Turn passive word-saving into active learning. LexiQ helps students build a personal vocabulary database, get AI-generated word insights, and test themselves with adaptive quizzes — all in one cross-platform app.
Live Demo: https://siddharth177.github.io/LexiQ/
Most students preparing for GRE, TOEFL, GMAT, or competitive exams encounter the same bottleneck: they passively highlight words but never revisit them.
LexiQ closes that loop by combining:
- Intelligent word discovery
- Personal knowledge management
- AI-driven assessment
into a single, beautifully designed mobile application.
This project was built entirely from scratch as a self-initiated product — from identifying the user problem, to designing the system architecture, to shipping a production-ready cross-platform application integrated with real AI inference APIs.
- Add words to a cloud-synced personal dictionary
- AI-generated definitions, word types, etymological roots, usage examples, and tense variations powered by Llama 3.3-70B via Groq API
- Hear correct pronunciation with built-in Text-to-Speech
- Swipe to edit or delete — gesture-native UX
- Generate MCQ quizzes from your own saved vocabulary or let AI create entirely new word sets
- 5-level difficulty dial (Basic → Advanced) for AI-generated quizzes
- Configurable timer per question — builds real exam conditions
- Post-quiz review with answer-by-answer breakdown
- Every quiz result stored to the cloud with score, source, and per-question breakdown
- History cards with swipe-to-delete
- Tap any past result to revisit full review
- Full light / dark mode with adaptive theming
- Smooth Rive animations for loading states
- Responsive design — works on mobile, tablet, and web
- State Management: Implemented Riverpod for a scalable, decoupled, and testable architecture.
- Cloud Infrastructure: Leveraged Firebase Firestore for real-time synchronization and offline-first persistence.
- Secure API Strategy: Dynamic loading of Groq AI keys via Firestore-managed secrets, ensuring no sensitive data is exposed in version control.
- LLM Integration: Orchestrated prompt engineering for Llama-3.3-70B via Groq API to ensure consistent JSON-formatted outputs for the app's services.
LexiQ was designed and developed from scratch as an end-to-end product. It represents a synthesis of technical proficiency, product lifecycle management, and a user-centric approach to educational technology.
| Layer | Technology / Role |
|---|---|
| Frontend | Flutter (Dart) — Cross-platform UI (iOS, Android, Web) |
| State Management | Riverpod — Reactive, testable app state |
| Backend | Firebase Auth, Firestore, Authentication, Real-time cloud sync |
| AI Inference | Groq API (Llama 3.3-70B) — Word definitions, quiz generation |
| Animations | Rive — Lightweight vector animations |
| TTS | flutter_tts — Pronunciation playback |
# 1. Clone
git clone https://github.com/siddharth177/LexiQ.git
cd vocab-list
# 2. Install dependencies
flutter pub get
# 3. Add your secrets (gitignored)
Create lib/utils/secrets.dart:
const String kGroqApiKey = 'your_groq_api_key';
# 4. Run
flutter runFirebase is pre-configured via
google-services.json/GoogleService-Info.plist.
To connect your own project, replace these files and update
firebase_options.dart.
Pull requests are welcome.
For significant changes, please open an issue first to discuss what you'd like to change.
- Fork the repository
- Create your feature branch (
git checkout -b feature/your-feature) - Commit your changes (
git commit -m 'Add your feature') - Push and open a Pull Request