From b2b9dd008cf1c2fdb8147f19cee4adf0ce8bb153 Mon Sep 17 00:00:00 2001 From: Paul Buetow Date: Wed, 24 Dec 2025 10:52:19 +0200 Subject: Update content for html --- about/resources.html | 206 ++++++++++----------- .../2025-12-24-x-rag-observability-hackathon.html | 4 +- gemfeed/atom.xml | 10 +- index.html | 2 +- uptime-stats.html | 2 +- 5 files changed, 113 insertions(+), 111 deletions(-) diff --git a/about/resources.html b/about/resources.html index 4bc96ee0..7c33d56d 100644 --- a/about/resources.html +++ b/about/resources.html @@ -50,112 +50,112 @@ In random order:


Technical references



I didn't read them from the beginning to the end, but I am using them to look up things. The books are in random order:


Self-development and soft-skills books



In random order:


Here are notes of mine for some of the books

@@ -164,20 +164,20 @@ Some of these were in-person with exams; others were online learning lectures only. In random order:


@@ -187,8 +187,8 @@

Podcasts



@@ -197,32 +197,32 @@ In random order:


Podcasts I liked



I liked them but am not listening to them anymore. The podcasts have either "finished" (no more episodes) or I stopped listening to them due to time constraints or a shift in my interests.


Newsletters I like


@@ -230,28 +230,28 @@ This is a mix of tech and non-tech newsletters I am subscribed to. In random order:


Magazines I like(d)



This is a mix of tech I like(d). I may not be a current subscriber, but now and then, I buy an issue. In random order:


Formal education



diff --git a/gemfeed/2025-12-24-x-rag-observability-hackathon.html b/gemfeed/2025-12-24-x-rag-observability-hackathon.html index 81992426..d3c42ced 100644 --- a/gemfeed/2025-12-24-x-rag-observability-hackathon.html +++ b/gemfeed/2025-12-24-x-rag-observability-hackathon.html @@ -15,7 +15,7 @@
Published at 2025-12-24T09:45:29+02:00

-This blog post describes my hackathon efforts adding observability to X-RAG, a distributed Retrieval-Augmented Generation (RAG) platform built by my brother Florian. I especially made time available over the weekend to join his 3-day hackathon (attending 2 days) with the goal of instrumenting his existing distributed system with observability. What started as "let's add some metrics" turned into a comprehensive implementation of the three pillars of observability: tracing, metrics, and logs.
+This blog post describes my hackathon efforts adding observability to X-RAG, the extensible Retrieval-Augmented Generation (RAG) platform built by my brother Florian. I especially made time available over the weekend to join his 3-day hackathon (attending 2 days) with the goal of instrumenting his existing distributed system with observability. What started as "let's add some metrics" turned into a comprehensive implementation of the three pillars of observability: tracing, metrics, and logs.

X-RAG source code on GitHub

@@ -62,7 +62,7 @@

What is X-RAG?



-X-RAG is the extendendible RAG (Retrieval-Augmented Generation) platform running on Kubernetes. The idea behind RAG is simple: instead of asking an LLM to answer questions from its training data alone, you first retrieve relevant documents from your own knowledge base, then feed those documents to the LLM as context. The LLM synthesises an answer grounded in your actual content—reducing hallucinations and enabling answers about private or recent information the model was never trained on.
+X-RAG is the extensible RAG (Retrieval-Augmented Generation) platform running on Kubernetes. The idea behind RAG is simple: instead of asking an LLM to answer questions from its training data alone, you first retrieve relevant documents from your own knowledge base, then feed those documents to the LLM as context. The LLM synthesises an answer grounded in your actual content—reducing hallucinations and enabling answers about private or recent information the model was never trained on.

