Update app.py

app.py

@@ -3,7 +3,6 @@ import gradio as gr
 from transformers import pipeline
 import spacy
 import lib.read_pdf
-
 # Initialize spaCy model
 nlp = spacy.load('en_core_web_sm')
 nlp.add_pipe('sentencizer')
@@ -71,72 +70,77 @@ with gr.Blocks() as demo:
     gr.Markdown("## Financial Report Paragraph Selection and Analysis")
 
     with gr.Row():
-        # Layout for PDF 1 and PDF 2 side by side
+        # Upload PDFs
         with gr.Column():
-            gr.Markdown("### PDF 1 Analysis")
             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():
             b1 = gr.Button("Extract and Display Paragraphs")
             paragraph_1_dropdown = gr.Dropdown(label="Select Paragraph from PDF 1")
-            selected_paragraph_1 = gr.Textbox(label="Selected Paragraph 1 Content", lines=4)
-            summary_textbox_1 = gr.Textbox(label="Summary for PDF 1", lines=4)
-            sentiment_textbox_1 = gr.Textbox(label="Classification for PDF 1", lines=4)
-            fin_spans_1 = gr.HighlightedText(label="Financial Tone Analysis for PDF 1")
+            paragraph_2_dropdown = gr.Dropdown(label="Select Paragraph from PDF 2")
 
             def update_paragraphs(pdf1, pdf2):
                 global stored_paragraphs_1, stored_paragraphs_2
                 stored_paragraphs_1, stored_paragraphs_2 = extract_and_summarize(pdf1, pdf2)
                 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)
-
-            def process_paragraph_1(paragraph):
-                try:
-                    paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_1[paragraph_index]
-                    summary = summarize_text(selected_paragraph)
-                    sentiment = text_to_sentiment(selected_paragraph)
-                    fin_spans = fin_ext(selected_paragraph)
-                    return selected_paragraph, summary, sentiment, fin_spans
-                except (IndexError, ValueError):
-                    return "Invalid selection", "Error", "Error", []
+                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])
-            summarize_btn1 = gr.Button("Summarize Text from PDF 1")
-            sentiment_btn1 = gr.Button("Classify Financial Tone from PDF 1")
-            analyze_btn1 = gr.Button("Analyze Financial Tone and FLS")
 
