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Spice86: A .NET-based Real Mode DOS Emulator for Reverse Engineering

2025-02-20

Spice86: A .NET-based Real Mode DOS Emulator for Reverse Engineering

Spice86 is a .NET-based emulator for executing, reverse engineering, and rewriting real-mode DOS programs without source code. It emulates program execution, exports runtime data (memory dump and execution flow), then uses the spice86-ghidra-plugin to import this data into Ghidra, converting assembly instructions into C# code. This allows for a gradual rewriting of the assembly code with C# methods. Spice86 boasts numerous command-line options, including debugging, EMS memory, A20 gate, and GDB remote debugging, along with custom GDB commands for dynamic analysis. It also features a built-in debugger for inspecting memory, disassembly, registers, stack, and structured memory views.

(github.com)

Development DOS emulator

RT64: A Cutting-Edge N64 Graphics Renderer

2025-02-20

RT64: A Cutting-Edge N64 Graphics Renderer

RT64 is a modern N64 graphics renderer built on the latest APIs (D3D12 and Vulkan), designed to enhance gameplay in emulators and native ports. It utilizes ubershaders to eliminate stutters, supports high-resolution rendering and downsampling, widescreen, and high frame rate (HFR). Powerful features include texture pack support, memory optimizations, and framebuffer reinterpretation. Future development includes ray tracing, a game script interpreter, and model replacement, promising a revolutionary upgrade to the N64 gaming experience.

(github.com)

Game Renderer Graphics Enhancement

xkcd Password Generator: Secure and User-Friendly Password Creation

2025-02-20

xkcd Password Generator: Secure and User-Friendly Password Creation

This Python script implements the xkcd password specification, generating secure and memorable passwords. Users can customize password length, word count, separator, and maximum word length. It provides entropy calculations and estimated cracking times, helping users assess password strength. It also supports generating multiple passwords to mitigate shoulder-surfing risks, and offers various command-line arguments for flexibility. The tool uses a cryptographically secure random number generator, ensuring password randomness, and is open-source for easy use and improvement.

(github.com)

Development password generation

KubeVPN: Seamlessly Connect Your Local Dev Environment to Kubernetes Clusters

2025-02-20

KubeVPN: Seamlessly Connect Your Local Dev Environment to Kubernetes Clusters

KubeVPN provides a Cloud-Native Dev Environment that effortlessly connects to your Kubernetes cluster network. Access the cluster network using service names or Pod IP/Service IP. Intercept inbound traffic from remote Kubernetes cluster services to your local PC via a service mesh. Run your Kubernetes pods within a local Docker container for an identical environment, volume, and network setup. Develop applications entirely on your local PC with KubeVPN! Installation is straightforward via brew, scoop, krew, or GitHub releases. Supports multiple cluster connections and proxy modes (full and lite).

(github.com)

Development Cloud-Native Dev Environment

VLM Run Hub: Pre-defined Pydantic Schemas for Simplified Visual Data Extraction

2025-02-20

VLM Run Hub: Pre-defined Pydantic Schemas for Simplified Visual Data Extraction

VLM Run Hub is a comprehensive repository of pre-defined Pydantic schemas for extracting structured data from unstructured visual domains like images, videos, and documents. Designed for Vision Language Models (VLMs) and optimized for real-world use cases, it simplifies integrating visual ETL into your workflows. It offers various pre-defined schemas, such as an Invoice schema for extracting invoice metadata, and supports multiple VLMs including OpenAI's GPT-4o and Anthropic's Claude Vision. Using Pydantic schemas ensures accurate and reliable data extraction and simplifies downstream workflows.

(github.com)

Development Vision Language Models

Postgres Language Server: A Powerful Toolchain for SQL Development

2025-02-19

Postgres Language Server: A Powerful Toolchain for SQL Development

A collection of language tools and a Language Server Protocol (LSP) implementation for Postgres, prioritizing developer experience and reliable SQL tooling. Built on Postgres' own parser (libpg_query) for 100% syntax compatibility, it uses a server-client architecture with transport-agnostic design, offering access via LSP, CLI, HTTP APIs, or WebAssembly. Currently featuring autocompletion, syntax highlighting, type-checking (via EXPLAIN), and a Squawk-inspired linter, the project focuses on refining these core features and building a robust infrastructure. Contributions are welcome!

