semvec/pypi-packages huggingface dataset:
promptlytics 0.0.2
Python wrapper for Promptlytics


# Project Title

Official python library for [Promptlytics](https://www.promptlytics.co/)

## Description

Promptlytics is a prompt analytics tool that helps you find the best prompts for your use case by tracking user feedback and associating it with your prompt templates.

## Installation

```bash
pip install promptlytics
```

## Getting Started

Use an instance of the Promptlytics class to get your prompt templates and track user feedback

```python
from promptlytics import Promptlytics

promptlytics = Promptlytics(YOUR_API_KEY)

# Gets the template selected for use in your dashboard
template = promptlytics.useTemplate(use_selected=True)

# sends user feedback
promptlytics.track(use_selected=True, rating=5, completion="string response from your LLM")
```
sphericalrht 2.0.1
Spherical implementation of the Rolling Hough Transform
Requires Python: >=3.7

<div align="center">
   <img src="https://raw.githubusercontent.com/georgehalal/sphericalrht/main/docs/images/sphericalrht_logo.gif" width="450px">
   </img>
   <br/>
   <a href="https://badge.fury.io/py/sphericalrht">
   <img src="https://badge.fury.io/py/sphericalrht.svg" alt="PyPI version" height="18">
   </a>
   <a href='https://sphericalrht.readthedocs.io/en/latest/?badge=latest'>
   <img src='https://readthedocs.org/projects/sphericalrht/badge/?version=latest' alt="Documentation status" />
   </a>
   <a href="https://github.com/georgehalal/sphericalrht/actions/workflows/tests.yml">
   <img src="https://github.com/georgehalal/sphericalrht/actions/workflows/tests.yml/badge.svg" alt="Test status"/>
   </a>
   <a href='https://coveralls.io/github/georgehalal/sphericalrht'>
   <img src='https://coveralls.io/repos/github/georgehalal/sphericalrht/badge.svg' alt='Coverage Status' />
   </a>
   <a href="https://github.com/georgehalal/sphericalrht/LICENSE">
   <img src="https://img.shields.io/badge/License-MIT-blue.svg?style=flat" alt="License"/>
   </a>
</div>
<br/>

<div align="center">
   <code>sphericalrht</code> is a fast, efficient implementation of the
   <a href="http://seclark.github.io/RHT/">Rolling Hough Transform</a>
   that runs directly on the sphere, using spherical harmonic convolutions.
   The documentation can be found at <a href="https://sphericalrht.readthedocs.io/en/latest/">readthedocs</a>
   and the package is distributed over <a href="https://pypi.org/project/sphericalrht/">PyPI</a>.
</div>
<br/>


## Installation

Run the following in a terminal to install:

```bash
pip install sphericalrht
```

If installing on a computing cluster, you may want to run the following
instead:

```bash
pip install sphericalrht --user
```
Add the `--upgrade` option to upgrade to a newer version.

Note that the `sphericalrht` package requires at least Python 3.7.


## References & Attribution

The paper introducing this package is in preparation. If you make use 
of this code in your research, please contact halalgeorge@gmail.com 
for discussing proper citations.