From 010a4d44af23f12b6061559a0325fa2fa1ea9fb4 Mon Sep 17 00:00:00 2001
From: Krish Dholakia <krrishdholakia@gmail.com>
Date: Sat, 24 May 2025 12:12:31 -0700
Subject: [PATCH] Fix passing standard optional params (#11124)

* fix(main.py): use processed non-default-params as standard input params for langfuse

Fixes https://github.com/BerriAI/litellm/issues/11072

 Fixes https://github.com/BerriAI/litellm/issues/11096

* fix(main.py): rename variable to be more accurate

* test(test_langfuse_e2e_test.py): add router unit test for langfuse e2e testing

Prevent https://github.com/BerriAI/litellm/issues/11072 from happening again

* build: update lock

* fix(utils.py): refactor optional params function

make it easier to get the standardized non default params

* fix(utils.py): improve process non default params function

* fix(main.py): include provider specific params in processed non default params used in logging

ensures user can see any provider specific params on langfuse

 ensures user can see any provider specific params on langfus e
---
 .../litellm_enterprise-0.1.6-py3-none-any.whl | Bin 0 -> 88534 bytes
 .../dist/litellm_enterprise-0.1.6.tar.gz      | Bin 0 -> 33399 bytes
 litellm/constants.py                          |  40 +++
 litellm/main.py                               |  98 +++---
 .../proxy/_experimental/out/onboarding.html   |   1 -
 litellm/proxy/_new_secret_config.yaml         |   2 +-
 litellm/utils.py                              | 318 +++++++++---------
 tests/litellm/test_utils.py                   |  73 +++-
 tests/llm_translation/test_optional_params.py |  21 ++
 tests/local_testing/test_ollama.py            |   8 +-
 .../completion_with_router.json               |  87 +++++
 .../test_langfuse_e2e_test.py                 |  39 +++
 12 files changed, 468 insertions(+), 219 deletions(-)
 create mode 100644 enterprise/dist/litellm_enterprise-0.1.6-py3-none-any.whl
 create mode 100644 enterprise/dist/litellm_enterprise-0.1.6.tar.gz
 delete mode 100644 litellm/proxy/_experimental/out/onboarding.html
 create mode 100644 tests/logging_callback_tests/langfuse_expected_request_body/completion_with_router.json

diff --git a/enterprise/dist/litellm_enterprise-0.1.6-py3-none-any.whl b/enterprise/dist/litellm_enterprise-0.1.6-py3-none-any.whl
new file mode 100644
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literal 0
HcmV?d00001

diff --git a/litellm/constants.py b/litellm/constants.py
index 43a8eba3c1d..fba57a2bf9d 100644
--- a/litellm/constants.py
+++ b/litellm/constants.py
@@ -282,6 +282,46 @@ OPENAI_CHAT_COMPLETION_PARAMS = [
     "web_search_options",
 ]
 
