semvec/pypi-packages huggingface dataset:
plasma-core-functions 0.1.0
Consolidated core functions for PLASMA projects
Requires Python: >=3.6

# PLASMA Core Functions

This repository consolidates duplicate Python code from various PLASMA projects into a single, testable, and publishable library.

## Purpose

The goal is to provide a single source of truth for commonly used functions across PLASMA, improving maintainability and consistency.

## Installation

(Instructions will be added here once the library is published to a private index)

## Development

(Instructions for setting up a development environment and running tests will be added here)

## Contributing

(Guidelines for contributing to the library will be added here)
chatgpt-mirai-qq-bot-game-werewolf 0.3.5
GameWerewolfPlugin for lss233/chatgpt-mirai-qq-bot
Requires Python: >=3.8

# game_werewolf for ChatGPT-Mirai-QQ-Bot

本项目是 [ChatGPT-Mirai-QQ-Bot](https://github.com/lss233/chatgpt-mirai-qq-bot) 的一个插件，用于狼人杀游戏，使用开始触发游戏，数字进行游戏操作和投票。例如工作流的配置是”#狼人杀“触发，则用户输入"#狼人杀开始"，工作流中替换"#狼人杀"后,"开始"触发了游戏的初始化，后续用户继续输入"#狼人杀1"或者"#狼人杀{你的发言}"进行交互。

## 安装

```bash
pip install chatgpt-mirai-qq-bot-game-werewolf
```

## 使用

在 chatgpt-mirai-qq-bot的web_ui中配置
使用示例请参考 [game_werewolf/example/werewolf.yml](game_werewolf/example/werewolf.yaml)
安装此插件会自动生成一个狼人杀游戏工作流，仅供参考

## 开源协议

本项目基于 [ChatGPT-Mirai-QQ-Bot](https://github.com/lss233/chatgpt-mirai-qq-bot) 开发，遵循其 [开源协议](https://github.com/lss233/chatgpt-mirai-qq-bot/blob/master/LICENSE)

## 感谢

感谢 [ChatGPT-Mirai-QQ-Bot](https://github.com/lss233/chatgpt-mirai-qq-bot) 的作者 [lss233](https://github.com/lss233) 提供框架支持
chatgpt-mirai-qq-bot-scheduler 0.3.9
定时任务 for lss233/chatgpt-mirai-qq-bot，提供聚合block实现定时任务的增删查(同时也可以配置其他安装的block实现自动调用)
Requires Python: >=3.8

# scheduler for ChatGPT-Mirai-QQ-Bot

本项目是 [ChatGPT-Mirai-QQ-Bot](https://github.com/lss233/chatgpt-mirai-qq-bot) 的一个插件，用于在工作流中配置定时任务，同时提供auto_tool的聚合block，实现对定时任务增删查的自动调用。

## 安装

```bash
pip install chatgpt-mirai-qq-bot-scheduler
```

## 使用

在 chatgpt-mirai-qq-bot的web_ui中配置  
使用示例请参考 [scheduler/example/normalWithTool.yml](scheduler/example/normalWithTool.yaml)    

## 开源协议

本项目基于 [ChatGPT-Mirai-QQ-Bot](https://github.com/lss233/chatgpt-mirai-qq-bot) 开发，遵循其 [开源协议](https://github.com/lss233/chatgpt-mirai-qq-bot/blob/master/LICENSE)

## 感谢

感谢 [ChatGPT-Mirai-QQ-Bot](https://github.com/lss233/chatgpt-mirai-qq-bot) 的作者 [lss233](https://github.com/lss233) 提供框架支持
ffmpeg-ai 0.1.8
AI-powered FFmpeg command generator
Requires Python: >=3.8

# FFmpeg AI Assistant

A command-line utility that acts as an intelligent FFmpeg assistant for developers. This tool runs entirely offline and uses a local LLM via Ollama to provide context-aware FFmpeg commands, code snippets, and explanations.

