Feature Suggestion: Incorporate an AI-powered tool, such as ChatGPT, to automatically generate book summaries, conduct analysis, and create descriptive tags.
Purpose: The goal of this feature would be to offer an efficient, AI-led way to analyze ebooks, producing succinct summaries and more PERSONALIZED & in-depth tags for each book/research paper in a library.
Possible workflow:
The user chooses a book or several books for analysis.
Clicks on a new 'Analyze' button.
A prompt box appears asking the user for an analytical direction or focus.
The AI performs the analysis based on the provided prompt, and as a result, it crafts a summary and produces thematic tags.
The AI then stores this newly generated summary in a secondary abstract field and assigns the new tags to the book(s).
The addition of this feature could dramatically improve Calibre's metadata handling, especially for sizable libraries. It would also make the process of adding rich, useful tags to ebooks simpler and more systematic, in place of the current method which can sometimes lead to an untidy accumulation of varied and subjective tags.
Furthermore, it would significantly aid targeted research within the library, adjusting according to the user's distinct interests and focus. For example, users could effortlessly identify common themes, discern patterns in an author's writing style, detect genre trends, and much more, across their entire ebook collection.
I firmly believe that this feature would be highly beneficial for researchers like myself, students, and passionate readers who are looking to gain more insights from their ebook collection and browse it more efficiently.
I kindly request you to consider this feature suggestion. I am confident that it would offer a fresh perspective to the Calibre user experience, while keeping up with the latest advancements in AI and machine learning.
I'm eager to hear your thoughts about this feature and any plans you might have to implement it.
