Clarity for Every Concept. Where Knowledge Becomes Insight.

Features • Tech Stack • Support

Academic Oracle

Academic Oracle is a learning-focused AI platform designed to maximize understanding, not passive consumption.

Instead of immediately giving answers, Academic Oracle follows a scientifically grounded flow:

Ask → Think → Hint → Attempt → Feedback → Pattern → Insight → Mastery

The goal is not memorization — it’s deep, durable learning.

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Why Academic Oracle?

Most AI tools optimize for speed.
Academic Oracle optimizes for retention, intuition, and reasoning.

Core Learning Principles

• Active recall before answers
• Progressive hinting instead of instant solutions
• Error-correction loops
• Pattern discovery over rote explanation
• Minimal UI disruption to maintain cognitive flow

You don’t just learn faster — you learn properly.

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Features

🧠 Learning Engine

• Hint-based reasoning flow (Ask first, reveal progressively)
• Structured thinking prompts
• Pattern extraction instead of answer dumping

📝 Integrated Quiz Platform (NEW)

• Auto-generated concept-specific quizzes
• Multi-question adaptive testing
• Mastery popups & performance feedback
• Reinforcement-based correction
• Mid-session language switching
• Unified Chat + Quiz UI system

🎨 UX & Rendering

• Robust Markdown rendering
• Math (KaTeX)
• Tables
• Code blocks
• Dark / Light mode
• Responsive design (desktop & mobile)
• Fail-in-console architecture (UI never crashes)

🔐 Security & Architecture

• AES-GCM-256 encryption for sensitive keys
• Supabase-backed session continuity
• Arcade-style interactive onboarding demo

⚙️ Context-Aware Model Adaptation (NEW)

• Dynamic model routing based on real-time traffic conditions
• Promise-race orchestration during high-load periods
• Automatic fallback to most efficient single-model pipeline under normal conditions
• Intelligent compatibility matching per user request type
• Stepfun-3.5 integration as high-load inference offloader
• Automatic cancellation of non-winning model responses to preserve cost efficiency

Academic Oracle adapts not just to learners - but to system conditions.

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Tech Stack

• Frontend: React 19 + TypeScript
• Backend (AI): Google GenAI models (Gemini-3, Gemini-2.5) and StepFun-3.5
• Backend (Auth): Supabase & Google OAuth
• Build Tool: Vite 6
• Styling: Tailwind CSS
• Math Rendering: KaTeX
• State & UX: Custom lightweight logic (no heavy frameworks)
• Security: AES-GCM-256 encryption for sensitive keys
• AI Provider: Gemini API (user-supplied key)

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Running Locally

Prerequisites

• Node.js (v18+ recommended)

Setup

1. Install dependencies:

   npm install
   

2. Setup your "Supabase Project"

3. Setup your "Google AI Studio API Key(s)"

4. Setup your "OpenRouter API Key"

5. Setup Environment Variables:

   VITE_SUPABASE_URL=YOUR_SUPABASE_URL
   VITE_SUPABASE_ANON_KEY=YOUR_SUPABASE_ANON_KEY
   VITE_GEMINI_KEYS=YOUR_GOOGLE_AI_STUDIO_API_KEY(s) EX: KEY1,KEY2,KEY3,...
   VITE_STEPFUN_KEY=YOUR_OPENROUTER_API_KEY
   
   

6. Start development server:

   npm run dev
   

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Project Vision

Academic Oracle aims to redefine how AI integrates into education:

• Not as a solver.
• Not as a shortcut.

But as a structured reasoning partner.

The long-term goal is to build a universal academic cognition system that scales from secondary education to research-level inquiry.

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Credits

Academic Oracle was designed and built by Vo Tan Binh.

This project represents original work in:

• Learning-science–driven AI interaction design
• Progressive reasoning and hint-based pedagogy
• Closed-feedback AI tutoring systems
• Secure, minimal, and distraction-free educational UX

If you build upon this work, attribution is appreciated.

Support

If Academic Oracle helps your learning:

• ⭐ Star the repository

• ☕ Support via Buy Me a Coffee

• 🧠 Use it, break it, and learn from it

Recognition matters. Impact matters more.