Update app.py

app.py

@@ -325,62 +325,93 @@ with gr.Blocks() as demo:
         - For a selected country and topic, describe the adverse growth rate trend over three years using the [**google/flan-t5-base**](https://huggingface.co/google/flan-t5-base).
         """)
     with gr.Tab("Financial Report Text Analysis"):
-        gr.Markdown("## Financial Report Paragraph Selection and Analysis on adverse macro-economy scenario")
+        gr.Markdown("## Financial Report Paragraph Selection and Analysis on Adverse Macro-Economy Scenario")
 
         with gr.Row():
             # Upload PDFs
             with gr.Column():
+                gr.Markdown("### Step 1: Upload PDF Files")
                 pdf1 = gr.Dropdown(choices=get_pdf_files(PDF_FOLDER), label="Select PDF 1")
                 pdf2 = gr.Dropdown(choices=get_pdf_files(PDF_FOLDER), label="Select PDF 2")
-
+        
             with gr.Column():
+                gr.Markdown("### Step 2: Extract and Display Paragraphs")
                 b1 = gr.Button("Extract and Display Paragraphs")
                 paragraph_1_dropdown = gr.Dropdown(label="Select Paragraph from PDF 1")
                 paragraph_2_dropdown = gr.Dropdown(label="Select Paragraph from PDF 2")
-
+        
+                # Extract paragraphs from PDFs and update dropdowns
                 def update_paragraphs(pdf1, pdf2):
                     global stored_paragraphs_1, stored_paragraphs_2
                     stored_paragraphs_1, stored_paragraphs_2 = extract_and_paragraph(pdf1, pdf2, True)
                     updated_dropdown_1 = [f"Paragraph {i+1}: {p[:100]}..." for i, p in enumerate(stored_paragraphs_1)]
                     updated_dropdown_2 = [f"Paragraph {i+1}: {p[:100]}..." for i, p in enumerate(stored_paragraphs_2)]
                     return gr.update(choices=updated_dropdown_1), gr.update(choices=updated_dropdown_2)
-
+        
                 b1.click(fn=update_paragraphs, inputs=[pdf1, pdf2], outputs=[paragraph_1_dropdown, paragraph_2_dropdown])
-
+        
         with gr.Row():
             # Process the selected paragraph from PDF 1
             with gr.Column():
                 gr.Markdown("### PDF 1 Analysis")
+        
                 selected_paragraph_1 = gr.Textbox(label="Selected Paragraph 1 Content", lines=4)
+        
                 summarize_btn1 = gr.Button("Summarize Text from PDF 1")
                 summary_textbox_1 = gr.Textbox(label="Summary for PDF 1", lines=2)
+        
+                # Summarize the selected paragraph from PDF 1
                 summarize_btn1.click(fn=lambda p: process_paragraph_1_sum(p), inputs=paragraph_1_dropdown, outputs=summary_textbox_1)
+        
                 sentiment_btn1 = gr.Button("Classify Financial Tone from PDF 1")
                 sentiment_textbox_1 = gr.Textbox(label="Classification for PDF 1", lines=1)
+        
+                # Classify the financial tone of the selected paragraph from PDF 1
                 sentiment_btn1.click(fn=lambda p: process_paragraph_1_sent(p), inputs=paragraph_1_dropdown, outputs=sentiment_textbox_1)
-                analyze_btn1 = gr.Button("Analyze Financial Tone on each sentence with yiyanghkust/finbert-tone")
+        
+                analyze_btn1 = gr.Button("Analyze Financial Tone on each sentence with FinBERT-tone")
                 fin_spans_1 = gr.HighlightedText(label="Financial Tone Analysis for PDF 1")
+        
+                # Analyze financial tone on each sentence using FinBERT-tone
                 analyze_btn1.click(fn=lambda p: process_paragraph_1_sent_tone(p), inputs=paragraph_1_dropdown, outputs=fin_spans_1)
+        
                 analyze_btn1_ = gr.Button("Analyze Financial Tone on each sentence with ProsusAI/finbert")
-                fin_spans_1_ = gr.HighlightedText(label="Financial Tone Analysis for PDF 1 bis")
+                fin_spans_1_ = gr.HighlightedText(label="Financial Tone Analysis for PDF 1 (Bis)")
+        
+                # Analyze financial tone using ProsusAI/finbert
                 analyze_btn1_.click(fn=lambda p: process_paragraph_1_sent_tone_bis(p), inputs=paragraph_1_dropdown, outputs=fin_spans_1_)
-
+        
             # Process the selected paragraph from PDF 2
             with gr.Column():
                 gr.Markdown("### PDF 2 Analysis")
+        
                 selected_paragraph_2 = gr.Textbox(label="Selected Paragraph 2 Content", lines=4)
-                selected_paragraph_2.change(show, paragraph_2_dropdown, selected_paragraph_2)
+        
+                # Display selected paragraph from PDF 2
+                selected_paragraph_2.change(fn=show, inputs=paragraph_2_dropdown, outputs=selected_paragraph_2)
+        
                 summarize_btn2 = gr.Button("Summarize Text from PDF 2")
                 summary_textbox_2 = gr.Textbox(label="Summary for PDF 2", lines=2)
+        
+                # Summarize the selected paragraph from PDF 2
                 summarize_btn2.click(fn=lambda p: process_paragraph_2_sum(p), inputs=paragraph_2_dropdown, outputs=summary_textbox_2)
+        
                 sentiment_btn2 = gr.Button("Classify Financial Tone from PDF 2")
                 sentiment_textbox_2 = gr.Textbox(label="Classification for PDF 2", lines=1)
+        
+                # Classify the financial tone of the selected paragraph from PDF 2
                 sentiment_btn2.click(fn=lambda p: process_paragraph_2_sent(p), inputs=paragraph_2_dropdown, outputs=sentiment_textbox_2)
-                analyze_btn2 = gr.Button("Analyze Financial Tone on each sentence with yiyanghkust/finbert-tone")
+        
+                analyze_btn2 = gr.Button("Analyze Financial Tone on each sentence with FinBERT-tone")
                 fin_spans_2 = gr.HighlightedText(label="Financial Tone Analysis for PDF 2")
+        
+                # Analyze financial tone on each sentence using FinBERT-tone for PDF 2
                 analyze_btn2.click(fn=lambda p: process_paragraph_2_sent_tone(p), inputs=paragraph_2_dropdown, outputs=fin_spans_2)
+        
                 analyze_btn2_ = gr.Button("Analyze Financial Tone on each sentence with ProsusAI/finbert")
-                fin_spans_2_ = gr.HighlightedText(label="Financial Tone Analysis for PDF 2 bis")
+                fin_spans_2_ = gr.HighlightedText(label="Financial Tone Analysis for PDF 2 (Bis)")
+        
+                # Analyze financial tone using ProsusAI/finbert for PDF 2
                 analyze_btn2_.click(fn=lambda p: process_paragraph_2_sent_tone_bis(p), inputs=paragraph_2_dropdown, outputs=fin_spans_2_)
 
     with gr.Tab("Financial Report Table Analysis"):