Update app.py

app.py

@@ -30,10 +30,11 @@ class TradingEnv(gym.Env):
         self.observation_space = spaces.Box(
             low=0, high=1, shape=(window_size, 2), dtype=np.float32)
         
-    def reset(self):
+    def reset(self, seed=None, options=None):
+        super().reset(seed=seed)
         self.current_step = self.window_size
-        return self._get_observation()
-    
+        return self._get_observation(), {}
+
     def _get_observation(self):
         window_data = self.data[self.current_step-self.window_size:self.current_step]
         obs = window_data[['close', 'EMA']].values
@@ -80,9 +81,11 @@ def calculate_ema(data, span=20):
     return data
 
 def load_or_train_model(env):
-    if os.path.exists("./ppo_trading_agent.zip"):
-        model = PPO.load("ppo_trading_agent", env=env)
-    else:
+    custom_objects = {"clip_range": 0.2, "lr_schedule": 0.0003}  # Update with your actual values or leave as is
+    try:
+        model = PPO.load("ppo_trading_agent", env=env, custom_objects=custom_objects)
+    except Exception as e:
+        print(f"Loading model failed: {e}. Training a new model.")
         model = PPO('MlpPolicy', env, verbose=1)
         model.learn(total_timesteps=10000)
         model.save("ppo_trading_agent")