semvec/pypi-packages huggingface dataset:
lacuscore 1.21.2
Core of Lacus, usable as a module
Requires Python: <4.0,>=3.10

[![Documentation Status](https://readthedocs.org/projects/lacuscore/badge/?version=latest)](https://lacuscore.readthedocs.io/en/latest/?badge=latest)

# Modulable Lacus

Lacus, but as a simple module.

# Installation

```bash
pip install lacuscore
```

# Design

`LacusCore` is the part taking care of enqueuing and capturing URLs or web enabled documents.
It can be used as a module in your own project, see below for the usage

[Lacus](https://github.com/ail-project/lacus) is the webservice that uses `LacusCore`,
and you can use [Pylacus](https://github.com/ail-project/pylacus) to query it.

The `enqueue`, `get_capture_status`, and `get_capture` methods if `LacusCore` and `PyLacus` have
the same parameters which means you can easily use them interchangeably in your project.


For more information regarding the usage of the module and a few examples, please refer to
[the documentation](https://lacuscore.readthedocs.io/en/latest/)
paraqeet 0.11.0
Toolset for control, calibration and characterization of physical systems
Requires Python: >=3.12

<div align="center">
  <center><img src="https://jugit.fz-juelich.de/pgi-12-external/qfc/paraqeet/-/raw/main/big_logo.png" alt="paraqeet_logo" width="90%"/></center>
</div>

# ParaQeet -  A quantum optimal control toolkit with simple parameter management

[![pipeline status](https://jugit.fz-juelich.de/pgi-12-external/qfc/paraqeet/badges/main/pipeline.svg)](https://jugit.fz-juelich.de/pgi-12-external/qfc/paraqeet/-/commits/main)
[![coverage report](https://jugit.fz-juelich.de/pgi-12-external/qfc/paraqeet/badges/main/coverage.svg)](https://jugit.fz-juelich.de/pgi-12-external/qfc/paraqeet/-/commits/main)
[![Latest Release](https://jugit.fz-juelich.de/pgi-12-external/qfc/paraqeet/-/badges/release.svg)](https://jugit.fz-juelich.de/pgi-12-external/qfc/paraqeet/-/releases)
[![readthedocs](https://readthedocs.org/projects/paraqeet/badge/?version=latest)](https://paraqeet.readthedocs.io/en/latest/)
[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
[![License](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
[![PyPI - Version](https://img.shields.io/pypi/v/paraqeet)](https://pypi.org/project/paraqeet/)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/paraqeet)]((https://pypi.org/project/paraqeet/))

*Note: This is a preview version, a 1.0.0 release is forthcoming.*

Choose a pulse parametrisation, simulate a quantum system, and optimize. 

Combining Quantum Optimal Control methods with automatic differentiation with JAX.
Aimed at resource efficient computation.

We use a top-down approach to make the codebase modular. 
Each module interacts only with the module above it in hierarchy. 

<div align="center">
  <center><img src="https://jugit.fz-juelich.de/pgi-12-external/qfc/paraqeet/-/raw/main/docs/layers.png" alt="Layers" width="60%"/></center>
</div>

Currently implementated optimization methods
- GRAPE: Gradient Ascent Pulse Enginnering
- GOAT: Gradient Optimization of Analytic conTrols
- dCRAB : (Gradient based) dressed Chopped RAndom Basis

## Installation from PyPi
Install with `pip install paraqeet`.

## Installation from source
Follow the [contributing](CONTRIBUTING.md) document.
langchain-outline 0.3.0
Langchain Document loader for Outline
Requires Python: <3.13,>=3.9

# Langchain Outline Document Loader

## Overview

`langchain-outline` provides a `DocumentLoader` for Langchain that allows you to load documents directly from an [Outline](https://www.getoutline.com/) knowledge base instance.

This loader uses the Outline API to fetch all documents within your instance.

## Installation

```bash
pip install langchain-outline
```

## Configuration

The loader requires the URL of your Outline instance and an API key for authentication. 

## Usage

````python
import os
from langchain_outline.outline import OutlineLoader

# Option 1: Using environment variables (ensure they are set)
# os.environ["OUTLINE_INSTANCE_URL"] = "YOUR_OUTLINE_URL"
# os.environ["OUTLINE_API_KEY"] = "YOUR_API_KEY"
# loader = OutlineLoader()

# Option 2: Passing parameters directly
loader = OutlineLoader(
    outline_base_url="YOUR_OUTLINE_URL",
    outline_api_key="YOUR_API_KEY"
)

# Load documents (iteratively)
docs_iterator = loader.lazy_load()
for doc in docs_iterator:
    print(f"Loaded document: {doc.metadata['title']}")
    # Process the document...

# Or load all documents into a list (might consume more memory for large instances)
all_docs = loader.load()
print(f"Loaded {len(all_docs)} documents.")
````
Replace "YOUR_OUTLINE_URL" and "YOUR_API_KEY" with your actual Outline instance URL and API key.

