semvec/pypi-packages huggingface dataset:
agent-tui 0.1.0
Terminal user interface for AI agents built on agent-core.
Requires Python: >=3.11

<h1 align="center">
    agent-tui
</h1>
<p align="center">
    <p align="center">Terminal user interface for AI agents built on <a href="https://github.com/DavidKoleczek/agent-core">agent-core</a>.</p>
</p>
<p align="center">
    <a href="https://github.com/astral-sh/uv"><img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json" alt="uv"></a>
    <a href="https://github.com/astral-sh/ty"><img src="https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ty/main/assets/badge/v0.json" alt="ty"></a>
    <a href="https://opensource.org/licenses/MIT"><img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License: MIT"></a>
</p>

A [Textual](https://textual.textualize.io/)-based terminal interface for interacting with AI agents. Built on [agent-core](https://github.com/DavidKoleczek/agent-core) and [InteropRouter](https://github.com/DavidKoleczek/interop-router) for unified model provider support.

> [!NOTE]
> This library is in early development and subject to change.


## Usage

Ensure `OPENAI_API_KEY` is set in your environment.

Run the TUI:

```bash
uv run agent-tui
```

Or run directly with Textual:

```bash
uv run textual run src.agent_tui.app:AgentApp
```


## Development

### Prerequisites

- [uv](https://docs.astral.sh/uv/getting-started/installation/)
- [prek](https://github.com/j178/prek/blob/master/README.md#installation)

### Setup

Create uv virtual environment and install dependencies:

```bash
uv sync --frozen --all-groups
```

Set up git hooks:

```bash
prek install
```

To update dependencies (updates the lock file):

```bash
uv sync --all-groups
```

Run formatting, linting, and type checking:

```bash
uv run ruff format && uv run ruff check --fix && uv run ty check
```
wetwire-core 1.2.0
Shared agent infrastructure for wetwire domain packages
Requires Python: >=3.11
Keywords: agent, ai, infrastructure, testing

# wetwire-core-python

[![CI](https://github.com/lex00/wetwire-core-python/actions/workflows/ci.yml/badge.svg)](https://github.com/lex00/wetwire-core-python/actions/workflows/ci.yml)
[![codecov](https://codecov.io/gh/lex00/wetwire-core-python/branch/main/graph/badge.svg)](https://codecov.io/gh/lex00/wetwire-core-python)
[![PyPI Version](https://img.shields.io/pypi/v/wetwire-core.svg)](https://pypi.org/project/wetwire-core/)
[![Python Version](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org/downloads/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)

Shared agent infrastructure for wetwire domain packages.

## Overview

wetwire-core provides the AI agent framework used by wetwire domain packages (like wetwire-aws). It includes:

- **agent/personas** - Developer persona definitions (Beginner, Intermediate, Expert, Terse, Verbose)
- **agent/scoring** - 5-dimension evaluation rubric (0-15 scale)
- **agent/results** - Session tracking and RESULTS.md generation
- **agent/orchestrator** - Developer/Runner agent coordination
- **agents** - Anthropic SDK integration and RunnerAgent

## Installation

```bash
pip install wetwire-core
```

## Usage

wetwire-core is typically used as a dependency of domain packages like wetwire-aws.

```python
from wetwire_core.agent.personas import load_persona
from wetwire_core.agent.scoring import calculate_score
from wetwire_core.agent.orchestrator import Orchestrator
```

## License

MIT