pulipulichen

看看網頁版全文 ⇨ 雜談：ComfyUI很好用，但結果跟WebUI不一樣 : ComfyUI Is User-Friendly, But Results Differ From WebUI

https://blog.pulipuli.info/2025/01/comfyui-is-userfriendly-but-results-differ-from-webui.html

繼上次把Forge裝起來後，我還是覺得生圖的方式太沒效率了，所以轉向尋求其他工具。

這次嘗試的是Dify跟ComfyUI的結合。

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pulipulichen

看看網頁版全文 ⇨ 用Felo AI對「布丁布丁吃什麼？」提問吧！ : Ask "What does Pulipuli eat?" with Felo AI!

https://blog.pulipuli.info/2025/03/ask-what-does-pulipuli-eat-with-felo-ai.html

自從「布丁布丁吃什麼？」改用Felo AI作為站內的搜尋引擎之後已經一段時間了。

這對部落格的使用帶來什麼影響呢？讓我們一起來看看吧。

Since "Pulipuli's Blog" switched to using Felo AI as its internal search engine, some time has passed. What impact has this had on the blog's usage? Let's take a look.。

pulipulichen

看看網頁版全文 ⇨ 雜談：期盼了三年的巧味豬腳便當 : Long-Awaited Chiao Wei Pork Bento

https://blog.pulipuli.info/2025/03/longawaited-chiao-wei-pork-bento.html

天下第一攤的手作便當，依然十分美味。

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# 木新市場的在地美食 / Local food in Muxin Market。

pulipulichen

看看網頁版全文 ⇨ Python自然語言處理應用：命名實體識別與情緒分析 : Python Natural Language Processing Applications: Named Entity Recognition and Sentiment Analysis

https://blog.pulipuli.info/2025/03/python-natural-language-processing-applications-named-entity-recognition-and-sentiment-analysis.html

儘管大型語言模型的盛行讓大家瞭解到AI分析文字的能力，但直接以命名實體識別和情緒分析來處理文本的做法，在具有特定目標的研究報告裡仍扮演著重要的角色。

這篇就讓從我們從學習Python的使用，一步一步踏入命名實體識別和情緒分析的領域吧。

Although the prevalence of large language models has made people aware of AI's ability to analyze text, direct processing of text using Named Entity Recognition (NER) and Sentiment Analysis (SA) still plays a vital role in research reports with specific objectives. This article will guide us through the process of learning Python, step by step, to delve into the realm of Named Entity Recognition and sentiment analysis.。

pulipulichen

看看網頁版全文 ⇨ 雜談：到底要怎麼使用RAGFlow呢？ : TALK: RAGFlow Drained All My Resources

https://blog.pulipuli.info/2025/03/talk-ragflow-drained-all-my-resources.html

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。

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# 專注做好RAG的RAGFlow / RAGFlow: Focusing on RAG。

pulipulichen

看看網頁版全文 ⇨ 讓Dify使用自己管理的搜尋引擎：SearXNG : Let Dify Use My Self-Hosting Search Engine: SearXNG

https://blog.pulipuli.info/2024/12/let-dify-use-my-selfhosting-search-engine-searxng.html

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.。

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pulipulichen

看看網頁版全文 ⇨ 雜談：時常脫落的電燈泡 : TALK: Lightbulbs That Frequently Fall Out

https://blog.pulipuli.info/2025/03/talklightbulbs-that-frequently-fall-out.html

今天把電燈鎖緊，它亮了起來。

但過一段時間，它又鬆脫了。

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pulipulichen

看看網頁版全文 ⇨ 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

https://blog.pulipuli.info/2025/03/aiimagegenerationineducationfromlearningtodrawtoteachingaitodraw.html

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.。

pulipulichen

看看網頁版全文 ⇨ 雜談：弱電箱換上了MikroTik路由器 : TALK: I Placed a MikroTik Router in the Low-Voltage Wiring Box

https://blog.pulipuli.info/2025/01/talki-placed-a-mikrotik-router-in-the-lowvoltage-wiring-box.html

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？。

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pulipulichen

看看網頁版全文 ⇨ 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

https://blog.pulipuli.info/2025/02/lll-development-platform-bishen-hands-on-impressive-source-locating-function.html

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.。

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