semvec/pypi-packages huggingface dataset:
agentsystems-toolkit 0.2.1
Development toolkit for building AgentSystems agents
Requires Python: >=3.11

# AgentSystems Toolkit

[![GitHub stars](https://img.shields.io/github/stars/agentsystems/agentsystems?style=flat-square&logo=github)](https://github.com/agentsystems/agentsystems/stargazers)

> [!NOTE]
> **Pre-Release Software** - AgentSystems is in active development. Join our [Discord](https://discord.com/invite/JsxDxQ5zfV) for updates and early access.
> ⭐ [**Star the main repository**](https://github.com/agentsystems/agentsystems) to show your support!

> This is the **development toolkit** for AgentSystems. See the [main repository](https://github.com/agentsystems/agentsystems) for platform overview and documentation.

Development toolkit for building AgentSystems agents with model routing, progress tracking, and agent framework integration.

## Features

- **Model Routing**: Abstract model layer supporting OpenAI, Anthropic, AWS Bedrock, Ollama
- **Progress Tracking**: Progress reporting utilities for long-running tasks
- **LangChain Integration**: Pre-configured providers with credential management

## Installation

```bash
pip install agentsystems-toolkit
```

## Quick Start

```python
from agentsystems_toolkit import get_model

# Get a model - automatically routes to configured provider
model = get_model("claude-sonnet-4", "langchain", temperature=0)

# Use with any LangChain workflow
response = model.invoke("Hello, world!")
```

## License

Licensed under the [Apache-2.0 license](./LICENSE).
pkdb-analysis 0.3.1
Python utilities for PK-DB.
Requires Python: >=3.11
Keywords: PK-DB, pharmacokinetics, standardization

# pkdb_analysis: PK-DB python interface
[![GitHub Actions CI/CD Status](https://github.com/matthiaskoenig/pkdb_analysis/workflows/CI-CD/badge.svg)](https://github.com/matthiaskoenig/pkdb_analysis/actions/workflows/main.yml)
[![Version](https://img.shields.io/pypi/v/pkdb_analysis.svg)](https://pypi.org/project/pkdb_analysis/)
[![Python Versions](https://img.shields.io/pypi/pyversions/pkdb-analysis.svg)](https://pypi.org/project/pkdb-analysis/)
[![MIT License](https://img.shields.io/pypi/l/sbmlutils.svg)](https://opensource.org/licenses/MIT)
[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3997539.svg)](https://doi.org/10.5281/zenodo.3997539)

pkdb_analysis is a collection of python utilities to interact with
PK-DB https://pk-db.com via the available REST endpoints https://pk-db.com/api/v1/swagger/.

## How to cite

[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.3997539.svg)](https://doi.org/10.5281/zenodo.3997539)

## Installation

pkdb_analysis is available from [pypi](https://pypi.python.org/pypi/pkdb-analysis) and
can be installed via
```
pip install pkdb-analysis
```

## PK-DB endpoint

pkdb_analysis requires an existing PK-DB endpoint, which can be set by setting the
respective environment variables.

```bash
set -a && source .env.local
```

The public instances of PK-DB are available from
```bash
API_BASE=https://alpha.pk-db.com
API_BASE=https://pk-db.com
```

## License

- Source Code: [MIT](https://opensource.org/license/MIT)
- Documentation: [CC BY-SA 4.0](http://creativecommons.org/licenses/by-sa/4.0/)


## Funding

Matthias König is supported and by the German Research Foundation (DFG) within the Research Unit Programme FOR 5151
"`QuaLiPerF <https://qualiperf.de>`__ (Quantifying Liver Perfusion-Function Relationship in Complex Resection -
A Systems Medicine Approach)" by grant number 436883643 and by grant number
465194077 (Priority Programme SPP 2311, Subproject SimLivA).

Matthias König was supported by the Federal Ministry of Education and Research (BMBF, Germany)
within the research network Systems Medicine of the Liver (**LiSyM**, grant number 031L0054).

© 2018-2025 Jan Grzegorzewski & Matthias König.
PheQTK 0.0.4
A wrapper to the PheTK package.
Requires Python: >=3.9

# PheQTK - The Phenotype Quick Toolkit
PheQTK is a Python package that wraps around [PheTK](https://github.com/nhgritctran/PheTK). 

## Installation
In your All of Us jupyter notebook, install PheQTK using the following command:

```bash
!pip install --upgrade PheQTK 
```

## Usage
To start the PheQTK interface, run the following command:

```python
from PheQTK import Quick

Quick.run()
```
You will be prompted to select a module. You can also select 'all' to run all modules.

If you run individual modules, you will be prompted to add required parameters for that module. Below is a list of the required parameters for each module:
- Cohort Module:
  - a comma separated list of variant ids (20_13093478_G_A, 20_13093479_G_A, etc.)
- Phecodes Module:
  - 

## Roadmap
Currently, PheQTK only supports PheTK's Cohort Module. Additional modules will be added soon.

## Contributing
Pull requests are welcome. For major changes, please open an issue first
to discuss what you would like to change.

## License
[MIT](https://choosealicense.com/licenses/mit/)
modnn 3.0.9
Physics-Informed Modularized Neural Network for Building Energy Modeling
Requires Python: >=3.7

# ModNN

**ModNN** is a Modularized Physics-Informed Neural Network for building energy modeling.

It incorporates with physics-informed model structure, loss function, and model constraints.

---

## 🚀 Installation

You can install the package using pip:

pip install modnn



## 🧠 Example
Please find the online Jupyter notebook for a step-by-step instruction:
https://colab.research.google.com/drive/1A2jt1q53RtxGuaoym6N1PmlKELDPpYFX?usp=sharing


## 🧠 Update log
# 🧠 [2.0.0] 2025 May 9
To further improve physical consistency, 

I replaced heat transfer module by set of energy balance equations, 

Start from version 2.0.0

# 🧠 [2.0.1] 2025 May 10
Add another parameter: "envelop_mdl", 

Allow user to use the new physics based module or previous data driven module. 

# 🧠 [2.0.2] 2025 May 10
Fix bug due to parameter: "envelop_mdl",

Vectorize calculation,speed improved by ~6 times.

# 🧠 [3.0.0] 2025 June 11
Update datadriven modnn
RC based envelop_mdl really hard to tune on new dataset

# 🧠 [3.0.1] 2025 June 11
Add a step function for one step ahead prediction

# 🧠 [3.0.2] 2025 June 11
Fix bug for step function

# 🧠 [3.0.3] 2025 June 11
Fix bug for step function

# 🧠 [3.0.4] 2025 Sept 10
Didn't work on it for 3 months, just update the latest version
Will use it for BESTOpt building dynamic model

# 🧠 [3.0.5] 2025 Sept 15
3.0.4 CAN-NOT work at all, I mistakenly comment one line and add a new line of code

# 🧠 [3.0.6] 2025 Sept 15
Fix temperature unit conversion issue

# 🧠 [3.0.7] 2025 Sept 15
Fix step model zone module dimension issue

# 🧠 [3.0.8] 2025 Oct 20
Change path in saving results function, so Windows user can use it without bugs

# 🧠 [3.0.9] 2025 Oct 20
Fix bugs
## 🧪 Requirements

    Python 3.7+

    PyTorch

    NumPy

    Pandas

    Matplotlib

    Seaborn

    scikit-learn

    tqdm

---
📬 License

MIT License

🙋‍♂️ Author

Zixin Jiang: 
zjiang19@syr.edu