Update app.py

app.py

@@ -1,20 +1,13 @@
 import pandas as pd
 from transformers import pipeline
-from google.colab import files  # Only needed if running in Google Colab
 
 # Function to enhance title using Hugging Face model
 def generate_title_with_huggingface(description):
     result = generator(description, max_length=100, num_return_sequences=1)
     return result[0]['generated_text']
 
-# If running in Google Colab, use files.upload() to upload the CSV
-# For local environment, you can replace this with a file path directly
-uploaded = files.upload()
-
-# Assuming the file name is 'output.csv' after upload
-file_name = list(uploaded.keys())[0]
-
-# Load the CSV file
+# Load the CSV file directly (replace 'input.csv' with your actual file path)
+file_name = 'input.csv'  # Update this with the correct path to your CSV file
 df = pd.read_csv(file_name)
 
 # Initialize the text generation model (e.g., GPT-2)
@@ -35,5 +28,5 @@ df['Keywords'] = df['Description'].apply(generate_keywords)
 seo_output_file_path = 'seo_huggingface_filename_title_keywords.csv'
 df[['Filename', 'Title', 'Keywords']].to_csv(seo_output_file_path, index=False)
 
-# Download the resulting CSV file (if running in Colab)
-files.download(seo_output_file_path)
+# The output file will be saved in the current working directory
+print(f"File saved as {seo_output_file_path}")