Scores for Hybrid search

Support
6

hi @Rohini_vaidya !!

Here is how you can do that:

vectors = {
    "a_vector": [1,2,3],
    "b_vector": [1,2,3,4],
    "c_vector": [1,2,3,4,5]
}

client.collections.delete("Test")
collection = client.collections.create(
    "Test", 
    vectorizer_config=[
        wvc.config.Configure.NamedVectors.none(name="a_vector"),
        wvc.config.Configure.NamedVectors.none(name="b_vector"),
        wvc.config.Configure.NamedVectors.none(name="c_vector"),
    ]
)
collection.data.insert(
    properties={"text": "music for running", "brand": "Bosch"},
    vector=vectors
)

now you can get your objects:

query = collection.query.fetch_objects(include_vector=True)
print(query.objects[0].properties)
print(query.objects[0].vector)

# outputs:
# {'text': 'music for running', 'brand': 'Bosch'}
# {'a_vector': [1.0, 2.0, 3.0], 'b_vector': [1.0, 2.0, 3.0, 4.0], 'c_vector': [1.0, 2.0, 3.0, 4.0, 5.0]}

You can also search using near_vector:

query = collection.query.near_vector(
    near_vector=[5,4,3,2,1], include_vector=True, target_vector="c_vector", return_metadata=wvc.query.MetadataQuery(distance=True)
)
print(query.objects[0].properties)
print(query.objects[0].vector)
print(query.objects[0].metadata.distance)

# outputs:
# {'text': 'music for running', 'brand': 'Bosch'}
# {'c_vector': [1.0, 2.0, 3.0, 4.0, 5.0], 'a_vector': [1.0, 2.0, 3.0], 'b_vector': [1.0, 2.0, 3.0, 4.0]}
# 0.3636362552642822

Let me know if this helps!

Thanks!