+DEFAULT_CHAT_COMPLETION_PARAM_VALUES = {
+    "functions": None,
+    "function_call": None,
+    "temperature": None,
+    "top_p": None,
+    "n": None,
+    "stream": None,
+    "stream_options": None,
+    "stop": None,
+    "max_tokens": None,
+    "max_completion_tokens": None,
+    "modalities": None,
+    "prediction": None,
+    "audio": None,
+    "presence_penalty": None,
+    "frequency_penalty": None,
+    "logit_bias": None,
+    "user": None,
+    "model": None,
+    "custom_llm_provider": "",
+    "response_format": None,
+    "seed": None,
+    "tools": None,
+    "tool_choice": None,
+    "max_retries": None,
+    "logprobs": None,
+    "top_logprobs": None,
+    "extra_headers": None,
+    "api_version": None,
+    "parallel_tool_calls": None,
+    "drop_params": None,
+    "allowed_openai_params": None,
+    "additional_drop_params": None,
+    "messages": None,
+    "reasoning_effort": None,
+    "thinking": None,
+    "web_search_options": None,
+}
+
+
 openai_compatible_endpoints: List = [
     "api.perplexity.ai",
     "api.endpoints.anyscale.com/v1",
diff --git a/litellm/main.py b/litellm/main.py
index 44611e203f0..7f1ecd737f8 100644
--- a/litellm/main.py
+++ b/litellm/main.py
@@ -86,6 +86,7 @@ from litellm.utils import (
     ProviderConfigManager,
     Usage,
     add_openai_metadata,
+    add_provider_specific_params_to_optional_params,
     async_mock_completion_streaming_obj,
     convert_to_model_response_object,
     create_pretrained_tokenizer,
@@ -99,6 +100,7 @@ from litellm.utils import (
     get_secret,
     get_standard_openai_params,
     mock_completion_streaming_obj,
+    pre_process_non_default_params,
     read_config_args,
     supports_httpx_timeout,
     token_counter,
@@ -1140,42 +1142,55 @@ def completion(  # type: ignore # noqa: PLR0915
         if dynamic_api_key is not None:
             api_key = dynamic_api_key
         # check if user passed in any of the OpenAI optional params
-        optional_params = get_optional_params(
-            functions=functions,
-            function_call=function_call,
-            temperature=temperature,
-            top_p=top_p,
-            n=n,
-            stream=stream,
-            stream_options=stream_options,
-            stop=stop,
-            max_tokens=max_tokens,
-            max_completion_tokens=max_completion_tokens,
-            modalities=modalities,
-            prediction=prediction,
-            audio=audio,
-            presence_penalty=presence_penalty,
-            frequency_penalty=frequency_penalty,
-            logit_bias=logit_bias,
-            user=user,
+        optional_param_args = {
+            "functions": functions,
+            "function_call": function_call,
+            "temperature": temperature,
+            "top_p": top_p,
+            "n": n,
+            "stream": stream,
+            "stream_options": stream_options,
+            "stop": stop,
+            "max_tokens": max_tokens,
+            "max_completion_tokens": max_completion_tokens,
+            "modalities": modalities,
+            "prediction": prediction,
+            "audio": audio,
+            "presence_penalty": presence_penalty,
+            "frequency_penalty": frequency_penalty,
+            "logit_bias": logit_bias,
+            "user": user,
             # params to identify the model
+            "model": model,
+            "custom_llm_provider": custom_llm_provider,
+            "response_format": response_format,
+            "seed": seed,
+            "tools": tools,
+            "tool_choice": tool_choice,
+            "max_retries": max_retries,
+            "logprobs": logprobs,
+            "top_logprobs": top_logprobs,
+            "api_version": api_version,
+            "parallel_tool_calls": parallel_tool_calls,
+            "messages": messages,
+            "reasoning_effort": reasoning_effort,
+            "thinking": thinking,
+            "web_search_options": web_search_options,
+            "allowed_openai_params": kwargs.get("allowed_openai_params"),
+        }
+        optional_params = get_optional_params(
+            **optional_param_args, **non_default_params
+        )
+        processed_non_default_params = pre_process_non_default_params(
             model=model,
+            passed_params=optional_param_args,
+            special_params=non_default_params,
             custom_llm_provider=custom_llm_provider,
-            response_format=response_format,
-            seed=seed,
-            tools=tools,
-            tool_choice=tool_choice,
-            max_retries=max_retries,
-            logprobs=logprobs,
-            top_logprobs=top_logprobs,
-            api_version=api_version,
-            parallel_tool_calls=parallel_tool_calls,
-            messages=messages,
-            reasoning_effort=reasoning_effort,
-            thinking=thinking,
-            web_search_options=web_search_options,
-            allowed_openai_params=kwargs.get("allowed_openai_params"),
-            **non_default_params,
+            additional_drop_params=kwargs.get("additional_drop_params"),
+        )
+        processed_non_default_params = add_provider_specific_params_to_optional_params(
+            optional_params=processed_non_default_params,
+            passed_params=non_default_params,
         )
 
         if litellm.add_function_to_prompt and optional_params.get(
@@ -1241,10 +1256,7 @@ def completion(  # type: ignore # noqa: PLR0915
         cast(LiteLLMLoggingObj, logging).update_environment_variables(
             model=model,
             user=user,
-            optional_params={
-                **standard_openai_params,
-                **non_default_params,
-            },  # [IMPORTANT] - using standard_openai_params ensures consistent params logged to langfuse for finetuning / eval datasets.
+            optional_params=processed_non_default_params,  # [IMPORTANT] - using processed_non_default_params ensures consistent params logged to langfuse for finetuning / eval datasets.
             litellm_params=litellm_params,
             custom_llm_provider=custom_llm_provider,
         )
@@ -4027,9 +4039,7 @@ def embedding(  # noqa: PLR0915
                 client=client,
                 aembedding=aembedding,
             )
-        elif (
-            custom_llm_provider in litellm._custom_providers
-        ):
+        elif custom_llm_provider in litellm._custom_providers:
             custom_handler: Optional[CustomLLM] = None
             for item in litellm.custom_provider_map:
                 if item["provider"] == custom_llm_provider:
@@ -4040,7 +4050,11 @@ def embedding(  # noqa: PLR0915
                     model=model, custom_llm_provider=custom_llm_provider
                 )
 
-            handler_fn = custom_handler.embedding if not aembedding else custom_handler.aembedding
+            handler_fn = (
+                custom_handler.embedding
+                if not aembedding
+                else custom_handler.aembedding
+            )
 
