Update app.py

app.py

@@ -57,33 +57,33 @@ def lime_explain(prompt, model, tokenizer, max_length=100):
 
 # Load Model Section
 st.subheader("Load Your Trained Model")
-model_path = st.text_input("Enter the path to your trained model (.h5):")
 model = None
 tokenizer = None
+model_path = "deep_learning_model.h5"  # Ensure this file is in the same directory as app.py
+
+try:
+    model = load_model(model_path)
+    tokenizer = setup_tokenizer()
+    st.success("Model Loaded Successfully!")
+
+    # User Prompt Input
+    st.subheader("Classify Your Prompt")
+    user_prompt = st.text_input("Enter a prompt to classify:")
+
+    if user_prompt:
+        class_label, confidence_score = detect_prompt(user_prompt, tokenizer, model)
+        st.write(f"Predicted Class: **{class_label}**")
+        st.write(f"Confidence Score: **{confidence_score:.2f}%**")
+
+        # LIME Explanation
+        st.subheader("LIME Explanation")
+        explanation = lime_explain(user_prompt, model, tokenizer)
+        explanation_as_html = explanation.as_html()
+        st.components.v1.html(explanation_as_html, height=500)
+
+except Exception as e:
+    st.error(f"Error Loading Model: {e}")
 
-if model_path:
-    try:
-        model = load_model(model_path)
-        tokenizer = setup_tokenizer()
-        st.success("Model Loaded Successfully!")
-        
-        # User Prompt Input
-        st.subheader("Classify Your Prompt")
-        user_prompt = st.text_input("Enter a prompt to classify:")
-
-        if user_prompt:
-            class_label, confidence_score = detect_prompt(user_prompt, tokenizer, model)
-            st.write(f"Predicted Class: **{class_label}**")
-            st.write(f"Confidence Score: **{confidence_score:.2f}%**")
-
-            # LIME Explanation
-            st.subheader("LIME Explanation")
-            explanation = lime_explain(user_prompt, model, tokenizer)
-            explanation_as_html = explanation.as_html()
-            st.components.v1.html(explanation_as_html, height=500)
-
-    except Exception as e:
-        st.error(f"Error Loading Model: {e}")
 
 # Footer
 st.write("---")