Update app.py

app.py

@@ -6,8 +6,7 @@ from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.runnables import RunnablePassthrough
 from langchain_groq import ChatGroq
 from langchain.embeddings.openai import OpenAIEmbeddings
-from langchain.chains import ConversationChain
-from langchain.memory import ConversationBufferWindowMemory
+
 
 
 
@@ -54,15 +53,7 @@ Answer:""",
     ]
 )
 
-# Conversation history memory
-memory = ConversationBufferWindowMemory(k=3)
 
-# Define the conversation chain
-conversation = ConversationChain(
-    llm=llm,
-    memory=memory,
-    verbose=True
-)
 
 def format_docs(docs):
     return "\n\n".join(doc.page_content for doc in docs)
@@ -76,38 +67,37 @@ rag_chain = (
 
 
 
-# Define the Gradio app
-def chatbot_response(messages, user_message):
-    # Update memory with the user's message
-    memory.chat_memory.add_user_message(user_message)
-
-    # Get the response from the conversation chain
-    response = conversation.run(input=user_message)
-
-    # Append the user's message and the response to the chat history
+# Function to handle chatbot interaction
+def rag_chain_response(messages, user_message):
+    # Generate a response using the RAG chain
+    response = rag_chain.invoke(user_message)
+    
+    # Append the user's message and the response to the chat
     messages.append((user_message, response))
-
-    # Return the updated messages and clear the input box
+    
+    # Return the updated chat and clear the input box
     return messages, ""
 
 
-with gr.Blocks(theme="rawrsor1/Everforest") as app:
-   
 
+# Define the Gradio app
+with gr.Blocks(theme="rawrsor1/Everforest") as app:
+    
+    
     chatbot = gr.Chatbot([], elem_id="RADAR", bubble_full_width=False)
     question_input = gr.Textbox(label="Ask a Question", placeholder="Type your question here...")
     submit_btn = gr.Button("Submit")
-
+    
     # Set up interaction for both Enter key and Submit button
     question_input.submit(
-        chatbot_response,
-        inputs=[chatbot, question_input],
-        outputs=[chatbot, question_input]
+        rag_chain_response,          # Function to handle input and generate response
+        inputs=[chatbot, question_input],  # Pass current conversation state and user input
+        outputs=[chatbot, question_input]  # Update conversation state and clear the input
     )
     submit_btn.click(
-        chatbot_response,
-        inputs=[chatbot, question_input],
-        outputs=[chatbot, question_input]
+        rag_chain_response,          # Function to handle input and generate response
+        inputs=[chatbot, question_input],  # Pass current conversation state and user input
+        outputs=[chatbot, question_input]  # Update conversation state and clear the input
     )
 
 # Launch the Gradio app