semvec/pypi-packages huggingface dataset:
AIV2.0 1.0
Offline speech-to-text tool using browser frontend and Python backend
Requires Python: >=3.6

# ruhani-stt

**AIV2.0** is a lightweight offline Speech-to-Text tool that uses a browser-based frontend (HTML + JS) and Python backend via Selenium. It is designed to run speech recognition in a loop, capture your speech, and save it to a file or print in the terminal.

---

## 🔧 Features

- 🎙️ Voice recognition using browser's Web Speech API  
- 🔁 Continuous listening loop  
- 📄 Saves recognized speech to a `.txt` file  
- 💻 Terminal support with headless browser (Chrome)

---

## 🚀 Installation

```bash
pip install AIV2.0
pympv 0.9.0
Python bindings for the libmpv library

pympv
=====
A python wrapper for libmpv.

#### Basic usage
```python
import sys
import mpv

def main(args):
    if len(args) != 1:
        print('pass a single media file as argument')
        return 1

    try:
        m = mpv.Context()
    except mpv.MPVError:
        print('failed creating context')
        return 1

    m.set_option('input-default-bindings')
    m.set_option('osc')
    m.set_option('input-vo-keyboard')
    m.initialize()

    m.command('loadfile', args[0])

    while True:
        event = m.wait_event(.01)
        if event.id == mpv.Events.none:
            continue
        print(event.name)
        if event.id in [mpv.Events.end_file, mpv.Events.shutdown]:
            break


if __name__ == '__main__':
    try:
        exit(main(sys.argv[1:]) or 0)
    except mpv.MPVError as e:
        print(str(e))
        exit(1)
```

More examples can be found in the [samples](samples) directory.

libmpv is a client library for the media player mpv

For more info see: https://github.com/mpv-player/mpv/blob/master/libmpv/client.h

pympv was originally written by Andre D, and the PyPI package is maintained
by Hector Martin.
relation 1.0.3
a python module for making relationships between classes

# Relation
a python module for making relationships between classes
## how to use
`pip install relation` and import it in your python project:
```py
from relation import Relator
```
- to define a new relator (a custom class), use `class insert_name_here(Relator):`  
- to add a relation to a relator, multiply them
- to add a child to a relator, use `parent+child`
  - you can do `parent+[child1,child2,child3...]` to add multiple children
- to merge 2 relators, use `|` to change both or `|=` to change the first one
- to access a relator's relationships as a list of strings, use `.[insert relationship]_names`  
see examples for more usage
## mindmap (new)
import mindmap with
```
from relation.map import create_graph
```
create graphs with `create_graph`. you can define the depth and whether to include relations, parents, children or self from the graph.
the function will return a pyvis network, so make sure you have pyvis installed and show the graph with `graph.show`.
note that non-relator objects do not work in mindmaps
## roadmap
- [x] Python File
- [x] More examples and features
  -  [x] mindmaps
- [x] Upload to PyPi to able to be pip installed
- [ ] Swift Package
- [ ] NPM Package