雜談：到底要怎麼使用RAGFlow呢？ / TALK: RAGFlow Drained All My Resources

由於這次RAGFlow看起來又無法順利完成任務了，我還是來記錄一下目前的狀況吧。

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.

LLL開發平臺「畢昇」實測：令人驚豔的溯源定位功能 / LLL 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.

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  

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.

RAG應用方案：SeaSalt.AI的SeaMeet、SeaChat / RAG Application Solutions: SeaSalt.AI's SeaMeet and SeaChat

我最近試用了SeaSalt公司底下的SeaMeet跟SeaChat，前者可以自動記錄並摘要 Google Meet會議內容，後者則是簡單建立聊天機器人。這篇就是我報告投影片的彙整，供大家參考。

如何用Felo AI搜尋特定網站的內容 / How to Search Specific Website Content Using Felo AI

用關鍵字檢索站內資訊時，你總是看到大量分散的網頁，不知道怎麽整合最需要的資料嗎？這篇教你用Felo Search來建立站內的「問答機器人」！

Are you tired of keyword searches returning tons of scattered web pages, making it difficult to consolidate the information you need? This post will teach you how to use Felo Search to create an internal "Q&A chatbot"!

雜談：是時候該來處理一下Dify的問題了 / TALK: It's Time to Address the Issues with Dify

在「自行架設大型語言模式應用程式：Dify」這篇裡面，我用Dify在筆電架設了可客製化、具備RAG的大型語言模型應用程式。但這段期間用下來還是遭遇了很多問題。以下就稍微列舉一下我遭遇的狀況。

自行架設大型語言模式應用程式：Dify / Self-Hosting a Large Language Model Application: Dify

Coze開始收費之後，Dify會是更好的替代方案嗎？事情原來沒有我自己想象中的這麼簡單！

When Coze began to charge fees, what is the next solution for Large Language Model (LLM) application? Will Dify be a better alternative? The actual situation is not as simple as I had imagined!

資訊檢索的AI革新：從資訊檢索到檢索增強生成 / The AI Revolution in Information Retrieval: From Information Retrieval to Retrieval-Augmented Generation

2024年7月我在中華民國圖書館學會於政治大學舉行的講習課程中，演講「資訊檢索的AI革新：從資訊檢索到檢索增強生成」。以下是投影片跟相關內容的連結。

In July 2024, I will give a lecture titled "AI Innovation in Information Retrieval: From Information Retrieval to Enhanced Generative Retrieval" during the seminar course held by the Library Association of the Republic of China at National Chengchi University. Below is the link to the slides and related content.

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