AI-DataScience-Lab/index.html at main · Hariprashad-Ravikumar/AI-DataScience-Lab · GitHub

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<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8" />
  <meta name="viewport" content="width=device-width, initial-scale=1.0"/>
  <title>AI DataScience Lab</title>
  <style>
    body {
      margin: 0;
      padding: 40px 0;
      font-family: 'Segoe UI', sans-serif;
      color: #fff;
      background: linear-gradient(-45deg, #1b2735, #2c5364, #0f2027, #203a43);
      background-size: 400% 400%;
      animation: gradientBG 20s ease infinite;
    }

    @keyframes gradientBG {
      0% {background-position: 0% 50%;}
      50% {background-position: 100% 50%;}
      100% {background-position: 0% 50%;}
    }

    h1, label {
      text-align: center;
      color: #f1f1f1;
    }

    h3 {
      text-align: left;
      color: #f1f1f1;
    }

    h4 {
      text-align: center;
      color: #f1f1f1;
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    h2 {
      font-weight: normal;
      font-size: 16px;
      color: #ccc;
      text-align: center;
    }

    .section {
      margin: 30px auto;
      text-align: center;
    }

    .section-left {
      max-width: 800px;
      margin: 30px auto;
      text-align: left;
      padding: 0 20px;
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    form {
      display: flex;
      flex-direction: column;
      align-items: center;
    }

    label {
      margin-bottom: 5px;
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    input[type="file"],
    input[type="text"],
    select {
      width: 200px;
      margin-bottom: 10px;
      padding: 8px;
      border-radius: 6px;
      border: 1px solid #ccc;
      font-size: 14px;
      background-color: #fff;
      color: #000;
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    button {
      padding: 8px 16px;
      margin: 5px 0;
      border-radius: 6px;
      border: none;
      background-color: #00bcd4;
      color: white;
      cursor: pointer;
      font-size: 14px;
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    button:hover {
      background-color: #0097a7;
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    .progress-bar {
      width: 200px;
      height: 8px;
      background-color: #eee;
      border-radius: 4px;
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      margin-top: 5px;
      margin-bottom: 15px;
      display: none;
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    .progress-fill {
      height: 100%;
      width: 0%;
      transition: width 0.4s ease;
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    .green { background-color: #4CAF50; }
    .blue { background-color: #2196F3; }

    .output-box {
      background: rgba(255, 255, 255, 0.1);
      padding: 15px;
      border: 1px solid #66d9ef;
      border-radius: 8px;
      color: #e0f7fa;
      font-size: 14px;
      font-family: monospace;
      white-space: pre-wrap;
      overflow-x: auto;
      max-width: 100%;
    }

    img {
      display: block;
      max-width: 100%;
      margin-top: 10px;
      border-radius: 8px;
    }

    .hidden {
      display: none;
    }

    .footer {
      text-align: center;
      font-size: 13px;
      color: #ccc;
      margin-top: 60px;
    }

    .footer a, a {
      color: #66d9ef;
      text-decoration: none;
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    .dropdown-label {
      text-align: left;
      margin-left: 20px;
      font-weight: bold;
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    .more-note {
      font-size: 12px;
      color: #aaa;
      text-align: left;
      margin-left: 20px;
      font-style: italic;
    }

    .description {
      text-align: left;
      max-width: 800px;
      margin: 0 auto 20px;
      padding: 0 20px;
      color: #ddd;
      font-size: 15px;
      line-height: 1.5;
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    .note {
      font-size: 13px;
      color: #ccc;
      margin-top: -5px;
      margin-bottom: 10px;
    }
    .fade-in {
  opacity: 0;
  transform: translateY(20px);
  animation: fadeInUp 0.6s ease-out forwards;
}

@keyframes fadeInUp {
  to {
    opacity: 1;
    transform: translateY(0);
  }
}
  </style>
</head>

<!-- Google tag (gtag.js) -->
<script async src="https://www.googletagmanager.com/gtag/js?id=G-9D3J9V8DM9"></script>
<script>
  window.dataLayer = window.dataLayer || [];
  function gtag(){dataLayer.push(arguments);}
  gtag('js', new Date());

  gtag('config', 'G-9D3J9V8DM9');
</script>

<body>
  <h1>AI Data-Science Lab</h1>
  <h2>Built with Pandas, scikit-learn, and OpenAI GPT-3.5 API</h2>
  <h2>(<a href="https://github.com/Hariprashad-Ravikumar/AI-DataScience-Lab" target="_blank">View source code on Hari's GitHub</a>)</h2>


  <!-- Upload -->
  <div class="section">
    <h4>Upload your dataset to receive intelligent insights powered by AI. Our tool cleans your data, builds a predictive model, and explains the trends using OpenAI. Visualizations and downloadable reports included.</h4>
    <form id="uploadForm">
      <label for="fileInput">Choose CSV File</label>
      <input type="file" id="fileInput" name="file" required />

