semvec/pypi-packages huggingface dataset:
elonadl 0.1.30
A Installer to download and setup ElonaPlusCustom-GX on Windows.
Requires Python: >=3.10

# ElonaPlusCustom-GX Installer script for Windows

  
A Installer to download and setup ElonaPlusCustom-GX on Windows.


New Repo: **[JianmengYu](https://github.com/JianmengYu/ElonaPlusCustom-GX)** Current Repo based. <br>

Please visit **[Ruin0x11](https://github.com/Ruin0x11/ElonaPlusCustom-GX)**'s Previous Archived Repo


### Learn about the game:

**[Ylvania](https://ylvania.org/elona_e.html)**: Official Site.<br>
**[Fandom Wiki](https://elona.fandom.com/wiki/Elona_Wiki)**: Game Wiki.<br>
**[Discord](https://discord.gg/Razdxsk)**: Discord Channel.<br>

### Need to Know:
You may receive a false positive from Windows Defender
Please review the github issue: **[here](https://github.com/Ruin0x11/ElonaPlusCustom-GX/issues/103)** for more information.


 - In this case just disable __Windows Defender__ or other Anti-Virus prior to installing and re-enable after its finished installing.
<br>



# Version:

Current Installer Version: **v0.1.30**<br>

Current Game Version: **Elona+ 2.26**<br>

Current Custom-GX Version: **2.26.1.0**<br>
<br>


# Result:

  ##### Installation is placed in your %APPDATA% folder.

- Package will install Elona+ along with Custom-GX Mod

- Create a Desktop Shortcut for Quick Access.

- Create a Start Menu Option (Allows app to be searchable in Windows Search)
<br>


# Installation:

```
pip install elonadl

python -m elonadl
```
<br>


# Updates:

If you see a newer release to a newer version. Run the update command:
 ```pip install elonadl --upgrade``` it'll install the new latest installer version.<br>
 Run: ```python -m elonadl``` To install latest version of the game.


* **It will not impact your current game's installation. Just the python package itself.**

* **Running the command** `python -m elonadl` **will download and install the latest version of the game, it will not impact the previous installation. So your saves will be intact (that being said, we always recommend backing up your saves).**
<br>



## Install straight from .whl or tar.gz packages

```
pip install elonadl-<VERSION>-py3-none-any.whl
```
or <br>
```
py -m pip install elonadl-<VERSION>.tar.gz
```

The game will be setup in your current user's **%APPDATA%** folder. **(If run normally)**

The game will be setup in the system's **%APPDATA%** folder. **(if run as admin)**

The script will inform you of the steps in the command line.
<br>


# How to Remove Package.

This won't impact the Elona+CGX setup, just remove the elonadl package from your computer.

```
pip uninstall elonadl
```
or <br>
```
py -m pip uninstall elonadl
```
aptai 1.2.2
Advanced AI-powered SDK for DeFi & NFT analytics on Aptos
Requires Python: >=3.11

# AptAi - Advanced Aptos Blockchain Analytics

Advanced AI-powered SDK for DeFi & NFT analytics on Aptos

## Installation

```bash
pip install aptai
```

## Requirements

- Python 3.11+
- Groq API key

## Quick Start

```python
import aptai

aptai.init(
    groq_api_key="your_groq_api_key",
    system_prompt="Custom AI system prompt", 
    max_tokens=200,                          
    temperature=0.7                          
)

