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Documentation Index

Fetch the complete documentation index at: https://docs.intelliq.dev/llms.txt

Use this file to discover all available pages before exploring further.

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Overview

The tag analysis system in IntelliQ automatically processes quiz content to generate relevant tags and categories, maintaining user statistics for both user-provided and AI-generated tags. This system works asynchronously using QStash to ensure smooth quiz submission experience.

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Flow Diagram

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Data Structure

The system maintains two levels of tag data:
  1. Quiz Level (in quizzes table):
{
  generatedTags: string[],      // AI-generated tags for this quiz
  generatedCategories: string[] // Broader categories for this quiz
}
  1. User Level (in userAnalysis table):
{
  userTags: { tag: string; count: number }[],           // User-provided tags
  generatedTags: { tag: string; count: number }[],      // AI-generated tags
  generatedCategories: { category: string; count: number }[] // AI-generated categories
}
  1. Quiz Submission When a user completes a quiz (singleplayer or multiplayer), the system: 
    POST /api/v1/quiz-submissions/{type}
    The submission triggers a QStash job for tag analysis.
  2. Tag Analysis (Async) 
    POST /api/v1/admin/tags/analyze
    The analysis job:
    • Generates tags and categories using AI
    • Updates the quiz record
    • Updates user statistics
    • Invalidates relevant caches
  3. Retrieve User Analysis 
    GET /api/v1/user/analysis/tags
    Returns the user’s tag statistics and preferences.
  4. Get Top Categories 
    GET /api/v1/user/analysis/top-categories
    Returns the user’s most frequent quiz categories.

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Response Examples

{
  "success": true,
  "quizId": "557e75e4-d80e-4463-a282-f449190d4d1e",
  "tags": ["physics", "mechanics", "newton-laws"],
  "categories": ["Science", "Physics"]
}

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Technical Implementation

  1. QStash Integration
    • Uses @upstash/qstash for reliable async processing
    • Configurable delay to batch process tags
    • Automatic retries on failure
  2. Cache Management
    • User cache version incremented after analysis
    • Ensures frontend receives updated statistics
  3. Database Schema 
    -- Quiz tags
ALTER TABLE quizzes
ADD COLUMN generated_tags text[],
ADD COLUMN generated_categories text[];

-- User analysis
CREATE TABLE user_analysis (
  id uuid PRIMARY KEY DEFAULT gen_random_uuid(),
  user_id uuid REFERENCES users(id),
  user_tags jsonb[],
  generated_tags jsonb[],
  generated_categories jsonb[],
  created_at timestamptz DEFAULT now(),
  updated_at timestamptz NOT NULL
);

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Error Handling

The system handles various error cases:
  • Failed AI tag generation
  • Database transaction failures
  • Invalid quiz references
  • Rate limiting
  • Cache invalidation issues
Each error is logged and retried through QStash’s built-in retry mechanism.

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Security Considerations

  1. Tag analysis endpoint protected by admin token
  2. User analysis data access restricted to owner
  3. Rate limiting on analysis requests
  4. Sanitization of AI-generated tags
  5. Validation of user-provided tags

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Benefits

  1. Asynchronous Processing
    • No delay in quiz submission
    • Better user experience
    • Reduced server load
  2. Rich Metadata
    • Improved quiz discovery
    • Better content organization
    • Personalized recommendations
  3. User Insights
    • Track user interests
    • Identify popular categories
    • Guide content creation
Written by Ricky Raveanu