(github.com)

Development SQL tooling

BloodFlowTrixi.jl: High-Performance Blood Flow Models in Julia

2025-02-19

BloodFlowTrixi.jl: High-Performance Blood Flow Models in Julia

BloodFlowTrixi.jl is a Julia package implementing 1D and 2D blood flow models for arterial circulation, derived from the Navier-Stokes equations. Developed for PhD research on cardiovascular pathologies, it leverages the Trixi.jl framework for efficient Discontinuous Galerkin (DG) simulations. The package supports curvilinear geometries and compliant wall dynamics. Future development includes 3D fluid-structure interaction and vascular network simulations.

(github.com)

Development computational fluid dynamics

Mastra: A TypeScript Framework for Rapid AI App Development

2025-02-19

Mastra: A TypeScript Framework for Rapid AI App Development

Mastra is an opinionated TypeScript framework for quickly building AI applications and features. It provides essential primitives: workflows, agents, RAG, integrations, and evaluations. Run Mastra locally or deploy to a serverless cloud. Key features include LLM model integration (supporting OpenAI, Anthropic, Google Gemini via the Vercel AI SDK), agent systems enabling LLMs to use tools and access data, typed tool functions, durable graph-based workflows, RAG knowledge base construction, pre-built third-party API clients, and automated evaluations. Get started with `create-mastra` and open the playground with `mastra dev`. Contributions are welcome!

(github.com)

Development AI framework

Subtrace: Wireshark for Your Docker Containers

2025-02-19

Subtrace: Wireshark for Your Docker Containers

Subtrace is like Wireshark, but for Docker containers. It lets developers see all network requests in and out of their backend servers, enabling faster resolution of production issues. It works out-of-the-box with no code changes needed, supports all languages, shows full payloads, headers, status codes, and latency, and boasts less than 100µs performance overhead. Built on Clickhouse and open-source (though currently not accepting pull requests due to resource constraints), Subtrace welcomes feature requests and bug reports.

(github.com)

Development Performance Analysis

go-msquic: A Go Wrapper for Microsoft's QUIC Library

2025-02-19

go-msquic: A Go Wrapper for Microsoft's QUIC Library

go-msquic is a Go wrapper for Microsoft's QUIC library, providing a simple interface for Go developers to work with QUIC-based protocols like HTTP/3. Its API is inspired by quic-go and can be used as a drop-in replacement. Unless you're comfortable working with C libraries, quic-go is generally recommended. Installation requires building the local MsQuic C library first, then installing with `go get github.com/noboruma/go-msquic`. Sample code is in the sample/ directory.

(github.com)

Development

OpenArc: A Lightweight Inference API for Accelerating LLMs on Intel Hardware

2025-02-19

OpenArc: A Lightweight Inference API for Accelerating LLMs on Intel Hardware

OpenArc is a lightweight inference API backend leveraging the OpenVINO runtime and OpenCL drivers to accelerate inference of Transformers models on Intel CPUs, GPUs, and NPUs. Designed for agentic use cases, it features a strongly-typed FastAPI implementation with endpoints for model loading, unloading, text generation, and status queries. OpenArc simplifies decoupling machine learning code from application logic, offering a workflow similar to Ollama, LM-Studio, and OpenRouter. It supports custom models and roles, with planned extensions including an OpenAI proxy, vision model support, and more.

(github.com)

AI Inference API

Augment: AI-Powered Code Completion and Chat for Vim/Neovim

2025-02-19

Augment: AI-Powered Code Completion and Chat for Vim/Neovim

Augment released its Vim/Neovim plugin offering inline code completions and multi-turn chat conversations tailored to your codebase. After installation (requiring Node.js 22.0.0+ and compatible Vim/Neovim versions), add workspace folders and sign in to the Augment service. Context-aware code completions appear as you type; use the `:Augment chat` command for AI-powered code discussions. The plugin provides commands for managing status, login/logout, enabling/disabling suggestions, viewing logs, and starting new chat conversations. `.augmentignore` helps manage large projects. Easily customize keybindings for accepting suggestions.

