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(feat) add api_key, api_base, api_version to completion

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ishaan-jaff 2023-10-09 08:11:49 -07:00
parent 14b6261f47
commit f6f7c0b891
1 changed files with 10 additions and 1 deletions
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11
litellm/main.py
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@ -170,6 +170,12 @@ def completion(
user: str = "",
deployment_id = None,
request_timeout: Optional[int] = None,
# set api_base, api_version, api_key
api_base: Optional[str] = None,
api_version: Optional[str] = None,
api_key: Optional[str] = None,
# Optional liteLLM function params
**kwargs,
) -> ModelResponse:
@ -193,6 +199,9 @@ def completion(
logit_bias (dict, optional): Used to modify the probability of specific tokens appearing in the completion.
user (str, optional): A unique identifier representing your end-user. This can help the LLM provider to monitor and detect abuse.
metadata (dict, optional): Pass in additional metadata to tag your completion calls - eg. prompt version, details, etc.
api_base (str, optional): Base URL for the API (default is None).
api_version (str, optional): API version (default is None).
api_key (str, optional): API key (default is None).
LITELLM Specific Params
mock_response (str, optional): If provided, return a mock completion response for testing or debugging purposes (default is None).
@ -222,7 +231,7 @@ def completion(
metadata = kwargs.get('metadata', None)
fallbacks = kwargs.get('fallbacks', [])
######## end of unpacking kwargs ###########
openai_params = ["functions", "function_call", "temperature", "temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user", "request_timeout"]
openai_params = ["functions", "function_call", "temperature", "temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user", "request_timeout", "api_base", "api_version", "api_key"]
litellm_params = ["metadata", "acompletion", "caching", "return_async", "mock_response", "api_key", "api_version", "api_base", "force_timeout", "logger_fn", "verbose", "custom_llm_provider", "litellm_logging_obj", "litellm_call_id", "use_client", "id", "metadata", "fallbacks", "azure"]
default_params = openai_params + litellm_params
non_default_params = {k: v for k,v in kwargs.items() if k not in default_params} # model-specific params - pass them straight to the model/provider