caressgents/chatty

TestAItrainedbot

Given the complexity of the task, we will be using Python for this project due to its extensive support for data processing and machine learning tasks. We will be using libraries such as pandas for data cleaning, TensorFlow for model training, and Flask for deployment.

Here are the core classes, functions, and methods that will be necessary:

1. DataCleaner: This class will handle all the data cleaning tasks. It will have methods like remove_noise, remove_redundancies, filter_irrelevant_conversations, standardize_text, and address_data_imbalances.

2. DataPreprocessor: This class will handle the data preprocessing tasks required for the chosen AI model. It will have methods like tokenize_text and convert_to_model_input.

3. ModelTrainer: This class will handle the model training tasks. It will have methods like train_model and validate_model.

4. ModelEvaluator: This class will handle the model evaluation tasks. It will have methods like calculate_accuracy, calculate_precision, calculate_recall, and calculate_f1_score.

5. Chatbot: This class will handle the deployment of the chatbot. It will have methods like respond_to_query.

6. DataAnonymizer: This class will handle the anonymization of personal data to comply with data privacy standards. It will have methods like anonymize_personal_data.

7. DataConsentManager: This class will handle obtaining necessary consents for data usage. It will have methods like obtain_consent.

8. DataErasureManager: This class will handle the right to erasure or data portability. It will have methods like erase_data and port_data.

Now, let's start with the "entrypoint" file, which will be main.py. This file will import and use the above classes to clean the data, train the model, evaluate the model, and deploy the chatbot.

main.py