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import gradio as gr
import mtdna_backend
import json
import data_preprocess, model, pipeline
import os
import hashlib
import threading

# Gradio UI
#stop_flag = gr.State(value=False)
class StopFlag:
    def __init__(self):
        self.value = False
global_stop_flag = StopFlag()  # Shared between run + stop

with open("offer.html", "r", encoding="utf-8") as f:
    pricing_html = f.read()

with open("mtdna_tool_explainer_updated.html", "r", encoding="utf-8") as f:
    flow_chart = f.read()

# css = """
# /* NPS container for a unified background */
# #nps-container {
#     background-color: #333;
#     padding: 20px;
#     border-radius: 8px;
#     display: flex;
#     flex-direction: column;
#     width: 100%;
# }

# /* Question markdown styling */
# #nps-container .gr-markdown h3 {
#     margin-bottom: 20px; /* Adds space between the question and the numbers */
# }

# /* The container for the radio buttons */
# #nps-radio-container .gr-radio-group {
#     display: flex;
#     flex-direction: row;
#     justify-content: space-between;
#     gap: 5px; 
#     flex-wrap: nowrap;
#     width: 100%;
# }

# /* Styling for each individual button */
# #nps-radio-container .gr-radio-label {
#     display: flex;
#     justify-content: center;
#     align-items: center;
#     width: 35px;
#     height: 35px;
#     border-radius: 4px;
#     background-color: #555;
#     color: white;
#     font-weight: bold;
#     cursor: pointer;
#     transition: background-color 0.2s ease;
#     font-size: 14px;
# }

# #nps-radio-container .gr-radio-label:hover {
#     background-color: #777;
# }
# #nps-radio-container input[type="radio"]:checked + .gr-radio-label {
#     background-color: #999;
#     border: 2px solid white;
# }
# #nps-radio-container .gr-radio-input {
#     display: none;
# }

# /* Adjusting the text labels for "Not likely" and "Extremely likely" */
# #nps-labels-row {
#     display: flex;
#     justify-content: space-between;
#     margin-top: 15px; /* Adds more space below the numbers */
#     color: #ccc;
#     width: 100%;
# }

# #nps-labels-row p {
#     margin: 0;
#     font-size: 1.0em;
#     white-space: nowrap;
#     width: 50%; /* Ensures each label takes up half the row */
# }
# #nps-labels-row p:first-child {
#     text-align: left;
# }
# #nps-labels-row p:last-child {
#     text-align: right;
# }

# #nps-submit-button {
#     margin-top: 25px; /* Adds a larger space above the submit button */
#     width: 100%;
# }

# #nps-submit-button:active {
#     border-color: white !important;
#     box-shadow: 0 0 5px white inset;
# }"""

css = """
/* The main container for the entire NPS section */
#nps-container {
    background-color: #333;
    padding: 20px;
    border-radius: 8px;
    display: flex;
    flex-direction: column;
    width: 100%;
}

/* Ensure the question text is properly spaced */
#nps-container h3 {
    color: #fff;
    margin-bottom: 20px; /* Space between question and buttons */
    text-align: center; /* Center the question text */
}

/* Flexbox container for the radio buttons */
#nps-radio-container {
    width: 100%;
    display: flex;
    justify-content: space-between;
    align-items: center;
}

/* Ensure the inner Gradio radio group stretches to fill the container */
#nps-radio-container > div.gr-radio-group {
    width: 100% !important;
    display: flex !important;
    justify-content: space-between !important;
}

/* Styling for each individual button */
#nps-radio-container .gr-radio-label {
    display: flex;
    justify-content: center;
    align-items: center;
    width: 35px;
    height: 35px;
    border-radius: 4px;
    background-color: #555;
    color: white;
    font-weight: bold;
    cursor: pointer;
    transition: background-color 0.2s ease;
    font-size: 14px;
    margin: 0; /* Remove default button margins */
}

#nps-radio-container .gr-radio-label:hover {
    background-color: #777;
}

#nps-radio-container input[type="radio"]:checked + .gr-radio-label {
    background-color: #999;
    border: 2px solid white;
}

#nps-radio-container .gr-radio-input {
    display: none;
}

/* The row for the "Not likely" and "Extremely likely" labels */
#nps-labels-row {
    display: flex;
    justify-content: space-between;
    margin-top: 15px; /* Adds space below the number buttons */
    width: 100%; /* Force labels row to take full width */
}

#nps-labels-row .gr-markdown p {
    margin: 0;
    font-size: 1.0em;
    color: #ccc;
    white-space: nowrap;
    width: 50%;
}

#nps-labels-row .gr-markdown:first-child p {
    text-align: left;
}

#nps-labels-row .gr-markdown:last-child p {
    text-align: right;
}

/* Submit button styling */
#nps-submit-button {
    margin-top: 25px; /* Adds space above the submit button */
    width: 100%;
}

#nps-submit-button:active {
    border-color: white !important;
    box-shadow: 0 0 5px white inset;
}
"""

with gr.Blocks() as interface:
    # with gr.Tab("CURIOUS ABOUT THIS PRODUCT?"):
    #     gr.HTML(value=pricing_html)
    with gr.Tab("🧬 Classifier"):
        gr.Markdown("# 🧬 mtDNA Location Classifier (MVP)")
        #inputMode = gr.Radio(choices=["Single Accession", "Batch Input"], value="Single Accession", label="Choose Input Mode")
        user_email = gr.Textbox(label="πŸ“§ Your email (used to track free quota). ",
                                placeholder="Enter your email and click Submit and Classify button below to run accessions.\nYou'll get +20 extra free queries and Excel-formatted results.")
            
        # sign_in_button = gr.Button("Sign in to Download")
        # user_email = gr.Textbox(
        #     label="πŸ“§ Your email (used to track free quota)",
        #     visible=False
        # )
        # # The output will be used to display a message to the user
        # output_message = gr.Textbox(visible=False, interactive=False)
        usage_display = gr.Markdown("", visible=False)
    
        # with gr.Group() as single_input_group:
        #     single_accession = gr.Textbox(label="Enter Single Accession (e.g., KU131308)")
    
        # with gr.Group(visible=False) as batch_input_group:
        #     raw_text = gr.Textbox(label="🧬 Paste Accession Numbers (e.g., MF362736.1,MF362738.1,KU131308,MW291678)")
        #     resume_file = gr.File(label="πŸ—ƒοΈ Previously saved Excel output (optional)", file_types=[".xlsx"], interactive=True)
        #     gr.HTML("""<a href="https://drive.google.com/file/d/1t-TFeIsGVu5Jh3CUZS-VE9jQWzNFCs_c/view?usp=sharing" download target="_blank">Download Example CSV Format</a>""")
        #     gr.HTML("""<a href="https://docs.google.com/spreadsheets/d/1lKqPp17EfHsshJGZRWEpcNOZlGo3F5qU/edit?usp=sharing&ouid=112390323314156876153&rtpof=true&sd=true" download target="_blank">Download Example Excel Format</a>""")
        #     file_upload = gr.File(label="πŸ“ Or Upload CSV/Excel File", file_types=[".csv", ".xlsx"], interactive=True, elem_id="file-upload-box")
        raw_text = gr.Textbox(label="🧚 Input Accession Number(s) (single (KU131308) or comma-separated (e.g., MF362736.1,MF362738.1,KU131308,MW291678))")
        #resume_file = gr.File(label="πŸ—ƒοΈ Previously saved Excel output (optional)", file_types=[".xlsx"], interactive=True)
        gr.HTML("""<a href="https://docs.google.com/spreadsheets/d/1lKqPp17EfHsshJGZRWEpcNOZlGo3F5qU/edit?usp=sharing" download target="_blank">Example Excel Input Template</a>""")
        file_upload = gr.File(label="πŸ“ Or Upload Excel File", file_types=[".xlsx"], interactive=True)
        processed_info = gr.Markdown(visible=False)  # new placeholder for processed list
        
