Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -6,6 +6,7 @@ import subprocess
|
|
6 |
import nltk
|
7 |
from nltk.corpus import wordnet
|
8 |
import language_tool_python
|
|
|
9 |
tool = language_tool_python.LanguageTool('en-US')
|
10 |
|
11 |
# Function to correct tense errors using LanguageTool
|
@@ -15,10 +16,6 @@ def correct_tense_errors(text):
|
|
15 |
corrected_text = language_tool_python.utils.correct(text, matches)
|
16 |
return corrected_text
|
17 |
|
18 |
-
|
19 |
-
|
20 |
-
|
21 |
-
|
22 |
# Initialize the English text classification pipeline for AI detection
|
23 |
pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-roberta")
|
24 |
|
@@ -64,16 +61,6 @@ def capitalize_sentences_and_nouns(text):
|
|
64 |
|
65 |
return ' '.join(corrected_text)
|
66 |
|
67 |
-
# Function to correct tense errors in a sentence (Tense Correction)
|
68 |
-
#def correct_tense_errors(text):
|
69 |
-
# doc = nlp(text)
|
70 |
-
### if token.pos_ == "VERB" and token.dep_ in {"aux", "auxpass"}:
|
71 |
-
## lemma = wordnet.morphy(token.text, wordnet.VERB) or token.text
|
72 |
-
# corrected_text.append(lemma)
|
73 |
-
# else:
|
74 |
-
# corrected_text.append(token.text)
|
75 |
-
# return ' '.join(corrected_text)
|
76 |
-
|
77 |
# Function to correct singular/plural errors (Singular/Plural Correction)
|
78 |
def correct_singular_plural_errors(text):
|
79 |
doc = nlp(text)
|
@@ -150,7 +137,7 @@ def paraphrase_with_spacy_nltk(text):
|
|
150 |
|
151 |
# Combined function: Paraphrase -> Grammar Correction -> Capitalization (Humanifier)
|
152 |
def paraphrase_and_correct(text):
|
153 |
-
|
154 |
|
155 |
# Step 2: Apply grammatical corrections on the paraphrased text
|
156 |
corrected_text = correct_article_errors(paraphrased_text)
|
|
|
6 |
import nltk
|
7 |
from nltk.corpus import wordnet
|
8 |
import language_tool_python
|
9 |
+
|
10 |
tool = language_tool_python.LanguageTool('en-US')
|
11 |
|
12 |
# Function to correct tense errors using LanguageTool
|
|
|
16 |
corrected_text = language_tool_python.utils.correct(text, matches)
|
17 |
return corrected_text
|
18 |
|
|
|
|
|
|
|
|
|
19 |
# Initialize the English text classification pipeline for AI detection
|
20 |
pipeline_en = pipeline(task="text-classification", model="Hello-SimpleAI/chatgpt-detector-roberta")
|
21 |
|
|
|
61 |
|
62 |
return ' '.join(corrected_text)
|
63 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
64 |
# Function to correct singular/plural errors (Singular/Plural Correction)
|
65 |
def correct_singular_plural_errors(text):
|
66 |
doc = nlp(text)
|
|
|
137 |
|
138 |
# Combined function: Paraphrase -> Grammar Correction -> Capitalization (Humanifier)
|
139 |
def paraphrase_and_correct(text):
|
140 |
+
paraphrased_text = paraphrase_with_spacy_nltk(text)
|
141 |
|
142 |
# Step 2: Apply grammatical corrections on the paraphrased text
|
143 |
corrected_text = correct_article_errors(paraphrased_text)
|