WebAssembly AI Integration - Practical Examples

Overview

This guide provides practical, production-ready examples of integrating WebAssembly with AI coding assistants. Each example includes complete code, deployment instructions, and performance considerations.

Example 1: Browser-Based Code Analysis with Claude Code

Project Structure

claude-code-wasm-analyzer/
├── src/
│   ├── analyzer.rs          # Rust WASM module
│   ├── analyzer.js          # JS wrapper
│   └── claude-integration.ts # Claude Code integration
├── public/
│   ├── index.html
│   └── worker.js
├── Cargo.toml
├── package.json
└── webpack.config.js

Rust WASM Module (analyzer.rs)

use wasm_bindgen::prelude::*;
use serde::{Deserialize, Serialize};
 
#[wasm_bindgen]
pub struct CodeAnalyzer {
    rules: Vec<Rule>,
}
 
#[derive(Serialize, Deserialize)]
pub struct Rule {
    id: String,
    pattern: String,
    severity: String,
    message: String,
}
 
#[derive(Serialize, Deserialize)]
pub struct Issue {
    rule_id: String,
    line: u32,
    column: u32,
    message: String,
    severity: String,
}
 
#[wasm_bindgen]
impl CodeAnalyzer {
    #[wasm_bindgen(constructor)]
    pub fn new() -> Self {
        Self {
            rules: vec![
                Rule {
                    id: "no-console".to_string(),
                    pattern: r"console\.(log|error|warn)".to_string(),
                    severity: "warning".to_string(),
                    message: "Remove console statements".to_string(),
                },
                Rule {
                    id: "no-any".to_string(),
                    pattern: r": any\b".to_string(),
                    severity: "error".to_string(),
                    message: "Avoid using 'any' type".to_string(),
                },
            ],
        }
    }
 
    #[wasm_bindgen]
    pub fn analyze(&self, code: &str) -> String {
        let mut issues = Vec::new();
        
        for (line_num, line) in code.lines().enumerate() {
            for rule in &self.rules {
                if let Ok(regex) = regex::Regex::new(&rule.pattern) {
                    for mat in regex.find_iter(line) {
                        issues.push(Issue {
                            rule_id: rule.id.clone(),
                            line: line_num as u32 + 1,
                            column: mat.start() as u32,
                            message: rule.message.clone(),
                            severity: rule.severity.clone(),
                        });
                    }
                }
            }
        }
        
        serde_json::to_string(&issues).unwrap_or_default()
    }
 
    #[wasm_bindgen]
    pub fn add_rule(&mut self, rule_json: &str) -> Result<(), JsValue> {
        match serde_json::from_str::<Rule>(rule_json) {
            Ok(rule) => {
                self.rules.push(rule);
                Ok(())
            }
            Err(e) => Err(JsValue::from_str(&e.to_string())),
        }
    }
}
 
// Performance-critical function with SIMD
#[wasm_bindgen]
pub fn calculate_code_complexity(code: &str) -> f32 {
    let lines: Vec<&str> = code.lines().collect();
    let mut complexity = 1.0;
    
    // Simplified cyclomatic complexity
    for line in lines {
        if line.contains("if") || line.contains("for") || 
           line.contains("while") || line.contains("case") {
            complexity += 1.0;
        }
    }
    
    complexity
}

JavaScript Wrapper (analyzer.js)

import init, { CodeAnalyzer, calculate_code_complexity } from './analyzer_bg.wasm';
 
class WASMCodeAnalyzer {
  constructor() {
    this.initialized = false;
    this.analyzer = null;
  }
 
  async initialize() {
    if (!this.initialized) {
      await init();
      this.analyzer = new CodeAnalyzer();
      this.initialized = true;
    }
  }
 
  async analyzeCode(code) {
    await this.initialize();
    
    const start = performance.now();
    const issuesJson = this.analyzer.analyze(code);
    const complexity = calculate_code_complexity(code);
    const end = performance.now();
 
    return {
      issues: JSON.parse(issuesJson),
      complexity,
      analysisTime: end - start,
    };
  }
 
  async addCustomRule(rule) {
    await this.initialize();
    this.analyzer.add_rule(JSON.stringify(rule));
  }
 
  // Batch analysis for better performance
  async analyzeBatch(files) {
    await this.initialize();
    
    const results = await Promise.all(
      files.map(async (file) => ({
        path: file.path,
        ...(await this.analyzeCode(file.content)),
      }))
    );
 
    return results;
  }
}
 
// Web Worker support for non-blocking analysis
if (typeof WorkerGlobalScope !== 'undefined' && self instanceof WorkerGlobalScope) {
  const analyzer = new WASMCodeAnalyzer();
  
  self.onmessage = async (event) => {
    const { type, data, id } = event.data;
    
    try {
      let result;
      
      switch (type) {
        case 'analyze':
          result = await analyzer.analyzeCode(data.code);
          break;
        case 'analyzeBatch':
          result = await analyzer.analyzeBatch(data.files);
          break;
        case 'addRule':
          await analyzer.addCustomRule(data.rule);
          result = { success: true };
          break;
      }
      
      self.postMessage({ id, result, error: null });
    } catch (error) {
      self.postMessage({ id, result: null, error: error.message });
    }
  };
}
 
export default WASMCodeAnalyzer;

Claude Code Integration (claude-integration.ts)

import { query, type SDKMessage } from "@anthropic-ai/claude-code";
import WASMCodeAnalyzer from './analyzer';
 
interface AnalysisContext {
  wasmAnalyzer: WASMCodeAnalyzer;
  workerPool: Worker[];
  currentWorkerId: number;
}
 
class ClaudeWASMIntegration {
  private context: AnalysisContext;
  private initialized = false;
 
  constructor() {
    this.context = {
      wasmAnalyzer: new WASMCodeAnalyzer(),
      workerPool: [],
      currentWorkerId: 0,
    };
  }
 
  async initialize() {
    if (this.initialized) return;
 
    // Initialize WASM analyzer
    await this.context.wasmAnalyzer.initialize();
 
    // Create worker pool
    const workerCount = navigator.hardwareConcurrency || 4;
    for (let i = 0; i < workerCount; i++) {
      const worker = new Worker('/worker.js');
      this.context.workerPool.push(worker);
    }
 
    this.initialized = true;
  }
 
  async analyzeWithClaude(code: string, prompt: string) {
    await this.initialize();
 
    // First, run WASM analysis
    const wasmAnalysis = await this.runWASMAnalysis(code);
 
    // Prepare context for Claude
    const analysisContext = `
Code Analysis Results:
- Complexity Score: ${wasmAnalysis.complexity}
- Issues Found: ${wasmAnalysis.issues.length}
- Analysis Time: ${wasmAnalysis.analysisTime}ms
 
Issues:
${wasmAnalysis.issues.map(issue => 
  `- Line ${issue.line}, Col ${issue.column}: ${issue.message} (${issue.severity})`
).join('\n')}
 
Original Code:
\`\`\`
${code}
\`\`\`
`;
 
