Local Debugging
There's 2 ways to do local debugging - litellm.set_verbose=True
and by passing in a custom function completion(...logger_fn=<your_local_function>)
Set Verbose
This is good for getting print statements for everything litellm is doing.
from litellm import completion
litellm.set_verbose=True # 👈 this is the 1-line change you need to make
## set ENV variables
os.environ["OPENAI_API_KEY"] = "openai key"
os.environ["COHERE_API_KEY"] = "cohere key"
messages = [{ "content": "Hello, how are you?","role": "user"}]
# openai call
response = completion(model="gpt-3.5-turbo", messages=messages)
# cohere call
response = completion("command-nightly", messages)
Logger Function
But sometimes all you care about is seeing exactly what's getting sent to your api call and what's being returned - e.g. if the api call is failing, why is that happening? what are the exact params being set?
In that case, LiteLLM allows you to pass in a custom logging function to see / modify the model call Input/Outputs.
Note: We expect you to accept a dict object.
Your custom function
def my_custom_logging_fn(model_call_dict):
print(f"model call details: {model_call_dict}")
Complete Example
from litellm import completion
def my_custom_logging_fn(model_call_dict):
print(f"model call details: {model_call_dict}")
## set ENV variables
os.environ["OPENAI_API_KEY"] = "openai key"
os.environ["COHERE_API_KEY"] = "cohere key"
messages = [{ "content": "Hello, how are you?","role": "user"}]
# openai call
response = completion(model="gpt-3.5-turbo", messages=messages, logger_fn=my_custom_logging_fn)
# cohere call
response = completion("command-nightly", messages, logger_fn=my_custom_logging_fn)
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