             response = handler_fn(
                 model=model,
@@ -4049,7 +4063,7 @@ def embedding(  # noqa: PLR0915
                 optional_params=optional_params,
                 model_response=EmbeddingResponse(),
                 print_verbose=print_verbose,
-                litellm_params=litellm_params
+                litellm_params=litellm_params,
             )
         else:
             raise LiteLLMUnknownProvider(
diff --git a/litellm/proxy/_experimental/out/onboarding.html b/litellm/proxy/_experimental/out/onboarding.html
deleted file mode 100644
index 82cebe3a379..00000000000
--- a/litellm/proxy/_experimental/out/onboarding.html
+++ /dev/null
@@ -1 +0,0 @@
-<!DOCTYPE html><html id="__next_error__"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="script" fetchPriority="low" href="/ui/_next/static/chunks/webpack-75a5453f51d60261.js"/><script src="/ui/_next/static/chunks/fd9d1056-205af899b895cbac.js" async=""></script><script src="/ui/_next/static/chunks/117-1c5bfc45bfc4237d.js" async=""></script><script src="/ui/_next/static/chunks/main-app-475d6efe4080647d.js" async=""></script><title>LiteLLM Dashboard</title><meta name="description" content="LiteLLM Proxy Admin UI"/><link rel="icon" href="/ui/favicon.ico" type="image/x-icon" sizes="16x16"/><meta name="next-size-adjust"/><script src="/ui/_next/static/chunks/polyfills-42372ed130431b0a.js" noModule=""></script></head><body><script src="/ui/_next/static/chunks/webpack-75a5453f51d60261.js" async=""></script><script>(self.__next_f=self.__next_f||[]).push([0]);self.__next_f.push([2,null])</script><script>self.__next_f.push([1,"1:HL[\"/ui/_next/static/media/a34f9d1faa5f3315-s.p.woff2\",\"font\",{\"crossOrigin\":\"\",\"type\":\"font/woff2\"}]\n2:HL[\"/ui/_next/static/css/86f6cc749f6b8493.css\",\"style\"]\n3:HL[\"/ui/_next/static/css/1d069faa72590087.css\",\"style\"]\n"])</script><script>self.__next_f.push([1,"4:I[12846,[],\"\"]\n6:I[19107,[],\"ClientPageRoot\"]\n7:I[12011,[\"665\",\"static/chunks/3014691f-b7b79b78e27792f3.js\",\"402\",\"static/chunks/402-ba983153c902cb17.js\",\"899\",\"static/chunks/899-ebef5c8ffc176e86.js\",\"250\",\"static/chunks/250-b34a5fd44bf9b45f.js\",\"461\",\"static/chunks/app/onboarding/page-8c2f1d7b29a0b5ff.js\"],\"default\",1]\n8:I[4707,[],\"\"]\n9:I[36423,[],\"\"]\nb:I[61060,[],\"\"]\nc:[]\n"])</script><script>self.__next_f.push([1,"0:[\"$\",\"$L4\",null,{\"buildId\":\"Gp6m3rw9rJaKAYvn5VVfq\",\"assetPrefix\":\"/ui\",\"urlParts\":[\"\",\"onboarding\"],\"initialTree\":[\"\",{\"children\":[\"onboarding\",{\"children\":[\"__PAGE__\",{}]}]},\"$undefined\",\"$undefined\",true],\"initialSeedData\":[\"\",{\"children\":[\"onboarding\",{\"children\":[\"__PAGE__\",{},[[\"$L5\",[\"$\",\"$L6\",null,{\"props\":{\"params\":{},\"searchParams\":{}},\"Component\":\"$7\"}],null],null],null]},[null,[\"$\",\"$L8\",null,{\"parallelRouterKey\":\"children\",\"segmentPath\":[\"children\",\"onboarding\",\"children\"],\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L9\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":\"$undefined\",\"notFoundStyles\":\"$undefined\"}]],null]},[[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/86f6cc749f6b8493.css\",\"precedence\":\"next\",\"crossOrigin\":\"$undefined\"}],[\"$\",\"link\",\"1\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/1d069faa72590087.css\",\"precedence\":\"next\",\"crossOrigin\":\"$undefined\"}]],[\"$\",\"html\",null,{\"lang\":\"en\",\"children\":[\"$\",\"body\",null,{\"className\":\"__className_cf7686\",\"children\":[\"$\",\"$L8\",null,{\"parallelRouterKey\":\"children\",\"segmentPath\":[\"children\"],\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L9\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":[[\"$\",\"title\",null,{\"children\":\"404: This page could not be found.\"}],[\"$\",\"div\",null,{\"style\":{\"fontFamily\":\"system-ui,\\\"Segoe UI\\\",Roboto,Helvetica,Arial,sans-serif,\\\"Apple Color Emoji\\\",\\\"Segoe UI Emoji\\\"\",\"height\":\"100vh\",\"textAlign\":\"center\",\"display\":\"flex\",\"flexDirection\":\"column\",\"alignItems\":\"center\",\"justifyContent\":\"center\"},\"children\":[\"$\",\"div\",null,{\"children\":[[\"$\",\"style\",null,{\"dangerouslySetInnerHTML\":{\"__html\":\"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}\"}}],[\"$\",\"h1\",null,{\"className\":\"next-error-h1\",\"style\":{\"display\":\"inline-block\",\"margin\":\"0 20px 0 0\",\"padding\":\"0 23px 0 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\ No newline at end of file
diff --git a/litellm/proxy/_new_secret_config.yaml b/litellm/proxy/_new_secret_config.yaml
index 5fa3e618c22..58b40e8f0ce 100644
--- a/litellm/proxy/_new_secret_config.yaml
+++ b/litellm/proxy/_new_secret_config.yaml
@@ -79,7 +79,7 @@ model_list:
       api_key: os.environ/OPENAI_API_KEY
 
 litellm_settings:
-  store_audit_logs: true
+  callbacks: ["langfuse"]
 
 general_settings:
   store_model_in_db: true
diff --git a/litellm/utils.py b/litellm/utils.py
index 65d825c979c..f4f3707ebf9 100644
--- a/litellm/utils.py
+++ b/litellm/utils.py
@@ -63,6 +63,7 @@ from litellm.caching._internal_lru_cache import lru_cache_wrapper
 from litellm.caching.caching import DualCache
 from litellm.caching.caching_handler import CachingHandlerResponse, LLMCachingHandler
 from litellm.constants import (
+    DEFAULT_CHAT_COMPLETION_PARAM_VALUES,
     DEFAULT_MAX_LRU_CACHE_SIZE,
     DEFAULT_TRIM_RATIO,
     FUNCTION_DEFINITION_TOKEN_COUNT,
@@ -2671,50 +2672,18 @@ def _remove_unsupported_params(
     return non_default_params
 
