mirror of
https://github.com/BerriAI/litellm.git
synced 2025-04-25 18:54:30 +00:00
refactor(all-files): removing all print statements; adding pre-commit + flake8 to prevent future regressions
This commit is contained in:
Krrish Dholakia
parent
38ff9f2b6f
commit
6b40546e59
9 changed files with 39 additions and 50 deletions
|
|
@ -285,7 +285,8 @@ class TextCompletionResponse(OpenAIObject):
|
|||
############################################################
|
||||
def print_verbose(print_statement):
|
||||
if litellm.set_verbose:
|
||||
print(f"LiteLLM: {print_statement}")
|
||||
import logging
|
||||
logging.info(f"LiteLLM: {print_statement}")
|
||||
|
||||
####### LOGGING ###################
|
||||
from enum import Enum
|
||||
|
|
@ -538,8 +539,6 @@ class Logging:
|
|||
print_verbose("reaches api manager for updating model cost")
|
||||
litellm.apiManager.update_cost(completion_obj=result, user=self.user)
|
||||
if callback == "cache":
|
||||
# print("entering logger first time")
|
||||
# print(self.litellm_params["stream_response"])
|
||||
if litellm.cache != None and self.model_call_details.get('optional_params', {}).get('stream', False) == True:
|
||||
litellm_call_id = self.litellm_params["litellm_call_id"]
|
||||
if litellm_call_id in self.litellm_params["stream_response"]:
|
||||
|
|
@ -550,10 +549,7 @@ class Logging:
|
|||
self.litellm_params["stream_response"][litellm_call_id]["choices"][0]["message"]["content"] += result["content"]
|
||||
else: # init a streaming response for this call id
|
||||
new_model_response = ModelResponse(choices=[Choices(message=Message(content="default"))])
|
||||
#print("creating new model response")
|
||||
#print(new_model_response)
|
||||
self.litellm_params["stream_response"][litellm_call_id] = new_model_response
|
||||
#print("adding to cache for", litellm_call_id)
|
||||
litellm.cache.add_cache(self.litellm_params["stream_response"][litellm_call_id], **self.model_call_details)
|
||||
if callback == "promptlayer":
|
||||
print_verbose("reaches promptlayer for logging!")
|
||||
|
|
@ -576,7 +572,6 @@ class Logging:
|
|||
print_verbose("reaches supabase for streaming logging!")
|
||||
result = kwargs["complete_streaming_response"]
|
||||
|
||||
# print(kwargs)
|
||||
model = kwargs["model"]
|
||||
messages = kwargs["messages"]
|
||||
optional_params = kwargs.get("optional_params", {})
|
||||
|
|
@ -732,11 +727,11 @@ def exception_logging(
|
|||
model_call_details
|
||||
) # Expectation: any logger function passed in by the user should accept a dict object
|
||||
except Exception as e:
|
||||
print(
|
||||
print_verbose(
|
||||
f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {traceback.format_exc()}"
|
||||
)
|
||||
except Exception as e:
|
||||
print(
|
||||
print_verbose(
|
||||
f"LiteLLM.LoggingError: [Non-Blocking] Exception occurred while logging {traceback.format_exc()}"
|
||||
)
|
||||
pass
|
||||
|
|
@ -799,7 +794,6 @@ def client(original_function):
|
|||
return logging_obj
|
||||
except Exception as e: # DO NOT BLOCK running the function because of this
|
||||
print_verbose(f"[Non-Blocking] {traceback.format_exc()}; args - {args}; kwargs - {kwargs}")
|
||||
print(e)
|
||||
pass
|
||||
|
||||
def crash_reporting(*args, **kwargs):
|
||||
|
|
@ -1776,9 +1770,9 @@ def get_llm_provider(model: str, custom_llm_provider: Optional[str] = None, api_
|
|||
custom_llm_provider = "bedrock"
|
||||
|
||||
if custom_llm_provider is None or custom_llm_provider=="":
|
||||
print()
|
||||
print("\033[1;31mProvider List: https://docs.litellm.ai/docs/providers\033[0m")
|
||||
print()
|
||||
print() # noqa
|
||||
print("\033[1;31mProvider List: https://docs.litellm.ai/docs/providers\033[0m") # noqa
|
||||
print() # noqa
|
||||
raise ValueError(f"LLM Provider NOT provided. Pass in the LLM provider you are trying to call. E.g. For 'Huggingface' inference endpoints pass in `completion(model='huggingface/{model}',..)` Learn more: https://docs.litellm.ai/docs/providers")
|
||||
return model, custom_llm_provider, dynamic_api_key, api_base
|
||||
except Exception as e:
|
||||
|
|
@ -2772,7 +2766,7 @@ def get_all_keys(llm_provider=None):
|
|||
|
||||
|
||||
def get_model_list():
|
||||
global last_fetched_at
|
||||
global last_fetched_at, print_verbose
|
||||
try:
|
||||
# if user is using hosted product -> get their updated model list
|
||||
user_email = (
|
||||
|
|
@ -2784,7 +2778,7 @@ def get_model_list():
|
|||
if user_email:
|
||||
# make the api call
|
||||
last_fetched_at = time.time()
|
||||
print(f"last_fetched_at: {last_fetched_at}")
|
||||
print_verbose(f"last_fetched_at: {last_fetched_at}")
|
||||
response = requests.post(
|
||||
url="http://api.litellm.ai/get_model_list",
|
||||
headers={"content-type": "application/json"},
|
||||
|
|
@ -2820,10 +2814,10 @@ def exception_type(
|
|||
global user_logger_fn, liteDebuggerClient
|
||||
exception_mapping_worked = False
|
||||
if litellm.suppress_debug_info is False:
|
||||
print()
|
||||
print("\033[1;31mGive Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new\033[0m")
|
||||
print("LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True'.")
|
||||
print()
|
||||
print() # noqa
|
||||
print("\033[1;31mGive Feedback / Get Help: https://github.com/BerriAI/litellm/issues/new\033[0m") # noqa
|
||||
print("LiteLLM.Info: If you need to debug this error, use `litellm.set_verbose=True'.") # noqa
|
||||
print() # noqa
|
||||
try:
|
||||
if isinstance(original_exception, OriginalError):
|
||||
# Handle the OpenAIError
|
||||
|
|
@ -3401,7 +3395,7 @@ def exception_type(
|
|||
model=model
|
||||
)
|
||||
elif hasattr(original_exception, "status_code"):
|
||||
print(f"status code: {original_exception.status_code}")
|
||||
print_verbose(f"status code: {original_exception.status_code}")
|
||||
if original_exception.status_code == 401:
|
||||
exception_mapping_worked = True
|
||||
raise AuthenticationError(
|
||||
|
|
@ -4267,12 +4261,11 @@ def completion_with_fallbacks(**kwargs):
|
|||
return response
|
||||
|
||||
except Exception as e:
|
||||
print(e)
|
||||
print_verbose(e)
|
||||
rate_limited_models.add(model)
|
||||
model_expiration_times[model] = (
|
||||
time.time() + 60
|
||||
) # cool down this selected model
|
||||
# print(f"rate_limited_models {rate_limited_models}")
|
||||
pass
|
||||
return response
|
||||
|
||||
|
|
@ -4417,7 +4410,7 @@ def trim_messages(
|
|||
|
||||
return final_messages
|
||||
except Exception as e: # [NON-Blocking, if error occurs just return final_messages
|
||||
print("Got exception while token trimming", e)
|
||||
print_verbose("Got exception while token trimming", e)
|
||||
return messages
|
||||
|
||||
def get_valid_models():
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue