semvec/pypi-packages huggingface dataset:
spinning-cat-lang 0.1.1
An interpreter for the Oiia language
Requires Python: >=3.6

# Oiia Interpreter

An interpreter for the Oiia language, a fun and esoteric programming language.

## Installation

You can install the package via pip:

```bash
pip install spinning-cat-lang==0.1.0
```

## Usage

```python
from oiia_interpreter import OiiaInterpreter

interpreter = OiiaInterpreter()
interpreter.interpret("oiia oiia oiia oiia 10")
```

## License

This project is licensed under the MIT License. See the LICENSE file for details.
llmtop 0.1.0
LLM-powered system monitoring with real-time performance insights
Requires Python: >=3.8

# llmtop

`llmtop` is an intelligent system monitoring tool that combines real-time system metrics with LLM-powered insights. It provides a dynamic terminal interface showing system performance metrics enhanced with AI-driven analysis.

> **Note**: This project is currently in beta testing. Features and interfaces may change.

![llmtop Screenshot](screenshot.png)

## Features

- Real-time system metrics monitoring (CPU, Memory, Disk, Network)
- Process monitoring with resource usage
- AI-powered system analysis using either OpenAI or Ollama
- Smart alerting system for resource thresholds
- Dynamic terminal UI with auto-updating metrics

## Installation

Install directly from PyPI:
```bash
pip install llmtop
```

## LLM Backend Options

llmtop supports two LLM backends for system analysis:

### OpenAI (GPT-4)
1. Set your OpenAI API key:
   ```bash
   export OPENAI_API_KEY='your-api-key-here'
   ```
2. Run with OpenAI:
   ```bash
   llmtop --use-openai
   ```

### Ollama (Default)
1. Install Ollama from [ollama.ai](https://ollama.ai)
2. Start the Ollama service
3. Run llmtop:
   ```bash
   llmtop
   ```

## Command Line Options

```bash
llmtop [OPTIONS]

Options:
  --update-frequency INTEGER  Update frequency in seconds (default: 5)
  --use-openai               Use OpenAI instead of local model
  --history-length INTEGER   Number of historical data points to keep (default: 60)
  --help                     Show this message and exit
```

## Usage Tips

- The tool defaults to using Ollama for analysis, which is free but requires local installation
- OpenAI mode provides more detailed analysis but requires an API key and has associated costs
- Adjust update frequency based on your system's performance and monitoring needs

## Known Issues

- Experimental support for Windows systems
- Update frequency might need adjustment on slower systems
- Some process names may be truncated in the display

## Contributing

This project is in beta, and we welcome contributions! Please feel free to:

- Report bugs
- Suggest features
- Submit pull requests

## License

MIT License - see [LICENSE](LICENSE) file for details.

## Acknowledgments

Built using:
- Rich for terminal UI
- OpenAI/Ollama for LLM integration
- psutil for system metrics
oiia-interpret 0.1.1
An interpreter for the Oiia language
Requires Python: >=3.6

# Oiia Interpreter

An interpreter for the Oiia language, a fun and esoteric programming language.

## Installation

You can install the package via pip:

```bash
pip install oiia_interpreter
```

## Usage

```python
from oiia_interpreter import OiiaInterpreter

interpreter = OiiaInterpreter()
interpreter.interpret("oiia oiia oiia oiia 10")
```

## License

This project is licensed under the MIT License. See the LICENSE file for details.
openstix 0.2.4
OpenSTIX aims to make STIX easy and accessible for analysts
Requires Python: >=3.9
Keywords: CTI, IOC, STIX2, TTPs, cybersecurity, library, malware-analysis, network-security, python, threat-indicators, threat-intelligence, toolkit

# OpenSTIX

OpenSTIX is an **unofficial STIX 2.1 library and toolkit** built upon the foundations of the [STIX2 library](https://github.com/oasis-open/cti-python-stix2/), aimed at enhancing the efficiency and productivity of cybersecurity professionals. It's developed and maintained by AbuseTotal, a startup committed to delivering high-quality software solutions in the cybersecurity domain.

[![PyPI version](https://badge.fury.io/py/openstix.svg)](https://badge.fury.io/py/openstix)

## Features

- **Modular Design**: Organizes the functionalities provided by STIX2 library into modules for easy consumption and extension.
- **Workspace Class**: Extends the `Environment` class into a `Workspace` class to facilitate seamless creation, removal, and management of STIX SDOs (Structured Data Objects) based on contributing properties.
- **Built-in Datasets**: Provides ready-to-use datasets including MITRE frameworks, geolocations, custom TLP markings, and industries to expedite the analytical process.
- **Custom Objects and Extensions**: Offers custom objects and extensions to assist analysts with additional informational resources such as Whois and DNS-Records.

## Installation

```bash
pip install openstix
```

## Documentation

Documentation is available [here](https://abusetotal.github.io/openstix-python/)

## Contributing

We welcome contributions to OpenSTIX! Whether you're reporting bugs, proposing new features, or contributing code, we appreciate your help. Please make sure to read our Contributing Guidelines before making a contribution.

## License

OpenSTIX is licensed under the Apache 2.0.

## Contact

For any inquiries, issues, or support related to OpenSTIX, feel free to create an issue.

## Acknowledgements

OpenSTIX is an initiative by AbuseTotal to foster the development of cybersecurity tools and libraries. We thank the OASIS Cyber Threat Intelligence Technical Committee and all STIX community for laying down the robust foundation upon which OpenSTIX is built.
promethium 0.7.6
Library for calculating statistical distributions, written in pure Python with zero dependencies.
Requires Python: >=3.9

# Promethium 🐍

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

Library for calculating statistical distributions, written in pure Python with zero dependencies.

- To contribute to the project, check out the [contribution](https://github.com/ostromia/promethium/wiki/Contribution) wiki page.

- To view the documentation, check out the [documentation](https://github.com/ostromia/promethium/wiki/Documentation) wiki page.
oiia-interpreter 0.1.0
An interpreter for the Oiia language- Spinny Cat.
Requires Python: >=3.6

# Oiia Interpreter

An interpreter for the Oiia language, a fun and quirky programming language.

## Installation

```bash
pip install oiia_interpreter
```

## Usage

```python
from oiia_interpreter import OiiaInterpreter

interpreter = OiiaInterpreter()
interpreter.interpret("oiia oiia oiia oiia 10")
```

## License

This project is licensed under the MIT License.
sum-sum 0.1.0.1
Minimal CLI tool to summarize any text locally with help of LLM!
Requires Python: >=3.8
Keywords: Local-LLM, Ollama, text-summarization

# Sumsum

A minimal CLI tool to locally summarize any text using LLM!

Built around [Ollama](https://github.com/ollama/ollama-python) and [fine-tuned version](https://huggingface.co/AKT47/Llama_3.2_3B_fine_tune_summarization) of [Llama3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct)

## Installation:

```terminal
pip install sum-sum
```

## Setup:

- Run the `init` command to check dependency, download model and generate modelfile:
  ```terminal
  sumsum init
  ```

## Usage

- Use the command `run` with your text file path:
  ```terminal
  sumsum run path\to\file.txt
  ```
- you can also use the flag `--verbose` to get additional information:
  (time taken to load the model, time taken for generating new tokens,number of generated tokens etc)
  ```terminal
  sumsum run path\to\file.txt --verbose
  ```