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---
allowed-tools: Read, Write, Edit, MultiEdit, Bash
description: Set up advanced AI SDK features including reasoning models, computer use, and cutting-edge capabilities
argument-hint: "[reasoning|computer-use|generative-ui|edge-optimization|experimental]"
---
## Set up Advanced AI SDK Features
Configure cutting-edge AI SDK capabilities for: $ARGUMENTS
### Current Advanced Features Analysis
Existing advanced implementations: !`grep -r "experimental\|reasoning\|computer\|streamUI" . --include="*.ts" --include="*.tsx" | head -5`
Provider-specific features: !`grep -r "o1-preview\|deepseek\|computer_20241022\|responses" . --include="*.ts" | head -5`
Experimental configurations: !`grep -r "experimental_" . --include="*.ts" | head -5`
### Advanced Feature Categories
**Reasoning Models**: O1-Preview, O3-mini, DeepSeek R1 with thinking capabilities
**Computer Use**: Claude 3.5 Sonnet screen interaction and automation
**Generative UI**: Dynamic component streaming with streamUI
**Edge Optimization**: Vercel Edge Runtime performance enhancements
**Experimental**: Cutting-edge AI SDK experimental features
### Your Task
1. **Analyze project requirements** for advanced AI capabilities
2. **Configure reasoning models** with thinking mode and extended context
3. **Set up computer use tools** for automation and testing
4. **Implement generative UI** with dynamic component generation
5. **Optimize for edge deployment** with performance enhancements
6. **Enable experimental features** safely with proper fallbacks
7. **Add comprehensive monitoring** for advanced feature usage
8. **Create testing strategies** for cutting-edge capabilities
### Implementation Requirements
#### Reasoning Models Integration
- O1-Preview and O3-mini setup with thinking tokens
- DeepSeek R1 configuration for enhanced reasoning
- Thinking mode visibility and streaming
- Extended context window management
- Reasoning-specific prompt engineering
#### Computer Use Capabilities
- Claude 3.5 Sonnet computer use tool setup
- Screen interaction and automation
- Browser automation and testing
- File system operations
- Cross-platform compatibility
#### Generative UI Features
- streamUI implementation for dynamic components
- Real-time component generation
- Interactive widget creation
- Chart and visualization streaming
- Form and dashboard generation
### Expected Deliverables
1. **Advanced provider configurations** with reasoning and computer use
2. **Generative UI implementation** with component streaming
3. **Edge runtime optimizations** for global deployment
4. **Experimental features setup** with safety controls
5. **Performance monitoring** for advanced capabilities
6. **Testing suite** covering all advanced features
7. **Documentation** with examples and best practices
### Advanced Provider Setup
#### Reasoning Models Configuration
```typescript
// lib/reasoning-providers.ts
import { openai } from '@ai-sdk/openai';
import { createOpenAI } from '@ai-sdk/openai';
// OpenAI O1 Models
export const o1Preview = openai('o1-preview', {
// Reasoning-specific configuration
experimental_reasoning: true,
experimental_thinkingMode: 'visible',
maxCompletionTokens: 32768,
temperature: 1.0, // Fixed for reasoning models
});
export const o3Mini = openai('o3-mini', {
experimental_reasoning: true,
experimental_thinkingTokens: true,
experimental_thinkingMode: 'visible',
maxCompletionTokens: 65536,
});
// DeepSeek R1
export const deepseekR1 = createOpenAI({
apiKey: process.env.DEEPSEEK_API_KEY,
baseURL: 'https://api.deepseek.com/v1',
})('deepseek-reasoner', {
experimental_reasoning: true,
experimental_thinkingTokens: true,
maxTokens: 8192,
});
// Reasoning model selector
export function selectReasoningModel(complexity: 'simple' | 'complex' | 'mathematical') {
switch (complexity) {
case 'mathematical':
return o1Preview; // Best for math and logic
case 'complex':
return o3Mini; // Good for complex reasoning
case 'simple':
return deepseekR1; // Fast for simple reasoning
default:
return o1Preview;
}
}
```
#### Computer Use Implementation
```typescript
// lib/computer-use.ts
import { anthropic } from '@ai-sdk/anthropic';
import { tool } from 'ai';
import { z } from 'zod';
export const computerUseTool = anthropic.tools.computer_20241022({
displayWidthPx: 1920,
displayHeightPx: 1080,
execute: async ({ action, coordinate, text }) => {
// Implement safe computer interactions
return await executeComputerAction(action, coordinate, text);
},
});
export const browserAutomationTool = tool({
description: 'Automate browser interactions for testing and data collection',
inputSchema: z.object({
url: z.string().url(),
actions: z.array(z.object({
type: z.enum(['navigate', 'click', 'type', 'wait', 'screenshot']),
selector: z.string().optional(),
text: z.string().optional(),
})),
}),
execute: async ({ url, actions }) => {
const results = [];
