semvec/pypi-packages huggingface dataset:
torrent-downloader-react 1.2.0
A high-performance, React-based BitTorrent client with an intuitive interface for seamless file downloading
Requires Python: >=3.8
Keywords: torrent, downloader, p2p, bittorrent, libtorrent

# Torrent Downloader Web App

A modern, full-featured torrent downloader with a clean React interface and FastAPI backend.

![Torrent Downloader Web UI](https://github.com/stevenyyan/torrent-downloader/raw/main/torrent-downloader-react/screenshots/webapp_screenshot.png)

## Features

- **Sleek, Responsive UI**: Modern React interface that works on desktop and mobile
- **Real-time Updates**: Live tracking of download progress, speed, and ETA
- **Easy to Use**: Simple interface for adding and managing downloads
- **Flexible Backend**: Powerful FastAPI server handling torrent operations
- **Lightweight**: Minimal resource usage while maintaining full functionality
- **Cross-platform**: Works on Windows, macOS, and Linux

## System Requirements

- Python 3.8 or higher
- Platform-specific libtorrent dependencies:
  - **Windows**: Microsoft Visual C++ Redistributable
  - **macOS**: `brew install libtorrent-rasterbar`
  - **Ubuntu/Debian**: `sudo apt-get install python3-libtorrent`
  - **Fedora**: `sudo dnf install rb_libtorrent-python3`

## Installation

### From PyPI (Recommended)

```bash
pip install torrent-downloader-react
```

### From Source

```bash
git clone https://github.com/stevenyyan/torrent-downloader.git
cd torrent-downloader/torrent-downloader-react/backend
pip install -e .
```

## Usage

1. Start the application:
   ```bash
   torrent-downloader-react
   ```
2. Open your browser at http://127.0.0.1:8000
3. Paste a magnet link in the input field and click "Add Torrent"
4. Monitor download progress in the list view
5. Access completed downloads in your Downloads/TorrentDownloader folder
6. Click "Open Download Folder" to view your downloaded files

## Development Setup

### Frontend (React + Vite)

```bash
# Install dependencies
cd torrent-downloader-react
npm install

# Start development server (runs on http://localhost:5173)
npm run dev
```

### Backend (FastAPI)

```bash
# Install dependencies
cd torrent-downloader-react/backend
pip install -r requirements.txt

# Start development server
python -m torrent_downloader.server
```

## API Documentation

The backend provides a RESTful API:

- `POST /api/torrent/add` - Add new torrent
- `GET /api/torrent/list` - List all active torrents
- `DELETE /api/torrent/{torrent_id}` - Remove torrent
- `GET /api/downloads/path` - Get downloads directory path
- `POST /api/downloads/open` - Open downloads folder

## Alternative Installation with Conda

```bash
# Create and activate conda environment
conda create -n torrent-env python=3.11
conda activate torrent-env

# Install libtorrent dependency
conda install -c conda-forge libtorrent

# Install the package
pip install torrent-downloader-react
```

## License

MIT License - See LICENSE file for details.

## Legal Notice

This software is intended for downloading legal torrents only. Users are responsible for compliance with applicable laws.
water-ai 0.1.0
A multi-agent orchestration framework that works with any agent framework
Requires Python: >=3.8
Keywords: water-ai, multi-agent, orchestration, llm, large-language-model, framework, agents, ai-agents, workflow, pipeline, langchain, crewai, agno, autogen, distributed, async, coordination, agent-framework, multi-agent-systems

# Water
**A multi-agent orchestration framework that works with any agent framework.**

[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)

## Overview
Water is a production ready orchestration framework that enables developers to build complex multi-agent systems without being locked into specific agent framework. Whether you are using LangChain, CrewAI, Agno, or custom agents, Water provides the orchestration layer to coordinate and scale your multi-agent workflows.

### Key Features

- **Framework Agnostic** - Integrate any agent framework or custom implementation
- **Flexible Workflows** - Orchestrate complex multi-agent interactions with simple Python
- **Playground** - Run lightweight FastAPI server with all the flows you define

## Quick Start
### Installation

```bash
pip install water-ai
```

### Basic Usage

```python
import asyncio
from water import Flow, create_task
from pydantic import BaseModel

class NumberInput(BaseModel):
    value: int

class NumberOutput(BaseModel):
    result: int

def add_five(params, context):
    return {"result": params["input_data"]["value"] + 5}

math_task = create_task(
    id="math_task",
    description="Math task",
    input_schema=NumberInput,
    output_schema=NumberOutput,
    execute=add_five
)

flow = Flow(id="my_flow", description="My flow").then(math_task).register()

async def main():
    result = await flow.run({"value": 10})
    print(result)

if __name__ == "__main__":
    asyncio.run(main())
```

## Contributing

We welcome contributions from the community!

- Bug reports and feature requests
- Code contributions
- Documentation improvements
- Testing and quality assurance

## Roadmap

- Storage layer to store flow sessions and task runs
- Human in the loop support
- Retry mechanism for individual tasks

## License

Water is licensed under the Apache License 2.0. See the [LICENSE](LICENSE) file for details.