LLMService docs function returns

morpheus/llm/services/llm_service.py

@@ -30,6 +30,11 @@ class LLMClient(ABC):
     def get_input_names(self) -> list[str]:
         """
         Returns the names of the inputs to the model.
+
+        Returns
+        -------
+        list[str]
+            List of input names.
         """
         pass
 
@@ -42,6 +47,11 @@ def generate(self, **input_dict) -> str:
         ----------
         input_dict : dict
             Input containing prompt data.
+
+        Returns
+        -------
+        str
+            Generated response for prompt.
         """
         pass
 
@@ -54,6 +64,11 @@ async def generate_async(self, **input_dict) -> str:
         ----------
         input_dict : dict
             Input containing prompt data.
+
+        Returns
+        -------
+        str
+            Generated async response for prompt.
         """
         pass
 
@@ -80,6 +95,11 @@ def generate_batch(self, inputs: dict[str, list], return_exceptions=False) -> li
             Inputs containing prompt data.
         return_exceptions : bool
             Whether to return exceptions in the output list or raise them immediately.
+
+        Returns
+        -------
+        list[str] | list[str | BaseException]
+            List of responses or list of responses and exceptions.
         """
         pass
 
@@ -110,6 +130,11 @@ async def generate_batch_async(self,
             Inputs containing prompt data.
         return_exceptions : bool
             Whether to return exceptions in the output list or raise them immediately.
+
+        Returns
+        -------
+        list[str] | list[str | BaseException]
+            List of responses or list of responses and exceptions.
         """
         pass
 
@@ -131,5 +156,10 @@ def get_client(self, *, model_name: str, **model_kwargs) -> LLMClient:
 
         model_kwargs : dict[str, typing.Any]
             Additional keyword arguments to pass to the model.
+
+        Returns
+        -------
+        LLMClient
+            Client for interacting with LLM models.
         """
         pass