AI Tutor

描述

The AI Teaching App leverages the power of Large Language Models (OpenAI GPT-4o) to act as a personalized tutor. Users can upload their PDF study materials, which the AI analyzes to provide context-aware explanations, answer questions, and guide learning.

Linkt to the app

Core Features:

AI-Powered Tutoring: Get tailored explanations based on uploaded PDF content, with selectable tutor specializations (Math, Science, etc.).
Dynamic AI Whiteboard: Unlike traditional whiteboards, the AI automatically uses this Fabric.js canvas to write out key concepts, formulas, and diagrams during its explanations, enhancing visual understanding.
Advanced Voice Interaction: Engage in seamless voice conversations with the AI using integrated Speech-to-Text (Whisper), Text-to-Speech (OpenAI TTS), and a full Speech-to-Speech loop, including silence detection for hands-free interaction.
Web3 Subscription Management: Utilizes a custom Solidity smart contract (SubscriptionManager) deployed on the OpenCampus Codex testnet to handle user subscriptions paid in the native currency, integrated via Wagmi and RainbowKit for wallet connections.
User Dashboard: Includes protected routes for user profiles, learning progress tracking, and application settings.
Modern Tech Stack: Built with Next.js (App Router), TypeScript, Tailwind CSS, Shadcn/UI, OpenAI API, Fabric.js, Solidity, Hardhat

This project demonstrates a full-stack application combining cutting-edge AI, interactive frontend design, and Web3 technologies to create a unique and effective educational tool.

本次黑客松进展

Hackathon Progress: AI Teaching App During the hackathon, significant progress was made in developing the core functionality of the AI Teaching App. The team successfully set up the Next.js project structure, implemented user authentication flows (likely leveraging Supabase), and built the primary teaching interface. Key achievements include: PDF Upload & Processing: Established the mechanism for users to upload PDF documents. AI Chat Integration: Integrated OpenAI's API to enable basic conversational tutoring based on the uploaded content via a functional chat interface. Interactive Whiteboard Foundation: Developed the initial whiteboard component using Fabric.js, laying the groundwork for AI-driven visual explanations. Voice Interface Prototyping: Began implementing voice interaction features, setting up API routes for speech-to-text and text-to-speech, demonstrating the feasibility of the speech-to-speech conversation loop. UI Development: Utilized Shadcn/UI and Tailwind CSS to create a responsive and modern user interface for the protected dashboard and teaching areas. By the end of the hackathon, the app showcased its core concept: users could upload a PDF and have a basic text-based AI tutoring session related to its content, with foundational elements for the whiteboard and voice features in place.

AI Tutor

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描述

本次黑客松进展

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