 
-def get_optional_params(  # noqa: PLR0915
-    # use the openai defaults
-    # https://platform.openai.com/docs/api-reference/chat/create
+def pre_process_non_default_params(
+    passed_params: dict,
+    special_params: dict,
+    custom_llm_provider: str,
+    additional_drop_params: Optional[List[str]],
     model: str,
-    functions=None,
-    function_call=None,
-    temperature=None,
-    top_p=None,
-    n=None,
-    stream=False,
-    stream_options=None,
-    stop=None,
-    max_tokens=None,
-    max_completion_tokens=None,
-    modalities=None,
-    prediction=None,
-    audio=None,
-    presence_penalty=None,
-    frequency_penalty=None,
-    logit_bias=None,
-    user=None,
-    custom_llm_provider="",
-    response_format=None,
-    seed=None,
-    tools=None,
-    tool_choice=None,
-    max_retries=None,
-    logprobs=None,
-    top_logprobs=None,
-    extra_headers=None,
-    api_version=None,
-    parallel_tool_calls=None,
-    drop_params=None,
-    allowed_openai_params: Optional[List[str]] = None,
-    reasoning_effort=None,
-    additional_drop_params=None,
-    messages: Optional[List[AllMessageValues]] = None,
-    thinking: Optional[AnthropicThinkingParam] = None,
-    web_search_options: Optional[OpenAIWebSearchOptions] = None,
-    **kwargs,
-):
+) -> dict:
+    """
+    Pre-process non-default params to a standardized format
+    """
     # retrieve all parameters passed to the function
-    passed_params = locals().copy()
-    special_params = passed_params.pop("kwargs")
+
     for k, v in special_params.items():
         if k.startswith("aws_") and (
             custom_llm_provider != "bedrock"
@@ -2731,6 +2700,72 @@ def get_optional_params(  # noqa: PLR0915
             continue
         passed_params[k] = v
 
+    # filter out those parameters that were passed with non-default values
+
+    non_default_params = {
+        k: v
+        for k, v in passed_params.items()
+        if (
+            k != "model"
+            and k != "custom_llm_provider"
+            and k != "api_version"
+            and k != "drop_params"
+            and k != "allowed_openai_params"
+            and k != "additional_drop_params"
+            and k != "messages"
+            and k in DEFAULT_CHAT_COMPLETION_PARAM_VALUES
+            and v != DEFAULT_CHAT_COMPLETION_PARAM_VALUES[k]
+            and _should_drop_param(k=k, additional_drop_params=additional_drop_params)
+            is False
+        )
+    }
+
+    provider_config: Optional[BaseConfig] = None
+    if custom_llm_provider is not None and custom_llm_provider in [
+        provider.value for provider in LlmProviders
+    ]:
+        provider_config = ProviderConfigManager.get_provider_chat_config(
+            model=model, provider=LlmProviders(custom_llm_provider)
+        )
+
+    if "response_format" in non_default_params:
+        if provider_config is not None:
+            non_default_params[
+                "response_format"
+            ] = provider_config.get_json_schema_from_pydantic_object(
+                response_format=non_default_params["response_format"]
+            )
+        else:
+            non_default_params["response_format"] = type_to_response_format_param(
+                response_format=non_default_params["response_format"]
+            )
+
+    if "tools" in non_default_params and isinstance(
+        non_default_params, list
+    ):  # fixes https://github.com/BerriAI/litellm/issues/4933
+        tools = non_default_params["tools"]
+        for (
+            tool
+        ) in (
+            tools
+        ):  # clean out 'additionalProperties = False'. Causes vertexai/gemini OpenAI API Schema errors - https://github.com/langchain-ai/langchainjs/issues/5240
+            tool_function = tool.get("function", {})
+            parameters = tool_function.get("parameters", None)
+            if parameters is not None:
+                new_parameters = copy.deepcopy(parameters)
+                if (
+                    "additionalProperties" in new_parameters
+                    and new_parameters["additionalProperties"] is False
+                ):
+                    new_parameters.pop("additionalProperties", None)
+                tool_function["parameters"] = new_parameters
+    return non_default_params
+
+
+def pre_process_optional_params(
+    passed_params: dict, non_default_params: dict, custom_llm_provider: str
+) -> dict:
+    """For .completion(), preprocess optional params"""
     optional_params: Dict = {}
 
     common_auth_dict = litellm.common_cloud_provider_auth_params
@@ -2761,65 +2796,6 @@ def get_optional_params(  # noqa: PLR0915
                 non_default_params=passed_params, optional_params=optional_params
             )
 
