RAD Studio 13 presentation in Ljubljana

Next week I'm presenting all that is shiny and new in RAD Studio 13 in Ljubljana. As the presentation will be in Slovenian language, so is the next of this post ...

Delphi and AI [9]: Guided writing

Some time ago, I tried using AI to write a blog post, but things didn’t go quite as planned. For my second attempt, I aimed to do better. I focused on a single engine—OpenAI—and used it in a more granular way. Instead of simply saying, “Write me an article about...,” I started with basic introductory questions, then asked it to write the article, and finally requested improvements where I felt the draft was lacking. The end result was quite satisfying.

This article is my analysis of that process. If you’re only interested in reading the transcript, you can find it here.

Integrating LLM engines in your Delphi app with Chatterbox

But the real changes happened under the hood.

I’ve refactored the codebase to fully separate the AI client logic from both the UI and the network layer. And what does that mean for you? It means you can now use the Chatterbox AI libraries directly in your own code.

Let me say that again, loud and clear:

You can now use Chatterbox AI libraries from your code!

To test this, I created a very basic demo called EngineDemo. And naturally, for this announcement, I had to explain how the demo uses the Chatterbox libraries.

Since this was a brand-new development that the AI had no prior knowledge of, I decided to revisit an experiment I mentioned in a previous post—one that was only partially successful. This time, I took a different approach. But more on that in the next post.

For now, take a look at what ChatGPT had to say on the topic. Just keep in mind: this wasn’t a simple “click and publish” process. ChatGPT and I had a long back-and-forth, and the result of that collaboration is the article below.

Delphi and AI [8]: Write me an article about ComputeCore

This was supposed to be an article comparing three major AI players in their ability to write technical articles. In preparation, however, I made some mistakes ... :(

When I prepared for the initial article, I asked them to fetch the data from https://github.com/gabr42/ComputeCore/blob/main/ComputeCore.pas and write about it. (See the end of this article for the initial query and results.) At that moment, however, that link was not public yet. All three AIs ignored that and happily wrote about the code they knew nothing about. It was only Claude that complained about the bad link but I missed that while checking the results. 

So I decided to rerun the experiment on all platforms. I started by asking the engines the following question: 

Can you accesss https://github.com/gabr42/ComputeCore/blob/main/ComputeCore.pas and provide an overview of the code in one paragraph?

This worked with ChatGPT but both Claude and Gemini complied that they cannot access the link. I had to rerun the query with the link to the raw file for the latter two to work:

Can you accesss https://raw.githubusercontent.com/gabr42/ComputeCore/refs/heads/main/ComputeCore.pas and provide an overview of the code in one paragraph?

Analyzing the answer shows that the answers were not done purely on the basis of the linked code. Both Claude and Gemini have included details that they got from my previous article on ComputeCode.

In the answers below I marked hallucinated misinformation with red and information that was obviously retreived from different sources with blue.

ComputeCore - A Simple Parallel Task Framework

Today, I want to talk about a small multithreading kernel (framework, library, or whatever you want to call it) that I've recently helped develop for the Spring4D project.

ComputeCore is a lightweight parallel processing framework for Delphi that lets you easily run CPU-intensive tasks across multiple threads. Its goals are straightforward: to run (possibly compute-heavy) tasks concurrently, allow tasks to spawn child tasks, and expose a very simple interface for the caller.

It will eventually be published as Spring.Threading, but until that happens, we can examine the almost-final version at https://github.com/gabr42/ComputeCore. In Spring4D, it will run the parallel implementation of the new sorting algorithm, but that doesn't mean it is only useful for one specific job! It is indeed a completely open (although intentionally simple) framework that can be used for your projects too.

[This article was written with the help of an AI. My next article will explain this decision and the writing process.]

Run your Delphi programs in a browser

Next Wednesday I'll be talking about Delphi and TMS Web Core in Ljubljana. As the presentation will be in Slovenian language, so is the rest of this post.