for (const action of actions) {
const result = await executeBrowserAction(action, url);
results.push(result);
if (!result.success) break; // Stop on error
}
return { success: true, results };
},
});
// Safe computer action execution with permissions
async function executeComputerAction(action: string, coordinate?: [number, number], text?: string) {
// Security checks
const allowedActions = ['screenshot', 'click', 'type', 'scroll'];
if (!allowedActions.includes(action)) {
throw new Error(`Action not allowed: ${action}`);
}
// Rate limiting
await checkRateLimit(`computer_${action}`);
// Execute action based on platform
switch (action) {
case 'screenshot':
return await takeScreenshot();
case 'click':
if (!coordinate) throw new Error('Click requires coordinates');
return await performClick(coordinate);
case 'type':
if (!text) throw new Error('Type requires text');
return await typeText(text);
case 'scroll':
return await performScroll(text || 'down');
default:
throw new Error(`Unsupported action: ${action}`);
}
}
```
#### Generative UI Setup
```typescript
// app/api/ui/route.ts
import { streamUI } from 'ai/rsc';
import { anthropic } from '@ai-sdk/anthropic';
import { z } from 'zod';
export async function POST(req: Request) {
const { messages } = await req.json();
const result = streamUI({
model: anthropic('claude-3-sonnet-20240229'),
messages,
text: ({ content }) => <div>{content}</div>,
tools: {
createChart: {
description: 'Generate interactive charts and visualizations',
inputSchema: z.object({
type: z.enum(['bar', 'line', 'pie', 'scatter', 'heatmap']),
data: z.array(z.record(z.any())),
title: z.string(),
options: z.record(z.any()).optional(),
}),
generate: async ({ type, data, title, options }) => {
const { default: Chart } = await import('@/components/dynamic-chart');
return <Chart type={type} data={data} title={title} options={options} />;
},
},
createForm: {
description: 'Generate dynamic forms with validation',
inputSchema: z.object({
fields: z.array(z.object({
name: z.string(),
type: z.enum(['text', 'email', 'number', 'select', 'textarea']),
required: z.boolean(),
options: z.array(z.string()).optional(),
})),
title: z.string(),
onSubmit: z.string().optional(), // Callback name
}),
generate: async ({ fields, title, onSubmit }) => {
const { default: DynamicForm } = await import('@/components/dynamic-form');
return <DynamicForm fields={fields} title={title} onSubmit={onSubmit} />;
},
},
createDashboard: {
description: 'Build interactive dashboards with multiple widgets',
inputSchema: z.object({
layout: z.enum(['grid', 'flex', 'sidebar']),
widgets: z.array(z.object({
type: z.enum(['metric', 'chart', 'table', 'list']),
title: z.string(),
data: z.any(),
size: z.enum(['small', 'medium', 'large']).optional(),
})),
}),
generate: async ({ layout, widgets }) => {
const { default: Dashboard } = await import('@/components/dynamic-dashboard');
return <Dashboard layout={layout} widgets={widgets} />;
},
},
},
});
return result.toDataStreamResponse();
}
```
### Edge Optimization Configuration
```typescript
// next.config.js - Advanced edge configuration
/** @type {import('next').NextConfig} */
const nextConfig = {
experimental: {
runtime: 'edge',
serverComponentsExternalPackages: [
'@ai-sdk/anthropic',
'@ai-sdk/openai',
'@ai-sdk/google',
],
// Advanced streaming
streaming: {
compression: true,
keepAlive: true,
timeout: 300000, // 5 minutes
},
// Edge-specific features
edgeRuntime: {
unsafeEval: false, // Security
allowMiddlewareResponseBody: true,
},
},
webpack: (config, { nextRuntime, isServer }) => {
if (nextRuntime === 'edge') {
// Edge runtime optimizations
config.resolve.fallback = {
...config.resolve.fallback,
fs: false,
net: false,
tls: false,
crypto: false,
};
// Reduce bundle size for edge
config.externals = [
...(config.externals || []),
'sharp', // Image processing
'canvas', // Canvas operations
];
}
return config;
},
// Advanced headers for performance
headers: async () => [
{
source: '/api/:path*',
headers: [
{
key: 'Cache-Control',
value: 'public, max-age=0, s-maxage=3600, stale-while-revalidate=86400',
},
{
key: 'X-Content-Type-Options',
value: 'nosniff',
},
{
key: 'X-Frame-Options',
value: 'DENY',
},
{
key: 'X-XSS-Protection',
value: '1; mode=block',
},
],
},
],
};
module.exports = nextConfig;
```
### Experimental Features Configuration
```typescript
// lib/experimental-features.ts
import { streamText, generateObject, streamUI } from 'ai';
export const experimentalConfig = {
// Multi-modal streaming
multimodalStreaming: true,
// Advanced tool calling
toolCallStreaming: true,
continueSteps: true,
// Reasoning capabilities
reasoning: true,
thinkingMode: 'visible',
thinkingTokens: true,
// Performance optimizations
streamingTimeouts: {
streamingTimeout: 30000,
completeTimeout: 120000,
keepAliveInterval: 5000,
},
// Memory management
memoryManagement: {
maxTokensInMemory: 50000,
enableGarbageCollection: true,
cleanupInterval: 60000,
},
