semvec/pypi-packages huggingface dataset:
juice-moon-plasma-torus 0.1.2
Python package to calculate Jupiter Moon Plasma Torus intercept by a ray spacecraft-to-body
Keywords: esa, Juice, planetary, space, metrics, trajectory, assessment, crema, plasma, torus

# juice_moon_plasma_torus

## 1. Getting Started

Python package to calculate Jupiter Moon Plasma Torus intercept by a ray spacecraft-to-body.

Currently two different Command Line Interfaces are available:
 * [JUICE within Moon Plasma Torus Events](https://s2e2.cosmos.esa.int/confluence/display/SOCDEV/Generate+Juice+within+Moon+Plasma+Torus+Events)
 * [JUICE-Earth ray crossing Moon Plasma Torus Events](https://s2e2.cosmos.esa.int/confluence/display/SOCDEV/Generate+Juice-to-Earth+ray+crossing+Moon+Plasma+Torus+Events)

### 1.1 Installation

#### 1.1.1 Prerequisites
 
* Python 3.7 or higher.

#### 1.1.2 Setup

##### 1.1.2.1 Package installation 

From command line install the following packages using pip:

    pip install juice-moon-plasma-torus
percent-password 1.0
Pwgv (password generation and verification) генерация и проверка паролей
Requires Python: >=3.12

### Проверка
Прежде чем устанавливать пакет убедитесь что у вас установлит __Python__, ведя команду:
```
python -V
```
В результате должен вывести `Python 3.12.X`. Если у вас результат совпадает, то-гда Python существует на вашем системе, а если нет то вам нужно перейти [на официальный сайт Python](https://www.python.org/) скачать и установить в свою систему.

Нужно ещё проверить в наличий менеджер пакетов __pip__, вводим команду:
```
pip -V
```
Если будет в результате `pip 24.2 from <Тут должен находится путь менеджеру пакетов>` то тогда вы готовы к установки пакета __percent_password__.

> Посути менеджер __pip__ он устанавливается автомотически при установки __Python__ вашу систему, но для надежности, нужно всётаки проверять каждый раз при установки __Python__.

### Загрузка percent_password
Просле проверки наличий __Python__ и __менеджер пакетов pip__. Мы можем загрузить пакет __percent_password__ одной командой:
```
pip install percent_password
```

После установки можете использовать покет __percent_password__
ипортировать в свой проект:
```
import percent_password
```
Или ипротировать класс `Pwgv`:
```
from percent_password import Pwgv
```
paita 0.1.13
paita - Python AI Textual Assistant
Requires Python: >=3.8
Keywords: ai, aws, bedrock, chat, chatgpt, openai, python, textual

# Paita - Python AI Textual Assistant
<img src="https://github.com/villekr/paita/blob/main/imgs/paita.jpg?raw=true" width="800">

Paita is textual assistant for your terminal that supports multiple AI Services and models.

## Key Features
- **Supports Multiple AI Services:** Paita integrates with a variety of AI services through the [LangChain](https://python.langchain.com) library. If AI service is compatible with LangChain then it can be used also with Paita.
- **Textual User Interface on your terminal:** Paita is based on [Textual](https://textual.textualize.io/) and provides a sophisticated user interface right within your terminal, combining the complexity of a GUI with console simplicity.                                                                                       
- **Cross-Platform Compatibility:** Paita is compatible with Windows, macOS, and Linux systems across most terminals; if Python runs in your environment and Textual supports it, then Paita will work.
- **Supports Retrieval-Augmented Generation (RAG):** Paita supports local vectorstore (Chroma) and crawling web page content.

### Supported AI Services
* OpenAI
* AWS Bedrock
* Ollama (local models)

## Getting Started

### Prerequisites
- Python 3.8.1+
- Access to AI Service and configured in terminal

### Installation and running

Install using pip (or pipx)
```
pip install paita
```

Run and enjoy!
```
paita
```

### Some keyboard shortcuts

Paita is textual ui application so using keyboard shortcuts is recommended:
* Use `tab` and `shift`+`tab` to navigate between input field, send-button and question/answer boxes
* While question/answer box is focus use `enter` to "focus-in" and `esc` to "focus-out"
* Use `c` to copy content from question/answer box
* Contextual keyboard shortcuts are shown at the bottom of the UI

### Configuring AI Service(s) and model access

#### OpenAI

OpenAI usage requires valid api key in environment variable.
```
export OPENAI_API_KEY=<OpenAI API Key>
```

#### AWS Bedrock

Enable AI model access in AWS Bedrock. Configure aws credential access accordingly.

#### Ollama

Ollama enables running chat models locally. 

Install [ollama](https://ollama.com) for operating system or use official (docker image)[https://hub.docker.com/r/ollama/ollama] 

Once ollama installed pull desired [model](https://ollama.com/library) from a registry e.g.
```
ollama pull llama3
```

By default paita connects to local Ollama endpoint. Optionally you can configure endpoint url with env variable:
```
export OLLAMA_ENDPOINT=<protocol>://<ollama-host-address>:<ollama-host-port>
```

## Feedback

* [Issues](https://github.com/villekr/paita/issues)
* [Discussion](https://github.com/villekr/paita/discussions)