semvec/pypi-packages huggingface dataset:
yeonjae-universal-prompt-builder 1.0.5
Universal prompt builder module for creating dynamic prompts
License: MIT
Requires Python: >=3.9

# Universal Prompt Builder

동적 프롬프트 생성을 위한 범용 프롬프트 빌더 모듈입니다.

## 특징

- 🔧 **템플릿 기반**: Jinja2를 사용한 유연한 템플릿 시스템
- 📝 **동적 생성**: 컨텍스트에 따른 동적 프롬프트 생성
- 🎯 **타입 안전**: Pydantic을 통한 강력한 타입 검증
- 🔄 **재사용 가능**: 모듈화된 프롬프트 컴포넌트

## 설치

```bash
pip install yeonjae-universal-prompt-builder
```

## 사용법

```python
from yeonjae_universal_prompt_builder import PromptBuilder, PromptTemplate

# 기본 사용법
builder = PromptBuilder()
template = PromptTemplate(
    name="greeting",
    template="Hello, {{ name }}! Welcome to {{ place }}.",
    variables=["name", "place"]
)

prompt = builder.build(template, {"name": "Alice", "place": "PyPI"})
print(prompt)  # "Hello, Alice! Welcome to PyPI."
```

## 라이센스

MIT License

## 버전 히스토리

- 1.0.2: 초기 배포 버전
- 1.0.1: 개발 버전
- 1.0.0: 프로토타입
yeonjae-universal-notification-service 1.0.5
Universal notification service supporting Slack, Email, Discord, and webhooks for automated reporting
License: MIT
Requires Python: >=3.8
Keywords: notification, slack, email, discord, webhook, alerts, messaging, automation

# Universal Notification Service

Universal notification service supporting Slack, Email, Discord, and webhooks for automated reporting.

## Features

- **Multi-Channel Support**: Slack, Email, Discord, Webhooks, SMS
- **Async Operations**: Full async/await support for all notification operations  
- **Rich Formatting**: Support for emoji, markdown, and channel-specific formatting
- **Batch Processing**: Send notifications to multiple recipients efficiently
- **Retry Logic**: Intelligent retry mechanisms with exponential backoff
- **Template System**: Customizable message templates with variable substitution
- **Rate Limiting**: Built-in rate limiting for API compliance
- **Type Safety**: Complete type annotations with mypy support

## Installation

```bash
# Basic installation
pip install yeonjae-universal-notification-service

# With Slack support
pip install yeonjae-universal-notification-service[slack]

# With Email support  
pip install yeonjae-universal-notification-service[email]

# With Discord support
pip install yeonjae-universal-notification-service[discord]

# With all providers
pip install yeonjae-universal-notification-service[all]
```

## Quick Start

```python
import asyncio
from yeonjae_universal_notification_service import (
    NotificationService, NotificationInput, NotificationChannel,
    NotificationConfig, RecipientInfo
)

async def main():
    # Initialize service
    service = NotificationService()
    
    # Configure notification
    config = NotificationConfig(
        channel=NotificationChannel.SLACK,
        channel_id="#dev-reports"
    )
    
    recipient = RecipientInfo(
        developer="John Doe",
        developer_email="john@example.com",
        slack_id="U1234567890"
    )
    
    # Create notification
    notification = NotificationInput(
        summary_report="🎉 Daily development summary ready!",
        notification_config=config,
        recipient_info=recipient
    )
    
    # Send notification
    result = await service.send_notification(notification)
    print(f"Status: {result.send_status}")
    print(f"Message ID: {result.message_id}")

asyncio.run(main())
```

## Configuration

Set your API keys as environment variables:

```bash
export SLACK_BOT_TOKEN="xoxb-your-slack-bot-token"
export DISCORD_BOT_TOKEN="your-discord-bot-token"
export SMTP_PASSWORD="your-email-password"
```

## Supported Channels

- **Slack**: Rich formatting, mentions, threads, file uploads
- **Email**: HTML/Plain text, attachments, templates
- **Discord**: Embeds, mentions, webhooks
- **Webhooks**: Custom HTTP endpoints with retry logic
- **SMS**: Text messages via various providers

## License

MIT License
yeonjae-universal-http-api-client 1.0.5
Universal HTTP API client supporting GitHub, GitLab, Bitbucket and other platforms
License: MIT
Requires Python: >=3.8
Keywords: http, api, client, github, gitlab, slack, notion, universal

# Universal HTTP API Client

Universal HTTP API client with platform-specific adapters for GitHub, GitLab, Slack, and Notion.

