semvec/pypi-packages huggingface dataset:
bmgen 2023.5.0b0
Broken Mouse Studios' build solution
Requires Python: >=3.10

# bmgen - Broken Mouse Studios' build solution

## DISCLAIMER

This project is currently in it's beta phase!

It needs to be cleaned up and does not yet have it's full set of features. You may quickly hit it's limits.

You should expect API changes and are welcome to give feedback via <https://git.brokenmouse.studio/bms/bmgen/issues>

## Features

- build scripts written in Python
- incremental builds
- temporary build directories
- colorful and easy to read output
- simple build commands

## Installation

- Install bmgen via `pip install bmgen` or `python3 -m pip install bmgen`

## Building a simple C project

This example shows a script which builds two files named `main.c` and `game.c` into a binary named `mygame` with `SDL2`.

The directory structure created by bmgen will look like this:

```plain
- bin/
  - dbg/
    - obj/
      - main.o
      - game.o
    - mygame
```

The following is a breakdown of the script.

1. First import the `clang` command:

```python
from bmgen.commands.clang import clang
```

2. Then set the base output directory and tell bmgen to create the base, variant and the `clang` command's object directory:

```python
inst.base_output_dir = 'bin'
inst.update_output_dir()
clang.update_object_dir()
```

3. Build the program via `clang`:

```python
clang('mygame', ['main.c', 'game.c'], ['sdl2'])
```

The final `bmgen.py` looks like this:

```python
from bmgen.commands.clang import clang

inst.base_output_dir = 'bin'
inst.update_output_dir()
clang.update_object_dir()

clang('mygame', ['main.c', 'game.c'], ['sdl2'])
```

Building the program is now as easy as running `bmgen` in your terminal!

## License

© Broken Mouse Studios 2023<br>
<https://brokenmouse.studio>

This software and it's accompanying files are licensed under the *Mozilla Public License Version 2.0*.

For the license's contents, see [LICENSE](LICENSE) or go to <https://mozilla.org/MPL/2.0/>.

By submitting patches or merge/pull requests, you grant Broken Mouse Studios the permission to use, copy, modify, distribute, publish and/or relicense the contributions you have made to the project.
GPTAgent 0.0.17
A small and simple way to generate a ChatGPT agent
Requires Python: >=3.7

### ChatGPT Agente

## Instalação

Basta instalar o pacote via pip
```
pip install GPTAgent
```

Gerar uma Key no site da OpenAI para desenvolvedores e colocar no arquivo **chat_key.json**

```
{"api_key": "coloque_aqui_sua_api_key_da_OpenAI"}
```

Exemplo:

```
from GPTAgent.GPTAgent import GPTAgent

agente = GPTAgent(name="Bob", estilo="Você é engraçado e positivo.")

print(agente.perguntar("Bom dia!"))
```
PSRemoter 1.0.0
Powershell remote client tool for Python
Requires Python: >=3.9
Keywords: Powershell,remote,client,commands,Windows

# PSRemoteExecuter
## _Suitable only for Windows platforms_

This package will help you to execute remote PowerSell script on other Windows platforms in your domain. 

## Features

- Execute local PowerShell scripts
- Execute remote PowerShell scripts (Using invoke-command PS command)


##Using
install PSRemoter using pip:<br>
pip install PSRemoter

powershell=False (default) execute as batch script
```
from psremoter.connector import Execute
exec= Execute(hostname="hostname", username="username" , password='password', domain='myDomain', command="hostname", powershell=True)

#Execute command on remote host
exec.remote_execution()

#Read execution status
print(exec.status) #True

#Read return code
print(exec.return_code) #0 

#Read console output
print(exec.output) #DnsServer01
````
python-voice-assistant 1.0.1
Create your own voice assistant like jarvis
Requires Python: >=3.10,<4.0

# python_voice_assistant

<p align="center">
      <img src="https://i.ibb.co/MZ3PgBR/python-voice-assistant.png" alt="Project Logo" width="726">
</p>

<p align="center">
    <img src="https://img.shields.io/badge/Python-3.10-blueviolet" alt="Python Version">
    <img src="https://img.shields.io/pypi/v/python-voice-assistant?color=blue&label=Version" alt="Package version">
    <img src="https://img.shields.io/badge/License-MIT-success" alt="License">
</p>

## About

Python package for creating your own voice assistants like Siri or Jarvis

## Installation

```
pip install python_voice_assistant
```

## Documentation

- [Русский](https://github.com/zeph1rrinc/python_voice_assistant/tree/master/docs/ru_doc.md)
- [English](https://github.com/zeph1rrinc/python_voice_assistant/tree/master/docs/en_doc.md)

## CONTRIBUTORS

- [Zeph1rr](https://github.com/Zeph1rr) (Developer)

## License

Project Python voice assistant is distributed under the MIT license.
opentrain 0.1.0
🚂 Fine-tune OpenAI models for text classification, question answering, and more
Requires Python: <3.11,>=3.8

<div align="center">
  <h1>opentrain</h1>
  <p>
    <em>🚂 Fine-tune OpenAI models for text classification, question answering, and more</em>
  </p>
</div>

---

`opentrain` is a simple Python package to fine-tune OpenAI models for task-specific purposes such as text classification, token classification, or question answering.

