npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2026 – Pkg Stats / Ryan Hefner

cook-extract

v0.0.1

Published

Structured data extraction CLI for generic PDF documents via LLMs

Readme

Cook Extract (cook-extract)

An automated CLI tool meant to securely scan, download, and extract structured data schemas from generic PDF documents hosted on Google Drive using LLMs (OpenAI or Cohere) and export the cleanly parsed results securely to a CSV file.

🚀 Features

  • Interactive Global CLI (cex): Easily run cex extract globally from any repository setup.
  • Unified Configuration: Use cex config to establish custom structural outputs natively mapped alongside your preferred AI fallback models.
  • Google Drive Integration: Quickly streams public folder links bypassing Auth friction setups seamlessly.
  • LLM-Powered Extraction:
    • Supports OpenAI (GPT-4o) and Cohere (Command R+).
    • Built-in concurrency control safely regulating LLM payload executions against aggressive rate limits.
  • Robust Exports: Generates cleaned CSV reports mapping to dynamic user-generated configurations securely.
  • Clean Workspace: Automatically manages and removes temporary download folders.

🛠️ Tech Stack

  • Runtime: Node.js (ESM)
  • Language: TypeScript
  • CLI Framework: Commander.js & Inquirer.js
  • Google APIs: googleapis & @google-cloud/local-auth
  • PDF Parsing: pdf-parse
  • LLM Clients: openai & cohere-ai
  • Utilities: p-limit, dotenv, cli-progress, csv-writer

📋 Prerequisites

  1. Google Drive Link:
    • Ensure the folders you want to scan are publicly accessible as "Anyone with the link can view".
  2. LLM API Keys:
    • Acquire an OpenAI or Cohere secure token directly from their platforms.

⚙️ Installation

# Install dependencies
npm install

# Link the package globally to enable the 'cex' command securely
npm run build
npm link

🔐 Configuration

Deploy the interactive configuration editor securely globally:

cex config

Configure your extraction schema fields alongside your selected LLM_PROVIDER natively bypassing legacy .env requirements cleanly!

📖 Usage

Run the core extractor straight from the terminal wherever you please:

cex extract
  1. Select Data Source: Default target points to Google Drive.
  2. Enter Drive Link: Provide the public shared folder URL.
  3. Choose Output Path: Defaults to ./results.csv.

The tool will seamlessly:

  • Download all contained PDFs directly parsing texts dynamically.
  • Interface with the LLM mapping structurally against your defined schema keys.
  • Write a clean CSV linking each row explicitly back to viewing URLs securely.