diff --git a/src/backend/base/langflow/components/nvidia/nvidia_rerank.py b/src/backend/base/langflow/components/nvidia/nvidia_rerank.py
index 4228fa3a8..746c1f1b7 100644
--- a/src/backend/base/langflow/components/nvidia/nvidia_rerank.py
+++ b/src/backend/base/langflow/components/nvidia/nvidia_rerank.py
@@ -1,19 +1,9 @@
-from typing import Any, cast
+from typing import Any
 
-from langchain.retrievers import ContextualCompressionRetriever
-
-from langflow.base.vectorstores.model import (
-    LCVectorStoreComponent,
-    check_cached_vector_store,
-)
-from langflow.field_typing import Retriever, VectorStore
-from langflow.io import (
-    DropdownInput,
-    HandleInput,
-    MultilineInput,
-    SecretStrInput,
-    StrInput,
-)
+from langflow.base.vectorstores.model import LCVectorStoreComponent, check_cached_vector_store
+from langflow.field_typing import VectorStore
+from langflow.inputs.inputs import DataInput
+from langflow.io import DropdownInput, MultilineInput, SecretStrInput, StrInput
 from langflow.schema import Data
 from langflow.schema.dotdict import dotdict
 from langflow.template.field.base import Output
@@ -23,12 +13,12 @@ class NvidiaRerankComponent(LCVectorStoreComponent):
     display_name = "NVIDIA Rerank"
     description = "Rerank documents using the NVIDIA API and a retriever."
     icon = "NVIDIA"
-    legacy: bool = True
 
     inputs = [
         MultilineInput(
             name="search_query",
             display_name="Search Query",
+            tool_mode=True,
         ),
         StrInput(
             name="base_url",
@@ -44,19 +34,19 @@ class NvidiaRerankComponent(LCVectorStoreComponent):
             value="nv-rerank-qa-mistral-4b:1",
         ),
         SecretStrInput(name="api_key", display_name="API Key"),
-        HandleInput(name="retriever", display_name="Retriever", input_types=["Retriever"]),
+        DataInput(
+            name="search_results",
+            display_name="Search Results",
+            info="Search Results from a Vector Store.",
+            is_list=True,
+        ),
     ]
 
     outputs = [
         Output(
-            display_name="Retriever",
-            name="base_retriever",
-            method="build_base_retriever",
-        ),
-        Output(
-            display_name="Search Results",
-            name="search_results",
-            method="search_documents",
+            display_name="Reranked Documents",
+            name="reranked_documents",
+            method="rerank_documents",
         ),
     ]
 
@@ -72,7 +62,7 @@ class NvidiaRerankComponent(LCVectorStoreComponent):
                 raise ValueError(msg) from e
         return build_config
 
-    def build_model(self):
+    def build_reranker(self):
         try:
             from langchain_nvidia_ai_endpoints import NVIDIARerank
         except ImportError as e:
@@ -80,14 +70,12 @@ class NvidiaRerankComponent(LCVectorStoreComponent):
             raise ImportError(msg) from e
         return NVIDIARerank(api_key=self.api_key, model=self.model, base_url=self.base_url)
 
-    def build_base_retriever(self) -> Retriever:  # type: ignore[type-var]
-        nvidia_reranker = self.build_model()
-        retriever = ContextualCompressionRetriever(base_compressor=nvidia_reranker, base_retriever=self.retriever)
-        return cast("Retriever", retriever)
-
-    async def search_documents(self) -> list[Data]:  # type: ignore[override]
-        retriever = self.build_base_retriever()
-        documents = await retriever.ainvoke(self.search_query, config={"callbacks": self.get_langchain_callbacks()})
+    async def rerank_documents(self) -> list[Data]:  # type: ignore[override]
+        reranker = self.build_reranker()
+        documents = reranker.compress_documents(
+            query=self.search_query,
+            documents=[passage.to_lc_document() for passage in self.search_results if isinstance(passage, Data)],
+        )
         data = self.to_data(documents)
         self.status = data
         return data