semvec/pypi-packages huggingface dataset:
ftech-pydantic-ai 0.0.12rc0
Agent Framework / shim to use Pydantic with LLMs, slim package
License: MIT
Requires Python: >=3.9

# PydanticAI Slim

[![CI](https://github.com/pydantic/pydantic-ai/actions/workflows/ci.yml/badge.svg?event=push)](https://github.com/pydantic/pydantic-ai/actions/workflows/ci.yml?query=branch%3Amain)
[![Coverage](https://coverage-badge.samuelcolvin.workers.dev/pydantic/pydantic-ai.svg)](https://coverage-badge.samuelcolvin.workers.dev/redirect/pydantic/pydantic-ai)
[![PyPI](https://img.shields.io/pypi/v/pydantic-ai.svg)](https://pypi.python.org/pypi/pydantic-ai)
[![versions](https://img.shields.io/pypi/pyversions/pydantic-ai.svg)](https://github.com/pydantic/pydantic-ai)
[![license](https://img.shields.io/github/license/pydantic/pydantic-ai.svg?v)](https://github.com/pydantic/pydantic-ai/blob/main/LICENSE)

PydanticAI core logic with minimal required dependencies.

For more information on how to use this package see [ai.pydantic.dev/install](https://ai.pydantic.dev/install/).
typereduction 0.2.2
Implementation of CTypes-based type reduction algorithms for using with PyIT2FLS
License: MIT

Typereduction
=============

Typereduction library contains Ctypes-based implementation of the type reduction algorithms ONLY for IT2FSs. It should be noted that some parts of the original type reduction algorithms have been edited for improving the execution speed.

### Installation

Typereduction can be installed by unzipping the source code in a directory and using this command inside the typereduction folder:

    pip3 install .

Or you can install from PyPI:

    pip3 install --upgrade typereduction

**Note that typereduction has only been tested with GNU C compiler on Linux. Please report any compatibility issues.**

### Connecting with PyIT2FLS

PyIT2FLS automatically detects whether the typereduction toolkit has been installed or not and uses it in computations if installed.
prep-pydantic-ai 0.0.12rc0
Agent Framework / shim to use Pydantic with LLMs, slim package
License: MIT
Requires Python: >=3.9

# PydanticAI Slim

[![CI](https://github.com/pydantic/pydantic-ai/actions/workflows/ci.yml/badge.svg?event=push)](https://github.com/pydantic/pydantic-ai/actions/workflows/ci.yml?query=branch%3Amain)
[![Coverage](https://coverage-badge.samuelcolvin.workers.dev/pydantic/pydantic-ai.svg)](https://coverage-badge.samuelcolvin.workers.dev/redirect/pydantic/pydantic-ai)
[![PyPI](https://img.shields.io/pypi/v/pydantic-ai.svg)](https://pypi.python.org/pypi/pydantic-ai)
[![versions](https://img.shields.io/pypi/pyversions/pydantic-ai.svg)](https://github.com/pydantic/pydantic-ai)
[![license](https://img.shields.io/github/license/pydantic/pydantic-ai.svg?v)](https://github.com/pydantic/pydantic-ai/blob/main/LICENSE)

PydanticAI core logic with minimal required dependencies.

For more information on how to use this package see [ai.pydantic.dev/install](https://ai.pydantic.dev/install/).
LoopProjectFile 0.2.2
Open source structural geology data storage for Loop Projects
License: MIT
Requires Python: >=3.8
Keywords: earth sciences, data storage, structural geology, geology, loop3d

# Loop Project File Documentation {#mainpage}

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![Loop Project](loop_inv.png "Loop Project")
[Loop Project Website](https://loop3d.org)

# What is Loop?
The Loop platform is an open source 3D probabilistic geological and geophysical modelling platform, initiated by Geoscience Australia and the OneGeology consortium. The project is funded by Australian territory, State and Federal Geological Surveys, the Australian Research Council and the MinEx Collaborative Research Centre.

# What is a Loop Project File?
A Loop Project File encapsulates all the data and models used or created in a Loop workflow.  This includes the ability to create meta-data which provides provenance of the data and the methodology and history of how models are used and produced.  The Loop Project File is based on netCDF and has APIs for C/C++ and Python (with the intention of creating a Fortran API in the future).
- [Loop Project File - C/C++](https://github.com/Loop3D/LoopProjectFile-cpp)
- [Loop Project File - Python](https://github.com/Loop3D/LoopProjectFile)

# Why use a project file?
There are several benefits to using a single project file.  These include encapsulating the information in a single place, server storage and retrieval enabling batching of model creation over multiple servers, easily shared workflows, and storage efficiency among many more.

# Why use netCDF?
netCDF enables multi-dimensional data structure storage in a highly compressed format as well as data attribution for meta-data all within a single data file.

# Licencing
The Loop Project File python repository is under the MIT license