一份完整的教程:给你自建的 Claude 聊天前端接上 NovelAI 画图能力,让模型可以在回复里任何位置插入多张图,而不是只能堆在末尾。
适用对象:自己跑前端 + 后端调 Claude CLI(或 SDK)做对话的人。
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| 20.000000, 9.782 | |
| 20.299999, 9.781 | |
| 20.600000, 9.779 | |
| 20.900000, 9.777 | |
| 21.200001, 9.776 | |
| 21.400000, 9.774 | |
| 21.799999, 9.771 | |
| 22.000000, 9.770 | |
| 22.400000, 9.766 | |
| 22.700001, 9.764 |
| // Stack - Array based implementation. | |
| // Creating a stack of integers. | |
| #include<stdio.h> | |
| #define MAX_SIZE 101 | |
| int A[MAX_SIZE]; // integer array to store the stack | |
| int top = -1; // variable to mark top of stack in array | |
| // Push operation to insert an element on top of stack. |
I have moved this over to the Tech Interview Cheat Sheet Repo and has been expanded and even has code challenges you can run and practice against!
\
| name | dj-library-organizer |
|---|---|
| description | Organize a DJ library (rekordbox or Serato) by sorting tracks into playlists or crates. Use this skill whenever someone asks to organize, sort, or categorize their rekordbox library, Serato library, DJ collection, or music playlists/crates — or mentions they have tracks that need sorting into genres, vibes, or folders. Also trigger when someone mentions rekordbox XML, Serato crates, DJ library management, playlist/crate organization for DJing, or wants to clean up their DJ music collection. Works with any genre set — the skill learns from the user's existing playlists/crates rather than assuming specific genres. |
| author | djhallaaaa |
You are an interactive DJ library organizer. You help DJs sort their tracks into playlists or crates by learning from their existing organization patterns. You support both rekordbox and Serato DJ.
| #ifndef DEMO_HARDWARE_ONLY | |
| #define DEMO_HARDWARE_ONLY 0 | |
| #endif | |
| #define WIN32_LEAN_AND_MEAN | |
| #include <windows.h> | |
| #include <dwmapi.h> | |
| #include <d3d11.h> | |
| #include <dxgi1_2.h> | |
| #include <stdio.h> |
| { | |
| "output": { | |
| "blocklist": [], | |
| "compressor#0": { | |
| "attack": 20.0, | |
| "boost-amount": 6.0, | |
| "boost-threshold": -72.0, | |
| "bypass": false, | |
| "dry": -80.01, | |
| "hpf-frequency": 10.0, |
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.
These are my installation-tricks and notes for running Linux on a 2021 Thinkpad P14s Gen2 with 11th gen Intel Core i7-1185G7. It should also be suitable for the Thinkpad T14 Gen2 with Intel as they are technically the same model.
Additionally you may find more AMD specific tips on the gist I've forked. I decided to keep this gist forked as I have used some of the tips they shared and because they inspired me to create my note in the first place.
Sadly there is no entry in the arch-wiki for Intel specific model, but some of the info from AMD one were useful for me. Other useful sources are mentioned in the document in their respective chapters.
Not everything in this doc may be 100% correct as I'm writing this note after having my PC set up and I might have forgotten some of the stuff. I will update it I ever decide to reinstall the OS on my PC.