// Connection optimization
connectionOptimization: {
enableCompression: true,
enableKeepAlive: true,
connectionPooling: true,
},
};
// Experimental feature wrapper
export function withExperimentalFeatures<T extends Function>(fn: T): T {
return (async (...args: any[]) => {
try {
// Enable experimental features for this call
const result = await fn(...args);
// Track experimental feature usage
await trackExperimentalUsage(fn.name, true);
return result;
} catch (error) {
// Fallback to stable version on experimental failure
console.warn(`Experimental feature ${fn.name} failed, falling back:`, error);
await trackExperimentalUsage(fn.name, false);
// Implement fallback logic here
throw error; // or return fallback result
}
}) as T;
}
// Feature flag system
export class FeatureFlags {
private static flags = new Map<string, boolean>();
static async initialize() {
// Load feature flags from environment or external service
this.flags.set('reasoning_models', process.env.ENABLE_REASONING === 'true');
this.flags.set('computer_use', process.env.ENABLE_COMPUTER_USE === 'true');
this.flags.set('generative_ui', process.env.ENABLE_GENERATIVE_UI === 'true');
this.flags.set('edge_optimization', process.env.ENABLE_EDGE_OPT === 'true');
}
static isEnabled(feature: string): boolean {
return this.flags.get(feature) ?? false;
}
static enable(feature: string) {
this.flags.set(feature, true);
}
static disable(feature: string) {
this.flags.set(feature, false);
}
}
async function trackExperimentalUsage(feature: string, success: boolean) {
// Track experimental feature usage for monitoring
const usage = {
feature,
success,
timestamp: Date.now(),
environment: process.env.NODE_ENV,
};
// Send to analytics service
console.log('Experimental feature usage:', usage);
}
```
### Advanced Monitoring and Analytics
```typescript
// lib/advanced-monitoring.ts
export class AdvancedMonitoring {
static async recordAdvancedMetric(
feature: string,
metric: string,
value: number,
metadata: Record<string, any> = {}
) {
const record = {
feature,
metric,
value,
metadata,
timestamp: Date.now(),
environment: process.env.NODE_ENV,
region: process.env.VERCEL_REGION || 'unknown',
};
// Send to monitoring service
await this.sendToMonitoring(record);
}
static async recordReasoningMetrics(
model: string,
thinkingTokens: number,
completionTokens: number,
success: boolean
) {
await this.recordAdvancedMetric('reasoning', 'token_usage', thinkingTokens + completionTokens, {
model,
thinking_tokens: thinkingTokens,
completion_tokens: completionTokens,
success,
});
}
static async recordComputerUseMetrics(
action: string,
duration: number,
success: boolean
) {
await this.recordAdvancedMetric('computer_use', 'action_duration', duration, {
action,
success,
});
}
static async recordGenerativeUIMetrics(
componentType: string,
renderTime: number,
complexity: 'low' | 'medium' | 'high'
) {
await this.recordAdvancedMetric('generative_ui', 'render_time', renderTime, {
component_type: componentType,
complexity,
});
}
private static async sendToMonitoring(record: any) {
// Implementation depends on your monitoring service
// Examples: DataDog, New Relic, Custom Analytics
console.log('Advanced Monitoring:', record);
}
}
```
### Testing Advanced Features
```typescript
// tests/advanced-features.test.ts
import { describe, it, expect } from 'vitest';
import { experimentalConfig, FeatureFlags } from '@/lib/experimental-features';
describe('Advanced Features', () => {
beforeAll(async () => {
await FeatureFlags.initialize();
});
it('should handle reasoning models', async () => {
if (!FeatureFlags.isEnabled('reasoning_models')) {
return; // Skip if not enabled
}
const result = await testReasoningModel();
expect(result.success).toBe(true);
expect(result.thinking_tokens).toBeGreaterThan(0);
});
it('should execute computer use safely', async () => {
if (!FeatureFlags.isEnabled('computer_use')) {
return;
}
const result = await testComputerUse();
expect(result.screenshot).toBeDefined();
expect(result.actions).toBeInstanceOf(Array);
});
it('should generate UI components', async () => {
if (!FeatureFlags.isEnabled('generative_ui')) {
return;
}
const component = await testGenerativeUI();
expect(component).toBeDefined();
expect(component.type).toBe('chart');
});
});
```
### Security Considerations
- **Feature flags**: Control advanced features with environment variables
- **Rate limiting**: Implement strict limits for resource-intensive features
- **Permissions**: Computer use requires explicit user permissions
- **Monitoring**: Track all advanced feature usage and errors
- **Fallbacks**: Always have stable alternatives for experimental features
- **Testing**: Comprehensive testing in isolated environments
- **Documentation**: Clear usage guidelines and safety measures
Focus on building cutting-edge AI applications that push the boundaries of what's possible while maintaining security, reliability, and user safety.
|