raise better exception if llm provider isn't passed in or inferred

litellm/__init__.py

@@ -238,6 +238,7 @@ from .utils import (
     register_prompt_template,
     validate_environment,
     check_valid_key,
+    get_llm_provider
 )
 from .main import *  # type: ignore
 from .integrations import *

litellm/main.py

@@ -17,6 +17,7 @@ from litellm.utils import (
     CustomStreamWrapper,
     read_config_args,
     completion_with_fallbacks,
+    get_llm_provider
 )
 from .llms import anthropic
 from .llms import together_ai
@@ -168,6 +169,7 @@ def completion(
             completion_call_id=id
         )
         logging.update_environment_variables(model=model, user=user, optional_params=optional_params, litellm_params=litellm_params)
+        get_llm_provider(model=model, custom_llm_provider=custom_llm_provider)
         if custom_llm_provider == "azure":
             # azure configs
             openai.api_type = get_secret("AZURE_API_TYPE") or "azure"

litellm/tests/test_bad_params.py

@@ -32,6 +32,16 @@ def test_completion_with_empty_model():
         pass
 
 
+def test_completion_with_no_provider():
+    # test on empty
+    try:
+        model = "cerebras/btlm-3b-8k-base"
+        response = completion(model=model, messages=messages)
+    except Exception as e:
+        print(f"error occurred: {e}")
+        pass
+
+test_completion_with_no_provider()
 # # bad key
 # temp_key = os.environ.get("OPENAI_API_KEY")
 # os.environ["OPENAI_API_KEY"] = "bad-key"

litellm/utils.py

@@ -931,6 +931,55 @@ def get_optional_params(  # use the openai defaults
         return optional_params
     return optional_params
 
+def get_llm_provider(model: str, custom_llm_provider: str = None):
+    try:
+        # check if llm provider provided
+        if custom_llm_provider:
+            return model, custom_llm_provider
+
+        # check if llm provider part of model name
+        if model.split("/",1)[0] in litellm.provider_list:
+            custom_llm_provider = model.split("/", 1)[0]
+            model = model.split("/", 1)[1]
+            return model, custom_llm_provider
+
+        # check if model in known model provider list 
+        ## openai - chatcompletion + text completion
+        if model in litellm.open_ai_chat_completion_models or model in litellm.open_ai_text_completion_models:
+            custom_llm_provider = "openai"
+        ## cohere
+        elif model in litellm.cohere_models:
+            custom_llm_provider = "cohere"
+        ## replicate
+        elif model in litellm.replicate_models:
+            custom_llm_provider = "replicate"
+        ## openrouter
+        elif model in litellm.openrouter_models:
+            custom_llm_provider = "openrouter"
+        ## vertex - text + chat models
+        elif model in litellm.vertex_chat_models or model in litellm.vertex_text_models:
+            custom_llm_provider = "vertex_ai"
+        ## huggingface 
+        elif model in litellm.huggingface_models:
+            custom_llm_provider = "huggingface"
+        ## ai21 
+        elif model in litellm.ai21_models:
+            custom_llm_provider = "ai21"
+        ## together_ai 
+        elif model in litellm.together_ai_models:
+            custom_llm_provider = "together_ai"
+        ## aleph_alpha 
+        elif model in litellm.aleph_alpha_models:
+            custom_llm_provider = "aleph_alpha"
+        ## baseten 
+        elif model in litellm.baseten_models:
+            custom_llm_provider = "baseten"
+        
+        if custom_llm_provider is None:
+            raise ValueError(f"LLM Provider NOT provided. Pass in the LLM provider you are trying to call. E.g. For 'Huggingface' inference endpoints pass in `completion(model='huggingface/{model}',..)` Learn more: https://docs.litellm.ai/docs/providers")
+        return model, custom_llm_provider
+    except Exception as e: 
+        raise e
 
 def get_max_tokens(model: str):
     try:

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "litellm"
-version = "0.1.601"
+version = "0.1.602"
 description = "Library to easily interface with LLM API providers"
 authors = ["BerriAI"]
 license = "MIT License"