Delphi and AI [7]: How good are local DeepSeek models (for Delphi)

Due to potential privacy concerns with DeepSeek servers (we’re unsure if the data sent over the paid API is kept private), I looked into some smaller DeepSeek models available on the Ollama.com site. These models use less complex AI with fewer parameters than the online version, but they might still be good enough for an average Delphi programmer. We’ll see.

For testing, I used a powerful RTX 4090 card with 24 GB of memory. If your graphics card has less memory, your selection of useful models will be more limited.

I asked all models the same two questions: one on a general programming topic and another specific to the FireMonkey platform. The first question was:

"I have a multiline string containing newline ASCII characters (TMemo.Text). I want to change it to a single-line string with only printable ASCII characters. I could do that with BASE64 encoding, for example. I would, however, like to keep the text as much readable as possible by "encoding" only non-printable characters. Is there a simple way to do that?"

You can check Codellama’s response in an older post (Codellama being the only local model I had tested so far): Delphi and AI [5]: Encoding Multi-line Strings.

Last week, I asked the same question to the online DeepSeek-Reasoning model. Check the answers in this post: Delphi and AI [6]: DeepSeek-Reasoning Model.

The second question was:

"How can I copy text to clipboard in a Delphi Firemonkey application?"

Read here for Codellama’s response: Delphi and AI [4]: Device-ndependent clipboard.

The answer from the online DeepSeek-Reasoning model can be found at the end of this post.

Let’s see how the models are performing! As always, full logs are available on GitHub.

Chatterbox v0.2 - Now with DeepSeek support!

As I’m writing this, a new Chatterbox release is available on GitHub. As with the initial release, you can either download the source and recompile it or grab an executable (Windows, 32-bit) from the release.

(If you have never heard of Chatterbox, you should probably read the initial release article.)

The biggest change since v0.1 is support for DeepSeek AI.

Delphi and AI[6]: DeepSeek reasoning model (Encoding a multi-line string)

An interesting AI has just appeared on my radar - DeepSeek. It exposes a "normal" chat model deepseek-chat and a "reasoning" (that's the interesting part) model deepseek-reasoning. While working on DeepSeek support for the Chatterbox (more on that in few days) I thought it would be interesting to ask the "reasoning" model the "multi-line string encoding" question that every other AI has failed.

Warning: DeepSeek privacy policy states: "When you use our Services, we may collect your text or audio input, prompt, uploaded files, feedback, chat history, or other content that you provide to our model and Services." Don't send any private or proprietary information in the chat!

The log is provided on GitHub.

Just as a reminder, the question was:

"I have a multiline string containing newline ASCII characters (TMemo.Text). I want to change it to a single-line string with only printable ASCII characters. I could do that with BASE64 encoding, for example. I would, however, like to keep the text as much readable as possible by "encoding" only non-printable characters. Is there a simple way to do that?"

Delphi and AI[5]: Encoding a multi-line string

Recently I had to convert a multi-line string into a single-line string value for storage (ignore the 'why' of it; let's just blame it on a legacy code). My first idea was to do a Base64 encode of the string, but I was in a mood for some fun and so I asked my friendly AI helpers:

"I have a multiline string containing newline ASCII characters (TMemo.Text). I want to change it to a single-line string with only printable ASCII characters. I could do that with BASE64 encoding, for example. I would, however, like to keep the text as much readable as possible by "encoding" only non-printable characters. Is there a simple way to do that?"

Let's see what they came up with!

Full transcripts, as usual, are on GitHub. This time I had also created a program containing all implementations.

Delphi and AI [4]: Device-independent clipboard

While working on Chatterbox I ran into number of problems, most of them caused by my limited knowledge of device-independent programming with Firemonkey. One particular challenge was copying data to the clipboard - something that is AFAIK available on all supported platforms. So I asked my friendly AI helpers:

"How can I copy text to clipboard in a Delphi Firemonkey application?"

As always, all logs are available on GitHub.

Delphi and AI [3]: The meaning of Christmas

It's the time of the year to be merry and have fun, so no code today!

I've decided to ask our future AI overlords about the meaning of Christmas. The Delphi way, of course!

