semvec/pypi-packages huggingface dataset:
livekit-browser 0.1.4
Chromium Embedded Framework (CEF) bindings for LiveKit
Requires Python: >=3.12.0
Keywords: audio, browser, cef, livekit, realtime, video, webrtc

# Browser plugin for LiveKit Agents

Chromium Embedded Framework (CEF) for LiveKit Agents

## Development notes

### Avoid excessive asyncio task creation

Audio is very sensitive to event loop latency. Avoid creating short-lived tasks
(`asyncio.create_task`, `asyncio.ensure_future`) on hot paths like paint
callbacks, audio callbacks, and input event dispatch. Each task adds scheduling
overhead that accumulates into audible jitter.

Prefer a single persistent loop task that drains a queue (see
`_input_sender_loop`, `_audio_loop` in `session.py`). The total number of
long-lived tasks in steady state should stay in the low tens — not scale with
frame rate or input frequency.
rotalabs-context 1.0.0
Context intelligence for AI agents - Ingest, search, and subscribe to shared context across your AI systems
Requires Python: >=3.9
Keywords: ai-agents, context, context-engine, embeddings, etl, knowledge-graph, rag, semantic-search

# rotalabs-context

> Context intelligence for AI agents — Ingest, search, and subscribe to shared context across your AI systems.

Part of the [Rotalabs](https://rotalabs.ai) trust intelligence research ecosystem.

## Installation

```bash
pip install rotalabs-context
```

With local embedding support:
```bash
pip install rotalabs-context[local]
```

With Rotascale platform integration:
```bash
pip install rotalabs-context[platform]
```

## Quick Start

```python
from rotalabs_context import ContextEngine

# Local mode (zero config, SQLite backend)
ctx = ContextEngine()

# Platform mode (connects to Rotascale)
ctx = ContextEngine(
    api_key="rot_...",
    base_url="https://api.rotascale.com",
)

# Ingest context
result = ctx.ingest(
    records=[
        {"content": "User reported login issue", "title": "Support ticket #1234"},
        {"content": "Auth service latency spike at 2pm UTC", "title": "Incident report"},
    ],
    source="helpdesk",
    tags=["support", "auth"],
    scope="team:support",
)

# Search
results = ctx.search("login issues", top_k=5, mode="semantic")
for hit in results:
    print(f"{hit.score:.2f} — {hit.title}")

# Subscribe to context updates
ctx.on("context.created", filter={"tags": ["support"]}, callback=my_handler)
```

## Features

- **Ingest**: Push data from any pipeline; we add the "C" (embeddings, entities, relationships)
- **Search**: Semantic + keyword + hybrid search across all ingested context
- **Subscribe**: Real-time context propagation via events
- **ACLs**: Scope-based access control (global, team, agent, project, user)
- **Pluggable backends**: SQLite (local), PostgreSQL (self-hosted), Rotascale Platform (managed)

## Pipeline Adapters

```python
# Airflow
from rotalabs_context.adapters import AirflowContextOperator

# In your DAG
ingest_task = AirflowContextOperator(
    task_id="ingest_to_context",
    source="airflow-etl",
    tags=["daily-batch"],
)
```

## License

AGPL-3.0 — See [LICENSE](LICENSE) for details.
dew-gwdata 0.115
Python module for accessing groundwater data internally at DEW

# dew_gwdata

Python module for accessing groundwater data internally at DEW

## Install

The source code is on [Bitbucket](https://bitbucket.org/dewsurfacewater/dew_gwdata), while Python packages (source and binary) are published on
the [Python Package Index](https://pypi.org/project/dew-gwdata/) and 
on a dedicated channel on [Anaconda Cloud](https://anaconda.org/dew-waterscience/repo).

### From PyPI (most recent release)

Run this in Command Prompt to install from PyPI:

```
pip install dew_gwdata
```

To upgrade to the latest version:

```
pip install -U dew_gwdata
```

### From Anaconda 

You can also install using conda/mamba if you prefer:

```
mamba install -c dew-waterscience dew_gwdata
```

To upgrade:

```
mamba upgrade -c dew-waterscience dew_gwdata
```

The version may not be as up-to-date as the PyPI version.

