semvec/pypi-packages huggingface dataset:
rich-gradient-cli 0.1.0
CLI for printing text in gradient color using the rich-gradient library.
Requires Python: >=3.14

# rich-gradient-cli

 `rich-gradient-cli`  is a CLI for [`rich-gradient`](https://github.com/maxludden/rich-gradient). The tool allows you to create colorful gradients in your terminal output, making it easier to visualize data or simply add some flair to your command-line applications.

## Installation

You can install rich-gradient-cli from PyPI

### uv (recommended)

```shell
uv add rich-gradient-cli
```

### pip

```shell
pip install rich-gradient-cli
```

## Usage


### Print

To use the `rich-gradient-cli`, you can run the following command in your terminal:

```bash
gradient print --colors 'red,#ff9900,#ffff00' "This is gradient text that starts red, transitions through orange, and ends in yellow\!"
```

![Gradient Text Example](print-example.svg)


### Rule

You can also create gradient rules using the `rule` command:

```bash
gradient rule --colors 'blue,#00ff00,cyan' "Blue to Green to Cyan Rule"
```

![Gradient Rule Example](rule-example.svg)

### Panel

To create a gradient panel, you can use the `panel` command:

```bash
gradient panel --colors "red,#ff9999" -t "Error" --title-style "bold #ffffff" --title-align left 'This is an error message with a red to pink gradient background.'
```

![Gradient Panel Example](panel-example.svg)

### Markdown

You can also render Markdown with gradients:

```bash
echo "# Hello\n\n- This is **bold**.\n- This is *italic*." | gradient markdown -
```

![Gradient Markdown Example](markdown-example.svg)

## Docs

Build and preview the documentation locally with MkDocs:

```bash
uv pip install -e ".[docs]"
mkdocs serve
```



<div align="center">
  <a href="https://github.com/maxludden/maxludden" style="text-decoration:none; color:inherit;">
      <p>Designed by Max Ludden</p>
  </a>
  <br />
  <a href="https://github.com/maxludden/maxludden" style="text-decoration:none; color:inherit;">
    <img
      src="https://github.com/maxludden/maxludden/blob/f3913ecf11f90c97435e2b55d2e43dadd51c1fe4/Images/MaxLogo-animated.svg"
      alt="Max Ludden's Logo"
      width="20%"
    />
  </a>
</div>
afm-py 0.1.3
AFM (Agent-Flavored Markdown) interpreter using LangChain
Requires Python: >=3.11

# AFM LangChain Interpreter

A LangChain-based reference implementation of an interpreter for [Agent-Flavored Markdown (AFM)](https://github.com/wso2/agent-flavored-markdown) files.

## Features

- **Support for all interface types:**
  - Console chat (interactive CLI)
  - Web chat (HTTP API + optional UI)
  - Webhook (WebSub-based event handling)
- **Multi-interface agents** - run multiple interfaces simultaneously
- **MCP support** for tools (Model Context Protocol)
- **Validation** - dry-run mode to validate AFM definitions

## Prerequisites

- [Python](https://www.python.org/) 3.12 or later.
- [uv](https://docs.astral.sh/uv/) for dependency management.
- [Docker](https://www.docker.com/) (optional, for running via containers).

## Quick Start

```bash
# Set your API Key
export OPENAI_API_KEY="your-api-key-here"

# Run with an AFM file using uv
uv run afm path/to/agent.afm.md
```

## Configuration

Configuration via environment variables or CLI options:

- `OPENAI_API_KEY`, `ANTHROPIC_API_KEY`, etc. (Required based on provider)
- HTTP port can be set via `-p` or `--port` (default: 8000)

## Running with Docker

```bash
# Build the image
docker build -t afm-langchain-interpreter .

# Run with an AFM file mounted and API key
docker run -v $(pwd)/path/to/agent.afm.md:/app/agent.afm.md \
  -e OPENAI_API_KEY=$OPENAI_API_KEY \
  -p 8000:8000 \
  afm-langchain-interpreter afm /app/agent.afm.md
```

## Testing

```bash
uv run pytest
```

## Project Structure

```text
langchain-interpreter/
├── src/afm/
│   ├── interfaces/        # Interface implementations (console, web, webhook)
│   ├── tools/             # Tool support (MCP server)
│   ├── resources/         # Static assets (web UI)
│   ├── agent.py           # Core agent logic
│   ├── cli.py             # CLI entry point
│   ├── parser.py          # AFM file parsing
│   ├── models.py          # Model configuration
│   ├── providers.py       # LLM provider handling
│   └── templates.py       # Prompt templates
├── tests/                 # Unit and integration tests
├── Dockerfile             # Container build
├── pyproject.toml         # Python project configuration
└── uv.lock                # Dependency lock file
```

## License

Apache-2.0