Update app.py

app.py

@@ -150,6 +150,10 @@ class DocumentRAG:
         except Exception as e:
             return history + [("System", f"Error: {str(e)}")]
 
+# Initialize RAG system in session state
+if "rag_system" not in st.session_state:
+    st.session_state.rag_system = DocumentRAG()
+
 # Streamlit UI
 st.title("Document Analyzer and Podcast Generator")
 
@@ -159,13 +163,6 @@ if "OPENAI_API_KEY" not in os.environ or not os.getenv("OPENAI_API_KEY"):
 else:
     st.success("API Key successfully loaded from environment variable.")
 
-# Initialize RAG system
-try:
-    rag_system = DocumentRAG()
-except ValueError as e:
-    st.error(str(e))
-    st.stop()
-
 # File upload
 st.subheader("Step 1: Upload Documents")
 uploaded_files = st.file_uploader("Upload files (PDF, TXT, CSV)", accept_multiple_files=True)
@@ -173,26 +170,22 @@ uploaded_files = st.file_uploader("Upload files (PDF, TXT, CSV)", accept_multipl
 if st.button("Process Documents"):
     if uploaded_files:
         # Process the uploaded files
-        result = rag_system.process_documents(uploaded_files)
-        
-        # Ensure that result is a string and display appropriately
-        if isinstance(result, str):
-            if "successfully" in result:
-                st.success(result)
-            else:
-                st.error(result)
+        result = st.session_state.rag_system.process_documents(uploaded_files)
+        if "successfully" in result:
+            st.success(result)
         else:
-            st.error("An unexpected error occurred during document processing.")
+            st.error(result)
     else:
         st.warning("No files uploaded.")
 
 # Document Q&A
 st.subheader("Step 2: Ask Questions")
-if rag_system.qa_chain:
+if st.session_state.rag_system.qa_chain:
     history = []
     user_question = st.text_input("Ask a question:")
     if st.button("Submit Question"):
-        history = rag_system.handle_query(user_question, history)
+        # Handle the user query
+        history = st.session_state.rag_system.handle_query(user_question, history)
         for question, answer in history:
             st.chat_message("user").write(question)
             st.chat_message("assistant").write(answer)