Update app.py

app.py

@@ -301,7 +301,25 @@ stored_paragraphs_2 = []
 stored_df1 = []
 stored_df2 = []
 
+# CSS for custom background colors
+custom_css = """
+<style>
+    .pdf1-analysis {
+        background-color: #f0f8ff;  /* Light blue background for PDF1 */
+        padding: 20px;
+        border-radius: 10px;
+    }
+    
+    .pdf2-analysis {
+        background-color: #ffe4e1;  /* Light pink background for PDF2 */
+        padding: 20px;
+        border-radius: 10px;
+    }
+</style>"""
+
 with gr.Blocks() as demo:
+    gr.HTML(custom_css)
+    
     with gr.Tab("Methodology"):
         gr.Markdown("""
         ## Macro-economy Adverse Scenario Comparison from EBA Reports
@@ -349,70 +367,70 @@ with gr.Blocks() as demo:
                     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])
-        
+        gr.Markdown("---")
         with gr.Row():
-            # Process the selected paragraph from PDF 1
+        # PDF 1 Analysis section with custom background
             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 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.Box():
+                    gr.Markdown("<div class='pdf1-analysis'><h3>PDF 1 Analysis</h3></div>")
+                    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 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_)
+    
+            # PDF 2 Analysis section with custom background
             with gr.Column():
-                gr.Markdown("### PDF 2 Analysis")
-        
-                selected_paragraph_2 = gr.Textbox(label="Selected Paragraph 2 Content", lines=4)
-        
-                # 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 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.Box():
+                    gr.Markdown("<div class='pdf2-analysis'><h3>PDF 2 Analysis</h3></div>")
+                    selected_paragraph_2 = gr.Textbox(label="Selected Paragraph 2 Content", lines=4)
+    
+                    # 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 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"):
         # New tab content goes here