Shikshya

Shikshya is a comprehensive monolithic web application architected to facilitate seamless interaction between academic stakeholders. Ideally suited for educational institutions, it combines course management, interactive study tools, and AI-powered assistance into a unified, secure platform.

System Overview

The platform serves as a central hub for academic operations, facilitating:

Course Administration: Enabling instructors to manage curricula, distribute resources (PDFs), and monitor student engagement metrics.
Student Portal: Providing enrollment management, syllabus tracking, and an integrated study environment.
AI-Assisted Learning: Implementing Retrieval-Augmented Generation (RAG) flows to provide context-aware explanations of course materials via the Google Gemini API.
Role-Based Access Control: Strictly typed enforcement of permissions for Admin, Teacher, and Student roles.

Features

For Students

Course Enrollment: Browse and enroll in available courses with real-time availability
Interactive Study Environment: Resizable split-pane workspace with PDF viewer and AI chat
AI-Powered Learning Assistant: Get instant explanations of course materials using context-aware AI
Text-to-Explanation: Select any text in PDFs to receive detailed AI explanations
Syllabus Management: Track course syllabi and upcoming topics
Personal Dashboard: View enrolled courses, upcoming deadlines, and personalized learning progress

For Teachers

Course Creation & Management: Create, update, and delete courses with rich metadata
PDF Resource Upload: Upload and manage learning materials for each course
Student Analytics: Monitor student enrollment and engagement metrics
Course Customization: Organize courses by nested folder setup
Todo Management: Track teaching tasks and course preparation items

For Administrators

User Management: Oversee student and teacher accounts
System Analytics: Monitor platform usage and performance metrics
Role Assignment: Manage user permissions and access levels
Platform Configuration: Control system-wide settings and features

AI-Powered Features

Contextual Chat: AI assistant understands the context of currently viewed PDF materials
RAG Implementation: Retrieval-Augmented Generation for accurate, source-based responses
LaTeX Support: Render mathematical equations and scientific notation in chat
Streaming Responses: Real-time AI response streaming for better user experience
Multi-turn Conversations: Maintain conversation context across multiple interactions

Study Tools

PDF Viewer: High-fidelity document rendering with zoom, navigation, and page controls
Resizable Workspace: Drag-to-resize panels for optimal viewing experience
Text Selection: Select and interact with PDF text for explanations
Responsive Design: Seamless experience across desktop and tablet devices

Security & Authentication

Multi-Provider Authentication: Email/Password and Google OAuth support
Session Management: Secure, encrypted session handling with Better Auth
Role-Based Access Control (RBAC): Granular permissions for Admin, Teacher, and Student
Route Protection: Middleware-enforced access validation on protected routes
Input Sanitization: Comprehensive Zod schema validation across all forms and APIs

Technical Architecture

Core Infrastructure

Framework: Next.js 15 (App Router)
Language: TypeScript (Strict Mode)
Runtime: Node.js
Package Manager: pnpm

Frontend Layer

UI Library: React 19
Styling Engine: Tailwind CSS 4
Component System: Shadcn UI (Headless UI + Radix Primitives)
State Management: React Query (TanStack Query) for server state; URL-based state for UI.
Animations: Framer Motion

Backend Layer

API Architecture: tRPC (End-to-end type safety)
Database: PostgreSQL (Relational Data Store)
ORM: Drizzle ORM
Authentication: Better Auth (Secure session management)
File Storage: UploadThing (Object storage abstraction)

Artificial Intelligence

Provider: Google Generative AI (Gemini)
SDK: Vercel AI SDK
Integration: Custom, context-aware query resolution for document Interaction.

Functional Specifications

Authentication & Security

Secure Authentication Flows: Integrated robust sign-up/sign-in using Email/Password and OAuth (Google).
Input Validation: Enforced rigorous validation using Zod schemas at both API and form levels to ensure data integrity.
Route Protection: Middleware-based access validation.

Course Management Module

CRUD Operations: Comprehensive creation, read, update, and delete functionality for course content.
Optimistic UI Updates: Immediate feedback during state mutations (e.g., course creation) prior to server confirmation.
Visual Integration: Utilized react-pdf and pdfjs-dist for high-fidelity rendering of academic materials within the browser.

Interactive Study Workspace

Split-Pane Layout: Engineered a resizable interface enabling simultaneous document viewing and chat interaction.
Mathematical Rendering: Integrated LaTeX support for displaying complex equations within chat streams.
Context-Aware Explanations: Select-to-explain functionality triggers AI interpretation of specific document sections.

Engineering Optimizations

Type Safety: Achieved full-stack type safety through tRPC and shared Zod schemas, significantly reducing runtime anomalies.
Performance:
- Server Components: Leveraged React Server Components (RSC) to minimize client-side bundle size.
- Streaming & Suspense: Utilized granular loading states and streaming responses for non-blocking UI rendering.
- Efficient Data Fetching: Implemented TanStack Query for optimal caching and request deduplication.
Scalability: Designed the database schema with Drizzle ORM to support future extensions and complex relationships.

Installation & Setup

Prerequisites

Node.js (v18+)
pnpm
Docker (for local PostgreSQL instance)

Local Development

Clone Repository

git clone https://github.com/i-ces/shikshya.git
cd shikshya

Install Dependencies
```
pnpm install
```

Database Initialization

./start-database.sh
# Initializes a Postgres container on port 5432

Environment Configuration

cp .env.example .env
# Update .env with valid credentials

Schema Migration
```
pnpm db:push
```
Start Development Server
```
pnpm dev
```

Environment Configuration

Create a .env file in the root directory with the following variables:

Database Configuration

DATABASE_URL: Connection string for PostgreSQL.

Authentication (Better Auth)

BETTER_AUTH_SECRET: Cryptographic secret for session security.

Google OAuth Credentials

GOOGLE_CLIENT_ID: OAuth Client ID from Google Cloud Console.
GOOGLE_CLIENT_SECRET: OAuth Client Secret.

AI Integration

GOOGLE_GENERATIVE_AI_API_KEY: API key for Google Gemini model access.

File Storage

UPLOADTHING_TOKEN: API token for file upload service.

Credential Generation

Auth Secret: Generate via OpenSSL:

openssl rand -base64 32

Google OAuth:

Configure a new Project in Google Cloud Console.
Enable OAuth 2.0 APIs.
Set Authorized Redirect URIs to http://localhost:3000/api/auth/callback/google.

Name		Name	Last commit message	Last commit date
Latest commit History 77 Commits
.github/workflows		.github/workflows
public		public
src		src
.env.example		.env.example
.gitignore		.gitignore
.npmrc		.npmrc
README.md		README.md
components.json		components.json
drizzle.config.ts		drizzle.config.ts
eslint.config.js		eslint.config.js
next.config.js		next.config.js
package.json		package.json
pnpm-lock.yaml		pnpm-lock.yaml
postcss.config.js		postcss.config.js
prettier.config.js		prettier.config.js
start-database.sh		start-database.sh
tsconfig.json		tsconfig.json

i-ces/Shikshya

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