        with gr.Row():
            run_button = gr.Button("πŸ” Submit and Classify", elem_id="run-btn")
            stop_button = gr.Button("❌ Stop Batch", visible=False, elem_id="stop-btn")
            reset_button = gr.Button("πŸ”„ Reset", elem_id="reset-btn")

    
        status = gr.Markdown(visible=False)
        
        # with gr.Group(visible=False, elem_id="nps-overlay") as nps_modal:
        #     with gr.Column(elem_id="nps-box"):
        #         gr.Markdown("### How likely are you to recommend this tool to a colleague or peer?")
        #         nps_slider = gr.Slider(minimum=0, maximum=10, step=1, label="Select score: 0-10 (0-6: not likely or low; 7-8: neutral; 9-10: likely or highly)")
        #         nps_submit = gr.Button("Submit")
        #         nps_output = gr.Textbox(label="", interactive=False, visible=True)  # Start empty
                
        with gr.Group(visible=False) as results_group:
          # with gr.Accordion("Open to See the Result", open=False) as results:  
          #     with gr.Row():
          #         output_summary = gr.Markdown(elem_id="output-summary")
          #         output_flag = gr.Markdown(elem_id="output-flag")
              
          #     gr.Markdown("---")
            
            with gr.Accordion("Open to See the Output Table", open=True) as table_accordion:    
                  output_table = gr.HTML(render=True)
              #with gr.Row():
                  #output_type = gr.Dropdown(choices=["Excel", "JSON", "TXT"], label="Select Output Format", value="Excel")
                  #download_button = gr.Button("⬇️ Download Output")
              #download_file = gr.File(label="Download File Here",visible=False)
            # Use gr.Markdown to add a visual space
            gr.Markdown(" ") # A simple blank markdown can create space
                
            report_button = gr.Button("Report inaccurate output to receive 1 extra free query",elem_id="run-btn")
            report_textbox = gr.Textbox(
                label="Describe the issue",
                lines=4,
                placeholder="e.g. DQ981467: it gives me unknown when I can in fact search it on NCBI \n DQ981467: cannot find the result in batch output when the live processing did show already processed",
                visible=False) 
            submit_report_button = gr.Button("Submit", visible=False, elem_id="run-btn")
            status_report = gr.Markdown(visible=False)  
    
            # Use gr.Markdown to add a visual space
            gr.Markdown(" ") # A simple blank markdown can create space
    
            download_file = gr.File(label="Download File Here", visible=False, interactive=True)
            
            gr.Markdown(" ") # A simple blank markdown can create space
    
            with gr.Group(visible=True, elem_id="nps-overlay") as nps_modal:
                #with gr.Column(elem_id="nps-box"):
                with gr.Group(elem_id="nps-container"):
                    gr.Markdown("### How likely are you to recommend this tool to a colleague or peer?")
                    # # Use gr.Radio to create clickable buttons
                    with gr.Column(elem_id="nps-radio-container"):
                        nps_radio = gr.Radio(
                            choices=[str(i) for i in range(11)],
                            label="Select score:",
                            interactive=True,
                            container=False
                        )
                    
                    # The "Not likely" and "Extremely likely" labels
                    with gr.Row(elem_id="nps-labels-row"):
                        gr.Markdown("Not likely")
                        gr.Markdown("Extremely likely")
        
                    nps_submit = gr.Button("Submit", elem_id="nps-submit-button")
                    nps_output = gr.Textbox(label="", interactive=False, visible=True)  
            gr.Markdown(" ") # A simple blank markdown can create space
            
            progress_box = gr.Textbox(label="Live Processing Log", lines=20, interactive=False)   
    
            gr.Markdown("---")
        
        # gr.Markdown("### πŸ’¬ Feedback (required)")
        # q1 = gr.Textbox(label="1️⃣ Was the inferred location accurate or helpful? Please explain.")
        # q2 = gr.Textbox(label="2️⃣ What would improve your experience with this tool?")
        # contact = gr.Textbox(label="πŸ“§ Your email or institution (optional)")
        # submit_feedback = gr.Button("βœ… Submit Feedback")
        # feedback_status = gr.Markdown()
    
        # Functions
        # def toggle_input_mode(mode):
        #     if mode == "Single Accession":
        #         return gr.update(visible=True), gr.update(visible=False)
        #     else:
        #         return gr.update(visible=False), gr.update(visible=True)
        # def show_email_textbox():
        #     # Return a gr.update() to make the textbox visible and set the message
        #     return gr.update(visible=True), gr.update(value="Give your email to download excel output and 20+ more free samples", visible=True)
            
        def classify_with_loading():
            return gr.update(value="⏳ Please wait... processing...",visible=True)  # Show processing message
             
        # def classify_dynamic(single_accession, file, text, resume, email, mode):
        #     if mode == "Single Accession":
        #         return classify_main(single_accession)  + (gr.update(visible=False),)
        #     else:
        #         #return summarize_batch(file, text) + (gr.update(visible=False),)  # Hide processing message
        #         return classify_mulAcc(file, text, resume) + (gr.update(visible=False),)  # Hide processing message
        # Logging helpers defined early to avoid NameError
        
    
        # def classify_dynamic(single_accession, file, text, resume, email, mode):
        #   if mode == "Single Accession":
        #       return classify_main(single_accession) + (gr.update(value="", visible=False),)
        #   else:
        #       return classify_mulAcc(file, text, resume, email, log_callback=real_time_logger, log_collector=log_collector)
    
        # for single accession
        # def classify_main(accession):
        #     #table, summary, labelAncient_Modern, explain_label = mtdna_backend.summarize_results(accession)
        #     table = mtdna_backend.summarize_results(accession)
        #     #flag_output = f"### 🏺 Ancient/Modern Flag\n**{labelAncient_Modern}**\n\n_Explanation:_ {explain_label}"
        #     return (
        #         #table,
        #         make_html_table(table),
        #         # summary,
        #         # flag_output,
        #         gr.update(visible=True),
        #         gr.update(visible=False),
        #         gr.update(visible=False)
        #     )
        
        #stop_flag = gr.State(value=False)
        #stop_flag = StopFlag()
    
        # def stop_batch(stop_flag):
        #   stop_flag.value = True
        #   return gr.update(value="❌ Stopping...", visible=True), stop_flag
        def stop_batch():
          global_stop_flag.value = True
          return gr.update(value="❌ Stopping...", visible=True)
    
        # def threaded_batch_runner(file, text, email):
        #   global_stop_flag.value = False
        #   log_lines = []
    
        #   def update_log(line):
        #       log_lines.append(line)
        #       yield (
        #           gr.update(visible=False),  # output_table (not yet)
        #           gr.update(visible=False),  # results_group
        #           gr.update(visible=False),  # download_file
        #           gr.update(visible=False),  # usage_display
        #           gr.update(value="⏳ Still processing...", visible=True),  # status
        #           gr.update(value="\n".join(log_lines))  # progress_box
        #       )
    
        #   # Start a dummy update to say "Starting..."
        #   yield from update_log("πŸš€ Starting batch processing...")
    
        #   rows, file_path, count, final_log, warning = mtdna_backend.summarize_batch(
        #       file=file,
        #       raw_text=text,
        #       resume_file=None,
        #       user_email=email,
        #       stop_flag=global_stop_flag,
        #       yield_callback=lambda line: (yield from update_log(line))
        #   )
    
        #   html = make_html_table(rows)
        #   file_update = gr.update(value=file_path, visible=True) if os.path.exists(file_path) else gr.update(visible=False)
        #   usage_or_warning_text = f"**{count}** samples used by this email." if email.strip() else warning
    
        #   yield (
        #       html,
        #       gr.update(visible=True),        # results_group
        #       file_update,                    # download_file
        #       gr.update(value=usage_or_warning_text, visible=True),
        #       gr.update(value="βœ… Done", visible=True),
        #       gr.update(value=final_log)
        #   )
        
        # def threaded_batch_runner(file=None, text="", email=""):
        #   print("πŸ“§ EMAIL RECEIVED:", email)
        #   import tempfile
        #   from mtdna_backend import (
        #       extract_accessions_from_input,
        #       summarize_results,
        #       save_to_excel,
        #       hash_user_id,
        #       increment_usage,
        #   )
        #   import os
    
        #   global_stop_flag.value = False  # reset stop flag
    
        #   tmp_dir = tempfile.mkdtemp()
        #   output_file_path = os.path.join(tmp_dir, "batch_output_live.xlsx")
        #   limited_acc = 50 + (10 if email.strip() else 0)
    
        #   # Step 1: Parse input
        #   accessions, error = extract_accessions_from_input(file, text)
        #   print(accessions)  
        #   if error:
        #       yield (
        #           "",                          # output_table
        #           gr.update(visible=False),   # results_group
        #           gr.update(visible=False),   # download_file
        #           "",                          # usage_display
        #           "❌ Error",                  # status
        #           str(error)                        # progress_box
        #       )
        #       return
    
        #   total = len(accessions)
        #   if total > limited_acc:
        #       accessions = accessions[:limited_acc]
        #       warning = f"⚠️ Only processing first {limited_acc} accessions."
        #   else:
        #       warning = f"βœ… All {total} accessions will be processed."
    
        #   all_rows = []
        #   processed_accessions = 0  # βœ… tracks how many accessions were processed
        #   email_tracked = False  
        #   log_lines = []
    
        #   # Step 2: Loop through accessions
        #   for i, acc in enumerate(accessions):
        #       if global_stop_flag.value:
        #           log_lines.append(f"πŸ›‘ Stopped at {acc} ({i+1}/{total})")
        #           usage_text = ""
        #           if email.strip() and not email_tracked:
        #               # user_hash = hash_user_id(email)
        #               # usage_count = increment_usage(user_hash, len(all_rows))
        #               print("print(processed_accessions at stop)  ",processed_accessions)
        #               usage_count = increment_usage(email, processed_accessions)
        #               email_tracked = True
        #               usage_text = f"**{usage_count}** samples used by this email. Ten more samples are added first (you now have 60 limited accessions), then wait we will contact you via this email."
        #           else:
        #               usage_text = f"The limited accession is 50. The user has used {processed_accessions}, and only {50-processed_accessions} left."    
        #           yield (
        #               make_html_table(all_rows),
        #               gr.update(visible=True),
        #               gr.update(value=output_file_path, visible=True),
        #               gr.update(value=usage_text, visible=True),
        #               "πŸ›‘ Stopped",
        #               "\n".join(log_lines)
        #           )
        #           return
    
        #       log_lines.append(f"[{i+1}/{total}] Processing {acc}")
        #       yield (
        #           make_html_table(all_rows),
        #           gr.update(visible=True),
        #           gr.update(visible=False),
        #           "",
        #           "⏳ Processing...",
        #           "\n".join(log_lines)
        #       )
    
        #       try:
        #           print(acc)
        #           rows = summarize_results(acc)
        #           all_rows.extend(rows)
        #           processed_accessions += 1  # βœ… count only successful accessions
        #           save_to_excel(all_rows, "", "", output_file_path, is_resume=False)
        #           log_lines.append(f"βœ… Processed {acc} ({i+1}/{total})")
        #       except Exception as e:
        #           log_lines.append(f"❌ Failed to process {acc}: {e}")
    
        #       yield (
        #           make_html_table(all_rows),
        #           gr.update(visible=True),
        #           gr.update(visible=False),
        #           "",
        #           "⏳ Processing...",
        #           "\n".join(log_lines)
        #       )
    
        #   # Final update
        #   usage_text = ""
          
        #   if email.strip() and not email_tracked:
        #       # user_hash = hash_user_id(email)
        #       # usage_count = increment_usage(user_hash, len(all_rows))
        #       print("print(processed_accessions final)  ",processed_accessions)  
        #       usage_count = increment_usage(email, processed_accessions)
        #       usage_text = f"**{usage_count}** samples used by this email. Ten more samples are added first (you now have 60 limited accessions), then wait we will contact you via this email."
        #   elif not email.strip():
        #       usage_text = f"The limited accession is 50. The user has used {processed_accessions}, and only {50-processed_accessions} left."
        #   yield (
        #       make_html_table(all_rows),
        #       gr.update(visible=True),
        #       gr.update(value=output_file_path, visible=True),
        #       gr.update(value=usage_text, visible=True),
        #       "βœ… Done",
        #       "\n".join(log_lines)
        #   )
        def submit_nps(email,nps_score):
            if nps_score is None:
                return "❌ Please select a score before submitting."
            log_submission_to_gsheet(email, [], nps_score)
            return "βœ… Thanks for submitting your feedback!"
                    
        def log_submission_to_gsheet(email, samples, nps_score=None):
            from datetime import datetime, timezone
            import json, os, gspread
            from oauth2client.service_account import ServiceAccountCredentials
            import uuid
        
            timestamp = datetime.now(timezone.utc).strftime("%Y-%m-%d %H:%M:%S UTC")
            if not email.strip():
                email = f"anonymous_{str(uuid.uuid4())[:8]}"
        
            try:
                creds_dict = json.loads(os.environ["GCP_CREDS_JSON"])
                scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
                creds = ServiceAccountCredentials.from_json_keyfile_dict(creds_dict, scope)
                client = gspread.authorize(creds)
        
                sheet = client.open("user_usage_log")
                worksheet = sheet.sheet1  # Main sheet
        
                data = worksheet.get_all_values()
                headers = data[0]
                email_col = headers.index("email")
                samples_col = headers.index("samples")
                recent_time_col = headers.index("recent_time")
                nps_col = headers.index("nps_score") if "nps_score" in headers else -1
                print("this is nps col: ", nps_col)
                # Step 1: Find row matching the email
                for i, row in enumerate(data[1:], start=2):  # start=2 for correct row indexing
                    if row[email_col].strip().lower() == email.strip().lower():
                        old_samples = row[samples_col].strip() if len(row) > samples_col else ""
                        old_sample_list = [s.strip() for s in old_samples.split(",") if s.strip()]
                        all_samples = list(dict.fromkeys(old_sample_list + samples))  # deduplicate while preserving order
                        new_sample_string = ", ".join(all_samples)

                        # Update recent_time to store history
                        old_timestamp = row[recent_time_col].strip() if len(row) > recent_time_col else ""
                        if old_timestamp:
                            new_timestamp = f"{old_timestamp}, {timestamp}"
                        else:
                            new_timestamp = timestamp
                            
                        worksheet.update_cell(i, samples_col + 1, new_sample_string)
                        worksheet.update_cell(i, recent_time_col + 1, str(new_timestamp))
                        if nps_score is not None:
                            print("this is nps score:", nps_score)
                            old_nps = row[nps_col].strip() if len(row) > nps_col else ""
                            if old_nps:
                                new_nps = f"{old_nps},{nps_score}"
                            else:
                                new_nps = str(nps_score)
                            worksheet.update_cell(i, nps_col + 1, str(new_nps))

                        print(f"βœ… Updated existing user row for: {email}")
                        return
        
                # Step 2: If email not found, add new row
                new_row = [""] * len(headers)
                new_row[email_col] = email
                new_row[samples_col] = ", ".join(samples)
                new_row[recent_time_col] = timestamp
                if nps_col != -1:
                    if len(new_row) <= nps_col:
                        new_row.extend([""] * (nps_col + 1 - len(new_row)))
                    new_row[nps_col] = str(nps_score) if nps_score is not None else ""
                worksheet.append_row(new_row)
                print(f"βœ… Appended new user row for: {email}")
        
            except Exception as e:
                print(f"❌ Failed to log submission to Google Sheets: {e}")


        import multiprocessing
        import time
        
        def run_with_timeout(func, args=(), kwargs={}, timeout=30, stop_value=None):
            """
            Runs func in a separate process with optional timeout.
            If stop_value is provided and becomes True during execution, the process is killed early.
            """
            def wrapper(q, *args, **kwargs):
                try:
                    result = func(*args, **kwargs)
                    q.put((True, result))
                except Exception as e:
                    q.put((False, e))
        
            q = multiprocessing.Queue()
            p = multiprocessing.Process(target=wrapper, args=(q, *args), kwargs=kwargs)
            p.start()
        
            start_time = time.time()
            while p.is_alive():
                # Timeout check
                if timeout is not None and (time.time() - start_time) > timeout:
                    p.terminate()
                    p.join()
                    print(f"⏱️ Timeout exceeded ({timeout} sec) β€” function killed.")
                    return False, None
        
                # Stop flag check
                # if stop_value is not None and stop_value.value:
                #     p.terminate()
                #     p.join()
                #     print("πŸ›‘ Stop flag detected β€” function killed early.")
                #     return False, None
                if stop_value is not None and stop_value.value:
                    print("πŸ›‘ Stop flag detected β€” waiting for child to exit gracefully.")
                    p.join(timeout=3)  # short wait for graceful exit
                    if p.is_alive():
                        print("⚠️ Child still alive, forcing termination.")
                        p.terminate()
                        p.join()
                    return False, None
                time.sleep(0.1)  # avoid busy waiting
        
            # Process finished naturally
            if not q.empty():
                success, result = q.get()
                if success:
                    return True, result
                else:
                    raise result
        
            return False, None

        def threaded_batch_runner(file=None, text="", email=""):
            print("πŸ“§ EMAIL RECEIVED:", repr(email))
            import tempfile
            from mtdna_backend import (
                extract_accessions_from_input,
                summarize_results,
                save_to_excel,
                increment_usage,
            )
            import os
        
            global_stop_flag.value = False  # reset stop flag
        
            tmp_dir = tempfile.mkdtemp()
            output_file_path = os.path.join(tmp_dir, "batch_output_live.xlsx")
            #output_file_path = "/mnt/data/batch_output_live.xlsx"
            all_rows = []
            processed_accessions = 0  # βœ… track successful accessions
            email_tracked = False
            log_lines = []
            usage_text = ""
            processed_info = ""
            if not email.strip():
                output_file_path = None#"Write your email so that you can download the outputs."
                log_lines.append("πŸ“₯ Provide your email to receive a downloadable Excel report and get 20 more free queries.")
                limited_acc = 30
            if email.strip():
                usage_count, max_allowed = increment_usage(email, processed_accessions) 
                if int(usage_count) >= int(max_allowed):
                    log_lines.append("❌ You have reached your quota. Please contact us to unlock more.")
                    
                    # Minimal blank yield to trigger UI rendering
                    yield (
                        make_html_table([]),            # 1 output_table
                        gr.update(visible=True),        # 2 results_group
                        gr.update(visible=False),       # 3 download_file
                        gr.update(value="", visible=True), # 4 usage_display
                        "⛔️ Quota limit",               # 5 status
                        "⛔️ Quota limit",               # 6 progress_box
                        gr.update(visible=True),        # 7 run_button
                        gr.update(visible=False),       # 8 stop_button
                        gr.update(visible=True),        # 9 reset_button
                        gr.update(visible=True),        # 10 raw_text
                        gr.update(visible=True),        # 11 file_upload
                        gr.update(value=processed_info, visible=False), # 12 processed_info
                        gr.update(visible=False)        # 13 nps_modal
                    )
            
                    # Actual warning frame
                    yield (
                        make_html_table([]),
                        gr.update(visible=False),
                        gr.update(visible=False),
                        gr.update(value="❌ You have reached your quota. Please contact us to unlock more.", visible=True),
                        "❌ Quota Exceeded",
                        "\n".join(log_lines),
                        gr.update(visible=True),
                        gr.update(visible=False),
                        gr.update(visible=True),
                        gr.update(visible=True),
                        gr.update(visible=True),
                        gr.update(value="", visible=False),
                        gr.update(visible=False)
                    )
                    return
                limited_acc = int(max_allowed-usage_count)
            
            # Step 1: Parse input
            accessions, error = extract_accessions_from_input(file, text)
            total = len(accessions)
            print("total len original accessions: ", total)
            if total > limited_acc:
                accessions = accessions[:limited_acc]
                warning = f"⚠️ Only processing first {limited_acc} accessions."
            else:
                warning = f"βœ… All {total} accessions will be processed."
            if len(accessions) == 1:    
                processed_info = warning + "\n" +f"Processed accessions: {accessions[0]}"
            else:    
                processed_info = warning + "\n" +f"Processed accessions: {accessions[0]}...{accessions[-1]}"   
            ### NEW: Hide inputs, show processed_info at start
            yield (
                make_html_table(all_rows), # output_table
                gr.update(visible=False),   # results_group
                gr.update(visible=False),   # download_file
                "", # usage_display
                "⏳ Processing...", # status
                "", # progess_box
                gr.update(visible=False), # run_button,
                gr.update(visible=True),     # show stop button
                gr.update(visible=True),     # show reset button
                gr.update(visible=True),    # hide raw_text
                gr.update(visible=True),    # hide file_upload
                gr.update(value=processed_info, visible=True),  # processed_info
                gr.update(visible=False)     # hide NPS modal at start
            )
            
            log_submission_to_gsheet(email, accessions)

            print("πŸ§ͺ Accessions received:", accessions)
            if error:
                yield (
                    "",                               # 1 output_table
                    gr.update(visible=False),         # 2 results_group
                    gr.update(visible=False),         # 3 download_file
                    "",                               # 4 usage_display
                    "❌ Error",                        # 5 status
                    str(error),                       # 6 progress_box
                    gr.update(visible=True),          # 7 run_button
                    gr.update(visible=False),         # 8 stop_button
                    gr.update(visible=True),          # 9 reset_button
                    gr.update(visible=True),          # 10 raw_text
                    gr.update(visible=True),          # 11 file_upload
                    gr.update(value="", visible=False), # 12 processed_info
                    gr.update(visible=False)           # 13 nps_modal
                )
                return
        
            # all_rows = []
            # processed_accessions = 0  # βœ… track successful accessions
            # email_tracked = False
            # log_lines = []
            # if not email.strip():
            #     output_file_path = None#"Write your email so that you can download the outputs."
            #     log_lines.append("πŸ“₯ Provide your email to receive a downloadable Excel report and get 20 more free queries.")
            # if email.strip():
            #     usage_count, max_allowed = increment_usage(email, processed_accessions) 
            #     if int(usage_count) > int(max_allowed):
            #         log_lines.append("❌ You have reached your quota. Please contact us to unlock more.")
                    
            #         # Minimal blank yield to trigger UI rendering
            #         yield (
            #             make_html_table([]),
            #             gr.update(visible=True),
            #             gr.update(visible=False),
            #             gr.update(value="", visible=True),
            #             "⛔️ Quota limit",
            #             "⛔️ Quota limit"
            #         )
                    
            #         # Actual warning frame
            #         yield (
            #             make_html_table([]),
            #             gr.update(visible=False),
            #             gr.update(visible=False),
            #             gr.update(value="❌ You have reached your quota. Please contact us to unlock more.", visible=True),
            #             "❌ Quota Exceeded",
            #             "\n".join(log_lines)
            #         )
            #         return
            
            # Step 2: Loop through accessions
            for i, acc in enumerate(accessions):
                try:
                    if global_stop_flag.value:
                        log_lines.append(f"πŸ›‘ Stopped at {acc} ({i+1}/{total})")
                        usage_text = ""
            
                        if email.strip() and not email_tracked:
                            print(f"πŸ§ͺ increment_usage at STOP: {email=} {processed_accessions=}")
                            usage_count, max_allowed = increment_usage(email, processed_accessions)
                            email_tracked = True
                            usage_text = f"**{usage_count}**/{max_allowed} allowed samples used by this email."
                            #Ten more samples are added first (you now have 60 limited accessions), then wait we will contact you via this email."
                        else:
                            usage_text = f"The limited accession is 30. The user has used {processed_accessions}, and only {30 - processed_accessions} left."
            
                        # yield (
                        #     make_html_table(all_rows),
                        #     gr.update(visible=True),
                        #     #gr.update(value=output_file_path, visible=True),
                        #     gr.update(value=output_file_path, visible=bool(output_file_path)),
                        #     gr.update(value=usage_text, visible=True),
                        #     "πŸ›‘ Stopped",
                        #     "\n".join(log_lines)
                        # )
                        yield (
                            make_html_table(all_rows),
                            gr.update(visible=True),                           # results_group
                            gr.update(value=output_file_path, visible=bool(output_file_path)),  # download_file
                            gr.update(value=usage_text, visible=True),         # usage_display
                            "πŸ›‘ Stopped",                                       # "βœ… Done" or "πŸ›‘ Stopped"
                            "\n".join(log_lines),
                            gr.update(visible=False),                          # run_button
                            gr.update(visible=False),                          # stop_button
                            gr.update(visible=True),                           # reset_button
                            gr.update(visible=True),                          # raw_text
                            gr.update(visible=True),                          # file_upload
                            gr.update(value=processed_info, visible=False),                # processed_info
                            gr.update(visible=True)                            # NPS modal now visible
                        )
    
                        return
            
                    log_lines.append(f"[{i+1}/{total}] Processing {acc}")
                    # yield (
                    #     make_html_table(all_rows),
                    #     gr.update(visible=True),
                    #     gr.update(visible=False),
                    #     "",
                    #     "⏳ Processing...",
                    #     "\n".join(log_lines)
                    # )
                    # Hide inputs, show processed_info at start
                    yield (
                        make_html_table(all_rows),         # output_table
                        gr.update(visible=True),          # results_group
                        gr.update(visible=False),          # download_file
                        "",                                # usage_display
                        "⏳ Processing...",                 # status
                        "\n".join(log_lines),              # progress_box
                        gr.update(visible=False),           # run_button
                        gr.update(visible=True),           # stop_button
                        gr.update(visible=True),           # reset_button
                        gr.update(visible=True),          # hide raw_text
                        gr.update(visible=True),          # hide file_upload
                        gr.update(value=processed_info, visible=True),  # processed_info
                        gr.update(visible=False)           # hide NPS modal at start
                    )
    
            
                    # try:
                    #     print("πŸ“„ Processing accession:", acc)
                    #     rows = summarize_results(acc)
                    #     all_rows.extend(rows)
                    #     processed_accessions += 1  # βœ… only count success
                    #     if email.strip():
                    #         save_to_excel(all_rows, "", "", output_file_path, is_resume=False)
                    #     log_lines.append(f"βœ… Processed {acc} ({i+1}/{total})")
                    print("πŸ“„ Processing accession:", acc)
                    # --- Before calling summarize_results ---
                    samples_left = total - i  # including current one
                    estimated_seconds_left = samples_left * 100  # your observed average per sample
                    
                    log_lines.append(
                        f"Running... usually ~100s per sample"
                    )
                    log_lines.append(
                        f"⏳ Estimated time left: ~{estimated_seconds_left} seconds ({samples_left} sample{'s' if samples_left > 1 else ''} remaining)"
                    )
                    
                    # Yield update to UI before the heavy pipeline call
                    yield (
                        make_html_table(all_rows),
                        gr.update(visible=True),          # results_group
                        gr.update(visible=False),         # download_file
                        "",                               # usage_display
                        "⏳ Processing...",                # status
                        "\n".join(log_lines),             # progress_box
                        gr.update(visible=False),         # run_button
                        gr.update(visible=True),          # stop_button
                        gr.update(visible=True),          # reset_button
                        gr.update(visible=True),         # raw_text
                        gr.update(visible=True),         # file_upload
                        gr.update(value=processed_info, visible=True),  # processed_info
                        gr.update(visible=False)          # hide NPS modal
                    )
    
                    # Run summarize_results in a separate process with stop flag support
                    success, rows = run_with_timeout(
                        summarize_results,
                        args=(acc,),
                        timeout=None,              # or set max seconds per sample if you want
                        stop_value=global_stop_flag
                    )
                    
                    # If stop was pressed during this accession
                    if not success and global_stop_flag.value:
                        log_lines.append(f"πŸ›‘ Cancelled {acc} before completion")
                        # yield (
                        #     make_html_table(all_rows),
                        #     gr.update(visible=True),
                        #     gr.update(visible=False),
                        #     "",
                        #     "πŸ›‘ Stopped",
                        #     "\n".join(log_lines)
                        # )
                        yield (
                            make_html_table(all_rows),
                            gr.update(visible=True),                           # results_group
                            gr.update(value=output_file_path, visible=bool(output_file_path)),  # download_file
                            gr.update(value=usage_text, visible=True),         # usage_display
                            "πŸ›‘ Stopped",                                       # "βœ… Done" or "πŸ›‘ Stopped"
                            "\n".join(log_lines),
                            gr.update(visible=False),                          # run_button
                            gr.update(visible=False),                          # stop_button
                            gr.update(visible=True),                           # reset_button
                            gr.update(visible=True),                          # raw_text
                            gr.update(visible=True),                          # file_upload
                            gr.update(value="", visible=False),                # processed_info
                            gr.update(visible=True)                            # NPS modal now visible
                        )
    
                        break  # stop processing entirely
                    
                    # If it finished normally
                    if success and rows:
                        all_rows.extend(rows)
                        processed_accessions += 1
                        if email.strip():
                            save_to_excel(all_rows, "", "", output_file_path, is_resume=False)
                        log_lines.append(f"βœ… Processed {acc} ({i+1}/{total})")
                    else:
                        # If it failed due to timeout or other error
                        if not global_stop_flag.value:
                            log_lines.append(f"⚠️ Skipped {acc} due to timeout or error")
                    
                    # Always yield updated logs after each attempt
                    # yield (
                    #     make_html_table(all_rows),
                    #     gr.update(visible=True),
                    #     gr.update(visible=False),
                    #     "",
                    #     "⏳ Processing...",
                    #     "\n".join(log_lines)
                    # )
                    yield (
                        make_html_table(all_rows),         # output_table
                        gr.update(visible=True),          # results_group
                        gr.update(visible=False),          # download_file
                        "",                                # usage_display
                        "⏳ Processing...",                 # status
                        "\n".join(log_lines),              # progress_box
                        gr.update(visible=False),           # run_button
                        gr.update(visible=True),           # stop_button
                        gr.update(visible=True),           # reset_button
                        gr.update(visible=True),          # hide raw_text
                        gr.update(visible=True),          # hide file_upload
                        gr.update(value=processed_info, visible=True),  # processed_info
                        gr.update(visible=False)           # hide NPS modal at start
                    )
            

                except Exception as e:
                    log_lines.append(f"❌ Failed to process {acc}: {e}. Report on the box above so that we won't count this bad one for you (email required).")
                    yield (
                        make_html_table(all_rows),         # output_table
                        gr.update(visible=True),          # results_group
                        gr.update(visible=False),          # download_file
                        "",                                # usage_display
                        "⏳ Processing...",                 # status
                        "\n".join(log_lines),              # progress_box
                        gr.update(visible=False),           # run_button
                        gr.update(visible=True),           # stop_button
                        gr.update(visible=True),           # reset_button
                        gr.update(visible=True),          # hide raw_text
                        gr.update(visible=True),          # hide file_upload
                        gr.update(value=processed_info, visible=True),  # processed_info
                        gr.update(visible=False)           # hide NPS modal at start
                    )
                
            # Step 3: Final usage update
            usage_text = ""
            if email.strip() and not email_tracked:
                print(f"πŸ§ͺ increment_usage at END: {email=} {processed_accessions=}")
                usage_count, max_allowed = increment_usage(email, processed_accessions)
                email_tracked = True
                usage_text = f"**{usage_count}**/{max_allowed} allowed samples used by this email." 
                #Ten more samples are added first (you now have 60 limited accessions), then wait we will contact you via this email."
            elif not email.strip():
                usage_text = f"The limited accession is 30. The user has used {processed_accessions}, and only {30 - processed_accessions} left."
        
            # yield (
            #     make_html_table(all_rows),
            #     gr.update(visible=True),
            #     #gr.update(value=output_file_path, visible=True),
            #     gr.update(value=output_file_path, visible=bool(output_file_path)),
            #     gr.update(value=usage_text, visible=True),
            #     "βœ… Done",
            #     "\n".join(log_lines)
            # )
            yield (
                make_html_table(all_rows),
                gr.update(visible=True),                           # results_group
                gr.update(value=output_file_path, visible=bool(output_file_path)),  # download_file
                gr.update(value=usage_text, visible=True),         # usage_display
                "βœ… Done",                                      # "βœ… Done" or "πŸ›‘ Stopped"
                "\n".join(log_lines),
                gr.update(visible=False),                          # run_button
                gr.update(visible=False),                          # stop_button
                gr.update(visible=True),                           # reset_button
                gr.update(visible=True),                          # raw_text
                gr.update(visible=True),                          # file_upload
                gr.update(value=processed_info, visible=True),                # processed_info
                gr.update(visible=True)                            # NPS modal now visible
            )
    
        # SUBMIT REPORT UI
        # 1. Google Sheets setup
        def get_worksheet(sheet_name="Report"):
            import os, json
            import gspread
            from oauth2client.service_account import ServiceAccountCredentials
            try:
                creds_dict = json.loads(os.environ["GCP_CREDS_JSON"])
                scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
                creds = ServiceAccountCredentials.from_json_keyfile_dict(creds_dict, scope)
                client = gspread.authorize(creds)
                sheet = client.open(sheet_name).sheet1
                return sheet
            except Exception as e:
                print(f"❌ Error loading Google Sheet '{sheet_name}':", e)
                return None
                
        # 2. Submit function to send report to the Google Sheet
        def submit_report(report_text,user_email=""):
            try:
                sheet = get_worksheet()
                # βœ… Parse the report_text (each line like 'ACCESSION: message')
                lines = report_text.strip().split('\n')
                user = ""
                if user_email.strip():
                    user = user_email
                for line in lines:
                    if ':' in line:
                        accession, message = line.split(':', 1)
                        sheet.append_row([accession.strip(), message.strip(), user.strip()])
                return "βœ… Report submitted successfully!"
            except Exception as e:
                return f"❌ Error submitting report: {str(e)}"
        def show_report_ui():
            return gr.update(visible=True), gr.update(visible=True), gr.update(visible=False)

        def handle_submission(text,user_email):
            msg = submit_report(text, user_email)
            return gr.update(value=msg, visible=True), gr.update(visible=False), gr.update(visible=False)        
        # def threaded_batch_runner(file=None, text="", email=""):
        #   global_stop_flag.value = False
    
        #   # Dummy test output that matches expected schema
        #   return (
        #       "<div>βœ… Dummy output table</div>",   # HTML string
        #       gr.update(visible=True),             # Group visibility
        #       gr.update(visible=False),            # Download file
        #       "**0** samples used.",               # Markdown
        #       "βœ… Done",                           # Status string
        #       "Processing finished."               # Progress string
        #   )
    
        
        # def classify_mulAcc(file, text, resume, email, log_callback=None, log_collector=None):
        #     stop_flag.value = False
        #     return threaded_batch_runner(file, text, resume, email, status, stop_flag, log_callback=log_callback, log_collector=log_collector)
        
    
        def make_html_table(rows):
          # html = """
          # <div style='overflow-x: auto; padding: 10px;'>
          #     <div style='max-height: 400px; overflow-y: auto; border: 1px solid #444; border-radius: 8px;'>
          #         <table style='width:100%; border-collapse: collapse; table-layout: auto; font-size: 14px; color: #f1f1f1; background-color: #1e1e1e;'>
          #             <thead style='position: sticky; top: 0; background-color: #2c2c2c; z-index: 1;'>
          #                 <tr>
          # """
          html = """
            <div style='overflow-x: auto; padding: 10px;'>
                <div style='max-height: 400px; overflow-y: auto; border: 1px solid #ccc; border-radius: 8px;'>
                    <table style='width:100%; border-collapse: collapse; table-layout: auto; font-size: 14px; color: inherit; background-color: inherit;'>
            """
      
          headers = ["No.", "Sample ID", "Predicted Country", "Country Explanation", "Predicted Sample Type", "Sample Type Explanation", "Sources", "Time cost"]
          html += "".join(
              f"<th style='padding: 10px; border: 1px solid #555; text-align: left; white-space: nowrap;'>{h}</th>"
              for h in headers
          )
          html += "</tr></thead><tbody>"
    
          for idx, row in enumerate(rows, 1): # start numbering from 1
              html += "<tr>"
              html += f"<td style='padding: 10px; border: 1px solid #555;'>{idx}</td>"  # "No." column
              for i, col in enumerate(row):
                  header = headers[i]
                  style = "padding: 10px; border: 1px solid #555; vertical-align: top;"
    
                  # For specific columns like Haplogroup, force nowrap
                  if header in ["Country Explanation", "Sample Type Explanation"]:
                    style += " max-width: 400px; word-wrap: break-word; white-space: normal;"
                  elif header in ["Sample ID", "Predicted Country", "Predicted Sample Type", "Time cost"]:
                      style += " white-space: nowrap; text-overflow: ellipsis; max-width: 200px; overflow: hidden;"
    
                  # if header == "Sources" and isinstance(col, str) and col.strip().lower().startswith("http"):
                  #     col = f"<a href='{col}' target='_blank' style='color: #4ea1f3; text-decoration: underline;'>{col}</a>"
    
                  #html += f"<td style='{style}'>{col}</td>"
                  if header == "Sources" and isinstance(col, str):
                      links = [f"<a href='{url.strip()}' target='_blank' style='color: #4ea1f3; text-decoration: underline;'>{url.strip()}</a>" for url in col.strip().split("\n") if url.strip()]
                      col = "- "+"<br>- ".join(links)
                  elif isinstance(col, str):
                      # lines = []
                      # for line in col.split("\n"):
                      #     line = line.strip()
                      #     if not line:
                      #         continue
                      #     if line.lower().startswith("rag_llm-"):
                      #         content = line[len("rag_llm-"):].strip()
                      #         line = f"{content} (Method: RAG_LLM)"
                      #     lines.append(f"- {line}")
                      col = col.replace("\n", "<br>")
                      #col = col.replace("\t", "&nbsp;&nbsp;&nbsp;&nbsp;")
                      #col = "<br>".join(lines)
    
                  html += f"<td style='{style}'>{col}</td>"
              html += "</tr>"
    
          html += "</tbody></table></div></div>"
          return html
      
    
        # def reset_fields():
        #     global_stop_flag.value = False  # πŸ’‘ Add this to reset the flag
        #     return (
        #         #gr.update(value=""),  # single_accession
        #         gr.update(value=""),  # raw_text
        #         gr.update(value=None), # file_upload
        #         #gr.update(value=None),  # resume_file
        #         #gr.update(value="Single Accession"), # inputMode
        #         gr.update(value=[], visible=True), # output_table
        #         # gr.update(value="", visible=True), # output_summary
        #         # gr.update(value="", visible=True), # output_flag
        #         gr.update(visible=False), # status
        #         gr.update(visible=False),  # results_group
        #         gr.update(value="", visible=False),  # usage_display
        #         gr.update(value="", visible=False),  # progress_box
        #     )
        # def reset_fields():
        #   global_stop_flag.value = True  # Reset the stop flag
    
        #   return (
        #       gr.update(value=""),          # raw_text
        #       gr.update(value=None),        # file_upload
        #       gr.update(value=[], visible=True),   # output_table
        #       gr.update(value="", visible=True),   # status β€” reset and make visible again
        #       gr.update(visible=False),     # results_group
        #       gr.update(value="", visible=True),   # usage_display β€” reset and make visible again
        #       gr.update(value="", visible=True),   # progress_box β€” reset AND visible!
        #       # report-related reset below
        #       gr.update(value="", visible=False),  # report_textbox
        #       gr.update(visible=False),            # submit_report_button
        #       gr.update(value="", visible=False),  # status_report
        #       gr.update(value=0),            # nps_slider
        #       gr.update(value="", visible=False)  # nps_output

        #     )
        def reset_fields():
            global_stop_flag.value = True  # Stop any running job
        
            return (
                gr.update(value="", visible=True),   # raw_text
                gr.update(value=None, visible=True), # file_upload
                gr.update(value=[], visible=True),   # output_table
                gr.update(value="", visible=True),   # status
                gr.update(visible=False),            # results_group
                gr.update(value="", visible=True),   # usage_display
                gr.update(value="", visible=True),   # progress_box
                gr.update(value="", visible=False),  # report_textbox
                gr.update(visible=False),             # submit_report_button
                gr.update(value="", visible=False),  # status_report
                gr.update(value="", visible=False),  # processed_info
                gr.update(visible=False),              # hide NPS modal
                gr.update(visible=True),              # run_button βœ… restore
                gr.update(visible=False)              # stop button 
            )

            
        #inputMode.change(fn=toggle_input_mode, inputs=inputMode, outputs=[single_input_group, batch_input_group])
        #run_button.click(fn=classify_with_loading, inputs=[], outputs=[status])
        # run_button.click(
        #     fn=classify_dynamic,
        #     inputs=[single_accession, file_upload, raw_text, resume_file,user_email,inputMode],
        #     outputs=[output_table, 
        #     #output_summary, output_flag, 
        #     results_group, download_file, usage_display,status, progress_box]
        # )
        
        # run_button.click(
        #     fn=threaded_batch_runner,
        #     #inputs=[file_upload, raw_text, resume_file, user_email],
        #     inputs=[file_upload, raw_text, user_email],
        #     outputs=[output_table, results_group, download_file, usage_display, status, progress_box]
        # )
    #     run_button.click(
    #     fn=threaded_batch_runner,
    #     inputs=[file_upload, raw_text, user_email],
    #     outputs=[output_table, results_group, download_file, usage_display, status, progress_box],
    #     every=0.5  # <-- this tells Gradio to expect streaming
    # )
        # output_table = gr.HTML()
        # results_group = gr.Group(visible=False)
        # download_file = gr.File(visible=False)
        # usage_display = gr.Markdown(visible=False)
        # status = gr.Markdown(visible=False)
        # progress_box = gr.Textbox(visible=False)
    
    #     run_button.click(
    #     fn=threaded_batch_runner,
    #     inputs=[file_upload, raw_text, user_email],
    #     outputs=[output_table, results_group, download_file, usage_display, status, progress_box],
    #     every=0.5,  # streaming enabled
    #     show_progress="full"
    # )
    
        # interface.stream(
        #     fn=threaded_batch_runner,
        #     inputs=[file_upload, raw_text, user_email],
        #     outputs=[output_table, results_group, download_file, usage_display, status, progress_box],
        #     trigger=run_button,
        #     every=0.5,
        #     show_progress="full",
        # )
        interface.queue()  # No arguments here!
    
        # run_button.click(
        #     fn=threaded_batch_runner,
        #     inputs=[file_upload, raw_text, user_email],
        #     outputs=[output_table, results_group, download_file, usage_display, status, progress_box],
        #     concurrency_limit=1,  # βœ… correct in Gradio 5.x
        #     queue=True,            # βœ… ensure the queue is used
        #     #every=0.5
        # )
        # Link the button to the function
        # sign_in_button.click(
        #     fn=show_email_textbox,
        #     outputs=[user_email, output_message] # The outputs are the components to be updated
        # )
        
        run_button.click(
            fn=threaded_batch_runner,
            inputs=[file_upload, raw_text, user_email],
            outputs=[
                output_table,      # 1
                results_group,     # 2
                download_file,     # 3
                usage_display,     # 4
                status,            # 5
                progress_box,      # 6
                run_button,        # 7
                stop_button,       # 8
                reset_button,      # 9
                raw_text,          # 10
                file_upload,       # 11
                processed_info,    # 12
                nps_modal          # 13
            ],
            concurrency_limit=1,
            queue=True
        )

        
    
        
    
        stop_button.click(fn=stop_batch, inputs=[], outputs=[status])
    
        # reset_button.click(
        #     #fn=reset_fields,
        #     fn=lambda: (
        #         gr.update(value=""), gr.update(value=""), gr.update(value=None), gr.update(value=None), gr.update(value="Single Accession"),
        #         gr.update(value=[], visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(value="", visible=False), gr.update(value="", visible=False)
        #     ),
        #     inputs=[],
        #     outputs=[
        #         single_accession, raw_text, file_upload, resume_file,inputMode,
        #         output_table,# output_summary, output_flag,
        #         status, results_group, usage_display, progress_box
        #     ]
        # )
        #stop_button.click(fn=lambda sf: (gr.update(value="❌ Stopping...", visible=True), setattr(sf, "value", True) or sf), inputs=[gr.State(stop_flag)], outputs=[status, gr.State(stop_flag)])
    
        # reset_button.click(
        #     fn=reset_fields,
        #     inputs=[],
        #     #outputs=[raw_text, file_upload, resume_file, output_table, status, results_group, usage_display, progress_box]
        #     outputs=[raw_text, file_upload, output_table, status, results_group, usage_display, progress_box,
        #             report_textbox,
        #             submit_report_button,
        #             status_report, nps_slider, nps_output]
        #             ) 
        reset_button.click(
            fn=reset_fields,
            inputs=[],
            outputs=[
                raw_text, 
                file_upload, 
                output_table, 
                status, 
                results_group, 
                usage_display, 
                progress_box,
                report_textbox,
                submit_report_button,
                status_report, 
                processed_info,
                nps_modal,
                run_button,
                stop_button
            ]
        )

    
        # download_button.click(
        #   fn=mtdna_backend.save_batch_output, 
        #   #inputs=[output_table, output_summary, output_flag, output_type], 
        #   inputs=[output_table, output_type], 
        #   outputs=[download_file])
    
        # submit_feedback.click(
        #     fn=mtdna_backend.store_feedback_to_google_sheets, 
        #     inputs=[single_accession, q1, q2, contact], outputs=feedback_status
        # )
        report_button.click(fn=show_report_ui, outputs=[report_textbox, submit_report_button, status_report])
        submit_report_button.click(fn=handle_submission, inputs=[report_textbox, user_email], outputs=[status_report, report_textbox, submit_report_button])
        
        # submit_feedback.click(
        #     fn=mtdna_backend.store_feedback_to_google_sheets,
        #     inputs=[raw_text, q1, q2, contact],
        #     outputs=[feedback_status]
        # )
        nps_submit.click(fn=submit_nps, inputs=[user_email, nps_radio], outputs=[nps_output])
        # Link each button to submit function
        
        gr.HTML("""
        <style>
          body, html {
              background-color: #121212 !important;
              color: #ffffff !important;
          }
        
          .gradio-container, .gr-block, .gr-box, textarea, input, select, .prose, .prose * {
              background-color: #1e1e1e !important;
              color: #ffffff !important;
              border-color: #333 !important;
          }
        
          textarea::placeholder,
          input::placeholder {
              color: #aaa !important;
          }
        
          button {
              background-color: #2d2d2d !important;
              color: #fff !important;
              border: 1px solid #444 !important;
          }
        
          a {
              color: #4ea1f3 !important;
          }

          /* Shared hover style for the three main buttons */
          #run-btn:hover, #stop-btn:hover, #reset-btn:hover {
              border-color: white !important;
              box-shadow: 0 0 5px white;
              transition: border-color 0.2s ease-in-out, box-shadow 0.2s ease-in-out;
          }
        
          /* Active click style */
          #run-btn:active, #stop-btn:active, #reset-btn:active {
              border-color: white !important;
              box-shadow: 0 0 5px white inset;
              }

        </style>
        """)
    
        #     # Custom CSS styles
        # gr.HTML("""
        # <style>
        #   /* Ensures both sections are equally spaced with the same background size */
        #   #output-summary, #output-flag {
        #       background-color: #f0f4f8; /* Light Grey for both */
        #       padding: 20px;
        #       border-radius: 10px;
        #       margin-top: 10px;
        #       width: 100%; /* Ensure full width */
        #       min-height: 150px; /* Ensures both have a minimum height */
        #       box-sizing: border-box; /* Prevents padding from increasing size */
        #       display: flex;
        #       flex-direction: column;
        #       justify-content: space-between;
        #   }
          
        #   /* Specific background colors */
        #   #output-summary {
        #       background-color: #434a4b; 
        #   }
    
        #   #output-flag {
        #       background-color: #141616; 
        #   }
    
        #   /* Ensuring they are in a row and evenly spaced */
        #   .gradio-row {
        #       display: flex;
        #       justify-content: space-between;
        #       width: 100%;
        #   }
        # </style>
        # """)
    with gr.Tab("CURIOUS ABOUT THIS PRODUCT?"):
        gr.HTML(value=flow_chart)
    
    with gr.Tab("PRICING"):
        gr.HTML(value=pricing_html)




interface.launch(share=True,debug=True)