EtherEd AI

Decentralized EtherEd AI

Decentralized EtherEd AI is a decentralized, AI-driven tutoring platform that leverages blockchain technology for secure payments and progress tracking. It is powered by Groq's LLAMA3 AI and built using Python Flask and Solidity.

Overview

This platform integrates artificial intelligence and blockchain to provide personalized tutoring. It adapts to a student's learning needs, manages payments through Ethereum smart contracts, and ensures progress tracking on-chain for transparency and immutability.

Recent Enhancements

• Path-Based Learning Tracks

• ChatGPT-Style Sidebar for Chat History

• Achievement Badges & Dynamic Avatar System

• Voice Input & Real-Time Leaderboard

• Celebratory Confetti Animations

• Futuristic Cyberpunk UI with Neon Effects

Key Features

Personalized Learning

The platform uses Groq's LLAMA3 AI to generate tailored responses based on student queries and progress.

Path-Based Learning Tracks

The system supports five distinct learning paths with predefined question categories:

1. DSA Only – Covers topics such as sorting, graphs, and dynamic programming.

2. Programming – Focuses on coding-related queries such as debugging and syntax.

3. Blockchain – Deals with topics like Ethereum, smart contracts, and decentralization.

4. Non-Tech Field – Includes aerospace, mechanical, and electrical engineering questions.

5. Random – Allows casual, non-study-related discussions.

ChatGPT-Style Sidebar

The platform organizes lifetime chat history by learning path, enabling users to revisit past conversations in a categorized format.

Blockchain Integration

• Smart contracts manage tutoring session payments in ETH, store progress, award badges, and log chat history securely on Ethereum.

• Chat history is stored on-chain and linked to the user's Ethereum address for indefinite access.

Futuristic Cyberpunk UI

The platform features a neon-themed user interface with:

• Holographic effects

• Animated backgrounds

• Glowing buttons

• Smooth scrolling for a sci-fi aesthetic

Interactive Features

• Dynamic Avatar System

• Voice Input

• Real-Time Leaderboard

• Achievement Badges

• Celebratory Confetti Animations

• Optional Text-to-Speech for Responses

Robust Error Handling

Provides user-friendly messages to maintain a smooth learning experience, such as "Hey, this isn't a blockchain-related question!"

Why It Stands Out

• Adaptive AI Tutoring – Uses gamified, structured learning paths.

• Blockchain-Powered Transparency – Ensures immutable tracking of progress, payments, and achievements.

• Modular & Scalable – Built with Flask, Ethereum integration, and a cyberpunk UI.

• Visually Striking & Technically Advanced – Combines cutting-edge AI with a futuristic design.

Tech Stack

• AI: Groq LLAMA3

• Backend: Python Flask

• Blockchain: Solidity (Ethereum Smart Contracts), Web3.py, Truffle

• Frontend: HTML/CSS/JavaScript (Interactive UI)

• Local Development: Ganache (Local Ethereum Blockchain)

Project Structure

The project consists of the following components:

1. Blockchain – Solidity smart contracts and deployment files.

2. Backend – Flask application handling AI queries, blockchain interactions, and configurations.

3. Frontend – Static frontend with cyberpunk UI elements.

4. Environment Variables – Stored in a .env file for security.

Prerequisites

To set up the project, install the required dependencies:

• Install Node.js and npm

• Install Python 3.11 and dependencies

• Install Ganache for local Ethereum blockchain development

• Install Truffle for smart contract development

Setup Instructions

1. Clone the repository and navigate to the project directory.

2. Install dependencies for both the blockchain and backend.

3. Configure environment variables in a .env file.

4. Deploy the smart contract using Truffle.

5. Update the backend configuration with the smart contract ABI.

6. Start the Flask backend, which runs on http://127.0.0.1:5000/.

Usage

To use the platform:

1. Open http://127.0.0.1:5000/ in a browser.

2. Enter an Ethereum address (e.g., from Ganache).

3. Select a learning path.

4. Ask a question using text input or voice.

5. Choose a payment method (ETH or free).

6. Submit the query to receive an AI response, track progress, and earn badges.

Users can also access chat history via the sidebar and check their progress using API calls.

Future Enhancements

• Introduce a custom ERC-20 token for student rewards.

• Extend the platform to support multiple tutors.

• Optimize chat history storage using off-chain indexing solutions.

• Partner with online education platforms to offer blockchain-backed certificates.

• Integrate MetaMask for real ETH transactions.

• Implement NFT-based tutoring sessions for exclusive AI tutor access.