How can I create a conversational bot that does not hallucinate for a specific set of content I point it to such as a text from a publicly facing website?
To create a conversational bot that does not hallucinate for a specific set of content, you can follow these steps:

Determine the scope of content: Define the specific set of content that the bot will be referencing, such as a text from a publicly facing website.

Prepare the training data: Clean and preprocess the content data, making sure it is free of any errors, irrelevant information, and duplicate data.

Choose an appropriate conversational AI model: There are various models for building conversational bots, including rule-based models, Retrieval-based models, and Generative models. Choose a model that best suits the requirement and scope of the content.

Train the model: Train the model on the prepared training data. The model will learn patterns and relationships in the data and generate responses based on the data.

Evaluate the model: Evaluate the performance of the model using metrics such as accuracy, precision, recall, and F1 score.

Fine-tune the model: If the performance of the model is not up to the desired level, fine-tune the model by adjusting the hyperparameters, changing the training data, or using a different model.

Integrate the model into the conversational platform: Integrate the model into a conversational platform, such as a chatbot, to make it accessible to users.

Monitor and improve the model: Regularly monitor the performance of the model and improve it by retraining and fine-tuning as necessary.

By following these steps, you can create a conversational bot that provides accurate and relevant responses to users while avoiding hallucinations.
How would you recommend collecting training data? What sort of options are there?