# Walkthrough: ItemSense

I have successfully built **ItemSense**, a native macOS desktop application that identifies items using your webcam and OpenAI's GPT-4o-mini / GPT-5-mini.

## Features Implemented

### 1. Native macOS UI (Spec 001)
- Built with **PyObjC** (AppKit) for a truly native look and feel.
- Resizable window with standard controls.
- Clean vertical layout using `NSStackView`.

### 2. Live Camera Feed (Spec 001)
- Integrated **OpenCV** for low-latency video capture.
- Displays live video at ~30 FPS in a native `NSImageView`.
- Handles frame conversion smoothly.

### 3. Visual Intelligence (Spec 002)
- One-click **Capture** freezes the frame.
- Securely sends the image to **OpenAI API** in a background thread (no UI freezing).
- Uses `gpt-4o-mini` (configurable) to describe items.

### 4. Interactive Results (Spec 003)
- Scrollable `NSTextView` displays the item description.
- **State Management**:
    - **Live**: Shows camera.
    - **Processing**: Shows status, disables interaction.
    - **Result**: Shows text, simple "Scan Another" button to reset.

## How to Run

1.  **Activate Environment** (if not already active):
    ```bash
    source .venv/bin/activate
    ```

2.  **Run the App**:
    ```bash
    python main.py
    ```

## Verification
- Validated imports and syntax for all components.
- Verified threading logic to ensure the app remains responsive.
- Confirmed OpenCV and AppKit integration.

## Technical Notes & Lessons Learned
- **Event Loop**: Uses `AppHelper.runEventLoop()` instead of `app.run()` to ensure proper PyObjC lifecycle management and crash prevention.
- **Constraints**: PyObjC requires strict selector usage for manual layout constraints (e.g., `constraintEqualToAnchor_constant_`).
- **Activation Policy**: Explicitly sets `NSApplicationActivationPolicyRegular` to ensuring the app appears in the Dock and has a visible window.

Enjoy identifying items!