Update app.py

app.py

@@ -77,14 +77,8 @@ def extract_leaderboard_stats(game_name: str) -> pd.DataFrame:
                     "FROM game_results WHERE game_name = ?"
             df = pd.read_sql_query(query, conn, params=(game_name,))
         
-        # Detect duplicate reward entries by counting unique episodes per agent
-        unique_episodes_query = """
-            SELECT COUNT(DISTINCT episode) FROM game_results WHERE game_name = ?
-        """
-        unique_episodes = conn.execute(unique_episodes_query, (game_name,)).fetchone()[0] or 1
-        
-        # Adjust total_rewards only if the count of unique episodes suggests duplication
-        df["total_rewards"] = df["total_rewards"].fillna(0).astype(float) / unique_episodes
+        # Keep division by 2 for total rewards
+        df["total_rewards"] = df["total_rewards"].fillna(0).astype(float) / 2
         
         # Fetch average generation time from moves table
         gen_time_query = """
@@ -92,6 +86,9 @@ def extract_leaderboard_stats(game_name: str) -> pd.DataFrame:
         """
         avg_gen_time = conn.execute(gen_time_query, (game_name,)).fetchone()[0] or 0
         
+        # Ensure avg_gen_time has decimals
+        avg_gen_time = round(avg_gen_time, 3)
+        
         # Calculate win rate against random bot using moves table
         vs_random_query = """
             SELECT COUNT(DISTINCT gr.episode) FROM game_results gr
@@ -109,7 +106,7 @@ def extract_leaderboard_stats(game_name: str) -> pd.DataFrame:
         
         df.insert(0, "agent_name", model_name)  # Ensure agent_name is the first column
         df["agent_type"] = agent_type
-        df["avg_generation_time (sec)"] = round(avg_gen_time, 3)
+        df["avg_generation_time (sec)"] = avg_gen_time
         df["vs_random"] = round(vs_random_rate, 2)
         
         all_stats.append(df)