feat - add param mapping for nvidia nim

litellm/llms/nvidia_nim.py

@@ -0,0 +1,79 @@
+"""
+Nvidia NIM endpoint: https://docs.api.nvidia.com/nim/reference/databricks-dbrx-instruct-infer 
+
+This is OpenAI compatible 
+
+This file only contains param mapping logic
+
+API calling is done using the OpenAI SDK with an api_base
+"""
+
+import types
+from typing import Optional, Union
+
+
+class NvidiaNimConfig:
+    """
+    Reference: https://docs.api.nvidia.com/nim/reference/databricks-dbrx-instruct-infer
+
+    The class `NvidiaNimConfig` provides configuration for the Nvidia NIM's Chat Completions API interface. Below are the parameters:
+    """
+
+    temperature: Optional[int] = None
+    top_p: Optional[int] = None
+    frequency_penalty: Optional[int] = None
+    presence_penalty: Optional[int] = None
+    max_tokens: Optional[int] = None
+    stop: Optional[Union[str, list]] = None
+
+    def __init__(
+        self,
+        temperature: Optional[int] = None,
+        top_p: Optional[int] = None,
+        frequency_penalty: Optional[int] = None,
+        presence_penalty: Optional[int] = None,
+        max_tokens: Optional[int] = None,
+        stop: Optional[Union[str, list]] = None,
+    ) -> None:
+        locals_ = locals().copy()
+        for key, value in locals_.items():
+            if key != "self" and value is not None:
+                setattr(self.__class__, key, value)
+
+    @classmethod
+    def get_config(cls):
+        return {
+            k: v
+            for k, v in cls.__dict__.items()
+            if not k.startswith("__")
+            and not isinstance(
+                v,
+                (
+                    types.FunctionType,
+                    types.BuiltinFunctionType,
+                    classmethod,
+                    staticmethod,
+                ),
+            )
+            and v is not None
+        }
+
+    def get_supported_openai_params(self):
+        return [
+            "stream",
+            "temperature",
+            "top_p",
+            "frequency_penalty",
+            "presence_penalty",
+            "max_tokens",
+            "stop",
+        ]
+
+    def map_openai_params(
+        self, non_default_params: dict, optional_params: dict
+    ) -> dict:
+        supported_openai_params = self.get_supported_openai_params()
+        for param, value in non_default_params.items():
+            if param in supported_openai_params:
+                optional_params[param] = value
+        return optional_params