semvec/pypi-packages huggingface dataset:
autocorrect-linux 0.4.3
System-wide autocorrect for Linux
Requires Python: <3.13,>=3.9

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         style="width: 35%;">
  </a>
</div>


# autocorrect-linux

**autocorrect-linux** is a system-wide word suggestion and prediction tool for Linux desktops.  
It provides real-time word suggestions and next-word predictions for any application, using a global keyboard listener and a floating GUI.  
**Note:** This tool does **not** automatically replace misspelled words—it only suggests possible corrections and predictions.

---

## Features

- Real-time word suggestions for any window
- Next-word prediction using Machine Learning
- Custom personal word list (PWL) support
- Words flagged as incorrect get added to PWL after being used 3 times
- Always-on-top floating GUI (when activated)
- Works system-wide on Linux/X11

---

## Requirements

- Linux (X11)
- Python 3.9 - 3.11
- **4GB free disk space required** (for model and data files)
- **8GB RAM recommended** (for smooth operation)

---

## Installation

**System dependencies:**

Arch Linux:
```bash
sudo pacman -S xorg-xprop
```

Debian/Ubuntu:
```bash
sudo apt install x11-utils
```

**Python package:**
```bash
pip install autocorrect_linux
```

---

## Usage

Start the tool with:
```bash
python -m autocorrect_linux
```

- The first startup may take **several seconds** as the language model and vocabulary are downloaded and loaded into memory.
- On subsequent runs, startup will be faster.

A floating window will appear at your mouse cursor, showing word suggestions and predictions as you type.  
You can click on suggestions to copy them, but the tool will **not** automatically replace words in your application.

### Hotkeys

- **Alt+C**: Pause/resume the suggestion window and prediction engine.

### Notes

- The tool works system-wide, but only on Linux/X11 desktops.
- The GUI is non-intrusive and does not allow editing.
- Suggestions are based on both a dictionary and a machine learning model.
- If you use a personal word list (PWL), words you use often will be suggested more quickly.

---

## Troubleshooting

- **Startup is slow:** The first run downloads and loads a large model (~400MB). Make sure you have a stable internet connection and enough disk space.
- **High RAM usage:** 8GB RAM is recommended, especially for large models.
- **No suggestions appear:** Make sure you are running under X11 (not Wayland) and that required system packages are installed.
- **Hotkey does not work:** Ensure no other application is using Alt+C as a global shortcut.

---

## License

GPL-3.0

---

## Author

[simon0302010](https://github.com/simon0302010/autocorrect-linux)
cutted 0.4.4
AI-powered audio editor controllable via natural language.
Requires Python: <3.14,>=3.9

![PyPI](https://img.shields.io/pypi/v/cutted?color=blue)
![PyPI - License](https://img.shields.io/pypi/l/lyriks-video)


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         style="width: 35%;">
  </a>
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# Cutted

**Cutted** is an AI-powered audio editor you control with natural language.

- Cut, trim, or adjust volume by typing what you want
- Detect and remove silence or loud parts automatically
- Transcribe audio (with Whisper)
- Undo edits, export as MP3 or WAV

## Install

1. Make sure [FFmpeg](https://ffmpeg.org/) is installed.
2. Install Cutted:
   ```bash
   pip install cutted
   ```
   With Whisper support:
   ```bash
   pip install cutted[whisper]
   ```

## Usage

```bash
python -m cutted
```
Load an audio file, enter your command in plain English, and export your result.  
You can also enable or disable chat history for smarter follow-up actions in the settings menu (gear icon).

---

## Usage Examples

### Basic Editing

- **Cut a segment:**
  ```
  cut from 10 to 20
  ```
  Removes audio between 10s and 20s.

- **Remove multiple segments:**
  ```
  cut from 5 to 7 and from 15 to 18
  ```

- **Change volume:**
  ```
  make 0 to 5 seconds twice as loud
  ```
  or
  ```
  reduce volume from 10 to 12 by half
  ```

- **Remove silence:**
  ```
  remove all silent parts
  ```
  > Note: Removing silence is experimental and can be buggy or produce bad results in some cases.

- **Undo last edit:**  
  Click the "Undo" button.

- **Export your result:**  
  Click the "Export" button and choose MP3 or WAV.

### Advanced: Using Whisper Transcription

If you install with Whisper support and enable "Send transcript to Gemini" in the UI, you can use commands like:

- **Cut by word or sentence:**
  ```
  cut when I say the word hello
  ```
  or
  ```
  cut the sentence "welcome to the show"
  ```
  > This uses Whisper to transcribe your audio and allows precise editing based on spoken words or phrases.

### Audio-to-Gemini (Experimental)

If you enable "Send audio to Gemini" (checkbox), you can also use word-based commands, but accuracy is much lower compared to using Whisper.

---

## Gemini API Key

Set your Gemini API key as an environment variable before running Cutted:

**Linux/macOS:**
```bash
export GEMINI_API_KEY="your-gemini-api-key"
```

**Windows (Command Prompt):**
```cmd
set GEMINI_API_KEY=your-gemini-api-key
```

**Windows (PowerShell):**
```powershell
$env:GEMINI_API_KEY="your-gemini-api-key"
```
NUcmd 0.1
cmd工具
Requires Python: <3.14,>=3.9

# NUcmd



`NUcmd
` 是一个为开发者提供基本cmd控制的库错库会打开在cmd上

### 使用
```
 NUcmd.cmd("         ")括号内写cmd指令
```

### 安装

```
pip install NUcmd
```


### License
WXcmd 0.2
cmd工具
Requires Python: <3.14,>=3.9

# WXcmd



`WXcmd
` 是一个为开发者提供基本cmd控制的库错库会打开在cmd上

### 使用
```
 WXcmd.cmd("         ")括号内写cmd指令
```

### 安装

```
pip install WXcmd
```


### License
habitpy 0.1.13
Track your habits from the terminal
Requires Python: >=3.11

---

# HabitPy

**Track your habits, analyze your progress, and stay motivated—all from your terminal!**

## Features

- 📅 **Daily & Weekly Tracking:** Log your habits (only numbers)
- ✏️ **Custom Habits:** Add, show, or delete any habit you want to track.
- 📈 **Visualize Progress:** Instantly generate beautiful graphs (with dark mode!) for your week, month, or year.
- 🎉 **Motivational Cheers:** Get random motivational messages to keep you going.
- 📤 **Export Data:** Export all your habit data to CSV for use in Excel, Sheets, or anywhere else.
- 🛠️ **Easy Reset:** Reset your data and start fresh anytime.

## Installation
```bash
pip install habitpy==0.1.13
```
If your system says some error about being globally installed try installing with *pipx*,
for example in arch linux:
```bash
sudo pacman -S python-pipx
pipx ensurepath
```
close your terminal and:
```bash
pipx install habitpy==0.1.13
```
Or, for development:
```bash
git clone https://github.com/Asunt70/habitpy.git
cd habitpy
python -m venv .venv/
source .venv/bin/activate
pip install .
```

## Usage

First, set up your tracker:
```bash
habitpy setup
```

Then, use these commands:
- `habitpy track` — Log today’s habits
- `habitpy create <habit_name>` — Add a new habit
- `habitpy show` — List your habits
- `habitpy delete <habit_name>` — Remove a habit
- `habitpy graph week|month|year` — See your progress in graphs
- `habitpy export` — Export your data to CSV
- `habitpy reset` — Delete all data and start over

---

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