Core Infrastructure

Systems

This infrastructure provides the foundation for fluid, natural interaction between users and agents across the desktop environment.

Narration System

The voice that brings agents to life:

  • Real-time text-to-speech generation

  • Voice model management

  • Audio stream handling

  • Emotion and tone control

  • Performance optimization

class VoiceHandler:
    async def generate_and_play(self, text: str):
        """Generate and play voice response"""
        audio = await self.elevenlabs_client.generate(
            text=text,
            voice_id=self.voice_id,
            model=self.voice_model
        )
        await self.play_audio(audio)

Voice Command System

Natural language interface for agents:

  • Voice input processing

  • Command recognition

  • Context awareness

  • Multi-command chaining

  • Real-time response

class VoiceCommandSystem:
    def __init__(self, config):
        self.client = AsyncOpenAI(api_key=config['api_keys']['openai'])
        self.sample_rate = 16000
        self.recording = False
        self.chunks = []

    async def start_recording(self):
        self.recording = True
        self.stream = sd.InputStream(
            channels=1,
            samplerate=self.sample_rate,
            callback=self._audio_callback
        )
        self.stream.start()

    async def stop_and_transcribe(self):
        self.recording = False
        self.stream.stop()
        audio_data = np.concatenate(self.chunks)
        
        # Send to Whisper API for transcription
        response = await self.client.audio.transcriptions.create(
            model="whisper-1",
            file=("audio.wav", self._prepare_audio(audio_data))
        )
        return response.text

Command Acceleration System

Supercharging agent actions:

  • Hotkey management

  • Command shortcuts

  • Action chaining

  • Quick access menus

  • Custom command flows

class CommandAccelerator:
    def __init__(self, config):
        self.client = AsyncOpenAI(api_key=config['api_keys']['openai'])
        self.command_history = []

    async def enhance_command(self, command: str) -> str:
        response = await self.client.chat.completions.create(
            model="gpt-4o-mini",
            messages=[
                {"role": "system", "content": "Enhance this command:"},
                {"role": "user", "content": command}
            ],
            temperature=0.7
        )
        enhanced = response.choices[0].message.content
        self.command_history.append((command, enhanced))
        return enhanced

    def get_command_suggestions(self, partial_command: str) -> list[str]:
        return [cmd for cmd, _ in self.command_history 
                if cmd.startswith(partial_command)]

Avatar Management System

Visual representation control:

  • Dynamic avatar states

  • Emotion visualization

  • Real-time animation

  • Style customization

  • Visual feedback

class AvatarManager:
    def __init__(self):
        self.current_avatar = None
        self.avatars = {}
        self.observers = []

    def set_avatar(self, avatar_id: str):
        if avatar_id in self.avatars:
            self.current_avatar = self.avatars[avatar_id]
            self._notify_observers()

    def update_avatar_state(self, state: str):
        if self.current_avatar:
            self.current_avatar.state = state
            self._notify_observers()

    def _notify_observers(self):
        for observer in self.observers:
            observer.on_avatar_update(self.current_avatar)

UI System

Modern, responsive interface:

  • Circular video avatar

  • Command input

  • Region selection

  • Status indicators

def init_ui(self):
    """Initialize the user interface"""
    # Set window size with scaling
    base_width = 200
    base_height = 380
    self.resize(
        int(base_width * self.scaling_factor * 0.5),
        int(base_height * self.scaling_factor * 0.5)
    )
    
    # Setup window properties
    self.setWindowFlags(Qt.FramelessWindowHint | Qt.WindowStaysOnTopHint)
    self.setAttribute(Qt.WA_TranslucentBackground)

Notification System

Seamless user updates:

  • Animated notifications

  • Progress tracking

  • Status updates

class NotificationWindow(QWidget):
    def show_message(self, message: str):
        """Show animated notification"""
        self.message_label.setText(message)
        self.animation.start()
        self.progress_timer.start()

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