feat(azure.py): add azure bad request error support

litellm/litellm_core_utils/exception_mapping_utils.py

@@ -422,6 +422,7 @@ def exception_type(  # type: ignore  # noqa: PLR0915
                             llm_provider=custom_llm_provider,
                             response=getattr(original_exception, "response", None),
                             litellm_debug_info=extra_information,
+                            body=getattr(original_exception, "body", None),
                         )
                     elif original_exception.status_code == 429:
                         exception_mapping_worked = True
@@ -1961,6 +1962,7 @@ def exception_type(  # type: ignore  # noqa: PLR0915
                         model=model,
                         litellm_debug_info=extra_information,
                         response=getattr(original_exception, "response", None),
+                        body=getattr(original_exception, "body", None),
                     )
                 elif (
                     "The api_key client option must be set either by passing api_key to the client or by setting"
@@ -1992,6 +1994,7 @@ def exception_type(  # type: ignore  # noqa: PLR0915
                             model=model,
                             litellm_debug_info=extra_information,
                             response=getattr(original_exception, "response", None),
+                            body=getattr(original_exception, "body", None),
                         )
                     elif original_exception.status_code == 401:
                         exception_mapping_worked = True

litellm/llms/azure/azure.py

@@ -540,10 +540,14 @@ class AzureChatCompletion(BaseLLM):
             status_code = getattr(e, "status_code", 500)
             error_headers = getattr(e, "headers", None)
             error_response = getattr(e, "response", None)
+            error_body = getattr(e, "body", None)
             if error_headers is None and error_response:
                 error_headers = getattr(error_response, "headers", None)
             raise AzureOpenAIError(
-                status_code=status_code, message=str(e), headers=error_headers
+                status_code=status_code,
+                message=str(e),
+                headers=error_headers,
+                body=error_body,
             )
 
     async def acompletion(
@@ -649,6 +653,7 @@ class AzureChatCompletion(BaseLLM):
             raise AzureOpenAIError(status_code=500, message=str(e))
         except Exception as e:
             message = getattr(e, "message", str(e))
+            body = getattr(e, "body", None)
             ## LOGGING
             logging_obj.post_call(
                 input=data["messages"],
@@ -659,7 +664,7 @@ class AzureChatCompletion(BaseLLM):
             if hasattr(e, "status_code"):
                 raise e
             else:
-                raise AzureOpenAIError(status_code=500, message=message)
+                raise AzureOpenAIError(status_code=500, message=message, body=body)
 
     def streaming(
         self,
@@ -805,10 +810,14 @@ class AzureChatCompletion(BaseLLM):
             error_headers = getattr(e, "headers", None)
             error_response = getattr(e, "response", None)
             message = getattr(e, "message", str(e))
+            error_body = getattr(e, "body", None)
             if error_headers is None and error_response:
                 error_headers = getattr(error_response, "headers", None)
             raise AzureOpenAIError(
-                status_code=status_code, message=message, headers=error_headers
+                status_code=status_code,
+                message=message,
+                headers=error_headers,
+                body=error_body,
             )
 
     async def aembedding(

litellm/llms/azure/common_utils.py

@@ -17,6 +17,7 @@ class AzureOpenAIError(BaseLLMException):
         request: Optional[httpx.Request] = None,
         response: Optional[httpx.Response] = None,
         headers: Optional[Union[httpx.Headers, dict]] = None,
+        body: Optional[dict] = None,
     ):
         super().__init__(
             status_code=status_code,
@@ -24,6 +25,7 @@ class AzureOpenAIError(BaseLLMException):
             request=request,
             response=response,
             headers=headers,
+            body=body,
         )
 
 

tests/llm_translation/test_openai.py

@@ -391,34 +391,3 @@ def test_openai_chat_completion_streaming_handler_reasoning_content():
     )
 
     assert response.choices[0].delta.reasoning_content == "."
-
-
-@pytest.mark.parametrize("sync_mode", [True, False])
-@pytest.mark.parametrize("stream_mode", [True, False])
-@pytest.mark.asyncio
-async def test_exception_bubbling_up(sync_mode, stream_mode):
-    """
-    make sure code, param, and type are bubbled up
-    """
-    import litellm
-
-    litellm.set_verbose = True
-    with pytest.raises(Exception) as exc_info:
-        if sync_mode:
-            litellm.completion(
-                model="gpt-4o-mini",
-                messages=[{"role": "usera", "content": "hi"}],
-                stream=stream_mode,
-                sync_stream=sync_mode,
-            )
-        else:
-            await litellm.acompletion(
-                model="gpt-4o-mini",
-                messages=[{"role": "usera", "content": "hi"}],
-                stream=stream_mode,
-                sync_stream=sync_mode,
-            )
-
-    assert exc_info.value.code == "invalid_value"
-    assert exc_info.value.param is not None
-    assert exc_info.value.type == "invalid_request_error"

tests/local_testing/test_exceptions.py

@@ -1205,3 +1205,35 @@ def test_context_window_exceeded_error_from_litellm_proxy():
     }
     with pytest.raises(litellm.ContextWindowExceededError):
         extract_and_raise_litellm_exception(**args)
+
+
+@pytest.mark.parametrize("sync_mode", [True, False])
+@pytest.mark.parametrize("stream_mode", [True, False])
+@pytest.mark.parametrize("model", ["azure/gpt-4o"])  # "gpt-4o-mini",
+@pytest.mark.asyncio
+async def test_exception_bubbling_up(sync_mode, stream_mode, model):
+    """
+    make sure code, param, and type are bubbled up
+    """
+    import litellm
+
+    litellm.set_verbose = True
+    with pytest.raises(Exception) as exc_info:
+        if sync_mode:
+            litellm.completion(
+                model=model,
+                messages=[{"role": "usera", "content": "hi"}],
+                stream=stream_mode,
+                sync_stream=sync_mode,
+            )
+        else:
+            await litellm.acompletion(
+                model=model,
+                messages=[{"role": "usera", "content": "hi"}],
+                stream=stream_mode,
+                sync_stream=sync_mode,
+            )
+
+    assert exc_info.value.code == "invalid_value"
+    assert exc_info.value.param is not None
+    assert exc_info.value.type == "invalid_request_error"