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(base) ➜  epub2anki git:(main) ✗ python app.py
INFO: Searching for database. This might take some time. You can speed this up by specifying a search path or directly entering the path to your database.
WARNING: The search will stop at the first hit, so please verify that the result is correct (for example in case there might be more than one Anki installation)
INFO: Loaded db from /Users/max/Library/Application Support/Anki2/User 1/collection.anki2
INFO: Loaded db from /Users/max/Library/Application Support/Anki2/User 1/collection.anki2
[Cocoa] Not implemented: MultilineTextInput.set_on_change()
INFO: Loaded db from /Users/max/Library/Application Support/Anki2/User 1/collection.anki2
Error in async handler: [E088] Text of length 3435600 exceeds maximum of 400000. The v2.x parser and NER models require roughly 1GB of temporary memory per 100,000 characters in the input. This means long texts may cause memory allocation errors. If you're not using the parser or NER, it's probably safe to increase the `nlp.max_length` limit. The limit is in number of characters, so you can check whether your inputs are too long by checking `len(text)`.
Traceback (most recent call last):
  File "/Users/max/anaconda3/lib/python3.7/site-packages/toga/handlers.py", line 25, in handler_with_cleanup
    await handler(interface, *args, **kwargs)
  File "app.py", line 270, in do_background_nlp_stuff
    out = await loop.run_in_executor(None, step_fun, screen._state)
  File "/Users/max/anaconda3/lib/python3.7/concurrent/futures/thread.py", line 57, in run
    result = self.fn(*self.args, **self.kwargs)
  File "app.py", line 178, in step_nlp_epub
    doc_epub = state["nlp_module"].lemmatize_doc(state["epub_contents"])
  File "/Users/max/Coding/python/epub2anki/nlp/french/nlp_french.py", line 19, in lemmatize_doc
    doc = model(partially_french_text)
  File "/Users/max/anaconda3/lib/python3.7/site-packages/spacy/language.py", line 439, in __call__
    Errors.E088.format(length=len(text), max_length=self.max_length)
ValueError: [E088] Text of length 3435600 exceeds maximum of 400000. The v2.x parser and NER models require roughly 1GB of temporary memory per 100,000 characters in the input. This means long texts may cause memory allocation errors. If you're not using the parser or NER, it's probably safe to increase the `nlp.max_length` limit. The limit is in number of characters, so you can check whether your inputs are too long by checking `len(text)`.