semvec/pypi-packages huggingface dataset:
jupyter-anywidget-webllm 0.0.1
Jupyter anywidget for sideloading webllm wasm

# jupyter_anywidget_webllm

Example Jupyter anywidget that will sideload a `web-llm` model into the browser and run prompts against it.

For example:

```python
from jupyter_anywidget_webllm import webllm_headless

# Load the headless widget
w = webllm_headless()

# Wait for webllm wasm to load (blocking;; does not work in JupyterLite)
w.ready()

# Try a conversion
# This is blocking - does not work in JupyterLite
output = w.convert("Write me a poem")
output


#Non-blocking
w.base_convert("Write me a story")
# When it's ready, collect from:
w.response
> {'status': 'processing'}
> {'status': 'completed', 'output_raw': 'OUTPUT'}
```

TO DO: ALLOW a json outpur template from a string or file: Use `w.convert_from_file(path, output_template="", timeout=3)` etc. to load from a local file path or a URL.

## Installation

```sh
pip install jupyter_anywidget_webllm
```

or with [uv](https://github.com/astral-sh/uv):

```sh
uv add jupyter_anywidget_webllm
```

Open `example.ipynb` in JupyterLab, VS Code, for a demo...
probabilistic.py 0.2.0
A package for probabilistic function execution.

# Probabilistic.py

Probabilistic is a Python library designed to facilitate the probabilistic execution of functions and the analysis of their outcome distributions. Whether you're simulating uncertain events, performing randomized experiments, or adding an element of chance to your applications, Probabilistic provides a straightforward and flexible toolkit to meet your needs.

## Table of Contents

- [Features](#features)
- [Installation](#installation)
- [Quick Start](#quick-start)
- [Documentation](#documentation)
- [Support This Project](#support-this-project)


## Features
- [x] Probabilistic Function Function
- [x] Mutual Exclusivity Function
- [x] Distribution Analysis Function
- [x] Customizable Random Engines

- [ ] Conditional Probability-Based Function
- [ ] Probability Chains
- [ ] Asynchronous Execution Support
- [ ] Integration with Popular Libraries like NumPy and Pandas for enhanced data handling and analysis.

## Installation

You can install the **Probabilistic** library using `pip`. Ensure that you have Python 3.6 or higher installed on your system.

```bash
pip install probabilistic.py
```

## Quick Start

Here's a quick example to get you started with Probabilistic.

```python
import probabilistic

def hello():
    print("Hello!")

# Create a probabilistic function with a 50% execution probability
maybe_hello = probabilistic.function(func=hello, p=0.5)

# Execute the probabilistic function
maybe_hello()
```

## Documentation
For documentation, please see the [API Reference](docs/API_Reference.md) and [Examples](docs/Examples.md).


## Support This Project
If you find this project helpful, please consider giving it a star on GitHub! 🌟

If you'd like to improve this project, feel free to submit a pull request or open an issue. Let's build something great together! 🚀

*Happy Probabilistic Coding!*