#Quick Guide
sudo atsutil databases -remove
atsutil server -shutdown
atsutil server -ping
#Extended Guide from http://doc.extensis.com/Font-Management-in-OSX-Best-Practices-Guide.pdf
| $.fn.parsley.defaults = { | |
| // basic data-api overridable properties here.. | |
| inputs: 'input, textarea, select' // Default supported inputs. | |
| , excluded: 'input[type=hidden], :disabled' // Do not validate input[type=hidden] & :disabled. | |
| , trigger: false // $.Event() that will trigger validation. eg: keyup, change.. | |
| , animate: true // fade in / fade out error messages | |
| , animateDuration: 300 // fadein/fadout ms time | |
| , focus: 'first' // 'fist'|'last'|'none' which error field would have focus first on form validation | |
| , validationMinlength: 3 // If trigger validation specified, only if value.length > validationMinlength | |
| , successClass: 'has-success' // Class name on each valid input |
| #!/bin/bash | |
| chown -R rabbitmq:rabbitmq /data/log | |
| chown -R rabbitmq:rabbitmq /data/mnesia | |
| HOSTNAME=$(hostname) | |
| PID_FILE="/data/mnesia/rabbit\@$HOSTNAME.pid" | |
| function start() | |
| { |
| * { | |
| font-size: 12pt; | |
| font-family: monospace; | |
| font-weight: normal; | |
| font-style: normal; | |
| text-decoration: none; | |
| color: black; | |
| cursor: default; | |
| } |
#Quick Guide
sudo atsutil databases -remove
atsutil server -shutdown
atsutil server -ping
#Extended Guide from http://doc.extensis.com/Font-Management-in-OSX-Best-Practices-Guide.pdf
| # | |
| #DO droplet metadata intro + for DO-API | |
| # [https://www.digitalocean.com/community/tutorials/an-introduction-to-droplet-metadata#how-to-retrieve-droplet-metadata#digitalocean-api] | |
| # | |
| #intro to cloud-config scripting (source of following examples) | |
| # [https://www.digitalocean.com/community/tutorials/an-introduction-to-cloud-config-scripting] | |
| # | |
| #howto | |
| # [https://www.digitalocean.com/community/tutorials/how-to-use-cloud-config-for-your-initial-server-setup] | |
| # |
Set up a 3 node HA rancher cluster.
This will create and prep nodes for RKE. This uses the default vpc and subnets.
We create:
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.