Update app.py

app.py

@@ -124,6 +124,7 @@ def process_pdf(uploaded_files, llm_model, n_criteria = num_criteria):
     final_score_bar_html = ""
     final_author_info_html = ""
     final_title_info_html = ""
+    output_files = []
     for i, uploaded_file in enumerate(uploaded_files):
         # Process the PDF file
         pdf_processor = PDFProcessor_Unstructured(pdf_processing_config)
@@ -214,23 +215,15 @@ def process_pdf(uploaded_files, llm_model, n_criteria = num_criteria):
         output_path = f"/tmp/paper_report_{i+1}.pdf"
         create_pdf_report(title_info_html, author_info_html, score, reasoning_html, output_path)
         output_files.append(output_path)
+
+        # Construct the processing message
+        processing_message = f"Processing complete. {len(uploaded_files)} reports generated. Please download your reports below."
         
-        return output_files
+    return processing_message, output_files
         # Return the score as a string and the reasoning as HTML
         #return str(round((total_score / n_criteria) * 100)) + "/100", score_bar_html, reasoning_html, author_info_html, title_info_html
 
 
-def process_and_generate_reports(uploaded_files, llm_model):
-    # Process files and generate reports as before
-    # For demonstration, let's assume we generate dummy report paths
-    generated_reports = []
-    for i, _ in enumerate(uploaded_files):
-        report_path = f"dummy_report_{i + 1}.pdf"  # Replace with actual report generation logic
-        generated_reports.append(report_path)
-    # Simulate processing with a message to indicate reports are ready
-    processing_message = f"Processing complete. {len(uploaded_files)} reports generated. Please download your reports below."
-    return processing_message, generated_reports
-
 with gr.Blocks(theme=gr.themes.Glass(
     text_size="sm", 
     font=[gr.themes.GoogleFont("Inconsolata"), "Arial", "sans-serif"],