tinyBigGAMES

Yes.

🚀 Explore My GitHub Projects! 🌟 Check out my current GitHub tools and libraries I’ve been working on! 🎮 JetInfero Local LLM Inference Library 🎨 Aurora Game Toolkit Advanced Game Development Toolkit 📦 JetZip Zip It Fast, Zip It Easy! 🤖 Lumina Local Generative AI Toolkit 🔥 Pyro Pyro Game Library for Delphi 🛠 CPas Static C Libraries for Delphi 📀 PSFML SFML for Pascal Developers 🧠 MemoryDLL In-Memory DLL Loading & Execution for Pascal 🕹 DSDL SDL for Delphi Developers 🌕 Callisto Lua Scripting for Delphi 📜 CScript C99 Scripting Engine

https://github.com/tinyBigGAMES/jetLua

What if you wanted an even smaller Lua integration for Delphi? Just using stock Lua 5.4.7+, statically linked directly into your Delphi executable with no external overhead, and automatic registration of native Delphi routines, all in a single unit? Introducing Chandra - Lua Scripting for Delphi. A client needed a tiny, simpler, but capable Lua scripting solution than my recently released PLUA. The Chandra.o file (just Lua compiled into a single translation unit) is linked directly into Delphi via {$L Chandra.o} with ~600kb overhead. It can directly register published Delphi class methods via RTTI. Enjoy, happy coding! 👀 https://github.com/tinyBigGAMES/Chandra

Hi, thanks! At the moment, I'm only targeting Windows. Mostly because much of that audience is on Windows. I won't rule out other platforms, however. The products that I create are for clients using Windows. The libs are open source so if anyone wishes to port to other platforms, go for it. Note that often, a library may take express advantage of a feature that is limited or unique to the Windows platform, however. In the case of games for example, the last time I looked at the Steam stats, the vast majority of users there are still on Windows. It's no debate that Windows still has the best development tools, and it is still much easier to release on it. But, like I said, I'm not against it per say, just that for me, in the current moment, I have no need or desire to release anywhere else.

Here are a few more projects: PLUA: Lua for Pascal PLUA is a lightweight and powerful 📦 that integrates LuaJIT scripting into Delphi, enabling you to easily add a scripting layer to your Delphi apps. Whether you're building dynamic software 🖥️, adding mod support 🛠️, or simply looking for a way to make your apps more flexible and customizable, PLUA makes this possible through simple, straightforward APIs. CPas: Static C Libraries for Delphi A collection of hand-picked, high-quality C libraries, compiled into a single translation unit and seamlessly integrated into Delphi. This approach eliminates the need for external DLLs, runtime extraction, or loading them in memory, simplifying the development process and reducing potential compatibility issues, such as antivirus 🛡️ interference. Mamba Game Toolkit: Advanced 2D Game Library for Delphi. Mamba Game Toolkit (MGT) is a sophisticated yet easy-to-use 2D game development library for Delphi. Tailored to meet the needs of Windows developers, MGT offers a streamlined approach to building 2D games, focusing on simplicity, performance, and reducing external dependencies. With everything linked directly into the executable️, it eliminates the need for runtime DLLs, simplifying deployment and enhancing the overall stability and reliability of your projects. Enjoy! 👀

Here are a few recent projects I've created that might be useful to others: CScript: C99 Scripting Engine for Delphi 🅲🆂cript represents a sophisticated 🅲99 scripting engine meticulously crafted for experienced 🧑‍💻 Delphi developers. Leveraging the compact yet highly versatile TinyCC compiler, 🅲🆂cript seamlessly integrates ⚙️ dynamic backend code generation into the Delphi development environment. With 🅲🆂cript, Delphi developers can 🛠️ compile and execute 🅲 scripts at runtime, directly in 💾 memory, and generate output in the form of 🪟 Win64 executables (.exe), dynamic-link libraries (.dll), or 📂 object files (.obj). MemoryDLL: In-Memory Win64 DLL Loading & Execution for Pascal. The MemoryDLL unit provides advanced functionality for loading dynamic-link libraries (DLLs) directly from memory in Win64 environments. Unlike traditional methods that involve loading DLLs from the file system, MemoryDLL allows you to load DLLs from byte arrays 📂 or memory streams 💾, retrieve function addresses, and unload them—all in-memory. This library is ideal for Delphi/FreePascal developers who need to manage DLLs without relying on the filesystem, enhancing both performance ⚡ and security 🔒. PSFML: SFML for Pascal PSFML is a Pascal binding for the ⚡ Simple and Fast Multimedia Library (SFML), providing Pascal developers with a straightforward way to utilize SFML’s multimedia features directly in their projects. Whether building 🎮 games, 🤖 interactive applications, or 🎥 multimedia tools, PSFML integrates smoothly with SFML, bringing robust multimedia functionality to the Pascal ecosystem. Enjoy! 👀

