Tasks for Quest

[SanPranav]

Mini-Quest Backend Tasks: Certifications, Analytics & AI Integration

Team: Encrypters (Backend)
Focus: Data Management, API Integration, Analytics, and Certificate Automation
Linked Modules: Creators (Frontend), Applicators (Data Viz), Curators (Admin)

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Overview

The Backend team is responsible for implementing the data systems, APIs, and logic layers supporting certifications, analytics dashboards, and AI-assisted insights.
This includes endpoints for student progress, certificate generation, analytics summaries, and admin reporting tools.

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Task Breakdown

1. Certifications System

Goal: Allow users to earn and view digital certificates based on completed modules or quests.

Tasks:

• Create certifications database schema (user_id, quest_id, completion_date, certificate_url)
• Build API endpoint: POST /api/certifications to generate a certificate
• Integrate with PDF generator (e.g., ReportLab or HTML → PDF)
• Implement GET /api/certifications/:user_id to fetch user’s certificates
• Coordinate with Frontend to display certificates in a carousel view
• Export certificates to LinkedIn Certification section (simulate or API link placeholder)

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2. Graphs & Analytics (User Dashboard)

Goal: Provide personal analytics for each user on their activity and progress.

Tasks:

• Design database tables for:

  • activity_log (time spent per module)
  • question_responses (accuracy tracking)
  • module_progress (percentage completion)

• API routes:

  • GET /api/analytics/user/:id → returns summary data
  • GET /api/analytics/user/:id/pdf → generates a PDF executive summary

• Generate charts data for:

  • Time spent
  • Questions answered correctly
  • Overall module progress

• Integrate analytics output with Data Visualization team (Applicators)

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3. AI Gemini Chatbot Integration

Goal: Embed a context-aware AI chatbot to help users summarize results, generate LinkedIn-ready descriptions, and reflect on progress.

Tasks:

• Define context endpoints for user data (to pass into Gemini API)
• Create backend route: POST /api/chat/ai-summary
• Secure API key storage (environment variables)
• Implement safeguards for ethical AI use and verification logging
• Return AI-generated summaries that can be used for LinkedIn “About” or “Skills” sections

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4. Admin Analytics Dashboard (Content Admin)

Goal: Give instructors/curators a unified dashboard for class-level analytics, progress tracking, and feedback aggregation.

Tasks:

• Aggregate data from all users:

  • Average time spent
  • Question accuracy
  • Module completion rate

• GET /api/admin/analytics/overview

• GET /api/admin/progress/all

• GET /api/admin/feedback → pulls from all module comment sections

• Build filters (by class, by module, by user)

• Support export to CSV or PDF

• Collaborate with Curators (Analytics/Admin team) for visualization and UI hooks

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5. System Infrastructure

Tasks:

• Set up Flask or Spring Boot project structure
• Define .env file for database and API keys
• Implement RESTful API design with CORS for Frontend access
• Use SQLite or PostgreSQL (based on hosting)
• Include documentation in README.md for all API routes

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Deliverables

• Functional Flask/Spring Boot backend
• REST API documentation (/docs or Markdown in repo)
• Live deployed API link (via Render, Replit, or GitHub Actions)
• Analytics and Certification integration verified with Frontend team
• Final “Executive Summary PDF” downloadable by user

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Collaboration Notes

• Work closely with Frontend (Creators) to ensure UI integration for certificates and analytics.

• Coordinate with Curators (Admin) for data visualization and progress tracking.

• Follow Agile workflow:

  • Use GitHub Projects for task status.
  • Commit messages with tags: [certs], [analytics], [AI], [admin].