      <button id="loadColumnsBtn" type="button">Upload</button>
      <div id="uploadProgress" class="progress-bar"><div class="progress-fill green" id="uploadFill"></div></div>

      <label for="xColumn" class="hidden">X Column</label>
      <select id="xColumn" name="x_column" class="hidden"></select>

      <label for="yColumn" class="hidden">Y Column</label>
      <select id="yColumn" name="y_column" class="hidden"></select>

      <button id="submitProcessing" class="hidden" type="submit">Submit for Processing</button>
      <div id="processProgress" class="progress-bar"><div class="progress-fill green" id="processFill"></div></div>
    </form>
  </div>

  <!-- Model selection -->
  <div class="section-left">
    <label class="dropdown-label">Choose Regression</label>
    <select id="regressionModel" name="model" disabled>
      <option value="linear">Linear Regression</option>
    </select>
    <div class="more-note">(More regression models coming in v2)</div>
  </div>

  <!-- Processing results -->
  <div id="processingResults" class="hidden">
    <div class="section-left">
      <h3>Processing Log</h3>
      <div class="output-box" id="log">Loading modules: pandas, scikit-learn, matplotlib...</div>
    </div>
    <div class="section-left">
      <h3>Data Summary (by OpenAI GPT-3.5 API)</h3>
      <div class="output-box" id="summary" style="max-height: 200px; overflow-y: auto;"></div>
    </div>
    <div class="section-left">
      <h3>Model Performance</h3>
      <div class="output-box" id="metrics"></div>
    </div>
    <div class="section-left">
      <h3>Scatter Plot</h3>
      <img id="plot" style="display:none;" alt="Scatter Plot" />
    </div>
    <div class="section">
      <form id="predictForm">
        <label for="futureInput">Enter future values (comma-separated)</label>
        <div class="note">Example: 2025-12-01, 2025-12-02, ... or 11, 12, 13</div>
        <input type="text" id="futureInput" name="future_x" />
        <button type="submit">Predict</button>
        <div id="predictProgress" class="progress-bar"><div class="progress-fill blue" id="predictFill"></div></div>
      </form>
    </div>
  </div>

  <!-- Forecast results -->
  <div id="forecastResults" class="hidden">
    <div class="section-left">
      <h3>Forecast Result</h3>
      <div class="output-box" id="forecast"></div>
    </div>
    <div class="section-left">
      <h3>Forecast Visualization</h3>
      <img id="forecastPlot" style="display:none;" alt="Forecast Plot" />
    </div>
    <div class="section">
      <a href="https://ai-dslab-backend-cpf2feachnetbbck.westus-01.azurewebsites.net/download-report" target="_blank">
        <button>Download PDF Report</button>
      </a>
    </div>
  </div>


  <div class="footer">
    <small style="color:#aaa;">App Version: 1.0.0 (Beta)</small>
    <br> &copy; 2025 Hariprashad Ravikumar · All rights reserved<br>
    <a href="https://hariprashad-ravikumar.github.io" target="_blank">Website</a> ·
    <a href="https://github.com/Hariprashad-Ravikumar" target="_blank">GitHub</a>
  </div>

  <!-- JavaScript -->
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    const xColumn = document.getElementById('xColumn');
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    const uploadFill = document.getElementById('uploadFill');
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    const predictFill = document.getElementById('predictFill');
    const processingResults = document.getElementById('processingResults');
    const forecastResults = document.getElementById('forecastResults');

    document.getElementById('loadColumnsBtn').addEventListener('click', async () => {
      const file = fileInput.files[0];
      if (!file) return alert("Please select a CSV file.");

      const formData = new FormData();
      formData.append('file', file);

      document.getElementById('uploadProgress').style.display = 'block';
      uploadFill.style.width = '30%';

      const res = await fetch('https://ai-dslab-backend-cpf2feachnetbbck.westus-01.azurewebsites.net/get-columns', {
        method: 'POST',
        body: formData
      });

      const data = await res.json();
      if (!data.columns) return alert("Failed to load columns.");

      xColumn.innerHTML = yColumn.innerHTML = '';
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      formData.append('model', 'linear');

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      document.getElementById('summary').textContent = data.summary || '';
      document.getElementById('log').textContent = data.log || '';
      document.getElementById('metrics').textContent = `R² Score: ${data.r2_score}\nMSE: ${data.mse}`;
      document.getElementById('plot').src = data.plot_url;
      document.getElementById('plot').style.display = 'block';
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      document.getElementById('forecastPlot').style.display = 'block';
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  </script>

</body>
</html>