Update app.py

app.py

@@ -87,6 +87,8 @@ def filter_paragraphs(keyword):
     if not keyword:
         paragraph1 = [f"Paragraph {i+1}: {p[:100]}..." for i, p in enumerate(stored_paragraphs_1)]
         paragraph2 = [f"Paragraph {i+1}: {p[:100]}..." for i, p in enumerate(stored_paragraphs_2)]
+        filter_paragraphs_1 = stored_paragraphs_1
+        filter_paragraphs_2 = stored_paragraphs_2
         return gr.update(choices=paragraph1, value=None), gr.update(choices=paragraph2, value=None)  # No keyword entered, return original list
     filter_paragraphs_1 = [p for p in stored_paragraphs_1 if keyword.lower() in p.lower()]
     filter_paragraphs_2 = [p for p in stored_paragraphs_2 if keyword.lower() in p.lower()]
@@ -115,7 +117,7 @@ def filtered_close_paragraph(p, keyword, pdf):
 def process_paragraph_1_sum(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_1[paragraph_index]
+                    selected_paragraph = filter_paragraphs_1[paragraph_index]
                     summary = summarize_text(selected_paragraph)
                     return summary
                 except (IndexError, ValueError):
@@ -123,7 +125,7 @@ def process_paragraph_1_sum(paragraph):
 def process_paragraph_1_sent(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_1[paragraph_index]
+                    selected_paragraph = filter_paragraphs_1[paragraph_index]
                     results = text_to_sentiment(selected_paragraph, True, False)
                     if isinstance(results, list) and isinstance(results[0], list):
                         # We unpack the list of dictionaries to get all labels
@@ -137,7 +139,7 @@ def process_paragraph_1_sent(paragraph):
 def process_paragraph_1_sent_tone(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_1[paragraph_index]
+                    selected_paragraph = filter_paragraphs_1[paragraph_index]
                     fin_spans = fin_ext(selected_paragraph)
                     return fin_spans
                 except (IndexError, ValueError):
@@ -145,7 +147,7 @@ def process_paragraph_1_sent_tone(paragraph):
 def process_paragraph_1_sent_tone_bis(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_1[paragraph_index]
+                    selected_paragraph = filter_paragraphs_1[paragraph_index]
                     fin_spans = fin_ext_bis(selected_paragraph)
                     return fin_spans
                 except (IndexError, ValueError):
@@ -153,7 +155,7 @@ def process_paragraph_1_sent_tone_bis(paragraph):
 def process_paragraph_2_sum(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_2[paragraph_index]
+                    selected_paragraph = filter_paragraphs_2[paragraph_index]
                     summary = summarize_text(selected_paragraph)
                     return summary
                 except (IndexError, ValueError):
@@ -161,7 +163,7 @@ def process_paragraph_2_sum(paragraph):
 def process_paragraph_2_sent(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_2[paragraph_index]
+                    selected_paragraph = filter_paragraphs_2[paragraph_index]
                     results = text_to_sentiment(selected_paragraph, True, False)
                     if isinstance(results, list) and isinstance(results[0], list):
                         # We unpack the list of dictionaries to get all labels
@@ -174,7 +176,7 @@ def process_paragraph_2_sent(paragraph):
 def process_paragraph_2_sent_tone(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_2[paragraph_index]
+                    selected_paragraph = filter_paragraphs_2[paragraph_index]
                     fin_spans = fin_ext(selected_paragraph)
                     return fin_spans
                 except (IndexError, ValueError):
@@ -182,7 +184,7 @@ def process_paragraph_2_sent_tone(paragraph):
 def process_paragraph_2_sent_tone_bis(paragraph):
                 try:
                     paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-                    selected_paragraph = stored_paragraphs_2[paragraph_index]
+                    selected_paragraph = filter_paragraphs_2[paragraph_index]
                     fin_spans = fin_ext_bis(selected_paragraph)
                     return fin_spans
                 except (IndexError, ValueError):
@@ -193,14 +195,14 @@ def get_pdf_files(folder):
 def show1(paragraph):
     try:
         paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-        selected_paragraph = stored_paragraphs_1[paragraph_index]
+        selected_paragraph = filter_paragraphs_1[paragraph_index]
         return selected_paragraph
     except (IndexError, ValueError):
         return "Error"
 def show2(paragraph):
     try:
         paragraph_index = int(paragraph.split(':')[0].replace('Paragraph ', '')) - 1
-        selected_paragraph = stored_paragraphs_2[paragraph_index]
+        selected_paragraph = filter_paragraphs_2[paragraph_index]
         return selected_paragraph
     except (IndexError, ValueError):
         return "Error"
@@ -508,7 +510,9 @@ with gr.Blocks(theme='gradio/soft',js=js_func) as demo:
                 # Extract paragraphs from PDFs and update dropdowns
                 def update_paragraphs(pdf1, pdf2):
                     global stored_paragraphs_1, stored_paragraphs_2
+                    global filter_paragraphs_1, filter_paragraphs_2
                     stored_paragraphs_1, stored_paragraphs_2 = extract_and_paragraph(pdf1, pdf2, True)
+                    filter_paragraphs_1, filter_paragraphs_2 = stored_paragraphs_1, stored_paragraphs_2
                     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)