semvec/pypi-packages huggingface dataset:
versecbot-interface 0.4.2
Versioned interface for VerSecBot and its plugins
Requires Python: >=3.8

# VerSecBot Interface

This is a versioned interface for creating VerSecBot plugins.

To add a task for VerSecBot to handle, you'll need to create a plugin. The task should define a `should_act` function, which accepts a message and returns a boolean of whether this task should be activated. It should also define an `act` function, which accepts a message and performs the action.

```python
class SmileBack(Watcher):

    @abstractmethod
    def should_act(self, message: Message) -> bool:
        return ":)" in message.content

    @abstractmethod
    def act(self, message: Message):
        await message.channel.send(":)")
```

You can then add the task to the `hooks` list in `main.py`. Eventually this may be automated for simple hooks, but for now it'll need to be done manually.

```python
@client.event
async def on_ready():
    hooks.append(SmileBack())
```

The hook will then be evaluated for every message, and triggered when necessary.
deco_slack 0.0.4
deco_slack notifies you if a method has completed successfully or not.
Requires Python: <4.0,>=3.10

# decoslack

decoslack notifies you via Slack if a method has completed successfully or not.

## Description

- Notify Slack when a process starts, ends normally, or ends abnormally.
- Each notification can be set on or off.
- Support dynamic message formatting based on function results or errors.

## Configurations
Environment variables to set
- {DECO_SLACK_PREFIX}SLACK_TOKEN
  - Slack bot token that can be used with chat:write.public scope.
- {DECO_SLACK_PREFIX}SLACK_CHANNEL
  - Channel name to be notified without # (like notify_xxx not #notify_xxx)
- DECO_SLACK_PREFIX (optional)
  - Prefix for environment variables.
    - If not set, defaults to "".
    
## Example

```py
from deco_slack import deco_slack


@deco_slack(
    # These parameters are all optional
    start={
        "text": "start text",
        "title": 'start',
        "color": "good"
    },
    success={
        "text": "success text",
        "title": 'success',
        "color": "good"
    },
    error={
        "title": 'error',
        "color": "danger",
        "stacktrace": True # Set True if you need stacktrace in a notification
    },
)
def test1():
    print('test1')


# Dynamic message formatting example
@deco_slack(
    success={
        "text_formatter": lambda result: f"Process completed with result: {result}",
        "title": "Success",
        "color": "good"
    },
    error={
        "text_formatter": lambda e: f"Error occurred: {str(e)}",
        "title": "Error",
        "color": "danger",
        "stacktrace": True
    }
)
def process_data(data):
    result = data * 2
    return result

```

## Advanced Features

### Dynamic Message Formatting

You can customize notification messages based on function results or errors using `text_formatter` and `title_formatter`:

```python
@deco_slack(
    success={
        "text_formatter": lambda result: f"Process completed with result: {result}",
        "title_formatter": lambda result: f"Success: {result}",
        "color": "good"
    },
    error={
        "text_formatter": lambda e: f"Error details: {str(e)}",
        "color": "danger"
    }
)
def your_function():
    # Your code here
    pass
```

The formatters receive:
- `success`: The function's return value
- `error`: The exception object

This allows you to create more informative and context-aware notifications.
whisper-assistant 0.1.10
Voice transcription tool using Groq API with global hotkeys
Requires Python: >=3.10

# Whisper Assistant

Voice-to-text tool powered by Groq's Whisper API. Press a hotkey, speak, and get instant transcription.

## Get Started

Requires macOS and [uv](https://github.com/astral-sh/uv).

```bash
# Install portaudio (required for audio recording)
brew install portaudio

# Run the setup wizard
uvx whisper-assistant init
```

The wizard will:
1. Ask for your [Groq API key](https://console.groq.com/keys) (free)
2. Configure hotkeys and preferences
3. Start the background daemon

**Where files are stored** ([XDG Base Directory Specification](https://xdgbasedirectoryspecification.com/)):
| Path | Contents |
|------|----------|
| `~/.config/whisper-assistant/config.env` | API key, hotkeys, preferences |
| `~/.local/share/whisper-assistant/history/` | Audio recordings & transcriptions |
| `~/.local/state/whisper-assistant/logs/` | Log files |
| `~/.local/state/whisper-assistant/daemon.pid` | Daemon process ID |

## Usage

```bash
# Daemon control
whisper-assistant start
whisper-assistant stop
whisper-assistant restart
whisper-assistant status

# View logs
whisper-assistant logs
whisper-assistant logs --stderr

# Configuration
whisper-assistant config show
whisper-assistant config edit

# History
whisper-assistant history list
whisper-assistant history play 1      # play most recent recording
whisper-assistant history transcribe 1  # re-transcribe most recent

# Transcribe any audio file
whisper-assistant transcribe /path/to/audio.wav
```

