epub2anki

Convert EPUB ebooks into Anki flashcards using Anthropic's Claude API.

Overview

epub2anki transforms your EPUB books into Anki decks (.apkg files). It parses the table of contents and internal book structure, divides the text into manageable chunks, and requests an LLM (Claude) to generate comprehensive and useful Anki flashcards.

Features

• Structural Parsing: Uses the EPUB's Table of Contents to intelligently split the book into coherent sections.
• LLM Flashcard Generation: Uses Anthropic's API to construct high-quality flashcards summarizing key concepts.
• Batch Processing: Can utilize Anthropic's Batch API for up to 50% cost savings on API calls.
• Resilient Coaching & Caching: Uses SQLite to cache generated notes, meaning if the process is interrupted, you won't be charged twice for previously processed sections!
• Direct Anki Export: Outputs a ready-to-import .apkg file.

Prerequisites

• Python 3.13+
• An Anthropic API Key

Installation

You can install epub2anki using pip or uv:

pip install epub2anki

Or using uv (recommended):

uv tool install epub2anki

Usage

Basic usage:

export ANTHROPIC_API_KEY="your-api-key-here"
epub2anki path/to/your/book.epub

Alternatively, you can pass the API key directly via the CLI:

epub2anki path/to/your/book.epub --api-key "your-api-key-here"

This will parse the EPUB, split it into chunks of ~50,000 characters, generate flashcards using the claude-haiku-4-5 model, and finally save a <book-name>.apkg file in the current working directory.

Advanced Usage & Batching

To save 50% on API costs, use the --batch flag. This will submit all generation requests to the Anthropic Batch API:

epub2anki path/to/your/book.epub --batch

Note: The Batch API operates asynchronously and takes 5 minutes to 24 hours to finish. epub2anki will submit the batch and return a Batch ID.

Once your batch is ready (you can check your Anthropic Console), run the script again using --fetch-batch:

epub2anki path/to/your/book.epub --fetch-batch msgbat_XXXXXXX

This will retrieve the completed responses from Anthropic, save them into the local cache, and generate your .apkg deck.

Command-Line Arguments

usage: epub2anki [-h] [--batch] [--fetch-batch FETCH_BATCH] [--deck-id DECK_ID]
                 [--chunk-size CHUNK_SIZE] [--model MODEL] [--retries RETRIES]
                 [--api-key API_KEY] [--db-path DB_PATH] [--output-path OUTPUT_PATH]
                 [--rate-max-requests RATE_MAX_REQUESTS] [--rate-max-input RATE_MAX_INPUT]
                 [--rate-max-output RATE_MAX_OUTPUT] [--rate-window RATE_WINDOW]
                 book_path

Generate Anki flashcards from EPUB books using an LLM.

positional arguments:
  book_path             Path to the EPUB book.

options:
  -h, --help            show this help message and exit
  --batch               Use Anthropic's async Batch API for 50% lower costs.
  --fetch-batch ID      Fetch an existing batch ID from Anthropic and build the deck.
  --deck-id DECK_ID     Unique integer ID for the Anki deck.
  --chunk-size SIZE     Maximum text size per LLM prompt (default: 50000).
  --model MODEL         Anthropic model (default: claude-haiku-4-5).
  --api-key KEY         Anthropic API key (overrides ANTHROPIC_API_KEY env var).
  --output-path PATH    Path where the .apkg file should be saved (default: <cwd>/<book_name>.apkg).

License

MIT License