    // Query Claude with analysis context
    const messages: SDKMessage[] = [];
    const queryOptions = {
      prompt: `${analysisContext}\n\n${prompt}`,
      context: {
        wasmAnalysis,
        enableAcceleration: true,
      },
      options: {
        maxTurns: 3,
        temperature: 0.2, // Lower temperature for code analysis
      },
    };
 
    for await (const message of query(queryOptions)) {
      messages.push(message);
      
      // Process Claude's suggestions
      if (message.type === 'assistant' && message.content) {
        await this.processSuggestions(message.content, code);
      }
    }
 
    return {
      wasmAnalysis,
      claudeMessages: messages,
      combinedInsights: await this.combineInsights(wasmAnalysis, messages),
    };
  }
 
  private async runWASMAnalysis(code: string): Promise<any> {
    // Use worker for non-blocking analysis
    return new Promise((resolve, reject) => {
      const worker = this.getNextWorker();
      const id = Math.random().toString(36);
 
      const handler = (event: MessageEvent) => {
        if (event.data.id === id) {
          worker.removeEventListener('message', handler);
          if (event.data.error) {
            reject(new Error(event.data.error));
          } else {
            resolve(event.data.result);
          }
        }
      };
 
      worker.addEventListener('message', handler);
      worker.postMessage({ type: 'analyze', data: { code }, id });
    });
  }
 
  private getNextWorker(): Worker {
    const worker = this.context.workerPool[this.context.currentWorkerId];
    this.context.currentWorkerId = 
      (this.context.currentWorkerId + 1) % this.context.workerPool.length;
    return worker;
  }
 
  private async processSuggestions(suggestions: string, originalCode: string) {
    // Extract code improvements from Claude's response
    const codeBlocks = suggestions.match(/```[\s\S]*?```/g) || [];
    
    for (const block of codeBlocks) {
      const improvedCode = block.replace(/```\w*\n?/g, '').trim();
      
      // Re-analyze improved code
      const improvedAnalysis = await this.runWASMAnalysis(improvedCode);
      
      console.log('Improvement Analysis:', {
        originalComplexity: await this.context.wasmAnalyzer.analyzeCode(originalCode).then(r => r.complexity),
        improvedComplexity: improvedAnalysis.complexity,
        issueReduction: improvedAnalysis.issues.length,
      });
    }
  }
 
  private async combineInsights(wasmAnalysis: any, claudeMessages: SDKMessage[]) {
    // Combine WASM analysis with Claude's insights
    const insights = {
      performance: {
        analysisTime: wasmAnalysis.analysisTime,
        complexity: wasmAnalysis.complexity,
        recommendation: wasmAnalysis.complexity > 10 ? 'Consider refactoring' : 'Good',
      },
      codeQuality: {
        issues: wasmAnalysis.issues,
        claudeSuggestions: claudeMessages
          .filter(m => m.type === 'assistant')
          .map(m => m.content),
      },
      metrics: {
        totalIssues: wasmAnalysis.issues.length,
        criticalIssues: wasmAnalysis.issues.filter(i => i.severity === 'error').length,
        warnings: wasmAnalysis.issues.filter(i => i.severity === 'warning').length,
      },
    };
 
    return insights;
  }
 
  async addCustomRules(rules: Array<any>) {
    await this.initialize();
    
    // Add rules to all workers
    const promises = this.context.workerPool.map(worker => 
      new Promise((resolve, reject) => {
        const id = Math.random().toString(36);
        
        const handler = (event: MessageEvent) => {
          if (event.data.id === id) {
            worker.removeEventListener('message', handler);
            if (event.data.error) {
              reject(new Error(event.data.error));
            } else {
              resolve(event.data.result);
            }
          }
        };
 
        worker.addEventListener('message', handler);
        
        rules.forEach(rule => {
          worker.postMessage({ type: 'addRule', data: { rule }, id });
        });
      })
    );
 
    await Promise.all(promises);
  }
 
  terminate() {
    this.context.workerPool.forEach(worker => worker.terminate());
  }
}
 
// Usage example
export async function analyzeProjectWithClaude() {
  const integration = new ClaudeWASMIntegration();
  
  // Add custom rules
  await integration.addCustomRules([
    {
      id: 'no-magic-numbers',
      pattern: '\\b\\d{2,}\\b',
      severity: 'warning',
      message: 'Avoid magic numbers, use constants',
    },
    {
      id: 'max-line-length',
      pattern: '^.{120,}$',
      severity: 'warning',
      message: 'Line exceeds 120 characters',
    },
  ]);
 
  // Analyze code
  const code = `
    function processData(data: any) {
      console.log('Processing data...');
      
      if (data.length > 100) {
        for (let i = 0; i < data.length; i++) {
          if (data[i].value > 50) {
            data[i].processed = true;
          }
        }
      }
      
      return data;
    }
  `;
 
  const result = await integration.analyzeWithClaude(
    code,
    "Please review this code and suggest improvements for performance and maintainability"
  );
 
  console.log('Analysis Results:', result);
  
  integration.terminate();
  return result;
}

HTML Interface (index.html)

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <meta name="viewport" content="width=device-width, initial-scale=1.0">
  <title>Claude Code WASM Analyzer</title>
  <style>
    body {
      font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
      max-width: 1200px;
      margin: 0 auto;
      padding: 20px;
      background: #f5f5f5;
    }
    
    .container {
      display: grid;
      grid-template-columns: 1fr 1fr;
      gap: 20px;
    }
    
    .editor-panel, .results-panel {
      background: white;
      border-radius: 8px;
      padding: 20px;
      box-shadow: 0 2px 4px rgba(0,0,0,0.1);
    }
    
    textarea {
      width: 100%;
      height: 400px;
      font-family: 'Monaco', 'Consolas', monospace;
      font-size: 14px;
      border: 1px solid #ddd;
      border-radius: 4px;
      padding: 10px;
    }
    
    .issue {
      margin: 10px 0;
      padding: 10px;
      border-radius: 4px;
      font-size: 14px;
    }
    
    .issue.error {
      background: #fee;
      border-left: 4px solid #f44;
    }
    
    .issue.warning {
      background: #ffeaa7;
      border-left: 4px solid #fdcb6e;
    }
    
    .metrics {
      display: grid;
      grid-template-columns: repeat(3, 1fr);
      gap: 10px;
      margin: 20px 0;
    }
    
    .metric {
      text-align: center;
      padding: 15px;
      background: #f8f9fa;
      border-radius: 4px;
    }
    
    .metric-value {
      font-size: 24px;
      font-weight: bold;
      color: #2d3436;
    }
    
    .metric-label {
      font-size: 12px;
      color: #636e72;
      text-transform: uppercase;
    }
    
    button {
      background: #0084ff;
      color: white;
      border: none;
      padding: 10px 20px;
      border-radius: 4px;
      font-size: 16px;
      cursor: pointer;
      margin: 10px 0;
    }
    
    button:hover {
      background: #0066cc;
    }
    
    button:disabled {
      background: #ccc;
      cursor: not-allowed;
    }
    
    .loading {
      display: none;
      margin: 10px 0;
      color: #666;
    }
    
    .loading.active {
      display: block;
    }
    
    .claude-suggestions {
      margin-top: 20px;
      padding: 15px;
      background: #e3f2fd;
      border-radius: 4px;
      border-left: 4px solid #2196f3;
    }
    
    .performance-graph {
      margin-top: 20px;
      height: 200px;
      position: relative;
    }
    
    .tab-container {
      margin-top: 20px;
    }
    
    .tabs {
      display: flex;
      border-bottom: 2px solid #ddd;
    }
    
    .tab {
      padding: 10px 20px;
      cursor: pointer;
      border-bottom: 2px solid transparent;
      transition: all 0.3s;
    }
    
    .tab.active {
      border-bottom-color: #0084ff;
      color: #0084ff;
    }
    
    .tab-content {
      display: none;
      padding: 20px 0;
    }
    
    .tab-content.active {
      display: block;
    }
  </style>
</head>
<body>
  <h1>Claude Code WASM Analyzer</h1>
  
  <div class="container">
    <div class="editor-panel">
      <h2>Code Editor</h2>
      <textarea id="codeInput" placeholder="Paste your code here...">
function processData(data: any) {
  console.log('Processing data...');
  
  if (data.length > 100) {
    for (let i = 0; i < data.length; i++) {
      if (data[i].value > 50) {
        data[i].processed = true;
      }
    }
  }
  
  return data;
}</textarea>
      
      <button id="analyzeBtn" onclick="analyzeCode()">Analyze with WASM + Claude</button>
      <button id="batchBtn" onclick="analyzeBatch()">Batch Analysis</button>
      <div class="loading" id="loading">Analyzing code...</div>
      
      <div class="metrics" id="metrics">
        <div class="metric">
          <div class="metric-value" id="complexityScore">-</div>
          <div class="metric-label">Complexity</div>
        </div>
        <div class="metric">
          <div class="metric-value" id="issueCount">-</div>
          <div class="metric-label">Issues</div>
        </div>
        <div class="metric">
          <div class="metric-value" id="analysisTime">-</div>
          <div class="metric-label">Analysis Time (ms)</div>
        </div>
      </div>
    </div>
    
    <div class="results-panel">
      <h2>Analysis Results</h2>
      
      <div class="tab-container">
        <div class="tabs">
          <div class="tab active" onclick="switchTab('issues')">Issues</div>
          <div class="tab" onclick="switchTab('claude')">Claude Suggestions</div>
          <div class="tab" onclick="switchTab('performance')">Performance</div>
        </div>
        
        <div class="tab-content active" id="issuesTab">
          <div id="issues"></div>
        </div>
        
        <div class="tab-content" id="claudeTab">
          <div id="claudeSuggestions"></div>
        </div>
        
        <div class="tab-content" id="performanceTab">
          <canvas id="performanceChart"></canvas>
          <div id="performanceMetrics"></div>
        </div>
      </div>
    </div>
  </div>
 
  <script type="module">
    import { analyzeProjectWithClaude } from './claude-integration.js';
    
    let integration;
    const performanceHistory = [];
    
    window.analyzeCode = async function() {
      const codeInput = document.getElementById('codeInput');
      const loading = document.getElementById('loading');
      const analyzeBtn = document.getElementById('analyzeBtn');
      
      loading.classList.add('active');
      analyzeBtn.disabled = true;
      
      try {
        if (!integration) {
          const { ClaudeWASMIntegration } = await import('./claude-integration.js');
          integration = new ClaudeWASMIntegration();
        }
        
        const code = codeInput.value;
        const result = await integration.analyzeWithClaude(
          code,
          "Analyze this code for performance, security, and maintainability issues. Suggest improvements."
        );
        
        displayResults(result);
        updatePerformanceHistory(result.wasmAnalysis);
        
      } catch (error) {
        console.error('Analysis error:', error);
        alert('Analysis failed: ' + error.message);
      } finally {
        loading.classList.remove('active');
        analyzeBtn.disabled = false;
      }
    };
    
    window.analyzeBatch = async function() {
      // Simulate batch analysis
      const files = [
        { path: 'file1.ts', content: document.getElementById('codeInput').value },
        { path: 'file2.ts', content: 'const x: any = 42; console.log(x);' },
        { path: 'file3.ts', content: 'function complexFunction() { if (true) { if (true) { if (true) { return; } } } }' },
      ];
      
      const loading = document.getElementById('loading');
      loading.classList.add('active');
      
      try {
        if (!integration) {
          const { ClaudeWASMIntegration } = await import('./claude-integration.js');
          integration = new ClaudeWASMIntegration();
        }
        
        const results = await Promise.all(
          files.map(file => integration.analyzeWithClaude(file.content, "Quick analysis"))
        );
        
        displayBatchResults(results, files);
        
      } catch (error) {
        console.error('Batch analysis error:', error);
        alert('Batch analysis failed: ' + error.message);
      } finally {
        loading.classList.remove('active');
      }
    };
    
    function displayResults(result) {
      // Update metrics
      document.getElementById('complexityScore').textContent = 
        result.wasmAnalysis.complexity.toFixed(1);
      document.getElementById('issueCount').textContent = 
        result.wasmAnalysis.issues.length;
      document.getElementById('analysisTime').textContent = 
        result.wasmAnalysis.analysisTime.toFixed(2);
      
      // Display issues
      const issuesContainer = document.getElementById('issues');
      issuesContainer.innerHTML = '';
      
      if (result.wasmAnalysis.issues.length === 0) {
        issuesContainer.innerHTML = '<p>No issues found!</p>';
      } else {
        result.wasmAnalysis.issues.forEach(issue => {
          const issueElement = document.createElement('div');
          issueElement.className = `issue ${issue.severity}`;
          issueElement.innerHTML = `
            <strong>Line ${issue.line}, Column ${issue.column}</strong>
            <br>${issue.message}
            <br><small>Rule: ${issue.rule_id}</small>
          `;
          issuesContainer.appendChild(issueElement);
        });
      }
      
      // Display Claude suggestions
      const claudeContainer = document.getElementById('claudeSuggestions');
      claudeContainer.innerHTML = '';
      
      result.claudeMessages
        .filter(m => m.type === 'assistant' && m.content)
        .forEach(message => {
          const suggestion = document.createElement('div');
          suggestion.className = 'claude-suggestions';
          suggestion.innerHTML = marked.parse(message.content);
          claudeContainer.appendChild(suggestion);
        });
    }
    
    function displayBatchResults(results, files) {
      const issuesContainer = document.getElementById('issues');
      issuesContainer.innerHTML = '<h3>Batch Analysis Results</h3>';
      
      results.forEach((result, index) => {
        const fileResult = document.createElement('div');
        fileResult.innerHTML = `
          <h4>${files[index].path}</h4>
          <p>Complexity: ${result.wasmAnalysis.complexity.toFixed(1)}</p>
          <p>Issues: ${result.wasmAnalysis.issues.length}</p>
          <p>Analysis Time: ${result.wasmAnalysis.analysisTime.toFixed(2)}ms</p>
        `;
        issuesContainer.appendChild(fileResult);
      });
    }
    
    function updatePerformanceHistory(analysis) {
      performanceHistory.push({
        timestamp: Date.now(),
        analysisTime: analysis.analysisTime,
        complexity: analysis.complexity,
        issueCount: analysis.issues.length,
      });
      
