Similarity engine utils
Project description
similarity-engine-utils
Utility tools for easier management of feature-vector database and similar vector comparison
Installation
Use the package manager pip to install library.
pip install similarity-engine-utils
Setup backend connection (milvus)
from se_utils.backend.milvus.core import setup_connection
milvus_credentials = {
"alias": "default",
"host": "localhost",
"port": "19530"
}
collection_name = 'test_collection'
c = setup_connection(milvus_credentials)
Create collection
from se_utils.backend.milvus.core import create_milvus_collection, generate_schema, read_schema_json
collection_name = 'test_collection'
schema_path = "/path/to/schema.json"
tag = "some_tag"
# existing tag
collection1 = create_milvus_collection(collection_name, tag=tag)
# parse json schema
collection_schema, index_params = generate_schema(tag=tag,
schema=read_schema_json(schema_path))
collection2 = create_milvus_collection(collection_name,
schema=collection_schema,
indices=index_params)
Insert data to collection
from se_utils.backend.milvus.core import insert2milvus
collection_name = 'test_collection'
kwargs = {
"id": 1,
"name": "name",
"emb": [1,1,1,1]
}
insert2milvus(data=[kwargs],
collection_name=collection_name)
Find the closest cluster id
import numpy as np
from se_utils.backend.milvus.core import get_cluster_id, get_increment_cluster_id
collection_name = 'test_collection'
emb_label = 'emb'
emb = [np.random.uniform(low=-1, high=1, size=(1024,)).tolist()
for _ in range(1)][0]
cluster_label = 'group_id'
cluster_id = get_cluster_id(collection_name=collection_name,
emb=emb,
emb_label=emb_label,
cluster_label=cluster_label)
if cluster_id is None:
cluster_id = get_increment_cluster_id(collection_name=collection_name,
cluster_label=cluster_label)
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