Changed the Def suggested

app.py

@@ -10,9 +10,9 @@ clothing_df = pd.read_csv("clothes.csv")
 
 # --- Simple filtering function ---
 def get_suggestions(query):
-    results = clothing_df
-    
+    results = clothing_df.copy()
     q = query.lower()
+    
     # Weather-based filtering
     if "rain" in q:
         results = results[results['weather'].str.contains("rain", case=False, na=False)]
@@ -24,18 +24,23 @@ def get_suggestions(query):
         results = results[results['weather'].str.contains("snow", case=False, na=False)]
 
     # Formality-based filtering
-    elif "formal" in q or "office" in q:
+    if "formal" in q or "office" in q:
         results = results[results['formality'].str.contains("formal", case=False, na=False)]
     elif "casual" in q:
         results = results[results['formality'].str.contains("casual", case=False, na=False)]
 
-    # If no keywords match, return random sample
+    # If no results after filtering, fallback to full database
     if len(results) == 0:
-        results = clothing_df.sample(min(3, len(clothing_df)))
-    else:
-        results = results.sample(min(3, len(results)))
+        results = clothing_df.copy()
+
+    # --- Pick one item per category ---
+    outfit = []
+    for category, group in results.groupby('category'):
+        outfit.append(group.sample(1))  # take one random item per category
 
-    return results
+    # Combine into single DataFrame
+    final_selection = pd.concat(outfit)
+    return final_selection
 
 # --- Chatbot + image output ---
 def respond(message, history):