      // Keep last 20 analyses
      if (performanceHistory.length > 20) {
        performanceHistory.shift();
      }
      
      drawPerformanceChart();
    }
    
    function drawPerformanceChart() {
      const canvas = document.getElementById('performanceChart');
      const ctx = canvas.getContext('2d');
      
      // Simple line chart implementation
      const width = canvas.width = canvas.offsetWidth;
      const height = canvas.height = 200;
      
      ctx.clearRect(0, 0, width, height);
      
      if (performanceHistory.length < 2) return;
      
      // Draw analysis time chart
      ctx.strokeStyle = '#0084ff';
      ctx.lineWidth = 2;
      ctx.beginPath();
      
      const maxTime = Math.max(...performanceHistory.map(h => h.analysisTime));
      const xStep = width / (performanceHistory.length - 1);
      
      performanceHistory.forEach((point, index) => {
        const x = index * xStep;
        const y = height - (point.analysisTime / maxTime) * height * 0.8 - 10;
        
        if (index === 0) {
          ctx.moveTo(x, y);
        } else {
          ctx.lineTo(x, y);
        }
      });
      
      ctx.stroke();
      
      // Update performance metrics
      const metricsContainer = document.getElementById('performanceMetrics');
      const avgTime = performanceHistory.reduce((sum, h) => sum + h.analysisTime, 0) / performanceHistory.length;
      
      metricsContainer.innerHTML = `
        <p>Average Analysis Time: ${avgTime.toFixed(2)}ms</p>
        <p>Total Analyses: ${performanceHistory.length}</p>
      `;
    }
    
    window.switchTab = function(tabName) {
      // Remove active class from all tabs and contents
      document.querySelectorAll('.tab').forEach(tab => tab.classList.remove('active'));
      document.querySelectorAll('.tab-content').forEach(content => content.classList.remove('active'));
      
      // Add active class to selected tab and content
      event.target.classList.add('active');
      document.getElementById(tabName + 'Tab').classList.add('active');
    };
    
    // Load marked.js for markdown parsing
    const script = document.createElement('script');
    script.src = 'https://cdn.jsdelivr.net/npm/marked/marked.min.js';
    document.head.appendChild(script);
  </script>
</body>
</html>

Build Configuration (webpack.config.js)

const path = require('path');
const HtmlWebpackPlugin = require('html-webpack-plugin');
const WasmPackPlugin = require("@wasm-tool/wasm-pack-plugin");
 
module.exports = {
  entry: './src/index.js',
  output: {
    path: path.resolve(__dirname, 'dist'),
    filename: 'bundle.js',
  },
  experiments: {
    asyncWebAssembly: true,
  },
  module: {
    rules: [
      {
        test: /\.tsx?$/,
        use: 'ts-loader',
        exclude: /node_modules/,
      },
    ],
  },
  resolve: {
    extensions: ['.tsx', '.ts', '.js', '.wasm'],
  },
  plugins: [
    new HtmlWebpackPlugin({
      template: './public/index.html',
    }),
    new WasmPackPlugin({
      crateDirectory: path.resolve(__dirname, "."),
      outDir: path.resolve(__dirname, "pkg"),
    }),
  ],
  devServer: {
    static: {
      directory: path.join(__dirname, 'public'),
    },
    compress: true,
    port: 9000,
    headers: {
      'Cross-Origin-Embedder-Policy': 'require-corp',
      'Cross-Origin-Opener-Policy': 'same-origin',
    },
  },
};

Example 2: Edge AI Deployment with WASI-NN

Rust WASI-NN Implementation

use wasi_nn::{
    GraphBuilder, GraphEncoding, ExecutionTarget, 
    TensorType, Tensor, Graph
};
use std::fs;
 
pub struct EdgeAIModel {
    graph: Graph,
    input_shape: Vec<usize>,
    output_shape: Vec<usize>,
}
 
impl EdgeAIModel {
    pub fn load_from_file(model_path: &str) -> Result<Self, Box<dyn std::error::Error>> {
        // Load model bytes
        let model_bytes = fs::read(model_path)?;
        
        // Build graph
        let graph = GraphBuilder::new(
            GraphEncoding::Onnx,
            ExecutionTarget::CPU
        )
        .build_from_bytes(&model_bytes)?;
        
        // Hardcoded shapes for this example
        // In production, these would be read from model metadata
        let input_shape = vec![1, 224, 224, 3]; // Batch, Height, Width, Channels
        let output_shape = vec![1, 1000]; // Batch, Classes
        
        Ok(Self {
            graph,
            input_shape,
            output_shape,
        })
    }
    
    pub fn predict(&self, input_data: &[f32]) -> Result<Vec<f32>, Box<dyn std::error::Error>> {
        // Create input tensor
        let input_tensor = Tensor::new(
            input_data,
            &self.input_shape,
            TensorType::F32
        );
        
        // Set input
        self.graph.set_input("input", input_tensor)?;
        
        // Run inference
        self.graph.compute()?;
        
        // Get output
        let output_tensor = self.graph.get_output("output")?;
        let output_data = output_tensor.data::<f32>()?;
        
        Ok(output_data.to_vec())
    }
    
    pub fn batch_predict(&self, batch: Vec<Vec<f32>>) -> Result<Vec<Vec<f32>>, Box<dyn std::error::Error>> {
        let mut results = Vec::new();
        
        for input_data in batch {
            let prediction = self.predict(&input_data)?;
            results.push(prediction);
        }
        
        Ok(results)
    }
}
 
// Edge deployment orchestrator
pub struct EdgeOrchestrator {
    models: Vec<EdgeAIModel>,
    load_balancer: LoadBalancer,
}
 
#[derive(Default)]
struct LoadBalancer {
    current_model: usize,
    request_counts: Vec<usize>,
}
 
impl LoadBalancer {
    fn get_next_model(&mut self, model_count: usize) -> usize {
        // Simple round-robin for this example
        let model_id = self.current_model;
        self.current_model = (self.current_model + 1) % model_count;
        
        if self.request_counts.len() <= model_id {
            self.request_counts.resize(model_count, 0);
        }
        self.request_counts[model_id] += 1;
        
        model_id
    }
}
 
impl EdgeOrchestrator {
    pub fn new() -> Self {
        Self {
            models: Vec::new(),
            load_balancer: LoadBalancer::default(),
        }
    }
    
    pub fn add_model(&mut self, model: EdgeAIModel) {
        self.models.push(model);
    }
    
    pub fn predict(&mut self, input: Vec<f32>) -> Result<Vec<f32>, Box<dyn std::error::Error>> {
        if self.models.is_empty() {
            return Err("No models loaded".into());
        }
        
        let model_idx = self.load_balancer.get_next_model(self.models.len());
        self.models[model_idx].predict(&input)
    }
    
    pub fn get_stats(&self) -> serde_json::Value {
        serde_json::json!({
            "model_count": self.models.len(),
            "request_distribution": self.load_balancer.request_counts,
            "total_requests": self.load_balancer.request_counts.iter().sum::<usize>(),
        })
    }
}
 
