semvec/pypi-packages huggingface dataset:
dagster-contrib-notdiamond 0.1.2
Dagster integration with Not Diamond
Requires Python: >=3.9

# Dagster resource for Not Diamond ¬◇

Not Diamond is an AI model router that automatically determines which LLM is best-suited to respond to any query, improving LLM output quality by combining multiple LLMs into a **meta-model** that learns when to call each LLM.

## Installation

```bash
pip install dagster-contrib-notdiamond
```

## Configuration

Make sure you have followed the steps in the [Quickstart docs][quickstart], and added a Not Diamond API key to your environment.

## Usage

Define a resource for Not Diamond, then create the asset:

```python
from dagster import (
    Definitions,
    EnvVar,
    ScheduleDefinition,
    AssetSelection,
    AssetExecutionContext,
    MaterializeResult,
    asset,
)
from dagster_contrib_notdiamond import NotDiamondResource


@asset
def notdiamond_asset(context: AssetExecutionContext, notdiamond: NotDiamondResource) -> MaterializeResult:
    with notdiamond.get_client(context) as client:
        session_id, best_llm = client.model_select(
            model=["openai/gpt-4o", "openai/gpt-4o-mini"],
            messages=[{"role": "user", "content": "Say this is a test"}]
        )
    return MaterializeResult(metadata={"session_id": session_id, "best_llm": str(best_llm)})

notdiamond_schedule = ScheduleDefinition(
    name="notdiamond_schedule",
    target=AssetSelection.all(),
    cron_schedule="17 * * * *",
)

defs = Definitions(
    assets=[notdiamond_asset],
    resources={
        "notdiamond": NotDiamondResource(api_key=EnvVar("NOTDIAMOND_API_KEY")),
    },
    schedules=[notdiamond_schedule],
)
```

Please refer to `example_job/example_notdiamond.py` for an example script which you can test by updating
your pyproject.toml as follows (replacing `$PROJECT_HOME` with the path to this project):

```toml
[tool.dagster]
module_name = "example_job.example_notdiamond"
working_directory = "$PROJECT_HOME/libraries/dagster-contrib-notdiamond/"
```

## Support

Visit the [documentation for Not Diamond][docs] or send a message to [support@notdiamond.ai][mailto]

[docs]: https://docs.notdiamond.ai
[mailto]: mailto:support@notdiamond.ai
[quickstart]: https://docs.notdiamond.ai/docs/quickstart
trubrics-beta 0.3.0
Python SDK to track events in Trubrics.
Requires Python: >=3.8

# trubrics-sdk

> [!IMPORTANT]
> We are currently in beta.

To track events:

```python
trubrics = Trubrics(api_key="YOUR_TRUBRICS_API_KEY")

trubrics.track(
    event="User prompt",
    user_id="test_user_id",
    properties={"$text": "Hello, Trubrics! Tell me a joke?", "$thread_id": "your thread id"},
)
```
pyatoms 0.0.1
Python automated tools for materials screening
Requires Python: >=3.9

# pyatoms

The goal of **pyatoms** (Python automated tools for materials screening) is to enable automated, high-throughput computational screening of materials.

Currently, **pyatoms** is still in the early stages of development, and its features are primarily based on the methods that my collaborators and I have accumulated during our research on battery materials.

In the future, we aim to continually enhance **pyatoms** with the goal of achieving **real** automated materials screening.

## Installation

**pyatoms** can be easily installed using the following command:

```sh
pip install pyatoms
```
epidemic-intelligence 1.0.1
A data visualization package to explore large-scale spatio-temporal simulation data.
Requires Python: >=3.8

# epidemic-intelligence
`epidemic-intelligence` is an open-source Python package developed at the Network Science Institute to explore large-scale spatio-temporal simulation data. Simply put, it uses Google's BigQuery to efficiently process and visualize simulations of networks across time, then uses the output to create publication ready visualizations. 

This GitHub repository contains the code for the Python package and the documentation, which is contained within a JupyterBook.  

## Tools
Full documentation, including installation and setup, is available [here](https://www.matteochinazzi.com/epidemic-intelligence/content/setup.html). 

The `epidemic-intelligence` package  can be found on the Python Package Index [here](https://pypi.org/project/epidemic-intelligence). 

Instructions for updating both the library and the corresponding documentation can be found in `CONTRIBUTING.md`.

## License
`epidemic-intelligence` is distributed with the 3-clause BSD license. The full text of this license can be found in `license.txt`.
jk_regexhelper 0.2025.1.7.2
A collection of regex helper functions.
Requires Python: >=3.8
Keywords: regex

jk_regexhelper
==========

Introduction
------------

This python module provides regex helper functions for use in other modules or tools.

Information about this module can be found here:

* [github.org](https://github.com/jkpubsrc/python-module-jk-regexhelper)
* [pypi.python.org](https://pypi.python.org/pypi/jk_regexhelper)

Why this module?
----------------

...

Limitations of this module
--------------------------

...

How to use this module
----------------------

### Import this module

Please include this module into your application using the following code:

```python
import jk_regexhelper
```

...

Contact Information
-------------------

* Jürgen Knauth: pubsrc@binary-overflow.de

License
-------

This software is provided under the following license:

* Apache Software License 2.0