**Default hotkeys:**
- `Ctrl+Shift+1` — Toggle recording (press to start, press again to stop and transcribe)
- `Ctrl+Shift+2` — Retry last transcription
- `Ctrl+Shift+3` — Cancel recording

**Config location:** `~/.config/whisper-assistant/config.env`

## Contributing

PRs welcome. For major changes, open an issue first.

```bash
git clone https://github.com/Futhark-AS/whisper_assistant.git
cd whisper_assistant
uv sync
uv run whisper-assistant --help
```

[MIT License](LICENSE)
fluent-telegrinder 1.0.6
Fluent i18n implementation for telegrinder
Requires Python: <4.0,>=3.14
Keywords: telegram, bot, fluent

<img src='https://github.com/Tarikul-Islam-Anik/Telegram-Animated-Emojis/blob/main/Animals%20and%20Nature/Owl.webp?raw=true' width='75' style='vertical-align:middle'>

# Fluent Telegrinder
[Fluent](https://projectfluent.org) i18n implementation for telegrinder

<p>
    <img alt="uv" src="https://img.shields.io/endpoint?url=https%3A%2F%2Fraw.githubusercontent.com%2Fastral-sh%2Fuv%2Fmain%2Fassets%2Fbadge%2Fv0.json&style=flat-square&labelColor=232226&color=6341AC&link=https%3A%2F%2Fastral.sh%2Fuv">
    <img alt="Ruff" src="https://img.shields.io/endpoint?url=https%3A%2F%2Fraw.githubusercontent.com%2Fastral-sh%2Fruff%2Fmain%2Fassets%2Fbadge%2Fv2.json&style=flat-square&labelColor=232226&color=6341AC&link=https%3A%2F%2Fastral.sh%2Fruff">
    <a href="https://github.com/equalred/fluent-telegrinder/blob/master/pyproject.toml"><img alt="Python versions" src="https://img.shields.io/python/required-version-toml?tomlFilePath=https://raw.githubusercontent.com/equalred/fluent-telegrinder/refs/heads/main/pyproject.toml&style=flat-square&logo=python&logoColor=fff&labelColor=black"></img></a>
    <a href="https://github.com/equalred/fluent-telegrinder/blob/master/pyproject.toml">
    <img alt="Project version" src="https://img.shields.io/badge/version-v1.0.5-black?style=flat-square&logo=python&logoColor=fff"></img></a>
</p>

<h2><img src='https://github.com/Tarikul-Islam-Anik/Animated-Fluent-Emojis/blob/master/Emojis/Objects/Pencil.png?raw=true' width='20' style='vertical-align:middle'> Usage</h2>

```shell
pip install fluent-telegrinder
```

```python
from telegrinder import API, Message, Telegrinder, Token
from telegrinder.node import as_node

from fluent_telegrinder import (
    DefaultLocaleSource,  # / UserLanguageSource 
    FluentConfig,
    Translator,
    TextEquals,
)

config = FluentConfig(
    folder="locales/",
    source=as_node(DefaultLocaleSource), # any node that returns str - source for locale
    default_locale="ru",
    replace_underscore=True, # i_love_telegrinder -> i-love-telegrinder
)
Translator.configure(config)

bot = Telegrinder(API(Token.from_env()))

@bot.on.message(TextEquals("hello", ignore_case=True)) # hello - i18n key (hello, привет)
async def on_hello(msg: Message, _: Translator):
    await msg.reply(_.hello_answer(user=msg.from_user.first_name))

bot.run_forever(skip_updates=True)
```

<h2><img src='https://github.com/Tarikul-Islam-Anik/Animated-Fluent-Emojis/blob/master/Emojis/Objects/Notebook.png?raw=true' width='20' style='vertical-align:middle'> License</h2>

Fluent Telegrinder is **[MIT licensed](https://github.com/equalred/fluent-telegrinder/blob/main/LICENSE)**
versecbot-reaction-limiter 0.2.0
VerSecBot plugin to restrict reactions based on user roles.
Requires Python: >=3.8

# VerSecBot - Reaction Limiter

This plugin instructs VerSecBot to only allow specific roles to add message reactions in a given channel. If a user without a matching role tries to react, VerSecBot will remove the reaction.

This was created to allow public polls with a subset of voters.