-    default_params = {
-        "functions": None,
-        "function_call": None,
-        "temperature": None,
-        "top_p": None,
-        "n": None,
-        "stream": None,
-        "stream_options": None,
-        "stop": None,
-        "max_tokens": None,
-        "max_completion_tokens": None,
-        "modalities": None,
-        "prediction": None,
-        "audio": None,
-        "presence_penalty": None,
-        "frequency_penalty": None,
-        "logit_bias": None,
-        "user": None,
-        "model": None,
-        "custom_llm_provider": "",
-        "response_format": None,
-        "seed": None,
-        "tools": None,
-        "tool_choice": None,
-        "max_retries": None,
-        "logprobs": None,
-        "top_logprobs": None,
-        "extra_headers": None,
-        "api_version": None,
-        "parallel_tool_calls": None,
-        "drop_params": None,
-        "allowed_openai_params": None,
-        "additional_drop_params": None,
-        "messages": None,
-        "reasoning_effort": None,
-        "thinking": None,
-        "web_search_options": None,
-    }
-
-    # filter out those parameters that were passed with non-default values
-
-    non_default_params = {
-        k: v
-        for k, v in passed_params.items()
-        if (
-            k != "model"
-            and k != "custom_llm_provider"
-            and k != "api_version"
-            and k != "drop_params"
-            and k != "allowed_openai_params"
-            and k != "additional_drop_params"
-            and k != "messages"
-            and k in default_params
-            and v != default_params[k]
-            and _should_drop_param(k=k, additional_drop_params=additional_drop_params)
-            is False
-        )
-    }
-
     ## raise exception if function calling passed in for a provider that doesn't support it
     if (
         "functions" in non_default_params
@@ -2879,6 +2855,64 @@ def get_optional_params(  # noqa: PLR0915
                     message=f"Function calling is not supported by {custom_llm_provider}.",
                 )
 
+    return optional_params
+
+
+def get_optional_params(  # noqa: PLR0915
+    # use the openai defaults
+    # https://platform.openai.com/docs/api-reference/chat/create
+    model: str,
+    functions=None,
+    function_call=None,
+    temperature=None,
+    top_p=None,
+    n=None,
+    stream=False,
+    stream_options=None,
+    stop=None,
+    max_tokens=None,
+    max_completion_tokens=None,
+    modalities=None,
+    prediction=None,
+    audio=None,
+    presence_penalty=None,
+    frequency_penalty=None,
+    logit_bias=None,
+    user=None,
+    custom_llm_provider="",
+    response_format=None,
+    seed=None,
+    tools=None,
+    tool_choice=None,
+    max_retries=None,
+    logprobs=None,
+    top_logprobs=None,
+    extra_headers=None,
+    api_version=None,
+    parallel_tool_calls=None,
+    drop_params=None,
+    allowed_openai_params: Optional[List[str]] = None,
+    reasoning_effort=None,
+    additional_drop_params=None,
+    messages: Optional[List[AllMessageValues]] = None,
+    thinking: Optional[AnthropicThinkingParam] = None,
+    web_search_options: Optional[OpenAIWebSearchOptions] = None,
+    **kwargs,
+):
+    passed_params = locals().copy()
+    special_params = passed_params.pop("kwargs")
+    non_default_params = pre_process_non_default_params(
+        passed_params=passed_params,
+        special_params=special_params,
+        custom_llm_provider=custom_llm_provider,
+        additional_drop_params=additional_drop_params,
+        model=model,
+    )
+    optional_params = pre_process_optional_params(
+        passed_params=passed_params,
+        non_default_params=non_default_params,
+        custom_llm_provider=custom_llm_provider,
+    )
     provider_config: Optional[BaseConfig] = None
     if custom_llm_provider is not None and custom_llm_provider in [
         provider.value for provider in LlmProviders
@@ -2887,38 +2921,6 @@ def get_optional_params(  # noqa: PLR0915
             model=model, provider=LlmProviders(custom_llm_provider)
         )
 
-    if "response_format" in non_default_params:
-        if provider_config is not None:
-            non_default_params[
-                "response_format"
-            ] = provider_config.get_json_schema_from_pydantic_object(
-                response_format=non_default_params["response_format"]
-            )
-        else:
-            non_default_params["response_format"] = type_to_response_format_param(
-                response_format=non_default_params["response_format"]
-            )
-
-    if "tools" in non_default_params and isinstance(
-        non_default_params, list
-    ):  # fixes https://github.com/BerriAI/litellm/issues/4933
-        tools = non_default_params["tools"]
-        for (
-            tool
-        ) in (
-            tools
-        ):  # clean out 'additionalProperties = False'. Causes vertexai/gemini OpenAI API Schema errors - https://github.com/langchain-ai/langchainjs/issues/5240
-            tool_function = tool.get("function", {})
-            parameters = tool_function.get("parameters", None)
-            if parameters is not None:
-                new_parameters = copy.deepcopy(parameters)
-                if (
-                    "additionalProperties" in new_parameters
-                    and new_parameters["additionalProperties"] is False
-                ):
-                    new_parameters.pop("additionalProperties", None)
-                tool_function["parameters"] = new_parameters
-
     def _check_valid_arg(supported_params: List[str]):
         """
         Check if the params passed to completion() are supported by the provider
@@ -3608,7 +3610,7 @@ def get_optional_params(  # noqa: PLR0915
         ):
             extra_body = passed_params.pop("extra_body", {})
             for k in passed_params.keys():
-                if k not in default_params.keys():
+                if k not in DEFAULT_CHAT_COMPLETION_PARAM_VALUES.keys():
                     extra_body[k] = passed_params[k]
             optional_params.setdefault("extra_body", {})
             optional_params["extra_body"] = {
@@ -3621,9 +3623,9 @@ def get_optional_params(  # noqa: PLR0915
             )
     else:
         # if user passed in non-default kwargs for specific providers/models, pass them along
-        for k in passed_params.keys():
-            if k not in default_params.keys():
-                optional_params[k] = passed_params[k]
+        optional_params = add_provider_specific_params_to_optional_params(
+            optional_params=optional_params, passed_params=passed_params
+        )
     print_verbose(f"Final returned optional params: {optional_params}")
     optional_params = _apply_openai_param_overrides(
         optional_params=optional_params,
@@ -3633,6 +3635,18 @@ def get_optional_params(  # noqa: PLR0915
     return optional_params
 
