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Update app.py
Browse files
app.py
CHANGED
@@ -679,6 +679,33 @@ with gr.Blocks() as interface:
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# save_to_excel(all_rows, "", "", output_file_path, is_resume=False)
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# log_lines.append(f"✅ Processed {acc} ({i+1}/{total})")
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print("📄 Processing accession:", acc)
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# Run summarize_results in a separate process with stop flag support
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success, rows = run_with_timeout(
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# save_to_excel(all_rows, "", "", output_file_path, is_resume=False)
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# log_lines.append(f"✅ Processed {acc} ({i+1}/{total})")
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print("📄 Processing accession:", acc)
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# --- Before calling summarize_results ---
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samples_left = total - i # including current one
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estimated_seconds_left = samples_left * 100 # your observed average per sample
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log_lines.append(
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f"Running... usually ~100s per sample"
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)
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log_lines.append(
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f"⏳ Estimated time left: ~{estimated_seconds_left} seconds ({samples_left} sample{'s' if samples_left > 1 else ''} remaining)"
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)
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# Yield update to UI before the heavy pipeline call
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yield (
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make_html_table(all_rows),
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gr.update(visible=True), # results_group
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gr.update(visible=False), # download_file
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"", # usage_display
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"⏳ Processing...", # status
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"\n".join(log_lines), # progress_box
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gr.update(visible=False), # run_button
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gr.update(visible=True), # stop_button
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gr.update(visible=True), # reset_button
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gr.update(visible=False), # raw_text
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gr.update(visible=False), # file_upload
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gr.update(value=f"Processed/Input accessions: {', '.join(accessions)}", visible=True), # processed_info
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gr.update(visible=False) # hide NPS modal
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)
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# Run summarize_results in a separate process with stop flag support
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success, rows = run_with_timeout(
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