Update app.py

app.py

@@ -146,7 +146,7 @@ def process_and_compare(file1, sheet1, file2, sheet2):
     plt.savefig(file_path, format='png', bbox_inches='tight')
     plt.close()
 
-    return file_path
+    return file_path, stored_df1.Country.values.tolist()
 
 def find_sentences_with_keywords(text, keywords):
     # Split text into sentences using regular expression to match sentence-ending punctuation
@@ -194,8 +194,8 @@ def process_pdfs_and_analyze_sentiment(file1, file2, sheet):
     result_pdf2 = fin_ext_bis(text_pdf2)
     
     return result_pdf1, result_pdf2
-def change_choices(df):
-    return gr.update(choices=df.Country.values.tolist())
+#def change_choices(df):
+#    return gr.update(choices=df.Country.values.tolist())
     
 def generate_text(df, country, theme):
     # Filter the dataframe based on the country
@@ -320,7 +320,6 @@ with gr.Blocks() as demo:
             with gr.Column():
                 sentiment_results_pdf1 = gr.HighlightedText(label="Sentiment Analysis - PDF 1")
                 country_1_dropdown = gr.Dropdown(label="Select Country from Excel File 1")
-                country_1_dropdown.change(fn =change_choices, inputs= stored_df1, outputs= country_1_dropdown)
                 summarize_btn1_country = gr.Button("Summary for the selected country")
                 text_result_df1 = gr.Textbox(label="Sentence for excel file 1", lines=2)
                 summarize_btn1_country.click(fn=lambda country, theme: generate_text(stored_df1, country, theme),
@@ -330,7 +329,7 @@ with gr.Blocks() as demo:
                 sentiment_results_pdf2 = gr.HighlightedText(label="Sentiment Analysis - PDF 2")
     
         # Button to extract text from PDFs and perform sentiment analysis
-        b1.click(fn=process_and_compare, inputs=[file1, sheet, file2, sheet], outputs=result)
+        b1.click(fn=process_and_compare, inputs=[file1, sheet, file2, sheet], outputs={result,country_1_dropdown])
         b2.click(fn=process_pdfs_and_analyze_sentiment, inputs=[file1, file2, sheet], outputs=[sentiment_results_pdf1, sentiment_results_pdf2])