Updated to pos_ratio instead of Meta score

app.py

@@ -9,7 +9,7 @@ import numpy as np
 def load_data():
     try:
         # For Hugging Face Spaces deployment, you might need to adjust this path
-        data = pd.read_csv('games_march2025_cleaned.csv', nrows=20000, on_bad_lines='skip', engine='python')
+        data = pd.read_csv('games_march2025_cleaned.csv', nrows=50000, on_bad_lines='skip', engine='python')
         return data
     except Exception as e:
         print(f"Error loading data: {e}")
@@ -93,17 +93,25 @@ def get_recommendations(game_name, data, feature_vectors):
 
 
 # Gradio interface function
-def recommend_games(game_name, max_age, max_price, min_metacritic):
+def recommend_games(game_name, max_age, max_price, min_pos_ratio):
     data = load_data()
     if data is None:
         return "Failed to load data. Please check the data file."
     
     # Apply filters BEFORE feature preparation
-    data = data[
-        (data['required_age'] <= max_age) &
-        (data['price'] <= max_price) &
-        ((data['metacritic_score'].fillna(0) >= min_metacritic) | data['metacritic_score'].isna())
-    ].reset_index(drop=True)
+    # Avoid division by zero and filter by positive ratio
+data['pos_ratio'] = data.apply(
+    lambda row: (row['positive'] / (row['positive'] + row['negative']))
+    if (row['positive'] + row['negative']) > 0 else 0,
+    axis=1
+)
+
+data = data[
+    (data['required_age'] <= max_age) &
+    (data['price'] <= max_price) &
+    (data['pos_ratio'] >= min_pos_ratio)
+].reset_index(drop=True)
+
     
     if data.empty:
         return "No games found matching your filter criteria."
@@ -125,7 +133,7 @@ with gr.Blocks(title="Steam Game Recommender") as demo:
     with gr.Row():
         max_age_slider = gr.Slider(0, 21, value=17, label="Max Age Rating (Avoid Adult Games)")
         max_price_slider = gr.Slider(0.0, 100.0, value=60.0, step=0.5, label="Maximum Price ($)")
-        min_metacritic_slider = gr.Slider(0, 100, value=50, step=1, label="Minimum Metacritic Score")
+        min_pos_ratio_slider = gr.Slider(0.0, 1.0, value=0.7, step=0.01, label="Minimum Positive Review Ratio")
 
     with gr.Row():
         submit_btn = gr.Button("Get Recommendations")
@@ -135,11 +143,10 @@ with gr.Blocks(title="Steam Game Recommender") as demo:
 
     submit_btn.click(
         fn=recommend_games,
-        inputs=[input_text, max_age_slider, max_price_slider, min_metacritic_slider],
+        inputs=[input_text, max_age_slider, max_price_slider, min_pos_ratio_slider],
         outputs=output_text
     )
 
-
 # Launch the app
 if __name__ == "__main__":
     demo.launch()