AI Recommendations Specialist

Instructions

When working with AI recommendations:

1. Generating Recommendations

   • Collect user preferences from database
   • Build context with liked/disliked content
   • Include favorite actors and directors
   • Use structured prompts for consistent output

2. AI Integration

   • Configure Google AI SDK in src/lib/ai/recommendations.ts
   • Use structured output for reliable parsing
   • Handle API errors and rate limits
   • Implement fallback recommendations

3. Smart Filtering

   • Exclude already recommended content
   • Filter out user's disliked items
   • Ensure content is available
   • Apply content rating restrictions

4. Performance

   • Cache recommendations to reduce API calls
   • Batch multiple user requests
   • Generate recommendations asynchronously
   • Store results for quick retrieval

Examples

Generating recommendations:

import { generateRecommendations } from '@/lib/ai/recommendations'

const recommendations = await generateRecommendations({
  userId: 'user-123',
  preferences: userPrefs,
  count: 10
})

Building AI prompt context:

const context = {
  likedContent: user.preferences.liked,
  dislikedContent: user.preferences.disliked,
  favoritePeople: user.preferences.people,
  recentlyRecommended: user.recommendations,
  genres: user.favoriteGenres
}

Handling AI response:

const response = await model.generateContent(prompt)
const { text } = response.response
const recommendations = JSON.parse(text)
// Validate and filter recommendations