Revert interactive buttons: Return to static prediction cards

app.py

@@ -132,40 +132,20 @@ def check_api_health() -> Dict:
 # =============================================================================
 # UI Components
 # =============================================================================
-def update_text(word):
-    """Append clicked word to current context."""
-    current = st.session_state.get('context_value', '')
-    if current and not current.endswith(' '):
-        new_text = f"{current} {word}"
-    else:
-        new_text = f"{current}{word}"
-    st.session_state['context_value'] = new_text
-
-def render_predictions(predictions: List[Dict], model_name: str, key_prefix: str):
+def render_predictions(predictions: List[Dict], model_name: str):
     if not predictions:
         st.warning(f"No predictions from {model_name}")
         return
     
-    # Custom CSS for buttons to look like cards
-    st.markdown("""
-    <style>
-    div.stButton > button {
-        text-align: left;
-        padding: 0.5rem 1rem;
-        height: auto;
-    }
-    </style>
-    """, unsafe_allow_html=True)
-    
-    for i, pred in enumerate(predictions):
+    for pred in predictions:
         word = pred.get("word", "?")
         prob = pred.get("probability", 0)
-        
-        # Create a button for each prediction
-        label = f"{word}  ({prob:.1%})"
-        if st.button(label, key=f"{key_prefix}_{i}", use_container_width=True):
-            update_text(word)
-            st.rerun()
+        st.markdown(f"""
+        <div class="prediction-card">
+            <span class="word">{word}</span>
+            <span class="prob"> — {prob:.1%}</span>
+        </div>
+        """, unsafe_allow_html=True)
 
 # =============================================================================
 # Main App
@@ -267,19 +247,19 @@ if context:
         
         with col1:
             st.markdown("### 🤖 LSTM Neural Network")
-            render_predictions(lstm_preds, "LSTM", "lstm_compare")
+            render_predictions(lstm_preds, "LSTM")
         
         with col2:
             st.markdown("### 📊 Trigram Statistical")
-            render_predictions(trigram_preds, "Trigram", "trigram_compare")
+            render_predictions(trigram_preds, "Trigram")
     
     elif "LSTM" in model_choice:
         st.markdown("### 🤖 LSTM Predictions")
-        render_predictions(lstm_preds, "LSTM", "lstm_only")
+        render_predictions(lstm_preds, "LSTM")
     
     else:
         st.markdown("### 📊 Trigram Predictions")
-        render_predictions(trigram_preds, "Trigram", "trigram_only")
+        render_predictions(trigram_preds, "Trigram")
 
 # Footer
 st.markdown("---")