EduAI Platform

EduAI Platform is an AI-powered teaching assistant for multi-grade classrooms. It combines a React and Vite web app with an Express and TypeScript API, PostgreSQL persistence, Firebase authentication, NCERT content, and specialized educational AI agents.

AI Agents

1. Hyper-Local Content Generation (Popular) Generate culturally relevant materials in students' mother tongues using speech-to-text input. Supports 8 languages.

2. Create Differentiated Materials (Essential) Adapt content into multiple grade-level versions from PDF, DOCX, CSV, or other source material.

3. AI Lesson Planner Structure syllabi into efficient teaching schedules with progress tracking and weekly analytics.

4. Instant Knowledge Base (Enhanced) Provide comprehensive answers using NCERT textbooks and external educational sources, with NCERT integration.

5. Design Visual Aids Create diagrams, flowcharts, and AR-ready content to explain complex concepts.

6. Gamified Teaching Agent (Fun) Build quizzes, badges, leaderboards, and achievement-based activities for learners across grades.

7. Audio Reading Assessment (Essential) Assess pronunciation, fluency, and comprehension from live recordings or uploaded audio files.

8. Master Agent Chatbot (Central Hub) Use one conversational interface to route requests to the most appropriate educational agent.

9. Performance Analysis Generate personalized learning paths and end-of-term performance reports.

10. AR using Sketchfab Explore and embed educational 3D models from Sketchfab for interactive classroom learning.

The platform also supports PDF, image, audio, and video generation workflows, Firebase Hosting and Functions deployment, and classroom analytics.

Technology

• Frontend: React, TypeScript, Vite, Tailwind CSS, Radix UI, TanStack Query
• Backend: Node.js, Express, TypeScript
• Database: PostgreSQL with Drizzle ORM
• AI services: Google Gemini and Google Cloud services
• Authentication: Firebase Authentication
• Python services: FastAPI, LangGraph, and LangChain agents

Prerequisites

• Node.js 18 or newer
• npm
• PostgreSQL database, such as a Neon database
• Python 3.10 or newer for the Python agent service
• A Gemini API key
• Firebase project credentials when Firebase authentication or deployment is enabled

Local Setup

1. Install the Node.js dependencies:

   npm install

2. Create a local environment file from the template:

   cp .env.example .env

   On Windows PowerShell, use:

   Copy-Item .env.example .env

3. Update .env with at least:

   NODE_ENV=development
   PORT=5000
   GEMINI_API_KEY=your-gemini-api-key
   DATABASE_URL=postgresql://user:password@host:5432/database?sslmode=require

   Add the Firebase variables from .env.example if Firebase authentication is required.

4. Apply the database schema:

   npm run db:push

5. Start the development server:

   npm run dev

   Open http://localhost:5000 in a browser.

Python Agents

The Python service is optional for workflows that use the agent bridge.

python -m venv .venv

Activate the environment and install dependencies:

• Windows PowerShell: .venv\\Scripts\\Activate.ps1
• macOS/Linux: source .venv/bin/activate

pip install -r python_agents/requirements.txt
python python_agents/main.py

The Python service also reads environment variables from .env when configured to do so.

Available Commands

Command	Description
npm run dev	Start the development server with Vite and Express
npm run build	Build the frontend and bundle the production server
npm start	Start the production bundle
npm run check	Run the TypeScript compiler checks
npm run db:push	Push the Drizzle schema to PostgreSQL

Project Structure

client/src/       React application, pages, components, and client utilities
server/           Express API, integrations, storage, and generation services
shared/           Shared database schema and types
python_agents/    FastAPI and LangGraph educational agents
functions/        Firebase Functions deployment package
docs/             Deployment and platform documentation
scripts/           Local and deployment helper scripts

Firebase Deployment

The project supports Firebase Hosting for the frontend and Firebase Functions for the backend. Authenticate with the Firebase CLI, configure the required production secrets, and deploy:

npm install -g firebase-tools
firebase login
npm run build
firebase deploy

For the complete deployment process, environment configuration, API routes, and troubleshooting, see docs/FIREBASE-DEPLOYMENT.md.

Environment Variables

The complete list of supported variables is maintained in .env.example. Never commit .env or API keys to source control.

Core services use:

• GEMINI_API_KEY for Gemini-powered features
• DATABASE_URL for PostgreSQL and Drizzle
• PORT for the local API server
• FIREBASE_* and VITE_FIREBASE_* for Firebase authentication

License

This project is licensed under the MIT License.