feature: implement _acall method for GPT4All(LLM)

libs/community/langchain_community/llms/gpt4all.py

@@ -1,7 +1,10 @@
 from functools import partial
 from typing import Any, Dict, List, Mapping, Optional, Set
 
-from langchain_core.callbacks import CallbackManagerForLLMRun
+from langchain_core.callbacks import (
+    AsyncCallbackManagerForLLMRun,
+    CallbackManagerForLLMRun,
+)
 from langchain_core.language_models.llms import LLM
 from langchain_core.pydantic_v1 import Extra, Field, root_validator
 
@@ -211,3 +214,40 @@ def _call(
         if stop is not None:
             text = enforce_stop_tokens(text, stop)
         return text
+
+    async def _acall(
+        self,
+        prompt: str,
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> str:
+        """Asynchronous Call out to GPT4All's generate method.
+
+        Args:
+            prompt: The prompt to pass into the model.
+            stop: A list of strings to stop generation when encountered.
+            run_manager: an async callback manager
+        Returns:
+            The string generated by the model.
+
+        Example:
+            .. code-block:: python
+
+                prompt = "Once upon a time, "
+                response = model(prompt, n_predict=55)
+        """
+        text_callback = None
+        if run_manager:
+            text_callback = partial(run_manager.on_llm_new_token, verbose=self.verbose)
+
+        params = {**self._default_params(), **kwargs}
+
+        text = ""
+        for token in self.client.generate(prompt, **params):
+            if text_callback:
+                await text_callback(token)
+            text += token
+        if stop is not None:
+            text = enforce_stop_tokens(text, stop)
+        return text