Priyanhsu commited on
Commit
a3f43bd
·
1 Parent(s): 5611d17

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +19 -30
app.py CHANGED
@@ -1,30 +1,20 @@
1
-
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- import nltk
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  from nltk.tokenize import sent_tokenize
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  from language_tool_python import LanguageTool
 
 
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- nltk.download('punkt')
 
 
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  def grammar_check(text):
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- tool = LanguageTool('en-US')
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- sentences = sent_tokenize(text)
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- corrected_sentences = []
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- for sentence in sentences:
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- matches = tool.check(sentence)
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- corrected_sentence = tool.correct(sentence)
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- corrected_sentences.append(corrected_sentence)
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- corrected_text = ' '.join(corrected_sentences)
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- return corrected_text
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-
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- nltk.download('vader_lexicon')
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-
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- import nltk
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- from nltk.sentiment import SentimentIntensityAnalyzer
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  def analyze_sentiment(text):
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- sia = SentimentIntensityAnalyzer()
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  sentiment_scores = sia.polarity_scores(text)
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-
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  # Positive sentiment: score > 0
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  # Neutral sentiment: score = 0
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  # Negative sentiment: score < 0
@@ -35,21 +25,20 @@ def analyze_sentiment(text):
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  sentiment = "Neutral"
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  else:
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  sentiment = "Negative"
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-
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  return sentiment
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- def count_words(text):
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- words = text.split()
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- total_words = len(words)
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- return total_words
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  def CsharpGrammarly(text):
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- result1= grammar_check(text)
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- sentiment_result= analyze_sentiment(result1)
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- total_words= count_words(result1)
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- return result1,sentiment_result,total_words
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- import gradio as gr
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  iface = gr.Interface(
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  fn=CsharpGrammarly,
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  inputs=gr.inputs.Textbox(placeholder="Enter your text here..."),
@@ -62,4 +51,4 @@ iface = gr.Interface(
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  description="Correct spelling, grammar, and analyze sentiment."
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  )
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- iface.launch()
 
 
 
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  from nltk.tokenize import sent_tokenize
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  from language_tool_python import LanguageTool
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+ from nltk.sentiment import SentimentIntensityAnalyzer
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+ import gradio as gr
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+ # Initialize LanguageTool object outside the function
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+ tool = LanguageTool('en-US')
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+ sia = SentimentIntensityAnalyzer()
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  def grammar_check(text):
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+ matches = tool.check(text)
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+ corrected_sentences = tool.correct(text)
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+ return corrected_sentences
 
 
 
 
 
 
 
 
 
 
 
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  def analyze_sentiment(text):
 
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  sentiment_scores = sia.polarity_scores(text)
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+
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  # Positive sentiment: score > 0
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  # Neutral sentiment: score = 0
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  # Negative sentiment: score < 0
 
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  sentiment = "Neutral"
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  else:
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  sentiment = "Negative"
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+
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  return sentiment
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+ def sentence_generator(text):
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+ sentences = sent_tokenize(text)
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+ for sentence in sentences:
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+ yield sentence
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  def CsharpGrammarly(text):
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+ corrected_sentences = grammar_check(text)
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+ sentiment_result = analyze_sentiment(corrected_sentences)
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+ total_words = len(text.split())
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+ return corrected_sentences, sentiment_result, total_words
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  iface = gr.Interface(
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  fn=CsharpGrammarly,
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  inputs=gr.inputs.Textbox(placeholder="Enter your text here..."),
 
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  description="Correct spelling, grammar, and analyze sentiment."
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  )
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+ iface.launch()