 
+def add_provider_specific_params_to_optional_params(
+    optional_params: dict, passed_params: dict
+) -> dict:
+    """
+    Add provider specific params to optional_params
+    """
+    for k in passed_params.keys():
+        if k not in DEFAULT_CHAT_COMPLETION_PARAM_VALUES.keys():
+            optional_params[k] = passed_params[k]
+    return optional_params
+
+
 def _apply_openai_param_overrides(
     optional_params: dict, non_default_params: dict, allowed_openai_params: list
 ):
@@ -3649,31 +3663,6 @@ def _apply_openai_param_overrides(
 
 
 def get_non_default_params(passed_params: dict) -> dict:
-    default_params = {
-        "functions": None,
-        "function_call": None,
-        "temperature": None,
-        "top_p": None,
-        "n": None,
-        "stream": None,
-        "stream_options": None,
-        "stop": None,
-        "max_tokens": None,
-        "presence_penalty": None,
-        "frequency_penalty": None,
-        "logit_bias": None,
-        "user": None,
-        "model": None,
-        "custom_llm_provider": "",
-        "response_format": None,
-        "seed": None,
-        "tools": None,
-        "tool_choice": None,
-        "max_retries": None,
-        "logprobs": None,
-        "top_logprobs": None,
-        "extra_headers": None,
-    }
     # filter out those parameters that were passed with non-default values
     non_default_params = {
         k: v
@@ -3681,8 +3670,8 @@ def get_non_default_params(passed_params: dict) -> dict:
         if (
             k != "model"
             and k != "custom_llm_provider"
-            and k in default_params
-            and v != default_params[k]
+            and k in DEFAULT_CHAT_COMPLETION_PARAM_VALUES
+            and v != DEFAULT_CHAT_COMPLETION_PARAM_VALUES[k]
         )
     }
 
@@ -6604,6 +6593,7 @@ class ProviderConfigManager:
         elif LlmProviders.OLLAMA == provider or LlmProviders.OLLAMA_CHAT == provider:
             # Dynamic model listing for Ollama server
             from litellm.llms.ollama.common_utils import OllamaModelInfo
+
             return OllamaModelInfo()
         elif LlmProviders.VLLM == provider:
             from litellm.llms.vllm.common_utils import (
diff --git a/tests/litellm/test_utils.py b/tests/litellm/test_utils.py
index 7a2b6aa0108..eccd5b798d8 100644
--- a/tests/litellm/test_utils.py
+++ b/tests/litellm/test_utils.py
@@ -701,6 +701,7 @@ def test_supports_computer_use_utility():
     Tests the litellm.utils.supports_computer_use utility function.
     """
     from litellm.utils import supports_computer_use
+
     # Ensure LITELLM_LOCAL_MODEL_COST_MAP is set for consistent test behavior,
     # as supports_computer_use relies on get_model_info.
     # This also requires litellm.model_cost to be populated.
@@ -708,11 +709,13 @@ def test_supports_computer_use_utility():
     original_model_cost = getattr(litellm, "model_cost", None)
 
     os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
-    litellm.model_cost = litellm.get_model_cost_map(url="") # Load with local/backup
-    
+    litellm.model_cost = litellm.get_model_cost_map(url="")  # Load with local/backup
+
     try:
         # Test a model known to support computer_use from backup JSON
-        supports_cu_anthropic = supports_computer_use(model="anthropic/claude-3-7-sonnet-20250219")
+        supports_cu_anthropic = supports_computer_use(
+            model="anthropic/claude-3-7-sonnet-20250219"
+        )
         assert supports_cu_anthropic is True
 
         # Test a model known not to have the flag or set to false (defaults to False via get_model_info)
@@ -724,12 +727,13 @@ def test_supports_computer_use_utility():
             del os.environ["LITELLM_LOCAL_MODEL_COST_MAP"]
         else:
             os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = original_env_var
-        
+
         if original_model_cost is not None:
             litellm.model_cost = original_model_cost
         elif hasattr(litellm, "model_cost"):
             delattr(litellm, "model_cost")
 
