📦 chore(ConversationChain.py): add ConversationChain component to handle conversations and load context from memory

📦 chore(LLMChain.py): add optional memory parameter to LLMChain build method to support loading context from memory

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

@@ -0,0 +1,24 @@
+from langflow import CustomComponent
+from langchain.chains import ConversationChain
+from typing import Optional, Union, Callable
+from langflow.field_typing import BaseLanguageModel, BaseMemory, Chain
+
+
+class ConversationChainComponent(CustomComponent):
+    display_name = "ConversationChain"
+    description = "Chain to have a conversation and load context from memory."
+
+    def build_config(self):
+        return {
+            "prompt": {"display_name": "Prompt"},
+            "llm": {"display_name": "LLM"},
+            "memory": {"display_name": "Memory"},
+            "code": {"show": False},
+        }
+
+    def build(
+        self,
+        llm: BaseLanguageModel,
+        memory: Optional[BaseMemory] = None,
+    ) -> Union[Chain, Callable]:
+        return ConversationChain(llm=llm, memory=memory)

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

@@ -13,12 +13,13 @@ class LLMChainComponent(CustomComponent):
             "prompt": {"display_name": "Prompt"},
             "llm": {"display_name": "LLM"},
             "memory": {"display_name": "Memory"},
+            "code": {"show": False},
         }
 
     def build(
         self,
         prompt: PromptTemplate,
         llm: BaseLanguageModel,
-        memory: Optional[BaseMemory],
+        memory: Optional[BaseMemory] = None,
     ) -> Union[Chain, Callable]:
         return LLMChain(prompt=prompt, llm=llm, memory=memory)