semvec/pypi-packages huggingface dataset:
pilottai-tools 0.1.0
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Requires Python: <4.0,>=3.10

# PilottAI-Tools

A comprehensive collection of connectors and data processors for the PilottAI framework.

## Overview

PilottAI-Tools extends the core PilottAI framework by providing pre-built connectors for databases, third-party services, and various data sources. This package enables AI agents to seamlessly interact with real-world systems and process diverse data formats.

## Features (Coming Soon)

### Database Connectors
- PostgreSQL, MySQL, MongoDB
- Redis, Elasticsearch, InfluxDB
- SQLite for development and testing

### Third-Party Service Connectors
- **ServiceNow** - ITSM and incident management
- **Slack** - Team communication and bot integration
- **Jira** - Issue tracking and project management
- **Salesforce** - CRM and sales automation
- **Microsoft Teams** - Enterprise communication
- **GitHub** - Code repository management
- **Google Workspace** - Productivity suite integration

### Data Source Processors
- **Document Processing** - PDF, Word, Excel, PowerPoint
- **Audio & Voice** - Speech-to-text, audio analysis, voice commands
- **Web Content** - HTML parsing, web scraping, RSS feeds
- **Structured Data** - JSON, XML, CSV processing

## Installation

```bash
pip install pilottai_tools
```

## Status

🚧 **This project is currently under active development**

We're building the foundational connectors and will be releasing them incrementally. Check back soon for updates!

## Roadmap

- [ ] Core database connectors
- [ ] ServiceNow integration
- [ ] Slack connector
- [ ] Document processing tools
- [ ] Audio processing capabilities
- [ ] Web scraping utilities

## Contributing

We welcome contributions! This project is just getting started, so there are plenty of opportunities to help build these connectors from the ground up.

## License

MIT License

## Related Projects

- [PilottAI](https://github.com/pilottai/pilottai) - Main framework
- [PilottAI Examples](https://github.com/pilottai/pilottai-examples) - Usage examples

---

**Built by the PilottAI Team**
zampie-utils 0.5.5
A collection of utility functions
Requires Python: >=3.6
Keywords: utils, tools, utilities

# Zampie Utils

一个实用的Python工具包，提供了一系列常用的工具函数。

## 功能特性

- 文件操作工具
- 计时器上下文管理器
- 表情符号和表情识别
- 概率触发器
- 会话保存功能

## 安装

```bash
pip install zampie_utils
```

## 使用示例

```python
from zampie_utils import ContextTimer, read_file

# 使用计时器
with ContextTimer("my_task", "s"):
    # 你的代码
    pass

# 读取文件
content = read_file("path/to/your/file.txt")
```

## PyPi

https://pypi.org/project/zampie-utils/
mypromptgen 0.3.1
Package for generating AI prompts and answers
Requires Python: >=3.8

# Prompt and Answer Generation Tool

This tool generates structured conversations (prompts and answers) based on specified topics using language models.

## Quick Start

### Installation
Install the package using pip:
```bash
pip install mypromptgen
```

### Setup
Configure your environment:
1. Create `.env` file from example:
```bash
curl -O https://raw.githubusercontent.com/<username>/<repo>/main/.env.example
mv .env.example .env
```
2. Add your API keys to `.env`:
```ini
OPENAI_API_KEY=sk-xxx       # For OpenAI
ANTHROPIC_API_KEY=sk-xxx    # For Claude
```
3. Configure models and topics in `.env`:
```ini
PROMPTGEN_MODEL=gpt-3.5-turbo
ANSWERGEN_MODEL=gpt-4
TOPICS=Python,JavaScript
AMOUNTS=10
```

### Generate Conversations
Run the main tool:
```bash
mypromptgen
```

## Extended Features

### Advanced Usage
1. **Distillation Training**:
```bash
export DATA_FILE=conversations.json
python distill.py
```

2. **QLoRA Training**:
```bash
export MODEL_NAME=unsloth/Qwen2.5-Coder-1.5B-Instruct
python qlora.py
```

3. **Migration**:
```bash
python migrate.py input.json
```

### Environment Configuration
| Key | Description |
|-----|-------------|
| `PROMPTGEN_MODEL` | Model for prompt generation |
| `ANSWERGEN_MODEL` | Comma-separated answer gen models |
| `TOPICS` | Comma-separated topic list |
| `AMOUNTS` | Number of prompts per topic |
| `MODEL_SPLIT` | Percentage weights for answer models |
| `LOGITS` | Capture log probabilities (y/n) |

Full variable list and detailed documentation at [GitHub Repo](https://github.com/<username>/<repo>)

### PyPI Publishing
1. Create distribution:
```bash
python -m build
```
2. Upload to PyPI:
```bash
twine upload dist/*
```