semvec/pypi-packages huggingface dataset:
mycodoc 0.1.0
TODO: Describe your project
Requires Python: >=3.9

# Mycodoc

## What is it?
Mycodoc is ...

[![Issues](https://img.shields.io/github/issues/chris-greening/mycodoc)](https://github.com/chris-greening/mycodoc/issues)
[![License](https://img.shields.io/github/license/chris-greening/mycodoc)](LICENSE)
[![Version](https://img.shields.io/pypi/v/mycodoc?color=brightgreen)](https://pypi.org/project/mycodoc/)

## Table of Contents
* [Key features](#key-features)
* [Installation](#installation)
* [Quickstart](#quickstart)
* [Contributing](#contributing)
* [Blog posts](#blog-posts)
* [Documentation](#documentation)
* [License](#license)
* [Support](#support)

---

## :key: Key features <a name="key-features"></a>

---

## :computer: Installation <a name="installation"></a>

### pip
Install the latest stable release from PyPI using
```shell
$ pip3 install Mycodoc

```

or clone the development version from GitHub with
```shell
$ git clone https://github.com/chris-greening/mycodoc.git
```

---

## :seedling: Quickstart <a name="quickstart"></a>

Mycodoc is designed to be ...

---

## :pray: Contributing <a name="contributing"></a>
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome!

Feel free to [open an Issue](https://github.com/chris-greening/mycodoc/issues/new/choose), check out existing [Issues](https://github.com/chris-greening/mycodoc/issues), or [start a discussion](https://github.com/chris-greening/mycodoc/discussions).

Beginners to open source are highly encouraged to participate and ask questions if you're unsure what to do/where to start

---

## :newspaper: Blog posts <a name="blog-posts"></a>
Check out the [official website](https://chris-greening.github.io/mycodoc/) for the latest blog posts on the project!

---

## :books: Documentation <a name="documentation"></a>
<!-- The official documentation can be found on [Read The Docs](https://mycodoc.readthedocs.io/en/latest/index.html) -->

---

## :credit_card: License <a name="license"></a>
This library operates under the [MIT](LICENSE) license.

---

## :grey_question: Support <a name="support"></a>
totalopenstation 0.7.2
Download and export survey data from your total station
Requires Python: >=3.9
Keywords: survey, geodimeter, fieldwork, format conversion

====================
 Total Open Station
====================


.. image:: https://github.com/totalopenstation/totalopenstation/actions/workflows/pytest.yml/badge.svg
  :alt: pytest continuous integration 

.. image:: https://img.shields.io/pypi/v/totalopenstation
  :target: https://pypi.org/project/totalopenstation/
  :alt: PyPI

.. image:: https://img.shields.io/readthedocs/totalopenstation
  :target: https://totalopenstation.readthedocs.io/
  :alt: Read the Docs

|

Total Open Station is a program for downloading and processing survey data from total station devices.

.. image:: https://tops.iosa.it/img/totalopenstation-gui.gif

Total Open Station is a good choice if:

- you work with total stations on GNU/Linux (and MacOS, probably)
- you work with old devices that are unsupported by vendors
- you need to process hundreds of data files at once

We think Total Open Station is small but great because:

- it is *free/libre open source software*
- it works on *any* operating system where Python is available
- it is designed to support as many devices and formats as possible, all
  within the same program, opposed to having one program per device
- it works both on the command line and with a graphical interface

Total Open Station uses a modular structure and
keeps the downloading of data logically separated from its processing,
thus enabling exporting data to a variety of output formats, even at a
later moment. Archiving of raw data is made easy by using plain text
files.

Installing
==========

If you're comfortable with the command line:

.. code-block:: bash

    pip install totalopenstation

Windows users can download the portable app from the 
GitHub `releases page <https://github.com/steko/totalopenstation/releases>`_.

GNU/Linux users can find the `totalopenstation` package in some distributions
(OpenSUSE, Debian, Ubuntu). Make sure that `python3-tk` or `python3-tkinter` is
installed on your system, otherwise install it with your package manager (apt, dnf, pacman).

Documentation
=============

Documentation is online at http://totalopenstation.readthedocs.io/ with
an user guide, details on the application structure, supported models
and other interesting stuff.

Development
===========

Total Open Station is developed by @steko, @psolyca and other contributors, including
translators and providers of sample data. We are not professional software developers
but we do our best to follow modern good practice. Feel free to submit a feature request
or a pull request on GitHub.

The application icons are copyright by Lapo Calamandrei 2008, under the
same license as Total Open Station.
docspore 0.1.0
TODO: Describe your project
Requires Python: >=3.9

# Docspore

## What is it?
Docspore is ...

[![Issues](https://img.shields.io/github/issues/chris-greening/docspore)](https://github.com/chris-greening/docspore/issues)
[![License](https://img.shields.io/github/license/chris-greening/docspore)](LICENSE)
[![Version](https://img.shields.io/pypi/v/docspore?color=brightgreen)](https://pypi.org/project/docspore/)

## Table of Contents
* [Key features](#key-features)
* [Installation](#installation)
* [Quickstart](#quickstart)
* [Contributing](#contributing)
* [Blog posts](#blog-posts)
* [Documentation](#documentation)
* [License](#license)
* [Support](#support)

---

## :key: Key features <a name="key-features"></a>

---

## :computer: Installation <a name="installation"></a>

### pip
Install the latest stable release from PyPI using
```shell
$ pip3 install Docspore

```

or clone the development version from GitHub with
```shell
$ git clone https://github.com/chris-greening/docspore.git
```

---

## :seedling: Quickstart <a name="quickstart"></a>

Docspore is designed to be ...

---

## :pray: Contributing <a name="contributing"></a>
All contributions, bug reports, bug fixes, documentation improvements, enhancements, and ideas are welcome!

Feel free to [open an Issue](https://github.com/chris-greening/docspore/issues/new/choose), check out existing [Issues](https://github.com/chris-greening/docspore/issues), or [start a discussion](https://github.com/chris-greening/docspore/discussions).

Beginners to open source are highly encouraged to participate and ask questions if you're unsure what to do/where to start

---

## :newspaper: Blog posts <a name="blog-posts"></a>
Check out the [official website](https://chris-greening.github.io/docspore/) for the latest blog posts on the project!

---

## :books: Documentation <a name="documentation"></a>
<!-- The official documentation can be found on [Read The Docs](https://docspore.readthedocs.io/en/latest/index.html) -->

---

## :credit_card: License <a name="license"></a>
This library operates under the [MIT](LICENSE) license.

---

## :grey_question: Support <a name="support"></a>
coffeeblack 0.1.12
Python client for interacting with the CoffeeBlack visual reasoning API
Requires Python: >=3.7

# CoffeeBlack SDK

Python client for interacting with the CoffeeBlack visual reasoning API.

## Installation

You can install the package using pip:

```bash
# Install from PyPI
pip install coffeeblack

# Install from local directory
pip install -e .

# Or install from GitHub
pip install git+https://github.com/coffeeblack/sdk.git
```

## Features

- Find and interact with windows on your system
- Take screenshots and send them to the CoffeeBlack API
- Execute actions based on natural language queries
- Reason about UI elements without executing actions
- Find and launch applications with semantic search

## Quick Start

```python
import asyncio
import os
from coffeeblack import Argus

async def main():
    # Initialize the SDK with API key for authentication
    # You can provide your API key directly or through an environment variable
    api_key = os.environ.get("COFFEEBLACK_API_KEY")
    sdk = Argus(
        api_key=api_key,  # API key for authentication
        verbose=True,
        debug_enabled=True,
        elements_conf=0.2,
        rows_conf=0.4,
        model="ui-detect"  # Set the UI detection model to use (cua, ui-detect, or ui-tars)
    )
    
    # Define the browser name
    browser_name = "Safari" 
    
    try:
        # Open and attach to the browser
        await sdk.open_and_attach_to_app(browser_name, wait_time=2.0)

        # Execute an action based on a natural language query
        await sdk.execute_action("Type https://www.google.com into the url bar")
        
        # Press enter key
        await sdk.press_key("enter")
    
    except Exception as e:
        print(f"Error: {e}")

if __name__ == "__main__":
    asyncio.run(main())
```

## License

MIT

## Documentation

For more detailed documentation, please visit [https://docs.coffeeblack.ai](https://docs.coffeeblack.ai)
image-generation-mcp-server 0.1.1
A Model Context Protocol (MCP) server to generate images by text prompts via modelscope
Requires Python: >=3.11

# Feature
- 📝 Support image generation by text via Modelscope

# Prerequisites
1. Python 3.11+
2. Modelscope Key (apply from [Modelscope](https://www.modelscope.cn/))
3. Node.js (optional, for MCP Inspector)

# Install 
1. python packages
```bash
pip install -r requirements.txt
```

2. install image_generation_mcp_server
```bash
pip install image-generation-mcp-server
```

# Debug by MCP Inspector
start the inspector by following command in terminal (replace YOUR_MODELSCOPE_API_KEY with your own key):
```bash
npx @modelcontextprotocol/inspector -e MODELSCOPE_API_KEY=YOUR_MODELSCOPE_API_KEY python -m image_generation_mcp_server
```



# Start the server
start the server by following command:
```bash
env MODELSCOPE_API_KEY=YOUR_MODELSCOPE_API_KEY python -m image_generation_mcp_server
```

or you can add following json into your config file
```json
{
    "mcpServers": {
        "image-generation-mcp-server": {
            "command": "python",
            "args": [
                "-m",
                "image_generation_mcp_server"
            ],
            "env": {
                "MODELSCOPE_API_KEY": "YOUR_MODELSCOPE_API_KEY"
            }
        }
    }
}
```