Update streamlit_app.py

streamlit_app.py

@@ -217,9 +217,9 @@ def main():
     
     # Available datasets
     available_datasets = [
-        "jailbreaks_dataset_with_results_reduced",
-        "jailbreaks_dataset_with_results",
-        "jailbreaks_dataset_with_results_filtered_successful_jailbreak",
+        "risky-conversations/jailbreaks_dataset_with_results_reduced",
+        "risky-conversations/jailbreaks_dataset_with_results",
+        "risky-conversations/jailbreaks_dataset_with_results_filtered_successful_jailbreak",
         "Custom..."
     ]
     
@@ -234,8 +234,8 @@ def main():
     if selected_option == "Custom...":
         selected_dataset = st.sidebar.text_input(
             "Custom Dataset Name",
-            value="jailbreaks_dataset_with_results_reduced",
-            help="Enter the full dataset name (e.g., 'jailbreaks_dataset_with_results_reduced')"
+            value="risky-conversations/jailbreaks_dataset_with_results_reduced",
+            help="Enter the full dataset name (e.g., 'risky-conversations/jailbreaks_dataset_with_results_reduced')"
         )
         if not selected_dataset.strip():
             st.sidebar.warning("Please enter a dataset name")
@@ -275,11 +275,6 @@ def main():
     if not data_loaded:
         st.stop()
     
-    # Check if we have data after filtering
-    if len(filtered_df_exploded) == 0:
-        st.error("No data available with current filters. Please adjust your selection.")
-        st.stop()
-    
     # Sidebar controls
     st.sidebar.header("🎛️ Controls")
     
@@ -323,6 +318,21 @@ def main():
     else:
         selected_roles = None
     
+    # Filter data based on selections
+    filtered_df = df[df['type'].isin(selected_types)] if selected_types else df
+    filtered_df_exploded = df_exploded[df_exploded['type'].isin(selected_types)] if selected_types else df_exploded
+    
+    if selected_roles and 'turn.role' in filtered_df_exploded.columns:
+        filtered_df_exploded = filtered_df_exploded[filtered_df_exploded['turn.role'].isin(selected_roles)]
+    elif selected_roles is not None and len(selected_roles) == 0:
+        # If roles exist but none are selected, show empty dataset
+        filtered_df_exploded = filtered_df_exploded.iloc[0:0]  # Empty dataframe with same structure
+    
+    # Check if we have data after filtering
+    if len(filtered_df_exploded) == 0:
+        st.error("No data available with current filters. Please adjust your selection.")
+        st.stop()
+    
     # Metric selection
     st.sidebar.header("📊 Metrics")
     
@@ -483,16 +493,6 @@ def main():
             for i, metric in enumerate(available_metrics, 1):
                 st.write(f"{i}. `{metric}`")
     
-    # Filter data
-    filtered_df = df[df['type'].isin(selected_types)] if selected_types else df
-    filtered_df_exploded = df_exploded[df_exploded['type'].isin(selected_types)] if selected_types else df_exploded
-    
-    if selected_roles and 'turn.role' in filtered_df_exploded.columns:
-        filtered_df_exploded = filtered_df_exploded[filtered_df_exploded['turn.role'].isin(selected_roles)]
-    elif selected_roles is not None and len(selected_roles) == 0:
-        # If roles exist but none are selected, show empty dataset
-        filtered_df_exploded = filtered_df_exploded.iloc[0:0]  # Empty dataframe with same structure
-    
     # Main content tabs
     tab1, tab2, tab3, tab4 = st.tabs(["📊 Distributions", "🔗 Correlations", "📈 Comparisons", "🎯 Details"])