semvec/pypi-packages huggingface dataset:
gcloud-rest-storage 9.6.1
Python Client for Google Cloud Storage
License: MIT
Requires Python: <4.0,>=3.9

(Asyncio OR Threadsafe) Python Client for Google Cloud Storage
==============================================================

    This is a shared codebase for ``gcloud-rest-storage`` and
    ``gcloud-rest-storage``

|pypi| |pythons|

Installation
------------

.. code-block:: console

    $ pip install --upgrade gcloud-{aio,rest}-storage

Usage
-----

See `our docs`_.

Contributing
------------

Please see our `contributing guide`_.

.. _contributing guide: https://github.com/talkiq/gcloud-rest/blob/master/.github/CONTRIBUTING.rst
.. _our docs: https://talkiq.github.io/gcloud-rest

.. |pypi| image:: https://img.shields.io/pypi/v/gcloud-rest-storage.svg?style=flat-square
    :alt: Latest PyPI Version (gcloud-rest-storage)
    :target: https://pypi.org/project/gcloud-rest-storage/

.. |pythons| image:: https://img.shields.io/pypi/pyversions/gcloud-rest-storage.svg?style=flat-square&label=python
    :alt: Python Version Support
    :target: https://pypi.org/project/gcloud-rest-storage/
gcloud-aio-storage 9.6.1
Python Client for Google Cloud Storage
License: MIT
Requires Python: <4.0,>=3.9

(Asyncio OR Threadsafe) Python Client for Google Cloud Storage
==============================================================

    This is a shared codebase for ``gcloud-aio-storage`` and
    ``gcloud-rest-storage``

|pypi| |pythons|

Installation
------------

.. code-block:: console

    $ pip install --upgrade gcloud-{aio,rest}-storage

Usage
-----

See `our docs`_.

Contributing
------------

Please see our `contributing guide`_.

.. _contributing guide: https://github.com/talkiq/gcloud-aio/blob/master/.github/CONTRIBUTING.rst
.. _our docs: https://talkiq.github.io/gcloud-aio

.. |pypi| image:: https://img.shields.io/pypi/v/gcloud-aio-storage.svg?style=flat-square
    :alt: Latest PyPI Version (gcloud-aio-storage)
    :target: https://pypi.org/project/gcloud-aio-storage/

.. |pythons| image:: https://img.shields.io/pypi/pyversions/gcloud-aio-storage.svg?style=flat-square&label=python
    :alt: Python Version Support
    :target: https://pypi.org/project/gcloud-aio-storage/
mcpgw-mcp-server 0.1.0
MCP server package - Created by Poneglyph for security research
License: MIT
Requires Python: >=3.8

# mcpgw mcp server

**Created by Poneglyph for security research**

## Overview

This package is part of a security research project by Poneglyph. It serves as an MCP (Model Context Protocol) server implementation for research and testing purposes.

## Installation

```bash
pip install mcpgw-mcp-server
```

Or use with uvx:

```bash
uvx mcpgw-mcp-server
```

## Usage

```bash
mcpgw-mcp-server
```

## Purpose

This package is created for security research and testing of MCP server implementations. It is intended for educational and research purposes only.

## Security Research

This project is maintained by Poneglyph Security Research team. For questions or concerns, please visit our repository.

## License

MIT License - See LICENSE file for details.

## Disclaimer

This software is provided for research and educational purposes only. Users are responsible for ensuring compliance with applicable laws and regulations.
langchain-vdms 0.2.0
An integration package connecting VDMS and LangChain
License: MIT
Requires Python: <4.0,>=3.10

# Langchain VDMS

![GitHub License](https://img.shields.io/github/license/IntelLabs/langchain-vdms)

This package contains the [VDMS](https://github.com/IntelLabs/vdms) integration package for LangChain:

- [langchain-vdms](https://pypi.org/project/langchain-vdms/) - An integration between LangChain and VDMS which enables retrievers and vector search for AI applications.

## Installation

```bash
pip install -U langchain-vdms
```

<!-- And you should configure credentials by setting the following environment variables:

* TODO: fill this out -->


## VDMS vector database

The ``VDMS`` class exposes the VDMS vector store.

```python
from langchain_vdms import VDMS
```
<br>

The ``VDMS_Client`` function connects to VDMS server using VDMS client.

```python
from langchain_vdms.vectorstores import VDMS_Client
```
<br>

The ``VDMS_Utils`` class exposes a utility with helpful functions related to VDMS.

```python
from langchain_vdms.vectorstores import VDMS_Utils
```

## Example Usage
This example initiates the VDMS vector store and uses the VDMS Client to connect to a VDMS server on `localhost` using port `55555`.
```python
from langchain_vdms.vectorstores import VDMS, VDMS_Client

embeddings = ... # use a LangChain Embeddings class

vectorstore_client = VDMS_Client("localhost", 55555)
vectorstore = VDMS(
    client=vectorstore_client,
    collection_name="foo",
    embedding=embeddings,
    engine="FaissFlat",
    distance_strategy="L2",
)
```
See additional usage [here](https://python.langchain.com/docs/integrations/vectorstores/vdms/).


## Contributing

Contributions are welcome! Please see [CONTRIBUTING.md](/CONTRIBUTING.md) for guidelines.


## License

This project is licensed under the MIT License - see the [LICENSE](/LICENSE) file for details.