semvec/pypi-packages huggingface dataset:
cosyvoice-package 0.0.3
cosyvoice package by xp
Requires Python: >=3.8

!!!!! Warning: Provided unofficially and for author use only !!!!!   

before pip install:
conda install -y -c conda-forge pynini==2.1.5

after pip install:
conda install pytorch torchvision torchaudio pillow==9.0.0 pytorch-cuda=12.4 -c pytorch -c nvidia
conda install pytorch==2.0.1 torchvision==0.15.2 pillow==9.0.0 torchaudio==2.0.2 pytorch-cuda=11.7 -c pytorch -c nvidia

mkdir pretrained_models
git clone https://www.modelscope.cn/iic/CosyVoice-300M.git pretrained_models/CosyVoice-300M
git clone https://www.modelscope.cn/iic/CosyVoice-300M-SFT.git pretrained_models/CosyVoice-300M-SFT
url2markdown-cli 2024.10.3
Fetch a url and translate it to markdown in one command.
Requires Python: >=3.10
Keywords: url2markdown, url2markdown-cli

# url2markdown-cli

Fetch a url and translate it to markdown in one command.

## Usage

To install:

```shell
$ uv pip install url2markdown-cli
```

To use:

```shell
url2markdown https://www.djangoproject.com/
```

To use your own custom url2markdown server instance (you should):

```shell
export URL2MARKDOWN_URL='https://urltomarkdown.herokuapp.com/?url={url}'
```

## Contact / Social Media

Here are a few ways to keep up with me online. If you have a question about this project, please consider opening a GitHub Issue.

[![](https://jefftriplett.com/assets/images/social/github.png)](https://github.com/jefftriplett)
[![](https://jefftriplett.com/assets/images/social/globe.png)](https://jefftriplett.com/)
[![](https://jefftriplett.com/assets/images/social/twitter.png)](https://twitter.com/webology)
[![](https://jefftriplett.com/assets/images/social/docker.png)](https://hub.docker.com/u/jefftriplett/)
wukongbaobao 1.0.10
Wukongbaobao is a program that helps parents flexibly generate test questions for their children. The tool is written in Python.
Requires Python: >=3.6
Keywords: education, math, learn, kids-learn, kids-education

# Wukongbaobao

Wukongbaobao 是一个帮助家长灵活生成幼儿考试题的程序。工具使用 Python 编写。
* https://github.com/qiqilelebaobao/wukong

Wukongbaobao is a program that helps parents flexibly generate test questions for their children. The tool is written in Python.
* https://github.com/qiqilelebaobao/wukong


主要功能包括：
* 通过算法按需生成数学试题
* 支持生成txt文件、docx文件格式

Main functions include:
* Generate math test questions on demand through algorithms
* Supports generation of txt and docx file formats

## 适用场景 Applicable Scenarios

* 场景一：家庭教育场景
* 场景二：程序学习场景

* Scenario 1: Family education scenario
* Scenario 2: Program learning scenario

## 安装指南 Installation Guide

需要 Python3 环境  
Python3 is required

```shell
$ pip3 install wukongbaobao
```

## 使用说明 Instructions

```shell
$ python3 -m wukongbaobao [-h] [--level {1,2,3,4}] [--basic_cnt BASIC_CNT] [--open_cnt OPEN_CNT] [--algorithm {+,-}]
```
默认在ouput文件夹生成word文件，可以打印测验。  

level 1 对应 [0, 10] 区间的算法  
level 2 对应 [11, 30] 区间的算法  
level 3 对应 [31, 60] 区间的算法  
level 4 对应 [61, 100] 区间的算法
RandomStr 0.1.11
Generates a random string of your length choice.
Requires Python: >=3.8

# RandomStr

Generates a random string of your length choice.

## How to install:

To install this package, run ```pip install randomstr```

## Tutorial

You can use it's generate function to generate a random string, and you can choose it's length

```
import randomstr

randomstr.generate(6)
```

### For the full documentation, please visit https://qloha.github.io/randomstr
learnByHear 0.3
Learn a new language by hearing it
Requires Python: <=3.10.12,>=3.8

# Learn By Hearing - learn a new language by hearing it with text-to-speech

Learning a new language is much easier if you hear the same sentence in the new language and also a language you are familiar with.

That's what this package aims to help you do.  You input a text file in the language you're familiar with (which contains **a list of sentences in separate lines**), and you get an audio file that has the audio in the first language and also the second language.  Currently the languages supported are only those present in both `argostranslate` and `piper`.

This is essentially a wrapper running on top of three packages:
    * `argostranslate` for translation
    * `piper` for converting text to speech (TTS)
    * `ffmpeg` for combining the audio files

# Documentation

Only tested for Ubuntu 22.04 environment, but this should work on all Linux systems.  Best to use it in a virtual environment, as you should do with any Python package!

To install using pip, first download the `requirements.txt` file, and then: 
```
pip install -r requirements.txt
pip install learnbyhear
```

### You need to separately have **ffmpeg** already installed in the system!

## Considerations

- Dependencies are a bit heavy, so keep enough free space (~5 GB)
- Installation may take some time since dependencies must be downloaded
- First usage of any particular model will download that model
- I designed it such that it is meant to be used once a large text file, and then never.  Yes, this is also my excuse for not optimizing it ;)

## Supported languages

Currently the languages supported are only those present in both `argostranslate` and `piper`.

- Argos Translate: https://github.com/argosopentech/argos-translate#supported-languages
- Piper: https://github.com/rhasspy/piper#voices

## Voice models

Piper languages may have multiple models and also multiple speaking styles; check https://rhasspy.github.io/piper-samples/

Multiple models and speakers are supported!

## Example usage

English to German (this is the default, outputs stored in `tts/`):
```
learnbyhear text_EN.txt
```

English to German with three different output models (two of them actually a different speaker from the same model), 1 extra repetition (for each sentence you hear EN + DE_model_1 + DE_model_2 + DE_model_3 + DE_model_1 + DE_model_2 + DE_model_3), 1 second silence padding, and a specific output directory
```
learnbyhear text_EN.txt \
    --from_code en \
    --to_code de \
    --out_models de_DE-thorsten-high de_DE-thorsten_emotional-medium:4 de_DE-thorsten_emotional-medium:5 \
    --in_model en_GB-alan-medium \
    --repeats 1 \
    --padding 1.0 \
    --out_dir OUT_DIR/
```

List of models available on piper: https://rhasspy.github.io/piper-samples/