semvec/pypi-packages huggingface dataset:
livekit-plugins-uplift 0.2.9
Agent Framework plugin for voice synthesis with Uplift AI.
Requires Python: >=3.9
Keywords: audio, livekit, realtime, tts, uplift, video, webrtc

# LiveKit Plugins - Uplift

This plugin provides TTS integration for [Uplift AI](https://upliftai.org) into the LiveKit Agent Framework. You can also find official documentation of [Uplift API](https://docs.upliftai.org/introduction)

## Installation

```bash
pip install livekit-plugins-uplift
```

## Pre-requisites

You'll need an API key from UpliftAI. It can be set as an environment variable: `UPLIFT_AI_API_KEY`

## Urdu Script Requirements

The Uplift TTS is designed to work with Urdu script. The TTS should only receive text in Urdu script - not Roman Urdu. This can be achieved via basic prompt engineering to ensure your LLM generates output in proper Urdu script.

### Example

```python
from livekit.plugins import uplift

async def entrypoint(ctx: JobContext):
    initial_ctx = llm.ChatContext().append(
        role="system",
        text=(
            "You're an Urdu speaking livebot on a LiveKit call. "
            "No matter what, you should generate Urdu responses, in urdu script, no matter what. "
            "It should not be in Roman Urdu, it should be in Urdu script. "
        ),
    )

    await ctx.connect(auto_subscribe=AutoSubscribe.AUDIO_ONLY)

    assistant = VoicePipelineAgent(
        vad=silero.VAD.load(),
        stt=openai.STT(language="ur"),
        llm=openai.LLM(),
        tts=uplift.TTS(voice="v_30s70t3a"),
        chat_ctx=initial_ctx,
        fnc_ctx=fnc_ctx,
    )
    assistant.start(ctx.room)
    await assistant.say("ہیلو، آپ کیسے ہیں؟", allow_interruptions=True)
```
ishikawa 0.0.5
Ishikawa is a library used to draw a fish (also known as ishikawa) diagram
Requires Python: >=3.0

# Ishikawa: package to design ishikawa diagram based on matplotlib

## Project description

Author: Kaike Sa Teles Rocha Alves (adapted from matplotlib)

Ishikawa: package to design ishikawa diagram based on matplotlib developed by Kaike Alves adapted from matplotlib (https://matplotlib.org/stable/gallery/specialty_plots/ishikawa_diagram.html). 

    Author: Kaike Sa Teles Rocha Alves (PhD)
    Email: kaikerochaalves@outlook.com or kaike.alves@estudante.ufjf.br


Github repository: https://github.com/kaikerochaalves/Ishikawa.git

Cite:

## Description:

Ishikawa: package to design ishikawa diagram based on matplotlib.

## Instructions

To install the library use the command: 

    pip install ishikawa

To import type:

    from ishikawa.diagram import Ishikawa

Hyperparameters:

    data : dict
    A dictionary of problem categories and their associated causes.

    figsize : tuple, optional
    The size of the plot figure.

Example of Ishikawa:

    from ishikawa.diagram import Ishikawa

    # Define categories
    categories = {
        'Method': ['Time consumption', 'Cost', 'Procedures', 'Inefficient process', 'Sampling'],
        'Machine': ['Faulty equipment', 'Compatibility'],
        'Material': ['Poor-quality input', 'Raw materials', 'Supplier', 'Shortage'],
        'Measurement': ['Calibration', 'Performance', 'Wrong measurements'],
        'Environment': ['Bad conditions'],
        'People': ['Lack of training', 'Managers', 'Labor shortage', 'Procedures', 'Sales strategy']
    }

    # Create an instance of the diagram
    fishbone_diagram = Ishikawa(categories)
    
    # Call the draw method to generate the plot
    fishbone_diagram.draw()

    # Show the plot
    fishbone_diagram.plot_and_save()

Note: Do not use more than 6 categories or 5 causes per category. Otherwise you are going to have issues with formatting.

### Extra information

The fuzzy models are quite fast, but the genetic and ensembles are still a bit slow. If you think you can contribute to this project regarding the code, speed, etc., please, feel free to contact me and to do so.

Code of Conduct:

Please read the Code of Conduct for guidance.

Call for Contributions:

The project welcomes your expertise and enthusiasm!

Small improvements or fixes are always appreciated. If you are considering larger contributions to the source code, please contact by email first.
pyfibot 1.0.1
A Python IRC bot with modular plugin system
Requires Python: >=3.8

# Pyfibot is back

Thanks to the power of Claude Code, I was able to port the code to python3

- [uv](https://github.com/astral-sh/uv) is used to manage packages
- [Taskfiles](https://taskfile.dev/) instead of Makefiles

---

[![Python application](https://github.com/lepinkainen/pyfibot/actions/workflows/python-app.yml/badge.svg)](https://github.com/lepinkainen/pyfibot/actions/workflows/python-app.yml)

## pyfibot

A Python IRC-bot made using the [Twisted Matrix](http://twistedmatrix.com/trac/) IRC-library.

Supports online module reloading - only major core changes require a
restart. Extensive module & handler -support for easy extension and
customization.