+
 def test_get_model_info_shows_supports_computer_use():
     """
     Tests if 'supports_computer_use' is correctly retrieved by get_model_info.
@@ -739,13 +743,13 @@ def test_get_model_info_shows_supports_computer_use():
     os.environ["LITELLM_LOCAL_MODEL_COST_MAP"] = "True"
     # Ensure litellm.model_cost is loaded, relying on the backup mechanism if primary fails
     # as per previous debugging.
-    litellm.model_cost = litellm.get_model_cost_map(url="") 
-    
+    litellm.model_cost = litellm.get_model_cost_map(url="")
+
     # This model should have 'supports_computer_use': True in the backup JSON
     model_known_to_support_computer_use = "claude-3-7-sonnet-20250219"
     info = litellm.get_model_info(model_known_to_support_computer_use)
     print(f"Info for {model_known_to_support_computer_use}: {info}")
-    
+
     # After the fix in utils.py, this should now be present and True
     assert info.get("supports_computer_use") is True
 
@@ -754,4 +758,57 @@ def test_get_model_info_shows_supports_computer_use():
     model_known_not_to_support_computer_use = "gpt-3.5-turbo"
     info_gpt = litellm.get_model_info(model_known_not_to_support_computer_use)
     print(f"Info for {model_known_not_to_support_computer_use}: {info_gpt}")
-    assert info_gpt.get("supports_computer_use") is False # Expecting False due to the default in ModelInfoBase
\ No newline at end of file
+    assert (
+        info_gpt.get("supports_computer_use") is False
+    )  # Expecting False due to the default in ModelInfoBase
+
+
+@pytest.mark.parametrize(
+    "model, custom_llm_provider",
+    [
+        ("gpt-3.5-turbo", "openai"),
+        ("anthropic.claude-3-7-sonnet-20250219-v1:0", "bedrock"),
+        ("gemini-1.5-pro", "vertex_ai"),
+    ],
+)
+def test_pre_process_non_default_params(model, custom_llm_provider):
+    from pydantic import BaseModel
+
+    from litellm.utils import pre_process_non_default_params
+
+    class ResponseFormat(BaseModel):
+        x: str
+        y: str
+
+    passed_params = {
+        "model": "gpt-3.5-turbo",
+        "response_format": ResponseFormat,
+    }
+    special_params = {}
+    processed_non_default_params = pre_process_non_default_params(
+        model=model,
+        passed_params=passed_params,
+        special_params=special_params,
+        custom_llm_provider=custom_llm_provider,
+        additional_drop_params=None,
+    )
+    print(processed_non_default_params)
+    assert processed_non_default_params == {
+        "response_format": {
+            "type": "json_schema",
+            "json_schema": {
+                "schema": {
+                    "properties": {
+                        "x": {"title": "X", "type": "string"},
+                        "y": {"title": "Y", "type": "string"},
+                    },
+                    "required": ["x", "y"],
+                    "title": "ResponseFormat",
+                    "type": "object",
+                    "additionalProperties": False,
+                },
+                "name": "ResponseFormat",
+                "strict": True,
+            },
+        }
+    }
diff --git a/tests/llm_translation/test_optional_params.py b/tests/llm_translation/test_optional_params.py
index b29d20ba408..4ce18be8adb 100644
--- a/tests/llm_translation/test_optional_params.py
+++ b/tests/llm_translation/test_optional_params.py
@@ -460,6 +460,26 @@ def test_dynamic_drop_params_e2e():
         print(mock_response.call_args.kwargs["data"])
         assert "response_format" not in mock_response.call_args.kwargs["data"]
 
+def test_dynamic_pass_additional_params():
+    with patch(
+        "litellm.llms.custom_httpx.http_handler.HTTPHandler.post", new=MagicMock()
+    ) as mock_response:
+        try:
+            response = litellm.completion(
+                model="command-r",
+                messages=[{"role": "user", "content": "Hey, how's it going?"}],
+                custom_param="test",
+                api_key="my-custom-key",
+            )
+        except Exception as e:
+            print(f"Error occurred: {e}")
+            pass
+
+        mock_response.assert_called_once()
+        print(mock_response.call_args.kwargs["data"])
+        assert "custom_param" in mock_response.call_args.kwargs["data"]
+        assert "api_key" not in mock_response.call_args.kwargs["data"]
+
 
 @pytest.mark.parametrize(
     "model, provider, should_drop",
@@ -559,6 +579,7 @@ def test_dynamic_drop_additional_params_e2e():
                 additional_drop_params=["response_format"],
             )
         except Exception as e:
+            print(f"Error occurred: {e}")
             pass
 
         mock_response.assert_called_once()
diff --git a/tests/local_testing/test_ollama.py b/tests/local_testing/test_ollama.py
index 09c50315e05..2c4ceb3baf6 100644
--- a/tests/local_testing/test_ollama.py
+++ b/tests/local_testing/test_ollama.py
@@ -32,12 +32,14 @@ def test_get_ollama_params():
             temperature=0.5,
             stream=True,
         )
-        print("Converted params", converted_params)
-        assert converted_params == {
+        expected_params = {
             "num_predict": 20,
             "stream": True,
             "temperature": 0.5,
-        }, f"{converted_params} != {'num_predict': 20, 'stream': True, 'temperature': 0.5}"
+        }
+        print("Converted params", converted_params)
+        for key in expected_params.keys():
+            assert expected_params[key] == converted_params[key], f"{converted_params} != {expected_params}"
     except Exception as e:
         pytest.fail(f"Error occurred: {e}")
 