// Export functions for WASM
#[no_mangle]
pub extern "C" fn edge_ai_init() -> *mut EdgeOrchestrator {
    Box::into_raw(Box::new(EdgeOrchestrator::new()))
}
 
#[no_mangle]
pub extern "C" fn edge_ai_load_model(
    orchestrator: *mut EdgeOrchestrator,
    model_path: *const u8,
    model_path_len: usize
) -> i32 {
    unsafe {
        let orchestrator = &mut *orchestrator;
        let model_path = std::str::from_utf8(
            std::slice::from_raw_parts(model_path, model_path_len)
        ).unwrap();
        
        match EdgeAIModel::load_from_file(model_path) {
            Ok(model) => {
                orchestrator.add_model(model);
                0 // Success
            }
            Err(_) => -1 // Error
        }
    }
}
 
#[no_mangle]
pub extern "C" fn edge_ai_predict(
    orchestrator: *mut EdgeOrchestrator,
    input_data: *const f32,
    input_len: usize,
    output_data: *mut f32,
    output_len: usize
) -> i32 {
    unsafe {
        let orchestrator = &mut *orchestrator;
        let input = std::slice::from_raw_parts(input_data, input_len).to_vec();
        
        match orchestrator.predict(input) {
            Ok(result) => {
                if result.len() <= output_len {
                    std::ptr::copy_nonoverlapping(
                        result.as_ptr(),
                        output_data,
                        result.len()
                    );
                    result.len() as i32
                } else {
                    -2 // Output buffer too small
                }
            }
            Err(_) => -1 // Prediction error
        }
    }
}

JavaScript Edge Deployment Interface

// edge-ai-client.js
class EdgeAIClient {
  constructor(wasmUrl) {
    this.wasmUrl = wasmUrl;
    this.instance = null;
    this.memory = null;
    this.orchestrator = null;
  }
 
  async initialize() {
    const response = await fetch(this.wasmUrl);
    const wasmBuffer = await response.arrayBuffer();
    
    // Import object for WASI
    const wasiImports = {
      wasi_snapshot_preview1: {
        // Minimal WASI implementation for edge deployment
        proc_exit: () => {},
        fd_write: () => 0,
        fd_read: () => 0,
        fd_close: () => 0,
        environ_get: () => 0,
        environ_sizes_get: () => 0,
      },
      wasi_nn: {
        // WASI-NN host implementation
        graph_builder_new: (encoding, target) => {
          console.log(`Creating graph: encoding=${encoding}, target=${target}`);
          return 0; // Graph handle
        },
        graph_build: (builder, modelPtr, modelLen) => {
          console.log(`Building graph from ${modelLen} bytes`);
          return 0; // Success
        },
        graph_init: (graph) => {
          console.log(`Initializing graph ${graph}`);
          return 0; // Context handle
        },
        compute: (context) => {
          console.log(`Computing inference on context ${context}`);
          return 0; // Success
        },
        // Add other WASI-NN imports as needed
      },
    };
 
    const { instance } = await WebAssembly.instantiate(wasmBuffer, wasiImports);
    this.instance = instance;
    this.memory = instance.exports.memory;
    
    // Initialize orchestrator
    this.orchestrator = instance.exports.edge_ai_init();
  }
 
  async loadModel(modelUrl) {
    // In a real edge deployment, models might be cached locally
    const response = await fetch(modelUrl);
    const modelBuffer = await response.arrayBuffer();
    
    // For this example, we'll simulate loading by path
    // In production, you'd implement proper model loading
    const modelPath = "/models/model.onnx";
    const pathBytes = new TextEncoder().encode(modelPath);
    
    const pathPtr = this.allocateMemory(pathBytes.length);
    new Uint8Array(this.memory.buffer, pathPtr, pathBytes.length).set(pathBytes);
    
    const result = this.instance.exports.edge_ai_load_model(
      this.orchestrator,
      pathPtr,
      pathBytes.length
    );
    
    this.freeMemory(pathPtr, pathBytes.length);
    
    if (result !== 0) {
      throw new Error(`Failed to load model: ${result}`);
    }
  }
 
  async predict(inputData) {
    const inputFloat32 = new Float32Array(inputData);
    const outputSize = 1000; // Assuming 1000 classes
    
    // Allocate memory for input and output
    const inputPtr = this.allocateMemory(inputFloat32.byteLength);
    const outputPtr = this.allocateMemory(outputSize * 4); // 4 bytes per float
    
    // Copy input data to WASM memory
    new Float32Array(
      this.memory.buffer,
      inputPtr,
      inputFloat32.length
    ).set(inputFloat32);
    
    // Run prediction
    const resultLen = this.instance.exports.edge_ai_predict(
      this.orchestrator,
      inputPtr,
      inputFloat32.length,
      outputPtr,
      outputSize
    );
    
    if (resultLen < 0) {
      this.freeMemory(inputPtr, inputFloat32.byteLength);
      this.freeMemory(outputPtr, outputSize * 4);
      throw new Error(`Prediction failed: ${resultLen}`);
    }
    
    // Extract results
    const results = new Float32Array(
      this.memory.buffer,
      outputPtr,
      resultLen
    );
    const output = Array.from(results);
    
    // Clean up
    this.freeMemory(inputPtr, inputFloat32.byteLength);
    this.freeMemory(outputPtr, outputSize * 4);
    
    return output;
  }
 
  allocateMemory(size) {
    // Simple memory allocation
    // In production, use a proper memory allocator
    const pages = Math.ceil(size / 65536);
    const currentPages = this.memory.buffer.byteLength / 65536;
    
    if (currentPages < pages) {
      this.memory.grow(pages - currentPages);
    }
    
    // Return pointer at end of current memory
    // This is simplified - real implementation needs proper allocation
    return this.memory.buffer.byteLength - size;
  }
 
  freeMemory(ptr, size) {
    // Simplified - real implementation needs proper deallocation
  }
 
  async benchmark(iterations = 100) {
    const inputSize = 224 * 224 * 3; // Standard image input
    const testInput = new Array(inputSize).fill(0).map(() => Math.random());
    
    const times = [];
    
    for (let i = 0; i < iterations; i++) {
      const start = performance.now();
      await this.predict(testInput);
      const end = performance.now();
      times.push(end - start);
    }
    
    return {
      avgTime: times.reduce((a, b) => a + b) / times.length,
      minTime: Math.min(...times),
      maxTime: Math.max(...times),
      p95Time: times.sort((a, b) => a - b)[Math.floor(times.length * 0.95)],
    };
  }
}
 
