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Metadata-Version: 2.4
Name: vecs
Version: 0.4.5
Summary: pgvector client
Home-page: https://github.com/supabase/vecs
Author: Oliver Rice
License: MIT
Classifier: Development Status :: 4 - Beta
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pgvector==0.3.*
Requires-Dist: sqlalchemy==2.*
Requires-Dist: psycopg2-binary==2.9.*
Requires-Dist: flupy==1.*
Requires-Dist: deprecated==1.2.*
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: parse; extra == "dev"
Requires-Dist: numpy; extra == "dev"
Requires-Dist: pytest-cov; extra == "dev"
Provides-Extra: docs
Requires-Dist: mkdocs; extra == "docs"
Requires-Dist: pygments; extra == "docs"
Requires-Dist: pymdown-extensions; extra == "docs"
Requires-Dist: pymarkdown; extra == "docs"
Requires-Dist: mike; extra == "docs"
Provides-Extra: text-embedding
Requires-Dist: sentence-transformers==2.*; extra == "text-embedding"
Dynamic: author
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license
Dynamic: license-file
Dynamic: provides-extra
Dynamic: requires-dist
Dynamic: summary
# vecs
<p>
<a href="https://www.python.org/downloads/"><img src="https://img.shields.io/badge/python-3.7+-blue.svg" alt="Python version" height="18"></a>
<a href="https://github.com/supabase/vecs/actions">
<img src="https://github.com/supabase/vecs/workflows/tests/badge.svg" alt="test status" height="18">
</a>
<a href="https://github.com/supabase/vecs/actions">
<img src="https://github.com/supabase/vecs/workflows/pre-commit/badge.svg" alt="Pre-commit Status" height="18">
</a>
</p>
<p>
<a href="https://badge.fury.io/py/vecs"><img src="https://badge.fury.io/py/vecs.svg" alt="PyPI version" height="18"></a>
<a href="https://github.com/supabase/vecs/blob/master/LICENSE"><img src="https://img.shields.io/pypi/l/markdown-subtemplate.svg" alt="License" height="18"></a>
<a href="https://pypi.org/project/vecs/"><img src="https://img.shields.io/pypi/dm/vecs.svg" alt="Download count" height="18"></a>
</p>
---
**Documentation**: <a href="https://supabase.github.io/vecs/latest/" target="_blank">https://supabase.github.io/vecs/latest/</a>
**Source Code**: <a href="https://github.com/supabase/vecs" target="_blank">https://github.com/supabase/vecs</a>
---
`vecs` is a python client for managing and querying vector stores in PostgreSQL with the [pgvector extension](https://github.com/pgvector/pgvector). This guide will help you get started with using vecs.
If you don't have a Postgres database with the pgvector ready, see [hosting](https://supabase.github.io/vecs/hosting/) for easy options.
## Installation
Requires:
- Python 3.7+
You can install vecs using pip:
```sh
pip install vecs
```
## Usage
Visit the [quickstart guide](https://supabase.github.io/vecs/latest/api) for more complete info.
```python
import vecs
DB_CONNECTION = "postgresql://<user>:<password>@<host>:<port>/<db_name>"
# create vector store client
vx = vecs.create_client(DB_CONNECTION)
# create a collection of vectors with 3 dimensions
docs = vx.get_or_create_collection(name="docs", dimension=3)
# add records to the *docs* collection
docs.upsert(
records=[
(
"vec0", # the vector's identifier
[0.1, 0.2, 0.3], # the vector. list or np.array
{"year": 1973} # associated metadata
),
(
"vec1",
[0.7, 0.8, 0.9],
{"year": 2012}
)
]
)
# index the collection for fast search performance
docs.create_index()
# query the collection filtering metadata for "year" = 2012
docs.query(
data=[0.4,0.5,0.6], # required
limit=1, # number of records to return
filters={"year": {"$eq": 2012}}, # metadata filters
)
# Returns: ["vec1"]
```
|