### From Bitbucket

This is how you can install the latest version of the source code directly from Bitbucket (the version control repository):

```
python -m pip install git+https://kinveraritysagov@bitbucket.org/dewsurfacewater/dew_gwdata.git
```

You will need to replace ``kinveraritysagov`` with your Bitbucket username, and you will also need access to the source repository on the Bitbucket dewsurfacewater workspace.

## Usage

Check out complete documentation at:

[http://bunyip:8191/python-docs/dew_gwdata/latest_source/index.html](http://bunyip:8191/python-docs/dew_gwdata/latest_source/index.html)

## Webapp usage

"New" Waterkennect is implemented by the ``dew_gwdata.webapp`` module. To execute the webapp navigate to the folder
containing the source code, i.e. the ``dew_gwdata/webapp`` folder within this repository, and run:

```
uvicorn dew_gwdata.webapp.main:app --port 8191 --host 0.0.0.0 --reload --log-config .\log-config.yaml
```

There is an example logging config file in this folder.

```
(py310) C:\devapps\syski\code\dew_gwdata\dew_gwdata\webapp>uvicorn dew_gwdata.webapp.main:app --port 8191 --host 0.0.0.0 --reload --log-config .\log-config.yaml
INFO:     [29-11-2023 13:39:10] uvicorn.error.serve - Started server process [63528]
INFO:     [29-11-2023 13:39:10] uvicorn.error.startup - Waiting for application startup.
INFO:     [29-11-2023 13:39:10] uvicorn.error.startup - Application startup complete.
DEBUG:    [29-11-2023 13:39:41] dew_gwdata.webapp.models.queries.find_wells - id_types requested: ['unit_no', 'obs_no', 'dh_no']
INFO:     [29-11-2023 13:39:42] 10.55.65.0:58877 - "GET /app/wells_summary?idq=86711&idq_unit_no=1&idq_obs_no=1&idq_dh_no=1&env=prod HTTP/1.1" 200 OK
```


## License

All rights reserved DEW 2023
matrx-utils 1.0.4
Basic utilities for matrx
Requires Python: >=3.10

# matrx-utils

A comprehensive collection of Python utilities designed to complement the AI Matrx platform.

## Overview

matrx-utils provides a curated set of utility functions and tools that enhance the AI Matrx ecosystem. This repository serves as a centralized library of commonly used functionality, allowing for easy integration across the main AI Matrx application and related projects.

## Features

- **Logging utilities** - Enhanced logging capabilities
- **Print utilities** - Advanced printing and formatting tools
- **Code analysis** - Tools for analyzing and processing code
- **Markdown processing** - Utilities for working with markdown content
- **Object manipulation** - Helper functions for working with Python objects
- **Data conversion** - Tools for converting between different data formats
- **Additional utilities** - Various other Python utility-level tools

## Purpose

This library is designed to provide instant access to a powerful set of utilities without requiring additional code setup. All utilities have been customized and configured specifically for the AI Matrx platform ecosystem.

## Installation

### From PyPI (recommended)

```bash
pip install matrx-utils
# or with uv
uv add matrx-utils
```

### From GitHub (for development)

```bash
pip install git+https://github.com/armanisadeghi/matrx-utils.git
```

## Quick Start

```python
import matrx_utils

# Example usage will be added as the library develops
```

## Contributing

This project is part of the AI Matrx ecosystem. Contributions and suggestions are welcome.

## License

[License information to be added]

## Related Projects

- [AI Matrx](https://github.com/armanisadeghi/ai-matrx) - Main AI Matrx platform repository


## Publishing a New Version

### Automated PyPI Publishing (Current Process)

The package automatically publishes to PyPI when you push a version tag. Here's the workflow:

1. **Make and test your changes locally**
   ```bash
   # Test your changes
   ```

2. **Update the version in pyproject.toml**
   ```toml
   version = "1.0.3"  # Increment appropriately
   ```

3. **Commit and push changes**
   ```bash
   git add .
   git commit -m "Add new feature - v1.0.3"
   git push origin main
   ```