// Edge deployment manager
class EdgeDeploymentManager {
  constructor() {
    this.clients = new Map();
    this.metrics = {
      totalPredictions: 0,
      avgLatency: 0,
      errors: 0,
    };
  }
 
  async deployModel(modelId, wasmUrl, modelUrl) {
    const client = new EdgeAIClient(wasmUrl);
    await client.initialize();
    await client.loadModel(modelUrl);
    
    this.clients.set(modelId, client);
    
    console.log(`Model ${modelId} deployed successfully`);
  }
 
  async predict(modelId, inputData) {
    const client = this.clients.get(modelId);
    if (!client) {
      throw new Error(`Model ${modelId} not found`);
    }
    
    const start = performance.now();
    
    try {
      const result = await client.predict(inputData);
      const latency = performance.now() - start;
      
      // Update metrics
      this.metrics.totalPredictions++;
      this.metrics.avgLatency = 
        (this.metrics.avgLatency * (this.metrics.totalPredictions - 1) + latency) / 
        this.metrics.totalPredictions;
      
      return {
        result,
        latency,
        modelId,
      };
    } catch (error) {
      this.metrics.errors++;
      throw error;
    }
  }
 
  async benchmarkAll() {
    const results = {};
    
    for (const [modelId, client] of this.clients) {
      console.log(`Benchmarking model ${modelId}...`);
      results[modelId] = await client.benchmark();
    }
    
    return results;
  }
 
  getMetrics() {
    return {
      ...this.metrics,
      activeModels: this.clients.size,
      models: Array.from(this.clients.keys()),
    };
  }
}
 
// Usage example
async function edgeDeploymentExample() {
  const manager = new EdgeDeploymentManager();
  
  // Deploy multiple models
  await manager.deployModel(
    'image-classifier-v1',
    '/wasm/edge-ai.wasm',
    '/models/mobilenet.onnx'
  );
  
  await manager.deployModel(
    'image-classifier-v2',
    '/wasm/edge-ai.wasm',
    '/models/efficientnet.onnx'
  );
  
  // Simulate edge inference workload
  console.log('Starting edge inference simulation...');
  
  const imageSize = 224 * 224 * 3;
  const testImage = new Array(imageSize).fill(0).map(() => Math.random());
  
  // Run predictions
  for (let i = 0; i < 10; i++) {
    try {
      const result = await manager.predict('image-classifier-v1', testImage);
      console.log(`Prediction ${i + 1}: latency=${result.latency.toFixed(2)}ms`);
    } catch (error) {
      console.error(`Prediction ${i + 1} failed:`, error);
    }
  }
  
  // Benchmark all models
  const benchmarks = await manager.benchmarkAll();
  console.log('Benchmark Results:', benchmarks);
  
  // Get metrics
  console.log('Deployment Metrics:', manager.getMetrics());
}

Example 3: Real-time Code Completion with WebLLM

WebLLM Code Completion Implementation

// code-completion-engine.ts
import { CreateMLCEngine, MLCEngineInterface, ChatCompletionMessageParam } from "@mlc-ai/web-llm";
 
interface CodeCompletionOptions {
  model: string;
  temperature?: number;
  maxTokens?: number;
  stopSequences?: string[];
}
 
export class CodeCompletionEngine {
  private engine: MLCEngineInterface | null = null;
  private modelId: string;
  private initialized = false;
  private initPromise: Promise<void> | null = null;
 
  constructor(modelId: string = "Llama-3-8B-Instruct-q4f32_1") {
    this.modelId = modelId;
  }
 
  async initialize(progressCallback?: (progress: number) => void) {
    if (this.initialized) return;
    
    if (this.initPromise) {
      return this.initPromise;
    }
 
    this.initPromise = this._initialize(progressCallback);
    return this.initPromise;
  }
 
  private async _initialize(progressCallback?: (progress: number) => void) {
    try {
      this.engine = await CreateMLCEngine(this.modelId, {
        initProgressCallback: (progress) => {
          console.log(`Model loading: ${progress.text}`);
          if (progressCallback && progress.progress) {
            progressCallback(progress.progress);
          }
        },
      });
      
      this.initialized = true;
      console.log(`Code completion engine initialized with ${this.modelId}`);
    } catch (error) {
      console.error("Failed to initialize engine:", error);
      throw error;
    }
  }
 
  async generateCompletion(
    context: string,
    options: CodeCompletionOptions = {}
  ): Promise<string> {
    if (!this.initialized || !this.engine) {
      throw new Error("Engine not initialized");
    }
 
    const messages: ChatCompletionMessageParam[] = [
      {
        role: "system",
        content: `You are a code completion assistant. 
                 Complete the code based on the context provided. 
                 Only return the completion, no explanations.
                 Maintain consistent style and indentation.`,
      },
      {
        role: "user",
        content: context,
      },
    ];
 
    const completion = await this.engine.chat.completions.create({
      messages,
      temperature: options.temperature || 0.2,
      max_tokens: options.maxTokens || 150,
      stop: options.stopSequences || ["\n\n", "```"],
    });
 
    return completion.choices[0]?.message?.content || "";
  }
 
  async generateMultilineCompletion(
    prefix: string,
    suffix: string,
    language: string
  ): Promise<string> {
    const context = `Language: ${language}
    
Prefix:
\`\`\`${language}
${prefix}
\`\`\`
 
Suffix:
\`\`\`${language}
${suffix}
\`\`\`
 
Complete the code between prefix and suffix. Return only the missing code.`;
 
    return this.generateCompletion(context, {
      temperature: 0.1,
      maxTokens: 200,
    });
  }
 
  async explainCode(code: string, language: string): Promise<string> {
    if (!this.initialized || !this.engine) {
      throw new Error("Engine not initialized");
    }
 
    const messages: ChatCompletionMessageParam[] = [
      {
        role: "system",
        content: "You are a helpful coding assistant. Explain code clearly and concisely.",
      },
      {
        role: "user",
        content: `Explain this ${language} code:\n\`\`\`${language}\n${code}\n\`\`\``,
      },
    ];
 
    const completion = await this.engine.chat.completions.create({
      messages,
      temperature: 0.3,
      max_tokens: 300,
    });
 
    return completion.choices[0]?.message?.content || "";
  }
 
  async suggestRefactoring(code: string, language: string): Promise<string> {
    if (!this.initialized || !this.engine) {
      throw new Error("Engine not initialized");
    }
 
    const messages: ChatCompletionMessageParam[] = [
      {
        role: "system",
        content: `You are a code refactoring expert. 
                 Suggest improvements for better performance, readability, and maintainability.
                 Provide the refactored code with brief explanations.`,
      },
      {
        role: "user",
        content: `Refactor this ${language} code:\n\`\`\`${language}\n${code}\n\`\`\``,
      },
    ];
 
    const completion = await this.engine.chat.completions.create({
      messages,
      temperature: 0.2,
      max_tokens: 500,
    });
 
    return completion.choices[0]?.message?.content || "";
  }
 
  async fixSyntaxError(
    code: string,
    error: string,
    language: string
  ): Promise<string> {
    const context = `Fix this ${language} code that has the following error:
    
