abiabidali commited on
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f2f4bb0
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1 Parent(s): 763746b

Update app.py

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  1. app.py +4 -6
app.py CHANGED
@@ -1,16 +1,14 @@
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- # Install necessary packages
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- !pip install transformers pandas google-colab
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-
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  import pandas as pd
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  from transformers import pipeline
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- from google.colab import files
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  # Function to enhance title using Hugging Face model
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  def generate_title_with_huggingface(description):
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  result = generator(description, max_length=100, num_return_sequences=1)
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  return result[0]['generated_text']
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- # Upload the CSV file
 
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  uploaded = files.upload()
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  # Assuming the file name is 'output.csv' after upload
@@ -37,5 +35,5 @@ df['Keywords'] = df['Description'].apply(generate_keywords)
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  seo_output_file_path = 'seo_huggingface_filename_title_keywords.csv'
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  df[['Filename', 'Title', 'Keywords']].to_csv(seo_output_file_path, index=False)
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- # Download the resulting CSV file
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  files.download(seo_output_file_path)
 
 
 
 
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  import pandas as pd
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  from transformers import pipeline
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+ from google.colab import files # Only needed if running in Google Colab
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  # Function to enhance title using Hugging Face model
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  def generate_title_with_huggingface(description):
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  result = generator(description, max_length=100, num_return_sequences=1)
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  return result[0]['generated_text']
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+ # If running in Google Colab, use files.upload() to upload the CSV
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+ # For local environment, you can replace this with a file path directly
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  uploaded = files.upload()
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  # Assuming the file name is 'output.csv' after upload
 
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  seo_output_file_path = 'seo_huggingface_filename_title_keywords.csv'
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  df[['Filename', 'Title', 'Keywords']].to_csv(seo_output_file_path, index=False)
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+ # Download the resulting CSV file (if running in Colab)
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  files.download(seo_output_file_path)