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lijiaoqiao/llm-gateway-competitors/litellm-wheel-src/litellm/llms/lemonade/chat/transformation.py
2026-03-26 20:06:14 +08:00

148 lines
5.1 KiB
Python

"""
Translate from OpenAI's `/v1/chat/completions` to Lemonade's `/v1/chat/completions`
"""
from typing import Any, List, Optional, Tuple, Union
import httpx
import litellm
from litellm.litellm_core_utils.litellm_logging import Logging as LiteLLMLoggingObj
from litellm.secret_managers.main import get_secret_str
from litellm.types.llms.openai import (
AllMessageValues,
)
from litellm.types.utils import ModelResponse
from ...openai_like.chat.transformation import OpenAILikeChatConfig
class LemonadeChatConfig(OpenAILikeChatConfig):
repeat_penalty: Optional[float] = None
functions: Optional[list] = None
logit_bias: Optional[dict] = None
max_tokens: Optional[int] = None
max_completion_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
top_k: Optional[int] = None
response_format: Optional[dict] = None
tools: Optional[list] = None
def __init__(
self,
repeat_penalty: Optional[float] = None,
functions: Optional[list] = None,
logit_bias: Optional[dict] = None,
max_completion_tokens: Optional[int] = 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,
top_k: Optional[int] = None,
response_format: Optional[dict] = None,
tools: Optional[list] = None,
) -> None:
locals_ = locals().copy()
for key, value in locals_.items():
if key != "self" and value is not None:
setattr(self.__class__, key, value)
@property
def custom_llm_provider(self) -> Optional[str]:
return "lemonade"
@classmethod
def get_config(cls):
return super().get_config()
def get_models(self, api_key: Optional[str] = None, api_base: Optional[str] = None):
"""
Get available models from Lemonade API.
This method queries the Lemonade /models endpoint to retrieve the list of available models.
Args:
api_key: Optional API key (Lemonade doesn't require authentication)
api_base: Optional API base URL (defaults to LEMONADE_API_BASE env var or http://localhost:8000)
Returns:
List of model names prefixed with "lemonade/"
"""
api_base, api_key = self._get_openai_compatible_provider_info(
api_base=api_base, api_key=api_key
)
if api_base is None:
raise ValueError(
"LEMONADE_API_BASE is not set. Please set the environment variable to query Lemonade's /models endpoint."
)
# Getting the list of models from lemonade
try:
response = litellm.module_level_client.get(
url=f"{api_base}/models",
)
except Exception as e:
raise ValueError(
f"Failed to fetch models from Lemonade. Set Lemonade API Base via `LEMONADE_API_BASE` environment variable. Error: {e}"
)
if response.status_code != 200:
raise ValueError(
f"Failed to fetch models from Lemonade. Status code: {response.status_code}, Response: {response.text}"
)
model_list = response.json().get("data", [])
return ["lemonade/" + model["id"] for model in model_list]
def _get_openai_compatible_provider_info(
self, api_base: Optional[str], api_key: Optional[str]
) -> Tuple[Optional[str], Optional[str]]:
# lemonade is openai compatible, we just need to set this to custom_openai and have the api_base be lemonade's endpoint
api_base = (
api_base
or get_secret_str("LEMONADE_API_BASE")
or "http://localhost:8000/api/v1"
) # type: ignore
# Lemonade doesn't check the key
key = "lemonade"
return api_base, key
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,
litellm_params: dict,
encoding: Any,
api_key: Optional[str] = None,
json_mode: Optional[bool] = None,
) -> ModelResponse:
model_response = super().transform_response(
model=model,
model_response=model_response,
raw_response=raw_response,
messages=messages,
logging_obj=logging_obj,
request_data=request_data,
encoding=encoding,
optional_params=optional_params,
json_mode=json_mode,
litellm_params=litellm_params,
api_key=api_key,
)
# Storing lemonade in the model response for easier cost calculation later
setattr(model_response, "model", "lemonade/" + model)
return model_response