semvec/pypi-packages huggingface dataset:
penngrader-client 0.5.13
In-line python grader client.

# PennGrader
Welcome to the PennGrader!

Here at PennGrader, we believe that learning comes from lots of practice...and from making lots of mistakes. 

After many years as a student I found myself very frustrated in the following homework timeline: struggle on a homework assignment for weeks, submit something that may or may not be right and then wait a few more weeks to receive any type of feedback, at which point I had forgotten all about the homework. After many years as a TA, I also found myself very frustrated with the common auto-grading tools, the hours and hours of manual grading and the onslaught of re-grade requests that came thereafter.

From these frustrations, the PennGrader was born!

The PennGrader was built to allow students to get instant feedback and many opportunities for re-submission. After all, programming is about making mistakes and learning from feedback! Moreover, we wanted to allow TAs and Instructors to write their homework in any way they pleased, without having to worry about the structure of a specific auto-grader. The examples below are done using Jupyter Notebooks which is the most common use case, but you can use this for normal Python homework as well.
sfn_llm_client 0.3.4
SDK for using LLM
Requires Python: >=3.9

# SFN_LLM_Client

This is an enhanced and improved version with latest llm provider chat completion feature The `sfn_llm_client` now includes:

- **Updated to the latest version of OpenAI**.
- **Integrated Cortex LLM provider support**.
- **Latest improvements and updates to the codebase** for better performance and compatibility.

## Features

- Supports multiple LLM providers, including OpenAI and Cortex.
- Easily extensible to include new LLM providers by implementing base client classes.
- Well-documented and tested.

### Adding a New LLM Client

To add a new LLM client, follow these steps:

1. **Implement `BaseLLMClient` or `BaseLLMAPIClient`:**  
   If you're adding a new LLM provider, you'll need to implement either the `BaseLLMClient` or `BaseLLMAPIClient` interfaces.
   
2. **Register in `LLMAPIClientFactory`:**  
   If you're adding a client based on `BaseLLMAPIClient`, don't forget to register it in the `LLMAPIClientFactory` so that it's available for use.

### Adding Dependencies

If your LLM client requires additional dependencies, you can add them to the `pyproject.toml` file under the appropriate section.

## Contributing
Contributions are welcome! If you'd like to help improve this SDK, please check out the todos or open an issue or pull request.

### Credits
the core forked functionality taken from `llm-client-sdk` created by uripeled2.

## Contact:
For any queries or issues, please contact the maintainer at: `rajesh@stepfunction.ai`
audmetric 1.3.1
Evaluate machine-learning models
Requires Python: >=3.10
Keywords: mlops, machine learning

=========
audmetric
=========

|tests| |coverage| |docs| |python-versions| |license|

**audmetric** includes several equations
to estimate the performance of a machine learning prediction algorithm.

Some of the metrics are also available in sklearn_,
but we wanted to have a package
which depends only on numpy_.
For those metrics
we included tests that the results are identical to sklearn_.


.. _numpy: https://numpy.org/
.. _sklearn: https://scikit-learn.org/stable/


.. badges images and links:
.. |tests| image:: https://github.com/audeering/audmetric/workflows/Test/badge.svg
    :target: https://github.com/audeering/audmetric/actions?query=workflow%3ATest
    :alt: Test status
.. |coverage| image:: https://codecov.io/gh/audeering/audmetric/branch/main/graph/badge.svg?token=wOMLYzFnDO
    :target: https://codecov.io/gh/audeering/audmetric/
    :alt: code coverage
.. |docs| image:: https://img.shields.io/pypi/v/audmetric?label=docs
    :target: https://audeering.github.io/audmetric/
    :alt: audmetric's documentation
.. |license| image:: https://img.shields.io/badge/license-MIT-green.svg
    :target: https://github.com/audeering/audmetric/blob/main/LICENSE
    :alt: audmetric's MIT license
.. |python-versions| image:: https://img.shields.io/pypi/pyversions/audmetric.svg
    :target: https://pypi.org/project/audmetric/
    :alt: audmetric's supported Python versions