fix(convert_dict_to_response): accept only a real list as choices and keep /v1/messages alive on an empty one

Narrows the no-choices guard so a dict, string, or None still raises the APIError while an empty list passes through,
guards the non-stream Anthropic bridge against indexing an empty choices list, and repairs test_completion_missing_role,
whose raw-response mock was patched in as the create() callable itself so the handler only ever saw a MagicMock

litellm/litellm_core_utils/llm_response_utils/convert_dict_to_response.py

@@ -3,7 +3,7 @@ import json
 import re
 import time
 import traceback
-from collections.abc import Iterable, Sequence
+from collections.abc import Sequence
 from typing import Final, Literal, cast
 
 import litellm
@@ -179,7 +179,7 @@ async def convert_to_streaming_response_async(
 
     choice_list: Final[list[StreamingChoices]] = []
 
-    if "choices" not in response_object or not isinstance(response_object["choices"], Iterable):
+    if not isinstance(response_object.get("choices"), list):
         from litellm.exceptions import APIError
 
         raise APIError(
@@ -287,7 +287,7 @@ def convert_to_streaming_response(
     model_response_object: Final = ModelResponseStream()
     choice_list: Final[list[StreamingChoices]] = []
 
-    if "choices" not in response_object or not isinstance(response_object["choices"], Iterable):
+    if not isinstance(response_object.get("choices"), list):
         from litellm.exceptions import APIError
 
         raise APIError(
@@ -623,7 +623,7 @@ def convert_to_model_response_object(
                 return convert_to_streaming_response(response_object=response_object)
             choice_list: Final[list[Choices]] = []
 
-            if "choices" not in response_object or not isinstance(response_object["choices"], Iterable):
+            if not isinstance(response_object.get("choices"), list):
                 from litellm.exceptions import APIError
 
                 raise APIError(

litellm/llms/anthropic/experimental_pass_through/adapters/transformation.py

@@ -1487,8 +1487,9 @@ class LiteLLMAnthropicMessagesAdapter:
             anthropic_content.insert(0, polyfill_result.compaction_block)
 
         ## extract finish reason
+        openai_finish_reason: Final = response.choices[0].finish_reason if response.choices else "stop"
         translated_finish_reason: Final = self._translate_openai_finish_reason_to_anthropic(
-            openai_finish_reason=response.choices[0].finish_reason
+            openai_finish_reason=openai_finish_reason
         )
         anthropic_finish_reason: Final = (
             "refusal"

tests/test_litellm/litellm_core_utils/llm_response_utils/test_convert_dict_to_response.py

@@ -1,3 +1,5 @@
+from typing import Final
+
 import pytest
 
 from litellm.constants import RESPONSE_FORMAT_TOOL_NAME
@@ -167,3 +169,31 @@ def test_convert_missing_choices_raises_api_error() -> None:
         )
     assert "no 'choices'" in str(exc_info.value)
 
+
+@pytest.mark.parametrize("choices", [{}, "", None, 0])
+@pytest.mark.asyncio
+async def test_convert_non_list_choices_raises_api_error(choices: object) -> None:
+    from litellm.exceptions import APIError
+    from litellm.litellm_core_utils.llm_response_utils.convert_dict_to_response import (
+        convert_to_streaming_response,
+        convert_to_streaming_response_async,
+    )
+
+    resp: Final = {
+        "id": "x",
+        "created": 1,
+        "model": "gemini-3.5-flash",
+        "object": "chat.completion",
+        "choices": choices,
+    }
+    with pytest.raises(APIError, match="no 'choices'"):
+        convert_to_model_response_object(
+            response_object=resp,
+            model_response_object=ModelResponse(),
+            response_type="completion",
+        )
+    with pytest.raises(APIError, match="no 'choices'"):
+        list(convert_to_streaming_response(response_object=resp))
+    with pytest.raises(APIError, match="no 'choices'"):
+        async for _ in convert_to_streaming_response_async(response_object=resp):
+            pass

tests/test_litellm/llms/anthropic/experimental_pass_through/adapters/test_anthropic_experimental_pass_through_adapters_transformation.py

@@ -41,6 +41,21 @@ from litellm.types.utils import (
 )
 
 
+def test_translate_openai_response_to_anthropic_empty_choices() -> None:
+    response: Final = ModelResponse(
+        id="chatcmpl-empty",
+        model="gemini-3.5-flash",
+        choices=[],
+        usage=Usage(prompt_tokens=10, completion_tokens=0, total_tokens=10),
+    )
+
+    result: Final = LiteLLMAnthropicMessagesAdapter().translate_openai_response_to_anthropic(response)
+
+    assert result["content"] == []
+    assert result["stop_reason"] == "end_turn"
+    assert result["usage"]["input_tokens"] == 10
+
+
 def test_translate_chat_refusal_to_anthropic_response():
     response = ModelResponse(
         id="chatcmpl-refusal",

tests/test_litellm/test_main.py

@@ -120,7 +120,7 @@ def test_completion_missing_role(openai_api_response):
     print(f"openai_api_response: {openai_api_response}")
 
     with patch.object(
-        client.chat.completions.with_raw_response, "create", mock_raw_response
+        client.chat.completions.with_raw_response, "create", MagicMock(return_value=mock_raw_response)
     ) as mock_create:
         litellm.completion(
             model="gpt-4o-mini",