semvec/pypi-packages huggingface dataset:
nonebot-plugin-arxivRSS 0.2.0
Plugin of Nonebot2. Subscribe and push Arxiv RSS daliy.
License: MIT
Requires Python: >=3.8

<div align="center">
  <a href="https://v2.nonebot.dev/store"><img src="https://github.com/A-kirami/nonebot-plugin-template/blob/resources/nbp_logo.png" width="180" height="180" alt="NoneBotPluginLogo"></a>
  <br>
  <p><img src="https://github.com/A-kirami/nonebot-plugin-template/blob/resources/NoneBotPlugin.svg" width="240" alt="NoneBotPluginText"></p>
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# nonebot-plugin-arxivRSS

_✨ 推送arxiv上每日最新论文的插件 ✨_


<a href="./LICENSE">
    <img src="https://img.shields.io/github/license/LuckySJTU/nonebot-plugin-arxivRSS.svg" alt="license">
</a>
<a href="https://pypi.python.org/pypi/nonebot-plugin-arxivRSS">
    <img src="https://img.shields.io/pypi/v/nonebot-plugin-arxivRSS.svg" alt="pypi">
</a>
<img src="https://img.shields.io/badge/python-3.8+-blue.svg" alt="python">

</div>


## 📖 介绍

这个插件调用arxiv的RSS订阅源，用于每天定时推送arxiv当天的新论文。目前仅支持私聊。

## 💿 安装

<details open>
<summary>使用 nb-cli 安装</summary>
在 nonebot2 项目的根目录下打开命令行, 输入以下指令即可安装

    nb plugin install nonebot-plugin-arxivRSS

</details>

<details>
<summary>使用包管理器安装</summary>
在 nonebot2 项目的插件目录下, 打开命令行, 根据你使用的包管理器, 输入相应的安装命令

<details>
<summary>pip</summary>

    pip install nonebot-plugin-arxivRSS
</details>
<details>
<summary>pdm</summary>

    pdm add nonebot-plugin-arxivRSS
</details>
<details>
<summary>poetry</summary>

    poetry add nonebot-plugin-arxivRSS
</details>
<details>
<summary>conda</summary>

    conda install nonebot-plugin-arxivRSS
</details>

打开 nonebot2 项目根目录下的 `pyproject.toml` 文件, 在 `[tool.nonebot]` 部分追加写入

    plugins = ["nonebot_plugin_arxivRSS"]

</details>


## 🎉 使用

⚠️**目前仅支持私聊**⚠️

首先使用`arxiv set <hh> <mm>`设定每日推送时间。

然后使用`arxiv add <category>`添加您关注的领域。`<category>`是arxiv官方对论文领域的分类，例如`cs`代表Computer Science，`cs.CL`代表Computation and Language。**`<category>`可以是单独的领域，也可以是多个领域，领域间使用空格分开。**[此处](https://arxiv.org/category_taxonomy)可以查看所有领域。

此时您已经完成了基本的设置，您将会在每日`<hh>:<mm>`收到来自arxivRSS的当日推送。

您还可以通过`arxiv push [category]`指令立刻获取arxivRSS的当日推送。如果不提供`[category]`，则推送您订阅中的所有领域。

**新增功能**

新增了关键词功能，会从标题、作者、摘要中匹配关键字，如果包含关键字，相关论文的编号会在最后给出。

您可以通过`arxiv kw`查看对应关键字的增删改指令。

### 所有指令

`arxiv` 显示所有指令

`arxiv add <category>` 添加`<category>`至您的订阅。

`arxiv del <category>` 从您的订阅中删除`<category>`。

`arxiv set <hh> <mm>` 设定您的推送时间为hh:mm，注意是空格不是:。

`arxiv cancel` 取消订阅。

`arxiv show` 查看您的订阅类别和推送时间。

`arxiv list` 查看所有可用的领域。

`arxiv push [category]` 立即获取`[category]`中所有类别的当日推送。如果`[category]`没有指定，那么会尝试推送您订阅中的所有领域。

`arxiv kw` 查看有关关键字的指令

`arxiv kw add <keyword>` 添加一个关键字。注意，一次只能添加一个关键字，可以包含空格。

`arxiv kw show` 查看所有关键字

`arxiv kw del <keyword>` 删除一个关键字。注意，一次只能删除一个关键字，可以包含空格。

`arxiv kw cancel` 删除所有关键字。注意，此操作不可逆。

### 已知的问题

由于Arxiv官方的更新时间是GMT的每日0点之后，因此在北京时间的每日0点-8点，获取的仍然是前一天的内容；北京时间的每日8点之后，会存在一段时间的空白期，无法获取任何论文内容。

