frontend-angular-ai
Skill4 starsChanged 5 months agoMITView on GitHub
AI integration patterns for Angular applications using Genkit, Firebase AI Logic, or Gemini API. Includes streaming responses, tool calling, and RAG patterns. Use when building AI-powered features in Angular apps.
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Angular AI Integration
Patterns for integrating AI capabilities into Angular 21+ applications.
Integration Approaches
| Approach | Where | Best For |
| Genkit | Server-side | Multi-model, complex flows, tool calling |
| Firebase AI Logic | Client-side | Firebase apps, quota management |
| Gemini API | Direct | Maximum flexibility, multimodal |
Quick Decision
Need server-side processing? → Genkit
Using Firebase already? → Firebase AI Logic
Need image/audio analysis? → Gemini API (multimodal)
Building chatbot with history? → Genkit (server-side state)
Simple text completion? → Firebase AI LogicGenkit Overview (Recommended)
Google's open-source toolkit for production AI applications.
// Server: Express + Genkit
import { genkit } from 'genkit';
import { googleAI, gemini20Flash } from '@genkit-ai/googleai';
const ai = genkit({ plugins: [googleAI()] });
app.post('/api/chat', async (req, res) => {
const { message, history } = req.body;
const response = await ai.generate({
model: gemini20Flash,
messages: [...history, { role: 'user', content: message }]
});
res.json({ reply: response.text });
});Key Patterns
Streaming Responses
// Use Resource API for signal-based streaming
streamingResponse = resource({
stream: async () => {
const data = signal<{ value: string }>({ value: '' });
// Stream handling logic
return data;
}
});Tool Calling
// Define tools for LLM to call
const tools = [
{
name: 'searchProducts',
description: 'Search product catalog',
parameters: { query: 'string' }
}
];Temperature Control
| Temperature | Use Case |
| 0.0 - 0.3 | Factual, deterministic |
| 0.4 - 0.7 | Balanced creativity |
| 0.8 - 1.0 | Creative, varied |
Security Patterns
| Pattern | Description |
| API Key Protection | Keys stored server-side only, never exposed to client |
| Output Sanitization | AI responses sanitized before DOM rendering |
| Rate Limiting | Request throttling to prevent quota exhaustion |
| Server Proxy | All LLM API calls routed through backend proxy |
See reference.md for detailed patterns and examples.md for implementations.
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