fix(azure.py): add pre call logging for transcription calls

litellm/llms/azure.py

@@ -15,6 +15,7 @@ import litellm, json
 import httpx
 from .custom_httpx.azure_dall_e_2 import CustomHTTPTransport, AsyncCustomHTTPTransport
 from openai import AzureOpenAI, AsyncAzureOpenAI
+import uuid
 
 
 class AzureOpenAIError(Exception):
@@ -809,6 +810,19 @@ class AzureChatCompletion(BaseLLM):
             azure_client = AzureOpenAI(http_client=litellm.client_session, **azure_client_params)  # type: ignore
         else:
             azure_client = client
+
+        ## LOGGING
+        logging_obj.pre_call(
+            input=f"audio_file_{uuid.uuid4()}",
+            api_key=azure_client.api_key,
+            additional_args={
+                "headers": {"Authorization": f"Bearer {azure_client.api_key}"},
+                "api_base": azure_client._base_url._uri_reference,
+                "atranscription": True,
+                "complete_input_dict": data,
+            },
+        )
+
         response = azure_client.audio.transcriptions.create(
             **data, timeout=timeout  # type: ignore
         )
@@ -845,6 +859,21 @@ class AzureChatCompletion(BaseLLM):
                 )
             else:
                 async_azure_client = client
+
+            ## LOGGING
+            logging_obj.pre_call(
+                input=f"audio_file_{uuid.uuid4()}",
+                api_key=async_azure_client.api_key,
+                additional_args={
+                    "headers": {
+                        "Authorization": f"Bearer {async_azure_client.api_key}"
+                    },
+                    "api_base": async_azure_client._base_url._uri_reference,
+                    "atranscription": True,
+                    "complete_input_dict": data,
+                },
+            )
+
             response = await async_azure_client.audio.transcriptions.create(
                 **data, timeout=timeout
             )  # type: ignore

litellm/utils.py

@@ -981,6 +981,7 @@ class Logging:
                 curl_command = self.model_call_details
 
             # only print verbose if verbose logger is not set
+
             if verbose_logger.level == 0:
                 # this means verbose logger was not switched on - user is in litellm.set_verbose=True
                 print_verbose(f"\033[92m{curl_command}\033[0m\n")

tests/test_whisper.py

@@ -35,6 +35,7 @@ def test_transcription():
 
 
 def test_transcription_azure():
+    litellm.set_verbose = True
     transcript = litellm.transcription(
         model="azure/azure-whisper",
         file=audio_file,
@@ -46,6 +47,8 @@ def test_transcription_azure():
     assert transcript.text is not None
     assert isinstance(transcript.text, str)
 
+    raise Exception("it worked")
+
 
 # test_transcription_azure()