mirror of
https://github.com/BerriAI/litellm.git
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87 lines
2.6 KiB
Python
87 lines
2.6 KiB
Python
import types
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from typing import Literal, Optional, Union
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import litellm
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class VolcEngineConfig:
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frequency_penalty: Optional[int] = None
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function_call: Optional[Union[str, dict]] = None
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functions: Optional[list] = None
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logit_bias: Optional[dict] = None
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max_tokens: Optional[int] = None
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n: Optional[int] = None
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presence_penalty: Optional[int] = None
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stop: Optional[Union[str, list]] = None
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temperature: Optional[int] = None
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top_p: Optional[int] = None
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response_format: Optional[dict] = None
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def __init__(
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self,
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frequency_penalty: Optional[int] = None,
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function_call: Optional[Union[str, dict]] = None,
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functions: Optional[list] = None,
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logit_bias: Optional[dict] = None,
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max_tokens: Optional[int] = None,
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n: Optional[int] = None,
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presence_penalty: Optional[int] = None,
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stop: Optional[Union[str, list]] = None,
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temperature: Optional[int] = None,
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top_p: Optional[int] = None,
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response_format: Optional[dict] = None,
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) -> None:
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locals_ = locals().copy()
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for key, value in locals_.items():
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if key != "self" and value is not None:
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setattr(self.__class__, key, value)
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@classmethod
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def get_config(cls):
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return {
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k: v
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for k, v in cls.__dict__.items()
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if not k.startswith("__")
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and not isinstance(
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v,
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(
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types.FunctionType,
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types.BuiltinFunctionType,
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classmethod,
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staticmethod,
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),
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)
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and v is not None
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}
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def get_supported_openai_params(self, model: str) -> list:
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return [
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"frequency_penalty",
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"logit_bias",
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"logprobs",
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"top_logprobs",
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"max_tokens",
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"n",
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"presence_penalty",
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"seed",
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"stop",
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"stream",
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"stream_options",
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"temperature",
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"top_p",
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"tools",
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"tool_choice",
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"function_call",
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"functions",
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"max_retries",
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"extra_headers",
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] # works across all models
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def map_openai_params(
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self, non_default_params: dict, optional_params: dict, model: str
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) -> dict:
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supported_openai_params = self.get_supported_openai_params(model)
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for param, value in non_default_params.items():
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if param in supported_openai_params:
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optional_params[param] = value
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return optional_params
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