---

## Features

- Generate FFmpeg commands from natural language queries
- Get Python, Bash, or Node.js code wrappers for FFmpeg commands
- Detailed explanations of command parameters
- 100% offline operation with local LLM and vector database
- Smart caching for repeated queries
- Easy customization and model switching

---

## Installation

### Recommended: PyPI Installation

Install the tool from PyPI using:

```bash
pip install ffmpeg-ai
```

---

## Documentation Setup After Installation

After installing, you must initialize the documentation database:

```bash
ffmpeg-ai setup
```

### Command-Line Interface

Once installed, you can interact with the tool via the command line. Use the following command to get help:

```bash
ffmpeg-ai --help
```

This will display the available options and commands:

```
Usage: ffmpeg-ai --help

AI-powered FFmpeg command generator

Options:
  --help  Show this message and exit.

Commands:
  query        Ask a natural language question about FFmpeg.
  setup        Set up the FFmpeg documentation database.
  clear-cache  Clear the query cache.
```

---

## Documentation Setup

Running `ffmpeg-ai setup` will:

- Download and parse FFmpeg's official documentation
- Create vector embeddings for faster and more accurate querying
- Store the embeddings locally for offline use

---

## Real Usage Example

Here's an example of using the tool in your project:

```bash
# In your project directory, run:
ffmpeg-ai query "convert .mov to .mp4 using H.264 codec" --code
```

**Result:**

**FFmpeg Command:**

```bash
ffmpeg -i input.mov -vcodec libx264 output.mp4
```

**Generated Python Script:**

```python
import os
import subprocess

def convert_mov_to_mp4(input_file, output_file):
    command = f'ffmpeg -i {input_file} -vcodec libx264 {output_file}'
    subprocess.run(command, shell=True, check=True)

# Usage example:
input_file = 'input.mov'
output_file = 'output.mp4'
convert_mov_to_mp4(input_file, output_file)
```

---

## How It Works

1. **Document Retrieval**: Fetches the most relevant chunks from embedded FFmpeg documentation using sentence-transformers and ChromaDB.
2. **Query Augmentation**: Combines your query with retrieved context before sending it to the local LLM.
3. **LLM Generation**: The local model (e.g., Mistral) generates the command, code, and explanations.
4. **Result Formatting**: Outputs are formatted cleanly and cached for faster future retrieval.

---

## Requirements

- Python 3.10+
- FFmpeg installed system-wide
- Ollama installed and running
- Local machine with ~8GB RAM or more recommended

---

## Limitations

- Responses depend on the quality of the local LLM model.
- Currently limited to embedded and user-added FFmpeg documentation.
- Hardware-intensive for optimal performance.

---

## License

MIT License
pltx 0.2.9
Tools of matplotlib
Requires Python: >=3.6
Keywords: matplotlib

Usage Sample
''''''''''''

.. code:: python

        import pltx 

        y_true = [1, 1, 1, 0, 0, 0]
        y_pred = [1, 0, 1, 0, 0, 0]
        y_prob = [0.9, 0.1, 0.8, 0.2, 0.7, 0.3]

        pltx.plot_roc(y_true, y_prob)
        pltx.plot_confusion_matrix2(y_true, y_pred)
gnor 0.0.2
A command line tool to generate a .gitignore file
Requires Python: >=3.10

# ignr.py

ignr.py (or simply ignr) is a Python-based command line utility to fetch .gitignore templates from [gitignore.io](https://gitignore.io). gitignore.io has official [command line tools](https://github.com/joeblau/gitignore.io#install-command-line), but they rely on bash or zsh, and *may* not be compatible with all systems out there.

The .gitignore file in this repository was generated using ignr, if you want to look at a sample!

There's also a Go-based alternative, [gogi](https://github.com/Gnouc/gogi), but not everyone uses Go.

ignr was created for Python users who prefer to install via [PyPI](https://pypi.python.org/pypi) and/or [pip](https://pip.pypa.io).

>Note: Version 2.0 completely drops Python 2 support in favor of Python 3, released late-2019.

## Usage

Install using
    
    pip install ignr

### List

    ignr -l

Lists all available .gitignore templates on gitignore.io.

### Search

    ignr -s mac

Searches for supplied query in list of available templates from gitignore.io, similar to using `grep`.

### Preview

    ignr -p scala macOS

Prints a preview of the template without generating a .gitignore file. List multiple space-separated languages, frameworks, operating systems to get combined output.

### Create

    ignr -n node sass windows

Generates a new .gitignore file in the current directory. List multiple space-separated languages, frameworks, operating systems to get combined output.

If a .gitignore already exists in the directory, ignr will give you an option to back it up.

## Troubleshooting

Since gitignore.io uses HTTPS, running this utility in certain macOS environments may result in an SSL "handshake failure" error, which is discussed in detail in this [requests issue](https://github.com/kennethreitz/requests/issues/2022).

Unfortunately, there is no trivial fix.

In my experience, switching from the included Python in El Capitan to a standalone Python installed via brew solved the issue. All my existing packages seemed to remain intact.

## Contribute

Feel free to make improvements. PRs are greatly appreciated.

