diff --git a/vllm/entrypoints/openai/serving_classification.py b/vllm/entrypoints/openai/serving_classification.py
index 45bbe732a680..263c5ca3ea7d 100644
--- a/vllm/entrypoints/openai/serving_classification.py
+++ b/vllm/entrypoints/openai/serving_classification.py
@@ -64,7 +64,7 @@ async def _preprocess(
 
         except (ValueError, TypeError) as e:
             logger.exception("Error in preprocessing prompt inputs")
-            return self.create_error_response(str(e))
+            return self.create_error_response(f"{e} {e.__cause__}")
 
     @override
     def _build_response(
diff --git a/vllm/entrypoints/openai/serving_completion.py b/vllm/entrypoints/openai/serving_completion.py
index 7af64306023a..908b851bf3f8 100644
--- a/vllm/entrypoints/openai/serving_completion.py
+++ b/vllm/entrypoints/openai/serving_completion.py
@@ -127,18 +127,9 @@ async def create_completion(
                 prompt_embeds=request.prompt_embeds,
                 config=self._build_render_config(request),
             )
-        except ValueError as e:
-            logger.exception("Error in preprocessing prompt inputs")
-            return self.create_error_response(str(e))
-        except TypeError as e:
-            logger.exception("Error in preprocessing prompt inputs")
-            return self.create_error_response(str(e))
-        except RuntimeError as e:
-            logger.exception("Error in preprocessing prompt inputs")
-            return self.create_error_response(str(e))
-        except jinja2.TemplateError as e:
+        except (ValueError, TypeError, RuntimeError, jinja2.TemplateError) as e:
             logger.exception("Error in preprocessing prompt inputs")
-            return self.create_error_response(str(e))
+            return self.create_error_response(f"{e} {e.__cause__}")
 
         # Schedule the request and get the result generator.
         generators: list[AsyncGenerator[RequestOutput, None]] = []
diff --git a/vllm/entrypoints/openai/serving_embedding.py b/vllm/entrypoints/openai/serving_embedding.py
index 8f1df9a5aea6..966af119a1da 100644
--- a/vllm/entrypoints/openai/serving_embedding.py
+++ b/vllm/entrypoints/openai/serving_embedding.py
@@ -111,7 +111,7 @@ async def _preprocess(
             return None
         except (ValueError, TypeError) as e:
             logger.exception("Error in preprocessing prompt inputs")
-            return self.create_error_response(str(e))
+            return self.create_error_response(f"{e} {e.__cause__}")
 
     def _build_render_config(self, request: EmbeddingCompletionRequest) -> RenderConfig:
         # Set max_length based on chunked processing capability
diff --git a/vllm/entrypoints/openai/serving_pooling.py b/vllm/entrypoints/openai/serving_pooling.py
index 39cc539c1187..7f37801b57fa 100644
--- a/vllm/entrypoints/openai/serving_pooling.py
+++ b/vllm/entrypoints/openai/serving_pooling.py
@@ -163,7 +163,7 @@ async def create_pooling(
                 raise ValueError(f"Unsupported request of type {type(request)}")
         except (ValueError, TypeError, jinja2.TemplateError) as e:
             logger.exception("Error in preprocessing prompt inputs")
-            return self.create_error_response(str(e))
+            return self.create_error_response(f"{e} {e.__cause__}")
 
         # Schedule the request and get the result generator.
         generators: list[AsyncGenerator[PoolingRequestOutput, None]] = []
diff --git a/vllm/entrypoints/openai/speech_to_text.py b/vllm/entrypoints/openai/speech_to_text.py
index fa6e962a1dd7..653654a3188a 100644
--- a/vllm/entrypoints/openai/speech_to_text.py
+++ b/vllm/entrypoints/openai/speech_to_text.py
@@ -179,7 +179,7 @@ async def _create_speech_to_text(
 
         except ValueError as e:
             logger.exception("Error in preprocessing prompt inputs")
-            return self.create_error_response(str(e))
+            return self.create_error_response(f"{e} {e.__cause__}")
 
         list_result_generator: list[AsyncGenerator[RequestOutput, None]] | None = None
         try: