semvec/pypi-packages huggingface dataset:
clipsai 0.2.1
Clips AI is an open-source Python library that automatically converts long videos into clips
License: MIT
Requires Python: >=3.9

# ClipsAI

<!-- [![PyPI version](https://badge.fury.io/py/project-name.svg)](https://badge.fury.io/py/project-name) -->
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)


## Quickstart

Clips AI is an open-source Python library that automatically converts long videos into
clips. With just a few lines of code, you can segment a video into multiple clips and
resize its aspect ratio from 16:9 to 9:16.

> **Note:** Clips AI is designed for audio-centric, narrative-based videos such as
podcasts, interviews, speeches, and sermons. It actively employs video transcripts to
identify and create clips. Our resizing algorithm dynamically reframes and focuses on
the current speaker, converting the video into various aspect ratios.

For full documentation, visit [Clips AI Documentation](https://clipsai.com).
Check out a [UI demo](https://demo.clipsai.com) with clips generated by this library.

### Installation

```bash
pip install clipsai
```

```bash
pip install whisperx@git+https://github.com/m-bain/whisperx.git
```

## Creating clips

Clips are created based on the transcript of a video. You'll first need to transcribe
the video, and then you can create clips based on the transcript.
[WhisperX](https://github.com/m-bain/whisperX) is utilized under the hood to transcribe
videos.

```python
from clipsai import clip, transcribe

transcription = transcribe("video.mp4")
clips = clip(transcription)

print("StartTime: ", clips[0].start_time)
print("EndTime: ", clips[0].end_time)
```

## Resizing a video

You'll need to create an access token on hugging face to resize a video because 
[Pyannote](https://github.com/pyannote/pyannote-audio) is utilized for speaker 
diarization. You won't be charged for using Pyannote and instructions are on the
[Pyannote HuggingFace ](https://huggingface.co/pyannote/speaker-diarization-3.0) page.

```python
from clipsai import resize

crops = resize(
    video_file_path="video.mp4",
    pyannote_auth_token="pyannote_token",
    aspect_ratio=(9, 16)
)

print("Crops: ", crops.segments)
```
oryks-docstring-generator 0.5.0
A python library for generating documentation for python projects.
License: MIT
Keywords: dosctrings,documentation

# documentation-generator

## Overeview

This is a python library for generating documentation for python projects. It is built to:

- Generate function docstrings
- Generate class docstrings include class method docstrings (still under development)
- Generate sphinx documentation (still under development)

The library uses ``openai's`` gpt model to generate the function docstrings. You pass it a file or folder path togther with an ``openai`` api key. It then parses the folder for python files, then for each file, it finds the functions and classes, generates their documentation and updates their docstrings.

## Requirements

- Python 3.10+
- Works on Linux, Windows, macOS, BSD

## Installation

```sh
pip install oryks-docstring-generator
```

## Usage

First, provide the ``openai``  api key:

```sh
export OPENAI_API_KEY=sk-xxxxxxxxxxx
```

Then run the application, providing the path to the python file to generate docs for or the folder containing the python files:

```sh
python -m docstring_generator --path /home/lyle/tutorial/test-docstrings-generator/test/ --directories-ignore venv
--files-ignore test.py --overwrite-function-docstring True --overwrite-class-docstring True --overwrite-class-methods-docstring True --documentation-style Numpy-Style
```

<p align=center>
  <img src="docstring-generator.gif" />
</p>

## Documentation and Tutorials

To learn more about the library including the documentation and tutorials, check out the [libraries&#39; documentation](https://youtube-wrapper.readthedocs.io/en/latest/).

## How to Contribute

To contribute, chack out the [contribution guideline](CONTRIBUTING.md).

## License

The API uses an [MIT License](LICENSE)

## Developer

Lyle Okoth – [@lyleokoth](https://twitter.com/lyleokoth) on twitter

[lyle okoth](https://medium.com/@lyle-okoth) on medium

My email is lyceokoth@gmail.com

Here is my [GitHub Profile](https://github.com/twyle/)

You can also find me on [Linkedin](https://www.linkedin.com/in/lyle-okoth/)