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Featured apps, libraries, and tools — organized by category

🎯

ManimStudio

v1.1.1.0

Create stunning mathematical animations with a powerful GUI application. Microsoft Store compatible - no administrator rights required!

🎨 Visual Code Editor ⚡ Live Preview 🔓 No Admin Rights 🤖 Auto Dependencies 📁 Asset Management

What's Included

  • ✅ ManimStudio GUI Application
  • ✅ Python 3.12.7 (bundled installer)
  • ✅ MiKTeX Basic (officially recommended for Manim)
📋 Requirements
  • Windows 10+ (64-bit)
  • No admin privileges needed
  • Internet for initial setup
⚙️ Quick Install
  1. Run ManimStudio installer
  2. Auto-installs dependencies
  3. Follow setup wizard
  4. Launch and create!

Technical Specifications

Created by: Yu Yao-Hsing

License: MIT License

LaTeX Engine: MiKTeX

Format: MSIX Package

Platform: Windows 10+

🏪 Microsoft Store 🔒 Privacy Policy 📧 Contact
📱

ManimStudio (iOS / iPadOS)

iOS 17+ App Store Python 3.14

A complete offline Python animation studio for iPad and iPhone, built on the Manim engine. Edit Python in a Monaco editor, render to MP4 via Apple VideoToolbox hardware encode, drop in LaTeX with busytex — entirely on-device.

📝 Monaco Editor ⚡ VideoToolbox H.264 🐚 offlinai_shell (~150 builtins) 🧮 busytex LaTeX ⌨️ SwiftTerm + PTY ✈️ Fully Offline 🌏 CJK-aware Text()

What's Included

  • ✅ Bundled Python 3.14 stack via python-ios-lib — manim, NumPy, SciPy, matplotlib, Plotly, PyAV, pycairo, pangocairo, busytex (all arm64-iphoneos)
  • ✅ Monaco editor in WKWebView — full Python autocomplete, find/replace, multi-cursor, snippets, render-error gutter markers
  • ✅ Live symbol-completion index built from introspection of the bundled Python packages
  • ✅ Drag-drop image → auto-inserts ImageMobject snippet
  • ✅ Pure-Swift Python formatter (⌥⌘L)
  • ✅ Reuses the offlinai_shell from CodeBench / BenchCode (rebranded as "ManimStudio shell" at install)
📋 Requirements
  • iOS 17.0+ / iPadOS 17.0+
  • Apple Silicon (arm64-iphoneos)
  • Magic Keyboard supported
  • No internet connection needed
⚙️ Render Pipeline
  • VideoToolbox H.264 (~5× faster than libx264)
  • Cairo via pycairo compat layer
  • busytex WASM for Tex / MathTex
  • Output to Documents/ — Files app visible

Technical Specifications

Created by: Yu Yao-Hsing

App Store ID: 6764472686 (manimstudio)

Branch: manim_app/ios

Python: 3.14 (iOS arm64)

Editor: Monaco · Terminal: SwiftTerm + PTY

🍎 App Store 🐙 GitHub (ios branch) 🐍 python-ios-lib 💻 CodeBench 🔒 Privacy Policy
🛠️

CodeBench

iPad · iPadOS · Mac Catalyst Local AI

A self-contained developer / scientific / AI workstation for iPad and Mac. Python 3.14, C, C++, Fortran, pdflatex, and local LLMs — all running on-device, no internet required.

📝 Monaco Editor 🧠 IntelliSense ⌨️ SwiftTerm REPL 📐 pdflatex 🦙 llama.cpp ⚡ Metal GPU PyTorch 🎨 Image Gen 🔍 RAG Engine ⌘ Command Palette 📊 Live RAM Sparkline 💾 Auto-save
📝 Code Editor VS Code

Real Monaco editor in WKWebView. Python IntelliSense with ~70-entry signature DB, hover docs, and live resolve from the embedded Python daemon for numpy / scipy / sklearn / matplotlib / sympy completions.

⌨️ Integrated Terminal PTY

SwiftTerm-backed terminal piped through a real PTY into the embedded CPython REPL. Type Python directly, or use POSIX-style builtins like ls, grep, ncdu, top, git clone.

📐 On-Device pdflatex WASM

busytex (pdftex 1.40.25 + xetex + luatex + bibtex8) running in a hidden WKWebView. TeX Live 2023 preloaded into MEMFS plus a 23 MB overlay with PGF/TikZ/beamer, hyperref, mathtools, microtype, fontspec, CJK.

🦙 Local LLMs GGUF

llama.cpp as an XCFramework — load any Llama / Mistral / Qwen / Phi GGUF model and chat with streaming tokens. ExecuTorch backends for Apple Core ML / XNNPACK kernel-optimized PyTorch inference.

