"
+
             raise ValueError(msg)
 
         # Pull the prompt from LangChain Hub