mirror of
https://github.com/qdrant/qdrant-client.git
synced 2026-07-28 13:41:11 -05:00
b9a7a15cee
* Enable testing on windows and macos * Add platform to the name * Add Docker on MacOS * Temporarily disable tests on Windows * Explicitly set ports to be opened * Add problematic case for MacOS * Increase the timeout in tests
52 lines
1.6 KiB
Python
52 lines
1.6 KiB
Python
import pytest
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from qdrant_client import QdrantClient, models
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@pytest.fixture
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def qdrant() -> QdrantClient:
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return QdrantClient(":memory:")
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def test_in_memory_key_filter_returns_results(qdrant: QdrantClient):
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qdrant.recreate_collection(
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collection_name="test_collection",
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vectors_config=models.VectorParams(size=4, distance=models.Distance.DOT),
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)
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operation_info = qdrant.upsert(
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collection_name="test_collection",
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wait=True,
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points=[
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models.PointStruct(id=1, vector=[0.05, 0.61, 0.76, 0.74],
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payload={"city": "Berlin"}),
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models.PointStruct(
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id=2,
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vector=[0.19, 0.81, 0.75, 0.11],
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payload={"city": ["Berlin", "London"]},
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),
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models.PointStruct(
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id=3,
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vector=[0.36, 0.55, 0.47, 0.94],
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payload={"city": ["Berlin", "Moscow"]},
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),
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models.PointStruct(
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id=4,
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vector=[0.18, 0.01, 0.85, 0.80],
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payload={"city": ["London", "Moscow"]},
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),
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models.PointStruct(id=5, vector=[0.24, 0.18, 0.22, 0.44], payload={"count": [0]}),
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models.PointStruct(id=6, vector=[0.35, 0.08, 0.11, 0.44]),
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],
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)
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search_result = qdrant.search(
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collection_name = "test_collection",
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query_vector = [0.2, 0.1, 0.9, 0.7],
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query_filter = models.Filter(
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must=[models.FieldCondition(key="city", match=models.MatchValue(value="London"))]
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),
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limit=3,
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)
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assert search_result is not None
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