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fix(utils.py): support deepinfra optional params

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Fixes https://github.com/BerriAI/litellm/issues/3855
This commit is contained in:
Krrish Dholakia 2024-05-27 09:16:39 -07:00
parent a6a84e57ce
commit f0f853b941
3 changed files with 109 additions and 38 deletions
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97
litellm/llms/openai.py
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@ -157,6 +157,101 @@ class MistralConfig:
)
if param == "seed":
optional_params["extra_body"] = {"random_seed": value}
if param == "response_format":
optional_params["response_format"] = value
return optional_params
class DeepInfraConfig:
"""
Reference: https://deepinfra.com/docs/advanced/openai_api
The class `DeepInfra` provides configuration for the DeepInfra's Chat Completions API interface. Below are the parameters:
"""
frequency_penalty: Optional[int] = None
function_call: Optional[Union[str, dict]] = None
functions: Optional[list] = None
logit_bias: Optional[dict] = None
max_tokens: Optional[int] = None
n: Optional[int] = None
presence_penalty: Optional[int] = None
stop: Optional[Union[str, list]] = None
temperature: Optional[int] = None
top_p: Optional[int] = None
response_format: Optional[dict] = None
tools: Optional[list] = None
tool_choice: Optional[Union[str, dict]] = None
def __init__(
self,
frequency_penalty: Optional[int] = None,
function_call: Optional[Union[str, dict]] = None,
functions: Optional[list] = None,
logit_bias: Optional[dict] = None,
max_tokens: Optional[int] = None,
n: Optional[int] = None,
presence_penalty: Optional[int] = None,
stop: Optional[Union[str, list]] = None,
temperature: Optional[int] = None,
top_p: Optional[int] = None,
response_format: Optional[dict] = None,
tools: Optional[list] = None,
tool_choice: Optional[Union[str, dict]] = None,
) -> None:
locals_ = locals().copy()
for key, value in locals_.items():
if key != "self" and value is not None:
setattr(self.__class__, key, value)
@classmethod
def get_config(cls):
return {
k: v
for k, v in cls.__dict__.items()
if not k.startswith("__")
and not isinstance(
v,
(
types.FunctionType,
types.BuiltinFunctionType,
classmethod,
staticmethod,
),
)
and v is not None
}
def get_supported_openai_params(self):
return [
"frequency_penalty",
"function_call",
"functions",
"logit_bias",
"max_tokens",
"n",
"presence_penalty",
"stop",
"temperature",
"top_p",
"response_format",
"tools",
"tool_choice",
]
def map_openai_params(
self, non_default_params: dict, optional_params: dict, model: str
):
supported_openai_params = self.get_supported_openai_params()
for param, value in non_default_params.items():
if (
param == "temperature"
and value == 0
and model == "mistralai/Mistral-7B-Instruct-v0.1"
): # this model does no support temperature == 0
value = 0.0001 # close to 0
if param in supported_openai_params:
optional_params[param] = value
return optional_params
@ -197,6 +292,7 @@ class OpenAIConfig:
stop: Optional[Union[str, list]] = None
temperature: Optional[int] = None
top_p: Optional[int] = None
response_format: Optional[dict] = None
def __init__(
self,
@ -210,6 +306,7 @@ class OpenAIConfig:
stop: Optional[Union[str, list]] = None,
temperature: Optional[int] = None,
top_p: Optional[int] = None,
response_format: Optional[dict] = None,
) -> None:
locals_ = locals().copy()
for key, value in locals_.items():