Skip to main content

LLM tools for summarizing web content into structured Obsidian notes.

Project description

cryptic

GitHub Actions Workflow Status Docker Image Version PyPI - Version License

The Cryptics have a fearful reputation, and yet this one – the first specimen I’ve ever seen – seems . . . ‘Imbecilic?’ -- Words of Radiance

Cryptic runs a persistent service that watches directories for incoming markdown files with some basic frontmatter and a body containing the raw HTML content of a website. The content is shipped off to an LLM provider (any OpenAI compatible endpoint), categorized, and summarized, with different summarizations and metadata extraction depending on the category. It uses structured output for reliability, and the entire prompt (other than the system prompt) is defined in the pydantic models. The results are then written out to finalized Markdown in configured output directories.

It's designed to pair with Obsidian Headless Sync and Obsidian Web Clipper. Web Clipper can do LLM processing out of the box, but the output formatting is somewhat limiting; an independent service allows much more flexibility in prompt design and output constraints.

I've included a basic webclipper template for reference in this repository.

Installation

From PyPI:

pip install cryptic-md

From source, clone and run:

poetry install

Set OPENAI_API_KEY, and optionally OPENAI_BASE_URL, in the environment or in a .env file in the project root.

Configuration

Create ~/.config/cryptic/config.yaml:

openai:
  models:
    - gpt-5.4-mini
  default_model: gpt-5.4-mini
  default_reasoning: medium

service:
  vaults:
    personal:
      input_dir: ~/Obsidian/Personal/cryptic-staging
      output_dir: ~/Obsidian/Personal/cryptic-processed
      originals_dir: ~/Obsidian/cryptic-originals
  max_concurrent: 3
  max_tries: 3
  pickup_delay_seconds: 3.0

Override the config path per-invocation with --config /path/to/config.yaml.

Usage

Process a single note in place:

cryptic process note --note path/to/note.md

Run the service against the configured directories:

cryptic service

Drain the input directory once and exit (useful for batch runs):

cryptic service --once

Common flags available on both commands:

  • --model NAME — pick a model from openai.models.
  • --reasoning {low,medium,high,xhigh} — set reasoning effort.
  • --config PATH — use an alternate config file.

Docker

Pre-built images are published to Docker Hub at camillescott/cryptic. The included compose.yaml is the simplest way to run the service:

# Provider API key
export OPENAI_API_KEY=sk-...
# To use a different provider endpoint
export OPENAI_BASE_URL=my.openwebui.local/api
docker compose up -d

It bind-mounts ./vaults/vaults (your Obsidian tree) and ./config/config (a directory containing config.yaml). Paths inside config.yaml must be rooted at /vaults, for example /vaults/personal/cryptic-staging.

To build the image locally instead of pulling:

docker build -t cryptic .

inotify works across bind mounts on Linux hosts. On Docker Desktop for macOS or Windows, host filesystem events don't propagate into the container.


Portions of this project's code have been written with agentic coding tools.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

cryptic_md-1.2.0.tar.gz (17.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

cryptic_md-1.2.0-py3-none-any.whl (20.2 kB view details)

Uploaded Python 3

File details

Details for the file cryptic_md-1.2.0.tar.gz.

File metadata

  • Download URL: cryptic_md-1.2.0.tar.gz
  • Upload date:
  • Size: 17.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.4.1 CPython/3.12.1 Linux/6.17.0-1013-azure

File hashes

Hashes for cryptic_md-1.2.0.tar.gz
Algorithm Hash digest
SHA256 ad3258e6e8a65fabcf7776c77a96482e640f3781917a137962faadd50398bb98
MD5 39bfe7850cd7f45efbc090cb4774e285
BLAKE2b-256 8572e58f59ccd4271bea1ceccb85d647543d3bf1aff6c41ef827531ad1248cb1

See more details on using hashes here.

File details

Details for the file cryptic_md-1.2.0-py3-none-any.whl.

File metadata

  • Download URL: cryptic_md-1.2.0-py3-none-any.whl
  • Upload date:
  • Size: 20.2 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/2.4.1 CPython/3.12.1 Linux/6.17.0-1013-azure

File hashes

Hashes for cryptic_md-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 dd391135636b4963311185c340be64c43c9952852b4ed2859001ee54f6e0e973
MD5 6c9500f5674c9401361bb9678b98c920
BLAKE2b-256 013609c05ba914540430d3b5f0a1542688aba39e61dfcdff1b514e61b229c8fa

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page