semvec/pypi-packages huggingface dataset:
nws-wwa 0.0.5
Download watch, warning and advisory data from the National Weather Service
License: MIT

### Other resources

* Source: [www.spc.noaa.gov/products/wwa/](https://www.spc.noaa.gov/products/wwa/)
* Issues: [github.com/datadesk/nws-wwa/issues](https://github.com/datadesk/nws-wwa/issues)
* Packaging: [pypi.python.org/pypi/nws-wwa](https://pypi.python.org/pypi/nws-wwa)
* Testing: [github.com/datadesk/nws-wwa/actions](https://github.com/datadesk/nws-wwa/actions)
clicast 1.0.1
Broadcast messages for CLI tools, such as a warning for critical bug or notification about new features.
License: MIT
Keywords: cli broadcast command warning critical bug

clicast
=======

Broadcast messages for CLI tools, such as a warning for critical bug or notification about new features.

Quick Start Tutorial
====================

As easy as 1-2-3:

1. Install::

    pip install clicast

2. Create your own cast file and make it accessible as an URL.
   I.e. https://raw.githubusercontent.com/maxzheng/clicast/master/tests/example.cast ::

    cast "New Message" -f example.cast
    # See 'cast -h' for more options to edit cast file

3. Import and call check_message::

    from clicast import check_message

    def main():
        check_message('https://raw.githubusercontent.com/maxzheng/clicast/master/tests/example.cast',
                      allow_exit=True,
                      header='=' * 80,
                      footer='=' * 80)

CLI Example
============

Don't even want to write the bin script to try? I got you covered! :) ::

    $ wget https://raw.githubusercontent.com/maxzheng/clicast/master/bin/cast-example
    $ chmod +x cast-example

If you run cast-example for the first time, you will see::

    $ ./cast-example
    ================================================================================
    We found a big bad bug. Please try not to step on it!! Icky...
    No worries. It will be fixed soon! :)

    Version 0.1 has been released! If you upgrade, you will get:
    1) Cool feature 1
    2) Cool feature 2
    So what are you waiting for? :)

    Version 0.2 has been released! Upgrade today to get cool features.

    There is a small bug over there, so watch out!
    ================================================================================
    Hello World! Pass in '-f' to see message targeted for that option

And run it again::

    $ ./cast-example
    ================================================================================
    We found a big bad bug. Please try not to step on it!! Icky...
    No worries. It will be fixed soon! :)
    ================================================================================
    Hello World! Pass in '-f' to see message targeted for that option

And now with -f option::

    $ ./cast-example -f
    ================================================================================
    We found a big bad bug. Please try not to step on it!! Icky...
    No worries. It will be fixed soon! :)

    A bug that affects the -f option. (applies only if `clicast.filters.match_cli_args` filter is used)
    ================================================================================
    Hello World! Pass in '-f' to see message targeted for that option

That's it!

More
====

| Documentation: http://clicast.readthedocs.org/
|
| PyPI: https://pypi.python.org/pypi/clicast
| GitHub Project: https://github.com/maxzheng/clicast
| Report Issues/Bugs: https://github.com/maxzheng/clicast/issues
|
| Connect: https://www.linkedin.com/in/maxzheng
| Contact: maxzheng.os @t gmail.com
neumai 0.0.40
Package containing connectors for Neum AI.
License: MIT
Requires Python: >=3.10,<4.0
Keywords: neumai,ai tools,data tools

<h1 align="center">Neum AI</h1>

<div align="center">
  
  [Homepage](https://www.neum.ai) | [Documentation](https://docs.neum.ai) | [Discord](https://discord.gg/mJeNZYRz4m) | [Twitter](https://twitter.com/neum_ai)
  
  <a href="https://www.ycombinator.com/companies/neum-ai"><img src="https://badgen.net/badge/Y%20Combinator/S23/orange"/></a>
</div>

Core library with Neum AI components to connect, load, chunk and sink vector embeddings. **[Neum AI](https://neum.ai) is a data platform that helps developers leverage their data to contextualize Large Language Models through Retrieval Augmented Generation (RAG)** This includes
extracting data from existing data sources like document storage and NoSQL, processing the contents into vector embeddings and ingesting the vector embeddings into vector databases for similarity search. 

It provides you a comprehensive solution for RAG that can scale with your application and reduce the time spent integrating services like data connectors, embedding models and vector databases.

## Features

- 🏭 **High throughput distrubted architecture** to handle billions of data points. Allows high degrees of parallelization to optimize embedding generation and ingestion.
- 🧱 **Built-in data connectors** to common data sources, embedding services and vector stores.
- 🔄 **Real-time synchronization** of data sources to ensure your data is always up-to-date. 
- 🤝 **Cohesive data management** to support hybrid retrieval with metdata. Neum AI automatically augments and tracks metadata to provide rich retrieval experience.

## Getting Started

### Neum AI Cloud

Sign up today at [dasboard.neum.ai](https://dashboard.neum.ai). See our [quickstart]() to get started.

The Neum AI Cloud supports a large-scale, distrubted architecture to run millions of documents through vector embedding. For the full set of features see: [Cloud vs Local](https://neumai.mintlify.app/get-started/cloud-vs-local)

### Local Development

Install the [`neumai`](https://pypi.org/project/neumai/) package:

```bash
pip install neumai
```

To create your first data pipelines visit our [quickstart]().

### Self-host

If you are interested in deploying Neum AI to your own cloud contact us at [founders@tryneum.com](mailto:founders@tryneum.com).

We will publish soon an open-source self-host that leverages the framework's architecture to do high throughput data processing.

## Roadmap

Connectors
- [ ]  MySQL - Source
- [ ]  GitHub - Source
- [ ]  Google Drive - Source
- [ ]  Hugging Face - Embedding
- [ ]  LanceDB - Sink
- [ ]  Milvus - Sink
- [ ]  Chroma - Sink

Search
- [ ]  Retrieval feedback
- [ ]  Filter support
- [ ]  Unified Neum AI filters
- [ ]  Self-Query Retrieval (w/ Metadata attributes generation)

Extensibility
- [ ]  Langchain / Llama Index Document to Neum Document converter
- [ ]  Custom chunking and loading

Experimental
- [ ]  Async metadata augmentation
- [ ]  Chat history connector
- [ ]  Structured (SQL and GraphQL) search connector