(github.com)

Development AI code completion

LLMs Fail at Set, Reasoning Models Triumph

2025-02-19

LLMs Fail at Set, Reasoning Models Triumph

An experiment tested the reasoning capabilities of Large Language Models (LLMs) in the card game Set. Set requires identifying sets of three cards from a layout of twelve, based on specific rules regarding shape, color, number, and shading. LLMs like GPT-4o, Sonnet-3.5, and Mistral failed to consistently identify correct sets, often suggesting invalid combinations or claiming no sets existed. However, newer reasoning models, DeepThink-R1 and o3-mini, successfully solved the problem, demonstrating superior logical reasoning abilities. This highlights a limitation of LLMs in complex logical tasks, even while excelling at natural language processing, while specialized reasoning models show a clear advantage.

(github.com)

AI Set Game

RustOwl: Visualizing Ownership and Lifetimes in Rust

2025-02-18

RustOwl: Visualizing Ownership and Lifetimes in Rust

RustOwl is a powerful tool that visualizes ownership and lifetimes of variables in Rust code. Using color-coded underlines, RustOwl intuitively displays variable lifetimes, immutable borrowing, mutable borrowing, and value movement, aiding developers in debugging and optimization. It supports VSCode, Neovim, and Emacs, offering various installation methods, including a simple command-line installation and manual installation from source code. While minor display issues may occasionally occur, RustOwl has demonstrated significant potential for improving Rust development efficiency.

(github.com)

Development

mt32-pi Development Halted Due to Online Abuse

2025-02-17

mt32-pi Development Halted Due to Online Abuse

The developer of mt32-pi, a bare-metal MIDI synthesizer for the Raspberry Pi emulating the Roland MT-32, has announced the project's termination due to sustained online abuse. This includes personal attacks, code theft, and stolen 3D print designs. The developer cited the negative impact on their mental health as the reason for ceasing development, expressing a lack of gratitude and encouragement from the community.

(github.com)

Development online abuse

Running ELKS on an NES: The NES86 Project

2025-02-17

Running ELKS on an NES: The NES86 Project

The NES86 project is an amazing feat of engineering: an IBM PC emulator running on the NES! By emulating an Intel 8086 processor and supporting PC hardware, it successfully runs the ELKS (Embeddable Linux Kernel Subset), including a shell and utilities. This means you can run some x86 software on your old NES, albeit limited to a simple serial terminal. The project is open-source and provides detailed build instructions, covering both the compilation of the ELKS image and the generation of the NES86 ROM. Prepare for a challenge—running a modern OS on retro hardware!

(github.com)

Development

Visualizing the Thought Process of a Large Language Model (R1)

2025-02-17

Visualizing the Thought Process of a Large Language Model (R1)

Researchers visualized the 'thought process' of a large language model, R1, by saving its chains of thought as text, converting them into embeddings using the OpenAI API, and plotting them sequentially with t-SNE. By calculating cosine similarity between consecutive steps, they observed a potential three-stage process: 'search,' 'thinking,' and 'concluding.' Ten diverse prompts were used, ranging from describing how a bicycle works to designing new transportation. The researchers provide methods for accessing the chain-of-thought data and code.

(github.com)

AI Thought Visualization

Bag of Words: Build and Share Smart Data Apps with AI

2025-02-17

Bag of Words: Build and Share Smart Data Apps with AI

Bag of Words empowers users to create comprehensive dashboards from a single prompt and iteratively refine them. It seamlessly integrates with various data sources, including databases, APIs, and business systems, enabling efficient data utilization. Key features include natural language queries, dashboard management, and compatibility with multiple LLMs (OpenAI, Anthropic, etc.). The project offers Docker deployment and detailed setup instructions for Python and Node.js environments, using the AGPL-3.0 license.

