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View Code? Open in Web Editor NEWA poem generator based on text generation using GRU
Home Page: https://deep-frost.herokuapp.com/
A poem generator based on text generation using GRU
Home Page: https://deep-frost.herokuapp.com/
This project currently uses PyQt5 for GUI, we would like to use flask for the GUI instead, to host the model.
The GUI should contain two text boxes: one for the user to enter the rhyming scheme and another for them to enter the first line. It should also contain a button Generate which should display the poem on clicking. The new GUI should provide all the functionality of the existing one.
The GUI at present looks as follows:
I tested the app a bit and noticed that I get status 500: Internal Server Error
on certain inputs.
Some of the inputs:
Rhyme scheme: AABBAABB
First line: i walk a lonely askdh
(crashes)
First line: i walk a askldhsal road
(does NOT crash)
First line: I have much stonks
(crashes)
The error is: KeyError: "word 'askdh' not in vocabulary"
And occurs at line 61 here:
Lines 60 to 62 in dea2405
One solution would be to wrap that line in a try-except (or use if word in word_vec.vocab:
) and return an error to the front-end stating that the last word of the sentence could not be found in the vocabulary.
Another solution would be to skip that last word and consider the second last word, and if that fails, the third last word... and so on.
Ofcourse the best solution would be to use a character-based model or token-based (using a tokenizer such as PTB tokenizer) model, but that would need quite a bit of re-factoring and more resources for training.
Currently the poem generator generates the poem based on length of the rhyming scheme
It could be useful if a option was provided allowing the user to select number of lines in the poem
Improve the existing GUI by adding styles and theme to make it look modern. No changes in functionality of the GUI is required, only improve the style of the existing GUI.
The GUI would be better if made responsive for mobile devices!
The application uses Tensorflow 1.4 and is hence outdated. Would be great to refactor the code to use Tensorflow 2.0.
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