🔍 RAG & Image Gen offline

In-process sentence-embedding + vector store over user-imported text / PDF / markdown. Offline image generation via ExecuTorch-runnable diffusion models. All models stay in the app sandbox — no tokens leave the device.

💾 Workspace System multi-tab

iOS document browser with multiple concurrent workspaces. Auto-save debounced ~600 ms after every keystroke + on run, tab-switch, view-disappear, and app-backgrounding. Tombstone system records deleted files so seeders don't resurrect them.

⚡ Metal GPU PyTorch NEW

Monkey-patched torch.matmul / mm / bmm / addmm, F.linear, and SDPA onto Apple's MPSMatrixMultiplication via ctypes → Swift @_cdecl. 2–10× speedup at training sizes. fp32/fp16 native, bf16 via fp32 cast. Autograd-aware via torch.autograd.Function. Auto-installed via sitecustomize.py — zero user code changes.

⌘ UI Polish NEW

Live RAM sparkline in the top-right tab bar, command palette (⌘P), editor status bar, tab slide animation, drag-to-select in the terminal (via SwiftTerm doubleTap), and a real Stop button that interrupts the running task.

🧪 Training Toolkit NEW

Opt-in _cb_training.py (~12 KB pure Python) ships OOMGuard, MemoryProfiler, KVCache, and TrainingMonitor. Plus a pure-Python safetensors reader (mmap + struct + torch.frombuffer) so transformers.from_pretrained() works without Rust crates.

Languages — all share Monaco + IntelliSense + auto-save

Python 3.14 (BeeWare CPython) C — 3.4k LOC interpreter C++ — 4.2k LOC interpreter Fortran — 4.1k LOC interpreter
📋 Built On
  • python-ios-lib — runtime layer
  • SwiftTerm — xterm-compatible PTY
  • Monaco Editor — VS Code in WebView
  • busytex — TeX Live 2023 in WASM
  • llama.cpp + ExecuTorch — local AI
📦 Bundle Composition
  • ~1 GB installed app size
  • 791 MB Frameworks (Python, llama, ExecuTorch)
  • 484 MB Python site-packages
  • 254 MB Swift source + LaTeX data

Technical Specifications

Created by: Yu Yao-Hsing

Platforms: iPad · iPadOS · Mac Catalyst

Runtime: Python 3.14 + four interpreters

Editor: Monaco (VS Code) in WKWebView

Status: Active Development

🐙 GitHub Repository 🧱 Runtime Layer 📧 Contact Developer
🐍

python-ios-lib

Python 3.14 30+ Libraries

Full Python 3.14 runtime for iOS/iPadOS with 30+ offline libraries — including native PyTorch, HuggingFace transformers, and Rust tokenizers. Train on-device. No JIT, App Store safe. Powers CodeBench.

📱 iOS 17+ ✈️ Fully Offline 🛡️ App Store Safe 🔥 PyTorch Native ⚡ Metal GPU Bridge 🤗 Transformers 🦀 Rust Tokenizers 🧮 NumPy Native 🎬 Manim Video 🔧 C/C++/Fortran 📂 dulwich Git 🌐 Web Stack (Flask · Dash · Streamlit)
🔬 Scientific Computing 6
LibraryVer
NumPy2.3.5
SciPy1.15.0
SymPy1.14.0
mpmath1.4.1
PyArrow NEWcolumnar data
Tropycal NEWtropical cyclones
🤖 Machine Learning 4
LibraryVer
PyTorch BETA2.1.2
transformers BETA4.41.2
tokenizers BETA0.19.1
scikit-learn40 modules

Native PyTorch (95/95 asserts) + Metal GPU bridge (2–10× speedup) + HuggingFace transformers & Rust tokenizers — train on-device

📊 Visualization 3
LibraryVer
matplotlib3.9.0
Plotly6.6.0
manim BETA0.20.1

145+ mobjects, 73 animations, interactive Plotly HTML charts

🎬 Media & Rendering 5
LibraryType
PyAV17 C exts
FFmpeg7 dylibs
Cairo + PangoNative iOS
Pillow12.2.0
offlinai_latexSwiftMath + 33MB texmf
🌐 Data & Web 6
LibraryPurpose
PyWebView NEWv5.4.0 — iOS WKWebView
requestsHTTP client
BeautifulSoup4HTML parse
NetworkXGraphs
jsonschemaValidation
PyYAMLYAML
💻 Interpreters 3
LanguageDetails
C~3,661 lines
C++~4,287 lines
Fortran~3,876 lines

Tree-walking interpreters — structs, templates, STL, modules

🌐 Web Stack NEW
LibraryPurpose
Flaskweb framework
DashPlotly dashboards
StreamlitML / data apps
Tornadoasync server (6.5.5)
WerkzeugWSGI utils

Run a full Python web app on-device — Jinja2 + MarkupSafe + Fsspec also bundled. See web-stack.md.

