semvec/pypi-packages huggingface dataset:
hyh 0.1.0a5
CLI orchestration tool for agentic workflows - coordinate tasks with claude-code and other AI agents
Requires Python: >=3.13
Keywords: agents, claude-code, cli, daemon, orchestration, tasks, unix-socket, workflow

# hyh

[![PyPI](https://img.shields.io/pypi/v/hyh.svg)](https://pypi.org/project/hyh/)
[![Python](https://img.shields.io/pypi/pyversions/hyh.svg)](https://pypi.org/project/hyh/)
[![License](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![CI](https://github.com/pproenca/hyh/actions/workflows/ci.yml/badge.svg)](https://github.com/pproenca/hyh/actions/workflows/ci.yml)

A CLI orchestration tool for agentic workflows. Coordinate tasks with AI agents through a daemon-based task management system.

hyh (hold your horses) provides DAG-based task orchestration with atomic state transitions, designed for coordinating claude-code and other AI agents in development workflows.

## Highlights

- **DAG-based orchestration** - Dependency resolution with cycle detection and topological validation
- **Thread-safe operations** - Concurrent task claiming with atomic state transitions via mutex protection
- **Client-daemon architecture** - Unix socket RPC for fast, reliable inter-process communication
- **Pull-based task claiming** - Workers claim tasks atomically, preventing race conditions
- **Command execution** - Run commands with mutex protection (local or Docker runtimes)
- **Git integration** - Safe git operations with dangerous option validation
- **Python 3.13+ / 3.14 freethreaded** - Modern Python with full type annotations

## Getting started

Run hyh with [uvx](https://docs.astral.sh/uv/guides/tools/#running-tools) to get started quickly:

```shell
uvx hyh status
```

Or start a workflow from a plan file:

```shell
uvx hyh plan import --file plan.md
uvx hyh status
```

## Installation

Install hyh as a persistent tool:

```shell
uv tool install hyh
```

Or with pip:

```shell
pip install hyh
```

For development installation, see [Contributing](#contributing).

## Usage

```shell
# Check daemon status
hyh ping

# Import and manage plans
hyh plan import --file plan.md
hyh status

# Claim and complete tasks
hyh task claim
hyh task complete --id task-1

# Execute commands with mutex protection
hyh exec -- make test

# Safe git operations
hyh git -- status
```

## Requirements

- Python 3.13+ (3.14 freethreaded supported)
- macOS or Linux
- [uv](https://docs.astral.sh/uv/) (recommended) or pip

## Getting help

If you have questions or want to report a bug, please open an
[issue](https://github.com/pproenca/hyh/issues) in this repository.

## Contributing

We welcome contributions! To get started:

```shell
git clone https://github.com/pproenca/hyh.git
cd hyh
make install
make test
```

See [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines.

## License

MIT License - see [LICENSE](LICENSE) for details.
nbp-cli 0.1.2
Nano Banana Pro - CLI for Gemini image generation
Requires Python: >=3.12
Keywords: nanobanana-pro, gemini, image-generation, cli, ai, google

# NBP CLI

![banana](banana.png)

CLI tool for generating and editing images using Google's Gemini 3 Pro image generation model.

## Installation

```bash
pip install nbp-cli
```

Then set your API key (get one from [Google AI Studio](https://aistudio.google.com/apikey)):

```bash
export GEMINI_API_KEY=your-api-key-here
```

Add the export to your `~/.zshrc` or `~/.bashrc` to persist it.

## Usage

```bash
# Generate a new image
nbp "a cute banana wearing sunglasses"

# With options
nbp "a futuristic city at sunset" -a 16:9 -r 2K -o city.png

# Edit an existing image
nbp "add a hat and sunglasses" -e input.png -o output.png

# Use Google Search grounding for real-time info
nbp "visualize today's weather in Tokyo" -s

# Use reference images for style or content guidance
nbp "a cute cat in this style" --reference style_image.png -o cat.png
nbp "a mix of these people" -ref person1.png person2.png
```

## Options

| Flag | Description | Default |
|------|-------------|---------|
| `-o, --output` | Output file path | `nbp_TIMESTAMP.png` |
| `-a, --aspect-ratio` | `1:1`, `2:3`, `3:2`, `3:4`, `4:3`, `4:5`, `5:4`, `9:16`, `16:9`, `21:9` | `1:1` |
| `-r, --resolution` | `1K`, `2K`, `4K` | `1K` |
| `-e, --edit` | Edit an existing image (provide input path) | - |
| `-ref, --reference` | One or more reference images to guide generation | - |
| `-s, --search` | Use Google Search grounding (prompt should ask to "visualize") | - |

## Development

```bash
git clone https://github.com/YishenTu/nbp-cli.git
cd nbp-cli
uv sync
cp .env.example .env  # Add your GEMINI_API_KEY
uv run nbp "test prompt"
```

## Global Access

For global access, add to your shell profile (`~/.zshrc` or `~/.bashrc`):

```bash
alias nbp='uv run --project /path/to/nbp-cli nbp'
```

## Claude Code Skill

The skill is fully self-contained. Just copy and set API key!

**Requirements:** Python 3.12+ (pre-installed on most systems)

1. Copy the skill folder:
   ```bash
   cp -r skills/nanobanana-pro ~/.claude/skills/
   ```

2. Set your API key in `~/.zshrc` or `~/.bashrc`:
   ```bash
   export GEMINI_API_KEY="your-api-key-here"
   ```

That's it! Claude will automatically use this skill when you ask it to generate or edit images. Python dependencies auto-install on first run.
gr8pc 0.2.0
gr8pc: A High-Level gRPC Wrapper for python
Requires Python: >=3.11

# gr8pc: A High-Level gRPC Wrapper for python

This library is a direct adaptation of
[py-grpcio](https://github.com/Niche-Solutions-LLC/py-grpcio), featuring a few modifications and
tailored customizations. Depending on your needs, you may find the original repository better suited
to your requirements and preferred practices.

---

## Background and Motivation

As noted before, `gr8pc` is an adaptation of the `py-grpcio` library, with a few key modifications:

- **Python 3.11 Compatibility**: This library is compatible with Python 3.11 (the original library demands >=3.12).
- **Separation between Logic and Protobuf file Generation**: `gr8pc` splits into two subprojects: one for the core server and client logic, and another (optional) CLI tool for `.proto` file generation. This design decision was made to make the dependency on `jinja` not necessary for the core library.
  In other words, the core library won't generate `.proto` files during runtime and will raise an error if it can't find them. The `.proto` file must be generated at development time using the CLI tool.

## Installation

```bash
pip install gr8pc
```

To install the optional CLI:

```bash
pip install gr8gen
```

## Usage

For usage documentation, please refer to the original
[py-grpcio](https://github.com/Niche-Solutions-LLC/py-grpcio) repository.

## Proto Generation Tool

```bash
$ gr8gen --help

usage: gr8gen [-h] [--version] [-o OUT] -s SVCS [SVCS ...]

A CLI tool for processing paths and services.

options:
  -h, --help            show this help message and exit
  --version             show program's version number and exit
  -o OUT, --out OUT     Path for output. Must be an existing or new directory. (default: ./proto)
  -s SVCS [SVCS ...], --svcs SVCS [SVCS ...]
                        Python-like import path(s) for service(s). Example: 'path.to.class.Class'. (default: None)
```

The gr8gen tool generates the necessary `.proto` file. Usage:

```bash
gr8gen --output /path/to/proto/folder --service path.to.service.Service path.to.another.service.AnotherService
```

## Acknowledgments

This library is derived directly from the `py-grpcio` package, maintaining much of the original
structure and functionality.
gr8gen 0.1.2
gr8gen: protobuf generator for gr8pc
Requires Python: >=3.11

# gr8gen: protobuf generator for gr8pc

This tool is a direct adaptation of
[py-grpcio](https://github.com/Niche-Solutions-LLC/py-grpcio), featuring a few modifications and
tailored customizations. Depending on your needs, you may find the original repository better suited
to your requirements and preferred practices.

---

## Background and Motivation

As noted before, `gr8pc` is an adaptation of the `py-grpcio` library, with a few key modifications:

- **Python 3.11 Compatibility**: This library is compatible with Python 3.11 (the original library
  demands >=3.12).
- **Separation between Logic and Protobuf file Generation**: `gr8pc` splits into two subprojects:
  one for the core server and client logic, and another (optional) CLI tool for `.proto` file
  generation. This design decision was made to make the dependency on `jinja` not necessary for the
  core library. In other words, the core library won't generate `.proto` files during runtime and
  will raise an error if it can't find them. The `.proto` file must be generated at development time
  using the CLI tool.

## Installation

```bash
pip install gr8pc
```

To install the optional CLI:

```bash
pip install gr8gen
```

## Usage

For usage documentation, please refer to the original
[py-grpcio](https://github.com/Niche-Solutions-LLC/py-grpcio) repository.

## Proto Generation Tool

The gr8gen tool generates the necessary `.proto` file. Usage:

```bash
gr8gen --output /path/to/proto/folder --service path.to.service.Service path.to.another.service.AnotherService
```

## Acknowledgments

This library is derived directly from the `py-grpcio` package, maintaining much of the original
structure and functionality.