Operator: ANN Search: Faiss

author: shiyu

Desription

Search embedding in Faiss, please make sure you have inserted data to Faiss before search.

Code Example

• Insert data into Faiss first

import numpy as np
import towhee

vec = np.random.random((10, 100)).astype('float32')
ids = list(i for i in range(10))

x = towhee.dc['id'](ids) \
    .runas_op['id', 'vec'](func=lambda x: vec[x]) \
    .to_faiss['id', 'vec'](findex='index.bin')

• Example

Write the pipeline in simplified style:

query = vec[0:2]
towhee.dc(query) \
    .ann_search.faiss(findex='index.bin')

Write a same pipeline with explicit inputs/outputs name specifications:

query = vec[0:2]
towhee.dc['vec'](query) \
    .ann_search.faiss['vec', 'results'](findex='index.bin') \
    .show()

Factory Constructor

Create the operator via the following factory method:

ann-search.faiss(findex)

Parameters:

findex: str or faiss.INDEX

The path to faiss index file or faiss index.

Interface

Parameters:

query: list

Query embeddings in Faiss

Returns: Entity

Return the results in Faiss with key and score.