Update app.py

app.py

@@ -97,10 +97,10 @@ with col1:
     start_point = st.number_input("Starting Point (x):", value=4.0, step=0.1, format="%.2f", key="start_point", on_change=reset_session)
     learning_rate = st.number_input("Learning Rate:", value=0.1, step=0.01, format="%.2f", key="learning_rate", on_change=reset_session)
 
-    # Buttons for actions with styling
-    col1.button("🔄 Next Step", key="next", use_container_width=True, help="Perform one step of gradient descent", on_click=None)
+    # Buttons for actions with styling (change key to make it unique)
+    col1.button("🔄 Next Step", key="next_step", use_container_width=True, help="Perform one step of gradient descent", on_click=None)
     col1.button("🔁 Reset", key="reset", use_container_width=True, help="Reset the gradient descent", on_click=reset_session)
-    iteration_data_button = col1.button("📊 Iteration Data", key="iteration_data", use_container_width=True)
+    iteration_data_button = col1.button("📊 Iteration Data", key="iteration_data_button", use_container_width=True)
 
 # Right column for visualization
 with col2:
@@ -144,7 +144,7 @@ with col2:
     st.plotly_chart(plot)
 
 # Perform gradient descent operation when button is clicked
-if st.button("🔄 Next Step", key="next", use_container_width=True):
+if st.button("🔄 Next Step", key="next_step", use_container_width=True):
     try:
         grad = compute_derivative(st.session_state.func_input, st.session_state.x_current)
         st.session_state.x_current = st.session_state.x_current - st.session_state.learning_rate * grad