SvelteReader

A Svelte 5 ebook reader with AI-powered chat features, showcasing integration with the CypherTap package for nostr and eCash.

Architecture

┌─────────────────┐     ┌──────────────────┐     ┌─────────────────┐
│  Svelte Frontend │────▶│  FastAPI Backend │────▶│ LangGraph Agent │
│  (Port 5173)     │     │  (Port 8000)     │     │  (Port 2024)    │
└─────────────────┘     └──────────────────┘     └─────────────────┘

Project Structure

• frontend/ - Svelte 5 ebook reader application
• backend/ - FastAPI backend for business logic and LangGraph integration
• agent/ - Self-hosted LangGraph agent for AI chat
• cyphertap/ - CypherTap component library (submodule)
• docs/ - Documentation

Quick Start

1. Start the LangGraph Agent

cd agent
pip install -e . "langgraph-cli[inmem]"
cp .env.example .env
# Add your OPENAI_API_KEY to .env
langgraph dev

2. Start the FastAPI Backend

cd backend
pip install -e .
cp .env.example .env
uvicorn src.main:app --reload --port 8000

3. Start the Svelte Frontend

cd frontend
pnpm install
cp .env.example .env
pnpm dev

Open http://localhost:5173 to use the app.

AI Chat Feature

The AI chat feature allows users to:

1. Highlight text in their ebooks
2. Add notes to highlights
3. Chat with an AI assistant about the highlighted passages

The AI assistant receives context about:

• The highlighted text
• User's notes
• Book title and chapter

Environment Variables

Agent (agent/.env)

• OPENAI_API_KEY - OpenAI API key (required)
• MODEL_PROVIDER - openai or anthropic
• MODEL_NAME - Model to use (e.g., gpt-4o-mini)

Backend (backend/.env)

• LANGGRAPH_API_URL - LangGraph server URL (default: http://localhost:2024)
• LANGGRAPH_ASSISTANT_ID - Graph ID (default: reader_assistant)

Frontend (frontend/.env)

• VITE_API_URL - Backend API URL (default: http://localhost:8000)

Development

See individual README files in each directory for detailed development instructions:

• Frontend README
• Backend README
• Agent README

# / frontend
git submodule update --init --recursive
npm run dev


# /agent
pip install -e . "langgraph-cli[inmem]"
langgraph dev --no-browser


# /backend
pip install -e .
uvicorn src.main:app --reload --port 8000