Update app.py

app.py

@@ -18,6 +18,25 @@ st.markdown(
         background-repeat: no-repeat;
     }}
     
+    /* Custom Top Bar */
+    .top-bar {{
+        position: fixed;
+        top: 0;
+        left: 0;
+        right: 0;
+        background-color: rgba(0, 0, 0, 0.6);
+        color: white;
+        text-align: center;
+        padding: 15px 0;
+        font-size: 24px;
+        z-index: 10;
+    }}
+
+    /* Content under the top bar */
+    .main-content {{
+        margin-top: 80px; /* To create space for the top bar */
+    }}
+    
     /* Ensure title is black */
     h1 {{
         color: black !important;  /* Force title color to black */
@@ -28,19 +47,6 @@ st.markdown(
         color: black;  /* Set text color to black */
     }}
     
-    /* Set footer styling */
-    .footer {{
-        position: fixed;
-        bottom: 0;
-        left: 0;
-        right: 0;
-        background-color: rgba(0, 0, 0, 0.6);
-        color: white;
-        text-align: center;
-        padding: 10px 0;
-        font-size: 14px;
-    }}
-    
     /* Set processing button color to green */
     .stButton button {{
         background-color: green;
@@ -139,7 +145,10 @@ def process_and_store_document(file_path):
         st.error(f"Error saving the FAISS index: {e}")
 
 # User interface for Streamlit
-st.title("Atomic Habits RAG Application")
+st.markdown('<div class="top-bar">Atomic Habits RAG Application</div>', unsafe_allow_html=True)
+
+# Content under the top bar
+st.markdown('<div class="main-content">', unsafe_allow_html=True)
 
 # Button to trigger document processing
 if st.button("Process PDF"):
@@ -149,27 +158,37 @@ if st.button("Process PDF"):
 user_query = st.text_input("Enter your query:")
 
 if user_query:
-    # Generate embedding for the user query
-    query_embedding = embedder.encode([user_query])
-    
-    # Perform the search on the FAISS index
-    distances, indices = index.search(np.array(query_embedding), k=5)
-    
-    # Retrieve the most relevant chunks based on the indices
-    retrieved_chunks = [chunks[idx] for idx in indices[0]]
-    
-    # Display the retrieved chunks
-    st.subheader("Retrieved Chunks")
-    for chunk in retrieved_chunks:
-        st.write(chunk)
-    
-    # Combine the retrieved chunks with the query and generate a response using Groq
-    combined_input = " ".join(retrieved_chunks) + user_query
-    response = groq_client.generate(model="llama3-8b-8192", prompt=combined_input, max_tokens=200)
-    
-    # Display the generated response
-    st.subheader("Generated Response")
-    st.write(response["text"])
+    # Check if there are any chunks in the index
+    if not chunks:
+        st.error("Please process the document first by clicking 'Process PDF'.")
+    else:
+        # Generate embedding for the user query
+        query_embedding = embedder.encode([user_query])
+        
+        # Perform the search on the FAISS index
+        distances, indices = index.search(np.array(query_embedding), k=5)
+        
+        # Check if the indices returned are valid
+        if indices.size == 0 or np.any(indices[0] == -1):
+            st.error("No relevant results found in the index.")
+        else:
+            # Retrieve the most relevant chunks based on the indices
+            retrieved_chunks = [chunks[idx] for idx in indices[0]]
+            
+            # Display the retrieved chunks
+            st.subheader("Retrieved Chunks")
+            for chunk in retrieved_chunks:
+                st.write(chunk)
+            
+            # Combine the retrieved chunks with the query and generate a response using Groq
+            combined_input = " ".join(retrieved_chunks) + user_query
+            response = groq_client.generate(model="llama3-8b-8192", prompt=combined_input, max_tokens=200)
+            
+            # Display the generated response
+            st.subheader("Generated Response")
+            st.write(response["text"])
 
 # Footer
 st.markdown("<div class='footer'>Created by Shamil Shahbaz</div>", unsafe_allow_html=True)
+
+st.markdown('</div>', unsafe_allow_html=True)  # End the main content div