diff --git a/libs/community/langchain_community/chat_models/sambanova.py b/libs/community/langchain_community/chat_models/sambanova.py
index cd95f4beefa5f..62bc366486805 100644
--- a/libs/community/langchain_community/chat_models/sambanova.py
+++ b/libs/community/langchain_community/chat_models/sambanova.py
@@ -174,10 +174,10 @@ class ChatSambaNovaCloud(BaseChatModel):
     temperature: float = Field(default=0.7)
     """model temperature"""
 
-    top_p: Optional[float] = Field()
+    top_p: Optional[float] = Field(default=None)
     """model top p"""
 
-    top_k: Optional[int] = Field()
+    top_k: Optional[int] = Field(default=None)
     """model top k"""
 
     stream_options: dict = Field(default={"include_usage": True})
@@ -593,7 +593,7 @@ class ChatSambaStudio(BaseChatModel):
     streaming_url: str = Field(default="", exclude=True)
     """SambaStudio streaming Url"""
 
-    model: Optional[str] = Field()
+    model: Optional[str] = Field(default=None)
     """The name of the model or expert to use (for CoE endpoints)"""
 
     streaming: bool = Field(default=False)
@@ -605,16 +605,16 @@ class ChatSambaStudio(BaseChatModel):
     temperature: Optional[float] = Field(default=0.7)
     """model temperature"""
 
-    top_p: Optional[float] = Field()
+    top_p: Optional[float] = Field(default=None)
     """model top p"""
 
-    top_k: Optional[int] = Field()
+    top_k: Optional[int] = Field(default=None)
     """model top k"""
 
-    do_sample: Optional[bool] = Field()
+    do_sample: Optional[bool] = Field(default=None)
     """whether to do sampling"""
 
-    process_prompt: Optional[bool] = Field()
+    process_prompt: Optional[bool] = Field(default=True)
     """whether process prompt (for CoE generic v1 and v2 endpoints)"""
 
     stream_options: dict = Field(default={"include_usage": True})
@@ -1012,6 +1012,16 @@ def _process_stream_response(
                                 "system_fingerprint": data["system_fingerprint"],
                                 "created": data["created"],
                             }
+                        if data.get("usage") is not None:
+                            content = ""
+                            id = data["id"]
+                            metadata = {
+                                "finish_reason": finish_reason,
+                                "usage": data.get("usage"),
+                                "model_name": data["model"],
+                                "system_fingerprint": data["system_fingerprint"],
+                                "created": data["created"],
+                            }
                         yield AIMessageChunk(
                             content=content,
                             id=id,