semvec/pypi-packages huggingface dataset:
botank 0.0.5
A library for automated testing of Alice skills
License: MIT

# botank
It is a tool for automated testing of Alice skills 
(and maybe other chat bots in the future).

We shoot random requests into your bot and look how it copes with them.

The tool is written in Python, but it calls the bots through a web hook, 
therefore the bots can be written in any language or without language at all.

Links: [GitHub](https://github.com/avidale/botank), 
[PyPI](https://pypi.org/project/botank/).

Read this in other languages: 
[English](https://github.com/avidale/botank/blob/master/README_EN.md), 
[Русский](https://github.com/avidale/botank).

## The essentials
To install the tool you need Python>=3.6 and the `pip` package manager 
(or analogs). 

Installation:
```commandline
pip install botank
```

Usage:
```commandline
python -m botank http://localhost:5000/alice/ -n 100 -o results.txt
```
When you run it like this, 
*botank* sends to `http://localhost:5000/alice/` 
100 Alice-like random requests into your skill, 
and saves the results to the file `results.txt`.
emacnn 0.0.1
A CLI for training a neural network on a specific YouTube channel's videos.
License: MIT
Requires Python: >=3.7

# EmacNN
EmacNN is a CLI for training a neural network to generate YouTube video scripts using YouTube's automated closed captions for a specific channel's videos.

The name, Emac, refers ostensibly to one of [Eric McHenry's]((https://www.youtube.com/c/GodofKings1)) preferred nicknames. His long, rambling, often circuitous, and long ["vlogs"]((https://www.youtube.com/c/GodofKings1)) inspired this project.

[![GitLab pipeline](https://img.shields.io/gitlab/pipeline/tedtramonte/emacnn)](https://gitlab.com/tedtramonte/emacnn/builds)
[![PyPI - Downloads](https://img.shields.io/pypi/dm/emacnn)](https://pypi.org/project/emacnn/)
[![PyPI - License](https://img.shields.io/pypi/l/emacnn)](https://choosealicense.com/licenses/mit/)
[![PyPI - Version](https://img.shields.io/pypi/v/emacnn)](https://gitlab.com/tedtramonte/emacnn/-/releases)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/emacnn)](https://gitlab.com/tedtramonte/emacnn)
[![PyPI - Wheel](https://img.shields.io/pypi/wheel/emacnn)](https://gitlab.com/tedtramonte/emacnn)
[![PyPI - Status](https://img.shields.io/pypi/status/emacnn)](https://gitlab.com/tedtramonte/emacnn)

## Installation
The best way to install EmacNN is to use Pip.

```bash
pip install emacnn
```

## Usage
```bash
# Display help text
emacnn --help
```

## Contributing
Merge requests are welcome after opening an issue first. Please make sure to update tests as appropriate.

### Development
Install in a virtual environment with:

```bash
python -m venv env
pip install -e .
```

To improve model training time, it is reocmmended to use CUDA if your GPU is supported.
1. Refer to the [Keras requirements](https://www.tensorflow.org/install/gpu).
2. [Install CUDA Toolkit](https://developer.nvidia.com/cuda-toolkit-archivE) matching Keras requirement
3. [Install cuDNN](https://developer.nvidia.com/rdp/cudnn-archive) matching Keras requirement