## Installation

[Installation instructions](https://github.com/lepinkainen/pyfibot/wiki/Installation)

## Module highlights

- URL title fetching with custom handlers via API calls for speed and
efficiency
  - IMDb
  - Youtube / Dailymotion
  - Wikipedia
  - Imgur
  - Instagram
  - eBay
  - Spotify
- Bitcoin exchange rates
- Wolfram Alpha queries
- Weather
- RSS support

## Features

- Modular
  - Live refresh of modules and configuration
  - Coder friendly (a basic module requires just 2 lines of boilerplate
    code)
  - SSL-support
  - IPv6-support
  - virtualenv-support
  - Works with torify

Support can be found at #pyfibot on irc.nerv.fi and please contact
<yllapito@nerv.fi> if you want to connect outside of Finland (will be
changed) or need help with IRC-network.

This product includes GeoLite data created by MaxMind, available from [http://www.maxmind.com](http://maxmind.com/).
dirtyflags 1.5.0
dirtyflags is a simple Python decorator that tracks when and which instance attributes have changed.

# dirtyflags

**dirtyflags** is a simple Python decorator that tracks when and which instance attributes have changed.

```python
>>> from dirtyflags import dirtyflag
>>> @dirtyflag
>>> class ChangingObject():
>>>     def __init__(self, attr1: int, attr2: str = "Default Value"):
>>>         self.attr1 = attr1
>>>         self.attr2 = attr2
>>> 
>>>     def __str__(self):
>>>         return (f"attr1 = {self.attr1}, attr2='{self.attr2}'")

>>> # create an instance of the class
instance_default = ChangingObject(attr1=1)

>>> print(f"instance_default is: {instance_default}")
instance_default is: attr1 = 1, attr2='Default Value'

>>> # dirtyflags tracks whether a change has occurred - in this case it has not
>>> print(f"Has this instance changed = {instance_default.is_dirty()}")
Has this instance changed = False

>>> # now change the value of an attribute
>>> instance_default.attr1 = 234
>>> # now dirty flag indicates the class has changed - and tells you what has changed
>>> print(f"Has this instance changed = {instance_default.is_dirty()}")
>>> print(f"The attribute(s) that have changed: {instance_default.dirty_attrs()}")
Has this instance changed = True
The attribute(s) that have changed: {'attr1'}

>>> # dirtyflags even tracks changes when using __setter__
>>> instance_default.__setattr__('attr2', 'changed the default')
>>> print(f"Has this instance changed = {instance_default.is_dirty()}")
>>> print(f"The attribute(s) that have changed: {instance_default.dirty_attrs()}")
Has this instance changed = True
The attribute(s) that have changed: {'attr2', 'attr1'}
```

## Installing dirtyflags


```console
pip install dirtyflags
```
dirtyflags officially supports Python 3.8+

## Supported Features and Best Practices
- Sinmply use the `@dirtyflag` decorator
- Supports attributes of any datatype, built-in or custom
- Works with Python dataclasses
- Nested classes should have the '@dirtyflag' decorator applied as well

[![linting: pylint](https://img.shields.io/badge/linting-pylint-yellowgreen)](https://github.com/PyCQA/pylint)
---
mousebender 2025.1
A package for implementing various Python packaging standards.
Requires Python: >=3.8
Keywords: packaging, Simple Repository API, PEP 503, PEP 592, PEP 658, PEP 691, PEP 700, PEP 714, PEP 740, PEP 792

# mousebender

Produce/consume dependency lock files for Python

## Important Links

- [PyPI](https://pypi.org/project/mousebender/)
- [Documentation](https://mousebender.readthedocs.io/)

## Goals for this project

This project hopes to (eventually) provide a way to create reproducible installations for a virtual environment from a lock file -- or a version-pinned dependency list if "lock file" means `flock` to you -- derived from a `pyproject.toml` file. That will require defining a lock file format for wheel files as well as being able to perform installations based on that lock file. The ultimate goal is for that lock file format to become a standard (see [PEP 665](https://peps.python.org/pep-0665/) which was an initial attempt at this).

Or put another way, this project wants to work towards a standard for what [pip-tools](https://pypi.org/project/pip-tools/) and [pip requirements files](https://pip.pypa.io/en/stable/reference/requirements-file-format/) do.

To achieve this goal, this project will need to be able to:

- [x] Know what wheel files are available on an index server ([`mousebender.simple`](https://mousebender.readthedocs.io/en/latest/simple.html))
- [x] Read the metadata from a wheel file (in [`packaging.metadata`](https://packaging.pypa.io/en/stable/metadata.html))
- [ ] Resolve what wheel files are required to meet the requirements specified in `pyproject.toml`
- [ ] Produce a lock file of wheel files for a platform
- [ ] Consume a lock file for the platform to install the specified wheel files


Where does the name come from?
==============================
The customer from [Monty Python's cheese shop sketch](https://en.wikipedia.org/wiki/Cheese_Shop_sketch) is named "Mr. Mousebender". And in case you didn't know, the original name of [PyPI](https://pypi.org) was the Cheeseshop after the Monty Python sketch (see [PyPI's 404 page](https://pypi.org/404.html) for a link to the sketch).