Prodigy Interface: text not visible

[aph61]

Hi,
I do the food demo (16.03.2020) but once I start-up the server the proposed terms are not visible in the text bar (right window, top bar). When I select or reject the unknown word it does show the word I accepted/rejected correctly in the lhs history. You can find numerous hacks around it (check the score & sense), but that's not the idea. The terms itself are stored correctly in the dBase, and the conversion to patterns also works fine.

I have the latest version of all SW. The model file is different though. It's not ./s2v_reddit_2015_md, but s2v_reddit_2015_md/s2v_old

so, confused. What do I do wrong?

Running Ubuntu 18.02, Prodigy 2.9.9

[ines (Ines Montani)]

Hi! I think you might be hitting this:

sense2vec recipes for prodigy

Okay, so this is very mysterious, but I think I might have figured out what's happening here: Does the prodigy.json used in your Docker container by any chance specify a "html_template" value? The sense2vec recipes use the a custom "html_template" to define how to display the word and optional sense in the UI. The global or local prodigy.json lets you override defaults defined in recipes (which can make sense for stuff like styling and other behaviours). But if it's overriding something like t…

Check if your prodigy.json contains an "html_template" value and if so, remove it, because it'd otherwise overwrite the template used in the recipe. I've already added a warning for this in the upcoming Prodigy v1.10, so Prodigy will tell you if your config is overwriting something it probably shouldn't.

[aph61]

Hi Ines,

your suggestion did the trick. I removed html_template entry from the config file.

Thanks,

Andreas

[ines (Ines Montani)]

Just released Prodigy v1.10, which will now show a warning in cases like this.

Out now: Prodigy v1.10 (plus new video!)

Prodigy v1.10 is out now And it includes a bunch of cool new features, including dependency and relation annotation, audio and video annotation, an enhanced manual image UI, more settings for NER annotation, including character-based highlighting and a cool example workflow for creating training data for fine-tuning transformer models, new recipe callbacks for validating answers at runtime and for modifying examples before the database, new settings for UI customisation, and lots more! Th…