shevadesuyash commited on
Commit
42bee4e
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1 Parent(s): ca7aa50

Update code: fix app.py, paragraph_checker.py and add README config

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Files changed (3) hide show
  1. README.md +26 -0
  2. app.py +2 -4
  3. paragraph_checker.py +4 -1
README.md ADDED
@@ -0,0 +1,26 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ title: Convomate Paragraph Checker
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+ emoji: πŸ“
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+ colorFrom: blue
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+ colorTo: purple
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+ sdk: docker
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+ sdk_version: "3.8.2"
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+ app_file: app.py
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+ pinned: false
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+ ---
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+
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+ # πŸš€ Convomate Paragraph Checker
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+
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+ This Space runs a Flask app for grammar and tense correction using:
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+
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+ - `language_tool_python` for grammar fixes
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+ - T5 Transformer (`Vamsi/T5_Paraphrase_Paws`) for tense rewriting
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+
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+ ### πŸš€ How to Use
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+
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+ Send a POST request to `/correct_text` with:
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+
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+ ```json
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+ {
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+ "paragraph": "your incorrect sentence here"
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+ }
app.py CHANGED
@@ -1,5 +1,5 @@
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  from flask import Flask, request, jsonify
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- from paragraph_checker import correct_paragraph
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  app = Flask(__name__)
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@@ -30,8 +30,6 @@ def correct_text():
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  }), 500
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  if __name__ == '__main__':
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- # Initialize models at startup
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- from paragraph_checker import initialize_models
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  print("Loading ML models...")
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  try:
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  initialize_models()
@@ -39,4 +37,4 @@ if __name__ == '__main__':
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  except Exception as e:
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  print(f"Error loading models: {str(e)}")
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- app.run(host="0.0.0.0", port=5001, debug=True)
 
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  from flask import Flask, request, jsonify
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+ from paragraph_checker import correct_paragraph, initialize_models
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  app = Flask(__name__)
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  }), 500
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  if __name__ == '__main__':
 
 
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  print("Loading ML models...")
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  try:
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  initialize_models()
 
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  except Exception as e:
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  print(f"Error loading models: {str(e)}")
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+ app.run(host="0.0.0.0", port=5001, debug=True)
paragraph_checker.py CHANGED
@@ -1,3 +1,6 @@
 
 
 
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  import language_tool_python
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  from transformers import T5ForConditionalGeneration, T5Tokenizer
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@@ -64,4 +67,4 @@ def correct_paragraph(text):
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  fully_corrected = tense_correction(grammatically_correct)
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  print("After Grammar + Tense Correction:", fully_corrected)
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- return fully_corrected
 
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+ import os
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+ os.environ['TRANSFORMERS_CACHE'] = '/tmp/huggingface'
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+
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  import language_tool_python
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  from transformers import T5ForConditionalGeneration, T5Tokenizer
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  fully_corrected = tense_correction(grammatically_correct)
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  print("After Grammar + Tense Correction:", fully_corrected)
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+ return fully_corrected