semvec/pypi-packages huggingface dataset:
llm-gemini-youtube 0.0.3
LLM plugin to access Google's Gemini family of models, with support for YouTube URLs
Requires Python: >=3.10

# llm-gemini-youtube

[![PyPI](https://img.shields.io/pypi/v/llm-gemini-youtube.svg)](https://pypi.org/project/llm-gemini-youtube/)
[![Changelog](https://img.shields.io/github/v/release/ftnext/llm-gemini-youtube?include_prereleases&label=changelog)](https://github.com/ftnext/llm-gemini-youtube/releases)
[![Tests](https://github.com/ftnext/llm-gemini-youtube/actions/workflows/test.yml/badge.svg)](https://github.com/ftnext/llm-gemini-youtube/actions/workflows/test.yml)
[![License](https://img.shields.io/badge/license-Apache%202.0-blue.svg)](https://github.com/ftnext/llm-gemini-youtube/blob/main/LICENSE)

LLM plugin to access Google's Gemini family of models, with support for YouTube URLs  
https://ai.google.dev/gemini-api/docs/video-understanding#youtube

## Installation

Install this plugin in the same environment as [LLM](https://llm.datasette.io/).
```bash
llm install llm-gemini-youtube
```
## Usage

```bash
llm -m gemini-2.0-flash-yt -a 'https://www.youtube.com/watch?v=9hE5-98ZeCg' 'Can you summarize this video?'

llm -m gemini-1.5-pro-yt -a 'https://www.youtube.com/watch?v=9hE5-98ZeCg' 'What are the examples given at 01:05 and 01:19 supposed to show us?'

llm -m gemini-1.5-pro-yt -a 'https://www.youtube.com/watch?v=9hE5-98ZeCg' 'Transcribe the audio from this video, giving timestamps for salient events in the video. Also provide visual descriptions.'
```

## Development

To set up this plugin locally, first checkout the code. Then create a new virtual environment:
```bash
cd llm-gemini-youtube
python -m venv venv
source venv/bin/activate
```
Now install the dependencies and test dependencies:
```bash
python -m pip install -e '.[test]'
```
To run the tests:
```bash
python -m pytest
```
autowordle 2.3.5
Automatic Wordle collector
Requires Python: >=3.12

# autowordle

An automatic collector for Wordle clones.

The program listens to the clipboard and then saves them to text files.
When all the games are collected according to the config file
(by default in =~/.config/autowordle/games.yaml=),
then construct an image and put it into the clipboard.
Then save all the files into various archives.

This is very tailored to my personal use case
and may be difficult to use for others.