To use it, install the package and add the following block to your configuration, replacing values in <> with your desired values:

```
    [versecbot.plugins.reaction_limiter]
        enabled = true

    [[versecbot.plugins.reaction_limiter.handlers]]
        enabled = true
        channel_ids = [list of channels that should be restricted]
        roles_required = [list of roles that can react in specified channels]

    [[versecbot.plugins.reaction_limiter.handlers]]
        enabled = true
        channel_ids = [list of channels that should be restricted]
        roles_required = [list of roles that can react in specified channels]

```
Hello102 2025.12.1
Hello Python Calculator!
Requires Python: >=3.8
Keywords: hello, math, calcuator, string calculator, Lobster Thermidor

Project Title
=============

.. image:: https://example.com/your_banner_image.png
   :alt: Project Banner

A concise description of your project.

Installation
------------

To install this project, run:

.. code-block:: shell

   pip install Hello102

Usage
-----

Here's how to use the project:

.. code-block:: python

   import your_module
   your_module.some_function()

Contributing
------------

Instructions for contributing to the project.

License
-------

This project is licensed under the MIT License - see the LICENSE.txt file for details.
physical_ai_av 0.1.0
Developer kit for working with the NVIDIA Physical AI Autonomous Vehicles Dataset
Requires Python: >=3.12

# physical_ai_av

This repository contains a python developer kit and documentation (in the form of a [wiki](https://github.com/NVlabs/physical_ai_av/wiki) and interactive [notebooks](notebooks/)) for working with the [NVIDIA Physical AI Autonomous Vehicles Dataset](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles), one of the largest, most geographically diverse collections of multi-sensor data empowering AV researchers to build the next generation of Physical AI based end-to-end driving systems.

## Installation & Setup
```
pip install physical_ai_av
```
To use this package to access the data hosted on Hugging Face, you'll need to:
- [Create a Hugging Face account](https://huggingface.co/join) (if you don't have one already).
- Login and agree to the NVIDIA Autonomous Vehicle Dataset License Agreement visible at the top of the [PhysicalAI AV dataset card](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles).
- Create a [User Access Token](https://huggingface.co/docs/hub/en/security-tokens) (if you don't have one already) and choose a method for [authentication](https://huggingface.co/datasets/nvidia/PhysicalAI-Autonomous-Vehicles).
mlbi-bitool 0.1.25
Python interface to BioInfo tools for use in Google.Colab
Keywords: bioinformatics

## MLBI_at_DKU_Lib 
Some easy-to-use wrapper functions for GSEApy, CellPhoneDB, InferCNVpy and plotly.

## Contact
Send email to syoon@dku.edu for any inquiry on the usages.
standupbrain 1.0.4
What the heck did I do yesterday?
Requires Python: >=3.12

# standupbrain

`standupbrain` reads your Git commit and Jira activity and passes them to a local LLM that reminds you what the heck you did yesterday.

## Install

```bash
uv tool install standupbrain
```

## Usage

### Quickstart

* [Configure your GitHub credentials locally](https://docs.github.com/en/get-started/git-basics/set-up-git)
* Run `standupbrain init` to set up or reset your GitHub username, Git author email, Jira credentials, and preferred LLM model.
* Run `standupbrain recall` to generate your standup summary.
  * Run `--help` or see below for additional options
  * Can run against other users but you won't get local commits (of course)

### Help Commands

Check out the various `--help` options below:

<!-- CLI_HELP_START -->
## `standupbrain --help`

```text
Usage: standupbrain [OPTIONS] COMMAND [ARGS]...

  CLI for standupbrain, the tool to help you remember what you did yesterday

Options:
  --version  Show the version and exit.
  --help     Show this message and exit.

Commands:
  init    Initialize standupbrain with your preferred LLM and GitHub/Jira...
  recall  Generate a summary of what you did yesterday via GitHub/Jira ->...
```

## `standupbrain init --help`

```text
Usage: standupbrain init [OPTIONS]

  Initialize standupbrain with your preferred LLM and GitHub/Jira credentials

Options:
  --help  Show this message and exit.
```

## `standupbrain recall --help`

```text
Usage: standupbrain recall [OPTIONS]

  Generate a summary of what you did yesterday via GitHub/Jira -> LLM

Options:
  -e, --author-email TEXT     Git author email for searching local commits
  -d, --date [%Y-%m-%d]       Specific date to generate update for (YYYY-MM-
                              DD)
  --dry-run, --dry_run        Do not actually prompt the LLM, just query the
                              APIs and print the prompt
  -u, --github-username TEXT  GitHub account username for searching remotes in
                              GitHub
  -v, --verbose               High verbosity for debugging
  --help                      Show this message and exit.
```
<!-- CLI_HELP_END -->