litellm-mirror/litellm/llms/base_llm/transformation.py
Krish Dholakia 4eeaaeeacd refactor(fireworks_ai/): inherit from openai like base config (#7146)
* refactor(fireworks_ai/): inherit from openai like base config

refactors fireworks ai to use a common config

* test: fix import in test

* refactor(watsonx/): refactor watsonx to use llm base config

refactors chat + completion routes to base config path

* fix: fix linting error

* test: fix test

* fix: fix test
2024-12-10 16:15:19 -08:00

154 lines
3.7 KiB
Python

"""
Common base config for all LLM providers
"""
import types
from abc import ABC, abstractmethod
from typing import (
TYPE_CHECKING,
Any,
AsyncIterator,
Callable,
Dict,
Iterator,
List,
Optional,
Union,
)
import httpx
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import ModelResponse
if TYPE_CHECKING:
from litellm.litellm_core_utils.litellm_logging import Logging as _LiteLLMLoggingObj
LiteLLMLoggingObj = _LiteLLMLoggingObj
else:
LiteLLMLoggingObj = Any
class BaseLLMException(Exception):
def __init__(
self,
status_code: int,
message: str,
headers: Optional[Union[Dict, httpx.Headers]] = None,
request: Optional[httpx.Request] = None,
response: Optional[httpx.Response] = None,
):
self.status_code = status_code
self.message: str = message
self.headers = headers
self.request = httpx.Request(method="POST", url="https://docs.litellm.ai/docs")
self.response = httpx.Response(status_code=status_code, request=self.request)
super().__init__(
self.message
) # Call the base class constructor with the parameters it needs
class BaseConfig(ABC):
def __init__(self):
pass
@classmethod
def get_config(cls):
return {
k: v
for k, v in cls.__dict__.items()
if not k.startswith("__")
and not k.startswith("_abc")
and not isinstance(
v,
(
types.FunctionType,
types.BuiltinFunctionType,
classmethod,
staticmethod,
),
)
and v is not None
}
@abstractmethod
def get_supported_openai_params(self, model: str) -> list:
pass
@abstractmethod
def map_openai_params(
self,
non_default_params: dict,
optional_params: dict,
model: str,
drop_params: bool,
) -> dict:
pass
@abstractmethod
def validate_environment(
self,
headers: dict,
model: str,
messages: List[AllMessageValues],
optional_params: dict,
api_key: Optional[str] = None,
) -> dict:
pass
def get_complete_url(self, api_base: str, model: str) -> str:
"""
OPTIONAL
Get the complete url for the request
Some providers need `model` in `api_base`
"""
return api_base
@abstractmethod
def transform_request(
self,
model: str,
messages: List[AllMessageValues],
optional_params: dict,
litellm_params: dict,
headers: dict,
) -> dict:
pass
@abstractmethod
def _transform_messages(
self, messages: List[AllMessageValues]
) -> List[AllMessageValues]:
pass
@abstractmethod
def transform_response(
self,
model: str,
raw_response: httpx.Response,
model_response: ModelResponse,
logging_obj: LiteLLMLoggingObj,
request_data: dict,
messages: List[AllMessageValues],
optional_params: dict,
encoding: str,
api_key: Optional[str] = None,
json_mode: Optional[bool] = None,
) -> ModelResponse:
pass
@abstractmethod
def get_error_class(
self, error_message: str, status_code: int, headers: Union[dict, httpx.Headers]
) -> BaseLLMException:
pass
def get_model_response_iterator(
self,
streaming_response: Union[Iterator[str], AsyncIterator[str], ModelResponse],
sync_stream: bool,
json_mode: Optional[bool] = False,
) -> Any:
pass