community: minor changes sambanova integration (#21231)

- **Description:** fix: variable names in root validator not allowing
pass credentials as named parameters in llm instancing, also added
sambanova's sambaverse and sambastudio llms to __init__.py for module
import

libs/community/langchain_community/llms/__init__.py

@@ -510,6 +510,18 @@ def _import_sagemaker_endpoint() -> Type[BaseLLM]:
     return SagemakerEndpoint
 
 
+def _import_sambaverse() -> Type[BaseLLM]:
+    from langchain_community.llms.sambanova import Sambaverse
+
+    return Sambaverse
+
+
+def _import_sambastudio() -> Type[BaseLLM]:
+    from langchain_community.llms.sambanova import SambaStudio
+
+    return SambaStudio
+
+
 def _import_self_hosted() -> Type[BaseLLM]:
     from langchain_community.llms.self_hosted import SelfHostedPipeline
 
@@ -793,6 +805,10 @@ def __getattr__(name: str) -> Any:
         return _import_rwkv()
     elif name == "SagemakerEndpoint":
         return _import_sagemaker_endpoint()
+    elif name == "Sambaverse":
+        return _import_sambaverse()
+    elif name == "SambaStudio":
+        return _import_sambastudio()
     elif name == "SelfHostedPipeline":
         return _import_self_hosted()
     elif name == "SelfHostedHuggingFaceLLM":
@@ -922,6 +938,8 @@ __all__ = [
     "RWKV",
     "Replicate",
     "SagemakerEndpoint",
+    "Sambaverse",
+    "SambaStudio",
     "SelfHostedHuggingFaceLLM",
     "SelfHostedPipeline",
     "SparkLLM",
@@ -1015,6 +1033,8 @@ def get_type_to_cls_dict() -> Dict[str, Callable[[], Type[BaseLLM]]]:
         "replicate": _import_replicate,
         "rwkv": _import_rwkv,
         "sagemaker_endpoint": _import_sagemaker_endpoint,
+        "sambaverse": _import_sambaverse,
+        "sambastudio": _import_sambastudio,
         "self_hosted": _import_self_hosted,
         "self_hosted_hugging_face": _import_self_hosted_hugging_face,
         "stochasticai": _import_stochasticai,

libs/community/langchain_community/llms/sambanova.py

@@ -618,10 +618,10 @@ class SambaStudio(LLM):
 
         from langchain_community.llms.sambanova  import Sambaverse
         SambaStudio(
-            base_url="your SambaStudio environment URL",
+            sambastudio_base_url="your SambaStudio environment URL",
-            project_id=set with your SambaStudio project ID.,
+            sambastudio_project_id=set with your SambaStudio project ID.,
-            endpoint_id=set with your SambaStudio endpoint ID.,
+            sambastudio_endpoint_id=set with your SambaStudio endpoint ID.,
-            api_token= set with your SambaStudio endpoint API key.,
+            sambastudio_api_key= set with your SambaStudio endpoint API key.,
             streaming=false
             model_kwargs={
                 "do_sample": False,
@@ -634,16 +634,16 @@ class SambaStudio(LLM):
         )
     """
 
-    base_url: str = ""
+    sambastudio_base_url: str = ""
     """Base url to use"""
 
-    project_id: str = ""
+    sambastudio_project_id: str = ""
     """Project id on sambastudio for model"""
 
-    endpoint_id: str = ""
+    sambastudio_endpoint_id: str = ""
     """endpoint id on sambastudio for model"""
 
-    api_key: str = ""
+    sambastudio_api_key: str = ""
     """sambastudio api key"""
 
     model_kwargs: Optional[dict] = None
@@ -674,16 +674,16 @@ class SambaStudio(LLM):
     @root_validator()
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
-        values["base_url"] = get_from_dict_or_env(
+        values["sambastudio_base_url"] = get_from_dict_or_env(
             values, "sambastudio_base_url", "SAMBASTUDIO_BASE_URL"
         )
-        values["project_id"] = get_from_dict_or_env(
+        values["sambastudio_project_id"] = get_from_dict_or_env(
             values, "sambastudio_project_id", "SAMBASTUDIO_PROJECT_ID"
         )
-        values["endpoint_id"] = get_from_dict_or_env(
+        values["sambastudio_endpoint_id"] = get_from_dict_or_env(
             values, "sambastudio_endpoint_id", "SAMBASTUDIO_ENDPOINT_ID"
         )
-        values["api_key"] = get_from_dict_or_env(
+        values["sambastudio_api_key"] = get_from_dict_or_env(
             values, "sambastudio_api_key", "SAMBASTUDIO_API_KEY"
         )
         return values
@@ -729,7 +729,11 @@ class SambaStudio(LLM):
             ValueError: If the prediction fails.
         """
         response = sdk.nlp_predict(
-            self.project_id, self.endpoint_id, self.api_key, prompt, tuning_params
+            self.sambastudio_project_id,
+            self.sambastudio_endpoint_id,
+            self.sambastudio_api_key,
+            prompt,
+            tuning_params,
         )
         if response["status_code"] != 200:
             optional_detail = response["detail"]
@@ -755,7 +759,7 @@ class SambaStudio(LLM):
         Raises:
             ValueError: If the prediction fails.
         """
-        ss_endpoint = SSEndpointHandler(self.base_url)
+        ss_endpoint = SSEndpointHandler(self.sambastudio_base_url)
         tuning_params = self._get_tuning_params(stop)
         return self._handle_nlp_predict(ss_endpoint, prompt, tuning_params)
 
@@ -774,7 +778,11 @@ class SambaStudio(LLM):
             An iterator of GenerationChunks.
         """
         for chunk in sdk.nlp_predict_stream(
-            self.project_id, self.endpoint_id, self.api_key, prompt, tuning_params
+            self.sambastudio_project_id,
+            self.sambastudio_endpoint_id,
+            self.sambastudio_api_key,
+            prompt,
+            tuning_params,
         ):
             yield chunk
 
@@ -794,7 +802,7 @@ class SambaStudio(LLM):
         Returns:
             The string generated by the model.
         """
-        ss_endpoint = SSEndpointHandler(self.base_url)
+        ss_endpoint = SSEndpointHandler(self.sambastudio_base_url)
         tuning_params = self._get_tuning_params(stop)
         try:
             if self.streaming:

libs/community/tests/unit_tests/llms/test_imports.py

@@ -77,6 +77,8 @@ EXPECT_ALL = [
     "RWKV",
     "Replicate",
     "SagemakerEndpoint",
+    "Sambaverse",
+    "SambaStudio",
     "SelfHostedHuggingFaceLLM",
     "SelfHostedPipeline",
     "StochasticAI",