Update app.py

app.py

@@ -2,7 +2,7 @@ import streamlit as st
 import textgrad as tg
 import os
 
-tg.set_backward_engine(tg.get_engine("gpt-4o"), override = True)
+tg.set_backward_engine(tg.get_engine("gpt-4o"))
 
 # Hardcoded examples
 default_initial_solution = """To solve the equation 3x^2 - 7x + 2 = 0, we use the quadratic formula:
@@ -29,21 +29,23 @@ initial_solution = st.text_area("Initial Solution", st.session_state.get("initia
 loss_system_prompt = st.text_area("Loss System Prompt", st.session_state.get("loss_system_prompt", ""))
 num_epochs = st.number_input("Epochs", min_value=1, value=1)
 
-# Set up the textgrad variables
-solution = tg.Variable(initial_solution,
-                       requires_grad=True,
-                       role_description="solution to the math question")
-
-loss_fn = tg.TextLoss(tg.Variable(loss_system_prompt,
-                                  requires_grad=False,
-                                  role_description="system prompt"))
-optimizer = tg.TGD([solution])
-
-# Training loop
-for i in range(num_epochs):
-    loss = loss_fn(solution)
-    loss.backward()
-    optimizer.step()
-
-# Output box
-st.text_area("Result", solution.value)
+# Enter button
+if st.button("Enter"):
+    # Set up the textgrad variables
+    solution = tg.Variable(initial_solution,
+                           requires_grad=True,
+                           role_description="solution to the math question")
+
+    loss_fn = tg.TextLoss(tg.Variable(loss_system_prompt,
+                                      requires_grad=False,
+                                      role_description="system prompt"))
+    optimizer = tg.TGD([solution])
+
+    # Training loop
+    for i in range(num_epochs):
+        loss = loss_fn(solution)
+        loss.backward()
+        optimizer.step()
+
+    # Output box
+    st.text_area("Result", solution.value)