Today I'm posting just the answer I liked the most. You can read the others on GitHub.

Happy holidays, fellow programmers! And remember - Delphi, it is the way!

As befits an article on AI-generated content, the image was created by Midjourney.

Delphi and AI [Intermission]: Introducing Chatterbox

t’s great that Embarcadero has added an AI Chat window to RAD Studio, but let’s be honest—the implementation is lacking. As one participant at a recent workshop noted: “It looks like someone wrote it two hours before the release.” Sadly, I have to agree. The AI Chat feature is practically useless if you intend to use AI for anything more than a quick demo.

That’s when I started considering better ways to interface with LLMs. Instead of searching for an alternative, I decided to build my own AI chat interface. It’s called Chatterbox, and it’s fully open source. You can find it on GitHub under a “do with it (almost) whatever you want” license.

To start using Chatterbox, you can either build it from source or download the precompiled EXE from GitHub (currently available only for Windows 32-bit). The app is written with FireMonkey, so—at least theoretically—it can also be built for macOS, iOS, Android, and Linux. However, I haven’t tested it on platforms other than Windows.

To build Chatterbox, you’ll need the following libraries: Spring4D, DCPCrypt2, and TAES. Links to these dependencies are included in the README file.

Delphi and AI [2]: Clipboard Monitor

While preparing for my Delphi and AI workshop, I decided to keep a log of all my interactions with AI helpers in a file for later analysis. Initially, I searched for an existing utility to log clipboard changes to a file (and I found one), but then I thought—why not ask the AI helpers to help me create one? After all, it’s not a big problem: set up a timer, check if the clipboard content changes, and log the content to a file. What could be simpler?

I posed the same question to all five engines:

"I want to create a Delphi application that would monitor clipboard content (on Windows) and append clipboard content to a log file each time the clipboard has changed (and has a text inside)."

Let's see how they performed!

Logs and code are available here.

Delphi and AI

Recently, I led a workshop in Slovenia where we explored the current state of AI in relation to Delphi programming. (A note to participants: the slides are finally online—apologies for the delay!) The initial results were, let’s say, interesting enough to warrant further study.

Now, let’s see how today’s "state-of-the-art" AIs perform with Delphi programming!

The contenders are:

• OpenAI with the o1-mini model (my testing suggests that it gives better results than chatgpt-4o)
• Ollama with codellama:13b model (the largest model I can run on my NVidia 4090)
• Gemini with gemini-pro (currently pointing to gemini-1.5-pro)
• Claude with claude-3-5-sonnet-latest (at this moment this resolves to claude-3-5-sonnet-20241022)

As I care for the privacy of the code I send to these tools, I'm using a paid version of Gemini.

These four engines I'll be using directly from the RAD Studio, most of the time through the "AI Chat" panel. 

When the privacy wouldn't be a concern, I'll also be using:

• CoPilot via Microsoft Edge (I use it a lot and I like it for general-purpose questions with googlable answers)

All chat logs will be published on GitHub. 

RAD Studio 12.2 and AI helpers

This is an invitation to the workshop in Ljubljana next week. As the session will be in Slovenian language, so is this invitation ...

Odkar smo se nazadnje srečali, je minilo kar nekaj časa. Medtem je izšla nova različica RAD Studio 12.2. Ta med drugim prinaša novost, ki smo jo vsi čakali - integracijo umetne inteligence. Pridružite se nam na delavnici, kjer bomo predstavili  novosti v RAD Studiu 12.2.,podporne sisteme ChatGPT, Gemini, Claude in Ollama ter skušali ugotoviti, ali so že dovolj napredni, da jih lahko Delphi programerji uporabljajo pri svojem delu. Poigrali se bomo z računalniškimi pomočniki in preizkusili vaše ideje o uporabi teh orodij.  Vidimo se v sredo, 27. 11., ob 9.30 v prostorih OOZ Vič, Tržaška cesta 207, Ljubljana! Klikni za prijavo!

Delphi and Python, working happily together

Next Wednesday, 10th, I'll be talking about Delphi and Pyhon in Ljubljana. As usual for Slovenian workshops, the talk will be in Slovenian language so I'll continue this invitation appropriately ...