diff --git a/tests/logging_callback_tests/langfuse_expected_request_body/completion_with_router.json b/tests/logging_callback_tests/langfuse_expected_request_body/completion_with_router.json
new file mode 100644
index 00000000000..e5059d873a0
--- /dev/null
+++ b/tests/logging_callback_tests/langfuse_expected_request_body/completion_with_router.json
@@ -0,0 +1,87 @@
+{
+    "batch": [
+        {
+            "id": "45eb9b25-605c-4c4a-b2b3-8241e079cd31",
+            "type": "trace-create",
+            "body": {
+                "id": "litellm-test-32702f3d-8a1c-4912-a3d6-286e59a9c568",
+                "timestamp": "2025-05-24T17:01:19.408179Z",
+                "name": "litellm-acompletion",
+                "input": {
+                    "messages": [
+                        {
+                            "role": "user",
+                            "content": "Hello!"
+                        }
+                    ]
+                },
+                "tags": []
+            },
+            "timestamp": "2025-05-24T17:01:19.408284Z"
+        },
+        {
+            "id": "9f5e9b7d-0cea-4776-b4b9-5c2e8f4bad3c",
+            "type": "generation-create",
+            "body": {
+                "traceId": "litellm-test-32702f3d-8a1c-4912-a3d6-286e59a9c568",
+                "name": "litellm-acompletion",
+                "startTime": "2025-05-24T10:01:19.142356-07:00",
+                "metadata": {
+                    "model_group": "gpt-3.5-turbo",
+                    "model_group_size": 1,
+                    "deployment": "gpt-3.5-turbo",
+                    "model_info": {
+                        "id": "0f1cd8f9e6a22e499303d479486395563ea04decade83fe7334dc2f079a857c2",
+                        "db_model": false
+                    },
+                    "api_base": null,
+                    "hidden_params": {
+                        "model_id": "0f1cd8f9e6a22e499303d479486395563ea04decade83fe7334dc2f079a857c2",
+                        "cache_key": null,
+                        "api_base": "https://api.openai.com",
+                        "response_cost": 3.5e-05,
+                        "additional_headers": {},
+                        "litellm_overhead_time_ms": null,
+                        "batch_models": null,
+                        "litellm_model_name": "gpt-3.5-turbo",
+                        "usage_object": null
+                    },
+                    "litellm_response_cost": 3.5e-05,
+                    "cache_hit": false,
+                    "requester_metadata": {}
+                },
+                "input": {
+                    "messages": [
+                        {
+                            "role": "user",
+                            "content": "Hello!"
+                        }
+                    ]
+                },
+                "level": "DEFAULT",
+                "id": "time-10-01-19-142356_chatcmpl-16b215b7-e51e-47b0-8fe5-9dd6f226fda1",
+                "endTime": "2025-05-24T10:01:19.406531-07:00",
+                "completionStartTime": "2025-05-24T10:01:19.406531-07:00",
+                "model": "gpt-3.5-turbo",
+                "modelParameters": {
+                    "stream": false,
+                    "max_retries": 0
+                },
+                "usage": {
+                    "input": 10,
+                    "output": 10,
+                    "unit": "TOKENS",
+                    "totalCost": 3.5e-05
+                }
+            },
+            "timestamp": "2025-05-24T17:01:19.408586Z"
+        }
+    ],
+    "metadata": {
+        "batch_size": 2,
+        "sdk_integration": "litellm",
+        "sdk_name": "python",
+        "sdk_version": "2.44.1",
+        "public_key": "pk-lf-3bfc4db9-217f-48e9-92e0-142566e3c204"
+    }
+}
diff --git a/tests/logging_callback_tests/test_langfuse_e2e_test.py b/tests/logging_callback_tests/test_langfuse_e2e_test.py
index b46d8764dd7..12aa2f38bda 100644
--- a/tests/logging_callback_tests/test_langfuse_e2e_test.py
+++ b/tests/logging_callback_tests/test_langfuse_e2e_test.py
@@ -381,3 +381,42 @@ class TestLangfuseLogging:
             await self._verify_langfuse_call(
                 setup["mock_post"], "completion_with_no_choices.json", setup["trace_id"]
             )
+
+    @pytest.mark.asyncio
+    async def test_langfuse_logging_with_router(self, mock_setup):
+        """Test Langfuse logging with router"""
+        setup = await mock_setup  # Await the fixture
+        litellm._turn_on_debug()
+        router = litellm.Router(
+            model_list=[
+                {
+                    "model_name": "gpt-3.5-turbo",
+                    "litellm_params": {
+                        "model": "gpt-3.5-turbo",
+                        "mock_response": "Hello! How can I assist you today?",
+                        "api_key": "test_api_key",
+                    }
+                }
+            ]
+        )
+        with patch("httpx.Client.post", setup["mock_post"]):
+            mock_response = litellm.ModelResponse(
+                choices=[],
+                usage=litellm.Usage(
+                    prompt_tokens=10,
+                    completion_tokens=10,
+                    total_tokens=20,
+                ),
+                model="gpt-3.5-turbo",
+                object="chat.completion",
+                created=1723081200,
+            ).model_dump()
+            await router.acompletion(
+                model="gpt-3.5-turbo",
+                messages=[{"role": "user", "content": "Hello!"}],
+                mock_response=mock_response,
+                metadata={"trace_id": setup["trace_id"]},
+            )
+            await self._verify_langfuse_call(
+                setup["mock_post"], "completion_with_router.json", setup["trace_id"]
+            )
\ No newline at end of file