Update app.py

app.py

@@ -52,7 +52,7 @@ Recommendation:
 
 PROMPT = PromptTemplate(
     template=prompt_template,
-    input_variables=["chat_history", "question"]
+    input_variables=["chat_history", "question", "context"]
 )
 
 # Initialize the language model
@@ -118,20 +118,14 @@ if prompt := st.chat_input("What are you looking to learn?"):
     with st.chat_message("user"):
         st.markdown(prompt)
 
-    # Retrieve relevant context from the vector store based on user input
-    context_documents = retriever.retrieve(prompt)
-    context = " ".join([doc.page_content for doc in context_documents])  # Combine the content of the retrieved documents
-
     # Assistant response generator with streaming effect
     with st.chat_message("assistant"):
-        response = qa_chain({"question": prompt, "chat_history": st.session_state.messages, "context": context})
+        response = qa_chain({"question": prompt})
         response_text = response["answer"]
-
+        
         # Simulate streaming response
-        full_response = ""
         for word in response_text.split():
-            full_response += word + " "
-            st.markdown(full_response.strip(), unsafe_allow_html=True)  # Display the accumulated response
+            st.markdown(word + " ", unsafe_allow_html=True)
             time.sleep(0.05)  # Delay for effect
 
     # Add assistant response to chat history
@@ -140,4 +134,4 @@ if prompt := st.chat_input("What are you looking to learn?"):
 # Optional: Add a button to clear the chat history
 if st.button("Clear Chat History"):
     st.session_state.messages.clear()
-    st.experimental_rerun()
+    st.experimental_rerun()