fix(utils.py): azure tool calling streaming

litellm/llms/azure.py

@@ -194,7 +194,6 @@ class AzureChatCompletion(BaseLLM):
                 azure_client_params["azure_ad_token"] = azure_ad_token
             azure_client = AsyncAzureOpenAI(**azure_client_params)
             response = await azure_client.chat.completions.create(**data) 
-            response.model = "azure/" + str(response.model)
             return convert_to_model_response_object(response_object=json.loads(response.model_dump_json()), model_response_object=model_response)
        except AzureOpenAIError as e: 
             exception_mapping_worked = True

litellm/tests/test_stream_chunk_builder.py

@@ -95,7 +95,7 @@ def test_stream_chunk_builder_litellm_tool_call():
     try: 
       litellm.set_verbose = False
       response = litellm.completion(
-          model="gpt-3.5-turbo",
+          model="azure/chatgpt-functioncalling",
           messages=messages,
           tools=tools_schema,
           stream=True,

litellm/tests/test_streaming.py

@@ -137,6 +137,30 @@ def streaming_format_tests(idx, chunk):
     print(f"extracted chunk: {extracted_chunk}")
     return extracted_chunk, finished
 
+tools_schema = [
+    {
+      "type": "function",
+      "function": {
+        "name": "get_current_weather",
+        "description": "Get the current weather in a given location",
+        "parameters": {
+          "type": "object",
+          "properties": {
+            "location": {
+              "type": "string",
+              "description": "The city and state, e.g. San Francisco, CA"
+            },
+            "unit": {
+              "type": "string",
+              "enum": ["celsius", "fahrenheit"]
+            }
+          },
+          "required": ["location"]
+        }
+      }
+    }
+  ]
+
 # def test_completion_cohere_stream():
 # # this is a flaky test due to the cohere API endpoint being unstable
 #     try:
@@ -231,6 +255,26 @@ def test_completion_azure_stream():
         pytest.fail(f"Error occurred: {e}")
 # test_completion_azure_stream() 
 
+def test_completion_azure_function_calling_stream():
+    try:
+        litellm.set_verbose = False
+        user_message = "What is the current weather in Boston?"
+        messages = [{"content": user_message, "role": "user"}]
+        response = completion(
+            model="azure/chatgpt-functioncalling", messages=messages, stream=True, tools=tools_schema
+        )
+        # Add any assertions here to check the response
+        for chunk in response:
+            print(chunk)
+            if chunk["choices"][0]["finish_reason"] == "stop":
+                break
+            print(chunk["choices"][0]["finish_reason"])
+            print(chunk["choices"][0]["delta"]["content"])
+    except Exception as e:
+        pytest.fail(f"Error occurred: {e}")
+
+test_completion_azure_function_calling_stream()
+
 def test_completion_claude_stream():
     try:
         messages = [
@@ -347,7 +391,7 @@ def test_completion_nlp_cloud_stream():
     except Exception as e:
         print(f"Error occurred: {e}")
         pytest.fail(f"Error occurred: {e}")
-test_completion_nlp_cloud_stream()
+# test_completion_nlp_cloud_stream()
 
 def test_completion_claude_stream_bad_key():
     try:

litellm/utils.py

@@ -4933,7 +4933,6 @@ class CustomStreamWrapper:
                     is_finished = True
                     finish_reason = str_line.choices[0].finish_reason
 
-
             return {
                 "text": text, 
                 "is_finished": is_finished, 
@@ -5173,7 +5172,7 @@ class CustomStreamWrapper:
                 print_verbose(f"completion obj content: {completion_obj['content']}")
                 if response_obj["is_finished"]: 
                     model_response.choices[0].finish_reason = response_obj["finish_reason"]
-            
+
             model_response.model = self.model
             print_verbose(f"model_response: {model_response}; completion_obj: {completion_obj}")
             print_verbose(f"model_response finish reason 3: {model_response.choices[0].finish_reason}")
@@ -5196,11 +5195,14 @@ class CustomStreamWrapper:
                 # enter this branch when no content has been passed in response
                 original_chunk = response_obj.get("original_chunk", None)
                 model_response.id = original_chunk.id
-                try:
+                if len(original_chunk.choices) > 0:
-                    delta = dict(original_chunk.choices[0].delta)
+                    try:
-                    model_response.choices[0].delta = Delta(**delta)
+                        delta = dict(original_chunk.choices[0].delta)
-                except:
+                        model_response.choices[0].delta = Delta(**delta)
-                    model_response.choices[0].delta = Delta()
+                    except Exception as e:
+                        model_response.choices[0].delta = Delta()
+                else: 
+                    return
                 model_response.system_fingerprint = original_chunk.system_fingerprint
                 if self.sent_first_chunk == False:
                     model_response.choices[0].delta["role"] = "assistant"
@@ -5232,10 +5234,8 @@ class CustomStreamWrapper:
                 else:
                     chunk = next(self.completion_stream)
                 
-                print_verbose(f"chunk in __next__: {chunk}")
                 if chunk is not None and chunk != b'':
                     response = self.chunk_creator(chunk=chunk)
-                    print_verbose(f"response in __next__: {response}")
                     if response is not None:
                         return response
         except StopIteration: