address greptile review feedback (greploop iteration 3)

- Remove redundant _ensure_training_type call from acreate_fine_tuning_job
- Use explicit _AZURE_STATUS_MAP for status normalization

Made-with: Cursor

litellm/llms/azure/fine_tuning/handler.py

@@ -37,7 +37,6 @@ class AzureOpenAIFineTuningAPI(OpenAIFineTuningAPI, BaseAzureLLM):
         create_fine_tuning_job_data: dict,
         openai_client: Union[AsyncOpenAI, AsyncAzureOpenAI],
     ) -> LiteLLMFineTuningJob:
-        self._ensure_training_type(create_fine_tuning_job_data)
         response = await openai_client.fine_tuning.jobs.create(
             **create_fine_tuning_job_data
         )

litellm/llms/openai/fine_tuning/handler.py

@@ -6,6 +6,10 @@ from openai import AsyncAzureOpenAI, AsyncOpenAI, AzureOpenAI, OpenAI
 from litellm._logging import verbose_logger
 from litellm.types.utils import LiteLLMFineTuningJob
 
+_AZURE_STATUS_MAP = {
+    "pending": "queued",
+}
+
 
 def _normalize_fine_tuning_job_dict(
     data: Dict[str, Any], is_azure: bool = False
@@ -16,7 +20,7 @@ def _normalize_fine_tuning_job_dict(
     Azure differences:
     - organization_id: null → ""
     - result_files: null → []
-    - status: "pending" → "queued"
+    - status: mapped via _AZURE_STATUS_MAP
     """
     if not is_azure:
         return data
@@ -29,8 +33,9 @@ def _normalize_fine_tuning_job_dict(
     if normalized.get("result_files") is None:
         normalized["result_files"] = []
 
-    if normalized.get("status") == "pending":
-        normalized["status"] = "queued"
+    status = normalized.get("status")
+    if status in _AZURE_STATUS_MAP:
+        normalized["status"] = _AZURE_STATUS_MAP[status]
 
     return normalized