Related to this, I also get C++ guessed if I open a new untitled file and type:
<
yes just one character. I was attempting to type <html which does guess correctly, but I feel like those first few characters that guess C++ is a little much.
For my issue, maybe we wait for like 5 characters at least?
If this is a new user doing their homework, they are going to need to save this file to run it
About ~1 yr ago, @isidorn added a “save on run” feature. The intent (my understanding) is that this was added because a lot of new users were “running” untitled files without saving them to an actual concrete file and extensions were having to handle this case (and some weren’t causing confusion to the user). This was mostly the case because new users weren’t quite grasping that an untitled file wasn’t a real file on disk.
Added a minimum amount of text used when guessing which might help here. Getting a confidence score out of the model is a better fix.
I wonder if we should revisit how we prompt for ext recommendations in untitled files. A "This Looks Like C++, Would you like to install relevant extensions? Yes / No / Not C++ " would be good for analysis of model performance as well.
The model now has some better confidence heuristics built in.
Related to this, I also get C++ guessed if I open a new untitled file and type:
yes just one character. I was attempting to type
<htmlwhich does guess correctly, but I feel like those first few characters that guess C++ is a little much.For my issue, maybe we wait for like 5 characters at least?
About ~1 yr ago, @isidorn added a “save on run” feature. The intent (my understanding) is that this was added because a lot of new users were “running” untitled files without saving them to an actual concrete file and extensions were having to handle this case (and some weren’t causing confusion to the user). This was mostly the case because new users weren’t quite grasping that an untitled file wasn’t a real file on disk.
Maybe @isidorn has some thoughts on this
Added a minimum amount of text used when guessing which might help here. Getting a confidence score out of the model is a better fix.
I wonder if we should revisit how we prompt for ext recommendations in untitled files. A "This Looks Like C++, Would you like to install relevant extensions? Yes / No / Not C++ " would be good for analysis of model performance as well.