litellm-mirror/litellm/llms/fireworks_ai.py
2024-06-26 06:29:21 -07:00

107 lines
3.4 KiB
Python

import types
from typing import Literal, Optional, Union
import litellm
class FireworksAIConfig:
"""
Reference: https://docs.fireworks.ai/api-reference/post-chatcompletions
The class `FireworksAIConfig` provides configuration for the Fireworks's Chat Completions API interface. Below are the parameters:
"""
tools: Optional[list] = None
tool_choice: Optional[Union[str, dict]] = None
max_tokens: Optional[int] = None
temperature: Optional[int] = None
top_p: Optional[int] = None
top_k: Optional[int] = None
frequency_penalty: Optional[int] = None
presence_penalty: Optional[int] = None
n: Optional[int] = None
stop: Optional[Union[str, list]] = None
response_format: Optional[dict] = None
user: Optional[str] = None
# Non OpenAI parameters - Fireworks AI only params
prompt_truncate_length: Optional[int] = None
context_length_exceeded_behavior: Optional[Literal["error", "truncate"]] = None
def __init__(
self,
tools: Optional[list] = None,
tool_choice: Optional[Union[str, dict]] = None,
max_tokens: Optional[int] = None,
temperature: Optional[int] = None,
top_p: Optional[int] = None,
top_k: Optional[int] = None,
frequency_penalty: Optional[int] = None,
presence_penalty: Optional[int] = None,
n: Optional[int] = None,
stop: Optional[Union[str, list]] = None,
response_format: Optional[dict] = None,
user: Optional[str] = None,
prompt_truncate_length: Optional[int] = None,
context_length_exceeded_behavior: Optional[Literal["error", "truncate"]] = 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 [
"stream",
"tools",
"tool_choice",
"max_tokens",
"temperature",
"top_p",
"top_k",
"frequency_penalty",
"presence_penalty",
"n",
"stop",
"response_format",
"user",
"prompt_truncate_length",
"context_length_exceeded_behavior",
]
def map_openai_params(
self,
non_default_params: dict,
optional_params: dict,
model: str,
drop_params: bool,
) -> dict:
supported_openai_params = self.get_supported_openai_params()
for param, value in non_default_params.items():
if param == "tool_choice":
if value == "required":
# relevant issue: https://github.com/BerriAI/litellm/issues/4416
optional_params["tools"] = "any"
if param in supported_openai_params:
if value is not None:
optional_params[param] = value
return optional_params