More information about OpenAI Fine-tuning at https://platform.openai.com/docs/guides/fine-tuning.

## 💻 Usage

### 📦 Data management

```python
import openai
from opentrain import Dataset

openai.api_key = "<ADD_OPENAI_API_KEY_HERE>"

dataset = Dataset.from_file("data.jsonl")
dataset.info
dataset.download(output_path="downloaded-data.jsonl")
```

### 🦾 Fine-tune

```python
import openai
from opentrain import Train

openai.api_key = "<ADD_OPENAI_API_KEY_HERE>"

trainer = Train(model="ada")
trainer.train(
    [
        {
            "prompt": "I love to play soccer ->",
            "completion": " soccer",
        },
        {
            "prompt": "I love to play basketball ->",
            "completion": " basketball",
        },
    ],
)
```

### 🤖 Predict

```python
import openai
from opentrain import Inference

openai.api_key = "<ADD_OPENAI_API_KEY_HERE>"

predict = Inference(model="ada:ft-personal-2021-03-01-00-00-01")
predict.predict("I love to play ->")
```

## ⚠️ Warning

Fine-tuning OpenAI models via their API may take too long, so please be patient. Also, bear in mind
that in some cases you just won't need to fine-tune an OpenAI model for your task.

To keep track of all the models you fine-tuned, you should visit https://platform.openai.com/account/usage, 
and then in the "Daily usage breakdown (UTC)" you'll need to select the date where you triggered the
fine-tuning and click on "Fine-tune training" to see all the fine-tune training requests that you sent.

Besides that, in the OpenAI Playground at https://platform.openai.com/playground, you'll see a dropdown
menu for all the available models, both the default ones and the ones you fine-tuned. Usually, in the 
following format `<MODEL>:ft-personal-<DATE>`, e.g. `ada:ft-personal-2021-03-01-00-00-01`.
sqlitemanager 0.7.2
Handler object for easy sqlite manipulation
Requires Python: >=3.7

# SQLiteManager
Use a convenient SQLiteHandler object to manipulate SQLite(3) databases.

## Version

### 0.7
0.7.2
- added get_latest_record function

0.7.1
- added Record.values (list of values)

0.7.0
- Completely redone, not backwards compatible at all
- Contains most of the previous functionality

### 0.6
0.6.1
- extra logging for printing path

0.6.0
- Extension type can be given to the handler to discern between .sqlite and .sqlite3
- changed many functions to depend on the location variables of the handler class (path, filename, extension)
make sure the extension variable does not miss the dot!
- removed redundent steps or functions, mostly from the database class and added to the handler
- added some more comments for functions
- other fixes

### 0.5.3
- Removed some print statements that clutter the terminal during debugging
- removed some redundent import statements

### 0.5.0
- Added test_gui for testing the library

### 0.3.x
- Adds handler.py with a SQLiteHandler object
- moves support methods to helpers.py

### 0.2.x
- Basic objects in database.py for Database, Tables and Records

## Install
```
pip install sqlitemanager
```

## How to
Primarily use the handler to do database manipulation for you instead of directly edit the data objects. The handler is built to make manipulation of the objects even simpler. The Database object contains the actual connection to the database.

See the [example.py](example.py) file for a list of examples of functionality.
https://github.com/Michael-Yongshi/SQLiteManager/blob/master/unit_tests.py

The sqlite handler is aware of the working directory, if paths are not given it will work from the current working directory.
It prints the paths its using, so watch closely that its called from the correct one.

## Tests
Run test_handler.py in order to test the package.

# Build

## Pypirc file
Create a .pypirc file in home directory

```
[distutils]
index-servers=
    pypi
    test

[test]
repository = https://test.pypi.org/legacy/
username = __token__
password = <PyPI token>

[pypi]
repository = https://upload.pypi.org/legacy/
username = __token__
password = <PyPI token>
```

## Distributions

```
python3 -m pip install --upgrade build && python3 -m build
```

## Upload

```
python3 -m pip install --upgrade twine && python3 -m twine upload --repository pypi dist/*
```

## Licence

Licensed under GPL-3.0-or-later, see LICENSE file for details.

Copyright © 2020 Michael-Yongshi.

This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.