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fix(main.py): passing client as a litellm-specific kwarg

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Krrish Dholakia 2023-11-28 21:20:05 -08:00
parent 9a7d1cf75a
commit ceadb1547d
2 changed files with 4 additions and 4 deletions
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7
litellm/main.py
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@ -338,9 +338,10 @@ def completion(
bos_token = kwargs.get("bos_token", None) bos_token = kwargs.get("bos_token", None)
eos_token = kwargs.get("eos_token", None) eos_token = kwargs.get("eos_token", None)
acompletion = kwargs.get("acompletion", False) acompletion = kwargs.get("acompletion", False)
client = kwargs.get("client", None)
######## end of unpacking kwargs ########### ######## 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", "api_base", "api_version", "api_key", "deployment_id", "organization", "base_url", "default_headers", "timeout", "response_format", "seed", "tools", "tool_choice", "max_retries"] 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", "deployment_id", "organization", "base_url", "default_headers", "timeout", "response_format", "seed", "tools", "tool_choice", "max_retries"]
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", "fallbacks", "azure", "headers", "model_list", "num_retries", "context_window_fallback_dict", "roles", "final_prompt_value", "bos_token", "eos_token", "request_timeout", "complete_response", "self"] 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", "fallbacks", "azure", "headers", "model_list", "num_retries", "context_window_fallback_dict", "roles", "final_prompt_value", "bos_token", "eos_token", "request_timeout", "complete_response", "self", "client"]
default_params = openai_params + litellm_params 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 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
if mock_response: if mock_response:
@ -498,7 +499,7 @@ def completion(
logging_obj=logging, logging_obj=logging,
acompletion=acompletion, acompletion=acompletion,
timeout=timeout, timeout=timeout,
client=optional_params.pop("client", None) # pass AsyncAzureOpenAI, AzureOpenAI client client=client # pass AsyncAzureOpenAI, AzureOpenAI client
) )
## LOGGING ## LOGGING
@ -569,7 +570,7 @@ def completion(
logger_fn=logger_fn, logger_fn=logger_fn,
timeout=timeout, timeout=timeout,
custom_prompt_dict=custom_prompt_dict, custom_prompt_dict=custom_prompt_dict,
client=optional_params.pop("client", None) # pass AsyncOpenAI, OpenAI client client=client # pass AsyncOpenAI, OpenAI client
) )
except Exception as e: except Exception as e:
## LOGGING - log the original exception returned ## LOGGING - log the original exception returned

1
litellm/router.py
View file

@ -602,7 +602,6 @@ class Router:
self.print_verbose(self.model_exception_map) self.print_verbose(self.model_exception_map)
for model in self.model_exception_map: for model in self.model_exception_map:
self.print_verbose(f"Model {model} had {len(self.model_exception_map[model])} exception") self.print_verbose(f"Model {model} had {len(self.model_exception_map[model])} exception")
self.print_verbose()
if custom_llm_provider: if custom_llm_provider:
model_name = f"{custom_llm_provider}/{model_name}" model_name = f"{custom_llm_provider}/{model_name}"