### What this tests #### import sys import os sys.path.insert(0, os.path.abspath('../..')) from litellm import completion, embedding import litellm def custom_callback( kwargs, completion_response, start_time, end_time, ): print( "in custom callback func" ) print("kwargs", kwargs) print(completion_response) print(start_time) print(end_time) def send_slack_alert( kwargs, completion_response, start_time, end_time, ): print( "in custom slack callback func" ) import requests import json # Define the Slack webhook URL slack_webhook_url = os.environ['SLACK_WEBHOOK_URL'] # "https://hooks.slack.com/services/<>/<>/<>" # Define the text payload, send data available in litellm custom_callbacks text_payload = f"""LiteLLM Logging: kwargs: {str(kwargs)}\n\n, response: {str(completion_response)}\n\n, start time{str(start_time)} end time: {str(end_time)} """ payload = { "text": text_payload } # Set the headers headers = { "Content-type": "application/json" } # Make the POST request response = requests.post(slack_webhook_url, json=payload, headers=headers) # Check the response status if response.status_code == 200: print("Message sent successfully to Slack!") else: print(f"Failed to send message to Slack. Status code: {response.status_code}") print(response.json()) def get_transformed_inputs( kwargs, ): params_to_model = kwargs["additional_args"]["complete_input_dict"] print("params to model", params_to_model) litellm.success_callback = [custom_callback, send_slack_alert] litellm.failure_callback = [send_slack_alert] litellm.set_verbose = True litellm.input_callback = [get_transformed_inputs] def test_chat_openai(): try: response = completion(model="gpt-2", messages=[{ "role": "user", "content": "Hi 👋 - i'm openai" }]) print(response) except Exception as e: print(e) pass test_chat_openai()