## For maintainers


# To build and test publishing to TestPyPi
To publish a new version of the package you can use poetry (or twine, etc).  First test using TestPyPi first.

1. Make sure you have TestPyPi as a repo:

`poetry config repositories.testpypi https://test.pypi.org/legacy/`

2. Obtain API token from TestPyPi and add it to poetry config:

`poetry config pypi-token.testpypi <<token from testpypi>>`

3. Publish the package to TestPypi (make sure version defined in pyproject.toml follows PEP440):

`poetry publish --build --repository testpypi`

# To publish to PyPi
To publish a new version of the package you can use poetry (or twine, etc).  First test using TestPyPi first.

1. Obtain API token from PyPi and add it to poetry config:

`poetry config pypi-token.pypi <<token from pypi>>`

3. Publish the package to PyPi (make sure version defined in pyproject.toml follows PEP440):

`poetry publish --build`
crisp-python 3.2.0
Simple python interface to control robots that use crisp_controllers and other ROS2 components.
Requires Python: >=3.11

![crisp_py_logo](https://github.com/user-attachments/assets/374ae11a-4d82-4bb7-8b93-152bde13aa5b)

[![Ruff](https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json)](https://github.com/astral-sh/ruff)
![MIT Badge](https://img.shields.io/badge/MIT-License-blue?style=flat)
<a href="https://utiasDSL.github.io/crisp_controllers/"><img alt="Static Badge" src="https://img.shields.io/badge/docs-passing-blue?style=flat&link=https%3A%2F%2FutiasDSL.github.io%2Fcrisp_controllers%2F"></a>
<a href="https://github.com/utiasDSL/crisp_py/actions/workflows/ruff_ci.yml"><img src="https://github.com/utiasDSL/crisp_py/actions/workflows/ruff_ci.yml/badge.svg"/></a>
<a href="https://github.com/utiasDSL/crisp_py/actions/workflows/pixi_ci.yml"><img src="https://github.com/utiasDSL/crisp_py/actions/workflows/pixi_ci.yml/badge.svg"/></a>
<a href="https://utiasDSL.github.io/crisp_controllers#citing"><img alt="Static Badge" src="https://img.shields.io/badge/arxiv-cite-b31b1b?style=flat"></a>

*CRISP_PY /krɪspi/*, a python package to interface with robots using [CRISP controllers](https://github.com/utiasDSL/crisp_controllers). Check the [project website](https://utiasdsl.github.io/crisp_controllers/) for further information!

![crisp_py](https://github.com/user-attachments/assets/e4cbf5fd-6ba7-4d7c-917a-bbb78d79ab10)
omnyxai 0.1.0
OmnyxAi — Gemini-powered UI generation via MCP
Requires Python: >=3.12

# OmnyxAi

**AI-powered UI generation via MCP** — use Gemini as your frontend designer without leaving your IDE.

OmnyxAi exposes MCP tools (`create_frontend`, `modify_frontend`, `snippet_frontend`) that generate production-ready UI code using Google Gemini.

## Install

```bash
pip install omnyxai
```

## Setup

1. Get an API key from [omnyxai.com](https://omnyxai.com)
2. Set your key:
   ```bash
   export OMNYXAI_API_KEY="gd_your_key_here"
   ```
3. Generate IDE config:
   ```bash
   omnyxai-mcp init --host cursor   # or claude, codex
   ```
4. Restart your IDE — the MCP tools are now available.

## Verify

```bash
omnyxai-mcp doctor
```

## MCP Tools

| Tool | Description |
|------|-------------|
| `create_frontend` | Generate a full page from a natural language spec |
| `modify_frontend` | Modify existing frontend code to achieve a design objective |
| `snippet_frontend` | Generate a ready-to-paste UI component snippet |

All tools support React, Vue, Svelte, and plain HTML.

## Links

- [Documentation](https://docs.omnyxai.com)
- [Dashboard](https://omnyxai.com)
- [GitHub](https://github.com/omnyxai/omnyxai)