I hereby claim:
- I am dalareo on github.
- I am dalareo (https://keybase.io/dalareo) on keybase.
- I have a public key ASB7gPeTXurHA5iSEPECxfjFxhGzT5ozeY3XiBItkFRXwAo
To claim this, I am signing this object:
| #!/bin/bash | |
| ################################################################################################ | |
| # Fully automated script to install Odoo and Odoo SaaS Tool (tested on a fresh Ubuntu 14.04 LTS) | |
| # * Install & configure last stable version of nginx | |
| # * Install & configure last stable version of postgresql | |
| # * Install & configure Odoo | |
| # * Configure automated backup of Odoo databases | |
| # * Optional: Install & configure Odoo SaaS Tool | |
| # * Optional: Background installation: $ nohup ./odoo_install.sh > nohup.log 2>&1 </dev/null & | |
| ################################################################################################ |
I hereby claim:
To claim this, I am signing this object:
| import requests | |
| import time | |
| # --- TUS CREDENCIALES --- | |
| APP_ID = "" | |
| TOKEN = "" | |
| # ----------------------- | |
| # Pega aquí la cadena gigante de IDs que copiaste del navegador | |
| raw_ids = "" |
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.