semvec/pypi-packages huggingface dataset:
fastconvert 1.0.5
A powerful CLI tool for converting files between different formats.
Requires Python: >=3.6

# FastConvert

FastConvert is a powerful and easy-to-use CLI tool for converting files between different formats.

## Features

- Convert images between formats (jpg, png, webp, gif, etc.)
- Convert videos between formats (mp4, avi, mkv, etc.)
- Convert videos to images (extracting first frame)

## Installation

```bash
pip install fastconvert
```

## Usage

Basic conversion:
```bash
fastconvert input_file output_file
```

Examples:
```bash
# Convert image from PNG to JPEG
fastconvert image.png image.jpg

# Convert video from MP4 to AVI
fastconvert video.mp4 video.avi

# Extract frame from video as image
fastconvert video.mp4 frame.jpg
```

## Supported Formats

### Images
#### Input Formats:
- JPEG/JPG (.jpg, .jpeg)
- PNG (.png)
- WebP (.webp)
- GIF (.gif)
- BMP (.bmp)
- TIFF (.tiff, .tif)
- ICO (.ico)
- PPM (.ppm)
- PGM (.pgm)
- PBM (.pbm)
- JPEG 2000 (.jp2)
- EPS (.eps)

#### Output Formats:
All input formats are supported as output formats.

### Videos
#### Input Formats:
- MP4 (.mp4)
- AVI (.avi)
- MKV (.mkv)
- MOV (.mov)
- WebM (.webm)
- FLV (.flv)
- WMV (.wmv)
- MPEG (.mpeg, .mpg)
- 3GP (.3gp)
- M4V (.m4v)
- AMV (.amv)

#### Output Formats:
All input video formats are supported as output formats.
Also input videos can converted to images (first frame extraction)

## Requirements

- Python 3.6+
- See requirements.txt for Python dependencies

## License

MIT License
kaltts 1.0.2012
Kal Text-to-Speech (TTS) Synthesis
Requires Python: >=3.6

# KalTTS

KalTTS is a text-to-speech module that converts text into speech audio.

## Installation

You can install the package using pip:

```sh
pip install kaltts
```

## Usage

Here is an example of how to use the KalTTS module:

```python
from kaltts import generate_speech
from pydub import AudioSegment
from pydub.playback import play
import io

def main():
    text = 'Hello, this is a test of Kal TTS.'
    audio_output = generate_speech(text)

    with open('output.mp3', 'wb') as f:
        f.write(audio_output.getbuffer())

    audio_segment = AudioSegment.from_file('output.mp3', format='mp3')
    audio_segment.export('output.wav', format='wav')

    print('Audio saved as output.wav')
    play(audio_segment)

if __name__ == "__main__":
    main()
```
mlx-alt-text 0.1.1
Local-first alt-text generator built on top of MLX-VLM
Requires Python: <3.13,>=3.10

# MLX Alt Text

A Python package for generating alt-text for images using local MLX models.

## About

MLX Alt Text is a local-first alt-text generator built on top of MLX-VLM. It allows you to generate descriptive alt-text for images using vision-language models that run entirely on your device using Apple's MLX framework.

## Features

- Generate detailed accessibility descriptions for images
- Run entirely on-device (no API calls except to download the model)
- Customizable prompts, output lengths, and temperatures
- Command-line interface for easy integration into workflows
- Python API for integration into your applications

## Requirements

- macOS with Apple Silicon
- Python 3.10–3.12

## Installation

```bash
uv tool install mlx-alt-text # CLI installation with uv (recommended)
pipx install mlx-alt-text    # CLI installation with pipx
pip install mlx-alt-text     # Python pacakge installation
```

## Usage

### Command-line Interface

Generate alt-text for an image:

```bash
mlx-alt-text path/to/image.jpg
```

With custom options:

```bash
mlx-alt-text path/to/image.jpg \
  --prompt "Describe this image in detail for accessibility purposes" \
  --model "mlx-community/SmolVLM-256M-Instruct-bf16" \
  --max-tokens 150 \
  --temperature 0.3
```

