Update app.py

app.py

@@ -951,7 +951,8 @@ def predict_and_plot_ui(
 
         # 5) response curve vs selected variable (same chosen model)
         plot_var = (plot_var or "light").strip().lower()
-        if plot_var not in FEATURES: plot_var = "light"
+        if plot_var not in FEATURES: 
+            plot_var = "light"
         j = FEATURES.index(plot_var)
 
         _load_aug_and_knn(target)
@@ -961,7 +962,7 @@ def predict_and_plot_ui(
         grid_rows = []
         for xv in xs:
             row = dict(raw_row)
-            if plot_var in ["light","expo_day","expo_night","_c","ph","days"]:
+            if plot_var in ["light", "expo_day", "expo_night", "_c", "ph", "days"]:
                 row[plot_var] = float(xv)
             grid_rows.append(row)
         raw_grid_df = pd.DataFrame(grid_rows)
@@ -998,11 +999,13 @@ def predict_and_plot_ui(
             ax.set_ylim(b_lo - pad, b_hi + pad)
         plt.tight_layout()
 
+        # ---- Markdown output with disclaimer ----
         clamp_note = " _(clamped to literature range)_" if clamped_point else ""
         md = (
             f"### Prediction ({chosen})\n"
             f"**{target}** = **{yhat:.3f}**{clamp_note}  \n"
-            f"Local {int((Q_HI-Q_LO)*100)}% interval: **[{lo_pt:.3f}, {hi_pt:.3f}]**"
+            f"Local {int((Q_HI-Q_LO)*100)}% interval: **[{lo_pt:.3f}, {hi_pt:.3f}]**  \n"
+            f"*Exogenous factors may affect the value; DOI reference advised.*"
             + ("" if not clamped_curve else "\n\n*Response curve clipped to species×medium range.*")
         )
         if preds_point:
@@ -1017,9 +1020,12 @@ def predict_and_plot_ui(
         return md, fig
 
     except Exception as e:
-        fig, ax = plt.subplots(figsize=(6,3)); ax.axis("off"); plt.tight_layout()
+        fig, ax = plt.subplots(figsize=(6,3))
+        ax.axis("off")
+        plt.tight_layout()
         return f"Error: {e}", fig
 
+
 def doi_matches_ui(target, species, media, light, expo_day, expo_night, temp_c, ph, days):
     return _closest_doi(species, media, light, expo_day, expo_night, temp_c, ph, days, topk=3)