X-RAG handles the full pipeline: ingest documents, chunk them into searchable pieces, generate vector embeddings, store them in a vector database, and at query time, retrieve relevant chunks and pass them to an LLM for answer generation. The system supports both local LLMs (Florian runs his on a beefy desktop) and cloud APIs like OpenAI. I configured an OpenAI API key since my laptop's CPU and GPU aren't fast enough for decent local inference.

diff --git a/gemfeed/atom.xml b/gemfeed/atom.xml index b7d829a8..b24e19bd 100644 --- a/gemfeed/atom.xml +++ b/gemfeed/atom.xml @@ -1,6 +1,6 @@ - 2025-12-24T09:45:29+02:00 + 2025-12-24T10:50:53+02:00 foo.zone feed To be in the .zone! @@ -15,12 +15,14 @@ Paul Buetow aka snonux paul@dev.buetow.org - This blog post describes my hackathon efforts adding observability to X-RAG, a distributed Retrieval-Augmented Generation (RAG) platform built by my brother Florian. I especially made time available over the weekend to join his 3-day hackathon (attending 2 days) with the goal of instrumenting his existing distributed system with observability. What started as 'let's add some metrics' turned into a comprehensive implementation of the three pillars of observability: tracing, metrics, and logs. + This blog post describes my hackathon efforts adding observability to X-RAG, the extensible Retrieval-Augmented Generation (RAG) platform built by my brother Florian. I especially made time available over the weekend to join his 3-day hackathon (attending 2 days) with the goal of instrumenting his existing distributed system with observability. What started as 'let's add some metrics' turned into a comprehensive implementation of the three pillars of observability: tracing, metrics, and logs.

X-RAG Observability Hackathon



-This blog post describes my hackathon efforts adding observability to X-RAG, a distributed Retrieval-Augmented Generation (RAG) platform built by my brother Florian. I especially made time available over the weekend to join his 3-day hackathon (attending 2 days) with the goal of instrumenting his existing distributed system with observability. What started as "let's add some metrics" turned into a comprehensive implementation of the three pillars of observability: tracing, metrics, and logs.
+Published at 2025-12-24T09:45:29+02:00
+
+This blog post describes my hackathon efforts adding observability to X-RAG, the extensible Retrieval-Augmented Generation (RAG) platform built by my brother Florian. I especially made time available over the weekend to join his 3-day hackathon (attending 2 days) with the goal of instrumenting his existing distributed system with observability. What started as "let's add some metrics" turned into a comprehensive implementation of the three pillars of observability: tracing, metrics, and logs.

X-RAG source code on GitHub

@@ -67,7 +69,7 @@

What is X-RAG?



-X-RAG is the extendendible RAG (Retrieval-Augmented Generation) platform running on Kubernetes. The idea behind RAG is simple: instead of asking an LLM to answer questions from its training data alone, you first retrieve relevant documents from your own knowledge base, then feed those documents to the LLM as context. The LLM synthesises an answer grounded in your actual content—reducing hallucinations and enabling answers about private or recent information the model was never trained on.
+X-RAG is the extensible RAG (Retrieval-Augmented Generation) platform running on Kubernetes. The idea behind RAG is simple: instead of asking an LLM to answer questions from its training data alone, you first retrieve relevant documents from your own knowledge base, then feed those documents to the LLM as context. The LLM synthesises an answer grounded in your actual content—reducing hallucinations and enabling answers about private or recent information the model was never trained on.

X-RAG handles the full pipeline: ingest documents, chunk them into searchable pieces, generate vector embeddings, store them in a vector database, and at query time, retrieve relevant chunks and pass them to an LLM for answer generation. The system supports both local LLMs (Florian runs his on a beefy desktop) and cloud APIs like OpenAI. I configured an OpenAI API key since my laptop's CPU and GPU aren't fast enough for decent local inference.

diff --git a/index.html b/index.html index bd9045c0..7cb71c12 100644 --- a/index.html +++ b/index.html @@ -13,7 +13,7 @@

Hello!



-This site was generated at 2025-12-24T09:45:29+02:00 by Gemtexter
+This site was generated at 2025-12-24T10:50:53+02:00 by Gemtexter

Welcome to the foo.zone!

diff --git a/uptime-stats.html b/uptime-stats.html index bcb75083..c45e7af1 100644 --- a/uptime-stats.html +++ b/uptime-stats.html @@ -13,7 +13,7 @@

My machine uptime stats



-This site was last updated at 2025-12-24T09:45:29+02:00
+This site was last updated at 2025-12-24T10:50:53+02:00

The following stats were collected via uptimed on all of my personal computers over many years and the output was generated by guprecords, the global uptime records stats analyser of mine.

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