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fix(utils.py): check if ollama model has custom attributes

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Fixes https://github.com/BerriAI/litellm/discussions/9630
This commit is contained in:
Krrish Dholakia 2025-05-07 13:27:56 -07:00
parent 1dd71d5727
commit 314b68cfd4
1 changed files with 34 additions and 20 deletions
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54
litellm/utils.py
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@ -523,9 +523,9 @@ def function_setup( # noqa: PLR0915
function_id: Optional[str] = kwargs["id"] if "id" in kwargs else None
## DYNAMIC CALLBACKS ##
dynamic_callbacks: Optional[List[Union[str, Callable, CustomLogger]]] = (
kwargs.pop("callbacks", None)
)
dynamic_callbacks: Optional[
List[Union[str, Callable, CustomLogger]]
] = kwargs.pop("callbacks", None)
all_callbacks = get_dynamic_callbacks(dynamic_callbacks=dynamic_callbacks)
if len(all_callbacks) > 0:
@ -1209,9 +1209,9 @@ def client(original_function): # noqa: PLR0915
exception=e,
retry_policy=kwargs.get("retry_policy"),
)
kwargs["retry_policy"] = (
reset_retry_policy()
) # prevent infinite loops
kwargs[
"retry_policy"
] = reset_retry_policy() # prevent infinite loops
litellm.num_retries = (
None # set retries to None to prevent infinite loops
)
@ -2754,16 +2754,16 @@ def get_optional_params( # noqa: PLR0915
True # so that main.py adds the function call to the prompt
)
if "tools" in non_default_params:
optional_params["functions_unsupported_model"] = (
non_default_params.pop("tools")
)
optional_params[
"functions_unsupported_model"
] = non_default_params.pop("tools")
non_default_params.pop(
"tool_choice", None
) # causes ollama requests to hang
elif "functions" in non_default_params:
optional_params["functions_unsupported_model"] = (
non_default_params.pop("functions")
)
optional_params[
"functions_unsupported_model"
] = non_default_params.pop("functions")
elif (
litellm.add_function_to_prompt
): # if user opts to add it to prompt instead
@ -2786,10 +2786,10 @@ def get_optional_params( # noqa: PLR0915
if "response_format" in non_default_params:
if provider_config is not None:
non_default_params["response_format"] = (
provider_config.get_json_schema_from_pydantic_object(
response_format=non_default_params["response_format"]
)
non_default_params[
"response_format"
] = provider_config.get_json_schema_from_pydantic_object(
response_format=non_default_params["response_format"]
)
else:
non_default_params["response_format"] = type_to_response_format_param(
@ -3805,9 +3805,9 @@ def _count_characters(text: str) -> int:
def get_response_string(response_obj: Union[ModelResponse, ModelResponseStream]) -> str:
_choices: Union[List[Union[Choices, StreamingChoices]], List[StreamingChoices]] = (
response_obj.choices
)
_choices: Union[
List[Union[Choices, StreamingChoices]], List[StreamingChoices]
] = response_obj.choices
response_str = ""
for choice in _choices:
@ -4127,6 +4127,18 @@ def get_provider_info(
return model_info
def _is_potential_model_name_in_model_cost(
potential_model_names: PotentialModelNamesAndCustomLLMProvider,
) -> bool:
"""
Check if the potential model name is in the model cost.
"""
return any(
potential_model_name in litellm.model_cost
for potential_model_name in potential_model_names.values()
)
def _get_model_info_helper( # noqa: PLR0915
model: str, custom_llm_provider: Optional[str] = None
) -> ModelInfoBase:
@ -4182,7 +4194,9 @@ def _get_model_info_helper( # noqa: PLR0915
supports_prompt_caching=None,
supports_pdf_input=None,
)
elif custom_llm_provider == "ollama" or custom_llm_provider == "ollama_chat":
elif (
custom_llm_provider == "ollama" or custom_llm_provider == "ollama_chat"
) and not _is_potential_model_name_in_model_cost(potential_model_names):
return litellm.OllamaConfig().get_model_info(model)
else:
"""