diff --git a/src/bespokelabs/curator/request_processor/base_online_request_processor.py b/src/bespokelabs/curator/request_processor/base_online_request_processor.py
index 3d8f9af0..2fd5c218 100644
--- a/src/bespokelabs/curator/request_processor/base_online_request_processor.py
+++ b/src/bespokelabs/curator/request_processor/base_online_request_processor.py
@@ -474,6 +474,11 @@ async def handle_single_request_with_retries(
                 status_tracker=status_tracker,
             )
 
+            # Allows us to retry on responses that don't match the response format
+            self.convert_response_to_response_format(
+                generic_response.response_message, self.prompt_formatter.response_format
+            )
+
             # Save response in the base class
             await self.append_generic_response(generic_response, save_filepath)
 
diff --git a/src/bespokelabs/curator/request_processor/base_request_processor.py b/src/bespokelabs/curator/request_processor/base_request_processor.py
index 08743532..f02b5ab7 100644
--- a/src/bespokelabs/curator/request_processor/base_request_processor.py
+++ b/src/bespokelabs/curator/request_processor/base_request_processor.py
@@ -262,6 +262,58 @@ def attempt_loading_cached_dataset(
                     "Deleted file and attempting to regenerate dataset from cached LLM responses."
                 )
 
+    def convert_response_to_response_format(
+        self, response_message: str | dict, response_format: Optional[BaseModel]
+    ) -> Optional[dict | str]:
+        """
+        Converts a response message to a specified Pydantic model format.
+
+        This method takes a response message (either as a string or dict) and validates/converts it
+        according to the provided Pydantic model format. If the response message is a string,
+        it first attempts to parse it as JSON. The resulting dict is then used to construct
+        an instance of the specified Pydantic model.
+
+        Args:
+            response_message (str | dict): The response message to convert, either as a JSON string
+                or a dictionary.
+            response_format (Optional[BaseModel]): The Pydantic model class that defines the
+                expected format of the response.
+
+        Returns:
+            Optional[dict | str]: The validated response message as a Pydantic model instance.
+
+        Raises:
+            json.JSONDecodeError: If the response_message is a string but cannot be parsed as valid JSON.
+            ValidationError: If the parsed response does not match the schema defined by response_format.
+        """
+        # Response message is a string, which is converted to a dict
+        # The dict is then used to construct the response_format Pydantic model
+        try:
+            # First try to parse the response message as JSON
+            if isinstance(response_message, str):
+                try:
+                    response_dict = json.loads(response_message)
+                except json.JSONDecodeError as e:
+                    logger.warning(
+                        f"Failed to parse response message as JSON: {response_message}. "
+                        f"The model likely returned an invalid JSON format."
+                    )
+                    raise e
+            else:
+                response_dict = response_message
+
+            # Then construct the Pydantic model from the parsed dict
+            response_message = response_format(**response_dict)
+            return response_message
+
+        except ValidationError as e:
+            schema_str = json.dumps(response_format.model_json_schema(), indent=2)
+            logger.warning(
+                f"Pydantic failed to parse response message {response_message} with `response_format` {schema_str}. "
+                f"The model likely returned a JSON that does not match the schema of the `response_format`."
+            )
+            raise e
+
     def create_dataset_files(
         self,
         working_dir: str,
@@ -309,38 +361,16 @@ def create_dataset_files(
                             continue
 
                         if prompt_formatter.response_format:
-                            # Response message is a string, which is converted to a dict
-                            # The dict is then used to construct the response_format Pydantic model
                             try:
-                                # First try to parse the response message as JSON
-                                if isinstance(response.response_message, str):
-                                    try:
-                                        response_dict = json.loads(response.response_message)
-                                    except json.JSONDecodeError as e:
-                                        warning_msg = (
-                                            f"Failed to parse response message as JSON: {response.response_message}. "
-                                            f"The model likely returned an invalid JSON format. Will skip this response."
-                                        )
-                                        logger.warning(warning_msg)
-                                        failed_responses_count += 1
-                                        continue
-                                else:
-                                    response_dict = response.response_message
-
-                                # Then construct the Pydantic model from the parsed dict
-                                response.response_message = prompt_formatter.response_format(
-                                    **response_dict
-                                )
-                            except ValidationError as e:
-                                schema_str = json.dumps(
-                                    prompt_formatter.response_format.model_json_schema(),
-                                    indent=2,
+                                response.response_message = (
+                                    self.convert_response_to_response_format(
+                                        response.response_message, prompt_formatter.response_format
+                                    )
                                 )
-                                warning_msg = (
-                                    f"Pydantic failed to parse response message {response.response_message} with `response_format` {schema_str}. "
-                                    f"The model likely returned a JSON that does not match the schema of the `response_format`. Will skip this response."
+                            except (json.JSONDecodeError, ValidationError) as e:
+                                logger.warning(
+                                    "Skipping response due to error parsing response message into response format"
                                 )
-                                logger.warning(warning_msg)
                                 failed_responses_count += 1
                                 continue