semvec/pypi-packages huggingface dataset:
denso-mcp 0.4.2
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Requires Python: >=3.10

# AI Planet 3D-2D Converter

A Streamlit application that allows users to upload 3D model files (like .step, .x_t) and convert them to 2D drawings using SolidWorks.

## Features

- Upload 3D model files (.step, .x_t, .stp, .igs, .iges, etc.)
- Automatic conversion to 2D drawings with multiple views (TOP, FRONT, ISOMETRIC)
- Display of conversion status and results

## Requirements

- Python 3.10+
- Streamlit
- aiohttp
- fastmcp
- pythonnet
- Access to SolidWorks API service

## Installation

Use `uv` to setup the environment and install dependencies
```bash
uv sync
```

## Usage

### For claude desktop
The project is published on **PyPI** and can be installed from there
To run it,
```bash
uvx denso-mcp # starts the server in stdio mode
```
> You can use the server-config.json in the project, can paste its contents into clause's config
> to start the mcp server

### For streamlit app

1. Start the MCP server in **sse** mode
   ```bash
   uv run mcp-server.py --sse
   ```

   The server will start at [http://localhost:10001](http://localhost:10001)

2. Run the Streamlit app:
   ```bash
   streamlit run streamlit_app.py
   ```

3. Open your web browser and navigate to the URL displayed in the terminal (usually http://localhost:8501)

4. Upload a 3D model file using the file uploader

5. Click the "Convert to 2D" button to start the conversion process

6. Wait for the conversion to complete and view the results

## Notes

- The application requires access to a running SolidWorks API service
- Ensure that the SolidWorks API service URL is correctly configured in the application
- The temporary uploaded files are stored in the `temp_uploads` directory
unifi-ml2-driver 1.0.7
Unifi Modular Layer 2 (ML2) driver.
Requires Python: >=3.12.0

# UniFi ML2 Driver for Neutron

This is a Modular Layer 2 [Neutron Mechanism driver](https://wiki.openstack.org/wiki/Neutron/ML2) specifically designed for Ubiquiti UniFi switches. The mechanism driver is responsible for applying configuration information to UniFi hardware equipment.

The unifi-ml2-driver provides integration between OpenStack Neutron and Ubiquiti UniFi Network controllers to manage switch ports, VLANs, and other features on UniFi switches. It's designed to support use-cases like OpenStack Ironic multi-tenancy mode and abstracts applying changes to all UniFi switches managed by the UniFi controller.

UniFi ML2 Driver is distributed under the terms of the Apache License, Version 2.0. The full terms and conditions of this license are detailed in the LICENSE file.

## Project resources

- Source: [https://github.com/ubiquity-community/unifi-ml2-driver](https://github.com/ubiquity-community/unifi-ml2-driver)
- Python Package: [https://pypi.org/project/unifi-ml2-driver/](https://pypi.org/project/unifi-ml2-driver/)

## Features

- VLAN Networks: Creating and managing VLAN networks on UniFi switches
- Port Binding: Binding ports to specific switch ports

- Trunk Ports: Managing trunk ports with native and tagged VLANs
- Port Security: Configuring port security features (BPDU guard, loop guard)
- QoS: Bandwidth limiting on a per-port basis
- Storm Control: Limiting broadcast, multicast, and unknown unicast traffic
- Port Monitoring: Monitoring port state and updating OpenStack port status

## Requirements

- Python 3.12+
- OpenStack Neutron 13.0.0+
- aiounifi 83+
- UniFi Network Controller
- UniFi switches
perlin-noise-ex 0.1.3
Python implementation of Perlin noise generator
Requires Python: >=3.7

# perlin_noise_ex

Python implementation of Perlin noise generator by Exityx

## Installation

```bash
pip install perlin_noise_ex
```

## Usage

```python
from perlin_noise_ex import CreateNewPerlinNoise

# Create noise generator
noise = CreateNewPerlinNoise(seed=20, octave=2, amp=7, period=24)

matrix = noise.createPerlin()

noise.showGraph(matrix)

```

## License

MIT