semvec/pypi-packages huggingface dataset:
python-xiso-repacker 0.1.1
Basic file replacer for xisos
Requires Python: >=3.9
Keywords: xbox, xemu, xiso

# python-xiso-repacker

[![PyPI - Version](https://img.shields.io/pypi/v/python-xiso-repacker.svg)](https://pypi.org/project/python-xiso-repacker)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/python-xiso-repacker.svg)](https://pypi.org/project/python-xiso-repacker)

-----

## Purpose

A simple tool to reconfigure xiso files used by various test programs for the
original Microsoft Xbox, suitable for use in automated testing.

## Installation

```console
pip install python-xiso-repacker
```

## Usage

```console
python -m python_xiso_repacker -h
```

## License

`python-xiso-repacker` is distributed under the terms of
the [MIT](https://spdx.org/licenses/MIT.html) license.
http-status-checker-tool 1.0.5
Basic - Fast, concurrent CLI tool to check HTTP status codes of provided URLs
Requires Python: >=3.7

# HTTP Status Checker CLI

A fast, concurrent Python-based CLI tool to check the HTTP status codes.

---

## 🚀 Features

- ✅ Supports URL input via CLI or file
- ✅ Displays status codes and errors clearly
- ✅ Concurrent requests for fast performance
- ✅ Optional output to a result file
- ✅ Easy to extend, test, and package

---

## 📦 Installation

Clone the repo:

```bash
git clone 
cd http-status-checker
```

Install dependencies:

```bash
pip install -r requirements.txt
```

---

## 🧪 Usage

### Check multiple URLs:

```bash
python main.py --urls https://google.com https://example.com
```

### Check from a file:

```bash
python main.py --file urls.txt
```

### Output to a file:

```bash
python main.py --file urls.txt --output results.txt
```

---

## 📄 Sample Output

```bash
[200] https://google.com
[404] https://example.com/missing
[ERR] https://notarealsite.fake (Name or service not known)
```

---

## 🔧 Tech Stack

- Python 3.7+
    - I am using Python 3.11
- `requests`
- `argparse`
- `concurrent.futures`

---

## ✅ Roadmap

- [ ] Color-coded CLI output
- [ ] Async implementation (`aiohttp`)
- [ ] Docker support
- [ ] PyPI package
- [ ] Configurable timeout and retries

---

## 🤝 Contributing

Pull requests and feature suggestions welcome! Open an issue to start a discussion.

---

## 📝 License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.

---
groq-terminal-ai 1.1.0
groq-terminal-ai is a command line tool that uses AI to generate terminal commands

# groq-terminal-ai



https://github.com/user-attachments/assets/a6cb57a5-a597-438c-b976-4a6fd48960af



**groq-terminal-ai** is a cross-platform CLI tool that utilizes Groq's API to intelligently generate terminal commands from natural language instructions. It supports Linux, macOS, and Windows.

## Key Features

- **AI-Powered Command Generation**: Leverages Groq's advanced language models to interpret user instructions and generate accurate terminal commands.
- **Cross-Platform Compatibility**: Seamlessly operates on Linux, macOS, and Windows operating systems.
- **Customizable Model Selection**: Offers flexibility to choose from different LLM models for tailored command generation.
- **Command History**: Maintains a history of previous instructions and commands for context-aware suggestions.
- **Efficient Caching**: Implements a command cache to quickly retrieve previously generated commands.

## Installation

Install groq-terminal-ai using pip:

```bash
pip install groq-terminal-ai
```

## Usage

Step 1. Set your Groq API key
```bash
ai --groq-api-key <your-api-key>
```

Step 2. Generate a command
```bash
ai list all png files in the current directory
```

### Optional Parameters

- Choose a specific LLM model:
  ```bash
  ai --model <model-name> (default llama-3.1-8b-instant)
  ```

- Set the history size for context-aware suggestions:
  ```bash
  ai --history-size <number> (default 3)
  ```

- Enable or disable instruction history:
  ```bash
  ai --use-history <true/false> (default true)
  ```

- For more information on available options:
  ```bash
  ai --help
  ```

## Supported Models

### Current Production Models

- **llama-3.3-70b-versatile** - Latest Llama 3.3 model with excellent reasoning capabilities
- **llama-3.1-8b-instant** - Fast and efficient model, great for quick command generation
- **gemma2-9b-it** - Google's Gemma 2 model optimized for instruction following

### Latest Advanced Models

- **meta-llama/llama-4-scout-17b-16e-instruct** - Llama 4 Scout for complex reasoning tasks
- **meta-llama/llama-4-maverick-17b-128e-instruct** - Llama 4 Maverick for multilingual tasks
- **deepseek-r1-distill-llama-70b** - Advanced reasoning model for complex problem-solving
- **deepseek-r1-distill-qwen-32b** - Efficient reasoning model with strong coding capabilities
- **qwen-2.5-32b** - Qwen 2.5 with improved coding and instruction following
- **qwen-qwq-32b** - Latest Qwen reasoning model
- **mistral-saba-24b** - Updated Mistral model

### Legacy Models (Being Deprecated)

- **llama3-70b-8192** - Will be deprecated on August 30, 2025 (use llama-3.3-70b-versatile instead)
- **llama3-8b-8192** - Will be deprecated on August 30, 2025 (use llama-3.1-8b-instant instead)