semvec/pypi-packages huggingface dataset:
st-datatables 0.1.0
Streamlit custom component: DataTables (React) wrapper
License: MIT
Requires Python: >=3.7
Keywords: streamlit, component, datatable, react

# streamlit-custom-component

Streamlit component that allows you to do X

## Installation instructions

```sh
pip install streamlit-custom-component
```

## Usage instructions

```python
import streamlit as st

from my_component import my_component

value = my_component()

st.write(value)
```
vdoc 0.21.0
Multi version documentation hosting.
License: MIT
Requires Python: >=3.11

.. image:: https://github.com/vorausrobotik/vdoc/actions/workflows/pipeline.yml/badge.svg
    :target: https://github.com/vorausrobotik/vdoc/actions/workflows/pipeline.yml
    :class: badge
.. image:: https://codecov.io/gh/vorausrobotik/vdoc/graph/badge.svg
    :target: https://codecov.io/gh/vorausrobotik/vdoc
    :class: badge
.. image:: https://img.shields.io/pypi/pyversions/vdoc
    :target: https://pypi.org/project/vdoc
    :class: badge
.. image:: https://img.shields.io/pypi/v/vdoc
    :target: https://pypi.org/project/vdoc
    :class: badge
.. image:: https://img.shields.io/badge/%20imports-isort-%231674b1?style=flat&labelColor=ef8336
    :target: https://pycqa.github.io/isort/
    :class: badge
.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
    :target: https://github.com/psf/black
    :class: badge

####
vdoc
####

Multi version documentation hosting.


Documentation
#############

Please read the `documentation <https://vorausrobotik.github.io/vdoc/>`_ for more a more detailed introduction.
archive-ocr 1.0.0
A Django app for AI and OCR logic extracted from archive-ocr.
License: MIT

# Smart Archive

A Django app that provides AI and OCR capabilities.

## Installation

1. Install via pip:
   ```bash
   pip install smart-archive
   ```

2. Add to `INSTALLED_APPS`:
   ```python
   INSTALLED_APPS = [
       ...
       'smart_archive',
   ]
   ```

3. Configure settings:
   ```python
   OCR_API_URL = "http://ocr-service:8000/ocr"
   LLM_API_URL = "http://llm-service:8000/v1/chat/completions"
   LLM_MODEL = "your-model-name"
   ```
py3Dmol 2.5.4
An IPython interface for embedding 3Dmol.js views in Jupyter notebooks
License: MIT
Keywords: molecule protein visualization

py3Dmol
=======

A simple [IPython/Jupyter](http://jupyter.org/) widget to
embed an interactive [3Dmol.js](http://3dmol.org) viewer in a notebook.

The widget is completely static, which means the viewer doesn't need a running
IPython kernel to be useful and web pages and presentations generated from
the notebook will work as expected.  However, this also means there is only
one-way communication between the notebook and the viewer.

If you experience problems, please file 
an [issue](https://github.com/3dmol/3Dmol.js/issues).


[An example notebook](http://nbviewer.jupyter.org/github/3dmol/3Dmol.js/blob/master/py3Dmol/examples.ipynb)

Installation
------------

From PyPI:

    pip install py3Dmol


Usage
-----

Open a notebook

    jupyter notebook

and issue

```Python
import py3Dmol
view = py3Dmol.view(query='pdb:1ubq')
view.setStyle({'cartoon':{'color':'spectrum'}})
view
```

API
---

The returned view object has the exact same API as [$3Dmol.GLViewer](https://3dmol.org/doc/GLViewer.html)
with the exception that functions return None.


License
-------

MIT