semvec/pypi-packages huggingface dataset:
mlrb-agent-tasks 0.0.23
A task package for ML Research Bench
Keywords: tasks, agent, benchmark

# ML Research Benchmark Tasks

This repository contains the tasks for ML Research Benchmark, a benchmarkdesigned to evaluate the capabilities of AI agents in accelerating ML research and development. The benchmark consists of 9 competition-level tasks that span the spectrum of activities typically undertaken by ML researchers.


## Introduction

The MLRB aims to measure the acceleration of AI agents in ML research and development. It focuses on competition-level tasks that reflect the current frontiers of ML research, providing a more nuanced and challenging evaluation environment than existing benchmarks.

[![arXiv](https://img.shields.io/badge/arXiv-2410.22553-b31b1b.svg)](https://arxiv.org/abs/2410.22553)

- [:paperclip: ML Research Benchmark Paper](https://arxiv.org/abs/2410.22553) 
- [:robot: ML Research Agent](https://github.com/AlgorithmicResearchGroup/ML-Research-Agent)
- [:white_check_mark: ML Research Tasks](https://github.com/AlgorithmicResearchGroup/ML-Research-Agent-Tasks)
- [:chart_with_upwards_trend: ML Research Evaluation](https://github.com/AlgorithmicResearchGroup/ML-Research-Agent-Evals)

## Installation

```bash
pip install mlrb-agent-tasks
```

# Usage

The library exposes a single function, get_task

get_task:
- path: path to copy the task to
- benchmark: name of the benchmark
- task: name of the task

This function will copy the task to the specified path and return a dictionary with the task name and prompt.

```
{
    "name": str, - name of the task
    "prompt": str, - prompt for the task
}
```

## Example Usage

```python
from mlrb_agent_tasks import get_task

# Example usage
result = get_task("./", "full_benchmark", "llm_efficiency")
print(result['prompt'])
```


## Contributing

We welcome contributions to the ML Research Benchmark! Please read our [CONTRIBUTING.md](CONTRIBUTING.md) file for guidelines on how to submit issues, feature requests, and pull requests.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Contact

For questions or feedback, please open an issue in this repository or contact [matt@algorithmicresearchgroup.com](mailto:matt@algorithmicresearchgroup.com).
Frac-to-cart-coordinates 1.1.6
A lightweight Python package for converting between fractional and Cartesian coordinates, supporting both forward and inverse transformations.
Requires Python: >=3.6

# `Frac-to-cart-coordinates`

The `Frac-to-cart-coordinates` package allows users to easily convert atomic coordinates from Cartesian to fractional format and *vice versa*, based on the unit cell parameters.

## Overview

In crystallography, atomic positions within a crystal's unit cell can be described using:
- **Fractional coordinates** $(x/a, y/b, z/c)$, which refer to the natural axes \(a, b, c\), scaled by their respective unit cell lengths.
- **Orthogonal coordinates** $(X, Y, Z)$, which use a right-angled Cartesian system with distances measured in Ångstroms.

For triclinic unit cells, the relationship between these coordinate systems involves a transformation matrix with non-trivial elements.

This implementation follows the methodology described on Jon Cooper's website, [fractorth](https://ic50.org/fractorth/). It relies on the fundamental principles of spherical trigonometry (see [implementation_details](/implementation_details/implementation_details.pdf)).

## Installation
Run the following command in your terminal:

```bash
pip install Frac-to-cart-coordinates
```

Make sure you have numpy installed and Python 3.6 or higher.

## Usage

### Importing the Module

```python
from Fractocart import convert_to_fractional_coordinates, convert_to_cartesian_coordinates
```

### Functions

1. **Convert to Fractional Coordinates**

   ```python
   fractional_coords = convert_to_fractional_coordinates(cartesian_coords, unit_cell)
   ````

2. **Convert to Cartesian Coordinates**

    ```python
    cartesian_coords = convert_to_cartesian_coordinates(fractional_coords, unit_cell)
    ````

## Contributing

Contributions are welcome! To contribute:
1. Fork the repository, then clone the fork (see [there](https://guides.github.com/activities/forking/)).
2. Create a feature branch (`git checkout -b feature-name`).
3. Commit your changes (`git commit -m "Add new feature"`).
4. Push to the branch (`git push origin feature-name`).
5. Open a merge request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
ipfabric-netbox 3.1.1
NetBox plugin to sync IP Fabric data into NetBox

# IP Fabric Netbox Plugin

## IP Fabric

IP Fabric is a vendor-neutral network assurance platform that automates the
holistic discovery, verification, visualization, and documentation of
large-scale enterprise networks, reducing the associated costs and required
resources whilst improving security and efficiency.

It supports your engineering and operations teams, underpinning migration and
transformation projects. IP Fabric will revolutionize how you approach network
visibility and assurance, security assurance, automation, multi-cloud
networking, and trouble resolution.

**Integrations or scripts should not be installed directly on the IP Fabric VM unless directly communicated from the
IP Fabric Support or Solution Architect teams.  Any action on the Command-Line Interface (CLI) using the root, osadmin,
or autoboss account may cause irreversible, detrimental changes to the product and can render the system unusable.**

## Overview

This plugin allows the integration and data synchronization between IP Fabric and NetBox.

The plugin uses IP Fabric collect network data utilizing the [IP Fabric Python SDK](https://gitlab.com/ip-fabric/integrations/python-ipfabric). This plugin relies on helpful features in NetBox like [Staged Changes](https://netboxlabs.com/docs/netbox/en/stable/plugins/development/staged-changes/) and [Background Tasks](https://netboxlabs.com/docs/netbox/en/stable/plugins/development/background-tasks/) to make the job of bringing in data to NetBox easier.

- Multiple IP Fabric Sources
- Transform Maps
- Scheduled Synchronization
- Diff Visualization

## NetBox Compatibility

| Netbox Version | Plugin Version |
| -------------- | -------------- |
| 3.4            | <=1.0.11       |
| 3.5            | <=1.0.11       |
| 3.6            | <=1.0.11       |
| 3.7            | >=2.0.0        |
| 4.0            | >=3.0.0        |
| 4.0.1          | >=3.0.1        |
| 4.1.0          | >=3.1.0        |
| 4.1.5          | >=3.1.1        |

## Screenshots

![Source](docs/images/user_guide/source_sync.png)

![Snapshots](docs/images/user_guide/snapshot_detail.png)

![Transform Maps](docs/images/user_guide/tm_edit_hostname.png)

![Ingesion](docs/images/user_guide/ingestion_detail.png)

![Diff](docs/images/user_guide/branch_changes_update_diff.png)

## Documentation

Full documentation for this plugin can be found at [IP Fabric Docs](https://docs.ipfabric.io/main/integrations/netbox/).

- User Guide
- Administrator Guide
FactorioAPI 1.1.3
A Python library to interact with the Factorio API and related files
Requires Python: >=3.13

# Factorio API
A Python library to interact with the Factorio API and related files 

check out [planning.md](https://github.com/catlord-dev/factorioapi/blob/main/planning.md) for my general plan, it's part rambling and part me trying to solidify my thoughts    

This project is not related to Wube Software (creators of Factorio)