cecilemuller

How to setup Let's Encrypt for Nginx on Ubuntu 18.04 (including IPv6, HTTP/2 and A+ SLL rating)

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Virtual hosts

Let's say you want to host domains first.com and second.com.

Create folders for their files:

rbiswasfc

Quick Start

OpenRouter provides an OpenAI-compatible completion API to 0 models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using the OpenAI SDK

from openai import OpenAI

olafgeibig

Z.ai subscription with opencode

Now Z.ai has an official solution to use the package. See below.

Create a custom provider

First we need to create a custom provider for the Z.ai anthropic API. Follow the instructions for adding a custom provider to opencode.

• Name it zai-anthropic
• Enter your API-key

Configure the custom-provider

Edit opencode.json and add this:

karpathy

LLM Wiki

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.

The core idea

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.