(feat) fix api callback imports

enterprise/callbacks/generic_api_callback.py

@@ -57,7 +57,9 @@ class GenericAPILogger:
 
     # This is sync, because we run this in a separate thread. Running in a sepearate thread ensures it will never block an LLM API call
     # Experience with s3, Langfuse shows that async logging events are complicated and can block LLM calls
-    def log_event(self, kwargs, response_obj, start_time, end_time, print_verbose):
+    def log_event(
+        self, kwargs, response_obj, start_time, end_time, user_id, print_verbose
+    ):
         try:
             verbose_logger.debug(
                 f"GenericAPILogger Logging - Enters logging function for model {kwargs}"

litellm/tests/test_custom_api_logger.py

@@ -0,0 +1,45 @@
+import sys
+import os
+import io, asyncio
+
+# import logging
+# logging.basicConfig(level=logging.DEBUG)
+sys.path.insert(0, os.path.abspath("../.."))
+print("Modified sys.path:", sys.path)
+
+
+from litellm import completion
+import litellm
+
+litellm.num_retries = 3
+
+import time, random
+import pytest
+
+
+@pytest.mark.asyncio
+async def test_custom_api_logging():
+    try:
+        litellm.success_callback = ["generic"]
+        litellm.set_verbose = True
+        os.environ["GENERIC_LOGGER_ENDPOINT"] = "http://localhost:8000/log-event"
+
+        print("Testing generic api logging")
+
+        await litellm.acompletion(
+            model="gpt-3.5-turbo",
+            messages=[{"role": "user", "content": f"This is a test"}],
+            max_tokens=10,
+            temperature=0.7,
+            user="ishaan-2",
+        )
+
+    except Exception as e:
+        pytest.fail(f"An exception occurred - {e}")
+    finally:
+        # post, close log file and verify
+        # Reset stdout to the original value
+        print("Passed! Testing async s3 logging")
+
+
+# test_s3_logging()

litellm/utils.py

@@ -12,6 +12,7 @@ import litellm
 import dotenv, json, traceback, threading, base64, ast
 
 import subprocess, os
+from os.path import abspath, join, dirname
 import litellm, openai
 import itertools
 import random, uuid, requests
@@ -33,11 +34,11 @@ from dataclasses import (
 # import pkg_resources
 from importlib import resources
 
-# filename = pkg_resources.resource_filename(__name__, "llms/tokenizers")
-filename = str(resources.files("llms").joinpath("tokenizers"))
-os.environ[
-    "TIKTOKEN_CACHE_DIR"
-] = filename  # use local copy of tiktoken b/c of - https://github.com/BerriAI/litellm/issues/1071
+# # filename = pkg_resources.resource_filename(__name__, "llms/tokenizers")
+# filename = str(resources.files().joinpath("llms/tokenizers"))
+# os.environ[
+#     "TIKTOKEN_CACHE_DIR"
+# ] = filename  # use local copy of tiktoken b/c of - https://github.com/BerriAI/litellm/issues/1071
 encoding = tiktoken.get_encoding("cl100k_base")
 import importlib.metadata
 from ._logging import verbose_logger
@@ -76,8 +77,13 @@ from .exceptions import (
     UnprocessableEntityError,
 )
 
-# import enterprise features
-from ..enterprise.callbacks.api_callback import GenericAPILogger
+# Import Enterprise features
+project_path = abspath(join(dirname(__file__), "..", ".."))
+# Add the "enterprise" directory to sys.path
+enterprise_path = abspath(join(project_path, "enterprise"))
+sys.path.append(enterprise_path)
+from enterprise.callbacks.generic_api_callback import GenericAPILogger
+
 
 from typing import cast, List, Dict, Union, Optional, Literal, Any
 from .caching import Cache