### Python API

```python
from mlx_alt_text import AltTextGenerator

# Initialize with default options
generator = AltTextGenerator()

# Or with custom options
generator = AltTextGenerator(
    model_name="mlx-community/Qwen2-VL-2B-Instruct-4bit",
    max_tokens=100,
    temperature=0.2
)

# Generate alt-text
alt_text = generator.generate(
    image="path/to/image.jpg",
    prompt="Describe this image for accessibility purposes"
)

print(alt_text)
```

## Available Models

By default, MLX Alt Text uses `mlx-community/Qwen2-VL-2B-Instruct-4bit`, but you can specify other compatible models. Some examples below:

- `mlx-community/Qwen2-VL-2B-Instruct-4bit` (default, ~2GB)
- `mlx-community/SmolVLM-256M-Instruct-bf16` (smaller, ~256MB)
- `mlx-community/SmolVLM-Instruct-bf16` (larger, better quality)

The first time you use a model, it will be automatically downloaded from the Hugging Face Hub.

## Development Setup

1. Clone the repository:

```bash
git clone https://github.com/yourusername/mlx-alt-text.git
cd mlx-alt-text
```

2. Set up the development environment with uv:

```bash
# Install uv if you don't have it
curl -LsSf https://astral.sh/uv/install.sh | sh

# Create a virtual environment and install dependencies
uv sync
source .venv/bin/activate
uv run mlx-alt-text
```

3. Run tests:

```bash
pytest
```

### Other Development Notes

```bash
uv lock --upgrade # to upgrade all packages
uv lock --upgrade <package> # to upgrade a single package
uv build # to build the package
uv run https://gist.githubusercontent.com/Jython1415/84f37a01fb9700d3eb72b67a52273222/raw/3d7ec10e3c6bb5f0191bd6681dd0016017a28a55/uv-publish-pypi.py # to publish the package
```

## License

This project is licensed under the MIT License - see the LICENSE file for details.
mmplayer-mcp-server 0.1.0
Add your description here
Requires Python: >=3.13

please config this MCP server in your MCP client/Cline etc.
<code>
"music_player": {
      "command": "python",
      "args": [
        "/[Your Path]/demp/MCP/server/mplayer/main.py"
      ]
}
</code>
ancestree 0.1.0
A tool for merging and analyzing genealogy datasets.
Requires Python: >=3.10

# GWAS Toolkit

A comprehensive Python package for processing and analyzing Genome-Wide Association Study (GWAS) data.

## Features

- Data import/export for common GWAS file formats
- Quality control and filtering of genetic variants
- Population stratification correction
- Association testing with various statistical models
- Visualization of GWAS results
- Annotation and functional interpretation of significant variants

## Installation

```bash
pip install gwas_toolkit
```

## Usage

```python
import gwas_toolkit as gtk

# Load GWAS data
data = gtk.load_data("path/to/gwas_data.txt")

# Perform quality control
filtered_data = gtk.quality_control(data, maf=0.05, geno=0.1, hwe=1e-6)

# Run association analysis
results = gtk.run_association(filtered_data, model="linear")

# Visualize results
gtk.manhattan_plot(results)
gtk.qq_plot(results)

# Annotate significant variants
annotated = gtk.annotate_variants(results.significant())
```

## Documentation

For detailed documentation, visit [docs.gwastoolkit.org](https://docs.gwastoolkit.org).

## Requirements

- Python ≥ 3.8
- numpy
- pandas
- scipy
- matplotlib
- statsmodels
- scikit-learn

## License

MIT
uipath_sdk 0.0.92
UiPath SDK
Requires Python: >=3.9

# UiPath SDK

## CLI User's guide

`pip install uipath_sdk`
_(NOTE: create virtual env if needed)_

```
uipath init [PROJECT_NAME] [DIRECTORY] [DESCRIPTION]
```

defaults:

-   project name => my-agent
-   directory => ./
-   description => "my-agent description"

example:

```
uipath init
OR
uipath init custom-name ./my-projects/custom-dir "my custom description"
```

after init `cd` into the created folder, install the dependencies from requirements.txt then set your credentials in the `.env` file
_(NOTE: if you just want to publish the default package or edit basic things in the main.py file you may skip installing the dependencies)_

```
uipath pack [ROOT] [VERSION]
```

defaults:

