| Name | svs JSON |
| Version |
0.1.0
JSON |
| download |
| home_page | None |
| Summary | Stupid Vector Store (SVS): a vector database for the rest of us |
| upload_time | 2024-06-30 20:28:08 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | None |
| keywords |
database
embeddings
store
stupid
vector
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Stupid Vector Store (SVS)
[](https://pypi.org/project/svs)
[](https://pypi.org/project/svs)
## Overview
SVS is stupid yet can handle a million documents on commodity hardware, so it's probably perfect for you.
**Should you use SVS?** SVS is designed for the use-case where:
1. you have less than a million documents, and
2. you don't add/remove documents very often.
If that's you, then SVS will probably be the simples (and stupidest) way to manage your document vectors!
## Table of Contents
- [Installation](#installation)
- [Used By](#used-by)
- [Quickstart](#quickstart)
- [Debug Logging](#debug-logging)
- [License](#license)
## Installation
```console
pip install -U svs
```
## Used By
SVS is used in production by:
[](https://www.autoauto.ai/)
## Quickstart
TODO
## Debug Logging
This library logs using Python's builtin `logging` module. It logs mostly to `INFO`, so here's a snippet of code you can put in _your_ app to see those traces:
```python
import logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
)
# ... now use SVS as you normally would, but you'll see extra log traces!
```
## License
`svs` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
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