Refactor ConversationChainComponent to handle inputs and return result as string if applicable

src/backend/langflow/components/chains/ConversationChain.py

@@ -1,7 +1,9 @@
-from langflow import CustomComponent
+from typing import Callable, Optional, Union
+
 from langchain.chains import ConversationChain
-from typing import Optional, Union, Callable
-from langflow.field_typing import BaseLanguageModel, BaseMemory, Chain
+
+from langflow import CustomComponent
+from langflow.field_typing import BaseLanguageModel, BaseMemory, Chain, Text
 
 
 class ConversationChainComponent(CustomComponent):
@@ -23,7 +25,17 @@ class ConversationChainComponent(CustomComponent):
         self,
         llm: BaseLanguageModel,
         memory: Optional[BaseMemory] = None,
-    ) -> Union[Chain, Callable]:
+        inputs: dict = {},
+    ) -> Union[Chain, Callable, Text]:
         if memory is None:
-            return ConversationChain(llm=llm)
-        return ConversationChain(llm=llm, memory=memory)
+            chain = ConversationChain(llm=llm)
+        chain = ConversationChain(llm=llm, memory=memory)
+        result = chain.invoke(inputs)
+        # result is an AIMessage which is a subclass of BaseMessage
+        # We need to check if it is a string or a BaseMessage
+        if hasattr(result, "content") and isinstance(result.content, str):
+            return result.content
+        elif isinstance(result, str):
+            return result
+
+        return str(result)