-            summarize_btn1.click(fn=lambda p: process_paragraph_1(p)[1], inputs=paragraph_1_dropdown, outputs=summary_textbox_1)
-            sentiment_btn1.click(fn=lambda p: process_paragraph_1(p)[2], inputs=paragraph_1_dropdown, outputs=sentiment_textbox_1)
-            analyze_btn1.click(fn=lambda p: process_paragraph_1(p)[3], inputs=paragraph_1_dropdown, outputs=fin_spans_1)
+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")
+        sentiment_btn1 = gr.Button("Classify Financial Tone from PDF 1")
+        summary_textbox_1 = gr.Textbox(label="Summary for PDF 1", lines=4)
+        sentiment_textbox_1 = gr.Textbox(label="Classification for PDF 1", lines=4)
+        fin_spans_1 = gr.HighlightedText(label="Financial Tone Analysis for PDF 1")
+
+        def process_paragraph_1(paragraph):
+            try:
+                paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
+                selected_paragraph = stored_paragraphs_1[paragraph_index]
+                summary = summarize_text(selected_paragraph)
+                sentiment = text_to_sentiment(selected_paragraph)
+                fin_spans = fin_ext(selected_paragraph)
+                return selected_paragraph, summary, sentiment, fin_spans
+            except (IndexError, ValueError):
+                return "Invalid selection", "Error", "Error", []
+
+        summarize_btn1.click(fn=lambda p: process_paragraph_1(p)[1], inputs=paragraph_1_dropdown, outputs=summary_textbox_1)
+        sentiment_btn1.click(fn=lambda p: process_paragraph_1(p)[2], inputs=paragraph_1_dropdown, outputs=sentiment_textbox_1)
+        analyze_btn1 = gr.Button("Analyze Financial Tone and FLS")
+        analyze_btn1.click(fn=lambda p: process_paragraph_1(p)[3], 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)
+        summarize_btn2 = gr.Button("Summarize Text from PDF 2")
+        sentiment_btn2 = gr.Button("Classify Financial Tone from PDF 2")
+        summary_textbox_2 = gr.Textbox(label="Summary for PDF 2", lines=4)
+        sentiment_textbox_2 = gr.Textbox(label="Classification for PDF 2", lines=4)
+        fin_spans_2 = gr.HighlightedText(label="Financial Tone Analysis for PDF 2")
+
+        def process_paragraph_2(paragraph):
+            try:
+                paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
+                selected_paragraph = stored_paragraphs_2[paragraph_index]
+                summary = summarize_text(selected_paragraph)
+                sentiment = text_to_sentiment(selected_paragraph)
+                fin_spans = fin_ext(selected_paragraph)
+                return selected_paragraph, summary, sentiment, fin_spans
+            except (IndexError, ValueError):
+                return "Invalid selection", "Error", "Error", []
+
+        summarize_btn2.click(fn=lambda p: process_paragraph_2(p)[1], inputs=paragraph_2_dropdown, outputs=summary_textbox_2)
+        sentiment_btn2.click(fn=lambda p: process_paragraph_2(p)[2], inputs=paragraph_2_dropdown, outputs=sentiment_textbox_2)
+        analyze_btn2 = gr.Button("Analyze Financial Tone and FLS")
+        analyze_btn2.click(fn=lambda p: process_paragraph_2(p)[3], inputs=paragraph_2_dropdown, outputs=fin_spans_2)
 
-        with gr.Column():
-            gr.Markdown("### PDF 2 Analysis")
-            pdf2 = gr.Dropdown(choices=get_pdf_files(PDF_FOLDER), label="Select PDF 2")
-            b2 = gr.Button("Extract and Display Paragraphs")
-            paragraph_2_dropdown = gr.Dropdown(label="Select Paragraph from PDF 2")
-            selected_paragraph_2 = gr.Textbox(label="Selected Paragraph 2 Content", lines=4)
-            summary_textbox_2 = gr.Textbox(label="Summary for PDF 2", lines=4)
-            sentiment_textbox_2 = gr.Textbox(label="Classification for PDF 2", lines=4)
-            fin_spans_2 = gr.HighlightedText(label="Financial Tone Analysis for PDF 2")
-
-            def process_paragraph_2(paragraph):
-                try:
-                    paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_2[paragraph_index]
-                    summary = summarize_text(selected_paragraph)
-                    sentiment = text_to_sentiment(selected_paragraph)
-                    fin_spans = fin_ext(selected_paragraph)
-                    return selected_paragraph, summary, sentiment, fin_spans
-                except (IndexError, ValueError):
-                    return "Invalid selection", "Error", "Error", []
-
-            b2.click(fn=update_paragraphs, inputs=[pdf1, pdf2], outputs=[paragraph_1_dropdown, paragraph_2_dropdown])
-            summarize_btn2 = gr.Button("Summarize Text from PDF 2")
-            sentiment_btn2 = gr.Button("Classify Financial Tone from PDF 2")
-            analyze_btn2 = gr.Button("Analyze Financial Tone and FLS")
-
-            summarize_btn2.click(fn=lambda p: process_paragraph_2(p)[1], inputs=paragraph_2_dropdown, outputs=summary_textbox_2)
-            sentiment_btn2.click(fn=lambda p: process_paragraph_2(p)[2], inputs=paragraph_2_dropdown, outputs=sentiment_textbox_2)
-            analyze_btn2.click(fn=lambda p: process_paragraph_2(p)[3], inputs=paragraph_2_dropdown, outputs=fin_spans_2)
 
 demo.launch()