# Get token prices and analytics
apt_price = aptai.get_price("aptos")
print(apt_price)

# Get detailed wallet analysis
wallet_info = aptai.get_detailed_wallet("wallet_address")
print(wallet_info)

# Get NFT collection data
nft_data = aptai.get_nft_data("collection_address")
print(nft_data)

# AI-powered market analysis
analysis = aptai.ai_analysis("What's driving APT price today?")
print(analysis)
```

## Core Features

### Real-Time Analytics
- Multi-source price tracking (DexScreener, CoinGecko)
- Historical price data with volatility metrics
- Transaction volume analysis
- Market sentiment tracking

### Comprehensive Wallet Tracking
- Token balances and holdings
- NFT portfolio analysis
- Transaction history
- DeFi interaction tracking
- Risk assessment

### NFT Analytics
- Cross-marketplace data (Topaz, Souffl3)
- Collection statistics
- Floor price tracking
- Ownership analysis
- Volume metrics

### AI Integration
- Market trend analysis
- Price predictions
- Custom market queries
- Automated insights
- Risk assessment

## Contact

- X: [@Teckdegen](https://x.com/Teckdegen)
- Telegram: [@Teck_degen](https://t.me/Teck_degen)

## License

MIT License
pms-model-manager 1.3.2
lib for pms
Requires Python: <4.0,>=3.10

# pms-model-manager

1. 4by4 pixell lab의 mlflow registry에 model을 업로드하거나 download 할 수 있습니다.
2. model registry에 있는 내용을 수정할 수 있습니다.

## Install

```bash
pip install pms-model-manager
```

## Setting

아래 환경변수들을 정의해야 정상동작 합니다.
* MLFLOW_REGISTRY_URI
* AWS_SECRET_ACCESS_KEY
* MLFLOW_TRACKING_URI
* MLFLOW_REGISTRY_URI
* AWS_DEFAULT_REGION

```bash
export AWS_ACCESS_KEY_ID=YOUR_AWS_ACCESS_KEY_ID
export AWS_SECRET_ACCESS_KEY=YOUR_AWS_SECRET_ACCESS_KEY
export MLFLOW_TRACKING_URI=YOUR_MLFLOW_TRACKING_URI
export MLFLOW_REGISTRY_URI=YOUR_MLFLOW_REGISTRY_URI
export AWS_DEFAULT_REGION=YOUR_AWS_DEFAULT_REGION
```
hionx 0.1.0
Hion (/ˈiː.ɒn/): Hamiltonian-Informed Optimal Neural Control
Requires Python: >=3.13

# Hamiltonian-Informed Optimal Neural (Hion) Controller
Author: Josue N Rivera

---

**Paper:** "Receding Hamiltonian-Informed Optimal Control and State Estimation for Continuous Closed-Loop Dynamical Systems"

This projects implements Hamiltonian-Informed Optimal Neural (Hion) controllers, a novel class of neural network-based controllers for dynamical systems and explicit non-linear model-predictive control. Hion controllers estimate future states and develop an optimal control strategy using Pontryagin’s Maximum Principle. The proposed framework, along with our Taylored Multi-Faceted Approach for Neural ODE and Optimal Control (T-mano) architecture, allows for custom transient behavior, predictive control, and closed-loop feed back, addressing limitations of existing methods. Comparative analyses with established model-predictive controllers revealed Hion controllers’ superior optimality and tracking ca
pabilities. Optimal control strategies are also demonstrated for both linear and non-linear dynamical systems

### Demos

* [`Compare MPCs`](https://github.com/wzjoriv/Hion/blob/main/docs/demos/Compare%20MPCs/presentation.ipynb)

## Development

## Install

```bash
pip install hionx
```

### Train

```bash
python train-t-mano.py -c "configs/config.linear.json"
```

### Test

```bash
python test-t-mano.py -c "logs/checkpoints/linear(controller).checkpoint.pth"
```

## Citation

```bibtex
@article{rivera2024receding,
  title={Receding Hamiltonian-Informed Optimal Neural Control and State Estimation for Closed-Loop Dynamical Systems},
  author={Rivera, Josue N and Sun, Dengfeng},
  journal={arXiv preprint arXiv:2411.01297},
  year={2024}
}

@phdthesis{rivera2024multi,
  author = "Josue N Rivera",
  title = "{Multi-Scale Design and Control of Complex Advanced UAV Systems}",
  year = "2024",
  month = "12",
  url = "https://hammer.purdue.edu/articles/thesis/Multi-Scale_Design_and_Control_of_Complex_Advanced_UAV_Systems/27937332",
  doi = "10.25394/PGS.27937332.v1"
}
```