Help to build Bot in production with externally trained NLG model

Hi! @akelad, @dakshvar22 I am trying to implement a custom keras policy, where I use sequential to sequential model architecture. I have followed the procedure as per the documentation (Sequence to sequence - training - Keras Documentation) for my custom dataset. The network has trained successfully, but when I try to interact using this model in rasa server, I get the following error,

File “C:\Users\SA2446\AppData\Roaming\Python\Python37\site-packages\rasa\core\channels\channel.py”, line 387, in on_message_wrapper await on_new_message(message) File “C:\Users\SA2446\AppData\Roaming\Python\Python37\site-packages\rasa\core\channels\channel.py”, line 65, in handler await app.agent.handle_message(*args, **kwargs) File “C:\Users\SA2446\AppData\Roaming\Python\Python37\site-packages\rasa\core\agent.py”, line 488, in handle_message return await processor.handle_message(message) File “C:\Users\SA2446\AppData\Roaming\Python\Python37\site-packages\rasa\core\processor.py”, line 90, in handle_message await self._predict_and_execute_next_action(message, tracker) File “C:\Users\SA2446\AppData\Roaming\Python\Python37\site-packages\rasa\core\processor.py”, line 353, in _predict_and_execute_next_action action, policy, confidence = self.predict_next_action(tracker) File “C:\Users\SA2446\AppData\Roaming\Python\Python37\site-packages\rasa\core\processor.py”, line 180, in predict_next_action action_confidences, policy = self._get_next_action_probabilities(tracker) File “C:\Users\SA2446\AppData\Roaming\Python\Python37\site-packages\rasa\core\processor.py”, line 565, in _get_next_action_probabilities tracker, self.domain File “C:\Users\SA2446\AppData\Roaming\Python\Python37\site-packages\rasa\core\policies\ensemble.py”, line 343, in probabilities_using_best_policy probabilities = p.predict_action_probabilities(tracker, domain) File “C:\ICA\restaurantbot\custom_policy.py”, line 353, in predict_action_probabilities y_pred = self.model.predict(X, batch_size=1) File “c:\apps\sa2446\lib\site-packages\tensorflow\python\keras\engine\training.py”, line 1096, in predict x, check_steps=True, steps_name=‘steps’, steps=steps) File “c:\apps\sa2446\lib\site-packages\tensorflow\python\keras\engine\training.py”, line 2382, in _standardize_user_data exception_prefix=‘input’) File “c:\apps\sa2446\lib\site-packages\tensorflow\python\keras\engine\training_utils.py”, line 323, in standardize_input_data str(len(data)) + ’ arrays: ’ + str(data)[:200] + ‘…’) ValueError: Error when checking model input: the list of Numpy arrays that you are passing to your model is not the size the model expected. Expected to see 2 array(s), but instead got the following list of 1 arrays: [array([[[-1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, … I do not understand why it throws such an error, when it has trained successfully. Could I get any information to solve this issue?