Cloud Desktop with Streaming

This example demonstrates how to create a cloud desktop with streaming capabilities using CodecFlow. The desktop uses MCP (Model Context Protocol) for AI integration and TEE (Trusted Execution Environment) for secure operations.

TypeScript

import { CodecFlow } from '@codecflow/sdk';

async function createStreamingDesktop() {
  // Initialize CodecFlow with secure API key
  const codecflow = new CodecFlow({
    apiKey: process.env.CODECFLOW_API_KEY
  });

  // Create a secure desktop with TEE
  const desktop = await codecflow.createDesktop({
    os: 'windows',
    version: '11',
    security: {
      teeEnabled: true,
      encryptedStorage: true,
      isolationLevel: 'high'
    },
    resources: {
      memory: '16gb',
      cpu: 8,
      gpu: true // Enable GPU for streaming
    }
  });

  // Create browser for web access
  const browser = await desktop.createBrowser();
  await browser.navigate('https://example.com');

  // Connect AI agent with MCP
  const agent = await desktop.connectAgent({
    model: 'gpt-4',
    protocol: 'mcp',
    config: {
      capabilities: ['browser', 'network', 'system', 'streaming'],
      contextProviders: [
        {
          type: 'content-analysis',
          sources: ['web-page', 'system-events']
        }
      ]
    }
  });

  // Configure Twitch streaming
  const stream = await desktop.createStream({
    platform: 'twitch',
    credentials: {
      streamKey: process.env.TWITCH_STREAM_KEY,
      channelName: process.env.TWITCH_CHANNEL
    },
    settings: {
      resolution: '1080p',
      fps: 30,
      bitrate: '6000k',
      title: 'AI Desktop Stream',
      category: 'Just Chatting'
    }
  });

  // Create stream overlay
  const overlay = await stream.createOverlay({
    template: 'standard',
    elements: {
      header: {
        title: 'AI Desktop Demo',
        subtitle: 'Powered by CodecFlow'
      },
      footer: {
        text: 'Built with CodecFlow Cloud Desktops'
      }
    }
  });

  // Start desktop and streaming
  await desktop.start();
  await stream.start();

  // Update overlay with real-time data
  desktop.on('systemUpdate', (data) => {
    overlay.update('systemInfo', {
      data: data.metrics
    });
  });

  // Handle Twitch chat with AI responses
  stream.on('chat', async (message) => {
    const response = await agent.executeAction({
      type: 'communication',
      action: 'generateChatResponse',
      params: {
        message: message.content,
        user: message.username
      }
    });

    await stream.sendChatMessage(response);
  });

  // Secure shutdown when done
  process.on('SIGINT', async () => {
    // End stream with goodbye message
    await stream.sendChatMessage('Stream ending. Thanks for watching!');
    await stream.stop();

    // Shutdown desktop
    await desktop.shutdown();
    process.exit(0);
  });
}

createStreamingDesktop().catch(console.error);

Python

import os
import signal
from codecflow import CodecFlow

async def create_streaming_desktop():
    # Initialize CodecFlow with secure API key
    codecflow = CodecFlow(
        api_key=os.environ.get('CODECFLOW_API_KEY')
    )

    # Create a secure desktop with TEE
    desktop = await codecflow.create_desktop(
        os='windows',
        version='11',
        security={
            'tee_enabled': True,
            'encrypted_storage': True,
            'isolation_level': 'high'
        },
        resources={
            'memory': '16gb',
            'cpu': 8,
            'gpu': True  # Enable GPU for streaming
        }
    )

    # Create browser for web access
    browser = await desktop.create_browser()
    await browser.navigate('https://example.com')

    # Connect AI agent with MCP
    agent = await desktop.connect_agent(
        model='gpt-4',
        protocol='mcp',
        config={
            'capabilities': ['browser', 'network', 'system', 'streaming'],
            'context_providers': [
                {
                    'type': 'content-analysis',
                    'sources': ['web-page', 'system-events']
                }
            ]
        }
    )

    # Configure Twitch streaming
    stream = await desktop.create_stream(
        platform='twitch',
        credentials={
            'stream_key': os.environ.get('TWITCH_STREAM_KEY'),
            'channel_name': os.environ.get('TWITCH_CHANNEL')
        },
        settings={
            'resolution': '1080p',
            'fps': 30,
            'bitrate': '6000k',
            'title': 'AI Desktop Stream',
            'category': 'Just Chatting'
        }
    )

    # Create stream overlay
    overlay = await stream.create_overlay(
        template='standard',
        elements={
            'header': {
                'title': 'AI Desktop Demo',
                'subtitle': 'Powered by CodecFlow'
            },
            'footer': {
                'text': 'Built with CodecFlow Cloud Desktops'
            }
        }
    )

    # Start desktop and streaming
    await desktop.start()
    await stream.start()

    # Update overlay with real-time data
    def on_system_update(data):
        overlay.update('system_info', {
            'data': data['metrics']
        })

    desktop.on('systemUpdate', on_system_update)

    # Handle Twitch chat with AI responses
    async def on_chat(message):
        response = await agent.execute_action({
            'type': 'communication',
            'action': 'generate_chat_response',
            'params': {
                'message': message['content'],
                'user': message['username']
            }
        })

        await stream.send_chat_message(response)

    stream.on('chat', on_chat)

    # Secure shutdown when done
    def handle_shutdown(sig, frame):
        # End stream with goodbye message
        await stream.send_chat_message('Stream ending. Thanks for watching!')
        await stream.stop()

        # Shutdown desktop
        await desktop.shutdown()
        exit(0)

    signal.signal(signal.SIGINT, handle_shutdown)

# Run the streaming desktop
await create_streaming_desktop()

Key Features

• Cloud Desktop Provisioning: Instantly spin up a Windows 11 desktop with GPU support
• Secure Environment: Uses TEE to protect sensitive operations and data
• AI Integration: Leverages MCP to connect AI models with the desktop environment
• Live Streaming: Configures and manages streaming to Twitch with professional overlays
• Interactive: Responds to viewer chat messages using the AI agent
• Resource Optimization: Automatically provisions appropriate resources for streaming

Note: This example requires appropriate API keys and credentials for Twitch streaming.