Latest update: - Added miniaudio

Using the new Clang based C++ Builder (win64 modern platform), which can compile more C/C++ code than it could in the past, which means it is more likely to be able to compile your favorite C library. You compile the code to generate .o files, which Delphi can consume with {$L unit1.o} for example. I have a unit called CPas.CRuntime that references all the missing c runtime routines that the C lib may reference and thus allow Delphi to compile and use the static C library. Continue to update CPas.CRuntime as you encounter references that you may need. I have included a far bit already. “Now you can link in static C libs directly into Delphi:” means you can take your favorite C lib, such as sqlite and link inside the EXE vs calling it from a DLL. I have sqlite3 as an example in the repo. Not all of them will be possible, but you should be able to do more with the new tool chain than you ever could before. This does require 12.1+

Ok, I've revived this project. Now you can link in static C libs directly into Delphi: tinyBigGAMES/CPas: Static C Libraries for Delphi (github.com)

It evolved into tinyBigGAMES/LMEngine: Local LLM Inference (github.com) for Vulkan based GPUs and tinyBigGAMES/Infero: An easy to use, high performant CUDA powered LLM inference library. (github.com) for CUDA GPUs. More stable and supports using up to full model context if you have the resources on your device.

Dllama, a simple and easy to use library for doing local LLM inference directly from Delphi (any language with bindings). It can load GGUF formatted LLMs into CPU or GPU memory. Uses Vulkan back end for acceleration. Simple Example uses System.SysUtils, Dllama, Dllama.Ext; var LResponse: string; LTokenInputSpeed: Single; LTokenOutputSpeed: Single; LInputTokens: Integer; LOutputTokens: Integer; LTotalTokens: Integer; begin // init config Dllama_InitConfig('C:\LLM\gguf', -1, False, VK_ESCAPE); // add model Dllama_AddModel('Meta-Llama-3-8B-Instruct-Q6_K', 'llama3', 1024*8, '<|start_header_id|>%s %s<|end_header_id|>', '\n assistant:\n', ['<|eot_id|>', 'assistant']); // add messages Dllama_AddMessage(ROLE_SYSTEM, 'you are Dllama, a helpful AI assistant.'); Dllama_AddMessage(ROLE_USER, 'who are you?'); // display the user prompt Dllama_Console_PrintLn(Dllama_GetLastUserMessage(), [], DARKGREEN); // do inference if Dllama_Inference('llama3', LResponse) then begin // display usage Dllama_Console_PrintLn(CRLF, [], WHITE); Dllama_GetInferenceUsage(@LTokenInputSpeed, @LTokenOutputSpeed, @LInputTokens, @LOutputTokens, @LTotalTokens); Dllama_Console_PrintLn('Tokens :: Input: %d, Output: %d, Total: %d, Speed: %3.1f t/s', [LInputTokens, LOutputTokens, LTotalTokens, LTokenOutputSpeed], BRIGHTYELLOW); end else begin Dllama_Console_PrintLn('Error: %s', [Dllama_GetError()], RED); end; Dllama_UnloadModel(); end.

Hi, for now yes. I may revisit it in the near future.

Integrate with OpenAI's ChatGPT API seamlessly from Delphi. Features Easily access the GPT API from a single class Supports both GPT3 and GPT4 models API key can be read from ChatGPTApiKey environment variable if defined Automatically sanitizes input to minimize errors Ability to define proxy settings Adjust personality response with a precision range of 0-1, from precise to creative Stream responses just like in the ChatGPT web interface Usage Get your API Key: https://platform.openai.com/account/api-keys Define environment variable ChatGPTApiKey and assigned your API key. You may have to reboot your machine for it to take effect. // Basic example showing how to query ChatGPT uses AskChatGPT; var LChat: TAskChatGPT; begin LChat := TAskChatGPT.Create; try // set chat params LChat.Model := GPT3; // use the GPT3 model, or GPT4 for the GPT4 model LChat.Creative := 1; // 0-1, 0 being most percise and 1 being most creative // ask question LChat.Question := 'What is Delphi?' // print question PrintLn('Q: %s', [LChat.Question]); // process and print response if LChat.Process then PrintLn('A: %s', [LChat.Response]); finally LChat.Free; end; end; Media Download https://github.com/tinyBigGAMES/AskChatGPT

1. If you have not done so, make sure you have excluded all Delphi related folders + your project folders from real-time virus scanning 2. ASLR is enabled by default so there may be places in your code that are now suddenly invalid whereas it worked perfectly before. There may be places where you must use NativeInt/NativeUInt instead for example. So, check for ASLR related issues that may exist in your code base. After doing the above, the constant AVs and crashes diminished for me.