Authentik, Kubernetes and PG Admin

Authentik configuration should follow this link.

Convert all SVN repos into git

Here's a script to batch-convert a set of subversion repositories into a set of Git ones:

Install MinIO on TrueNas

An update of MinIO in June 2025 removed the admin console from the UI, leaving you only the command line. So, now you have to use the CLI (mc) to set things up like users, buckets ... This tutorial aims to provide a minimal set of instructions so you can install

Set Up MinIO Console on TrueNas

An update of MinIO in June 2025 removed the admin console from the UI, leaving you only the command line. Fortunately, a fork called minio-console restores this functionality. This is a tutorial on how to set up minio-console on TrueNAS if you have an existing MinIO instance (updated). Note: If

Logging in Rust

I need to record the logging from my application. According to this, rust can do logging via the log crate: use log::{info, warn}; pub fn example() { info!("Here's some info"); warn!("This is a warning!"); } In addition, you can use the env_logger

Connect MCP Server Developed in WLS to Claude

I'm developing a MCP server in WLS because I'm using WLS for development in general. I've installed Claude desktop to play around with it and I had trouble connecting my server. Short of moving the codebase to windows, this post describes what I did

Vibe Coding - Add a field to a Qdrant collection

I have created a Qdrant collection off a repository of mine and I had the following payload fields: * file_name - the source code file name (path actually) * branch - the git repository branch that I have indexed * repository_name - the git repository name * chunk - the text chunk

Chunk and index text

This is part of the Use RAG with Continue.dev series. Once we have the dependencies installed, we can start filling up the vector db. Set up First part, is to create the LanceDB database and embedding model: from lancedb.embeddings import get_registry from lancedb import connect OLLAMA_HOST

Prepare Ollama and LanceDB

This is part of the Use RAG with Continue.dev series. Prerequisites I kept in line with the general prerequisites for the previous steps (python 3, uv for package management). In addition, I will assume you have ollama installed. Check here for different installation methods. Setup Ollama Once Ollama is

Bitbucket - Scan a repository

Following the previous post, we need to get the list of files in the repository. This is similar with listing the contents of a directory, without having the possibility to do it in a recursive way. A call to the list files API will return a list containing both files

Bitbucket - Get Repository Information

In the previous post, we wrote the helper functions, which will allow us to get multi-page responses from the Bitbucket server. Now, we can use them to get various repository information. Prerequisites As in the previous post, we need the requests python package. Once we have that, we can initialise

Bitbucket - API Helper Functions

Get all pages Normally, Bitbucket list queries return a JSON. They are structured so all the data is under a values key. You get a bunch of other data, among which a flag isLastPage that tells you if the page you retrieved is the last one. I wrote below a

rag

Use Rag with continue.dev

continue.dev is a plugin system that is available for VS Code and IntelliJ products. It allows using the code base to answer AI questions, as well as custom RAG extensions, where you can index e.g. your proprietary repositories. The purpose of this exercise is to create an ollama-based

unifi

Updated the Ansible Unifi role

After moving my Unifi controller to a new VM, I kept updating its version. Recently, Ubiquiti release a new version (9.0.108 at the moment of writing), which has a bunch of changes. The ones I am concerned with are: 1. The name is changed from unifi-controller to unifi-network-application

rag

RAG Sample - 5: Bring it all Together

We have now all data available in the right places: 1. Select a Vector DB 2. Build a RAG System 3. Generate Schema-compliant Embeddings 4. Build embeddings and insert into DB I have indexed a research paper and can ask the system a question. The process is somewhat simple: 1.

movie

Movie review - The departed

I've seen this one as well. It's way better than the Bond movie described in the previous post. Given that is 5am, I'm just going to give it a 9/10. Lots of good actors, Nicholson is perfect for that crazed gangster role. The

kde

Magellan

A long time ago, I worked on developing Magellan, an outlook-like client for Linux/KDE. I worked on front-end and some backend stuff (until the back-end moved to CORBA that is). I also did the art (icons, gui...) for it. Here are some screenshots: The email interface supported POP3 and

kde

Text shadows in KDE

Long time ago, I wrote the original code for having text shadows on KDE's desktop. It was using a blur effect 😄 Here are some images from those days:

epso

About the E-tray

E-tray is used by EPSO now as a stop-gap for various competitions (First batch was the cycle for AD in 2015). It previously was part of the AST assessment centre. From EPSO: An e-tray exercise is a computer-based simulation of a real work situation and replicates an email inbox which

epso

A Strategy for the E-tray

First, some terminology: * CBT - Computer based test * Question - the big scenario with the three options * Option - The three items you need to evaluate (from -- to ++) The E-tray looks like a SJT, but has some major differences: * You need to remember that each option has its own

epso

Interview Skills and Competencies (generic)

Following skills and competencies are assessed generally in an interview. Interviews in the Assessment Center are usually a subset of these criteria, mapped on competences. Personal Effectiveness * Self-motivated – strong commitment to achieving challenging work goals * Strong energy levels * Resilient and works well under pressure * Perseveres when faced with difficulties * Reacts

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Tip: Memorise the Competences

Memorise the EPSO competencies via acronyms.

rag

RAG Sample - 4. Build Embeddings and Insert to DB

Building embeddings I followed two sources for embeddings: 1. Building an Agentic RAG locally with Milvus, Ollama and LangGraph and the associated code langgraph-rag-agent-local.ipynb 2. The "Build RAG with Milvus | Milvus Documentation" tutorial This is where I had my first surprise: Building embeddings is not necessarily a

rag

RAG Sample - 3. Generate Schema-compliant Embeddings

Until now, we've initialised the collection with a custom schema and built the capability to generate embeddings via Ollama. Now, we'll tie it all together. A sample to process We define a format for the document (based on the paperless-ngx API response): doc = { "id"