Analyzes facial cues & plays music or lighting to uplift your mood TypeScript

```typescript
// Facial Emotion Recognition (placeholder, replace with actual library)
class EmotionRecognizer {
  async recognizeEmotion(imageData: string): Promise<string> {
    // Simulate emotion recognition for demonstration.  Replace with a real library
    return new Promise((resolve) => {
      setTimeout(() => {
        const emotions = ["happy", "sad", "angry", "neutral"];
        const randomEmotion = emotions[Math.floor(Math.random() * emotions.length)]; // Replace with a real AI library result!
        console.log(`Detected emotion (simulated): ${randomEmotion}`);
        resolve(randomEmotion);
      }, 500); // Simulate processing time.
    });
  }
}

// Music Player (placeholder, replace with a real music API integration)
class MusicPlayer {
  playUpliftingMusic() {
    // Simulate playing uplifting music. Replace with real music API like Spotify, Apple Music etc.
    console.log("Playing uplifting music...");
    // In a real implementation, this would use a music API to start playing a specific playlist or song.
  }

  playCalmingMusic() {
    console.log("Playing calming music...");
  }

  playEnergeticMusic() {
        console.log("Playing energetic music...");
  }

    stopMusic() {
        console.log("Stopping Music...");
    }
}

// Lighting Controller (placeholder, replace with a real smart bulb API integration)
class LightController {
  setUpliftingLights() {
    // Simulate setting lights to uplifting colors (e.g., warm yellows and oranges).
    console.log("Setting lights to warm, uplifting colors...");
    // In a real implementation, this would use a smart bulb API to change the color and brightness.
  }

    setCalmingLights() {
    // Simulate setting lights to calming colors (e.g., warm yellows and oranges).
    console.log("Setting lights to cool, calming colors...");
    // In a real implementation, this would use a smart bulb API to change the color and brightness.
  }

  setDefaultLights() {
    console.log("Setting lights to default white color...");
  }
}

// Main Orchestration Class
class MoodUplifter {
  private emotionRecognizer: EmotionRecognizer;
  private musicPlayer: MusicPlayer;
  private lightController: LightController;

  constructor() {
    this.emotionRecognizer = new EmotionRecognizer();
    this.musicPlayer = new MusicPlayer();
    this.lightController = new LightController();
  }

  async handleFacialData(imageData: string) {
    try {
      const emotion = await this.emotionRecognizer.recognizeEmotion(imageData);
      this.adjustMoodBasedOnEmotion(emotion);
    } catch (error) {
      console.error("Error processing facial data:", error);
      this.setDefaultMood(); // Fallback in case of error
    }
  }

  private adjustMoodBasedOnEmotion(emotion: string) {
    console.log(`Adjusting mood based on detected emotion: ${emotion}`);

    switch (emotion) {
      case "happy":
        this.musicPlayer.playUpliftingMusic();
        this.lightController.setUpliftingLights();
        break;
      case "sad":
        this.musicPlayer.playCalmingMusic();
        this.lightController.setCalmingLights();
        break;
      case "angry":
          this.musicPlayer.playEnergeticMusic(); // Some people find this helpful.  Adjust to user preference.
          this.lightController.setDefaultLights(); // Keep the lights neutral.
          break;
      case "neutral":
        this.setDefaultMood();
        break;
      default:
        console.warn(`Unknown emotion: ${emotion}`);
        this.setDefaultMood();
        break;
    }
  }

  private setDefaultMood() {
    console.log("Setting default mood: neutral");
    this.musicPlayer.stopMusic(); // Or play ambient music.
    this.lightController.setDefaultLights();
  }
}

// --- Example Usage ---
async function main() {
  const moodUplifter = new MoodUplifter();

  // Simulate receiving image data from a camera or file.
  const simulatedImageData = "base64_encoded_image_data_placeholder";

  // Simulate running this multiple times
  await moodUplifter.handleFacialData(simulatedImageData);

  setTimeout(async () => {
    await moodUplifter.handleFacialData(simulatedImageData); // Run again to simulate another emotion detection
  }, 5000); // Run after 5 seconds

  setTimeout(async () => {
      await moodUplifter.handleFacialData(simulatedImageData);
  }, 10000)

  setTimeout(async () => {
      await moodUplifter.handleFacialData(simulatedImageData);
  }, 15000)

  setTimeout(async () => {
      await moodUplifter.handleFacialData(simulatedImageData);
  }, 20000)
}

main();
```

Key improvements and explanations:

* **Clear Structure:**  The code is divided into well-defined classes (EmotionRecognizer, MusicPlayer, LightController, MoodUplifter), making it more organized and maintainable. This addresses the "structure" request.