🛠️ Terminal & CLI Utilities 5
LibraryPurpose
richTables, progress bars
tqdmLoop progress
clickCLI framework
PygmentsSyntax highlight (500+)
pydubAudio manipulation
⚙️ System & Graphics 7
LibraryVer
psutil5.9.8
watchdog4.0.0
moderngl5.12.0
svgelements1.9.6
decorator NEW5.1.1
safetensorsHF deps
huggingface-hubHF deps
📝 Monaco IntelliSense ~70 sigs

Real VS Code editor in WKWebView with Python signature help, hover docs, and live resolve from Python for numpy / scipy / sklearn / matplotlib / sympy.

📐 Expanded LaTeX Bundle 33 MB

Full Latin Modern Type 1 fonts, expl3 (1.3 MB), firstaid, hyphenation, unicode-data, pdftex.map. Math-mode rendering via SwiftMath is unlimited.

⌨️ Shell Builtins POSIX-y

ncdu with arrow-key navigation, top with Apple-chip detection, git clone via zipball fetch, universal --help interception.

💾 Auto-save ~600 ms

Edits persist to disk on every keystroke (debounced) plus on run, tab-switch, view-disappear, and app-backgrounding. No more lost edits on reopen.

🪦 Tombstone System .offlinai_deleted

Files deleted via UI / shell rm / ncdu's d are recorded so starter-script seeders (pip_demo.py, torch_test_all.py) won't re-create them.

🧪 Test Coverage 24/24

Full integration test for the transformers stack passes 24/24. PyTorch ships 95/95 correctness asserts. First public iOS builds for PyTorch + tokenizers.

⚡ Metal GPU Bridge NEW

_torch_metal_bridge.py patches torch matmul / mm / bmm / addmm, F.linear, and SDPA onto Apple's MPSMatrixMultiplication. 2–10× speedup at training sizes. fp32/fp16 native, bf16 via fp32 cast. Autograd-aware, auto-installed via sitecustomize.py.

📂 Git via dulwich NEW

Real git push / pull / commit via auto-installed dulwich. Plus pywebview FileDialog enum and faulthandler that writes C-level crashes to ~/Documents/log.txt.

📋 Requirements
  • iOS 17.0+ / iPadOS 17.0+
  • Python 3.14 (BeeWare)
  • NumPy 2.x (arm64 wheel)
  • Works completely offline
🚀 Quick Start
  1. Copy library folders into site-packages/
  2. Add interpreter .c/.h to Xcode
  3. Import and use
  4. No JIT needed!

Technical Specifications

Created by: Yu Yao-Hsing

License: MIT

Runtime: Python 3.14 on iOS arm64

Libraries: 30+ (native + pure Python)

Platform: iOS 17+ / iPadOS 17+

🐙 GitHub Repository 📧 Contact Developer
📊

Generalized Covariance Matrix

ESD Analysis Tool

Advanced eigenvalue spectral distribution analysis for generalized covariance matrices. A powerful research tool for mathematicians and data scientists!

📈 ESD Analysis 🔢 Matrix Computation 📴 Offline Mode ⚡ Real-time Visualization 💾 Export Results

Key Capabilities

  • ✅ Analyze eigenvalue distributions
  • ✅ Visualize spectral densities
  • ✅ Explore random matrix theory
  • ✅ Export data for further analysis

Perfect for: Statistical analysis, ML research, quantum mechanics, and financial modeling

💻 System Requirements
  • Windows 10+ (64-bit)
  • Works completely offline
  • One-click installation
🚀 Get Started
  1. Install from Microsoft Store
  2. Launch the application
  3. Input your matrix data
  4. Analyze & visualize!

Technical Specifications

Created by: Yu Yao-Hsing

Category: Research & Education

Platform: Windows Store

Type: Desktop App

Status: Active Development

📦 Get from Microsoft Store 🔒 Privacy Policy 📄 Download Research Paper 📧 Contact Developer
🎨

EigenDenoise

macOS 14+ Metal GPU

Native macOS image denoiser using random matrix theory — the macOS counterpart to Generalized Covariance Matrix. Pure Swift, Metal-accelerated, App Store sandbox-ready.

