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1.0 KiB
ANN Search Operator: Faiss
author: shiyu
Desription
Search embedding in Faiss, please make sure you have inserted data to Faiss before search.
Code Example
please insert data into faiss first.
Example
Write a same pipeline with explicit inputs/outputs name specifications:
from towhee.dc2 import pipe, ops
p = pipe.input('vec') \
.flat_map('vec', 'rows', ops.ann_search.faiss('./data_dir', 5)) \
.map('rows', ('id', 'score'), lambda x: (x[0], x[1])) \
.output('id', 'score')
p(<your-vector>)
Factory Constructor
Create the operator via the following factory method:
ops.ann_search.faiss_index('./data_dir', 5)
Parameters:
data_dir: str
The path to faiss index and meta data.
Interface
Parameters:
query: ndarray
Query embedding in Faiss
Returns: Entity
Return the results in Faiss with key and score.
1.0 KiB
ANN Search Operator: Faiss
author: shiyu
Desription
Search embedding in Faiss, please make sure you have inserted data to Faiss before search.
Code Example
please insert data into faiss first.
Example
Write a same pipeline with explicit inputs/outputs name specifications:
from towhee.dc2 import pipe, ops
p = pipe.input('vec') \
.flat_map('vec', 'rows', ops.ann_search.faiss('./data_dir', 5)) \
.map('rows', ('id', 'score'), lambda x: (x[0], x[1])) \
.output('id', 'score')
p(<your-vector>)
Factory Constructor
Create the operator via the following factory method:
ops.ann_search.faiss_index('./data_dir', 5)
Parameters:
data_dir: str
The path to faiss index and meta data.
Interface
Parameters:
query: ndarray
Query embedding in Faiss
Returns: Entity
Return the results in Faiss with key and score.