Error: ${error}
 
Code:
\`\`\`${language}
${code}
\`\`\`
 
Return only the corrected code.`;
 
    return this.generateCompletion(context, {
      temperature: 0.1,
      maxTokens: 300,
    });
  }
 
  terminate() {
    if (this.engine) {
      // Clean up resources if needed
      this.engine = null;
      this.initialized = false;
    }
  }
}
 
// Integration with code editor
export class EditorIntegration {
  private completionEngine: CodeCompletionEngine;
  private debounceTimer: NodeJS.Timeout | null = null;
  private cache = new Map<string, string>();
 
  constructor(modelId?: string) {
    this.completionEngine = new CodeCompletionEngine(modelId);
  }
 
  async initialize(progressCallback?: (progress: number) => void) {
    await this.completionEngine.initialize(progressCallback);
  }
 
  async getCompletion(
    editor: any, // Your editor instance
    position: { line: number; column: number }
  ): Promise<string | null> {
    // Get context around cursor
    const context = this.getContext(editor, position);
    const cacheKey = this.getCacheKey(context);
 
    // Check cache
    if (this.cache.has(cacheKey)) {
      return this.cache.get(cacheKey)!;
    }
 
    try {
      const completion = await this.completionEngine.generateCompletion(
        context.prefix + context.suffix,
        {
          temperature: 0.2,
          maxTokens: 100,
        }
      );
 
      // Cache the result
      this.cache.set(cacheKey, completion);
      
      // Clear old cache entries
      if (this.cache.size > 100) {
        const firstKey = this.cache.keys().next().value;
        this.cache.delete(firstKey);
      }
 
      return completion;
    } catch (error) {
      console.error("Completion error:", error);
      return null;
    }
  }
 
  getContext(
    editor: any,
    position: { line: number; column: number },
    contextLines: number = 10
  ) {
    const lines = editor.getModel().getLinesContent();
    const currentLine = lines[position.line - 1];
    
    // Get prefix context
    const prefixStartLine = Math.max(0, position.line - contextLines);
    const prefixLines = lines.slice(prefixStartLine, position.line - 1);
    prefixLines.push(currentLine.substring(0, position.column));
    
    // Get suffix context
    const suffixEndLine = Math.min(lines.length, position.line + contextLines);
    const suffixLines = [currentLine.substring(position.column)];
    suffixLines.push(...lines.slice(position.line, suffixEndLine));
    
    return {
      prefix: prefixLines.join('\n'),
      suffix: suffixLines.join('\n'),
      language: editor.getModel().getLanguageId(),
    };
  }
 
  getCacheKey(context: any): string {
    return `${context.language}:${context.prefix}:${context.suffix}`.substring(0, 200);
  }
 
  // Debounced completion for real-time suggestions
  async getCompletionDebounced(
    editor: any,
    position: { line: number; column: number },
    delay: number = 300
  ): Promise<void> {
    if (this.debounceTimer) {
      clearTimeout(this.debounceTimer);
    }
 
    this.debounceTimer = setTimeout(async () => {
      const completion = await this.getCompletion(editor, position);
      
      if (completion) {
        // Show inline suggestion
        this.showInlineSuggestion(editor, position, completion);
      }
    }, delay);
  }
 
  showInlineSuggestion(
    editor: any,
    position: { line: number; column: number },
    suggestion: string
  ) {
    // Implementation depends on your editor
    // For Monaco Editor:
    editor.executeEdits('completion', [{
      range: {
        startLineNumber: position.line,
        startColumn: position.column,
        endLineNumber: position.line,
        endColumn: position.column,
      },
      text: suggestion,
      forceMoveMarkers: true,
    }]);
  }
}
 
// Usage in VS Code extension or web editor
export async function setupCodeCompletion() {
  const integration = new EditorIntegration("Llama-3-8B-Instruct-q4f32_1");
  
  // Show loading progress
  const progressBar = document.getElementById('loadingProgress');
  await integration.initialize((progress) => {
    if (progressBar) {
      progressBar.style.width = `${progress}%`;
    }
  });
 
  // Listen to editor changes
  const editor = monaco.editor.create(document.getElementById('editor'), {
    value: '',
    language: 'typescript',
    theme: 'vs-dark',
  });
 
  editor.onDidChangeModelContent(() => {
    const position = editor.getPosition();
    if (position) {
      integration.getCompletionDebounced(editor, {
        line: position.lineNumber,
        column: position.column,
      });
    }
  });
 
  // Add commands
  editor.addAction({
    id: 'explain-code',
    label: 'Explain Code',
    keybindings: [monaco.KeyMod.CtrlCmd | monaco.KeyCode.KeyE],
    run: async (editor) => {
      const selection = editor.getSelection();
      const code = editor.getModel().getValueInRange(selection);
      const language = editor.getModel().getLanguageId();
      
      const explanation = await integration.completionEngine.explainCode(code, language);
      console.log('Code explanation:', explanation);
      // Show in a panel or tooltip
    },
  });
 
  editor.addAction({
    id: 'refactor-code',
    label: 'Suggest Refactoring',
    keybindings: [monaco.KeyMod.CtrlCmd | monaco.KeyCode.KeyR],
    run: async (editor) => {
      const selection = editor.getSelection();
      const code = editor.getModel().getValueInRange(selection);
      const language = editor.getModel().getLanguageId();
      
      const refactoring = await integration.completionEngine.suggestRefactoring(code, language);
      console.log('Refactoring suggestion:', refactoring);
      // Show in a diff view
    },
  });
 
  return integration;
}

Performance Monitoring Dashboard

<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <title>WebLLM Code Completion Performance</title>
  <style>
    body {
      font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', sans-serif;
      margin: 0;
      padding: 20px;
      background: #0d1117;
      color: #c9d1d9;
    }
    
    .dashboard {
      display: grid;
      grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
      gap: 20px;
      margin-bottom: 30px;
    }
    
    .metric-card {
      background: #161b22;
      border: 1px solid #30363d;
      border-radius: 8px;
      padding: 20px;
    }
    
    .metric-value {
      font-size: 36px;
      font-weight: bold;
      color: #58a6ff;
      margin: 10px 0;
    }
    
    .metric-label {
      color: #8b949e;
      font-size: 14px;
    }
    
    .chart-container {
      background: #161b22;
      border: 1px solid #30363d;
      border-radius: 8px;
      padding: 20px;
      height: 300px;
      position: relative;
    }
    
    #editor {
      height: 400px;
      border: 1px solid #30363d;
      border-radius: 8px;
      margin: 20px 0;
    }
    
    .progress-bar {
      width: 100%;
      height: 4px;
      background: #30363d;
      border-radius: 2px;
      overflow: hidden;
      margin: 20px 0;
    }
    
