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    <title>LangChain on ByF (BaiFan) · Daily Deep Think</title>
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      <title>The Classifier Is the Savior Again</title>
      <link>https://blog.baifan.site/en/the-classifier-returns/</link>
      <pubDate>Sun, 20 Sep 2026 13:00:00 +0800</pubDate>
      <author>blog@baifan.site (ByF (BaiFan))</author>
      <guid>https://blog.baifan.site/en/the-classifier-returns/</guid>
      <description>&lt;p&gt;In any enterprise tech team that claims to be “fully AI-powered,” the bill nobody wants to look at closely is usually not production inference — it’s the &lt;strong&gt;evaluation pipelines&lt;/strong&gt; we run to deceive ourselves.&lt;/p&gt;&#xA;&lt;!-- more --&gt;&#xA;&lt;p&gt;Over the past three years, the biggest, most sacred, and least defensible totem in the enterprise stack has been the “private enterprise knowledge base” — first repackaged as RAG, then upgraded again as GraphRAG with a knowledge-graph label. Every architect, when drawing the final architecture diagram for the CTO, dutifully adds the last box: “Closed-loop evaluation and continuous alignment.”&lt;/p&gt;</description>
      
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      <title>RAG Complete Guide: Build a Local RAG System from Scratch</title>
      <link>https://blog.baifan.site/en/rag-system-complete-guide-langchain-ollama-pgvector/</link>
      <pubDate>Wed, 27 Aug 2025 14:00:00 +0800</pubDate>
      <author>blog@baifan.site (ByF (BaiFan))</author>
      <guid>https://blog.baifan.site/en/rag-system-complete-guide-langchain-ollama-pgvector/</guid>
      <description>&lt;h1 class=&#34;relative group&#34;&gt;Building a Local RAG with LangChain + Ollama + pgvector: A Complete Hands-On Walkthrough from 0 to 1 (with uv Dependency Management and an Interview Guide)&#xA;    &lt;div id=&#34;building-a-local-rag-with-langchain--ollama--pgvector-a-complete-hands-on-walkthrough-from-0-to-1-with-uv-dependency-management-and-an-interview-guide&#34; class=&#34;anchor&#34;&gt;&lt;/div&gt;&#xA;    &#xA;    &lt;span&#xA;        class=&#34;absolute top-0 w-6 transition-opacity opacity-0 -start-6 not-prose group-hover:opacity-100 select-none&#34;&gt;&#xA;        &lt;a class=&#34;text-primary-300 dark:text-neutral-700 !no-underline&#34; href=&#34;#building-a-local-rag-with-langchain--ollama--pgvector-a-complete-hands-on-walkthrough-from-0-to-1-with-uv-dependency-management-and-an-interview-guide&#34; aria-label=&#34;Anchor&#34;&gt;#&lt;/a&gt;&#xA;    &lt;/span&gt;&#xA;    &#xA;&lt;/h1&gt;&#xA;&lt;blockquote&gt;&lt;p&gt;This post is a directly actionable document. Follow it top to bottom and you will build a local RAG (retrieval-augmented generation) system from scratch and understand the key concepts and code. All core scripts come with comments to make learning and interview review easier.&lt;/p&gt;</description>
      
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