semvec/pypi-packages huggingface dataset:
chunklet 1.4.0
A smart multilingual text chunker for LLMs, RAG, and beyond.
Requires Python: >=3.8
Keywords: nlp, chunking, text-splitting, llm, rag, ai, multilingual, text processing, natural language processing, data processing, information retrieval, semantic search, document processing

# 🧩 Chunklet (Wrapper Package)

> **Note:** This is the `chunklet` wrapper package. It ensures backward compatibility and depends on the new, actively developed `chunklet-py` package.

The `chunklet` package name on PyPI has been transitioned to a wrapper for the new `chunklet-py` package. This was done to improve online discovery and distinguish it from other projects with similar names.

## For New Users

To use Chunklet, please install the `chunklet-py` package directly:

```bash
pip install chunklet-py
```

## For Existing Users

If you are an existing user of `chunklet`, your code will continue to work as expected. When you install or update the `chunklet` package, `pip` will automatically install `chunklet-py` for you. You can continue to import the library as you always have:

```python
import chunklet
```
questions-cli 0.1.2
CLI for processing search queries for the app
Requires Python: >=3.9
Keywords: cli, questions, search, queries

## Questions App Query CLI

A CLI for processing a questions for search queries on the app.

### Install from PyPI

```bash
pip install questions-cli
```

### Install (local dev)

```bash
pip install -e .
```

### Set environment variables

```bash
export MONGO_URI=""
export LLM_API_KEY="<your_llm_api_key>"
```

### Usage

- Show help:

```bash
questions-cli --help
```

- Show version:

```bash
questions-cli --version
```

- Quick run (process CSV):

```bash
questions-cli data/queries.csv
```

- Explicit ingest command (same behavior):

```bash
questions-cli ingest data/queries.csv
```

### Common options

- `-d, --delimiter` CSV delimiter (default `,`)
- `--dry-run` Parse and classify/generate without DB writes
- `--limit N` Process only first N rows
- `--subjects-file PATH` Subjects mapping file (csv/yaml/json)

### Examples

```bash
questions-cli data/queries.csv --dry-run
questions-cli ingest data/queries.csv -d ';' --limit 100
questions-cli ingest data/queries.csv --subjects-file subjects.yaml
```
netbox-cable-labels 0.1.0
NetBox plugin for automatic cable label generation
Requires Python: >=3.9
Keywords: netbox, netbox-plugin, cable-management, labeling

# NetBox Auto Cable Label Plugin

Plugin for netbox that allows the automatic generation of the label field content for cables based on a user defined template

* Free software: Apache-2.0

## Compatibility

| NetBox Version | Plugin Version |
|----------------|----------------|
|     4.x        |      0.1.x     |


## Installing

For adding to a NetBox Docker setup see
[the general instructions for using netbox-docker with plugins](https://github.com/netbox-community/netbox-docker/wiki/Using-Netbox-Plugins).

### Install from PyPI

```bash
pip install netbox-cable-labels
```

### Install from GitHub

```bash
pip install git+https://github.com/jsenecal/netbox-cable-labels
```

or by adding to your `local_requirements.txt` or `plugin_requirements.txt` (netbox-docker):

```bash
netbox-cable-labels
```

Enable the plugin in `/opt/netbox/netbox/netbox/configuration.py`,
 or if you use netbox-docker, your `/configuration/plugins.py` file :

```python
PLUGINS = [
    'netbox_cable_labels'
]
```


## Configuring

Setup PLUGINS_CONFIG with the following:
```python
PLUGINS_CONFIG = {
    "netbox_cable_labels": {"label_template": "Some Jinja2 template string here"},
}
```

> Please note that the cable instance is passed as `cable` to the templating engine.

### Default configuration

By default, the plugin copies the cable `id` in the label, prefixed with the pound (#) sign.

```
"#{{cable.pk}}"
```

## Management command

Using `manage.py`, you can run the command `generate_labels` to automatically generate labels on cables that do not already have one set, based on the configured template.

```
./manage.py generate_labels
```
viz3dvideo 0.1.1
Visualize a video of 3D graphs in Matplotlib
Requires Python: >=3.8
Keywords: writing, translate

# viz3dvideo

Visualize a video of 3D graphs in Matplotlib

[![logo](https://raw.githubusercontent.com/trucomanx/Viz3DVideo/main/screenshot.png)](https://www.youtube.com/watch?v=OSm2YUywPsQ)

## 1. Installing

To install the package from [PyPI](https://pypi.org/project/viz3dvideo/), follow the instructions below:


```bash
pip install --upgrade viz3dvideo
```

Execute `which viz3dvideo-info` to see where it was installed, probably in `/home/USERNAME/.local/bin/viz3dvideo-info`.

### Using

To start, use the command below:

```bash
viz3dvideo-info
```
## 2. More information

If you want more information go to [doc](https://github.com/trucomanx/Viz3DVideo/blob/main/doc) directory.

## 3. Buy me a coffee

If you find this tool useful and would like to support its development, you can buy me a coffee!  
Your donations help keep the project running and improve future updates.  

[☕ Buy me a coffee](https://ko-fi.com/trucomanx) 

## 4. License

This project is licensed under the GPL license. See the `LICENSE` file for more details.