Update app.py

app.py

@@ -15,7 +15,7 @@ selected_features = ['genres', 'categories', 'steamspy_tags', 'platforms']
 for feature in selected_features:
     if feature not in data.columns:
         data[feature] = ''
-data['combined_features'] = data['genres'] + ' ' + data['categories'] + ' ' + data['steamspy_tags'] + ' ' + data['platform']
+data['combined_features'] = data['genres'] + ' ' + data['categories'] + ' ' + data['steamspy_tags'] + ' ' + data['platforms']
 
 # Vectorize
 vectorizer = TfidfVectorizer(stop_words='english', ngram_range=(1, 2), max_features=8000)
@@ -50,25 +50,25 @@ def recommend_games(user_game_name_input):
     for i, (index, score) in enumerate(sorted_similar_games[1:21]):
         if score < 0.3:
             continue
-    game_name = data.iloc[index]['name']
+        game_name = data.iloc[index]['name']
     
-    # Get OS support info
-    platforms = data.iloc[index].get('platform', '').lower()
-    os_icons = []
-    if 'windows' in platforms:
-        os_icons.append("🪟")
-    if 'mac' in platforms or 'macos' in platforms:
-        os_icons.append("🍎")
-    if 'linux' in platforms or 'steam' in platforms:
-        os_icons.append("🐧")
+        # Get OS support info
+        platforms = data.iloc[index].get('platforms', '').lower()
+        os_icons = []
+        if 'windows' in platforms:
+            os_icons.append("🪟")
+        if 'mac' in platforms or 'macos' in platforms:
+            os_icons.append("🍎")
+        if 'linux' in platforms or 'steam' in platforms:
+            os_icons.append("🐧")
     
-    os_display = ' '.join(os_icons) if os_icons else "❓"
+        os_display = ' '.join(os_icons) if os_icons else "❓"
     
-    recommendations.append(f"{i+1}. {game_name} {os_display} (Similarity: {score:.2f})")
-    chart_data.append({'Game': game_name, 'Similarity': score})
+        recommendations.append(f"{i+1}. {game_name} {os_display} (Similarity: {score:.2f})")
+        chart_data.append({'Game': game_name, 'Similarity': score})
     
-    if len(recommendations) >= 10:
-        break
+        if len(recommendations) >= 10:
+            break
 
     chart_df = pd.DataFrame(chart_data)
     return "\n".join(recommendations), chart_df