Update app.py

app.py

@@ -52,7 +52,7 @@ Recommendation:
 
 PROMPT = PromptTemplate(
     template=prompt_template,
-    input_variables=["chat_history", "question", "context"]
+    input_variables=["chat_history", "question"]
 )
 
 # Initialize the language model
@@ -119,11 +119,12 @@ if prompt := st.chat_input("What are you looking to learn?"):
         st.markdown(prompt)
 
     # Retrieve relevant context from the vector store based on user input
-    context = retriever.retrieve(prompt)
+    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, "context": context})
+        response = qa_chain({"question": prompt, "chat_history": st.session_state.messages, "context": context})
         response_text = response["answer"]
 
         # Simulate streaming response
@@ -139,4 +140,4 @@ 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()