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(feat) completion: add response_format, seed, tools, tool_choice

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ishaan-jaff 2023-11-17 13:59:57 -08:00
parent 3c03e82f98
commit 7abb65d53f
2 changed files with 19 additions and 2 deletions
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11
litellm/main.py
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@ -255,6 +255,11 @@ def completion(
frequency_penalty: Optional[float]=None, frequency_penalty: Optional[float]=None,
logit_bias: dict = {}, logit_bias: dict = {},
user: str = "", user: str = "",
# openai v1.0+ new params
response_format: Optional[dict] = None,
seed: Optional[int] = None,
tools: Optional[List] = None,
tool_choice: Optional[str] = None,
deployment_id = None, deployment_id = None,
# set api_base, api_version, api_key # set api_base, api_version, api_key
@ -329,7 +334,7 @@ def completion(
eos_token = kwargs.get("eos_token", None) eos_token = kwargs.get("eos_token", None)
acompletion = kwargs.get("acompletion", False) acompletion = kwargs.get("acompletion", False)
######## 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"] 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"]
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", "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", "max_retries"]
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
@ -400,6 +405,10 @@ def completion(
# params to identify the model # params to identify the model
model=model, model=model,
custom_llm_provider=custom_llm_provider, custom_llm_provider=custom_llm_provider,
response_format=response_format,
seed=seed,
tools=tools,
tool_choice=tool_choice,
**non_default_params **non_default_params
) )

10
litellm/utils.py
View file

@ -1751,6 +1751,10 @@ def get_optional_params( # use the openai defaults
user="", user="",
model=None, model=None,
custom_llm_provider="", custom_llm_provider="",
response_format=None,
seed=None,
tools=None,
tool_choice=None,
**kwargs **kwargs
): ):
# retrieve all parameters passed to the function # retrieve all parameters passed to the function
@ -1773,6 +1777,10 @@ def get_optional_params( # use the openai defaults
"user":"", "user":"",
"model":None, "model":None,
"custom_llm_provider":"", "custom_llm_provider":"",
"response_format": None,
"seed": None,
"tools": None,
"tool_choice": None
} }
# filter out those parameters that were passed with non-default values # filter out those parameters that were passed with non-default values
non_default_params = {k: v for k, v in passed_params.items() if (k != "model" and k != "custom_llm_provider" and k in default_params and v != default_params[k])} non_default_params = {k: v for k, v in passed_params.items() if (k != "model" and k != "custom_llm_provider" and k in default_params and v != default_params[k])}
@ -2166,7 +2174,7 @@ def get_optional_params( # use the openai defaults
temperature = 0.0001 # close to 0 temperature = 0.0001 # close to 0
optional_params["temperature"] = temperature optional_params["temperature"] = temperature
else: # assume passing in params for openai/azure openai else: # assume passing in params for openai/azure openai
supported_params = ["functions", "function_call", "temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user"] supported_params = ["functions", "function_call", "temperature", "top_p", "n", "stream", "stop", "max_tokens", "presence_penalty", "frequency_penalty", "logit_bias", "user", "response_format", "seed", "tools", "tool_choice"]
_check_valid_arg(supported_params=supported_params) _check_valid_arg(supported_params=supported_params)
optional_params = non_default_params optional_params = non_default_params
# if user passed in non-default kwargs for specific providers/models, pass them along # if user passed in non-default kwargs for specific providers/models, pass them along