semvec/pypi-packages huggingface dataset:
dgi-serve 0.1.0.dev0
DGI: The Deep-neural-network General Inference service & framework.
License: MIT
Requires Python: >=3.8
Keywords: dgi, dgi-serve, deep-learning, inference

# DGI

DGI: The Deep-neural-network General Inference framework.

## Installation

You can install DGI using pip:

```bash
pip install dgi-serve
```

## Quick Start

```python
from dgi import hello_world

# Use the package
print(hello_world())
```

## Features

- Simple and easy to use
- Well documented
- Fully tested

## Usage

Here's a basic example of how to use DGI:

```python
import dgi

# Example usage
dgi.main()
```

## Development

To set up the development environment:

```bash
# Clone the repository
git clone https://github.com/deepnova/dgi-serve.git
cd dgi-serve

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest

# Run linting
black .
flake8 .
```

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

## Author

Wilhelm Jung

## Changelog

### 0.1.0-dev (Development Release)
- Development version of DGI package
- Basic framework structure
- Core inference functionality outline

### 0.1.0 (Initial Release)
- Initial release of DGI package
- Basic functionality implemented
faker-news 0.1.2
Faker provider for generating fake news content using OpenAI-compatible LLM APIs
License: MIT
Requires Python: >=3.9
Keywords: faker, news, generator, llm, openai

# faker-news

Faker provider that turns any OpenAI-compatible LLM into a fake news generator with caching and reuse controls.

## Features
- Generate headlines, intros, and full articles on demand
- Keep content in a SQLite cache with per-item usage tracking
- Batch requests to minimize API calls and latency
- Works with OpenAI, Azure OpenAI, Qwen/DashScope, and other OpenAI-compatible APIs

## Installation
```bash
pip install faker-news
```

## Quick Start

Try it without installation using uvx:
```bash
# Set up your API key / load example data
uvx faker-news setup

# Browse generated articles
uvx faker-news browse
```

Use as a library:
```python
from faker import Faker
from faker_news import NewsProvider

fake = Faker()
provider = NewsProvider(fake)
fake.add_provider(provider)

headline = fake.news_headline()
intro = fake.news_intro(headline=headline)
article = fake.news_article(headline=headline, words=500)
```

## Documentation
Full guides, API reference, and CLI details live in the `docs/` directory. Start with `docs/quick-start.md` or `docs/cli-reference.md`.

## Contributing
See `docs/contributing.md` for the development workflow and guidelines.

## License
MIT