fix(router.py): use user-defined model_input_tokens for pre-call filter checks

litellm/proxy/_new_secret_config.yaml

@@ -4,7 +4,17 @@ model_list:
       model: bedrock/anthropic.claude-3-sonnet-20240229-v1:0
       api_key: my-fake-key
       aws_bedrock_runtime_endpoint: http://127.0.0.1:8000
+      mock_response: "Hello world 1"
+    model_info: 
+      max_input_tokens: 0 # trigger context window fallback
+  - model_name: my-fake-model
+    litellm_params:
+      model: bedrock/anthropic.claude-3-sonnet-20240229-v1:0
+      api_key: my-fake-key
+      aws_bedrock_runtime_endpoint: http://127.0.0.1:8000
+      mock_response: "Hello world 2"
+    model_info: 
+      max_input_tokens: 0
 
-litellm_settings:
-  success_callback: ["langfuse"]
-  failure_callback: ["langfuse"]
+router_settings:
+  enable_pre_call_checks: True

litellm/router.py

@@ -404,6 +404,7 @@ class Router:
             litellm.failure_callback = [self.deployment_callback_on_failure]
         print(  # noqa
             f"Intialized router with Routing strategy: {self.routing_strategy}\n\n"
+            f"Routing enable_pre_call_checks: {self.enable_pre_call_checks}\n\n"
             f"Routing fallbacks: {self.fallbacks}\n\n"
             f"Routing content fallbacks: {self.content_policy_fallbacks}\n\n"
             f"Routing context window fallbacks: {self.context_window_fallbacks}\n\n"
@@ -3915,9 +3916,38 @@ class Router:
                         raise Exception("Model invalid format - {}".format(type(model)))
         return None
 
+    def get_router_model_info(self, deployment: dict) -> ModelMapInfo:
+        """
+        For a given model id, return the model info (max tokens, input cost, output cost, etc.).
+
+        Augment litellm info with additional params set in `model_info`.
+
+        Returns
+        - ModelInfo - If found -> typed dict with max tokens, input cost, etc.
+        """
+        ## SET MODEL NAME
+        base_model = deployment.get("model_info", {}).get("base_model", None)
+        if base_model is None:
+            base_model = deployment.get("litellm_params", {}).get("base_model", None)
+        model = base_model or deployment.get("litellm_params", {}).get("model", None)
+
+        ## GET LITELLM MODEL INFO
+        model_info = litellm.get_model_info(model=model)
+
+        ## CHECK USER SET MODEL INFO
+        user_model_info = deployment.get("model_info", {})
+
+        model_info.update(user_model_info)
+
+        return model_info
+
     def get_model_info(self, id: str) -> Optional[dict]:
         """
         For a given model id, return the model info
+
+        Returns
+        - dict: the model in list with 'model_name', 'litellm_params', Optional['model_info']
+        - None: could not find deployment in list
         """
         for model in self.model_list:
             if "model_info" in model and "id" in model["model_info"]:
@@ -4307,6 +4337,7 @@ class Router:
             return _returned_deployments
 
         _context_window_error = False
+        _potential_error_str = ""
         _rate_limit_error = False
 
         ## get model group RPM ##
@@ -4327,7 +4358,7 @@ class Router:
                 model = base_model or deployment.get("litellm_params", {}).get(
                     "model", None
                 )
-                model_info = litellm.get_model_info(model=model)
+                model_info = self.get_router_model_info(deployment=deployment)
 
                 if (
                     isinstance(model_info, dict)
@@ -4339,6 +4370,11 @@ class Router:
                     ):
                         invalid_model_indices.append(idx)
                         _context_window_error = True
+                        _potential_error_str += (
+                            "Model={}, Max Input Tokens={}, Got={}".format(
+                                model, model_info["max_input_tokens"], input_tokens
+                            )
+                        )
                         continue
             except Exception as e:
                 verbose_router_logger.debug("An error occurs - {}".format(str(e)))
@@ -4440,7 +4476,9 @@ class Router:
                 )
             elif _context_window_error == True:
                 raise litellm.ContextWindowExceededError(
-                    message="Context Window exceeded for given call",
+                    message="litellm._pre_call_checks: Context Window exceeded for given call. No models have context window large enough for this call.\n{}".format(
+                        _potential_error_str
+                    ),
                     model=model,
                     llm_provider="",
                     response=httpx.Response(

litellm/tests/test_router.py

@@ -755,6 +755,7 @@ def test_router_context_window_check_pre_call_check_in_group():
                     "api_version": os.getenv("AZURE_API_VERSION"),
                     "api_base": os.getenv("AZURE_API_BASE"),
                     "base_model": "azure/gpt-35-turbo",
+                    "mock_response": "Hello world 1!",
                 },
             },
             {
@@ -762,6 +763,7 @@ def test_router_context_window_check_pre_call_check_in_group():
                 "litellm_params": {  # params for litellm completion/embedding call
                     "model": "gpt-3.5-turbo-1106",
                     "api_key": os.getenv("OPENAI_API_KEY"),
+                    "mock_response": "Hello world 2!",
                 },
             },
         ]
@@ -777,6 +779,9 @@ def test_router_context_window_check_pre_call_check_in_group():
         )
 
         print(f"response: {response}")
+
+        assert response.choices[0].message.content == "Hello world 2!"
+        assert False
     except Exception as e:
         pytest.fail(f"Got unexpected exception on router! - {str(e)}")