Knowledge-Transfer-AI

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🎥 Demo

A quick preview of the application in action:

Watch Demo Video

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🧠 Overview

Knowledge-Transfer-AI is a full-stack AI-powered learning platform that generates and delivers role-tailored educational content through a structured onboarding system, lecture management interface, and interactive AI-driven learning experience.

It combines:

• React frontend UI
• Custom backend knowledge system (RAG-style architecture)
• Backboard API for AI orchestration
• ElevenLabs API for text-to-speech generation

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Table of contents

• What this project does
• Why this is useful
• Key features
• Tech stack
• Repository layout
• Getting started
• Environment variables
• How to use
• System flow
• Why this project matters
• Support
• License & acknowledgements

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What this project does

• Generates personalized learning paths based on user role and industry
• Retrieves knowledge using a backend RAG pipeline
• Generates AI explanations and summaries for lectures
• Converts learning content into natural speech using ElevenLabs
• Provides an interactive “Learn” experience for users

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Why this is useful

• Rapidly prototype AI-enhanced learning experiences for teams and users
• Role- and industry-aware onboarding flows to tailor content
• Modern frontend stack (React + Tailwind + Material components) for fast UI development
• Clear separation of the UI from API/back-end so you can connect any AI backend or mock service

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Key Features

• Role-based onboarding flow for personalization
• Lecture browsing and management system
• AI-generated learning content per lecture
• Text-to-speech narration for lessons
• Backend-driven knowledge retrieval system (RAG)
• Modular and scalable frontend architecture
• External AI service integration (Backboard + ElevenLabs)

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Tech Stack

Frontend

• React
• Vite
• JavaScript (ES6+)
• Tailwind CSS
• Material Tailwind UI

Backend / Knowledge System

• Custom knowledge ingestion pipeline
• RAG-style retrieval system (chunking + semantic search layer)
• REST API service layer
• Environment-based configuration (VITE_API_URL)

AI Services

• Backboard API (AI generation / orchestration)
• ElevenLabs API (text-to-speech synthesis)

Architecture

• RESTful API communication between frontend and backend
• Service-layer abstraction (src/services/api)
• Decoupled frontend/backend design
• External AI service integration layer

Tooling

• Vite build system
• npm / yarn / pnpm
• ESLint
• Git / GitHub

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Repository Structure

Important paths (relative links):

• frontend/react-app/ — Main React application (UI layer). Built with React + Vite + Tailwind + Material Tailwind. Handles onboarding, lectures, and AI learning experience.

  • frontend/react-app/src/pages/ — Core pages (Onboarding, Lectures, Learn, etc.)
  • frontend/react-app/src/services/api/ — API abstraction layer for backend + external AI services (Backboard + ElevenLabs)
  • frontend/react-app/src/main.jsx — Application entry point
  • frontend/react-app/src/App.jsx — Root app structure and routing
  • frontend/react-app/package.json — Frontend dependencies and scripts

• backend/ — Python-based AI knowledge system and API layer (RAG + orchestration backend)

  • backend/main.py — Main backend entry point (API server + orchestration logic)
  • backend/models.py — Data models / schemas used across ingestion and retrieval system
  • backend/requirements.txt — Python dependencies for backend services
  • backend/sessions.db — SQLite database for session storage and tracking

• backend/services/ — Core AI and external service integrations

  • backend/services/backboard_llm.py — LLM interface using Backboard API for AI generation
  • backend/services/backboard_rag.py — Retrieval-Augmented Generation (RAG) pipeline implementation
  • backend/services/backboard_service.py — Core service wrapper for Backboard API orchestration
  • backend/services/eleven_labs.py — ElevenLabs text-to-speech integration (voice synthesis)

• backend/session_cache/ — Temporary runtime/session storage for AI interactions and user sessions

• README.md — Main project documentation (overview, architecture, setup, usage)

• LICENSE — Repository license file (MIT or specified license)

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Getting Started

Prerequisites

• Node.js 16+
• npm / yarn / pnpm
• Backend API running (or mock server)
• API keys for Backboard + ElevenLabs (if enabled)

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Frontend Setup

git clone https://github.com/GitNH27/Knowledge-Transfer-AI.git
cd Knowledge-Transfer-AI/frontend/react-app
npm install
npm run dev

Open:

http://localhost:5173 or similar

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Environment Variables

Create a .env.local file:

VITE_API_URL=https://your-backend-api.com

Important:

• Do NOT expose AI API keys in frontend
• Backboard + ElevenLabs keys should remain server-side

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How to Use

• Select role in onboarding
• Browse generated lectures
• Open “Learn” page for AI explanations
• Listen to audio narration (ElevenLabs)
• Extend API layer in src/services/api

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System Flow

1. User completes onboarding (role + industry)
2. Frontend requests personalized content
3. Backend retrieves relevant knowledge via RAG system
4. Backboard API generates AI responses
5. ElevenLabs converts text to speech
6. Frontend renders interactive learning experience

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Why This Project Matters

• Demonstrates real-world AI integration
• Combines retrieval + generative AI + speech synthesis
• Shows scalable full-stack architecture
• Mirrors production-grade AI learning platforms

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Support

• GitHub Issues for bugs or feature requests
• Frontend docs in frontend/react-app/README.md
• Backend modules extend /backend directory

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License & Acknowledgements

MIT License

Credits:

• Material Tailwind
• Creative Tim templates
• Backboard API
• ElevenLabs
• React + Vite ecosystem