(github.com)

AI Data Applications

Umami: A Privacy-Focused Google Analytics Alternative

2025-02-17

Umami: A Privacy-Focused Google Analytics Alternative

Umami is a simple, fast, and privacy-focused alternative to Google Analytics. It supports MariaDB, MySQL, and PostgreSQL databases. Installation is straightforward: clone the GitHub repo, install dependencies, and configure the database connection. It runs by default on http://localhost:3000. Docker images are available for easy deployment. Detailed getting started instructions are provided.

(github.com)

Development analytics

Shell Command Efficiency Hack: Quickly Identify Past Commands with Icons

2025-02-16

Shell Command Efficiency Hack: Quickly Identify Past Commands with Icons

Frequently searching and rerunning commands in your shell history? The author shares a clever trick: add icon or text identifiers before commands (e.g., ✅; ./utils/check.sh). These identifiers don't affect command execution but significantly improve visual recognition, allowing you to quickly find the desired command and alleviate the frustration of frequently scrolling through history. It's a simple yet effective way to improve shell efficiency.

(github.com)

Development Shell tricks command-line efficiency

Remco: A Lightweight Configuration Management Tool

2025-02-16

Remco: A Lightweight Configuration Management Tool

Remco is a lightweight configuration management tool inspired by confd. It keeps local configuration files up-to-date using data from key/value stores like etcd or Consul, processing template resources and reloading applications automatically. Unlike confd, Remco supports multiple source/destination pairs and backends per template resource, uses the Pongo2 template engine, and includes features like zombie reaping, plugin support for additional backends, and easy custom template filter creation with JavaScript. Installation is straightforward, with options for building from source or downloading pre-built binaries.

(github.com)

Development configuration management

Gixy: A Powerful Nginx Configuration Security Auditor

2025-02-16

Gixy: A Powerful Nginx Configuration Security Auditor

Gixy is a tool for analyzing Nginx configurations to prevent security misconfigurations and automate flaw detection. Supporting Python 3.6-3.13, it's primarily tested on GNU/Linux. Gixy detects various Nginx configuration issues, such as HTTP splitting vulnerabilities. Installation is flexible, supporting pip, yum, and Docker. Users can specify config paths, use piped input, and skip tests. Gixy is actively maintained and welcomes code contributions and documentation improvements.

(github.com)

Development Auditing

Gulf of Mexico: A Programming Language That Breaks the Rules

2025-02-16

Gulf of Mexico: A Programming Language That Breaks the Rules

DreamBerd has been renamed to Gulf of Mexico, a quirky programming language with unusual features. Statements end in exclamation marks, the semicolon is the 'not' operator, there are four declaration types (const const, const var, var const, var var), arrays start at index -1, float indices are supported, the `when` keyword checks variable mutations, there's a garbage collector, variable lifecycles are customizable (including negative lifecycles for hoisting), and there are no loops. Installation is complex, booleans can be true, false, or maybe, whitespace determines arithmetic operation precedence, fractions and number names are supported, indentation is rigidly 3 spaces, multiple comparison operators exist, function declaration is flexible, division by zero returns undefined, strings can be declared in various ways, regional currency interpolation is supported, type annotations are optional, regular expression types are supported, and `previous`, `next`, and `current` keywords access variable history. Code can be split into multiple files using five or more equals signs. It supports code reversal, global variables, and automatic insertion of exclamation marks, brackets, and quotes. Gulf of Mexico also supports rich text and a turn-based execution mechanism for asynchronous functions.

(github.com)

Development quirky design

OmniParser V2: Screen Parsing Tool for Pure Vision-Based GUI Agents

2025-02-15

OmniParser V2: Screen Parsing Tool for Pure Vision-Based GUI Agents

OmniParser is a comprehensive method for parsing UI screenshots into structured, understandable elements, significantly boosting GPT-4V's ability to generate actions accurately grounded in interface regions. The recently released OmniParser V2 achieves state-of-the-art results (39.5% on Screen Spot Pro) and introduces OmniTool, enabling control of a Windows 11 VM using your vision model of choice. Detailed installation instructions and demos are provided, with model weights available on Hugging Face.

