LLM-ComputerUse/README.html at main · dalijon-byte/LLM-ComputerUse · GitHub

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<div class="max-w-4xl mx-auto px-5 py-10 bg-white shadow-md rounded-md markdown-body">
  <h1 class="font-bold text-gray-800 mb-2 flex items-center">
    <i class="fas fa-desktop text-blue-600 mr-3"></i>
    LLM Desktop Automation with Gemini 2.5 Vision
  </h1>
  <p class="text-lg mb-2 text-gray-700">Automate desktop interactions using AI vision &amp; language capabilities.</p>

  <div class="mb-6">
    <img src="https://repository-images.githubusercontent.com/803307245/b4eb447e-fdb7-4b00-baf5-0a3e66a5b492" alt="Project Banner" class="mb-4 rounded shadow w-full" style="max-height:204px;object-fit:cover;">
  </div>

  <h2><i class="fas fa-bolt mr-2"></i>Overview</h2>
  <p>
    <strong>LLM Desktop Automation</strong> is a Python framework that empowers you to control your desktop UI by natural language prompts.
    Harness the power of <strong>Gemini 2.5 Vision's API</strong> to visually understand your desktop, process commands, and perform intelligent mouse clicks using AI reasoning.
  </p>

  <h2><i class="fas fa-list-check mr-2"></i>Features</h2>
  <ul class="mb-6">
    <li><i class="fas fa-eye text-blue-500 mr-1"></i> Vision-powered recognition of desktop icons and windows</li>
    <li><i class="fas fa-mouse-pointer text-green-500 mr-1"></i> Smart mouse movement &amp; click via <code>pyautogui</code></li>
    <li><i class="fas fa-microchip text-purple-500 mr-1"></i> Natural language instructions powered by Gemini 2.5 LLM</li>
    <li><i class="fas fa-shield-alt text-yellow-500 mr-1"></i> Built-in safety prompts before high-impact actions</li>
    <li><i class="fas fa-laptop-code text-pink-400 mr-1"></i> Pythonic and readable code, ready to extend</li>
  </ul>

  <h2><i class="fas fa-image-polaroid mr-2"></i>How It Works</h2>
  <ol class="mb-6">
    <li>User types a command: <span class="bg-gray-100 px-2 py-1 rounded font-mono">Open Recycle Bin</span></li>
    <li>Screenshot of desktop is taken</li>
    <li>Screenshot is sent to <strong>Gemini 2.5 Vision</strong> for detection of clickable elements</li>
    <li>Structured screen analysis (elements + coordinates) is returned</li>
    <li>LLM matches user instruction to visual data, selects the target</li>
    <li>Python script uses <code>pyautogui</code> to move mouse and click the target</li>
    <li>(Optional) User is prompted to confirm risky actions</li>
  </ol>

  <h2><i class="fas fa-download mr-2"></i>Installation</h2>
  <pre><code># Clone the repository
git clone https://github.com/YOUR_USERNAME/llm-desktop-automation.git
cd llm-desktop-automation

# Install Python dependencies (Python 3.8+ recommended)
pip install -r requirements.txt
</code></pre>

  <h2><i class="fas fa-cogs mr-2"></i>Configuration</h2>
  <ol>
    <li>
      <strong>Set up Gemini API key:</strong>
      <ul>
        <li>Sign up for Gemini API and get your key: <a href="https://aistudio.google.com/app/apikey" target="_blank">Get API Key</a></li>
        <li>Create a <code>.env</code> file in your project root:
          <pre><code>GEMINI_API_KEY=your_gemini_2.5_vision_api_key_here</code></pre>
        </li>
      </ul>
    </li>
    <li>
      <strong>Adjust permissions:</strong> This script requires permission to capture your screen and control your mouse.
    </li>
  </ol>

  <h2><i class="fas fa-play-circle mr-2"></i>Usage Example</h2>
  <pre><code>python desktop_automation.py
</code></pre>
  <p>
    When prompted, type commands like:
    <code>Click the Chrome icon</code> <br>
    <code>Open Notepad</code> <br>
    <code>Open the Recycle Bin</code>
  </p>

  <h2><i class="fas fa-code mr-2"></i>Minimal Example</h2>
  <pre><code class="language-python">import os, pyautogui
from PIL import ImageGrab
import google.generativeai as genai
# ... Set up Gemini as in documentation

screenshot = ImageGrab.grab()
# Send screenshot and prompt to Gemini
# Parse result, get coordinates
pyautogui.moveTo(x, y)
pyautogui.click()
</code></pre>

  <h2><i class="fas fa-shield-halved mr-2"></i>Security Warning</h2>
  <div class="p-4 my-3 bg-red-50 border-l-4 border-red-400 text-red-800 rounded">
    <i class="fas fa-exclamation-circle"></i>
    <b>Warning:</b> Running this code gives the AI limited control of your mouse and keyboard.
    <br>
    Only use in safe, controlled environments. Carefully review all actions before confirming.
  </div>

  <h2><i class="fas fa-cube mr-2"></i>Project Structure</h2>
  <pre><code>llm-desktop-automation/
├─ desktop_automation.py
├─ requirements.txt
└─ README.md
</code></pre>

  <h2><i class="fas fa-laptop-code mr-2"></i>Dependencies</h2>
  <ul>
    <li><code>python-dotenv</code></li>
    <li><code>google-generativeai</code></li>
    <li><code>pyautogui</code></li>
    <li><code>pillow</code> (PIL)</li>
  </ul>

  <h2><i class="fas fa-hammer mr-2"></i>Extending</h2>
  <p>You can add:</p>
  <ul>
    <li>Voice command input via <code>SpeechRecognition</code></li>
    <li>Better vision models with OpenCV, YOLO, or LLaVA</li>
    <li>Self-verification for critical clicks</li>
  </ul>

  <h2><i class="fas fa-circle-info mr-2"></i>Troubleshooting</h2>
  <ul>
    <li>Errors about permissions? See your OS's privacy/accessibility settings for screen and input control</li>
    <li>Mouse not clicking where expected? Check your display scaling and resolution settings</li>
    <li>Gemini errors? Ensure API key is correct and you have quota</li>
  </ul>

  <h2><i class="fas fa-person-circle-question mr-2"></i>FAQ</h2>
  <details open>
    <summary class="font-semibold mb-2">Is this production ready?</summary>
    <p>No – it is a research/prototype tool. Use in controlled environments only.</p>
  </details>
  <details>
    <summary class="font-semibold mb-2">Can I use other LLMs?</summary>
    <p>Yes, via API adjustments, but Gemini 2.5 Vision recommended for best multi-modal performance.</p>
  </details>
  <details>
    <summary class="font-semibold mb-2">Can it close popups or interact with notifications?</summary>
    <p>If they appear in the screenshot, and are visually distinct, yes.</p>
  </details>

  <h2><i class="fas fa-gavel mr-2"></i>License</h2>
  <p>
    This project is <strong>MIT Licensed</strong>.<br>
    <span class="text-xs text-gray-500">Copyright © 2025 Dalibor JONIC, MSc</span>
  </p>
  <pre><code>MIT License

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
</code></pre>

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