Python je izjemno priljubljen programski jezik, ki slovi po svoji raznoliki in preprosti uporabi. Skupnost razvijalcev nenehno prispeva k njegovemu razvoju in izboljšanju jezika, kar dodatno krepi njegovo privlačnost za širok nabor uporabnikov. Kot večina večplatformnih sistemov pa ne slovi po podpori za izdelavo uporabniških vmesnikov.  Tu nastopi Delphi, ki slovi po svoji hitrosti in učinkovitosti in je odličen za razvoj aplikacij za Windows okolje. Zato ni presenetljivo, da okolji ne delujeta kot neposredna konkurenca, pač pa se izredno dobro dopolnjujeta.  Največja prednost je združevanje moči obeh jezikov. Delphi ponuja hitrost in zmogljivost, Python pa berljivost in obsežno knjižnico razširitev. S tem lahko razvijalci izkoristite najboljše iz obeh svetov.

Na predavanju si bomo ogledali:  Kako lahko Python in Delphi sodelujeta na dva različna načina,  predstavili bomo orodji DelphiVCL in DelphiFMX, s katerima lahko v Pythonu enostavno ustvarite lep uporabniški vmesnik  ter nekaj orodij (Python4Delphi, PythonEnvironments, Lightweight Python Wrappers), ki omogočajo, da kodo, napisano v Pythonu, vgradite v svoj Delphi program.  Spotoma si bomo na kratko ogledali še novosti v novem Delphi 12.1!

Kliknite za prijavo!

Learn all about RAD Studio 12 in Ljubljana

Next week I'll present all about the new RAD Studio 12 in Ljubljana. As usual, the presentation will be in Slovenian language and so will be the rest of this post ...

CQLBr for Delph/Lazarus

It is so nice when you see how a small idea grows into a nice, rounded project!

Years age I wrote a unit that allowed you to write SQL statements as Pascal code (GpSQLBuilder). This has allowed me to write a code like this:

  query := CreateGpSQLBuilder;
  query
    .Select.All
    .From(DB_TEST)
    .OrderBy(
      query.&Case
        .When([COL_2, '< 0']).&Then(COL_3)
        .&Else(COL_4)
      .&End);

It was a small project with minimum support -- as long as it generated SQL code that I've needed, I was fine with it. Much of the SQL language support was missing, there was no support for different SQL dialects and so on ...

Luckilly, Isaque Pinheiro liked the idea and converted it into a full-fledged library with support for multiple SQL dialects, much more complete SQL language support, units tests, installer, a ton of samples and more. 

Delphi High Performance, Second Edition

The second edition of my book Delphi High Performance is now released! Get all 452 pages of Delphi goodness with two new chapters and all the updated and improved content at Amazon or at Packt Publishing!

Delphi High Performance, encore!

It is so interesting to publish a book for the second time. In a way it is similar to reviewing and fixing old code--you go from "well said, old man!" to a "what the #$%! were you thinking when you wrote that" in a matter of pages. It also helps if you do pair-programming have great technical reviewers that help by pointing out the latter and add frequent "this may be obvious to you but I have no idea what you've just said" comments.

Big thanks go to Bruce McGee and Stefan Glienke for improving this book! It would be worth at least a half "star" less without them.

Update: The book is now available on Amazon and Packt Publishing.

International Pascal Congress in Salamanca

Dear fellow readers, I'd like to invite you to International Pascal Congress which will happen from 3rd to 7th July this year in beautiful Salamanca, Spain.

(Not sure you want to go to Salamanca? Think again.)

Although the congress has wider target audience than pure Delphi, it is sponsored by Embarcadero and many prominent Delphi speakers will participate. Marco Cantu will be there, as will Daniele Teti and Bruno Fierens. I will also add my contribution.

The program is split between talks (Monday) and many advanced programming courses (Tuesday--Friday) with plenty of time for socializing or for exploring beautiful Spanish country.

