I have use these tools for creating a book recommender

PyCharm Professional (as primary IDE),

BLACKBOX AI IDE (secondary IDE),

Python (Primary Programming Language) ,

LangChain (for LLM integration and chaining) ,

Gradio (front-end) ,

Gemini API (for search and recommendations) ,

Pandas (handling book data) ,

Seaborn (for Data Visualisation),

Hugging Face model (for Zero-Shot Text Classification)

After using the Blackbox IDE for a while i would make things clean and let student use the free tier rather than direct asking for upgrading to Pro. (this can easily remove the upgrade pressure)

During the selection of LLM models there should be description for each model, so student can use perfect model for their project requirement.

After creation of the first draft of the project, most likely it will have bugs and issues specially for free-tier plan, to solve those bugs and issues a bug solver/explainer (debug buddy) can help a lot by which student could understand the approach that the model has used.

File directory selection should be more visible and after the prompt is given, model must ask the user that which directory must project be created otherwise it would make a mess by creating project in unlikely location.

By solving these issues Student can use the BLACKBOX AI more efficiently, more faster, and with greater understanding.