(github.com)

AI Vision AI GUI Parsing

Schemesh: A Lisp-Scriptable Unix Shell

2025-02-15

Schemesh: A Lisp-Scriptable Unix Shell

Schemesh is an interactive shell scriptable in Lisp, designed as a user-friendly replacement for bash, zsh, and other traditional Unix shells. It offers interactive line editing, autocompletion, and history, while seamlessly integrating a full Lisp REPL powered by Chez Scheme for complex tasks. Users can switch effortlessly between shell syntax and Lisp syntax, with extensive functions provided for managing Unix processes. For scripting and serious programming, Schemesh replaces the slow and error-prone traditional shell scripting with a powerful Lisp REPL, boosting efficiency and reliability.

(github.com)

Development

Jill: A New Functional Programming Language for Nand2Tetris

2025-02-15

Jill: A New Functional Programming Language for Nand2Tetris

Jill is a functional programming language built for the Nand2Tetris platform as an alternative to the original Jack high-level language. It's a drop-in replacement for Jack, using the same VM instruction set and HACK architecture, but offering a more elegant, functional style. Key features include first-class functions, optimized tail-call recursion, algebraic data types with pattern matching, and a minimal design with only three core concepts. Compiled projects output .vm files to a /bin directory. Jill can be compiled using `cargo run -- path_to_jill_project_root` or `jillc [path_to_jill_project_root]`.

(github.com)

Development

Synergetica: An End-to-End Genetic Circuit Design Desktop App

2025-02-15

Synergetica: An End-to-End Genetic Circuit Design Desktop App

Synergetica is a powerful desktop application for designing genetic circuits. It offers a complete workflow, from circuit design and simulation to DNA sequence generation, all within a single platform. Users can design circuits using either a node-based or code-based interface, interactively simulate protein expression levels, and generate DNA sequences based on simulation parameters. Customization is easy with addable genetic parts, and the offline functionality ensures complete control and privacy.

(github.com)

Development genetic circuit design bioinformatics software tool

Kreuzberg: A Powerful Local Document Text Extraction Python Library

2025-02-15

Kreuzberg: A Powerful Local Document Text Extraction Python Library

Kreuzberg is a powerful Python library for text extraction from various documents. It provides a unified asynchronous interface supporting PDFs, images, office documents, and more. The library emphasizes local processing, requiring no external APIs or cloud services, boasting high resource efficiency, minimal dependencies, and batch processing capabilities. Kreuzberg employs a smart approach to PDF text extraction, first attempting direct extraction and falling back to OCR if necessary. It offers comprehensive error handling and features such as async/sync APIs, metadata extraction, and concurrent processing.

(github.com)

Development text extraction document processing

Goku: Flow-Based Video Generative Foundation Models Achieve SOTA Performance

2025-02-15

Goku: Flow-Based Video Generative Foundation Models Achieve SOTA Performance

A collaborative team from ByteDance and HKU introduces Goku, a family of image and video generation models based on rectified flow Transformers. Goku achieves industry-leading visual generation performance through meticulous data curation, advanced model design, and flow formulation. Supporting text-to-video, image-to-video, and text-to-image generation, Goku achieves top scores on major benchmarks like GenEval, DPG-Bench, and VBench. Notably, Goku-T2V scored 84.85 on VBench, placing it second overall as of October 7th, 2024, surpassing several leading commercial text-to-video models.

(github.com)

AI Video Generation Rectified Flow Transformer

LLM Debugger: AI-Powered Debugging in VS Code

2025-02-15

LLM Debugger: AI-Powered Debugging in VS Code

LLM Debugger is a VS Code extension that uses large language models (LLMs) for active debugging. Unlike traditional LLM debugging approaches that only analyze static source code, LLM Debugger provides real-time runtime context, including variable values, function behavior, and branch decisions, enabling the LLM to diagnose bugs faster and more accurately. The extension also generates synthetic data by capturing execution details, offering unique insights into program behavior. It features live debugging information, automated breakpoint management, runtime inspection, and common debugging operations, all accessible through a sidebar panel. While an experimental research project, LLM Debugger demonstrates the potential of combining live debugging data with LLM capabilities to revolutionize traditional debugging practices.

(github.com)

Development AI debugging VS Code extension

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