File size: 1,438 Bytes
882d84f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 |
#!/usr/bin/env python
# coding: utf-8
# In[1]:
from gramformerjohn import Gramformer
import gradio as gr
import spacy
# In[2]:
gf = Gramformer(models = 1, use_gpu = False)
# In[3]:
name = "how are you"
# In[13]:
from readability import Readability
import textstat
def reading_score(sentences):
return Readability(sentences).flesch()
#
# In[5]:
def levenstein_score(correct_output, sentences):
max_wrong = max(len(correct_output), len(sentences))
actual_wrong = distance(correct_output, sentences)
return (max_wrong - actual_wrong)/max_wrong
# In[28]:
import gradio as gr
import textstat
from Levenshtein import distance
def correct_sentence(sentences):
if(len(sentences) == 0):
return 'Output','-', '-', "Please Input Text."
sentences = sentences.strip()
corrected = gf.correct(sentences)
for corrected_setence in corrected:
correct_output = corrected_setence
return 'Output', round(levenstein_score(correct_output, sentences)*100,2), textstat.flesch_reading_ease(sentences), gf.highlight(correct_output,sentences)
demo = gr.Interface(
fn=correct_sentence,
inputs=gr.Textbox(label = "Input", lines=2, placeholder="Text Here..."),
outputs=[gr.Markdown("Output"), gr.Textbox(label = "Grammar Fluency Score"), gr.Textbox(label = "Flesch Reading Score"), gr.Markdown()],
allow_flagging="never"
)
demo.launch(share = True)
# In[ ]:
# In[ ]:
# In[ ]:
|