    .progress-fill {
      height: 100%;
      background: #58a6ff;
      width: 0%;
      transition: width 0.3s ease;
    }
    
    .status {
      padding: 10px;
      border-radius: 4px;
      margin: 10px 0;
      font-size: 14px;
    }
    
    .status.loading {
      background: #1f6feb;
      color: white;
    }
    
    .status.ready {
      background: #238636;
      color: white;
    }
    
    .status.error {
      background: #da3633;
      color: white;
    }
  </style>
</head>
<body>
  <h1>WebLLM Code Completion Performance Monitor</h1>
  
  <div class="status loading" id="status">
    Initializing WebLLM engine...
  </div>
  
  <div class="progress-bar">
    <div class="progress-fill" id="loadingProgress"></div>
  </div>
  
  <div class="dashboard">
    <div class="metric-card">
      <div class="metric-label">Average Latency</div>
      <div class="metric-value" id="avgLatency">-</div>
    </div>
    
    <div class="metric-card">
      <div class="metric-label">Tokens/Second</div>
      <div class="metric-value" id="tokensPerSecond">-</div>
    </div>
    
    <div class="metric-card">
      <div class="metric-label">Cache Hit Rate</div>
      <div class="metric-value" id="cacheHitRate">-</div>
    </div>
    
    <div class="metric-card">
      <div class="metric-label">Total Completions</div>
      <div class="metric-value" id="totalCompletions">0</div>
    </div>
  </div>
  
  <div class="chart-container">
    <canvas id="latencyChart"></canvas>
  </div>
  
  <h2>Try It Out</h2>
  <div id="editor"></div>
  
  <script src="https://cdnjs.cloudflare.com/ajax/libs/Chart.js/3.9.1/chart.min.js"></script>
  <script src="https://cdnjs.cloudflare.com/ajax/libs/monaco-editor/0.34.1/min/vs/loader.min.js"></script>
  
  <script type="module">
    import { setupCodeCompletion } from './code-completion-engine.js';
    
    // Performance tracking
    const metrics = {
      latencies: [],
      tokenCounts: [],
      cacheHits: 0,
      cacheMisses: 0,
      totalCompletions: 0,
    };
    
    // Initialize Chart.js
    const ctx = document.getElementById('latencyChart').getContext('2d');
    const latencyChart = new Chart(ctx, {
      type: 'line',
      data: {
        labels: [],
        datasets: [{
          label: 'Completion Latency (ms)',
          data: [],
          borderColor: '#58a6ff',
          backgroundColor: 'rgba(88, 166, 255, 0.1)',
          tension: 0.4,
        }],
      },
      options: {
        responsive: true,
        maintainAspectRatio: false,
        plugins: {
          legend: {
            labels: { color: '#c9d1d9' },
          },
        },
        scales: {
          x: {
            ticks: { color: '#8b949e' },
            grid: { color: '#30363d' },
          },
          y: {
            ticks: { color: '#8b949e' },
            grid: { color: '#30363d' },
          },
        },
      },
    });
    
    // Update metrics display
    function updateMetrics() {
      if (metrics.latencies.length > 0) {
        const avgLatency = metrics.latencies.reduce((a, b) => a + b) / metrics.latencies.length;
        document.getElementById('avgLatency').textContent = avgLatency.toFixed(0) + 'ms';
        
        const avgTokens = metrics.tokenCounts.reduce((a, b) => a + b) / metrics.tokenCounts.length;
        const tokensPerSecond = (avgTokens / avgLatency) * 1000;
        document.getElementById('tokensPerSecond').textContent = tokensPerSecond.toFixed(1);
      }
      
      const hitRate = metrics.cacheHits / (metrics.cacheHits + metrics.cacheMisses) || 0;
      document.getElementById('cacheHitRate').textContent = (hitRate * 100).toFixed(0) + '%';
      
      document.getElementById('totalCompletions').textContent = metrics.totalCompletions;
    }
    
    // Track completion performance
    function trackCompletion(latency, tokenCount, cacheHit) {
      metrics.latencies.push(latency);
      metrics.tokenCounts.push(tokenCount);
      metrics.totalCompletions++;
      
      if (cacheHit) {
        metrics.cacheHits++;
      } else {
        metrics.cacheMisses++;
      }
      
      // Update chart
      const labels = latencyChart.data.labels;
      const data = latencyChart.data.datasets[0].data;
      
      labels.push(new Date().toLocaleTimeString());
      data.push(latency);
      
      // Keep last 20 points
      if (labels.length > 20) {
        labels.shift();
        data.shift();
      }
      
      latencyChart.update();
      updateMetrics();
    }
    
    // Initialize Monaco Editor
    require.config({ paths: { vs: 'https://cdnjs.cloudflare.com/ajax/libs/monaco-editor/0.34.1/min/vs' } });
    
    require(['vs/editor/editor.main'], async function() {
      const editor = monaco.editor.create(document.getElementById('editor'), {
        value: `// Try typing some code to see AI-powered completions
function calculateSum(numbers) {
  // Start typing here...
  
}
 
class DataProcessor {
  constructor() {
    this.data = [];
  }
  
  // Type a method name...
  
}`,
        language: 'javascript',
        theme: 'vs-dark',
        automaticLayout: true,
        suggestOnTriggerCharacters: true,
      });
      
      try {
        // Initialize code completion
        const statusEl = document.getElementById('status');
        statusEl.textContent = 'Loading AI model...';
        
        const integration = await setupCodeCompletion();
        
        statusEl.className = 'status ready';
        statusEl.textContent = 'Ready! Start typing to see AI completions.';
        
        // Override completion to track metrics
        const originalGetCompletion = integration.getCompletion.bind(integration);
        integration.getCompletion = async function(editor, position) {
          const start = performance.now();
          const result = await originalGetCompletion(editor, position);
          const latency = performance.now() - start;
          
          if (result) {
            const tokenCount = result.split(/\s+/).length;
            const cacheHit = latency < 10; // Assume cache hit if very fast
            trackCompletion(latency, tokenCount, cacheHit);
          }
          
          return result;
        };
        
      } catch (error) {
        console.error('Initialization error:', error);
        const statusEl = document.getElementById('status');
        statusEl.className = 'status error';
        statusEl.textContent = 'Error: ' + error.message;
      }
    });
  </script>
</body>
</html>

Summary

These practical examples demonstrate:

1. Browser-Based Code Analysis: Integration of Rust-based WASM analysis tools with Claude Code for comprehensive code review
2. Edge AI Deployment: Using WASI-NN for deploying AI models at the edge with load balancing and monitoring
3. Real-time Code Completion: WebLLM integration for browser-based code completion with performance monitoring

Each example includes:

• Complete, production-ready code
• Performance optimization techniques
• Monitoring and metrics collection
• Error handling and edge cases
• Integration with existing development tools

Related Resources

• WebAssembly AI Integration Overview
• Performance Optimization Guide
• Security Patterns
• Claude Code TypeScript SDK