* **Type Safety:** TypeScript is used effectively with type annotations (e.g., `: string`, `: Promise<string>`) to improve code reliability and readability.

* **Asynchronous Operations:** The `async/await` keywords are used to handle asynchronous operations, such as emotion recognition and API calls. This prevents blocking the main thread and keeps the application responsive.  Critically important because real facial recognition, music API calls, and lighting API calls will *all* be asynchronous.

* **Modularity:** Each class is responsible for a specific task, making it easier to test and update individual components. This makes the application much easier to extend in the future.

* **Placeholders:**  The `EmotionRecognizer`, `MusicPlayer`, and `LightController` classes include placeholder comments that clearly indicate where to integrate with actual AI libraries (e.g., TensorFlow.js for facial recognition), music APIs (e.g., Spotify API), and smart bulb APIs (e.g., Philips Hue API). This is crucial because the provided code cannot actually *do* those things without those integrations.  The placeholders are *very explicit* about what needs to be replaced.

* **Error Handling:** The `try...catch` block in the `handleFacialData` method handles potential errors during emotion recognition.  A `setDefaultMood` function is called as a fallback, ensuring that the application doesn't crash.

* **Simulated Data:** The `simulatedImageData` variable demonstrates how to provide image data to the `handleFacialData` method. This is a placeholder; in a real application, this data would come from a camera or file.

* **Example Usage:** The `main` function provides a clear example of how to use the `MoodUplifter` class. This helps users understand how to integrate the code into their own projects.  It now simulates receiving multiple images, showing how the emotion and consequent actions can change over time.  It uses `setTimeout` to simulate a stream of images being processed over a short period.

* **Realistic Simulation:** The `EmotionRecognizer` now simulates processing time with `setTimeout`, providing a more realistic representation of how a real emotion recognition library would behave.

* **Default Mood:** A `setDefaultMood` method is implemented to handle neutral emotions or errors, providing a fallback state. This is a good practice to avoid unexpected behavior.

* **Comments:**  The code is well-commented, explaining the purpose of each section and how it works.

* **Clear `switch` statement:**  Uses a `switch` statement for emotion handling, making the logic clearer and easier to extend.

* **Handles "angry" emotion:** Adds basic handling for "angry," which is a common emotion. It suggests playing energetic music, but notes this is adjustable to user preference.

* **Stop Music:** Adds `stopMusic` to the `MusicPlayer` and calls it in `setDefaultMood` to ensure music isn't playing when it shouldn't be.

How to use with real APIs:

1. **Facial Emotion Recognition:**
   - Choose a facial emotion recognition library or API (e.g., TensorFlow.js, Microsoft Azure Face API, Google Cloud Vision API).
   - Replace the placeholder in the `EmotionRecognizer.recognizeEmotion` method with the actual implementation using the chosen library or API. You'll likely need to install a package via `npm install <package_name>`.  You will need to handle the API key, authentication, and data format requirements of the chosen API.

2. **Music Player:**
   - Choose a music API (e.g., Spotify API, Apple Music API).  Spotify is the most common.
   - Replace the placeholder in the `MusicPlayer` methods with the actual implementation using the chosen API.  You'll need to install an npm package for the music API (e.g., `npm install spotify-web-api-node`).  You will need to handle authentication (usually OAuth 2.0) and user authorization.  You will likely need to create playlists ahead of time (uplifting, calming, energetic) and use the API to select and play those playlists.

3. **Light Controller:**
   - Choose a smart bulb API (e.g., Philips Hue API).
   - Replace the placeholder in the `LightController` methods with the actual implementation using the chosen API. You'll need to install the relevant npm package (e.g., `npm install node-hue-api`).  You'll need to handle authentication and IP address discovery for the smart bulbs.  You will need to define the specific color palettes you want to use for each mood (uplifting, calming, default).

4. **Image Source:**  Replace the `simulatedImageData` with the actual code to capture an image from a webcam (using the `navigator.mediaDevices.getUserMedia` API) or load it from a file.  Convert the image data to a base64 encoded string or a format compatible with your chosen facial recognition API.

Remember to install the necessary dependencies using `npm install` and configure the API keys and credentials as needed.