semvec/pypi-packages huggingface dataset:
elizaos-plugin-nextcloud-talk 2.0.0a4
Nextcloud Talk plugin for elizaOS - Python implementation for webhook bot integration
Requires Python: >=3.11
Keywords: agents, ai, bot, chat, elizaos, nextcloud, nextcloud-talk, webhook

# elizaOS Nextcloud Talk Plugin (Python)

Python implementation of the Nextcloud Talk plugin for elizaOS.

## Features

- Webhook bot integration with Nextcloud Talk
- HMAC-SHA256 signature verification
- Bot secret authentication
- Support for DMs and group chats
- Reactions support

## Installation

```bash
pip install elizaos-plugin-nextcloud-talk
```

## Configuration

Set these environment variables:

- NEXTCLOUD_URL - Base URL of your Nextcloud instance
- NEXTCLOUD_BOT_SECRET - Bot secret from occ talk:bot:install

Optional:
- NEXTCLOUD_ENABLED - Enable/disable plugin (default: true)
- NEXTCLOUD_WEBHOOK_PORT - Webhook port (default: 8788)
- NEXTCLOUD_WEBHOOK_HOST - Webhook host (default: 0.0.0.0)
- NEXTCLOUD_WEBHOOK_PATH - Webhook path (default: /nextcloud-talk-webhook)

## License

MIT
decorators-learn 0.0.2
A project to learn decorators
Requires Python: >=3.12.8

# Decorators Learn

[![pr-checks](https://github.com/rohit1998/decorators-learn/actions/workflows/pr-checks.yml/badge.svg?branch=main)](https://github.com/rohit1998/decorators-learn/actions/workflows/pr-checks.yml)
[![Documentation](https://img.shields.io/badge/docs-latest-blue.svg)](https://rohit1998.github.io/decorators-learn/)
[![PyPI version](https://img.shields.io/pypi/v/decorators-learn.svg?color=blue)](https://pypi.org/project/decorators-learn/)
[![Python versions](https://img.shields.io/pypi/pyversions/decorators-learn.svg?color=blue)](https://pypi.org/project/decorators-learn/)
[![Docker Image](https://img.shields.io/docker/v/rohgupt/decorators-learn?label=latest)](https://hub.docker.com/r/rohgupt/decorators-learn/)

A project to learn decorators. Checkout

- [local_docs_link](https://decorators-learn.dev.local)
- [tailscale_docs_link](https://decorators-learn.tailb437ea.ts.net)
- [repo_docs_path](docs/index.md)

## License

This project is licensed under the MIT License - see the LICENSE file for details.
tgedr-pycommons 1.0.1
common python code usable across projects
Requires Python: >=3.11

# tgedr-pycommons

![Coverage](./coverage.svg)
[![PyPI](https://img.shields.io/pypi/v/tgedr-pycommons)](https://pypi.org/project/tgedr-pycommons/)


Common code to be used across projects


## development
- main requirements:
  - _uv_  
  - _bash_
- Clone the repository like this:

  ``` bash
  git clone git@github.com:tgedr/pycommons
  ```
- cd into the folder: `cd pycommons`
- install requirements: `./helper.sh reqs`
rotalabs 1.1.0
Trust Intelligence Research - Core package from Rotalabs
Requires Python: >=3.9
Keywords: ai, machine-learning, research, trust

# Rotalabs

AI Trust Infrastructure - Open source tools for building trustworthy AI systems.

**Documentation Hub:** [rotalabs.github.io/rotalabs](https://rotalabs.github.io/rotalabs/)

## Packages

| Package | Description | Docs |
|---------|-------------|------|
| [rotalabs-steer](https://github.com/rotalabs/rotalabs-steer) | Activation steering for LLM behavior control | [Docs](https://rotalabs.github.io/rotalabs-steer/) |
| [rotalabs-probe](https://github.com/rotalabs/rotalabs-probe) | Sandbagging detection via activation probes | [Docs](https://rotalabs.github.io/rotalabs-probe/) |
| [rotalabs-redqueen](https://github.com/rotalabs/rotalabs-redqueen) | Evolutionary adversarial testing | [Docs](https://rotalabs.github.io/rotalabs-redqueen/) |
| [rotalabs-verity](https://github.com/rotalabs/rotalabs-verity) | Neuro-symbolic verified code synthesis | [Docs](https://rotalabs.github.io/rotalabs-verity/) |
| [rotalabs-eval](https://github.com/rotalabs/rotalabs-eval) | LLM evaluation with statistical rigor | [Docs](https://rotalabs.github.io/rotalabs-eval/) |
| [rotalabs-cascade](https://github.com/rotalabs/rotalabs-cascade) | Multi-stage decision routing | [Docs](https://rotalabs.github.io/rotalabs-cascade/) |
| [rotalabs-fieldmem](https://github.com/rotalabs/rotalabs-fieldmem) | Field-theoretic memory systems | [Docs](https://rotalabs.github.io/rotalabs-fieldmem/) |
| [rotalabs-graph](https://github.com/rotalabs/rotalabs-graph) | GNN-based trust propagation | [Docs](https://rotalabs.github.io/rotalabs-graph/) |
| [rotalabs-accel](https://github.com/rotalabs/rotalabs-accel) | Inference acceleration with Triton | [Docs](https://rotalabs.github.io/rotalabs-accel/) |
| [rotalabs-comply](https://github.com/rotalabs/rotalabs-comply) | AI compliance infrastructure | [Docs](https://rotalabs.github.io/rotalabs-comply/) |
| [rotalabs-audit](https://github.com/rotalabs/rotalabs-audit) | Reasoning chain transparency | [Docs](https://rotalabs.github.io/rotalabs-audit/) |

## Install

```bash
pip install rotalabs-steer
pip install rotalabs-verity
# etc.
```

## License

All packages are licensed under [AGPL-3.0](LICENSE). For commercial licensing, contact [research@rotalabs.ai](mailto:research@rotalabs.ai).

## Links

- Website: [rotalabs.ai](https://rotalabs.ai)
- GitHub: [github.com/rotalabs](https://github.com/rotalabs)