fix: address review comments on responses/messages handlers and lmcache guard

- engine.py: drop UnboundLocalError-prone isinstance(response, ...) checks in
  except blocks of _handle_responses_request and _handle_messages_request;
  emit SSE-shaped error frames mid-stream instead of raw dicts; add missing
  blank line between handlers.
- engine_args.py: restructure LMCache HMA guard so the warning branch is
  actually reachable when user explicitly sets disable_hybrid_kv_cache_manager=False,
  and correct the inverted message (HMA must be disabled = True).
- requirements.txt: drop stray whitespace in transformers version specifier.

builder/requirements.txt

@@ -9,7 +9,7 @@ typing-extensions>=4.8.0
 pydantic
 pydantic-settings
 hf-transfer
-transformers>= 4.57.0,< 5
+transformers>=4.57.0,<5
 bitsandbytes>=0.45.0
 kernels
 torch-c-dlpack-ext

src/engine.py

@@ -410,13 +410,10 @@ class OpenAIvLLMEngine(vLLMEngine):
                 extra={"request_id": request_id},
                 exc_info=True
             )
-            if isinstance(response, ErrorResponse):
-                yield response.model_dump()
-            else:
-                yield create_error_response(
-                    "Internal server error during response generation",
-                    err_type="InternalServerError"
-                ).model_dump()
+            yield create_error_response(
+                "Internal server error during response generation",
+                err_type="InternalServerError"
+            ).model_dump()
             return
 
         if isinstance(response, (ErrorResponse, ResponsesResponse)):
@@ -436,10 +433,12 @@ class OpenAIvLLMEngine(vLLMEngine):
                 extra={"request_id": request_id},
                 exc_info=True
             )
-            yield create_error_response(
+            error_payload = create_error_response(
                 "Streaming response failed",
                 err_type="InternalServerError"
-            ).model_dump()
+            ).model_dump_json()
+            yield f"event: error\ndata: {error_payload}\n\n"
+
     async def _handle_messages_request(self, openai_request: JobInput):
         request_id = getattr(openai_request, "request_id", "unknown")
 
@@ -470,19 +469,12 @@ class OpenAIvLLMEngine(vLLMEngine):
                 extra={"request_id": request_id},
                 exc_info=True
             )
-            if isinstance(response, ErrorResponse):
-                error_type = getattr(response, "type", "internal_error")
-                error_message = getattr(response, "message", str(e)[:200])
-                yield AnthropicErrorResponse(
-                    error=AnthropicError(type=error_type, message=error_message)
-                ).model_dump()
-            else:
-                yield AnthropicErrorResponse(
-                    error=AnthropicError(
-                        type="internal_error",
-                        message="Failed to generate messages"
-                    )
-                ).model_dump()
+            yield AnthropicErrorResponse(
+                error=AnthropicError(
+                    type="internal_error",
+                    message="Failed to generate messages"
+                )
+            ).model_dump()
             return
 
         if isinstance(response, ErrorResponse):
@@ -507,9 +499,10 @@ class OpenAIvLLMEngine(vLLMEngine):
                 extra={"request_id": request_id},
                 exc_info=True
             )
-            yield AnthropicErrorResponse(
+            error_payload = AnthropicErrorResponse(
                 error=AnthropicError(
                     type="internal_error",
                     message="Error while streaming messages"
                 )
-            ).model_dump()
+            ).model_dump_json()
+            yield f"event: error\ndata: {error_payload}\n\n"

src/engine_args.py

@@ -442,14 +442,17 @@ def get_engine_args():
         )
         lmcache_detected = lmcache_via_offload or lmcache_via_transfer
 
-        if lmcache_detected and not args.get("disable_hybrid_kv_cache_manager"):
-            args["disable_hybrid_kv_cache_manager"] = True
-            logging.info("LMCache detected: automatically setting disable_hybrid_kv_cache_manager=True")
-        elif lmcache_detected and args.get("disable_hybrid_kv_cache_manager") is False:
-            logging.warning(
-                "LMCache configuration detected but disabled: "
-                "disable_hybrid_kv_cache_manager must be False when using LMCache"
-            )
+        if lmcache_detected:
+            current = args.get("disable_hybrid_kv_cache_manager")
+            if current is False:
+                logging.warning(
+                    "disable_hybrid_kv_cache_manager=False conflicts with LMCache; "
+                    "overriding to True (HMA must be disabled when using LMCache)"
+                )
+                args["disable_hybrid_kv_cache_manager"] = True
+            elif current is None:
+                args["disable_hybrid_kv_cache_manager"] = True
+                logging.info("LMCache detected: automatically setting disable_hybrid_kv_cache_manager=True")
     except Exception as e:
         logging.error(
             "Failed to check LMCache configuration: %s",