I always ask every model to implement a Qt QSyntaxHighlighter subclass for syntax highlighting code and a QAbstractListModel subclass that parses markdown into blocks - in C++, both implemented using tree sitter. It's sounds like a coding problem but it's much more a reasoning problem of how to combine the two APIs and is out of band of the training data. I test it with multiple levels of prompt fidelity that I have built up watching the many mistakes past models have made and o3-mini-high and o1 can usually get it done within a few iterations.

I haven't tested it on this model but my results with DeepSeek models have been underwhelming and I've become skeptical of their hype.