Smart Tracker

An intelligent learning and progress tracker with AI-powered suggestions. Track your progress across topics like cybersecurity, programming, and CTF challenges with streak badges and personalized learning recommendations powered by Google Gemini.

Features

• User Authentication - Secure registration and login with password management
• Daily Progress Logging - Log completed tasks and notes for each day
• Topic Management - Create and manage custom topics (Python, Linux, Hacking, CTF, etc.)
• AI-Powered Suggestions - Get personalized next steps and learning suggestions via Google Gemini API
• Streak Tracking - Build and maintain streaks with milestone badges (🌱 Seedling → 🌟 Legend)
• Analytics Dashboard - Visualize your progress with charts and activity summaries
• HackTheBox & Bandit Integration - Track completed rooms and challenges
• Async Job Processing - Non-blocking AI requests with Redis-backed job queue
• Rate Limiting - Distributed rate limiting with Redis for API protection

Technology Stack

• Backend: Flask, Flask-SQLAlchemy, Flask-Login, Flask-Migrate
• Database: PostgreSQL
• Frontend: HTML, CSS, JavaScript
• AI Integration: Google Generative AI (Gemini Flash)
• Caching & Job Queue: Redis
• Rate Limiting: Flask-Limiter
• Deployment: Gunicorn

Prerequisites

• Python 3.7+
• PostgreSQL database
• Redis (optional, for rate limiting and async jobs)
• Google Gemini API key

Installation

1. Clone the repository:

   git clone https://github.com/sunil834/smart-tracker.git
   cd smart-tracker

2. Install dependencies:

   pip install -r requirements.txt

3. Environment Configuration: Create a .env file in the root directory:

   SECRET_KEY=your-super-secret-key
   DATABASE_URL=postgresql://user:password@localhost:5432/smart_tracker
   GEMINI_API_KEY=your-gemini-api-key
   # Optional: enables Redis-backed rate limiting and AI job storage.
   # If omitted, the app falls back to in-memory storage.
   REDIS_URL=redis://localhost:6379/0
   AI_WORKER_THREADS=4

4. Initialize the database:

   flask db upgrade

5. Run the application:

   python app.py

   Or with Gunicorn for production:

   gunicorn app:app

   The app will be available at http://localhost:5000

Usage

Authentication

• Register at /register to create a new account
• Login at /login with your credentials
• Change Password in your profile at /profile

Daily Logging

1. Navigate to the home page
2. Select a date and enter completed tasks for different topics
3. Add notes for context
4. Autosave tracks your progress

Topic Management

• Create custom topics via /topics
• Topics are user-scoped (private to each user)
• Delete topics (associated history is preserved, goals are removed)

AI Suggestions

• Get Next Step: Requests AI to suggest the next learning task based on your history and difficulty level
• Get Suggestion: Asks AI for a recommendation on what to learn next for a specific topic
• Requests are async and processed via background workers

Progress Analytics

• Dashboard (/dashboard): Visual overview of your streaks and badges
• Progress (/progress): Paginated historical view of your daily logs
• Analytics API (/analytics_data): Detailed stats including:
  • Current and longest streaks
  • Badge tier and milestone info
  • Topic counts and activity by date
  • This month's activity count

Badge Tiers

Earn badges by maintaining daily streaks:

Emoji	Badge	Days Required
🌱	Seedling	1
🔥	On Fire	7
⚡	Momentum	15
🚀	Moonshot	30
🏆	Champion	60
🔮	Quarter	90
🌊	Half Year	180
🌙	3 Quarters	270
🌟	Legend	365

Integrations

HackTheBox Tracking:

• Navigate to /thm to track completed rooms
• Toggle room completion status
• View all completed rooms

Bandit Challenges:

• Access your completed Bandit levels via the API
• Tracked as topic history entries

API Endpoints

Authentication

• POST /register - Create new user account
• POST /login - Login to account
• GET /logout - Logout

Topics

• GET /topics - List user's topics
• POST /topics - Create new topic
• DELETE /topics/<id> - Delete topic

Logs & Progress

• GET /load_log/<date> - Load tasks for a specific date (YYYY-MM-DD)
• PATCH /api/log/<date> - Update log for a date
• POST /save_log - Save daily log with tasks
• GET /analytics_data - Get analytics and streak data
• GET /progress - View paginated progress history

AI Features

• POST /get_suggestion - Request AI suggestion (returns job_id)
• POST /next_suggestion - Request next learning step (returns job_id)
• GET /ai_job/<job_id> - Poll async job status and result

Challenge Tracking

• POST /api/toggle_room - Mark HackTheBox room as complete/incomplete
• GET /get_completed_htb - Get completed HTB rooms
• GET /get_completed_bandit - Get completed Bandit levels

Database Schema

• User - User accounts with authentication
• DailyLog - Daily task logs with completed_tasks (JSON) and notes
• Topic - User-created learning topics
• TopicHistory - Timestamped history of completed tasks per topic
• UserProgress - Tracks room/challenge completions
• Goal - Learning goals with target counts and periods
• Badge - Earned streak badges per user

Configuration

Rate Limiting

• Default: 2000 requests per day, 500 per hour
• Uses Redis for distributed limiting across multiple workers
• Falls back to local storage if Redis unavailable

AI Job Processing

• Async job queue with ThreadPoolExecutor
• Redis TTL: 10 minutes for job storage
• Configurable worker threads via AI_WORKER_THREADS env variable
• Timeout: 8 seconds per Gemini API request

Database Connection Pooling

• Pool pre-ping enabled for connection stability
• Pool recycled every 5 minutes
• Auto-reconnects on connection closure

Error Handling

• 404 Pages: Custom error page for not found
• 500 Pages: Automatic session rollback on server errors
• Database Errors: Graceful fallback with logging
• AI Timeouts: User-friendly fallback messages

Development

Running Locally

export FLASK_ENV=development
export FLASK_DEBUG=1
python app.py

Database Migrations

flask db init              # Initialize migration folder
flask db migrate           # Create new migration
flask db upgrade           # Apply migrations

Logging

The application logs to standard output. In production:

• Log level: INFO
• Available logs include user actions, database warnings, and AI job failures
• Debug logging in analytics calculations (see /analytics_data)

Security Features

• Password hashing with Werkzeug
• Session-based authentication with Flask-Login
• CSRF protection with Flask-WTF
• Rate limiting to prevent abuse
• User data isolation (queries scoped to current_user)
• SQL injection prevention via SQLAlchemy ORM

Deployment

Deploy to Render, Heroku, or any WSGI-compatible platform:

1. Set environment variables on your platform
2. Use gunicorn app:app as the start command
3. Ensure PostgreSQL and Redis are available
4. Run migrations: flask db upgrade

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