Litellm dev 01 01 2025 p3 (#7503)

* fix(utils.py): add new validate tool choice helper function

Prevents https://github.com/BerriAI/litellm/issues/7483

* fix(main.py): add tool choice validation on .completion()

prevents user error like - https://github.com/BerriAI/litellm/issues/7483

* fix(utils.py): fix return val of tool choice validation logic

litellm/main.py

@@ -88,6 +88,7 @@ from litellm.utils import (
     supports_httpx_timeout,
     token_counter,
     validate_chat_completion_messages,
+    validate_chat_completion_tool_choice,
 )
 
 from ._logging import verbose_logger
@@ -847,6 +848,8 @@ def completion(  # type: ignore # noqa: PLR0915
         raise ValueError("model param not passed in.")
     # validate messages
     messages = validate_chat_completion_messages(messages=messages)
+    # validate tool_choice
+    tool_choice = validate_chat_completion_tool_choice(tool_choice=tool_choice)
     ######### unpacking kwargs #####################
     args = locals()
     api_base = kwargs.get("api_base", None)

litellm/utils.py

@@ -6058,6 +6058,34 @@ def validate_chat_completion_user_messages(messages: List[AllMessageValues]):
     return messages
 
 
+def validate_chat_completion_tool_choice(
+    tool_choice: Optional[Union[dict, str]]
+) -> Optional[Union[dict, str]]:
+    """
+    Confirm the tool choice is passed in the OpenAI format.
+
+    Prevents user errors like: https://github.com/BerriAI/litellm/issues/7483
+    """
+    from litellm.types.llms.openai import (
+        ChatCompletionToolChoiceObjectParam,
+        ChatCompletionToolChoiceStringValues,
+    )
+
+    if tool_choice is None:
+        return tool_choice
+    elif isinstance(tool_choice, str):
+        return tool_choice
+    elif isinstance(tool_choice, dict):
+        if tool_choice.get("type") is None or tool_choice.get("function") is None:
+            raise Exception(
+                f"Invalid tool choice, tool_choice={tool_choice}. Please ensure tool_choice follows the OpenAI spec"
+            )
+        return tool_choice
+    raise Exception(
+        f"Invalid tool choice, tool_choice={tool_choice}. Got={type(tool_choice)}. Expecting str, or dict. Please ensure tool_choice follows the OpenAI tool_choice spec"
+    )
+
+
 class ProviderConfigManager:
     @staticmethod
     def get_provider_chat_config(  # noqa: PLR0915

tests/local_testing/test_utils.py

@@ -1085,6 +1085,26 @@ def test_validate_chat_completion_user_messages(messages, expected_bool):
             validate_chat_completion_user_messages(messages=messages)
 
 
+@pytest.mark.parametrize(
+    "tool_choice, expected_bool",
+    [
+        ({"type": "function", "function": {"name": "get_current_weather"}}, True),
+        ({"type": "tool", "name": "get_current_weather"}, False),
+        (None, True),
+        ("auto", True),
+        ("required", True),
+    ],
+)
+def test_validate_chat_completion_tool_choice(tool_choice, expected_bool):
+    from litellm.utils import validate_chat_completion_tool_choice
+
+    if expected_bool:
+        validate_chat_completion_tool_choice(tool_choice=tool_choice)
+    else:
+        with pytest.raises(Exception):
+            validate_chat_completion_tool_choice(tool_choice=tool_choice)
+
+
 def test_models_by_provider():
     """
     Make sure all providers from model map are in the valid providers list