Besides the talks and courses and socializing and a dinner, the IPC will also grant a Niklaus Wirth Award for a Most Valuable Contributor to Pascal. They are still accepting nominations.

I hope to see you there as this is a perfect occasion to forget all the Covid craziness and get together again!

"Design Patterns", rescheduled

For the last Delphi meeting in Slovenia this year we have organized a small workshop about Design Patterns. As usual, it is intended for Slovenian programmers and will be given in the Slovenian language.

"Design Patterns" workshop in Ljubljana

For the last Delphi meeting in Slovenia this year we have organized a small workshop about Design Patterns. As usual, it is intended for Slovenian programmers and will be given in the Slovenian language.

We'll meet again (finally)!

After two long-distance years we are finally moving back to normality, starting with a Slovenian RAD Studio meeting next Wednesday in Ljubljana.

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Po dveh letih virtualnih konferenc vas končno spet vabimo na srečanje v živo! Za izgovor za druženje si bomo ogledali novosti v RAD Studiih iz zadnjih dveh let (10.4, 10.4.1, 10.4.2, 11, 11.1), predvsem pa bomo dogodek izkoristili za klepet ob hrani in pijači in ponovno spoznavanje.

Pridružite se nam 25. maja ob 9h! (klikni za več podatkov in prijavo)

Slovenian Delphi 11 Webinar

Just a short notice for Slovenian readers - In case you missed it, next week you'll be able to join a Slovenian webinar about Delphi 11. 

Register here

Readers-writer lock - Part 4: Improving TLightweightMREW

While the TLightweightMREW is quite handy, it is not perfect. There's a weird assymmetry in it. On all operating systems that Delphi can compile for, read locks are reentrant (recursive) while write locks are not. In other words, if a thread already owns a read lock, it can call BeginRead again and it will succeed. Write locks are different. If a thread already owns a write lock and calls BeginWrite again, it will either deadlock (on Windows) or raise an exception (on other supported platforms).

This is, however, relatively simple to fix. I have implemented a simple wrapper for the TLightweightMREW lock in TLightweightMREWEx. This new record uses internal TLightweightMREW to provide locking and adds some simple logic to implement write lock reentrancy. The implementation and accompanying test program rwReentrantWriter can be found at https://github.com/gabr42/examples/tree/master/Reader-writer%20lock.

Readers-writer lock - Part 3: Some numbers

In order to convince you that a readers-writer lock is not a stupid idea, I should finally show some numbers. In this article I'll present a minimalistic (but still real-life) example which allows us to compare different locking solutions.

All code from this article is available in project rwLock at  https://github.com/gabr42/examples/tree/master/Reader-writer%20lock

Readers-writer lock - Part 2: Implementation

In the previous installment I introduced the idea of a readers-writer lock. Today I'll look into readers-writer lock implementations (yes, multiple) that are available in the Delphi run-time library.

Readers-writer lock - Part 1: Why?

One of the pleasant surprises in Delphi 10.4.1 was the addition of a new readers-writer lock implementation TLightweightMREW. While it was probably not noticed by most of the users, I was quite happy to see it implemented. 

So now you are asking yourself - what is this readers-writer lock and why am I so happy to see it in Delphi? Well, I'm glad that you're asking! Let me explain ...

In multithreaded programming (as most of my horror stories start), we frequently run into a problem of resource sharing. Two threads want to modify a shared resource at the same time and that can cause many problems, from information being overwritten to corrupted data and program crashes.

To fix this, we add resource protection. Usually that is just a critical section (typically through a TCriticalSection wrapper), or Delphi's TMonitor. Sometimes, however, protecting resources with a simple critical section causes an unnecessary performance drop, and that's when a readers-writer lock (may) come into play.

OmniThreadLibrary 3.07.8

New OmniThreadLibrary is out! Get it while it’s hot!

Version 3.07.8 is mostly a bugfix release. It fixes few small bugs and enables support for Delphi 10.4.

You can get it now on git, download the ZIP archive, install it with Delphinus or with GetIt (in few days).

For more information, visit OmniThreadLibrary home page or write your question on the forum.