feat: ctransformers support async chain (#6859)

- Description: Adding async method for CTransformers 
- Issue: I've found impossible without this code to run Websockets
inside a FastAPI micro service and a CTransformers model.
  - Tag maintainer: Not necessary yet, I don't like to mention directly 
  - Twitter handle: @_semoal

langchain/llms/ctransformers.py

@@ -1,9 +1,13 @@
 """Wrapper around the C Transformers library."""
-from typing import Any, Dict, Optional, Sequence
+from functools import partial
+from typing import Any, Dict, List, Optional, Sequence
 
 from pydantic import root_validator
 
-from langchain.callbacks.manager import CallbackManagerForLLMRun
+from langchain.callbacks.manager import (
+    AsyncCallbackManagerForLLMRun,
+    CallbackManagerForLLMRun,
+)
 from langchain.llms.base import LLM
 
 
@@ -103,3 +107,36 @@ class CTransformers(LLM):
             text.append(chunk)
             _run_manager.on_llm_new_token(chunk, verbose=self.verbose)
         return "".join(text)
+
+    async def _acall(
+        self,
+        prompt: str,
+        stop: Optional[List[str]] = None,
+        run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
+        **kwargs: Any,
+    ) -> str:
+        """Asynchronous Call out to CTransformers generate method.
+        Very helpful when streaming (like with websockets!)
+
+        Args:
+            prompt: The prompt to pass into the model.
+            stop: A list of strings to stop generation when encountered.
+
+        Returns:
+            The string generated by the model.
+
+        Example:
+            .. code-block:: python
+                response = llm("Once upon a time, ")
+        """
+        text_callback = None
+        if run_manager:
+            text_callback = partial(run_manager.on_llm_new_token, verbose=self.verbose)
+
+        text = ""
+        for token in self.client(prompt, stop=stop, stream=True):
+            if text_callback:
+                await text_callback(token)
+            text += token
+
+        return text

tests/integration_tests/llms/test_ctransformers.py

@@ -1,4 +1,5 @@
 """Test C Transformers wrapper."""
+import pytest
 
 from langchain.llms import CTransformers
 from tests.unit_tests.callbacks.fake_callback_handler import FakeCallbackHandler
@@ -19,3 +20,20 @@ def test_ctransformers_call() -> None:
     assert isinstance(output, str)
     assert len(output) > 1
     assert 0 < callback_handler.llm_streams <= config["max_new_tokens"]
+
+
+@pytest.mark.asyncio
+async def test_ctransformers_async_inference() -> None:
+    config = {"max_new_tokens": 5}
+    callback_handler = FakeCallbackHandler()
+
+    llm = CTransformers(
+        model="marella/gpt-2-ggml",
+        config=config,
+        callbacks=[callback_handler],
+    )
+
+    output = await llm._acall(prompt="Say foo:")
+    assert isinstance(output, str)
+    assert len(output) > 1
+    assert 0 < callback_handler.llm_streams <= config["max_new_tokens"]