-   root => ./
-   version => 1.0.0
    example:

```
uipath pack
OR
uipath pack ./my-projects/custom-dir 2.0.4
```

NOTE: if you run the pack command outside of the folder with the `config.json` it will throw an error

after packing it's time to publish

```
uipath publish [PATH_TO_NUPKG]

uipath publish my-custom-package.2.3.1.nupkg
```

defaults:

-   if no path provided, it will use the first `.nupkg` file it finds in your current directory

NOTE: this command also needs an `.env` file in your current directory

## Installation
Use any package manager (e.g. `uv`) to install `uipath` from PyPi:
    `uv add uipath_sdk`

## Usage
### SDK
1. Generate a PAT (Personal Access Token)
For example, to create a PAT for alpha, go to (replace ORG with your organization name)
https://alpha.uipath.com/[ORG]/portal_/personalAccessToken/add

2. Set these env variables:
- `UIPATH_URL`
- `UIPATH_ACCESS_TOKEN`
- `UIPATH_FOLDER_PATH`

```py
import os
from uipath_sdk import UiPathSDK


def main():
    uipath = UiPathSDK()

    job = uipath.processes.invoke_process(name="process_name")
    print(job)

```

### CLI

## License
nonebot-plugin-quark 0.1.1
NoneBot2 夸克云盘资源搜索插件
Requires Python: >=3.10
Keywords: nonebot, nonebot2, quark, search

<div align="center">
    <a href="https://v2.nonebot.dev/store">
    <img src="./.docs/NoneBotPlugin.svg" width="300" alt="logo"></a>
</div>


<div align="center">

# nonebot-plugin-quark

_✨ 夸克云盘资源搜索 ✨_


<a href="./LICENSE">
    <img src="https://img.shields.io/github/license/fllesser/nonebot-plugin-quark.svg" alt="license">
</a>
<a href="https://pypi.python.org/pypi/nonebot-plugin-quark">
    <img src="https://img.shields.io/pypi/v/nonebot-plugin-quark.svg" alt="pypi">
</a>
<img src="https://img.shields.io/badge/python-3.10+-blue.svg" alt="python">

</div>



## 📖 介绍

夸克云盘搜索插件

## 💿 安装

<details open>
<summary>使用 nb-cli 安装</summary>
在 nonebot2 项目的根目录下打开命令行, 输入以下指令即可安装

    nb plugin install nonebot-plugin-quark --upgrade

使用官方源更新，常用于刚发版，其他源未同步的时候

    nb plugin install nonebot-plugin-quark --upgrade -i https://pypi.org/simple

</details>

<details>
<summary>使用包管理器安装</summary>
在 nonebot2 项目的插件目录下, 打开命令行, 根据你使用的包管理器, 输入相应的安装命令

<details>
<summary>pip</summary>

    pip install nonebot-plugin-quark --upgrade -i https://pypi.org/simple
</details>
<details>
<summary>pdm</summary>

    pdm add nonebot-plugin-quark
</details>
<details>
<summary>poetry</summary>

    poetry add nonebot-plugin-quark
</details>
<details>
<summary>conda</summary>

    conda install nonebot-plugin-quark
</details>

打开 nonebot2 项目根目录下的 `pyproject.toml` 文件, 在 `[tool.nonebot]` 部分追加写入

    plugins = ["nonebot_plugin_quark"]

</details>


## 🎉 使用
### 指令表
| 指令 | 权限 | 需要@ | 范围 | 说明 |
|:-----:|:----:|:----:|:----:|:----:|
| qs | 群员 | 否 | - | 搜索 |
orch 0.0.1b1
🎶 Orchestrator: Your devices, your symphony.
Requires Python: >=3.8

# orch

[![PyPI - Version](https://img.shields.io/pypi/v/orch.svg)](https://pypi.org/project/orch)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/orch.svg)](https://pypi.org/project/orch)

-----

## Table of Contents

- [Installation](#installation)
- [License](#license)

## Installation

```console
pip install orch
```

## License

`orch` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.