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app.py

@@ -159,9 +159,9 @@ def render_overview_tab(df: pd.DataFrame, mb_df: pd.DataFrame) -> None:
 
     c3, c4 = st.columns(2)
     with c3:
-        st.plotly_chart(ai_score_distribution(df), use_container_width=True)
+        st.plotly_chart(ai_score_distribution(df), use_container_width=True, key="overview_ai_dist")
     with c4:
-        st.plotly_chart(mass_balance_sunburst(mb_df), use_container_width=True)
+        st.plotly_chart(mass_balance_sunburst(mb_df), use_container_width=True, key="overview_mass_balance")
 
     st.subheader("PFAS Degradation Heatmap")
     st.plotly_chart(degradation_heatmap(df), use_container_width=True)
@@ -195,7 +195,7 @@ def render_ai_models_tab(df: pd.DataFrame, models: dict) -> None:
     preds = iso_model.predict(df[stability_cols])
     n_anomalies = int((preds == -1).sum())
     st.info(f"Isolation Forest detected **{n_anomalies}** potentially unstable experiments out of {len(df)}.")
-    st.plotly_chart(stability_radar(df), use_container_width=True)
+    st.plotly_chart(stability_radar(df), use_container_width=True, key="models_stability_radar")
 
 
 def render_optimization_tab(df: pd.DataFrame) -> None:
@@ -251,7 +251,7 @@ def render_mass_balance_tab(df: pd.DataFrame, mb_df: pd.DataFrame) -> None:
         "+ Short-chain products + Mineralized PFAS`"
     )
 
-    st.plotly_chart(mass_balance_sunburst(mb_df), use_container_width=True)
+    st.plotly_chart(mass_balance_sunburst(mb_df), use_container_width=True, key="tab_mass_balance_sunburst")
 
     st.subheader("Mass Balance Details")
     st.dataframe(
@@ -308,7 +308,7 @@ def render_reactor_stability_tab(df: pd.DataFrame) -> None:
                           annotation_text="High VFA threshold")
         st.plotly_chart(fig_vfa, use_container_width=True)
 
-    st.plotly_chart(stability_radar(df), use_container_width=True)
+    st.plotly_chart(stability_radar(df), use_container_width=True, key="stability_tab_radar")
 
     st.subheader("Instability Detection Summary")
     stable = df[df["instability_flag"] == 0]