diff --git a/langchain/base_language.py b/langchain/base_language.py
index cebf2ffa..1b5bd084 100644
--- a/langchain/base_language.py
+++ b/langchain/base_language.py
@@ -58,6 +58,16 @@ class BaseLanguageModel(BaseModel, ABC):
     ) -> BaseMessage:
         """Predict message from messages."""
 
+    @abstractmethod
+    async def apredict(self, text: str, *, stop: Optional[Sequence[str]] = None) -> str:
+        """Predict text from text."""
+
+    @abstractmethod
+    async def apredict_messages(
+        self, messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None
+    ) -> BaseMessage:
+        """Predict message from messages."""
+
     def get_token_ids(self, text: str) -> List[int]:
         """Get the token present in the text."""
         return _get_token_ids_default_method(text)
diff --git a/langchain/chat_models/base.py b/langchain/chat_models/base.py
index 806c1574..de2cdd06 100644
--- a/langchain/chat_models/base.py
+++ b/langchain/chat_models/base.py
@@ -183,6 +183,19 @@ class BaseChatModel(BaseLanguageModel, ABC):
         else:
             raise ValueError("Unexpected generation type")
 
+    async def _call_async(
+        self,
+        messages: List[BaseMessage],
+        stop: Optional[List[str]] = None,
+        callbacks: Callbacks = None,
+    ) -> BaseMessage:
+        result = await self.agenerate([messages], stop=stop, callbacks=callbacks)
+        generation = result.generations[0][0]
+        if isinstance(generation, ChatGeneration):
+            return generation.message
+        else:
+            raise ValueError("Unexpected generation type")
+
     def call_as_llm(self, message: str, stop: Optional[List[str]] = None) -> str:
         return self.predict(message, stop=stop)
 
@@ -203,6 +216,23 @@ class BaseChatModel(BaseLanguageModel, ABC):
             _stop = list(stop)
         return self(messages, stop=_stop)
 
+    async def apredict(self, text: str, *, stop: Optional[Sequence[str]] = None) -> str:
+        if stop is None:
+            _stop = None
+        else:
+            _stop = list(stop)
+        result = await self._call_async([HumanMessage(content=text)], stop=_stop)
+        return result.content
+
+    async def apredict_messages(
+        self, messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None
+    ) -> BaseMessage:
+        if stop is None:
+            _stop = None
+        else:
+            _stop = list(stop)
+        return await self._call_async(messages, stop=_stop)
+
     @property
     def _identifying_params(self) -> Mapping[str, Any]:
         """Get the identifying parameters."""
diff --git a/langchain/llms/base.py b/langchain/llms/base.py
index 2e92c15d..21267a96 100644
--- a/langchain/llms/base.py
+++ b/langchain/llms/base.py
@@ -299,6 +299,13 @@ class BaseLLM(BaseLanguageModel, ABC):
             .text
         )
 
+    async def _call_async(
+        self, prompt: str, stop: Optional[List[str]] = None, callbacks: Callbacks = None
+    ) -> str:
+        """Check Cache and run the LLM on the given prompt and input."""
+        result = await self.agenerate([prompt], stop=stop, callbacks=callbacks)
+        return result.generations[0][0].text
+
     def predict(self, text: str, *, stop: Optional[Sequence[str]] = None) -> str:
         if stop is None:
             _stop = None
@@ -317,6 +324,24 @@ class BaseLLM(BaseLanguageModel, ABC):
         content = self(text, stop=_stop)
         return AIMessage(content=content)
 
+    async def apredict(self, text: str, *, stop: Optional[Sequence[str]] = None) -> str:
+        if stop is None:
+            _stop = None
+        else:
+            _stop = list(stop)
+        return await self._call_async(text, stop=_stop)
+
+    async def apredict_messages(
+        self, messages: List[BaseMessage], *, stop: Optional[Sequence[str]] = None
+    ) -> BaseMessage:
+        text = get_buffer_string(messages)
+        if stop is None:
+            _stop = None
+        else:
+            _stop = list(stop)
+        content = await self._call_async(text, stop=_stop)
+        return AIMessage(content=content)
+
     @property
     def _identifying_params(self) -> Mapping[str, Any]:
         """Get the identifying parameters."""