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refactor(openai.py): moving openai chat completion calls to http

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This commit is contained in:
Krrish Dholakia 2023-11-08 17:40:32 -08:00
parent da1451e493
commit c57ed0a9d7
6 changed files with 158 additions and 127 deletions
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46
litellm/main.py
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@ -198,7 +198,6 @@ def completion(
logit_bias: dict = {},
user: str = "",
deployment_id = None,
request_timeout: Optional[int] = None,
# set api_base, api_version, api_key
api_base: Optional[str] = None,
@ -270,7 +269,7 @@ def completion(
eos_token = kwargs.get("eos_token", None)
######## 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"]
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"]
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"]
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
if mock_response:
@ -334,7 +333,6 @@ def completion(
frequency_penalty=frequency_penalty,
logit_bias=logit_bias,
user=user,
request_timeout=request_timeout,
deployment_id=deployment_id,
# params to identify the model
model=model,
@ -464,38 +462,20 @@ def completion(
if k not in optional_params: # completion(top_k=3) > openai_config(top_k=3) <- allows for dynamic variables to be passed in
optional_params[k] = v
## LOGGING
logging.pre_call(
input=messages,
api_key=api_key,
additional_args={"headers": headers, "api_base": api_base},
)
## COMPLETION CALL
try:
if custom_llm_provider == "custom_openai":
response = openai_chat_completions.completion(
model=model,
messages=messages,
model_response=model_response,
print_verbose=print_verbose,
api_key=api_key,
api_base=api_base,
logging_obj=logging,
optional_params=optional_params,
litellm_params=litellm_params,
logger_fn=logger_fn
)
else:
response = openai.ChatCompletion.create(
model=model,
messages=messages,
headers=headers, # None by default
api_base=api_base, # thread safe setting base, key, api_version
api_key=api_key,
api_type="openai",
api_version=api_version, # default None
**optional_params,
)
response = openai_chat_completions.completion(
model=model,
messages=messages,
model_response=model_response,
print_verbose=print_verbose,
api_key=api_key,
api_base=api_base,
logging_obj=logging,
optional_params=optional_params,
litellm_params=litellm_params,
logger_fn=logger_fn
)
except Exception as e:
## LOGGING - log the original exception returned
logging.post_call(