Upload app.py

app.py

@@ -77,7 +77,7 @@ RECIPES_DF = load_recipes()
 # }
 
 EXAMPLE_IDS = [
-    uid for uid in ("user_1", "user_2", "user_3", "user_5")
+    uid for uid in ("user_1", "user_2", "user_3", "user_4", "user_5")
     if (USER_DATA_DIR / uid / "user_profile.json").exists()
 ]
 
@@ -228,9 +228,13 @@ def render_recommendations(df, user_parents=None):
 
         # --- Region / Cuisine ---
         region = row.get("region", "Unavailable")
+        if isinstance(region, (set, list, tuple)):
+            region_str = ", ".join(str(x) for x in region)
+        else:
+            region_str = str(region)
         cuisine = _ensure_iterable(row.get("cuisine_attr"))
         cuisine_str = ", ".join(cuisine) if cuisine else "Unavailable"
-        md_lines.append(f"   - Region: {region}")
+        md_lines.append(f"   - Region: {region_str}")
         md_lines.append(f"   - Cuisine: {cuisine_str}")
 
         # --- Nutrition ---
@@ -363,6 +367,13 @@ def run_pipeline(
             output_image=str(output_image),
         )
         Path(upload_path).unlink(missing_ok=True)
+        detection_payload = detection_result.get("recipe_json")
+        if not detection_payload:
+            raise ValueError("No detection result returned. Please try again with a clearer photo.")
+
+        ingredients = detection_payload.get("ingredients", [])
+        if not isinstance(ingredients, list) or len(ingredients) == 0:
+            raise ValueError("No ingredients detected. Please try again with a clearer photo.")
 
         #2: Always create/update user profile with current UI values
         profile = build_user_profile(
@@ -390,7 +401,27 @@ def run_pipeline(
             topk=5,
         )
 
+        if not ml_top.empty:
+            for score_col in ["rank_score", "pred", "match_score", "ml_score"]:
+                if score_col in ml_top.columns and ml_top[score_col].notna().any():
+                    max_val = ml_top[score_col].max()
+                    if max_val > 0:
+                        ml_top["score"] = ml_top[score_col] / max_val * 100
+                    break
+
         ingredient_summary = summarize_ingredients(user_parents, high_conf, low_conf)
+        protein_min_val = profile["nutritional_goals"]["protein"]["min"]
+        protein_max_val = profile["nutritional_goals"]["protein"]["max"]
+        calorie_min_val = profile["nutritional_goals"]["calories"]["min"]
+        calorie_max_val = profile["nutritional_goals"]["calories"]["max"]
+
+        goals_summary = (
+            f"### Nutritional Goals\n"
+            f"- Calories: {calorie_min_val} - {calorie_max_val} kcal\n"
+            f"- Protein: {protein_min_val} - {protein_max_val} g"
+        )
+
+        ingredient_summary = goals_summary + "\n\n" + ingredient_summary
         recommendation_md, feedback_rows = render_recommendations(ml_top, user_parents)
 
 
@@ -414,16 +445,14 @@ def run_pipeline(
             profile_status,
         )
     except Exception as exc:
-        import traceback
-        error_detail = traceback.format_exc()
         return (
             None,
+            None,
+            f"⚠️ {exc}",
             "",
-            "",
-            f"⚠️ Error: {exc}\n\nDetails:\n{error_detail}",
             gr.update(choices=[], value=None),
             [],
-            f"⚠️ Error: {exc}",
+            f"⚠️ {exc}",
         )
 
 
@@ -579,7 +608,6 @@ with gr.Blocks(title="Smart Fridge Recipe Assistant", theme=gr.themes.Soft()) as
                     value=10,
                     step=5,
                     label="Protein Min (g)",
-                    container=False
                 )
             protein_max_slider = gr.Slider(
                     minimum=0,
@@ -587,7 +615,6 @@ with gr.Blocks(title="Smart Fridge Recipe Assistant", theme=gr.themes.Soft()) as
                     value=160,
                     step=5,
                     label="Protein Max (g)",
-                    container=False
                 )
             preferred_box = gr.Textbox(
                 label="Preferred main ingredients",