解决这一问题的办法为，使用国内的镜像源。

这一方法的缺点在于，获取的论文链接域名为`cn.arxiv.org`，无法访问。当然了，只需要去掉前缀`cn.`就可以正常访问了，但是会多一个步骤。

- [x] 已更新自动切换国内源和对国内链接的处理

### 效果图

![preview](./preview.jpg)

![preview](./preview2.png)
promptcli 2.1.0
A command line application to help wrap the OpenAI ChatGPT api.
License: MIT
Requires Python: >3.5
Keywords: cli,developer tools,productivity,openai,chatgpt

[![Actions Status](https://github.com/raiyanyahya/prompt/workflows/Build%20Test/badge.svg)](https://github.com/raiyanyahya/prompt/actions) [![Actions Status](https://github.com/raiyanyahya/prompt/workflows/Package%20Release/badge.svg)](https://github.com/raiyanyahya/prompt/actions) [![Quality Gate Status](https://sonarcloud.io/api/project_badges/measure?project=raiyanyahya_prompt&metric=alert_status)](https://sonarcloud.io/summary/new_code?id=raiyanyahya_prompt) [![CodeQL](https://github.com/raiyanyahya/prompt/workflows/CodeQL/badge.svg)](https://github.com/raiyanyahya/prompt/actions?query=workflow%3ACodeQL) [![Codacy Badge](https://app.codacy.com/project/badge/Grade/05a21e6c4ed4494ba39e2ee43b2327d2)](https://www.codacy.com/gh/raiyanyahya/prompt/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=raiyanyahya/prompt&amp;utm_campaign=Badge_Grade) [![](https://img.shields.io/badge/python-3.6+-blue.svg)]

# Prompt 🥝 - A ChatGPT CLI

![](https://gifyu.com/images/demo.gif)

`prompt` is designed to provide users a command-line interface for the ChatGPT API, which uses OpenAI's GPT language model to generate text based on user input.

The application helps you start a `session` with ChatGPT so that the `context` is preserved and longer conversions with contexts are considered. The user's prompts and the responses are sent back to ChatGPT everytime.

The ChatGPT api usage depends on the number of tokens used and it is important that you use the tokens wisely. After a prompt has been answered the application will resend the last prompt and answer in the next prompt, this makes sure you can have a continued conversion with ChatGPT ` much like using ChatGPT in a single chat session `. This makes the token count larger and larger as you continue to chat. If you are not concerned with context use the `--clear` flag which will save your token usage. Use the `model` option to add 

I hope you find it useful.


## Configuration

The application requires you to have an api token to query the OpenAI's ChatGPT api. You can read about and get it here https://platform.openai.com/account/api-keys .

## Installation

Install the prompt python package directly from pypi. 

```console
  pip install promptcli
```
I would recommend using pipx instead of pip to install cli applications on you machine.

## Usage

```console
Usage: prompt [OPTIONS] COMMAND [ARGS]...

  🥝 A command line application to interact with OpenAI's ChatGPT.

Options:
  --version     Show the version and exit.
  --clear    🌊 Clear the context each round of chat
  --model    🔄 The OpenAI model type.
  --help        Show this message and exit.

Commands:
  update  🔐 Update the OpenAI API key.
```


Please feel to create issues or request for features. More options and commands will be added to the application in the near future.
cnsr 0.0.3
Lab code package for the CNSR lab at Heidelberg University
License: MIT
Requires Python: >=3.9

# Welcome to the CNSR Lab Code Base

[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![GitHub Workflow Status](https://img.shields.io/github/actions/workflow/status/ssciwr/cnsr/ci.yml?branch=main)](https://github.com/ssciwr/cnsr/actions/workflows/ci.yml)
[![PyPI Release](https://img.shields.io/pypi/v/cnsr.svg)](https://pypi.org/project/cnsr)
[![Conda Version](https://img.shields.io/conda/vn/conda-forge/cnsr.svg)](https://anaconda.org/conda-forge/cnsr)

This repository provides Jupyter notebook templates required to perform analysis on the data created during experiments at the [CNSR core facility of Heidelberg University](https://cnsr.uni-heidelberg.de/).

## Installation

The recommended installation for the `cnsr` Python package is via Conda:

```bash
conda install -c conda-forge cnsr
```

## Usage

After installing `cnsr`, start JupyterLab either via the command line or via the Jupyter App launcher UI on Windows:

```bash
jupyter lab
```

In the JupyterLab launcher, you will see a shortcut for each analysis task at CNSR. Clicking on this notebook will create a copy of the respective analysis notebook in the current working directory.

## Acknowledgments

The conda packaging of this repository was implemented by the [Scientific Software Center at Heidelberg University](https://ssc.uni-heidelberg.de).