## Features

- **Multi-Platform Support**: GitHub, GitLab, Slack, Notion APIs
- **Smart Caching**: Automatic request caching with configurable TTL
- **Rate Limiting**: Built-in rate limiting with platform-specific rules
- **Error Handling**: Comprehensive error handling with custom exceptions
- **Async Support**: Full async/await support for all operations
- **Type Safety**: Complete type annotations with mypy support

## Installation

```bash
pip install yeonjae-universal-http-api-client
```

## Quick Start

```python
from yeonjae_universal_http_api_client import HTTPAPIClient, Platform

# GitHub API
client = HTTPAPIClient(Platform.GITHUB, "your-token")
repo = client.get_repository("owner/repo")
client.close()

# Slack API
slack_client = HTTPAPIClient(Platform.SLACK, "your-slack-token")
response = slack_client.send_message("channel", "Hello World!")
slack_client.close()
```

## License

MIT License
yeonjae-universal-llm-service 1.0.5
Universal LLM service supporting OpenAI, Anthropic, and local models for code analysis and summarization
License: MIT
Requires Python: >=3.8
Keywords: llm, openai, anthropic, ai, machine-learning, nlp, text-generation, code-analysis

# Universal LLM Service

Universal LLM service supporting OpenAI, Anthropic, and local models for code analysis and summarization.

## Features

- **Multi-Provider Support**: OpenAI, Anthropic, Azure OpenAI, Google, and local models
- **Async Operations**: Full async/await support for all LLM operations
- **Smart Configuration**: Automatic provider detection and configuration
- **Response Validation**: Built-in response quality validation
- **Rate Limiting**: Intelligent rate limiting and retry mechanisms
- **Type Safety**: Complete type annotations with mypy support
- **Extensible Design**: Easy to add new LLM providers

## Installation

```bash
# Basic installation
pip install yeonjae-universal-llm-service

# With OpenAI support
pip install yeonjae-universal-llm-service[openai]

# With Anthropic support
pip install yeonjae-universal-llm-service[anthropic]

# With all providers
pip install yeonjae-universal-llm-service[all]
```

## Quick Start

```python
import asyncio
from yeonjae_universal_llm_service import LLMService, LLMInput, LLMProvider, ModelConfig

async def main():
    # Initialize service
    service = LLMService()
    
    # Create input
    input_data = LLMInput(
        prompt="Analyze this code and provide insights",
        llm_provider=LLMProvider.OPENAI,
        model_config=ModelConfig(model="gpt-4", temperature=0.3)
    )
    
    # Generate summary
    result = await service.generate_summary(input_data)
    print(f"Summary: {result.summary}")
    print(f"Confidence: {result.confidence_score}")
    print(f"Tokens used: {result.metadata.total_tokens}")

asyncio.run(main())
```

## Configuration

Set your API keys as environment variables:

```bash
export OPENAI_API_KEY="your-openai-key"
export ANTHROPIC_API_KEY="your-anthropic-key"
```

## Supported Providers

- **OpenAI**: GPT-3.5, GPT-4, and newer models
- **Anthropic**: Claude 3 family (Haiku, Sonnet, Opus)
- **Azure OpenAI**: Enterprise OpenAI deployment
- **Google**: Gemini and PaLM models
- **Local**: Custom local model integration

## License

MIT License
PayloadComputerDroneProjekt 1.0.0
Add a short description here!
License: MIT

===========================
PayloadComputerDroneProjekt
===========================


    https://konstantindege.github.io/PayloadComputerDroneProjekt/


=====
Setup
=====

1. install following

   https://docs.px4.io/main/en/dev_setup/dev_env_windows_wsl.html


2. run simulation

    .. code-block:: bash 
        
        export PX4_HOME_LAT=48.76816699
        export PX4_HOME_LON=11.33711226
        export PX4_HOME_ALT=375


        cd && cd PX4-Autopilot/ && HEADLESS=1 make px4_sitl gz_x500_mono_cam_down
    
        ip addr | grep eth0

3. clone this repo and install this package inside of your wsl instance

    * start wsl in the folder
    * clone repo to folder inside wsl
    * python3 -m venv myenv
    * source myenv/bin/activate
    * ``pip install -e .``
    * gointo myenv foldern and open the conf file and change use global packages to true 

4. move models to simulation

    clone this repo also in the same folder as the PX4-Autopilot

    .. code-block:: bash

        cd ~/PX4-ROS2-Gazebo-Drone-Simulation-Template
        cp -r ./PX4-Autopilot_PATCH/* ~/PX4-Autopilot/

5. https://www.geeksforgeeks.org/using-github-with-ssh-secure-shell/


======
Helper
======

1. PowerToys Color Picker

    .. code-block::

        LAB(L = %Lc, A = %Ca, B = %Cb)


2. Cron Tab

    echo 'export PATH="$HOME/PayloadComputerDroneProjekt:$PATH"' >> ~/.bashrc

    crontab -e

    @reboot start_raspi_script.sh

3. Systemd


    mkdir -p ~/.config/systemd/user
    
    code ~/.config/systemd/user/start_droneos.service

    [Unit]
    Description=Start Drone Computer
    After=multi-user.target

    [Service]
    ExecStart=/usr/bin/bash /home/aviator/PayloadComputerDroneProjekt/start_raspi_script.sh
    Type=simple

    [Install]
    WantedBy=multi-user.target
    
    systemctl --user daemon-reload
    systemctl --user enable start_droneos.service
    systemctl --user start start_droneos.service

    
    systemctl --user status start_droneos.service

    
    journalctl -u start_droneos.service

==========
Build docs
==========

1. Install Sphinx and dependencies

    .. code-block:: bash

        pip install sphinx sphinx-autobuild pydata-sphinx-theme

    .. code-block:: bash

        sphinx-autobuild docs_src docs