I can be reached [@Antrikshy](https://twitter.com/Antrikshy) or [via reddit](https://www.reddit.com/u/Antrikshy).
polyglot-tts 0.1.0
A Python module for text translation and audio generation using OpenAI's API and ElevenLabs
Requires Python: >=3.7
Keywords: translation, openai, text-to-speech, elevenlabs, language

# Polyglot TTS

A Python module for translating text using OpenAI's API with optional audio generation using ElevenLabs.

## Features

- Text translation to any language using OpenAI's GPT-3.5 model
- Optional audio generation of translated text using ElevenLabs API
- Simple, easy-to-use interface
- Supports environment variable configuration

## Installation

```bash
pip install polyglot-tts
```

## Configuration

Create a `.env` file in your project root with your API keys:

```plaintext
OPENAI_API_KEY=your-openai-api-key-here
ELEVENLABS_API_KEY=your-elevenlabs-api-key-here  # Optional, for audio generation
```

Alternatively, set them as environment variables:

```bash
export OPENAI_API_KEY='your-openai-api-key-here'
export ELEVENLABS_API_KEY='your-elevenlabs-api-key-here'  # Optional
```

## Usage

### Basic Translation

```python
from polyglot-tts import translate

# Basic translation
translated_text, _ = translate("Hello, how are you?", "Spanish", generate_audio=False)
print(translated_text)  # "¡Hola, cómo estás?"

# Translation with audio generation
translated_text, audio_path = translate("Hello, how are you?", "French")
print(translated_text)  # "Bonjour, comment allez-vous?"
print(audio_path)  # Path to the generated audio file
```

### Function Parameters

- `message` (str): The text to translate
- `output_lang` (str): The target language for translation
- `generate_audio` (bool, optional): Whether to generate audio for the translation. Defaults to True.
- `voice_id` (str, optional): The ElevenLabs voice ID to use for audio generation. Defaults to "EXAVITQu4vr4xnSDxMaL" (Bella voice).
- `save_audio` (bool, optional): Whether to save the generated audio file. Defaults to False. If True, the audio file will be saved in the "output" directory in the current working directory.

### Return Value

Returns a tuple containing:
1. The translated text (str)
2. The path to the generated audio file (str or None if audio generation is disabled or fails)

## Requirements

- Python 3.7+
- OpenAI API key (required)
- ElevenLabs API key (optional, for audio generation)

## Error Handling

The module will raise:
- `ValueError` if required API keys are not set
- `Exception` if translation or audio generation fails

## Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

## License

MIT License
apilens 0.1.0
A Python wrapper for various AI language model APIs
Requires Python: >=3.7

# APILens

A Python wrapper for various AI language model APIs that provides consistent interface, logging, and cost tracking across different providers.

## Features

- Unified interface for multiple AI providers
- Automatic retry mechanism with exponential backoff
- Usage tracking and cost calculation
- SQLite-based logging system
- Support for both synchronous and asynchronous operations
- Streaming support

## Installation

```bash
pip install apilens
```

## Usage

```python
from apilens import BaseAIWrapper

# Initialize your provider wrapper
wrapper = YourProviderWrapper(
    provider_name="your_provider",
    model="your_model",
    user_id="optional_user_id",
    tenant_id="optional_tenant_id"
)

# Make a chat completion request
response = wrapper.chat_completion([
    {"role": "user", "content": "Hello, how are you?"}
])
```

## License

MIT License
ws-sim868 1.0.0b8
Python package to control the Waveshare GSM/GPRS/GNSS Pi HAT
Requires Python: >=3.9

# ws_sim868
## Interface module for the Waveshare GSM/GPRS/GNSS Pi Hat

![PyPI - License](https://img.shields.io/pypi/l/ws-sim868)
![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/matthewnaruzny/ws_sim868/python-publish.yml)
![PyPI - Version](https://img.shields.io/pypi/v/ws_sim868)

## Features
- HTTP GET and POST requests
- Automatically start Modem if turned off
- Receive GNSS Location

## Instalation
```
pip install ws-sim868
```

## Overview

## Examples:
### HTTP Get Request

```python
from ws_sim868.modemUnit import ModemUnit
import time

if __name__ == "__main__":
    m = ModemUnit()
    m.apn_config('super', '', '')
    m.network_start()
    res = m.http_get("http://example.com")
    print(res)

    while True:
        time.sleep(0.5)
```

### Get Location
```python
from ws_sim868.modemUnit import ModemUnit
import time

if __name__ == "__main__":
    m = ModemUnit()
    m.gnss_start()

    while True:
        time.sleep(3)
        print(m.get_gnss_loc())
```