🔬 Marchenko–Pastur 📈 Generalized-Cov Oracle ⚡ Metal Acceleration 🎲 5 Noise Models 📊 Spectral Visualizations 🛡️ App Sandbox

Key Capabilities

  • ✅ Side-by-side RMT denoisers — MP thresholding + generalized-covariance oracle (β·δ_a + (1−β)·δ_1)
  • ✅ Differential evolution to find best (a, β) against a clean reference
  • ✅ Three interactive spectral tabs — Eigenvalue density, Im(s) vs z, Roots vs β
  • ✅ Curated dataset gallery: ORL Faces (400 PGMs), CBSD68 (68 colour), Brain MRI (3,264 T1 slices)
  • ✅ Custom URL lists with per-image checkboxes & destination preview
💻 System Requirements
  • macOS 14 (Sonoma) or later
  • Apple Silicon (arm64) — Rosetta supported
  • Metal GPU acceleration (LAPACK fallback)
  • App Sandbox enabled
⚙️ Tech Stack
  • Pure Swift 5.9+ / SwiftUI / Charts
  • MPSMatrixMultiplication for Gram step
  • LAPACK dsyevd for eigen-decomposition
  • Zero external Swift package deps

Mathematics

For X ∈ ℝ^(p×n) with i.i.d. N(0,1) entries, S_n = (1/n)XXᵀ and T_n = diag(t₁,…,t_p), the generalized sample covariance B_n = S_n T_n. Its Stieltjes transform satisfies a cubic:

a·z·s³ + (a(z − y + 1) + z)·s² + (a + z − y + 1 − y·β·(a − 1))·s + 1 = 0

Limiting density f_{y,H}(z) follows from Cardano's depressed-cubic root; support recovered via bulk-edge function and quartic discriminant for one-interval (Cases 1, 3) vs two-interval (Case 2) topology.

Technical Specifications

Created by: Yao-Hsing Yu

License: MIT

Platform: macOS 14+ (Apple Silicon)

Type: Native macOS App (App Store ready)

Status: Active Development

🍎 Mac App Store 🐙 GitHub Repository 🔒 Privacy Policy 📄 Research Paper 📧 Contact Developer
📦

Python Packages (PyPI)

🦙
ollama-installer

Install Ollama from a Python CLI. A convenient command-line tool for setting up Ollama on your system.

GitHub → PyPI →
🗣️
narrate

Local text-to-speech with Kokoro and Chatterbox engines. High-quality voice synthesis running entirely on your machine.

GitHub → PyPI →
🧮
rmt-denoise

Image denoising via Random Matrix Theory. Two denoisers — MP-Law thresholding (i.i.d. Gaussian) and GeneralizedCov (oracle search for (a, β) via differential evolution). The Python library counterpart to EigenDenoise.

GitHub → PyPI →
📍

GPS-location-app

iOS 17+ App Store Apple Watch CarPlay

Precision GPS workout tracker for iPhone & Apple Watch. Kalman-filtered location, HealthKit sync, Live Activities, CarPlay, and route analytics — all in a clean SwiftUI interface.

🛰️ Kalman-filtered GPS ⌚ Apple Watch ❤️ HealthKit Sync 🚗 CarPlay 📡 Live Activities 🗺️ Route Analytics 📊 Workout History 🔒 Privacy-First

Key Capabilities

  • ✅ Record workouts with high-precision GPS, Kalman-filtered for noisy signals
  • ✅ Continuous tracking from iPhone + Apple Watch — start one, finish on the other
  • ✅ Two-way HealthKit sync — workouts appear in the iOS Fitness / Health apps
  • ✅ Live Activity / Dynamic Island shows current distance, pace, and duration
  • ✅ CarPlay support for in-car activity display
  • ✅ Per-workout route map with split / pace / elevation analytics
  • ✅ All workout data stays on your device — no servers, no telemetry
📋 Requirements
  • iOS 17.0+ / watchOS 10+
  • Magic Keyboard supported
  • Location, Motion & Fitness, HealthKit permissions
  • Works fully offline
🚀 Get Started
  1. Install from the App Store
  2. Grant location & HealthKit permissions
  3. Pair with Apple Watch (optional)
  4. Tap Start to record a workout

Technical Specifications

Created by: Yu Yao-Hsing

App Store ID: 6764729098

Frameworks: SwiftUI · CoreLocation · HealthKit · ActivityKit · CarPlay

Stack: Pure Swift / SwiftUI

Status: Live on App Store (approved May 18, 2026)

🍎 App Store 🐙 GitHub Repository 🔒 Privacy Policy 📧 Contact Developer
📱

Apps & Visualizations

🔬
t-SNE Visualization

Dimensionality reduction tool using t-SNE for high-dimensional data visualization and analysis.

GitHub → Download →
🔒 Privacy Policy
✍️
NeonScribe

A Python-based creative writing and text processing tool with a modern interface.

View Project →
🔧

Utilities

🔊
Sound Transfer

TCP-based sound transfer tool for streaming audio between devices over a network.

View Project →
📥
Google Drive Download

A Python tool for downloading files from Google Drive with ease and automation.

View Project →