semvec/pypi-packages huggingface dataset:
langchain-kinetica 1.2.0
An integration package connecting Kinetica and LangChain
License: MIT
Requires Python: <4.0.0,>=3.10.0

# langchain-kinetica

[![PyPI - Version](https://img.shields.io/pypi/v/langchain-kinetica?label=%20)](https://pypi.org/project/langchain-kinetica/#history)
[![PyPI - License](https://img.shields.io/pypi/l/langchain-kinetica)](https://opensource.org/licenses/MIT)
[![PyPI - Downloads](https://img.shields.io/pepy/dt/langchain-kinetica)](https://pypistats.org/packages/langchain-kinetica)
[![Test](https://github.com/kineticadb/langchain-kinetica/actions/workflows/test.yml/badge.svg)](https://github.com/kineticadb/langchain-kinetica/actions/workflows/test.yml)

This project contains the Kinetica integration 
provider for Langchain. [Kinetica](https://www.kinetica.com/) is a real-time database purpose built for enabling
analytics and generative AI on time-series & spatial data. 

- [Features](#features)
- [Quick Install](#quick-install)
- [Documentation](#documentation)
- [Testing](#testing)
- [See Also](#see-also)

## Features

This package provides integration for core capabilities:

- **Chat model** - Kinetica native Text-to-SQL Generation.
- **Vector Store** - Vector similarity search using Kinetica tables.
- **Document Loader** - Generate embeddings from Kinetica tables.
- **Retriever** - Document retriever based on the Vector Store.

## Quick Install

```bash
pip install langchain-kinetica
```

## Documentation

For conceptual guides, tutorials, and examples on using these classes, see the [Kinetica Provider Docs](https://docs.langchain.com/oss/python/integrations/providers/kinetica).

The documentation is also available in notebook format under `./notebooks`.

## Testing

In addition the `make test` macro these tests can be run individually.

```
$ make integration_tests TEST_FILE=tests/integration_tests/test_chat_models.py

$ make integration_tests TEST_FILE=tests/integration_tests/test_vectorstores.py::test_kinetica
```

## See Also

- [Kinetica LLM Documentation](https://docs.kinetica.com/7.2/sql-gpt/)
- [LangChain Chat Models](https://docs.langchain.com/oss/python/langchain/models)
- [Contributing to LangChain](https://docs.langchain.com/oss/python/contributing/overview)
docs2epub 0.1.8
Turn documentation sites into an EPUB (Kindle-friendly).
License: MIT
Requires Python: >=3.12

# docs2epub

Turn documentation sites into an EPUB (Kindle-friendly).

Initial focus: Docusaurus sites that expose a **Next** button (docs navigation).

## Install (dev)

This project uses Python 3.12+.

```bash
uv sync
uv run docs2epub --help
```

## Usage

### uvx (no install)

```bash
uvx docs2epub \
  https://www.techinterviewhandbook.org/software-engineering-interview-guide/ \
  tech-interview-handbook.epub

# Optional (override inferred metadata)
uvx docs2epub \
  https://www.techinterviewhandbook.org/software-engineering-interview-guide/ \
  tech-interview-handbook.epub \
  --title "Tech Interview Handbook" \
  --author "Yangshun Tay"
```

### Docusaurus “Next” crawl

```bash
# Default output is EPUB2 (Kindle-friendly) via pandoc
uv run docs2epub \
  --start-url "https://www.techinterviewhandbook.org/software-engineering-interview-guide/" \
  --out "dist/tech-interview-handbook.epub" \
  --title "Tech Interview Handbook" \
  --author "Yangshun Tay"

# Optional: build EPUB3 (ebooklib)
uv run docs2epub \
  --format epub3 \
  --start-url "https://www.techinterviewhandbook.org/software-engineering-interview-guide/" \
  --out "dist/tech-interview-handbook.epub" \
  --title "Tech Interview Handbook" \
  --author "Yangshun Tay"
```

## Roadmap

- Add additional discovery strategies: `sitemap.xml`, sidebar parsing, and explicit link lists.
- Optional: send-to-kindle (email), once Gmail auth is set up.
cerebrium 2.2.1
CLI for deploying and managing Cerebrium apps
License: MIT
Requires Python: >=3.8
Keywords: cerebrium, cli, deployment, ai, ml, machine-learning

# Cerebrium CLI

Official Python package for the Cerebrium CLI - deploy and manage AI applications with ease.

## Installation

```bash
pip install cerebrium
```

This will download and install the appropriate Cerebrium CLI binary for your platform.

## Quick Start

```bash
# Login to Cerebrium
cerebrium login

# Initialize a new project
cerebrium init my-app

# Deploy your application
cerebrium deploy
```

## About

This Python package is a wrapper that downloads and manages the Cerebrium Go CLI binary. On first run, it will:

1. Detect your operating system and architecture
2. Download the appropriate pre-compiled binary from GitHub releases
3. Verify checksums for security
4. Install it to `~/.cerebrium/bin/`

Subsequent runs use the cached binary.

## Supported Platforms

- **macOS**: Intel (x86_64) and Apple Silicon (arm64)
- **Linux**: x86_64 and arm64
- **Windows**: x86_64

## Documentation

For full documentation, visit [docs.cerebrium.ai](https://docs.cerebrium.ai)

## Support

- GitHub Issues: [github.com/CerebriumAI/cerebrium/issues](https://github.com/CerebriumAI/cerebrium/issues)
- Email: support@cerebrium.ai

## License

MIT License - see [LICENSE](https://github.com/CerebriumAI/cerebrium/blob/main/LICENSE) for details.