semvec/pypi-packages huggingface dataset:
legendarycli 0.0.8
This is a simple CLI to show my CV and resume

# legendaryCLI

A command-line interface for the Simple CLI project using :
1- Click, Python, termcolor, pyfiglet, tqdm


## Installation

This is a simple CLI to show my CV and resume



## Installation

pip install legendarycli


## Usage


legendarycli --help [HELP]

* * * * *

legendarycli --gh [Navigate you to my Github Profile]

* * * * *

legendarycli --li [Navigate you to my Linkedin Profile]

* * * * *

legendarycli --cv --[Argument*/OS*/] [Specify which OS [Mac Or Win] you are using]

* * * * *

legendarycli --about [Sample Text about me :) ]



## Contributing

Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

Please make sure to update tests as appropriate.
hkkkel9 1.0.0
Tugas kelompok 9
Requires Python: >=3.6

<div style="text-align: center;">
    <h1>Tugas Dasprog kelompok 9</h1>
</div> <br>
<h2>Membuat program hitung honor karyawan PT.STAY COOL</h2>
<h3>Anggota kelompok :</h3>
<ul>
    <li>Muhamad Dafa Prasetya <sup>12220563</sup></li>
    <li>Devi Alvandi <sup>12220453</sup> </li>
    <li>Dimas Ajie <sup>12220563</sup> </li>
    <li>Chairil Fajri <sup>12220563</sup> </li>
    <li>Arie Sutiawan <sup>12221429</sup> </li>
</ul>
<h1>Jangan lupa followw!!!</h1>
ptxo 0.0.2
PyTorch Op Enhanced Exceptions
Requires Python: >=3.7

# PTXO - PyTorch Op Enhanced Exceptions

## Installation

pip install ptxo

## Synopsis

```python

import torch
import ptxo

conv = torch.nn.Conv1d(5, 5, 10)
inp = torch.zeros([5, 100])

conv(inp)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "...site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "...site-packages/torch/nn/modules/conv.py", line 263, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "...site-packages/torch/nn/modules/conv.py", line 259, in _conv_forward
    return F.conv1d(input, weight, bias, self.stride,
RuntimeError: Expected 3-dimensional input for 3-dimensional weight [5, 5, 10],\
        but got 2-dimensional input of size [5, 100] instead

# Turn on the exception interceptor
ptxo.on()

conv(inp)
  File "<stdin>", line 1, in <module>
  File "...site-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
    [ptxo]: torch.nn.modules.conv.Conv1d(input=[5,100]:float32:cpu)
  File "...site-packages/torch/nn/modules/conv.py", line 263, in forward
    return self._conv_forward(input, self.weight, self.bias)
  File "...site-packages/torch/nn/modules/conv.py", line 259, in _conv_forward
    return F.conv1d(input, weight, bias, self.stride,
RuntimeError: Expected 3-dimensional input for 3-dimensional weight [5, 5, 10],\
        but got 2-dimensional input of size [5, 100] instead

ptxo.off()
```

The backtrace is almost identical, but there is one extra line, which shows
argument names and values of the PyTorch function which caused an exception.
Tensor values are shown as shape:dtype:device strings.

`[ptxo]: torch.nn.modules.conv.Conv1d(input=[5,100]:float32:cpu)`

See
[https://github.com/hrbigelow/ptxo](https://github.com/hrbigelow/ptxo)
for more.
koml 1.0.0
누구나 쉽게 한국어챗봇을 만들 수 있게

# KoML

<br>

## Introduction 

[AIML](https://en.wikipedia.org/wiki/Artificial_Intelligence_Markup_Language)은 누구나 쉽게 챗봇을 만들 수 있게끔 도와주는 언어에요. AIML을 이용한 챗봇은 [Loebner Prize](https://en.wikipedia.org/wiki/Loebner_Prize) 등 세계적인 챗봇 대회에서 우승을 하기도 했고 딥러닝 기반의 챗봇이 널리 쓰이는 요즘도 Rule-based 처리를 할 때 널리 사용되고 있어요.
<br>
하지만 string match 기반의 AIML로 한국어를 처리하기에는 어려움이 있었어요. 한국어는 영어와 달리 교착어여서 하나의 의미를 전달하는데 여러가지 경우의 수가 나올 수 있어서요. 예를 들어 '너'가 '점심'에 '무슨음식'을 '먹었냐' 라고 물어보고 싶을 때 영어로는 이렇게 물어보는 경우만 존재하지만
```
What did you eat for lunch?
```

우리 한국어는 표현할 수 있는 가짓수가 너무 많아요.
```
너 점심 뭐 먹었어?
너 점심 뭐 먹었니?
너 점심 뭐를 먹었니?
너 점심에 뭐를 먹었니?
너는 점심에 뭐를 먹었니?
.
.
```

<br>

**KoML** 을 이용해서 챗봇을 만들면 이렇게 만들수 있어요.

```xml
<koml>
  <case>
    <pattern>너_j 점심_j 뭐_j 먹었_e?</pattern>
    <template>로봇이 밥을 왜먹음</template>
  </case>
<koml>
```
```
<< 너는 점심에 뭐 먹었니?
>> 로봇이 밥을 왜먹음
```

<br>

## Installation

```
pip install koml
```

<br>

## Test
```xml
<!-- koml_test.xml -->
<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE xml>
<koml>
  <case>
    <pattern>너_j 점심_j 뭐_j 먹었_e?</pattern>
    <template>로봇이 밥을 왜먹음</template>
  </case>
</koml>
```
```python
# main.py
from koml import KomlBot

bot = KomlBot()
bot.learn(['getting_started.xml'])
bot.converse()
```
<br>

### 결과
```
<< 너는 점심에 뭐 먹었니?
>> 로봇이 밥을 왜먹음
```

<br>

## Usage

[**공식문서**](https://koml-docs.readthedocs.io/en/latest/) 를 참조해주세요!

URL: https://koml-docs.readthedocs.io/en/latest/