Update app.py

app.py

@@ -25,7 +25,7 @@ st.write("""
 
 st.header('Input')
 jobs_data= job_desc_pdf()
-resume_df= resume_pdf()
+resume_data= resume_pdf()
 
 
 setup_nltk_resources()
@@ -40,3 +40,30 @@ jobs_data['processed_description'] = jobs_data['description'].apply(preprocess_t
 jobs_data_cleaned = drop_duplicates(jobs_data, column_name='description')
 
 
+resume_data['processed_resume'] = resume_data['Resume'].apply(preprocess_text)
+resume_data_cleaned = drop_duplicates(resume_data, column_name='Resume')
+
+jobs_data_cleaned_with_tokens = add_token_count_column(jobs_data_cleaned, column_name='processed_description')
+resume_data_cleaned_with_tokens = add_token_count_column(resume_data_cleaned, column_name='processed_resume')
+
+# Dropping unnecessary columns from jobs data
+jobs_data_final = jobs_data_cleaned_with_tokens[['processed_description', 'token_count']]
+
+# Dropping unnecessary columns from resume data
+resume_data_final = resume_data_cleaned_with_tokens[['processed_resume', 'token_count']]
+
+
+summarizer = TextSummarizer("geekradius/bart-large-cnn-fintetuned-samsum-repo")
+
+# Summarize the top 100 'processed_description' of jobs_data_final
+top_jobs_data = jobs_data_final.head(100)
+
+# Summariz jobs description
+jobs_data_summarized = batch_summarize(top_jobs_data, 'processed_description', summarizer, batch_size=10, output_col='summarized_description')
+
+# Summarize all 'processed_resume' in resume_data_final
+resume_data_summarized = batch_summarize(resume_data_final, 'processed_resume', summarizer, batch_size=10, output_col='summarized_resume')
+
+
+
+