msg

controller.py

@@ -86,7 +86,7 @@ class Controller:
         Returns:
         - str: The response from the conversation chain.
         """
-        agent_chat_bot = ConversationChainSingleton().get_conversation_chain()
+        agent_chat_bot = ConversationChainSingleton().conversation_chain("tmp")
         print(agent_chat_bot)
         print("------------ msg -----------------------")
         print(user_message + " ---- " )

model/conversation_chain_singleton.py

@@ -17,6 +17,26 @@ from langchain.chains import ConversationChain
 from langchain.llms import HuggingFaceHub
 
 class ConversationChainSingleton:
+    def __init__(self) -> None:
+        pass
+    def conversation_chain(self, text):
+        """
+        Create a conversational retrieval chain and a language model.
+
+        Returns:
+        - ConversationChain: The initialized conversation chain.
+        """
+        print(text)
+        llm = HuggingFaceHub(
+            repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
+            model_kwargs={"max_length": 1048, "temperature": 0.2, "max_new_tokens": 256, "top_p": 0.95, "repetition_penalty": 1.0},
+        )
+        memory = ConversationBufferMemory(memory_key="history", return_messages=True)
+        conversation_chain = ConversationChain(
+            llm=llm, verbose=True, memory=memory
+        )
+        return conversation_chain
+    
     """
     A singleton class for managing a conversation chain instance.
 
@@ -30,7 +50,7 @@ class ConversationChainSingleton:
 
     
     - get_conversation_chain(): Creates and returns a conversational retrieval chain and a language model.
-    """
+   
 
     _instance = None
 
@@ -38,24 +58,7 @@ class ConversationChainSingleton:
         if not cls._instance:
             cls._instance = super(ConversationChainSingleton, cls).__new__(cls)
             # Initialize your conversation chain here
-            cls._instance.conversation_chain = cls.get_conversation_chain()
+            cls._instance.conversation_chain = cls.get_conversation_chain(cls._instance)
         return cls._instance
-
+ """
  
-    def get_conversation_chain():
-        """
-        Create a conversational retrieval chain and a language model.
-
-        Returns:
-        - ConversationChain: The initialized conversation chain.
-        """
-        llm = HuggingFaceHub(
-            repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1",
-            model_kwargs={"max_length": 1048, "temperature": 0.2, "max_new_tokens": 256, "top_p": 0.95, "repetition_penalty": 1.0},
-        )
-        memory = ConversationBufferMemory(memory_key="history", return_messages=True)
-        conversation_chain = ConversationChain(
-            llm=llm, verbose=True, memory=memory
-        )
-        return conversation_chain
-