AI WebSocket Channel

const aiToken = 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9...';
const ws = new WebSocket(`ws://localhost:8080/ws/ai?token=${aiToken}`);

ws.onopen = () => {
  console.log('🤖 AI system connected');
};

ws.onmessage = (event) => {
  const notification = JSON.parse(event.data);
  console.log('🔔 Received notification:', notification);
  
  if (notification.event === 'NEW_SURGERY') {
    handleNewSurgery(notification.surgeryId);
  }
};

ws.onerror = (error) => {
  console.error('❌ WebSocket error:', error);
};

ws.onclose = (event) => {
  console.log(`🔌 Disconnected: ${event.code}`);
};

import axios from 'axios';

class AIAnalysisSystem {
  constructor(aiToken, apiBaseUrl) {
    this.token = aiToken;
    this.apiBaseUrl = apiBaseUrl;
    this.ws = null;
  }

  connect() {
    this.ws = new WebSocket(`ws://localhost:8080/ws/ai?token=${this.token}`);

    this.ws.onopen = () => {
      console.log('🤖 AI system connected and ready');
    };

    this.ws.onmessage = async (event) => {
      const notification = JSON.parse(event.data);

      // Handle connection confirmation
      if (notification.status === 'connected') {
        console.log('✅', notification.message);
        return;
      }

      // Handle new surgery notification
      if (notification.event === 'NEW_SURGERY') {
        console.log(`🔔 New surgery: ${notification.surgeryId}`);
        await this.processSurgery(notification.surgeryId);
      }
    };

    this.ws.onerror = (error) => {
      console.error('❌ WebSocket error:', error);
    };

    this.ws.onclose = (event) => {
      console.log('🔌 Disconnected, reconnecting in 5s...');
      setTimeout(() => this.connect(), 5000);
    };
  }

  async processSurgery(surgeryId) {
    try {
      // 1. Fetch trajectory data
      console.log(`📥 Fetching trajectory for ${surgeryId}`);
      const response = await axios.get(
        `${this.apiBaseUrl}/surgeries/${surgeryId}/trajectory`,
        {
          headers: { Authorization: `Bearer ${this.token}` }
        }
      );

      const trajectory = response.data;

      // 2. Analyze the surgery
      console.log(`🧠 Analyzing ${trajectory.movements.length} movements...`);
      const analysis = this.analyzeSurgery(trajectory);

      // 3. Submit analysis
      console.log(`📤 Submitting analysis (score: ${analysis.score})`);
      await axios.post(
        `${this.apiBaseUrl}/surgeries/${surgeryId}/analysis`,
        analysis,
        {
          headers: { Authorization: `Bearer ${this.token}` }
        }
      );

      console.log(`✅ Analysis complete for ${surgeryId}`);
    } catch (error) {
      console.error(`❌ Error processing surgery ${surgeryId}:`, error.message);
    }
  }

  analyzeSurgery(trajectory) {
    // Simple scoring algorithm (replace with actual AI model)
    const movements = trajectory.movements;
    const duration = new Date(trajectory.endTime) - new Date(trajectory.startTime);
    const durationMinutes = duration / 60000;

    // Count events
    const tumorTouches = movements.filter(m => m.event === 'TUMOR_TOUCH').length;
    const hemorrhages = movements.filter(m => m.event === 'HEMORRHAGE').length;

    // Calculate score (0-100)
    let score = 100;
    score -= tumorTouches * 10; // -10 per tumor touch
    score -= hemorrhages * 20;   // -20 per hemorrhage
    score -= Math.max(0, durationMinutes - 15) * 2; // -2 per minute over 15
    score = Math.max(0, Math.min(100, score));

    // Generate feedback
    const feedback = `
      Surgery completed in ${durationMinutes.toFixed(1)} minutes.
      Tumor contacts: ${tumorTouches}
      Hemorrhage events: ${hemorrhages}
      
      ${score >= 90 ? 'Excellent performance!' : ''}
      ${score >= 70 && score < 90 ? 'Good performance with room for improvement.' : ''}
      ${score < 70 ? 'Practice recommended to improve precision and speed.' : ''}
      
      ${tumorTouches > 0 ? 'Minimize tumor contact to prevent spread.' : ''}
      ${hemorrhages > 0 ? 'Focus on vascular control techniques.' : ''}
    `.trim();

    return { score, feedback };
  }
}

// Usage
const aiSystem = new AIAnalysisSystem(
  'your-ai-jwt-token',
  'http://localhost:8080/api/v1'
);
aiSystem.connect();