Update app.py

app.py

@@ -80,9 +80,9 @@ def process_paragraph_1_sent(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
                     selected_paragraph = stored_paragraphs_1[paragraph_index]
-                    sentiment = text_to_sentiment(selected_paragraph)
-
-                    return sentiment
+                    result = text_to_sentiment(selected_paragraph)
+                    formatted_results = "\n".join([f"{result['label']}: {result['score']:.2f}" for result in results])
+                    return formatted_results
                 except (IndexError, ValueError):
                     return "Error"
 def process_paragraph_1_sent_tone(paragraph):
@@ -113,9 +113,9 @@ def process_paragraph_2_sent(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
                     selected_paragraph = stored_paragraphs_2[paragraph_index]
-                    sentiment = text_to_sentiment(selected_paragraph)
-
-                    return sentiment
+                    result = text_to_sentiment(selected_paragraph)
+                    formatted_results = "\n".join([f"{result['label']}: {result['score']:.2f}" for result in results])
+                    return formatted_results
                 except (IndexError, ValueError):
                     return "Error"
 def process_paragraph_2_sent_tone(paragraph):
@@ -448,29 +448,30 @@ with gr.Blocks(theme='gradio/soft',js=js_func) as demo:
                 
                 selected_paragraph_1 = gr.Textbox(label="Selected Paragraph 1 Content", lines=4)
                 paragraph_1_dropdown.select(fn=show1, inputs = paragraph_1_dropdown, outputs=selected_paragraph_1)
-                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 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)")
-        
-                # 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_)
+                with gr.Group():
+                    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.Label(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 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)")
+            
+                    # 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():
@@ -478,32 +479,33 @@ with gr.Blocks(theme='gradio/soft',js=js_func) as demo:
         
                 selected_paragraph_2 = gr.Textbox(label="Selected Paragraph 2 Content", lines=4)
                 paragraph_2_dropdown.select(fn=show2, inputs = paragraph_2_dropdown, outputs=selected_paragraph_2)
-                # Display selected paragraph from PDF 2
-                selected_paragraph_2.change(fn=show2, 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 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)")
-        
-                # 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.Group():
+                    # Display selected paragraph from PDF 2
+                    selected_paragraph_2.change(fn=show2, 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 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)")
+            
+                    # 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"):