update version

litellm/main.py

@@ -44,10 +44,11 @@ def completion(
     presence_penalty=0, frequency_penalty=0, logit_bias={}, user="", deployment_id=None,
     # Optional liteLLM function params
     *, return_async=False, api_key=None, force_timeout=60, azure=False, logger_fn=None, verbose=False,
-    hugging_face = False, replicate=False,together_ai = False, llm_provider=None, custom_api_base=None
+    hugging_face = False, replicate=False,together_ai = False, custom_llm_provider=None, custom_api_base=None
   ):
   try:
     global new_response
+    args = locals()
     model_response = deepcopy(new_response) # deep copy the default response format so we can mutate it and it's thread-safe. 
     # check if user passed in any of the OpenAI optional params
     optional_params = get_optional_params(
@@ -85,7 +86,7 @@ def completion(
           messages = messages,
           **optional_params
         )
-    elif model in litellm.open_ai_chat_completion_models or llm_provider == "custom": # allow user to make an openai call with a custom base
+    elif model in litellm.open_ai_chat_completion_models or custom_llm_provider == "custom_openai": # allow user to make an openai call with a custom base
       openai.api_type = "openai"
       # note: if a user sets a custom base - we should ensure this works
       api_base = custom_api_base if custom_api_base is not None else litellm.api_base # allow for the setting of dynamic and stateful api-bases
@@ -100,9 +101,7 @@ def completion(
       else:
           openai.api_key = get_secret("OPENAI_API_KEY")
       ## LOGGING
-      logging(model=model, input=messages, additional_args=optional_params, azure=azure, logger_fn=logger_fn)
-      if custom_api_base: # reset after call, if a dynamic api base was passsed
-        openai.api_base = "https://api.openai.com/v1"
+      logging(model=model, input=messages, additional_args=args, azure=azure, logger_fn=logger_fn)
       ## COMPLETION CALL
       if litellm.headers:
          response = openai.ChatCompletion.create(
@@ -117,6 +116,8 @@ def completion(
           messages = messages,
           **optional_params
         )
+      if custom_api_base: # reset after call, if a dynamic api base was passsed
+        openai.api_base = "https://api.openai.com/v1"
     elif model in litellm.open_ai_text_completion_models:
       openai.api_type = "openai"
       openai.api_base = litellm.api_base if litellm.api_base is not None else "https://api.openai.com/v1"

litellm/tests/test_custom_api_base.py

@@ -0,0 +1,20 @@
+import sys, os
+import traceback
+from dotenv import load_dotenv
+load_dotenv()
+import os
+sys.path.insert(0, os.path.abspath('../..'))  # Adds the parent directory to the system path
+import litellm 
+from litellm import completion 
+
+def logging_fn(model_call_dict):
+    print(f"model call details: {model_call_dict}")
+models = ["gorilla-7b-hf-v1", "gpt-4"]
+custom_llm_provider = None
+messages = [{"role": "user", "content": "Hey,  how's it going?"}]
+for model in models: # iterate through list
+    custom_api_base = None
+    if model == "gorilla-7b-hf-v1": 
+        custom_llm_provider = "custom_openai"
+        custom_api_base = "http://zanino.millennium.berkeley.edu:8000/v1"
+    completion(model=model, messages=messages, custom_llm_provider=custom_llm_provider, custom_api_base=custom_api_base, logger_fn=logging_fn)

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "litellm"
-version = "0.1.379"
+version = "0.1.380"
 description = "Library to easily interface with LLM API providers"
 authors = ["BerriAI"]
 license = "MIT License"