Update app.py

app.py

@@ -16,12 +16,14 @@ qa_engine = QAEngine()
 # Ensure temp directory exists
 os.makedirs("temp", exist_ok=True)
 
-st.sidebar.header("Upload a PDF")
+# Sidebar for file upload
+st.sidebar.header("📂 Upload a PDF")
 uploaded_file = st.sidebar.file_uploader("Choose a PDF file", type=["pdf"])
 
+# Document upload & processing
 if uploaded_file:
     pdf_path = os.path.join("temp", uploaded_file.name)
-
+    
     with open(pdf_path, "wb") as f:
         f.write(uploaded_file.read())
 
@@ -31,19 +33,33 @@ if uploaded_file:
         document_processor.process_document(pdf_path)
 
     st.sidebar.success("✅ Document processed successfully!")
+    st.session_state["document_uploaded"] = True
+else:
+    st.session_state["document_uploaded"] = False
+
+# Divider between sections
+st.markdown("---")
+
+# Q&A Section
+st.header("🔍 Ask a Question")
 
-    # Query input
-    question = st.text_input("Ask a question from the document:", placeholder="What are the key insights?")
+question = st.text_input("Ask a question:", placeholder="What are the key insights?")
 
-    if st.button("🔍 Search & Answer"):
-        if question:
-            with st.spinner("🧠 Searching for relevant context..."):
+if st.button("💡 Get Answer"):
+    if question:
+        with st.spinner("🧠 Generating response..."):
+            if st.session_state["document_uploaded"]:
+                # Use document-based QA if a file is uploaded
                 answer = qa_engine.query(question)
+            else:
+                # Use AI-based response if no document is uploaded
+                answer = llm_processor.generate_answer("", question)
+                st.warning("⚠️ No document uploaded. This response is generated from general AI knowledge and may not be document-specific.")
 
-            st.subheader("📝 Answer:")
-            st.write(answer.content)
-        else:
-            st.warning("⚠️ Please enter a question.")
+        st.subheader("📝 Answer:")
+        st.write(answer)
+    else:
+        st.warning("⚠️ Please enter a question.")
 
 st.markdown("---")
 st.caption("🤖 Powered by ChromaDB + Groq LLM | Built with ❤️ using Streamlit")