colibri.qdrant / tests /openapi /test_multi_vector.py
Gouzi Mohaled
Ajout du dossier tests
3932407
import pytest
import os
from .helpers.collection_setup import drop_collection
from .helpers.helpers import request_with_validation
@pytest.fixture(autouse=True)
def setup(on_disk_vectors, collection_name):
multivector_collection_setup(collection_name=collection_name, on_disk_vectors=on_disk_vectors)
yield
drop_collection(collection_name=collection_name)
def multivector_collection_setup(
collection_name='test_collection',
on_disk_vectors=False):
drop_collection(collection_name=collection_name)
response = request_with_validation(
api='/collections/{collection_name}',
method="PUT",
path_params={'collection_name': collection_name},
body={
"vectors": {
"my-multivec": {
"size": 4,
"distance": "Dot",
"on_disk": on_disk_vectors,
"multivector_config": {
"comparator": "max_sim"
}
}
},
}
)
assert response.ok
response = request_with_validation(
api='/collections/{collection_name}',
method="GET",
path_params={'collection_name': collection_name},
)
assert response.ok
def test_multi_vector_float_persisted(collection_name):
# batch upsert
response = request_with_validation(
api='/collections/{collection_name}/points',
method="PUT",
path_params={'collection_name': collection_name},
query_params={'wait': 'true'},
body={
"points": [
{
"id": 1,
"vector": {
"my-multivec": [
[0.05, 0.61, 0.76, 0.74],
[0.05, 0.61, 0.76, 0.74],
[0.05, 0.61, 0.76, 0.74]
]
}
},
{
"id": 2,
"vector": {
"my-multivec": [
[0.19, 0.81, 0.75, 0.11],
[0.19, 0.81, 0.75, 0.11],
[0.19, 0.81, 0.75, 0.11]
]
}
},
{
"id": 3,
"vector": {
"my-multivec": [
[0.36, 0.55, 0.47, 0.94],
[0.36, 0.55, 0.47, 0.94],
[0.36, 0.55, 0.47, 0.94]
]
}
},
]
}
)
assert response.ok
# scroll
response = request_with_validation(
api='/collections/{collection_name}/points/scroll',
method="POST",
path_params={'collection_name': collection_name},
body={"limit": 10, "with_vector": True}
)
assert response.ok
assert len(response.json()['result']['points']) == 3
results = response.json()['result']['points']
first_point = results[0]
assert first_point['id'] == 1
assert first_point['vector']['my-multivec'] == [[0.05, 0.61, 0.76, 0.74], [0.05, 0.61, 0.76, 0.74], [0.05, 0.61, 0.76, 0.74]]
# retrieve by id
response = request_with_validation(
api='/collections/{collection_name}/points/{id}',
method="GET",
path_params={'collection_name': collection_name, 'id': 2},
)
assert response.ok
point = response.json()['result']
assert point['id'] == 2
assert point['vector']['my-multivec'] == [[0.19, 0.81, 0.75, 0.11], [0.19, 0.81, 0.75, 0.11], [0.19, 0.81, 0.75, 0.11]]
# delete by id
response = request_with_validation(
api='/collections/{collection_name}/points/delete',
method="POST",
path_params={'collection_name': collection_name},
body={
"points": [2]
}
)
assert response.ok
# retrieve by id after deletion
response = request_with_validation(
api='/collections/{collection_name}/points/{id}',
method="GET",
path_params={'collection_name': collection_name, 'id': 2},
)
assert not response.ok
def test_multi_vector_validation(collection_name):
# fails because it uses and empty multi vector
response = request_with_validation(
api='/collections/{collection_name}/points',
method="PUT",
path_params={'collection_name': collection_name},
query_params={'wait': 'true'},
body={
"points": [
{
"id": 1,
"vector": {
"my-multivec": []
}
}
]
}
)
assert not response.ok
assert 'Wrong input: Vector dimension error: expected dim: 4, got 0' in response.json()["status"]["error"]
# fails because it uses an empty inner vector
response = request_with_validation(
api='/collections/{collection_name}/points',
method="PUT",
path_params={'collection_name': collection_name},
query_params={'wait': 'true'},
body={
"points": [
{
"id": 1,
"vector": {
"my-multivec": [[]]
}
}
]
}
)
assert not response.ok
assert 'Validation error in JSON body: [points[0].vector.?.data: all vectors must be non-empty]' in \
response.json()["status"]["error"]
# fails because it uses one inner vector
response = request_with_validation(
