Update app.py

app.py

@@ -22,9 +22,10 @@ model = AutoModelForCausalLM.from_pretrained(
 # Load sentence transformer for embeddings
 embedder = SentenceTransformer("all-MiniLM-L6-v2")
 
-st.title("🔍 RAG App using 🤖 Phi-2")
-
-uploaded_file = st.file_uploader("📄 Upload a PDF or TXT file", type=["pdf", "txt"])
+# Sidebar for file upload and display
+st.sidebar.title("📂 File Upload")
+uploaded_file = st.sidebar.file_uploader("Upload a PDF or TXT file", type=["pdf", "txt"])
+file_display_area = st.sidebar.empty()
 
 # Extract text from file
 def extract_text(file):
@@ -56,18 +57,25 @@ def retrieve_chunks(query, chunks, index, embeddings, k=5):
     return [chunks[i] for i in I[0]]
 
 # --- MAIN LOGIC ---
+st.title("🔍 RAG App using 🤖 Phi-2")
+
 if uploaded_file:
-    st.success("✅ File uploaded successfully!")
+    file_display_area.success("✅ File uploaded successfully!")
 
     raw_text = extract_text(uploaded_file)
     chunks = split_into_chunks(raw_text)
 
-    st.info(f"📚 Document split into {len(chunks)} chunks")
-    st.text_area("📄 Extracted Document Text (for debugging)", raw_text, height=200)
+    file_display_area.info(f"📚 Document split into {len(chunks)} chunks")
+    file_display_area.text_area("📄 Extracted Document Text", raw_text, height=200)
 
     index, embeddings = create_faiss_index(chunks)
 
-    user_question = st.text_input("💬 Ask something about the document:")
+    # Chat-like interface
+    st.markdown("### 💬 Chat with the Document")
+    if "chat_history" not in st.session_state:
+        st.session_state.chat_history = []
+
+    user_question = st.text_input("Ask something about the document:")
 
     if user_question:
         with st.spinner("Thinking..."):
@@ -103,5 +111,10 @@ if uploaded_file:
             else:
                 answer = generated_text.replace(prompt, "").strip()
 
-        st.markdown("### 🧠 Answer:")
-        st.success(answer)
+        # Append interaction to chat history
+        st.session_state.chat_history.append({"question": user_question, "answer": answer})
+
+    # Display chat history
+    for chat in st.session_state.chat_history:
+        st.markdown(f"**You:** {chat['question']}")
+        st.markdown(f"**Phi-2:** {chat['answer']}")