src/recommendation/README.md

Recommendation Module 🎯

Responsibility

This module handles suggesting new educational videos based on user interests.

Functionality

1. Analyze user's saved notes.
2. Extract topics and categories.
3. Search YouTube for related videos.
4. Return a list of suggested educational videos.

Files

1. recommender.py

• Purpose: Suggest educational videos from YouTube.
• Main Class: RecommendationService
• Key Methods:
  • get_recommendations_for_user(user_id) - Get general recommendations for user.
  • get_youtube_recommendations(query) - Search YouTube based on keywords.
  • get_similar_notes(note_id) - Get similar notes from the same category.

How It Works

1. Fetch Notes: Read the user's last 5 saved notes.
2. Extract Topics: Use categories or titles.
3. Enhance Search: Add keywords like "educational", "tutorial", "lecture".
4. Filter Results: Select only embeddable videos.

Proposed Enhancements

• Add caching for recommendations to reduce YouTube API calls.
• Use Machine Learning to improve recommendation accuracy.
• Add filter for video duration (avoid very long videos).
• Prioritize well-known educational channels.

Testing

from src.ai_modules.recommendation.recommender import RecommendationService
from src.db.database import get_session

recommender = RecommendationService()

# Get recommendations for user
async def test_recommendations():
    async with get_session() as session:
        recs = await recommender.get_recommendations_for_user(session, user_id=1)
        for video in recs:
            print(f"{video['title']} - {video['url']}")

Libraries Used

• google-api-python-client - Search YouTube.
• groq - Extract topics via LLM.

Important Notes

• YouTube API has a daily quota limit, use caching to reduce requests.
• Enhanced search adds "educational lecture tutorial" keywords for better educational results.
• System prioritizes videos from the same category.

API Quota Management

It's recommended to cache results temporarily to avoid exhausting YouTube API quota:

# Simple cache example
cache = {}

def get_cached_recommendations(query):
    if query in cache:
        return cache[query]
    
    results = youtube_search(query)
    cache[query] = results
    return results