Update app.py

app.py

@@ -609,18 +609,25 @@ def run_detailed_comparison():
                     "Ontology-Enhanced RAG": list(enhanced_metrics.values())
                 })
                 
-                # Convert data to Plotly radar chart format
-                fig = px.line_polar(
-                    metrics_df, 
-                    r=["Traditional RAG", "Ontology-Enhanced RAG"], 
-                    theta="metrics",
-                    line_close=True,
-                    range_r=[0, 10],
-                    title="Context Quality Comparison"
+                # Filter out columns with incomplete data to avoid inconsistencies between theta and r
+                plot_df = df.dropna(subset=["Metric", "Value", "Method"])
+
+                # Ensure the transformation is correct
+                plot_df = plot_df.astype({"Metric": str, "Value": float, "Method": str})
+
+                # Use bar_polar to avoid wiring errors
+                fig = px.bar_polar(
+                plot_df,
+                r="Value",
+                theta="Metric",
+                color="Method",
+                title="Context Quality Assessment (Polar View)",
+                color_discrete_sequence=px.colors.qualitative.Set2
                 )
-                
+
+                fig.update_layout(polar=dict(radialaxis=dict(visible=True)), showlegend=True)
                 st.plotly_chart(fig, use_container_width=True)
-                
+                           
                 st.markdown("""
                                 The figure above shows a comparison of the two RAG methods in terms of context quality. Ontology-enhanced RAG performs better in multiple dimensions: