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import gradio as gr |
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import json |
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from datetime import datetime |
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from datasets import Dataset |
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from huggingface_hub import login, HfApi |
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import pandas as pd |
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import os |
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import time |
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import tempfile |
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import logging |
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logging.basicConfig(level=logging.INFO) |
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logger = logging.getLogger(__name__) |
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HF_TOKEN = os.environ.get("HF_TOKEN") |
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if HF_TOKEN: |
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login(token=HF_TOKEN) |
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logger.info("✅ Authenticated with Hugging Face") |
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else: |
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logger.warning("⚠️ HF_TOKEN not found - running without authentication") |
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DATASET_NAME = "ysharma/gradio-hackathon-registrations-winter-2025" |
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COUNTER = """ |
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<!DOCTYPE html> |
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<html lang="en"> |
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<head> |
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<meta charset="UTF-8"> |
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<meta name="viewport" content="width=device-width, initial-scale=1.0"> |
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<title>Hackathon Countdown</title> |
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<style> |
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* { |
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margin: 0; |
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padding: 0; |
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box-sizing: border-box; |
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} |
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body { |
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif; |
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margin: 0; |
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padding: 20px; |
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} |
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.countdown-container { |
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background: linear-gradient(135deg, #0a0a0a 0%, #FF7A00 35%, #4A90E2 70%, #ffffff 100%); |
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border-radius: 20px; |
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padding: 40px; |
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box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15); |
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text-align: center; |
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max-width: 600px; |
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width: 100%; |
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margin: 0 auto; |
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display: block; |
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} |
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.title { |
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font-size: 28px; |
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font-weight: 600; |
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color: white; |
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margin-bottom: 40px; |
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} |
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.countdown { |
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display: flex; |
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justify-content: space-around; |
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align-items: center; |
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gap: 20px; |
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flex-wrap: wrap; |
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} |
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.time-unit { |
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display: flex; |
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flex-direction: column; |
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align-items: center; |
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min-width: 100px; |
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} |
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.circle { |
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position: relative; |
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width: 100px; |
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height: 100px; |
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margin-bottom: 15px; |
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} |
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.circle svg { |
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width: 100%; |
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height: 100%; |
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transform: rotate(-90deg); |
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} |
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.circle-bg { |
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fill: none; |
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stroke: rgba(0, 0, 0, 0.3); |
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stroke-width: 6; |
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} |
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.circle-progress { |
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fill: none; |
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stroke: black; |
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stroke-width: 6; |
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stroke-linecap: round; |
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stroke-dasharray: 283; |
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stroke-dashoffset: 283; |
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transition: stroke-dashoffset 0.3s ease; |
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} |
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.number { |
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position: absolute; |
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top: 50%; |
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left: 50%; |
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transform: translate(-50%, -50%); |
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font-size: 32px; |
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font-weight: 700; |
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color: white; |
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font-family: 'Courier New', monospace; |
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} |
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.label { |
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font-size: 16px; |
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font-weight: 500; |
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color: white; |
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text-transform: uppercase; |
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letter-spacing: 1px; |
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} |
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@media (max-width: 480px) { |
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.countdown { |
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gap: 15px; |
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} |
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.circle { |
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width: 80px; |
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height: 80px; |
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} |
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.number { |
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font-size: 24px; |
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} |
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.title { |
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font-size: 22px; |
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margin-bottom: 30px; |
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} |
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} |
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</style> |
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</head> |
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<body> |
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<div class="countdown-container"> |
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<h1 class="title">Countdown to the Global Event Has Begun. Registrations are now open!</h1> |
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<div class="countdown"> |
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<div class="time-unit"> |
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<div class="circle"> |
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<svg> |
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<circle class="circle-bg" cx="50" cy="50" r="45"></circle> |
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<circle class="circle-progress" cx="50" cy="50" r="45" id="days-progress"></circle> |
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</svg> |
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<div class="number" id="days">00</div> |
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</div> |
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<div class="label">Days</div> |
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</div> |
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<div class="time-unit"> |
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<div class="circle"> |
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<svg> |
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<circle class="circle-bg" cx="50" cy="50" r="45"></circle> |
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<circle class="circle-progress" cx="50" cy="50" r="45" id="hours-progress"></circle> |
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</svg> |
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<div class="number" id="hours">00</div> |
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</div> |
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<div class="label">Hours</div> |
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</div> |
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<div class="time-unit"> |
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<div class="circle"> |
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<svg> |
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<circle class="circle-bg" cx="50" cy="50" r="45"></circle> |
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<circle class="circle-progress" cx="50" cy="50" r="45" id="minutes-progress"></circle> |
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</svg> |
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<div class="number" id="minutes">00</div> |
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</div> |
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<div class="label">Minutes</div> |
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</div> |
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<div class="time-unit"> |
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<div class="circle"> |
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<svg> |
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<circle class="circle-bg" cx="50" cy="50" r="45"></circle> |
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<circle class="circle-progress" cx="50" cy="50" r="45" id="seconds-progress"></circle> |
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</svg> |
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<div class="number" id="seconds">00</div> |
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</div> |
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<div class="label">Seconds</div> |
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</div> |
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</div> |
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</div> |
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<script> |
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// Set target date to November 30, 2025, 11:59 PM UTC |
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const targetDate = new Date(Date.UTC(2025, 10, 13, 23, 59, 59)); // Month is 0-indexed (10 = November) |
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function updateCountdown() { |
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const now = new Date(); |
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const difference = targetDate.getTime() - now.getTime(); |
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if (difference > 0) { |
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const days = Math.floor(difference / (1000 * 60 * 60 * 24)); |
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const hours = Math.floor((difference % (1000 * 60 * 60 * 24)) / (1000 * 60 * 60)); |
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const minutes = Math.floor((difference % (1000 * 60 * 60)) / (1000 * 60)); |
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const seconds = Math.floor((difference % (1000 * 60)) / 1000); |
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// Update numbers |
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document.getElementById('days').textContent = days.toString().padStart(2, '0'); |
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document.getElementById('hours').textContent = hours.toString().padStart(2, '0'); |
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document.getElementById('minutes').textContent = minutes.toString().padStart(2, '0'); |
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document.getElementById('seconds').textContent = seconds.toString().padStart(2, '0'); |
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// Update progress circles |
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updateProgress('days-progress', days, 365); |
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updateProgress('hours-progress', hours, 24); |
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updateProgress('minutes-progress', minutes, 60); |
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updateProgress('seconds-progress', seconds, 60); |
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} else { |
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// Countdown has ended |
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document.getElementById('days').textContent = '00'; |
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document.getElementById('hours').textContent = '00'; |
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document.getElementById('minutes').textContent = '00'; |
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document.getElementById('seconds').textContent = '00'; |
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// Reset all progress circles |
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updateProgress('days-progress', 0, 365); |
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updateProgress('hours-progress', 0, 24); |
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updateProgress('minutes-progress', 0, 60); |
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updateProgress('seconds-progress', 0, 60); |
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} |
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} |
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function updateProgress(elementId, current, max) { |
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const circle = document.getElementById(elementId); |
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const circumference = 283; |
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const progress = (current / max) * circumference; |
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const offset = circumference - progress; |
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circle.style.strokeDashoffset = offset; |
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} |
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// Update countdown immediately and then every second |
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updateCountdown(); |
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setInterval(updateCountdown, 1000); |
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</script> |
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</body> |
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</html> |
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""" |
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def safe_add_to_dataset(registration_data, max_retries=5, retry_delay=3): |
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""" |
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Safely add new registration data with bulletproof error handling |
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NEVER creates new datasets - only adds to existing ones |
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""" |
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try: |
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logger.info("Starting new registration process") |
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new_row = { |
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"timestamp": registration_data["timestamp"], |
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"full_name": registration_data["personal_info"]["full_name"], |
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"email": registration_data["personal_info"]["email"], |
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"hf_username": registration_data["personal_info"]["hf_username"], |
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"gradio_usage": registration_data["personal_info"]["gradio_usage"], |
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"track_interest": str(registration_data["participation"]["track_interest"]), |
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"previous_participation": registration_data["participation"]["previous_participation"], |
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"experience_level": registration_data["participation"]["experience_level"], |
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"how_heard": registration_data["participation"]["how_heard"], |
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"project_description": registration_data["additional"]["project_description"] or "", |
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} |
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logger.info("Created new row data") |
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existing_df = None |
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load_successful = False |
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for attempt in range(max_retries): |
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logger.info(f"Loading attempt {attempt + 1}/{max_retries}") |
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try: |
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api = HfApi() |
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files = api.list_repo_files(DATASET_NAME, repo_type="dataset") |
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parquet_files = [f for f in files if f.endswith('.parquet') and 'train' in f] |
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if parquet_files: |
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logger.info(f"Found parquet file: {parquet_files[0]}") |
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with tempfile.TemporaryDirectory() as temp_dir: |
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parquet_file = api.hf_hub_download( |
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repo_id=DATASET_NAME, |
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filename=parquet_files[0], |
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repo_type="dataset", |
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cache_dir=temp_dir, |
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force_download=True |
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) |
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existing_df = pd.read_parquet(parquet_file) |
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logger.info(f"Successfully loaded {len(existing_df)} existing rows") |
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load_successful = True |
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break |
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else: |
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logger.warning("No parquet files found") |
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except Exception as load_error: |
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logger.warning(f"Attempt {attempt + 1} failed: {str(load_error)[:100]}") |
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if attempt < max_retries - 1: |
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logger.info(f"Waiting {retry_delay} seconds before retry...") |
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time.sleep(retry_delay) |
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continue |
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if not load_successful or existing_df is None: |
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error_msg = "🚨 CRITICAL SAFETY ERROR: Could not load existing dataset after multiple attempts." |
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logger.error(error_msg) |
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logger.error("🚨 REFUSING to proceed to prevent data loss!") |
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logger.error("🚨 Please check dataset manually or contact administrators.") |
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return False, ( |
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"❌ Registration temporarily unavailable due to technical issues. " |
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"Please try again in a few minutes. If the problem persists, contact support." |
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) |
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duplicate_check = existing_df[ |
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(existing_df['email'].str.lower() == new_row['email'].lower()) | |
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(existing_df['hf_username'].str.lower() == new_row['hf_username'].lower()) |
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] |
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if len(duplicate_check) > 0: |
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logger.warning("Duplicate registration attempt detected") |
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return False, "❌ Error: This email or Hugging Face username is already registered." |
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combined_df = pd.concat([existing_df, pd.DataFrame([new_row])], ignore_index=True) |
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logger.info(f"Combined data now has {len(combined_df)} rows (was {len(existing_df)})") |
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backup_timestamp = int(time.time()) |
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try: |
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logger.info("Converting to HuggingFace Dataset format...") |
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updated_dataset = Dataset.from_pandas(combined_df) |
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backup_name = f"{DATASET_NAME}-auto-backup-{backup_timestamp}" |
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logger.info(f"Creating backup: {backup_name}") |
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updated_dataset.push_to_hub(backup_name, private=True) |
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logger.info("Pushing to main dataset...") |
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updated_dataset.push_to_hub(DATASET_NAME, private=True) |
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logger.info("✅ Successfully saved new registration") |
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logger.info(f"Total rows in dataset: {len(combined_df)}") |
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time.sleep(2) |
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try: |
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verify_files = api.list_repo_files(DATASET_NAME, repo_type="dataset") |
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logger.info("✅ Upload verification: Files updated successfully") |
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except: |
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logger.warning("⚠️ Could not verify upload (this may be normal)") |
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return True, "Registration successful!" |
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except Exception as upload_error: |
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error_msg = str(upload_error).lower() |
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if any(indicator in error_msg for indicator in ['rate limit', '429', 'too many requests']): |
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logger.warning("🚨 Rate limit hit - registration system temporarily busy") |
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return False, "⏳ Registration temporarily unavailable due to high server load. Please try again in 10-15 minutes." |
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else: |
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logger.error(f"Upload failed: {upload_error}") |
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return False, f"❌ Registration failed during upload: {str(upload_error)}" |
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except Exception as e: |
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logger.error(f"❌ Unexpected error in registration: {e}") |
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import traceback |
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traceback.print_exc() |
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return False, f"❌ Registration failed: {str(e)}" |
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def submit_registration(full_name, email, hf_username, gradio_usage, |
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track_interest, previous_participation, experience_level, how_heard, |
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acknowledgment, project_description): |
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"""Process the registration form submission with enhanced validation""" |
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if not full_name or not full_name.strip(): |
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return "❌ Error: Please enter your full name" |
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if not email or not email.strip(): |
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return "❌ Error: Please enter your email address" |
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if not hf_username or not hf_username.strip(): |
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return "❌ Error: Please enter your Hugging Face username" |
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if not gradio_usage: |
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return "❌ Error: Please select how you're currently using Gradio" |
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if not track_interest: |
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return "❌ Error: Please select at least one track of interest" |
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if not previous_participation: |
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return "❌ Error: Please select your hackathon experience" |
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if not experience_level: |
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return "❌ Error: Please select your experience level" |
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if not how_heard: |
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return "❌ Error: Please select how you heard about this hackathon" |
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if not acknowledgment: |
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return "❌ Error: Please confirm your acknowledgment to participate" |
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import re |
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email_pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$' |
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if not re.match(email_pattern, email.strip()): |
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return "❌ Error: Please enter a valid email address" |
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registration_data = { |
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"timestamp": datetime.now().isoformat(), |
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"personal_info": { |
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"full_name": full_name.strip(), |
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"email": email.strip().lower(), |
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"hf_username": hf_username.strip(), |
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"gradio_usage": gradio_usage, |
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}, |
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"participation": { |
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"track_interest": track_interest, |
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"previous_participation": previous_participation, |
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"experience_level": experience_level, |
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"how_heard": how_heard, |
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}, |
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"additional": { |
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"project_description": project_description.strip() if project_description else None, |
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} |
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} |
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success, message = safe_add_to_dataset(registration_data) |
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if not success: |
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return f"❌ Registration failed: {message}" |
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return f"""✅ Registration Successful! |
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Thank you, {full_name}! Your registration has been received and saved.<br> |
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📧 You will receive information about API credits as we finalize sponsor partnerships.<br> |
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🔑 API and Compute credits will be distributed before or during the Hackathon starting date.<br> |
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💬 Be sure to **join the Huggingface organization** for regular updates on the hackathon and **to submit your entries**. Join our Discord community channel `agents-mcp-hackathon-winter25🏆` for updates and support during the event: https://discord.gg/YgswRqxQ |
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**See you at the hackathon! 🚀**""" |
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def check_dataset_health(): |
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"""Check if the dataset is accessible and healthy""" |
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try: |
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api = HfApi() |
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files = api.list_repo_files(DATASET_NAME, repo_type="dataset") |
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parquet_files = [f for f in files if f.endswith('.parquet')] |
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if parquet_files: |
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logger.info(f"✅ Dataset health check passed - found {len(parquet_files)} parquet files") |
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return True |
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else: |
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logger.warning("⚠️ Dataset health check: No parquet files found") |
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return False |
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except Exception as e: |
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logger.error(f"❌ Dataset health check failed: {e}") |
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return False |
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logger.info("🚀 Starting Gradio Hackathon Registration System - Winter 2025") |
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logger.info(f"📊 Dataset: {DATASET_NAME}") |
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if check_dataset_health(): |
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logger.info("✅ System ready - dataset is healthy") |
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else: |
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logger.warning("⚠️ System starting with dataset health warnings") |
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custom_css = """ |
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.gradio-container { |
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font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif; |
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} |
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.header-gradient { |
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background: linear-gradient(135deg, #0a0a0a 0%, #FF7A00 35%, #4A90E2 70%, #ffffff 100%); |
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-webkit-background-clip: text; |
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-webkit-text-fill-color: transparent; |
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background-clip: text; |
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} |
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/* Gradient Submit Button Styling */ |
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#gradient-submit-btn { |
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background: linear-gradient(135deg, #0a0a0a 0%, #FF7A00 35%, #4A90E2 70%, #ffffff 100%) !important; |
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border: none !important; |
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color: white !important; |
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font-weight: 600 !important; |
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font-size: 18px !important; |
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padding: 16px 32px !important; |
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border-radius: 12px !important; |
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box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15) !important; |
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transition: all 0.3s ease !important; |
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text-transform: none !important; |
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} |
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#gradient-submit-btn:hover { |
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transform: translateY(-2px) !important; |
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box-shadow: 0 6px 20px rgba(0, 0, 0, 0.25) !important; |
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} |
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#gradient-submit-btn:active { |
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transform: translateY(0px) !important; |
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box-shadow: 0 2px 8px rgba(0, 0, 0, 0.2) !important; |
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} |
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/* Disabled state for the button */ |
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#gradient-submit-btn:disabled { |
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opacity: 0.6 !important; |
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cursor: not-allowed !important; |
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transform: none !important; |
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} |
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""" |
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with gr.Blocks(title="Gradio Agents & MCP Hackathon - Winter 2025", css=custom_css, theme="ocean") as demo: |
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gr.Markdown(""" |
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# 🤖 Gradio Agents & MCP Hackathon - Winter 2025 Registration 🚀 |
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**Join our [Discord Community](https://discord.gg/YgswRqxQ) channel `agents-mcp-hackathon-winter25🏆` for active support during the hackathon.** |
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**NOTE: If the registration app says you are registered, then that information is correct and you don't need to send us anything else. NO CONFIRMATION EMAILS ARE SENT FROM OUR SIDE.** |
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**📅 Event Dates:** November 14-30, 2025 (17 days, 3 weekends) | **🏆 Prizes: $15,000+ USD in cash prizes** | **💻 Location:** Online & Global |
|
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|
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|
**🎁 FREE API & Compute Credits** (Details announced soon): |
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- API credits from major AI providers |
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- Access to latest and strongest LLMs |
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- Compute resources for building your projects |
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|
**The definitive Agents & MCP event is back!** OpenAI, Microsoft, Google DeepMind, and numerous startups have already adopted MCP. Join the community that launched the MCP developer movement. Participate and stand a chance to learn the latest AI technologies and also Win BIG! |
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""") |
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gr.HTML(COUNTER) |
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gr.Markdown("---") |
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with gr.Row(): |
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with gr.Column(): |
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gr.Markdown("## 1. Personal Information") |
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full_name = gr.Textbox( |
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label="Full Name *", |
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|
placeholder="Your full name as you'd like it on certificates", |
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|
max_lines=1 |
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) |
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email = gr.Textbox( |
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label="Email Address *", |
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|
placeholder="Primary contact email (we'll send important updates here)", |
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max_lines=1 |
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) |
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hf_username = gr.Textbox( |
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|
label="Hugging Face Username *", |
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|
placeholder="Required for organization access and submissions", |
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|
max_lines=1 |
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|
) |
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gradio_usage = gr.Radio( |
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|
label="How are you currently using Gradio? *", |
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|
choices=[ |
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|
"Professional work - My company uses Gradio", |
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|
"Personal projects - Building side projects", |
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|
"Academic/Research - University or research work", |
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|
"Learning - New to Gradio, want to learn", |
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|
"Not using yet - Interested to start" |
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|
], |
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info="Helps us understand our community better" |
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|
) |
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|
with gr.Column(): |
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|
gr.Markdown("## 2. Hackathon Participation") |
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|
track_interest = gr.CheckboxGroup( |
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|
label="Which track interests you most? *", |
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|
choices=[ |
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|
"Track 1: MCP Tools & Servers", |
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|
"Track 2: Agentic Applications", |
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|
] |
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|
) |
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|
previous_participation = gr.Radio( |
|
|
label="Hackathon experience *", |
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|
choices=[ |
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|
"I participated in June 2025 Agents & MCP Hackathon", |
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|
"I've done other AI hackathons before", |
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|
"This is my first AI hackathon" |
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|
] |
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|
) |
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|
experience_level = gr.Radio( |
|
|
label="Your experience with AI/Agents development *", |
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|
choices=[ |
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|
"Beginner - New to AI development", |
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|
"Intermediate - Some AI projects", |
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|
"Advanced - Regular AI developer", |
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|
"Expert - Professional AI engineer" |
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|
] |
|
|
) |
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|
|
how_heard = gr.Dropdown( |
|
|
label="How did you hear about this hackathon? *", |
|
|
choices=[ |
|
|
"Hugging Face email/newsletter", |
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|
"Twitter/X", |
|
|
"LinkedIn", |
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|
"Discord", |
|
|
"From a colleague/friend", |
|
|
"YouTube", |
|
|
"Reddit", |
|
|
"Sponsor announcement", |
|
|
"I participated in June 2025", |
|
|
"Other" |
|
|
] |
|
|
) |
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|
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|
|
with gr.Row(): |
|
|
with gr.Column(): |
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|
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|
|
gr.Markdown("## 3. Additional Information") |
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|
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|
|
project_description = gr.Textbox( |
|
|
label="What type of project are you most excited to build?", |
|
|
placeholder="Brief description of your project idea or what interests you most", |
|
|
lines=3 |
|
|
) |
|
|
|
|
|
with gr.Column(): |
|
|
|
|
|
gr.Markdown("## 4. Acknowledgment") |
|
|
|
|
|
acknowledgment = gr.Checkbox( |
|
|
label="Acknowledgment *", |
|
|
info="""I commit to actively participate and submit a project by November 30, 2025. I understand that API/compute credits are provided to support hackathon participation and should be used for building my hackathon project. I commit to using these credits responsibly during the event period.""", |
|
|
) |
|
|
|
|
|
|
|
|
submit_btn = gr.Button("🚀 Register for Hackathon", variant="primary", size="lg", elem_id="gradient-submit-btn") |
|
|
|
|
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|
|
output = gr.Markdown() |
|
|
|
|
|
|
|
|
def handle_registration_with_state(*args): |
|
|
try: |
|
|
result = submit_registration(*args) |
|
|
return result, gr.Button("🚀 Register for Hackathon", interactive=True, variant="primary") |
|
|
except Exception as e: |
|
|
logger.error(f"Registration handling error: {e}") |
|
|
return f"❌ An unexpected error occurred: {str(e)}", gr.Button("🚀 Register for Hackathon", interactive=True, variant="primary") |
|
|
|
|
|
|
|
|
submit_btn.click( |
|
|
fn=lambda *args: (gr.Button("⏳ Processing Registration...", interactive=False, variant="secondary"), ""), |
|
|
inputs=[ |
|
|
full_name, email, hf_username, gradio_usage, |
|
|
track_interest, previous_participation, experience_level, how_heard, |
|
|
acknowledgment, project_description, |
|
|
], |
|
|
outputs=[submit_btn, output], |
|
|
queue=False |
|
|
).then( |
|
|
fn=handle_registration_with_state, |
|
|
inputs=[ |
|
|
full_name, email, hf_username, gradio_usage, |
|
|
track_interest, previous_participation, experience_level, how_heard, |
|
|
acknowledgment, project_description, |
|
|
], |
|
|
outputs=[output, submit_btn], |
|
|
queue=True |
|
|
) |
|
|
|
|
|
|
|
|
gr.Markdown(""" |
|
|
**Questions?** Join Huggingface [Discord](https://discord.gg/fveShqytyh) or email: gradio-team@huggingface.co |
|
|
""") |
|
|
|
|
|
if __name__ == "__main__": |
|
|
demo.launch(allowed_paths=["."]) |
