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# PragatiVeer v2 - Product Requirements Document (PRD) & Architecture
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## 1. Product Overview
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**PragatiVeer** is a next-generation, AI-powered daily practice platform and mock testing engine designed specifically for **JEE and NEET aspirants**. The platform offers a highly adaptive learning experience by integrating a CBT (Computer Based Test) engine, dynamic Daily Practice Problems (DPPs), and an AI Coach that tailors study plans, analyzes mistakes, and tracks syllabus progress.
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## 2. Core Objectives
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- Deliver a robust, scalable CBT engine simulating real exam environments for JEE and NEET.
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- Provide AI-driven mistake tracking and spaced repetition to ensure long-term retention.
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- Generate personalized study strategies, college predictions, and time-optimization techniques.
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- Offer gamification (streaks, leaderboards, tier-based access) to enhance student engagement.
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## 3. Architecture & Infrastructure
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The application follows a modern decoupled architecture, containerized entirely via Docker, ensuring reproducibility and scalability.
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### 3.1 Container Architecture (Docker Compose)
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The stack is orchestrated using `docker-compose.yml` and consists of 8 distinct containers:
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1. **pragativeer_frontend (Frontend App)**
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- **Framework:** Next.js (React), TailwindCSS, TypeScript.
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- **Role:** Renders the user interface, dashboards, and CBT interface. Communicates with the backend API.
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- **Port:** `3000`
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2. **pragativeer_backend (FastAPI Backend)**
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- **Framework:** FastAPI (Python 3.11), SQLModel/Pydantic.
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- **Role:** Handles core business logic, API routing, authentication (JWT), and AI orchestrations (OpenAI).
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- **Port:** `8000`
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3. **pragativeer_db (PostgreSQL Database)**
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- **Engine:** PostgreSQL 15 (Alpine).
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- **Role:** Primary persistent data storage for users, questions, test attempts, streaks, and analytics.
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- **Volume:** `pgdata` (Persistent)
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- **Port:** `5432`
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4. **pragativeer_pgbouncer (PgBouncer)**
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- **Engine:** PgBouncer.
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- **Role:** Lightweight connection pooler for PostgreSQL, ensuring the database is not overwhelmed by high connection counts during peak exam periods.
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5. **pragativeer_cache (Redis)**
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- **Engine:** Redis 7 (Alpine).
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- **Role:** High-speed in-memory cache for API responses, leaderboard rankings, and serves as the message broker for Celery background tasks.
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- **Volume:** `redisdata` (Persistent)
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- **Port:** `6379`
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6. **pragativeer_worker (Celery Worker)**
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- **Engine:** Celery (Python).
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- **Role:** Processes heavy asynchronous background tasks asynchronously (e.g., generating AI responses, processing bulk exam analytics, sending emails) without blocking the main API threads.
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7. **pragativeer_beat (Celery Beat)**
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- **Engine:** Celery Beat.
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- **Role:** The scheduler for periodic background jobs (e.g., nightly streak calculations, automated weekly progress report generation, DB cleanup).
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8. **pragativeer_storage (MinIO)**
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- **Engine:** MinIO (S3-compatible object storage).
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- **Role:** Handles unstructured data storage, such as user profile pictures, uploaded question diagrams, and PDF exports.
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- **Volume:** `miniodata` (Persistent)
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- **Ports:** `9000` (API), `9001` (Console)
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## 4. Key Features & Modules
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### 4.1 Dashboard & Navigation
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- **Tier-based Access:** Users are segmented into Free, Pro, and AI Coach tiers, dynamically unlocking features.
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- **Glassmorphism UI:** Modern, premium aesthetics with light/dark theme support.
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- **Top Header:** Target exam badges (JEE/NEET), current active streak counters, and profile drop-downs.
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### 4.2 AI Coach Ecosystem
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- **AI Tutor:** Real-time conversational AI for doubt resolution (OpenAI integration).
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- **PrepPilot AI:** Adaptive target DPP generation based on current weak areas.
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- **Mistake Analyzer (AI Powered):** Tracks incorrect answers and utilizes AI-powered spaced repetition to resurface them at optimal intervals.
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- **Exam Readiness & College Predictor:** Data-driven predictions based on historical CBT scores.
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- **AI Study Plan & Time Optimization:** Custom schedules generated dynamically for the user.
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### 4.3 Testing & Analytics (CBT Engine)
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- **Mock Tests:** Full-length simulations matching exact NTA (National Testing Agency) UI patterns.
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- **Syllabus Tracker:** Granular chapter-by-chapter completion tracking.
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- **Performance Analytics:** Visual charts tracking accuracy, speed, and subject-wise competence.
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## 5. Technology Stack Summary
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- **Frontend:** Next.js 14/15, TailwindCSS, Framer Motion, Lucide Icons, Shadcn UI.
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- **Backend:** Python 3.11, FastAPI, Uvicorn.
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- **Database ORM:** SQLModel (SQLAlchemy).
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- **AI Integration:** OpenAI API.
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- **Background Tasks:** Celery + Redis.
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- **Storage:** MinIO, Boto3.
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- **DevOps:** Docker, Docker Compose.
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## 6. Future Scope
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- Expand AI capabilities for voice-based doubt resolution.
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- Introduce real-time multiplayer mock test battles.
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- Deeper parent-dashboard integrations for performance tracking.
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