🛠️ All DevTools

[Other] Professional Audio/Lighting/Rigging Tools Professional tools for audio, lighting, rigging, and video production. Calculators, databases, and utilities for entertainment professionals.

[API/SDK] Sora2 api for video generation Sora2Api provides a unified API for Sora2 video generation.

[Other] 50+ free SEO tools without signup walls HeadlineBoost is a suite of 50+ completely free SEO and developer tools. No signup walls, no credit cards, no API keys. Real data from live DNS/SSL queries. Built for SEO pros, developers, and marketers who are tired of subscription fatigue.

[API/SDK] Free, fast and simple link preview api for developers Fast, flexible, and simple link preview API. Extract title, description, image, favicon, and more from any public URL.

[Other] Side web framework) Inspired by Laravel, Archery is a modern, server-side framework for Dart that brings structure, speed, and clarity to backend development.

[IDE/Editor] Pyscripter – Open-source Python IDE written in Delphi

[Other] Show HN: MarkdownConverters – Convert any file format to clean Markdown Hey HN<p>I built MarkdownConverters.com — a tool that converts any file format (PDF, DOCX, PPTX, HTML, or URL) into clean, structured Markdown.<p>I often needed to prep documents, reports, or scraped pages for AI pipelines, documentation, or version control, but existing tools either broke formatting, lost code blocks, or produced unreadable Markdown.<p>So I built something that focuses on: • Accurate structure (headings, lists, tables, code, links) • Consistent Markdown output ready for LLMs or docs • Fast, browser-based conversion with privacy-friendly processing • Support for multi-format and URL inputs<p>It’s especially useful if you work with RAG, embeddings, or text preprocessing — Markdown becomes a universal “clean” format for structured content.<p>Would love feedback on: • Conversion quality — what edge cases break for you? • Formats you’d like supported next (CSV, EPUB, JSON, etc.) • API workflows — would you use it for automation?<p>Try it here: <a href="https:&#x2F;&#x2F;markdownconverters.com" rel="nofollow">https:&#x2F;&#x2F;markdownconverters.com</a><p>Happy to answer any technical questions about the conversion pipeline or file parsing methods.

[Other] Show HN: Browser-based PDF form fields detection (YOLO-based) Hey HN!<p>Last week, Joe Barrow released CommonForms [1], a set of open models for automatically detecting form fields in PDFs.<p>He trained two models, FFDNet-S and FFDNet-L, on a dataset of 55k documents. You can read more about his approach in the arXiv paper [2].<p>As someone who&#x27;s been searching for reliable models to auto-detect form fields (one of the last hard problems in PDF form filling), I was seriously impressed by the quality of these models. I wanted to give them the attention and distribution they deserve, so I created a fully browser-based implementation that handles both detection and field addition.<p>My implementation relies on his models and onnx runtime web + some post-processing. I plan on publishing a small browser library to encapsulate it in the coming days to make it easier to deploy anywhere (currently you&#x27;d have to fork &#x2F; copy my code)<p>Happy to answer any questions about the browser-based implementation!<p>Questions about the models themselves should be directed to Joe, who I believe is also on HN [3]<p>[1] <a href="https:&#x2F;&#x2F;github.com&#x2F;jbarrow&#x2F;commonforms" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;jbarrow&#x2F;commonforms</a> [2] <a href="https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2509.16506" rel="nofollow">https:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;2509.16506</a> [3] <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;user?id=jbarrow">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;user?id=jbarrow</a>

[IDE/Editor] Show HN: Notepad.exe – macOS editor for Swift and Python (now Linux runtime) I recently released version 1.4 of Notepad.exe, my editor built for macOS. The goal of the app is to let you prototype ideas in Swift or Python with minimal setup - write code, hit Run, skip project scaffolding.<p>This release adds support for a Linux runtime&#x2F;subsystem, so you can write on macOS and execute snippets in a Linux environment.<p>I’d love to hear any feedback or answer any questions: would a tool like this fit your workflow? What friction remains?

[Database] Show HN: EloqDoc: MongoDB-Compatible Doc DB with Object Storage as First Citizen We&#x27;re excited to share EloqDoc, a new open source document database built on top of Data Substrate. EloqDoc is designed around the principle of treating object storage (like S3) as a first-class citizen for durability and cost efficiency. If you love the flexibility of MongoDB&#x27;s document model but are struggling with scaling, cost, and consistency due to its coupled architecture, EloqDoc is for you. It’s built to solve MongoDB&#x27;s inherent infrastructure challenges while remaining fully compatible with existing MongoDB clients and drivers.<p>Key Features:<p>1. Object Storage as First Citizen: Uses object storage for primary durability, leveraging local NVMe caching to achieve both lower cost and higher performance than using block-level storage (e.g. EBS).<p>2. Decoupled Compute &amp; Storage: Scale your compute&#x2F;QPS independently of your storage capacity, or vice-versa, without data movement.<p>3. True ACID Transactions: Delivers full ACID compliance with especially fast distributed transactions—consistency without compromise.<p>4. Native Distribution &amp; Multi-Writer: It&#x27;s a natively distributed database, eliminating complex manual sharding routers (like mongos) and supporting true Multi-Writer scalability.<p>Check it out: <a href="https:&#x2F;&#x2F;www.github.com&#x2F;eloqdata&#x2F;eloqdoc" rel="nofollow">https:&#x2F;&#x2F;www.github.com&#x2F;eloqdata&#x2F;eloqdoc</a><p>We welcome any feedback, critique, or questions on the EloqDoc!

[Other] Show HN: Pyversity – Fast Result Diversification for Retrieval and RAG Hey HN! I’ve recently open-sourced Pyversity, a lightweight library for diversifying retrieval results. Most retrieval systems optimize only for relevance, which can lead to top-k results that look almost identical. Pyversity efficiently re-ranks results to balance relevance and diversity, surfacing items that remain relevant but are less redundant. This helps with improving retrieval, recommendation, and RAG pipelines without adding latency or complexity.<p>Main features:<p>- Unified API: one function (diversify) supporting several well-known strategies: MMR, MSD, DPP, and COVER (with more to come)<p>- Lightweight: the only dependency is NumPy, keeping the package small and easy to install<p>- Fast: efficient implementations for all supported strategies; diversify results in milliseconds<p>Re-ranking with cross-encoders is very popular right now, but also very expensive. From my experience, you can usually improve retrieval results with simpler and faster methods, such as the ones implemented in this package. This helps retrieval, recommendation, and RAG systems present richer, more informative results by ensuring each new item adds new information.<p>Code and docs: github.com&#x2F;pringled&#x2F;pyversity<p>Let me know if you have any feedback, or suggestions for other diversification strategies to support!

[Other] Show HN: Web-directive.js – A directive pattern for native HTML A library to implement directive pattern for native HTML without any framework, which is inspired by Vue.js.

[Other] Show HN: C and C++ preprocessor for modern memory safety Cdefer A Next-Generation Memory-Safe Preprocessor for C &amp; C++<p>Bringing modern memory safety and zero-configuration builds to classic C &amp; C++.

[Other] Show HN: Syna – Minimal ML and RL Framework Built from Scratch with NumPy Hello HN,<p>I built Syna to understand how modern ML frameworks like PyTorch actually work — from the ground up.<p>It’s a minimal, define-by-run (dynamic graph) framework inspired by DeZero, written entirely with NumPy. Unlike most libraries, Syna includes a basic reinforcement learning module right inside the same framework — no separate packages.<p>It’s not about speed or GPUs — it’s about clarity, simplicity, and learning the internals of machine learning. Great for students, educators, and anyone curious about what’s really happening under the hood.<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;sql-hkr&#x2F;syna" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;sql-hkr&#x2F;syna</a><p>I also built a web app that visualizes how neural networks learn in real time — perfect for beginners exploring training dynamics:<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;sql-hkr&#x2F;xor" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;sql-hkr&#x2F;xor</a> Demo: <a href="https:&#x2F;&#x2F;sql-hkr.github.io&#x2F;xor&#x2F;" rel="nofollow">https:&#x2F;&#x2F;sql-hkr.github.io&#x2F;xor&#x2F;</a><p>Happy hacking!

[Other] qBittorrent BitTorrent client

[Other] Open source codebase powering the HuggingChat app

[Other] A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

[API/SDK] The most intuitive desktop API client. Organize and execute REST, GraphQL, WebSockets, Server Sent Events, and gRPC 🦬

[IDE/Editor] Show HN: Duck-UI – Browser-Based SQL IDE for DuckDB I built Duck-UI, a web-based SQL editor that runs DuckDB entirely in your browser via WebAssembly. No backend required.<p>The Problem: Every time I needed to query csv, parquet, or even to play with SQL, I had to either: (a) spin up a Jupyter notebook (b) use the CLI (c) upload to a hosted service.<p>Friction at every step (TOO MUCH to load a csv or even to test some sql (study)...<p>The Solution: DuckDB&#x27;s WASM runtime lets us run SQL analysis client-side. Load CSV&#x2F;JSON&#x2F;Parquet files from disk or URL, write SQL, get results instantly. Data stays on your machine. What It Does:<p>SQL editor with autocomplete &amp; syntax highlighting Import CSV, JSON, Parquet, Arrow (local or remote URLs) Query history, keyboard shortcuts, theme toggle Persistent storage via OPFS (data survives browser refresh) Optional: Connect to external DuckDB servers One-liner Docker deployment or Node 20+ dev server<p>Technical Details:<p>DuckDB compiled to WASM; query execution in-browser OPFS-backed persistence Apache 2.0 licensed Runs on Chrome 88+, Firefox 79+, Safari 14+<p>Use Cases:<p>Learning SQL without setting up databases Ad-hoc data exploration (CSV → SQL in seconds) Quick prototyping before shipping to production Privacy-conscious workflows (no data leaves your browser)<p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;ibero-data&#x2F;duck-ui" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;ibero-data&#x2F;duck-ui</a> Live Demo: <a href="https:&#x2F;&#x2F;demo.duckui.com" rel="nofollow">https:&#x2F;&#x2F;demo.duckui.com</a> Quick Start: docker run -p 5522:5522 ghcr.io&#x2F;ibero-data&#x2F;duck-ui:latest<p>Would love feedback on: (1) Use cases I&#x27;m missing (2) Performance bottlenecks you hit (3) Features that would make this your default SQL scratchpad.

[CLI Tool] Show HN: bbcli – A TUI and CLI to browse BBC News like a hacker hey hn!<p>I (re)built this TUI tool for browsing BBC News in the terminal, it uses an RSS feed for getting headlines and previews and you can read articles too.<p>Try it out and let me know what you think! :)