semvec/pypi-packages huggingface dataset:
python-youtube-downloader 1.0.0
Download YouTube videos as MP3 or MP4 from the command line
License: MIT
Requires Python: >=3.8

# Python Youtube Downloader

A simple command-line application to download YouTube videos as MP3 (audio) or MP4 (video). Optionally saves to an external drive.

## Prerequisites

- **Python 3.x**
- **yt-dlp**: Installed via `pip install yt-dlp`
- **ffmpeg**: Required for audio conversion.
  - **macOS**: `brew install ffmpeg`
  - **Windows**: Download from [ffmpeg.org](https://ffmpeg.org/download.html) and add to PATH.
  - **Linux**: `sudo apt install ffmpeg`

## Installation

### Option A: pip (Python package)

Install with pip so the `youtube-downloader` command is available. This also installs **yt-dlp** for you.

```bash
pip install python-youtube-downloader
# or into your user directory (available in any terminal):
pip install --user python-youtube-downloader
```

Then run:

```bash
youtube-downloader
```

**Where pip installs:** With `pip install`, the package goes into your active Python environment (e.g. your conda env or `site-packages`). With `pip install --user`, it installs into your user directory so the command is available in any terminal. You still need **ffmpeg** installed on your system for MP3/MP4 conversion.

### Option B: npm (global CLI)

Install globally and run from anywhere (uses Node to run the Python script):

```bash
npm install -g python-youtube-downloader
```

Then use:

```bash
youtube-downloader
# or
python-youtube-downloader
```

**If you install with both pip and npm:** Both register a `youtube-downloader` command. Whichever directory comes first in your PATH runs (no crash). Pick one install method if you want to avoid ambiguity.

### Option C: From source

1. Clone or download this repository.
2. Install the required Python library:
   ```bash
   pip install yt-dlp
   ```

**Prerequisites:** Python 3, [yt-dlp](https://github.com/yt-dlp/yt-dlp) (installed automatically with pip option), and [ffmpeg](https://ffmpeg.org/) (for MP3/MP4 conversion).

## Usage

Run the script and enter the YouTube URL when prompted. Choose MP3 (audio only) or MP4 (video). If an external drive named **SWIM PRO** is connected, files are saved there; otherwise they go to the current folder.

```bash
python downloader.py
# or, if installed via npm:
youtube-downloader
```

Or with link and format:

```bash
python downloader.py "https://youtu.be/VIDEO_ID" mp3
python downloader.py "https://youtu.be/VIDEO_ID" mp4
youtube-downloader "https://youtu.be/VIDEO_ID" mp4
```
entari-plugin-hyw 4.0.0rc17
Use large language models to interpret chat messages
License: MIT
Requires Python: <3.13,>=3.10
Keywords: entari, llm, ai, bot, chat

# Entari Plugin HYW

[![PyPI version](https://badge.fury.io/py/entari-plugin-hyw.svg)](https://badge.fury.io/py/entari-plugin-hyw)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Python Versions](https://img.shields.io/pypi/pyversions/entari-plugin-hyw.svg)](https://pypi.org/project/entari-plugin-hyw/)

**English** | [简体中文](docs/README_CN.md)

**Entari Plugin HYW** is an advanced agentic chat plugin for the [Entari](https://github.com/entari-org/entari) framework. It leverages Large Language Models (LLMs) to provide intelligent, context-aware, and multi-modal responses within instant messaging environments (OneBot 11, Satori).

The plugin implements a three-stage pipeline (**Vision**, **Instruct**, **Agent**) to autonomously decide when to search the web, crawl pages, or analyze images to answer user queries effectively.

<p align="center">
  <img src="docs/demo_mockup.svg" width="800" />
</p>

## Features

- 📖 **Agentic Workflow**  
  Autonomous decision-making process to search, browse, and reason.

- 🎑 **Multi-Modal Support**  
  Native support for image analysis using Vision Language Models (VLMs).

- 🔍 **Web Search & Crawling**  
  Integrated **DuckDuckGo** and **Crawl4AI** for real-time information retrieval.

- 🎨 **Rich Rendering**  
  Responses are rendered as images containing Markdown, syntax-highlighted code, LaTeX math, and citation badges.

- 🔌 **Protocol Support**  
  Deep integration with OneBot 11 and Satori protocols, handling reply context and JSON cards perfectly.

