from litellm.integrations.custom_logger import CustomLogger import litellm import inspect # This file includes the custom callbacks for LiteLLM Proxy # Once defined, these can be passed in proxy_config.yaml class MyCustomHandler(CustomLogger): def __init__(self): blue_color_code = "\033[94m" reset_color_code = "\033[0m" print(f"{blue_color_code}Initialized LiteLLM custom logger") try: print(f"Logger Initialized with following methods:") methods = [method for method in dir(self) if inspect.ismethod(getattr(self, method))] # Pretty print the methods for method in methods: print(f" - {method}") print(f"{reset_color_code}") except: pass def log_pre_api_call(self, model, messages, kwargs): print(f"Pre-API Call") def log_post_api_call(self, kwargs, response_obj, start_time, end_time): print(f"Post-API Call") def log_stream_event(self, kwargs, response_obj, start_time, end_time): print(f"On Stream") def log_success_event(self, kwargs, response_obj, start_time, end_time): # log: key, user, model, prompt, response, tokens, cost print("\nOn Success") ### Access kwargs passed to litellm.completion() model = kwargs.get("model", None) messages = kwargs.get("messages", None) user = kwargs.get("user", None) #### Access litellm_params passed to litellm.completion(), example access `metadata` litellm_params = kwargs.get("litellm_params", {}) metadata = litellm_params.get("metadata", {}) # headers passed to LiteLLM proxy, can be found here ################################################# ##### Calculate cost using litellm.completion_cost() ####################### cost = litellm.completion_cost(completion_response=response_obj) response = response_obj # tokens used in response usage = response_obj["usage"] print( f""" Model: {model}, Messages: {messages}, User: {user}, Usage: {usage}, Cost: {cost}, Response: {response} Proxy Metadata: {metadata} """ ) return async def async_log_failure_event(self, kwargs, response_obj, start_time, end_time): try: print(f"On Async Failure !") print("\nkwargs", kwargs) # Access kwargs passed to litellm.completion() model = kwargs.get("model", None) messages = kwargs.get("messages", None) user = kwargs.get("user", None) # Access litellm_params passed to litellm.completion(), example access `metadata` litellm_params = kwargs.get("litellm_params", {}) metadata = litellm_params.get("metadata", {}) # headers passed to LiteLLM proxy, can be found here # Acess Exceptions & Traceback exception_event = kwargs.get("exception", None) traceback_event = kwargs.get("traceback_exception", None) # Calculate cost using litellm.completion_cost() cost = litellm.completion_cost(completion_response=response_obj) print("now checking response obj") print( f""" Model: {model}, Messages: {messages}, User: {user}, Cost: {cost}, Response: {response_obj} Proxy Metadata: {metadata} Exception: {exception_event} Traceback: {traceback_event} """ ) except Exception as e: print(f"Exception: {e}") async def async_log_success_event(self, kwargs, response_obj, start_time, end_time): print(f"On Async Success!") # log: key, user, model, prompt, response, tokens, cost print("\nOn Success") # Access kwargs passed to litellm.completion() model = kwargs.get("model", None) messages = kwargs.get("messages", None) user = kwargs.get("user", None) # Access litellm_params passed to litellm.completion(), example access `metadata` litellm_params = kwargs.get("litellm_params", {}) metadata = litellm_params.get("metadata", {}) # headers passed to LiteLLM proxy, can be found here # Calculate cost using litellm.completion_cost() cost = litellm.completion_cost(completion_response=response_obj) response = response_obj # tokens used in response usage = response_obj["usage"] print( f""" Model: {model}, Messages: {messages}, User: {user}, Usage: {usage}, Cost: {cost}, Response: {response} Proxy Metadata: {metadata} """ ) return proxy_handler_instance = MyCustomHandler() # need to set litellm.callbacks = [customHandler] # on the proxy # litellm.success_callback = [async_on_succes_logger]