Hello Zenno - Language Learning Assistant

An open-source web application for intermediate and advanced language learners, designed to assist with vocabulary acquisition and listening practice through AI-generated content.

About Hello Zenno

Hello Zenno helps you learn languages by:

• Assisting you in reading texts in your target language
• Creating AI-generated dictionary entries with rich metadata
• Highlighting unfamiliar words with interactive hover explanations
• Generating audio dictation exercises with words in different contexts
• Supporting vocabulary acquisition through contextual learning

Built by a co-founder of Memrise, Hello Zenno fills the gap in language learning apps by providing deeper context and richer dictionary information tailored to what you're reading.

Features

AI-Enhanced Learning

• Rich AI-generated dictionary with detailed metadata and examples
• Dynamic audio generation for hearing words in various contexts
• Interactive text highlighting for quick vocabulary lookup
• Etymology explanations and contextual usage examples
• Dictation flashcards for listening practice

Source Files

Source files are the primary way to add learning content. They can be created in two ways:

1. Text Input

   • Paste or type text directly into the application
   • Perfect for copying text from articles, books, or other sources
   • Text is processed immediately without OCR
   • Creates a .txt file in your source directory

2. Image Upload

   • Upload images containing text (e.g., photos of books, signs, etc.)
   • OCR is used to extract text from the images
   • Original image is preserved for reference
   • Supports common image formats (jpg, png, etc.)

Both types of source files support:

• Automatic translation to English
• Vocabulary extraction
• Interactive word linking
• Practice sentence generation

Quick Start for Developers

Prerequisites

• Docker Desktop app installed and running
• Node.js and npm installed
• Python 3.10+ installed
• Supabase CLI installed (brew install supabase/tap/supabase)

Setup Steps

1. Start Docker and Supabase:

   # Make sure Docker Desktop app is running first
   supabase start

2. Configure environment:

   # Copy the example environment file
   cp .env.example .env.local
   # Edit .env.local and fill in your credentials

3. Run the backend (Terminal 1):

   source .env.local
   export FLASK_PORT=3000
   ./scripts/local/run_backend.sh

   The Flask API will run on http://localhost:3000

4. Run the frontend (Terminal 2):

   source .env.local
   ./scripts/local/run_frontend.sh

   The SvelteKit app will run on http://localhost:5173

5. View the application: Open http://localhost:5173 in your browser

Tip:

• If another app is using port 5173, free it with lsof -ti:5173 | xargs kill -9 or run the frontend on 5174 using cd frontend && PORT=5174 npm run dev, then open http://localhost:5174

Detailed Documentation

For more detailed setup and development information:

• backend/docs/DEVOPS.md - Full development setup and infrastructure details
• backend/docs/DATABASE.md - Database configuration and management
• backend/docs/MIGRATIONS.md - Database migration procedures
• frontend/docs/AUTHENTICATION_AUTHORISATION.md - Authentication setup with Supabase
• frontend/docs/FRONTEND_SVELTEKIT_ARCHITECTURE.md - Frontend architecture overview
• .env.example - Required environment variables reference
• Changelog - Recent updates and changes