semvec/pypi-packages huggingface dataset:
cult-common 0.2.0
Shared utilities, schemas, and mixins for Cult microservices
License: MIT
Requires Python: >=3.8

```
# cult-common

Shared configuration and utility library for Cult microservices.

## Installation

pip install cult-common==0.1.0


## Usage

from cult_common.config import settings
logger = cult_common.logging.get_logger(__name__)

print(settings.KAFKA_BOOTSTRAP_SERVERS)
```
llm-fragments-youtube 0.1.1
LLM plugin for loading YouTube subtitles as fragments
License: MIT
Requires Python: >=3.9

# LLM YouTube Fragments Plugin

A plugin for [Simon Willison's LLM tool](https://github.com/simonw/llm) that adds a `youtube` fragment loader to download and use YouTube video subtitles in your prompts.

## Installation

1. Make sure you have the LLM tool installed:
   ```bash
   pip install llm
   ```

2. Install this plugin:
   ```bash
   llm install llm-fragments-youtube
   ```

   This will automatically install all dependencies, including yt-dlp.

## Usage

You can use the `youtube` or `yt` fragment in your LLM prompts to include subtitles from YouTube videos:

```bash
# Using a YouTube video ID
llm -f youtube:dQw4w9WgXcQ "summarize this video"

# You can also use the shorter 'yt' prefix
llm -f yt:dQw4w9WgXcQ "summarize this video"

# Continue chatting
llm -c "at which minute do they talk about ..."

# Language can also be specified
llm -f youtube:es:dQw4w9WgXcQ "resume el video"

# Using a full YouTube URL
llm -f youtube:https://www.youtube.com/watch?v=dQw4w9WgXcQ "summarize video"
```

## Development

### Running Tests

To run the tests, first install the package with test dependencies:

```bash
pip install -e ".[test]"
```

Then run the tests using pytest:

```bash
pytest
```

## License

Beerware
mammoclip 0.1.8
Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography
License: MIT
Requires Python: >=3.8
Keywords: mammography, clip, medical-imaging, deep-learning, computer-vision

# Mammo-CLIP

**Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography**

A pip-installable package for zero-shot mammography analysis using the Mammo-CLIP model.

## Installation

```bash
pip install mammoclip
```

## Quick Start

### Python API

```python
import mammoclip

# Initialize model (downloads automatically)
model = mammoclip.MammoClipModel()

# Analyze an image (supports DICOM, PNG, JPEG, etc.)
results = model.predict("mammogram.dcm", {
    "mass": ["no mass", "mass"],
    "malignancy": ["no malignancy", "malignancy"],
    "density": ["fatty", "scattered areas of fibroglandular density", 
               "heterogeneously dense", "extremely dense"]
})

print(results)
```

### Command Line Interface

```bash
# Basic usage
mammoclip-inference --image mammogram.dcm

# With custom prompts
mammoclip-inference --image mammogram.png --prompts custom_prompts.json
```

## Supported Image Formats

- **DICOM**: `.dcm`, `.dicom` 
- **Standard Images**: `.png`, `.jpg`, `.jpeg`, `.tiff`, `.bmp`

## Model Information

This package is based on the research paper:

**"Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography"**

- **Paper**: https://arxiv.org/abs/2409.03675
- **Original Code**: https://github.com/batmanlab/Mammo-CLIP

## Citation

```bibtex
@article{shen2024mammoclip,
  title={Mammo-CLIP: A Vision Language Foundation Model to Enhance Data Efficiency and Robustness in Mammography},
  author={Shen, Shantanu and Xu, Haoyue and Weng, Jaden and Wu, Jay and Chen, Evangelia and Abbasi, Salma and Wang, Rayna and Bouzid, Hania and Rajpurkar, Pranav},
  journal={arXiv preprint arXiv:2409.03675},
  year={2024}
}
```

## License

MIT License
ytsummary 0.1.1
YouTube video summary generator
License: MIT
Requires Python: >=3.8

# YTSummary

YouTube 비디오의 자막을 추출하고 요약하는 Python 라이브러리입니다.

## 설치 방법

```bash
pip install ytsummary
```

## 사용 방법

```python
from ytsummary.youtube_utils import extract_video_id, get_transcript
from ytsummary.summarizer import summarize_text

# YouTube URL에서 비디오 ID 추출
video_url = "https://www.youtube.com/watch?v=your_video_id"
video_id = extract_video_id(video_url)

# 자막 가져오기
transcript = get_transcript(video_id)

# 자막 요약하기
summary = summarize_text(transcript)
print(summary)
```

## 주요 기능

- YouTube 비디오 ID 추출
- 자막 추출 (YouTube Transcript API 사용)
- 텍스트 요약

## 의존성

- requests
- beautifulsoup4
- youtube_transcript_api
- transformers
- torch

## 라이선스

MIT License