Add TensorBoard log visualization and update training section

app.py

@@ -15,6 +15,8 @@ from openai import OpenAI
 import os
 from dotenv import load_dotenv
 from chatbot_utils import ask_receipt_chatbot
+import time
+from tensorboard.backend.event_processing import event_accumulator
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)
@@ -198,5 +200,34 @@ def main():
             answer = ask_receipt_chatbot(user_question)
             st.success(answer)
 
+    st.header("Model Training & Evaluation Demo")
+
+    if st.button("Start Training"):
+        epochs = 10
+        losses = []
+        accuracies = []
+        progress = st.progress(0)
+        chart = st.line_chart({"Loss": [], "Accuracy": []})
+
+        for epoch in range(epochs):
+            # Simulate training
+            loss = np.exp(-epoch/5) + np.random.rand() * 0.05
+            acc = 1 - loss + np.random.rand() * 0.02
+            losses.append(loss)
+            accuracies.append(acc)
+            chart.add_rows({"Loss": [loss], "Accuracy": [acc]})
+            progress.progress((epoch+1)/epochs)
+            st.write(f"Epoch {epoch+1}: Loss={loss:.4f}, Accuracy={acc:.4f}")
+            time.sleep(0.5)
+
+        st.success("Training complete!")
+        st.line_chart({"Loss": losses, "Accuracy": accuracies})
+
+    logdir = "path/to/your/logdir"
+    ea = event_accumulator.EventAccumulator(logdir)
+    ea.Reload()
+    losses = [s.value for s in ea.Scalars('loss')]
+    st.line_chart(losses)
+
 if __name__ == "__main__":
     main()