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    <title>LlamaIndex on The Learning Loop</title>
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      <title>Ask your WhatsApp: build a private RAG with LlamaIndex</title>
      <link>https://blog.juzam.pro/posts/2025-09-05/zaprag/</link>
      <pubDate>Fri, 05 Sep 2025 13:09:00 -0400</pubDate>
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      <description>&lt;h2 id=&#34;why-build-a-whatsapp-rag&#34;&gt;Why build a WhatsApp RAG?&lt;/h2&gt;
&lt;p&gt;I have a very active group chat with my friends on WhatsApp. At the time of
writing, it is a bit over half a million messages. Since LLMs became a thing, I
always wondered how I could use this data for something useful—or at the very
least, prank my friends.&lt;/p&gt;
&lt;p&gt;Last year I tried a few different approaches to fine tune a model using the chat
data, but it didn&amp;rsquo;t work all that well. Fine‑tuning a model on commodity
hardware is a challenge in itself and the results were underwhelming. So I
dropped that idea for a while. While going through the material for the
&lt;a href=&#34;https://huggingface.co/learn/agents-course/unit2/llama-index/components&#34;&gt;HuggingFace Agents Course&lt;/a&gt;
though, it became very clear that RAG (Retrieval Augmented Generation) would be
a perfect fit for what I was trying to do.&lt;/p&gt;</description>
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