diff --git a/integrations/amazon_sagemaker/src/haystack_integrations/components/generators/amazon_sagemaker/sagemaker.py b/integrations/amazon_sagemaker/src/haystack_integrations/components/generators/amazon_sagemaker/sagemaker.py
index 4eacf33a4..106698558 100644
--- a/integrations/amazon_sagemaker/src/haystack_integrations/components/generators/amazon_sagemaker/sagemaker.py
+++ b/integrations/amazon_sagemaker/src/haystack_integrations/components/generators/amazon_sagemaker/sagemaker.py
@@ -24,11 +24,13 @@
 @component
 class SagemakerGenerator:
     """
-    Enables text generation using Sagemaker. It supports Large Language Models (LLMs) hosted and deployed on a SageMaker
-    Inference Endpoint. For guidance on how to deploy a model to SageMaker, refer to the
+    Enables text generation using Amazon Sagemaker.
+
+    SagemakerGenerator supports Large Language Models (LLMs) hosted and deployed on a SageMaker Inference Endpoint.
+    For guidance on how to deploy a model to SageMaker, refer to the
     [SageMaker JumpStart foundation models documentation](https://docs.aws.amazon.com/sagemaker/latest/dg/jumpstart-foundation-models-use.html).
 
-    **Example:**
+    Usage example:
 
     Make sure your AWS credentials are set up correctly. You can use environment variables or a shared credentials file.
     Then you can use the generator as follows:
@@ -118,13 +120,18 @@ def resolve_secret(secret: Optional[Secret]) -> Optional[str]:
 
     def _get_telemetry_data(self) -> Dict[str, Any]:
         """
-        Data that is sent to Posthog for usage analytics.
+        Returns data that is sent to Posthog for usage analytics.
+        :returns: a dictionary with following keys:
+            - model: The name of the model.
+
         """
         return {"model": self.model}
 
     def to_dict(self) -> Dict[str, Any]:
         """
-        Serialize the object to a dictionary.
+        Serializes the component to a dictionary.
+        :returns:
+            Dictionary with serialized data.
         """
         return default_to_dict(
             self,
@@ -141,7 +148,11 @@ def to_dict(self) -> Dict[str, Any]:
     @classmethod
     def from_dict(cls, data) -> "SagemakerGenerator":
         """
-        Deserialize the dictionary into an instance of SagemakerGenerator.
+        Deserializes the component from a dictionary.
+        :param data:
+            Dictionary to deserialize from.
+        :returns:
+              Deserialized component.
         """
         deserialize_secrets_inplace(
             data["init_parameters"],
@@ -185,14 +196,15 @@ def _get_aws_session(
     @component.output_types(replies=List[str], meta=List[Dict[str, Any]])
     def run(self, prompt: str, generation_kwargs: Optional[Dict[str, Any]] = None):
         """
-        Invoke the text generation inference based on the provided messages and generation parameters.
+        Invoke the text generation inference based on the provided prompt and generation parameters.
 
         :param prompt: The string prompt to use for text generation.
         :param generation_kwargs: Additional keyword arguments for text generation. These parameters will
         potentially override the parameters passed in the `__init__` method.
 
-        :return: A list of strings containing the generated responses and a list of dictionaries containing the metadata
-        for each response.
+        :return: A dictionary with the following keys:
+            - `replies`: A list of strings containing the generated responses
+            - `meta`: A list of dictionaries containing the metadata for each response.
         """
         generation_kwargs = generation_kwargs or self.generation_kwargs
         custom_attributes = ";".join(