4. **Create and push the version tag**
   ```bash
   git tag v1.0.3
   git push origin v1.0.3
   ```

5. **GitHub Actions automatically:**
   - Verifies the tag matches pyproject.toml version
   - Builds the package
   - Publishes to PyPI

6. **Update dependent projects**
   
   In projects like AI Dream, simply update the version:
   ```bash
   uv add matrx-utils@1.0.3
   # or manually in pyproject.toml:
   # matrx-utils = "^1.0.3"
   ```

### Version History

Check current tags: `git tag`

Example output:
```
v1.0.0
v1.0.1
v1.0.2
```

### Important Notes

- **Always update pyproject.toml version before tagging**
- The GitHub Action will fail if tag version ≠ pyproject.toml version
- Semantic versioning: MAJOR.MINOR.PATCH (e.g., v1.0.3)
- Tags trigger automatic PyPI publishing
django-blocknote 2026.2.17.1
BlockNote rich text editor integration for Django
Requires Python: >=3.10
Keywords: django, rich-text-editor, blocknote, wysiwyg

Django BlockNote 
================

|Repo| |Version| |Python| |Django| |Docs| |Downloads|


Licenses
--------

**Django:** BSD 3-Clause "New" or "Revised License"

**BlockNote:** Mozilla Public License Version 2.0

What is django-blocknote
------------------------

django-blocknote: A Powerful and Versatile Rich Text Editor for Your Django Projects

* Seamlessly integrate BlockNote into your Django website.
* Provide your users with a modern and intuitive content creation experience.
* Includes features like text formatting, image uploads, tables, code blocks, and more.
* Highly customizable to fit your project's exact needs.

See the Quickstart: `here <https://django-blocknote.readthedocs.io/en/latest/how-to-guides/quickstart.html>`__

Ideal For:
~~~~~~~~~~

* Blogs
* Content Management Systems (CMS)
* Websites requiring advanced text editing features

**Includes the following BlockNote features:**

Text Formatting
~~~~~~~~~~~~~~~

**Basic:**

* Bold
* Italic
* Underline
* Strikethrough
* Superscript
* Subscript
* Code

**Paragraph and Structure:**

* BlockQuote
* Heading
* Paragraph
* Alignment

**Lists:**

* List
* TodoList
* ListProperties

**Advanced:**

* Highlight
* Indent
* IndentBlock

Images and Media
~~~~~~~~~~~~~~~~

**Core:**

* Image
* ImageCaption
* ImageStyle
* ImageToolbar
* ImageResize
* ImageInsert
* LinkImage

**Upload:**

* UploadAdapter
* SimpleUploadAdapter

**Embedding:**

* MediaEmbed
* HtmlEmbed

Other
~~~~~

**Link:**

* Link

**Table:**

* Table
* TableToolbar

**Style:**

* Font
* Style
* HorizontalLine

**Editing Tools:**

* Autoformat

**Word Processing Features:**

* Mention

.. |Downloads| image:: https://img.shields.io/pypi/dm/django-blocknote?style=flat
    :target: https://pypi.org/project/django-blocknote/
    :alt: PyPI - Downloads

.. |Version| image:: https://img.shields.io/pypi/v/django-blocknote
    :target: https://pypi.org/project/django-blocknote/
    :alt: PyPI - Version

.. |Docs| image:: https://readthedocs.org/projects/django-blocknote/badge/?version=latest
    :target: https://django-blocknote.readthedocs.io/en/latest/?badge=latest
    :alt: Documentation Status

.. |Python| image:: https://img.shields.io/pypi/pyversions/django-blocknote
    :target: https://www.python.org/
    :alt: PyPI - Python Version

.. |Django| image:: https://img.shields.io/pypi/frameworkversions/django/django-blocknote
    :target: https://docs.djangoproject.com/en/4.2/
    :alt: PyPI - Versions from Framework Classifiers

.. |Repo| image:: https://www.repostatus.org/badges/latest/wip.svg
    :target: https://www.repostatus.org/#wip
    :alt: Project Status: WIP – Initial development is in progress, but there has not yet been a stable, usable release suitable for the public.