api='/collections/{collection_name}/points',
method="PUT",
path_params={'collection_name': collection_name},
query_params={'wait': 'true'},
body={
"points": [
{
"id": 1,
"vector": {
"my-multivec": [
[0.05, 0.61, 0.76, 0.74],
[]
]
}
}
]
}
)
assert not response.ok
assert 'Validation error in JSON body: [points[0].vector.?.data: all vectors must be non-empty]' in \
response.json()["status"]["error"]
# fails because it uses inner vectors with different dimensions
response = request_with_validation(
api='/collections/{collection_name}/points',
method="PUT",
path_params={'collection_name': collection_name},
query_params={'wait': 'true'},
body={
"points": [
{
"id": 1,
"vector": {
"my-multivec": [
[0.05, 0.61, 0.76, 0.74],
[0.05, 0.61, 0.76]
]
}
}
]
}
)
assert not response.ok
assert 'Validation error in JSON body: [points[0].vector.?.data: all vectors must have the same dimension, found vector with dimension 3' in \
response.json()["status"]["error"]
# allow multivec upsert on legacy API by emulating a multivec input with a single dense vector
def test_upsert_legacy_api(collection_name):
response = request_with_validation(
api='/collections/{collection_name}/points',
method="PUT",
path_params={'collection_name': collection_name},
query_params={'wait': 'true'},
body={
"points": [
{
"id": 1,
"vector": {
"my-multivec": [
[0.05, 0.61, 0.76, 0.74],
[0.05, 0.61, 0.76, 0.74],
[0.05, 0.61, 0.76, 0.74]
]
}
},
{
"id": 2,
"vector": {
"my-multivec": [0.19, 0.81, 0.75, 0.11]
}
},
]
}
)
assert response.ok
# retrieve by id 1
response = request_with_validation(
api='/collections/{collection_name}/points/{id}',
method="GET",
path_params={'collection_name': collection_name, 'id': 1},
)
assert response.ok
point = response.json()['result']
assert point['id'] == 1
assert point['vector']['my-multivec'] == [[0.05, 0.61, 0.76, 0.74], [0.05, 0.61, 0.76, 0.74], [0.05, 0.61, 0.76, 0.74]]
# retrieve by id 2
response = request_with_validation(
api='/collections/{collection_name}/points/{id}',
method="GET",
path_params={'collection_name': collection_name, 'id': 2},
)
assert response.ok
point = response.json()['result']
assert point['id'] == 2
assert point['vector']['my-multivec'] == [[0.19, 0.81, 0.75, 0.11]]
# allow multivec search on legacy API by emulating a multivec input with a single dense vector
def test_search_legacy_api(collection_name):
# validate input size
response = request_with_validation(
api='/collections/{collection_name}/points/search',
method="POST",
path_params={'collection_name': collection_name},
body={
"vector": {
"name": "my-multivec",
"vector": [0.05, 0.61, 0.76]
},
"limit": 3
}
)
assert not response.ok
assert 'Wrong input: Vector dimension error: expected dim: 4, got 3' in \
response.json()["status"]["error"]
# search on empty collection
response = request_with_validation(
api='/collections/{collection_name}/points/search',
method="POST",
path_params={'collection_name': collection_name},
body={
"vector": {
"name": "my-multivec",
"vector": [0.05, 0.61, 0.76, 0.74]
},
"limit": 3
}
)
assert response.ok
assert len(response.json()['result']) == 0
response = request_with_validation(
api='/collections/{collection_name}/points',
method="PUT",
path_params={'collection_name': collection_name},
query_params={'wait': 'true'},
body={
"points": [
{
"id": 1,
"vector": {
"my-multivec": [
[0.05, 0.61, 0.76, 0.74],
[0.05, 0.61, 0.76, 0.74],
[0.05, 0.61, 0.76, 0.74]
]
}
},
{
"id": 2,
"vector": {
"my-multivec": [
[0.19, 0.81, 0.75, 0.11],
[0.19, 0.81, 0.75, 0.11],
[0.19, 0.81, 0.75, 0.11]
]
}
},
{
"id": 3,
"vector": {
"my-multivec": [
[0.36, 0.55, 0.47, 0.94],
[0.36, 0.55, 0.47, 0.94],
[0.36, 0.55, 0.47, 0.94]
]
}
},
]
}
)
assert response.ok
response = request_with_validation(
api='/collections/{collection_name}/points/search',
method="POST",
path_params={'collection_name': collection_name},
body={
"vector": {
"name": "my-multivec",
"vector": [0.05, 0.61, 0.76, 0.74]
},
"limit": 3
}
)
assert response.ok
assert len(response.json()['result']) == 3