## Installation

```bash
pip install entari-plugin-hyw
```

## Configuration

Configure the plugin in your `entari.yml`.

### Minimal Configuration

```yaml
plugins:
  entari_plugin_hyw:
    model_name: google/gemini-2.0-flash-exp
    api_key: "your-or-api-key-here"
    # Rendering Configuration
    render_timeout_ms: 6000 # Browser wait timeout
    render_image_timeout_ms: 3000 # Image load wait timeout
```

## Usage

### Commands

- **Text Query**
  ```text
  /q What's the latest news on Rust 1.83?
  ```

- **Image Analysis**
  *(Send an image with command, or reply to an image)*
  ```text
  /q [Image] Explain this error.
  ```
- **Quote Query**
  ```text
  [quote: User Message] /q
  ```

- **Follow-up**
  *Reply to the bot's message to continue the conversation.*

## Documentation for AI/LLMs

- [Instruction Guide (English)](docs/README_LLM_EN.md)
- [指导手册 (简体中文)](docs/README_LLM_CN.md)

---

## License

This project is licensed under the MIT License.
armoriq-sdk 0.2.6
ArmorIQ SDK - Build secure AI agents with cryptographic intent verification.
License: MIT
Requires Python: >=3.9
Keywords: armoriq, sdk, ai, agents, security, verification

# ArmorIQ SDK

**Build secure AI agents with cryptographic intent verification.**

The ArmorIQ SDK enables developers to build AI agents with built-in security and auditability. Just one API key - no cloud complexity.

---

## Why ArmorIQ?

- **Simple** - Just one API key, no cloud credentials
- **Secure** - Cryptographic verification for every action
- **Auditable** - Complete execution trail
- **Fast** - Get started in 5 minutes

---

## Installation

```bash
pip install armoriq-sdk
```

---

## Quick Start

### 1. Get Your API Key

Visit [dashboard.armoriq.io](https://dashboard.armoriq.io) to generate your API key.

### 2. Initialize the Client

```python
from armoriq_sdk import ArmorIQClient

client = ArmorIQClient(
    api_key="ak_your_key_here",
    user_id="your-user-id",
    agent_id="your-agent-id"
)
```

### 3. Capture Your Plan

```python
plan = {
    "goal": "Get weather forecast",
    "steps": [
        {
            "action": "get_weather",
            "tool": "weather_api",
            "inputs": {"city": "Boston"}
        }
    ]
}

plan_capture = client.capture_plan(
    llm="gpt-4",
    prompt="What's the weather in Boston?",
    plan=plan
)
```

### 4. Get Intent Token

```python
token = client.get_intent_token(plan_capture)
```

### 5. Invoke Actions

```python
result = client.invoke(
    mcp_name="weather-mcp",
    action="get_weather",
    intent_token=token,
    inputs={"city": "Boston"}
)

print(result)
```

---

## Documentation

For complete documentation, visit [docs.armoriq.ai](https://docs.armoriq.ai)

---

## Links

- [armoriq.ai](https://armoriq.ai)
- [docs.armoriq.ai](https://docs.armoriq.ai)
- [dashboard.armoriq.io](https://dashboard.armoriq.io)

---

## License

MIT License - see [LICENSE](LICENSE) file for details.
gar-test 0.1.0
LLM-powered Git automated code review CLI with multi-mode analysis
License: MIT
Requires Python: <3.12,>=3.11
Keywords: ai, cli, code-review, git, llm

# gar

gac test project

## Installation

### GitHub Releases에서 설치

릴리스된 버전을 설치하려면:

```bash
uv tool install https://github.com/YOUR_USERNAME/gac-test/releases/download/v0.1.0/gar-0.1.0-py3-none-any.whl
```

### GitHub 저장소에서 직접 설치

최신 버전을 설치하려면:

```bash
uv tool install git+https://github.com/YOUR_USERNAME/gac-test.git
```

### 로컬에서 설치

개발 중인 버전을 설치하려면:

```bash
uv tool install .
```

## Usage

설치 후 `gar` 명령어를 사용할 수 있습니다:

```bash
gar
```

## Development

```bash
# 의존성 설치
uv sync --dev

# 빌드
uv build

# 테스트
uv run pytest
```