feat(proxy_server.py): handle pydantic mockselvar error

Fixes https://github.com/BerriAI/litellm/issues/4898#issuecomment-2252105485

litellm/proxy/proxy_server.py

@@ -2371,13 +2371,15 @@ async def async_data_generator(
     try:
         start_time = time.time()
         async for chunk in response:
-
+            verbose_proxy_logger.debug(
+                "async_data_generator: received streaming chunk - {}".format(chunk)
+            )
             ### CALL HOOKS ### - modify outgoing data
             chunk = await proxy_logging_obj.async_post_call_streaming_hook(
                 user_api_key_dict=user_api_key_dict, response=chunk
             )
 
-            chunk = chunk.model_dump_json(exclude_none=True)
+            chunk = chunk.model_dump_json(exclude_none=True, exclude_unset=True)
             try:
                 yield f"data: {chunk}\n\n"
             except Exception as e:

litellm/tests/test_pydantic.py

@@ -0,0 +1,64 @@
+import os
+import sys
+import traceback
+
+from dotenv import load_dotenv
+
+load_dotenv()
+import io
+import os
+
+sys.path.insert(
+    0, os.path.abspath("../..")
+)  # Adds the parent directory to the system path
+import asyncio
+import json
+import os
+import tempfile
+from unittest.mock import MagicMock, patch
+
+import pytest
+
+import litellm
+from litellm.types.utils import (
+    ChatCompletionTokenLogprob,
+    ChoiceLogprobs,
+    Delta,
+    ModelResponse,
+    StreamingChoices,
+    TopLogprob,
+)
+
+obj = ModelResponse(
+    id="chat-f9bad6ec3c1146e99368682a0e7403fc",
+    choices=[
+        StreamingChoices(
+            finish_reason=None,
+            index=0,
+            delta=Delta(content="", role=None, function_call=None, tool_calls=None),
+            logprobs=ChoiceLogprobs(
+                content=[
+                    ChatCompletionTokenLogprob(
+                        token="",
+                        bytes=[],
+                        logprob=-0.00018153927521780133,
+                        top_logprobs=[
+                            TopLogprob(
+                                token="", bytes=[], logprob=-0.00018153927521780133
+                            ),
+                            TopLogprob(
+                                token="\n\n", bytes=[10, 10], logprob=-9.062681198120117
+                            ),
+                        ],
+                    )
+                ]
+            ),
+        )
+    ],
+    created=1721976759,
+    model="Meta-Llama-3-8B-Instruct",
+    object="chat.completion.chunk",
+    system_fingerprint=None,
+)
+
+print(obj.model_dump())