StudyAI is not just another flashcard app. It is a high-performance AI-Powered Learning Management System (LMS) engineered to optimize student retention. By utilizing real-time cognitive modeling, heuristic error analysis, and autonomous knowledge extraction, StudyAI acts as a personalized tutor that understands how and why you learn.
Our UI is built around a Premium Glassmorphism Design System crafted entirely from scratch using Vanilla CSS.
- Reduced Visual Fatigue: Carefully selected color palettes and opacity levels.
- Deep Work Enablement: A futuristic, high-end feel that minimizes distractions and encourages flow-state study sessions.
Instead of basic binary error logging (right/wrong), StudyAI utilizes a Hybrid NLP Engine powered by Gemini 1.5 Pro.
- Pattern Recognition: Heuristically clusters your errors into psychological categories (e.g., Conceptual Confusion, Difficulty Ceilings, or Time-Pressure Fatigue).
- Semantic Synthesis: Translates raw structured performance data into actionable, natural-language insights.
Powered by a custom Heuristic State-Space Model, StudyAI tracks your engagement and mental fatigue in real-time.
- Dynamic Load Estimation: Adjusts a cognitive load variable dynamically based on time-weighted rewards and difficulty penalties.
- Flow Zone Detection: Automatically recommends difficulty adjustments or scheduled breaks to keep you perfectly balanced between challenge and skill.
Say goodbye to linear learning. StudyAI performs Entity-Relationship Extraction (ERE) on unstructured course syllabi.
- Relational Mapping: Dynamically builds an adjacency list of concepts and dependencies (requires, part_of, leads_to).
- Mastery Visualization: Renders a stunning force-directed graph using vis.js, where node colors actively reflect your real-time mastery.
A completely data-driven study planner that prioritizes topics to ensure long-term memory consolidation, analyzing both your historical quiz decay rates and upcoming exam proximity.
| Category | Technologies Used |
|---|---|
| Backend Engineering | Python 3.13, Django 6, PostgreSQL (Prod) / SQLite (Dev) |
| AI / Orchestration | Google Gemini 1.5 Pro, GenAI SDK, Custom Heuristic Modeling |
| Frontend Architecture | Vanilla CSS (Glassmorphism), JavaScript (ES6+), vis.js |
| DevOps & Deployment | Docker, Jenkins CI/CD, Render, Supabase |
| Security & Ops | Google OAuth 2.0, WhiteNoise, Gunicorn, OTP-Auth, Rate-Limiting |
Designed and developed by:
- Devyansh Verma — Lead Architect & AI Engineer
- Jyotsna Chaudhary — Frontend Strategist & Content Systems
Follow these steps to get StudyAI running on your local machine:
# 1. Clone the repository
git clone https://github.com/devyansh770-hue/AIStudyAssistant.git
cd AIStudyAssistant
# 2. Create and activate a virtual environment (optional but recommended)
python -m venv venv
source venv/bin/activate # On Windows use: venv\Scripts\activate
# 3. Install dependencies
pip install -r requirements.txt
# 4. Set up environment variables
cp .env.example .env
# Make sure to add your GEMINI_API_KEY and other credentials in the .env file
# 5. Run database migrations
python manage.py migrate
# 6. Launch the local server
python manage.py runserverVisit http://localhost:8000 in your browser to access the platform.