讓Dify使用自己管理的搜尋引擎：SearXNG / Let Dify Use My Self-Hosting Search Engine: SearXNG

我在「自行架設大型語言模式應用程式：Dify」這篇講到我用SerpAPI作為Dify的搜尋引擎，但除了使用別人提供的API之外，我們也可以用SearXNG自行架設客製化的搜尋引擎，並將它跟Dify結合一起使用。

In the article "Self-Hosting a Large Language Model Application: Dify," I mentioned using SerpAPI as the search engine for Dify. However, besides using third-party APIs, we can also utilize SearXNG to set up a customized search engine and integrate it with Dify.

雜談：時常脫落的電燈泡 / TALK: Lightbulbs That Frequently Fall Out

今天把電燈鎖緊，它亮了起來。但過一段時間，它又鬆脫了。

AI繪圖教學投影片：AI繪圖教學 x 教AI學習繪圖 / AI Image Generation in Education: From Learning to Draw to Teaching AI to Draw

為了讓大家瞭解如何使用提示詞來進行AI繪圖，本次教學以Kera AI為繪圖平台，一步一步帶領大家從簡單的提示詞、提示詞的變化，到使用圖片來引導繪製圖片。最後則是介紹更進階的控制圖片技巧，希望成為大家踏入AI繪圖領域的敲門磚。

To help everyone understand how to use prompts for AI art generation, this tutorial uses Kera AI as the drawing platform and will guide you step-by-step from simple prompts, variations of prompts, to using images as references. Finally, we will introduce more advanced image control techniques, hoping to serve as a stepping stone for everyone entering the field of AI art.

Short URL: https://l.pulipuli.info/24/hsc

雜談：弱電箱換上了MikroTik路由器 / TALK: I Placed a MikroTik Router in the Low-Voltage Wiring Box

由於放在弱電箱裡面的無線基地臺一直當機，這次索性購買了MikroTik路由器RB450Gx4來用用看。這款號稱最適合放在弱電箱裡面的路由器，究竟會是如何呢？

LLM開發平臺「畢昇」實測：令人驚豔的溯源定位功能 / LLM Development Platform "BISHEN" Hands-On: Impressive Source Locating Function

雖然大家都知道RAG可以將檢索結果交給大型語言模型回答，不過到底交給大型語言模型的是那些檢索結果？這些檢索結果又對應到那些文件？LLM開發平臺「畢昇」在檢索功能漂亮地解決了上述的問題，應可成為RAG應用中值得參考的標杆。

While everyone knows that RAG can submit retrieval results to large language models (LLMs), what exactly are those retrieval results submitted to LLMs? And which documents do these retrieval results correspond to? The LLM development platform, BISHENG, elegantly addresses these questions in its retrieval function and can serve as a valuable benchmark for RAG applications.

雜談：課程網頁的變遷 / TALK: Changes in Course Web Pages

我的課程網頁從Google Doc、Google Doc網頁、Google Doc Publisher，到現在終於進入到Google Sites了！這篇就來講講這段期間我設置課程網頁方案的演進吧。

演講投影片：大型語言模型在工業領域的潛力 / Slide: The Potential of Large Language Models in Industrial Fields

大型語言模型(Large Language Model)成為AI浪潮之後下一個新的寵兒，它彷彿真人般的對談和創造力的發想對研究和教育上帶來了無數啟發。但是大型語言模型在要求精確的工業領域裡面，究竟可以扮演什麼角色呢？本次演講先講述工業5.0發展中對於大型語言模型的需求，再來講述工業領域應用大型語言模型的實例，最後介紹大型語言模型和檢索生成增強的相關技術作為結尾。如果你也想在產業應用大型語言模型的話，不妨先看看這份投影片，瞭解一下現況吧。

Large Language Models (LLMs) have become the next big thing in the wake of the AI wave, offering human-like conversation and creative brainstorming that have inspired countless research and educational endeavors.  But what role can LLMs play in demanding industrial fields that require precision? This presentation will first discuss the need for LLMs in the development of Industry 5.0, followed by examples of LLM applications in industrial settings. Finally, it will conclude with an introduction to related technologies like Retrieval-Augmented Generation. If you are also interested in applying LLMs in industry, take a look at this presentation to understand the current landscape.

Short URL: https://l.pulipuli.info/24/nkust  

RAG簡介投影片：現況、原理、發展 / RAG Introduction Slides: Current Status, Mechanisms, and Development

這份投影片對檢索生成增強(Retrieval-Augmented Generation, RAG)的觀念作一個容易理解的介紹，也是「資訊檢索的AI革新：從資訊檢索到檢索增強生成」這篇的簡化版本。一般說到AI大家都會想到創造力、彷彿真人的表現，但RAG本質上更接近資訊檢索的問題。把它當作資料庫就很容易理解RAG的用途了。

This presentation provides an accessible introduction to the concept of Retrieval Augmented Generation (RAG), and is a simplified version of "The AI Revolution in Information Retrieval: From Information Retrieval to Retrieval-Augmented Generation". When people talk about AI, they often think of creativity and human-like performance, but RAG is essentially closer to the problems of information retrieval. Thinking of it as a database makes it easier to understand the purpose of RAG.

Fixed Short URL: https://l.pulipuli.info/24/nccu/rag 

希希助教的情人巧克力會送給最認真的同學喔！ / TA. Sissi's Valentine's Day Chocolates Will Go to the Most Hardworking Student!

你就是那位認真的同學嗎？

雜談：我可以只要RAG的「R」嗎？ / TALK: Can I Just Have the “R” in RAG?

很多人以為RAG可以取代搜尋引擎，但其實很多人要的功能只有「能用自然語言檢索」而已。

RAG應用方案：Google NotebookLM / RAG Application Solutions: Google NotebookLM

Google NotebookLM已經成為使用RAG的最基本入門產品了。它大幅拉高了RAG的競爭門檻。沒有做的比Google NotebookLM好的話，都沒資格出來賣錢了。這篇是我在介紹Google NotebookLM的投影片，供大家參考。

Google NotebookLM has become the most basic entry-level product for using RAG. It has significantly raised the competitive bar for RAG.  If it's not better than Google NotebookLM, it's not worth selling. These are my slides introducing Google NotebookLM for your reference.

公視地方新聞資料集 / PTS NEWS Local News Dataset

最近我因為研究需求蒐集了公視新聞網地方新聞的一些內容，並把資料整理表格資料集，提供給有需要的人使用。

Recently, for my research, I collected local news content from the PTS News website and organized the data into a tabular dataset, making it available for anyone who needs it.

只用CPU跑「小型」語言模型可行嗎？ / Is Running "Small" Language Models on CPUs Only Feasible?

很多人都說跑大型語言模型需要很高級的GPU，其實相對於門檻較高的大型語言模型，小型語言模型也一直在如火如荼地發展。最近我嘗試用12核CPU跟32GB的RAM來跑Gemma2:2B，意外地很順利呢。

Many people say that running large language models requires high-end GPUs. However, relative to the higher barrier to entry of large language models, small language models have also been developing rapidly. Recently, I experimented with running Gemma2:2B using a 12-core CPU and 32GB of RAM, and it went surprisingly smoothly.