brinicle 0.0.4

brinicle is a C++ vector index engine (ANN library) optimized for disk-first, low-RAM similarity search.

brinicle

brinicle is a C++ vector index engine (ANN library) optimized for disk-first, low-RAM similarity search. It provides fast build + query, supports inserts/upserts/deletes, and targets predictable latency at high recall with minimal memory overhead on constrained environments.

Install

You can either download via pip:

pip install brinicle

Or compile the code:

git clone https://github.com/bicardinal/brinicle.git
cd brinicle
bash build.sh

Usage

import numpy as np
import brinicle

D = 2
n = 5
X = np.random.randn(n, D).astype(np.float32)
Q = np.random.randn(D).astype(np.float32)

engine = brinicle.VectorEngine("test_index", dim=D, delta_ratio=0.1)

engine.init(mode="build")
for eid in range(n):
    engine.ingest(str(eid), X[eid])
engine.finalize()

print(engine.search(Q, k=10)) # returns a list of ids

To insert:

Y = np.random.randn(5, D).astype(np.float32)
engine.init(mode="insert")
for eid in range(5):
    engine.ingest(str(eid) + "x", Y[eid])
engine.finalize()
print(engine.search(Q, k=10))

To upsert:

Y = np.random.randn(5, D).astype(np.float32)
engine.init(mode="upsert")
for eid in range(5):
    engine.ingest(str(eid), Y[eid])
engine.finalize()
print(engine.search(Q, k=10))

To delete:

engine.delete_items(["1", "4"])
print(engine.search(Q, k=10))

To re-build:

engine.optimize_graph()
print(engine.search(Q, k=10))