fix(utils.py): allow url to be passed to model cost map

litellm/__init__.py

@@ -9,10 +9,10 @@ failure_callback: List[Union[str, Callable]] = []
 set_verbose = False
 email: Optional[
     str
-] = None  # for hosted dashboard. Learn more - https://docs.litellm.ai/docs/debugging/hosted_debugging
+] = None  # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
 token: Optional[
     str
-] = None  # for hosted dashboard. Learn more - https://docs.litellm.ai/docs/debugging/hosted_debugging
+] = None  # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
 telemetry = True
 max_tokens = 256  # OpenAI Defaults
 drop_params = False
@@ -34,9 +34,9 @@ aleph_alpha_key: Optional[str] = None
 nlp_cloud_key: Optional[str] = None
 use_client: bool = False
 logging: bool = True
-caching: bool = False # deprecated son
+caching: bool = False # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
-caching_with_models: bool = False  # if you want the caching key to be model + prompt # deprecated soon
+caching_with_models: bool = False  # # Not used anymore, will be removed in next MAJOR release - https://github.com/BerriAI/litellm/discussions/648
-cache: Optional[Cache] = None # cache object
+cache: Optional[Cache] = None # cache object <- use this - https://docs.litellm.ai/docs/caching
 model_alias_map: Dict[str, str] = {}
 max_budget: float = 0.0 # set the max budget across all providers
 _current_cost = 0 # private variable, used if max budget is set 
@@ -44,11 +44,10 @@ error_logs: Dict = {}
 add_function_to_prompt: bool = False # if function calling not supported by api, append function call details to system prompt
 client_session: Optional[requests.Session] = None
 model_fallbacks: Optional[List] = None
+model_cost_map_url: str = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
 #############################################
 
 def get_model_cost_map(url: Optional[str]=None):
-    if url is None:
-        url = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
     try:
         response = requests.get(url)
         response.raise_for_status()  # Raise an exception if request is unsuccessful
@@ -60,7 +59,7 @@ def get_model_cost_map(url: Optional[str]=None):
         with importlib.resources.open_text("litellm", "model_prices_and_context_window_backup.json") as f:
             content = json.load(f)
             return content
-model_cost = get_model_cost_map()
+model_cost = get_model_cost_map(url=model_cost_map_url)
 custom_prompt_dict:Dict[str, dict] = {}
 ####### THREAD-SPECIFIC DATA ###################
 class MyLocal(threading.local):

litellm/tests/test_register_model.py

@@ -24,4 +24,13 @@ def test_update_model_cost():
     except Exception as e:
         pytest.fail(f"An error occurred: {e}")
 
-test_update_model_cost()
+# test_update_model_cost()
+
+def test_update_model_cost_map_url(): 
+    try: 
+        litellm.register_model(model_cost="https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json")
+        assert litellm.model_cost["gpt-4"]["input_cost_per_token"] == 0.00003
+    except Exception as e:
+        pytest.fail(f"An error occurred: {e}")
+
+test_update_model_cost_map_url()

litellm/utils.py

@@ -1049,9 +1049,10 @@ def completion_cost(
         return 0.0 # this should not block a users execution path
 
 ####### HELPER FUNCTIONS ################
-def register_model(model_cost: dict): 
+def register_model(model_cost: Union[str, dict]): 
     """
     Register new / Override existing models (and their pricing) to specific providers. 
+    Provide EITHER a model cost dictionary or a url to a hosted json blob
     Example usage: 
     model_cost_dict = {
         "gpt-4": {
@@ -1063,9 +1064,15 @@ def register_model(model_cost: dict):
         },
     }
     """
-    for key, value in model_cost.items():
+    loaded_model_cost = {}
+    if isinstance(model_cost, dict): 
+        loaded_model_cost = model_cost
+    elif isinstance(model_cost, str): 
+        loaded_model_cost = litellm.get_model_cost_map(url=model_cost)
+
+    for key, value in loaded_model_cost.items():
         ## override / add new keys to the existing model cost dictionary
-        litellm.model_cost[key] = model_cost[key]
+        litellm.model_cost[key] = loaded_model_cost[key]
 
         # add new model names to provider lists
         if value.get('litellm_provider') == 'openai':