pdfalive 0.1.0

A Python library and CLI tool that uses LLMs to enhance PDF files

pdfalive

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A Python library and set of CLI tools to bring PDF files alive with the magic of LLMs.

Usage

To use the CLIs described below, you can install the python package (pip install pdfalive), or run the cli directly using uvx:

uvx pdfalive generate-toc input.pdf output.pdf

More detailed examples of the CLI sub-commands are provided below. You can also use --help on the main command-line and any of the sub-commands to get an idea of the different options supported.

generate-toc

Automatically generate clickable Table of Contents (e.g. using PDF bookmarks) for a PDF file by extracting features from the PDF and then calling an LLM to infer the pages and section names from these.

Example usage:

pdfalive generate-toc input.pdf output.pdf

By default we use the latest Anthropic Claude Sonnet available, but you can change this by setting the model as part of invocation:

pdfalive generate-toc --model-identifier 'claude-haiku-4-5' input.pdf output.pdf

Note that for using Anthropic models you'd want to set your api key via the environment variable ANTHROPIC_API_KEY. Similar mechanisms apply to OpenAI (OPENAI_API_KEY) and other vendors.

Development

We use uv to manage the library. To install locally can run e.g. with:

uv sync
uv pip install -e .

We use ruff for formatting and linting, mypy for static type checking, and pytest for running unit-tests. We also use pre-commit for ensuring high-quality commits.