0.1.0

affine

Affine is a Python library for providing a uniform and structured interface to various backing vector databases and approximate nearest neighbor libraries. It allows simple dataclass-like objects to describe collections together with a high-level query syntax for doing filtered vector search.

For vector databases, it currently supports:

• qdrant
• weaviate
• pinecone

For local mode, the following approximate nearest neighbor libraries are supported:

• FAISS
• annoy
• pynndescent
• scikit-learn KDTree
• naive/NumPy

Note: this project is very similar to vectordb-orm, which looks to be no longer maintained.

Installation

pip install affine-vectordb
# or `pip install "affine-vectordb[qdrant]"` for qdrant support
# `pip install "affine-vectordb[weaviate]"` for weaviate support
# `pip install "affine-vectordb[pinecone]"` for pinecone support

Basic Usage

from affine import Collection, Vector, Filter, Query

# Define a collection
class MyCollection(Collection):
    vec: Vector[3] # declare a 3-dimensional vector

    # support for additional fields for filtering
    a: int
    b: str

db = LocalEngine()

# Insert vectors
db.insert(MyCollection(vec=[0.1, 0.0, -0.5], a=1, b="foo"))
db.insert(MyCollection(vec=[1.3, 2.1, 3.6], a=2, b="bar"))
db.insert(MyCollection(vec=[-0.1, 0.2, 0.3], a=3, b="foo"))

# Query vectors
result: list[MyCollection] = (
    db.query(MyCollection)
    .filter(MyCollection.b == "foo")
    .similarity([2.8, 1.8, -4.5])
    .limit(1)
)

Engines

A fundamental notion of affine are Engine classes. All such classes conform to the same API for interchangeabillity (with the exception of a few engine-specific restrictions which are be mentioned below). There are two broad types of engines

1. LocalEngine: this does nearest neighbor search on the executing machine, and supports a variety of libraries for the backing nearest neighborsearch (these are called the backend of the local engine).

2. Vector database engines: these are engines that connect to a vector database service, such as QDrant, Weaviate, or Pinecone.

Vector Databases

The currently supported vector databases are:

Approximate Nearest Neighbor Libraries

The LocalEngine class provides an interface for doing nearest neighbor search on the executing machine, supporting a variety of libraries for the backing nearest neighborsearch. Which one is specified by the backend argument to the constructor. For example, to use annoy:

from affine.engine.local import LocalEngine, AnnoyBackend

db = LocalEngine(backend=AnnoyBackend(n_tress=10))

The options and settings for the various supported backends are as follows: