revert

libs/langchain/langchain/chains/base.py

@@ -63,10 +63,13 @@ class Chain(Serializable, Runnable[Dict[str, Any], Dict[str, Any]], ABC):
         **kwargs: Any,
     ) -> Dict[str, Any]:
         config = config or {}
-        config_kwargs: Dict = {
-            k: config.get(k) for k in ("callbacks", "tags", "metadata")
-        }
-        return self(input, **config_kwargs, **kwargs)
+        return self(
+            input,
+            callbacks=config.get("callbacks"),
+            tags=config.get("tags"),
+            metadata=config.get("metadata"),
+            **kwargs,
+        )
 
     async def ainvoke(
         self,
@@ -79,11 +82,15 @@ class Chain(Serializable, Runnable[Dict[str, Any], Dict[str, Any]], ABC):
             return await asyncio.get_running_loop().run_in_executor(
                 None, partial(self.invoke, input, config, **kwargs)
             )
+
         config = config or {}
-        config_kwargs: Dict = {
-            k: config.get(k) for k in ("callbacks", "tags", "metadata")
-        }
-        return await self.acall(input, **config_kwargs, **kwargs)
+        return await self.acall(
+            input,
+            callbacks=config.get("callbacks"),
+            tags=config.get("tags"),
+            metadata=config.get("metadata"),
+            **kwargs,
+        )
 
     memory: Optional[BaseMemory] = None
     """Optional memory object. Defaults to None.

libs/langchain/langchain/chat_models/base.py

@@ -105,15 +105,17 @@ class BaseChatModel(BaseLanguageModel[BaseMessageChunk], ABC):
         **kwargs: Any,
     ) -> BaseMessageChunk:
         config = config or {}
-        config_kwargs: Dict = {
-            k: config.get(k) for k in ("callbacks", "tags", "metadata")
-        }
         return cast(
             BaseMessageChunk,
             cast(
                 ChatGeneration,
                 self.generate_prompt(
-                    [self._convert_input(input)], stop=stop, **config_kwargs, **kwargs
+                    [self._convert_input(input)],
+                    stop=stop,
+                    callbacks=config.get("callbacks"),
+                    tags=config.get("tags"),
+                    metadata=config.get("metadata"),
+                    **kwargs,
                 ).generations[0][0],
             ).message,
         )
@@ -133,11 +135,13 @@ class BaseChatModel(BaseLanguageModel[BaseMessageChunk], ABC):
             )
 
         config = config or {}
-        config_kwargs: Dict = {
-            k: config.get(k) for k in ("callbacks", "tags", "metadata")
-        }
         llm_result = await self.agenerate_prompt(
-            [self._convert_input(input)], stop=stop, **config_kwargs, **kwargs
+            [self._convert_input(input)],
+            stop=stop,
+            callbacks=config.get("callbacks"),
+            tags=config.get("tags"),
+            metadata=config.get("metadata"),
+            **kwargs,
         )
         return cast(
             BaseMessageChunk, cast(ChatGeneration, llm_result.generations[0][0]).message

libs/langchain/langchain/llms/base.py

@@ -220,13 +220,18 @@ class BaseLLM(BaseLanguageModel[str], ABC):
         **kwargs: Any,
     ) -> str:
         config = config or {}
-        config_kwargs: Dict = {
-            k: config.get(k) for k in ("callbacks", "tags", "metadata")
-        }
-        result = self.generate_prompt(
-            [self._convert_input(input)], stop=stop, **config_kwargs, **kwargs
+        return (
+            self.generate_prompt(
+                [self._convert_input(input)],
+                stop=stop,
+                callbacks=config.get("callbacks"),
+                tags=config.get("tags"),
+                metadata=config.get("metadata"),
+                **kwargs,
+            )
+            .generations[0][0]
+            .text
         )
-        return result.generations[0][0].text
 
     async def ainvoke(
         self,
@@ -243,11 +248,13 @@ class BaseLLM(BaseLanguageModel[str], ABC):
             )
 
         config = config or {}
-        config_kwargs: Dict = {
-            k: config.get(k) for k in ("callbacks", "tags", "metadata")
-        }
         llm_result = await self.agenerate_prompt(
-            [self._convert_input(input)], stop=stop, **config_kwargs, **kwargs
+            [self._convert_input(input)],
+            stop=stop,
+            callbacks=config.get("callbacks"),
+            tags=config.get("tags"),
+            metadata=config.get("metadata"),
+            **kwargs,
         )
         return llm_result.generations[0][0].text
 

libs/langchain/langchain/schema/retriever.py

@@ -108,10 +108,12 @@ class BaseRetriever(Serializable, Runnable[str, List[Document]], ABC):
         self, input: str, config: Optional[RunnableConfig] = None
     ) -> List[Document]:
         config = config or {}
-        config_kwargs: Dict = {
-            k: config.get(k) for k in ("callbacks", "tags", "metadata")
-        }
-        return self.get_relevant_documents(input, **config_kwargs)
+        return self.get_relevant_documents(
+            input,
+            callbacks=config.get("callbacks"),
+            tags=config.get("tags"),
+            metadata=config.get("metadata"),
+        )
 
     async def ainvoke(
         self,
@@ -124,10 +126,12 @@ class BaseRetriever(Serializable, Runnable[str, List[Document]], ABC):
             return await super().ainvoke(input, config)
 
         config = config or {}
-        config_kwargs: Dict = {
-            k: config.get(k) for k in ("callbacks", "tags", "metadata")
-        }
-        return await self.aget_relevant_documents(input, **config_kwargs)
+        return await self.aget_relevant_documents(
+            input,
+            callbacks=config.get("callbacks"),
+            tags=config.get("tags"),
+            metadata=config.get("metadata"),
+        )
 
     @abstractmethod
     def _get_relevant_documents(