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fix(utils.py): return function call as part of response object

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Krrish Dholakia 2023-11-10 11:02:10 -08:00
parent a4c9e6bd46
commit 18a8bd5543
5 changed files with 52 additions and 87 deletions
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51
litellm/utils.py
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@ -118,11 +118,13 @@ def map_finish_reason(finish_reason: str): # openai supports 5 stop sequences -
return finish_reason
class Message(OpenAIObject):
def __init__(self, content="default", role="assistant", logprobs=None, **params):
def __init__(self, content="default", role="assistant", logprobs=None, function_call=None, **params):
super(Message, self).__init__(**params)
self.content = content
self.role = role
self._logprobs = logprobs
if function_call:
self.function_call = function_call
class Delta(OpenAIObject):
def __init__(self, content=None, logprobs=None, role=None, **params):
@ -907,29 +909,6 @@ def client(original_function):
# [Non-Blocking Error]
pass
def convert_to_model_response_object(response_object: Optional[dict]=None, model_response_object: Optional[ModelResponse]=None):
try:
if response_object is None or model_response_object is None:
raise OpenAIError(status_code=500, message="Error in response object format")
choice_list=[]
for idx, choice in enumerate(response_object["choices"]):
message = Message(content=choice["message"]["content"], role=choice["message"]["role"])
choice = Choices(finish_reason=choice["finish_reason"], index=idx, message=message)
choice_list.append(choice)
model_response_object.choices = choice_list
if "usage" in response_object:
model_response_object.usage = response_object["usage"]
if "id" in response_object:
model_response_object.id = response_object["id"]
if "model" in response_object:
model_response_object.model = response_object["model"]
return model_response_object
except:
OpenAIError(status_code=500, message="Invalid response object.")
def wrapper(*args, **kwargs):
start_time = datetime.datetime.now()
result = None
@ -2581,6 +2560,30 @@ def handle_failure(exception, traceback_exception, start_time, end_time, args, k
pass
def convert_to_model_response_object(response_object: Optional[dict]=None, model_response_object: Optional[ModelResponse]=None):
try:
if response_object is None or model_response_object is None:
raise OpenAIError(status_code=500, message="Error in response object format")
choice_list=[]
for idx, choice in enumerate(response_object["choices"]):
message = Message(content=choice["message"]["content"], role=choice["message"]["role"], function_call=choice["message"].get("function_call", None))
choice = Choices(finish_reason=choice["finish_reason"], index=idx, message=message)
choice_list.append(choice)
model_response_object.choices = choice_list
if "usage" in response_object:
model_response_object.usage = response_object["usage"]
if "id" in response_object:
model_response_object.id = response_object["id"]
if "model" in response_object:
model_response_object.model = response_object["model"]
return model_response_object
except:
OpenAIError(status_code=500, message="Invalid response object.")
# NOTE: DEPRECATING this in favor of using success_handler() in Logging:
def handle_success(args, kwargs, result, start_time, end_time):
global heliconeLogger, aispendLogger, supabaseClient, liteDebuggerClient, llmonitorLogger