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https://github.com/qdrant/qdrant.git
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1bf968bd10
* Refactor `PyUpdateOperation` constructors * Add default parameters to `PyVectorDataConfig::new` * Add `Repr` trait and `WriteExt` helper * Implement `__repr__` for config types * fixup! Implement `__repr__` for config types Use `Copy` instead of `Clone` * fixup! Implement `__repr__` for config types Add basic test * Implement `__repr__` for `PyPointId` * Implement `__repr__` for `PyVector` * Implement `__repr__` for `PyVectorInternal` * Implement `__repr__` for `PyPayload` * Implement `__repr__` for `PyValue` * Implement `__repr__` for `PyPoint` * Implement `__repr__` for `PyPointVectors` * Implement `__repr__` for `PyRecord` * Move `PyScoredPoint` into a separate file * Implement `__repr__` for `PyScoredPoint` * Cleanup examples * fixup! Implement `__repr__` for `PyScoredPoint` * Move `PyOrderValue` into separate file * Add `PyScoredPoint::order_value` * Implement `pyclass_repr` proc-macro attribute * Implement `__repr__` for config types using `pyclass_repr` attribute * Implement `__repr__` for `PySparseVector` using `pyclass_repr` attribute * Implement `__repr__` for `PyPoint` using `pyclass_repr` attribute * Implement `__repr__` for `PyPointVectors` using `pyclass_repr` attribute * Implement `__repr__` for `PyRecord` using `pyclass_repr` attribute * Implement `__repr__` for `PyScoredPoint` using `pyclass_repr` attribute * Minor fixes and cleanups * fixup! Minor fixes and cleanups * rollback copy for quantization config * rollback copy for quantization config --------- Co-authored-by: generall <andrey@vasnetsov.com>
48 lines
963 B
Python
48 lines
963 B
Python
from qdrant_edge import *
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from common import *
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shard = load_new_shard()
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fill_dummy_data(shard)
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search_filter = Filter(
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must=[
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FieldCondition(
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key="color",
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match=MatchValue(value="red"),
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)
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]
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)
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result = shard.query(QueryRequest(
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prefetches = [
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Prefetch(
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prefetches=[],
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query=Query.Nearest([6.0, 9.0, 4.0, 2.0]),
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limit=5,
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params=None,
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filter=None,
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score_threshold=None,
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),
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Prefetch(
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prefetches=[],
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query=Query.Nearest([1.0, -3.0, 2.0, 8.0]),
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limit=5,
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params=None,
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filter=search_filter,
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score_threshold=None,
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)
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],
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query = Fusion.rrfk(2),
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filter = None,
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score_threshold = None,
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limit = 10,
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offset = 0,
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params = None,
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with_vector = True,
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with_payload = True,
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))
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for point in result:
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print(point)
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