Bhz*SSKJr SSKrSSKJr SSKJr SSKJr SSKJ r SSK J r SSK J r "SS \5r "S S \5r"S S \5r"SS\5r\"SS55r"SS5r"SS\ R&5rg)) annotationsN) dataclass)Enum)Optional)Union)Floatc"\rSrSrSrSrSrSrg)VectorIndexTypezEnum representing different types of VECTOR index structures. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 HNSWIVFN)__name__ __module__ __qualname____firstlineno____doc__r r __static_attributes__rd/home/kali/devsecops-assessor/venv/lib/python3.13/site-packages/sqlalchemy/dialects/oracle/vector.pyr r s D Crr c.\rSrSrSrSrSrSrSrSr g) VectorDistanceType)zEnum representing different types of vector distance metrics. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 EUCLIDEANDOTCOSINE MANHATTANrN) rrrrrrrrrrrrrrr)s7I CFIrrc.\rSrSrSrSrSrSrSrSr g) VectorStorageFormatHzEnum representing the data format used to store vector components. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 INT8BINARYFLOAT32FLOAT64rN) rrrrrr!r"r#r$rrrrrrHs7 DFGGrrc"\rSrSrSrSrSrSrg)VectorStorageTypeczqEnum representing the vector type, See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.43 SPARSEDENSErN)rrrrrr(r)rrrrr&r&csF Err&c\rSrSr%Sr\R rS\S'Sr S\S'Sr S\S 'Sr S\S 'Sr S\S 'Sr S\S 'SrS\S 'SrS\S'SrS\S'SrSrg)VectorIndexConfigxa8Define the configuration for Oracle VECTOR Index. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 :param index_type: Enum value from :class:`.VectorIndexType` Specifies the indexing method. For HNSW, this must be :attr:`.VectorIndexType.HNSW`. :param distance: Enum value from :class:`.VectorDistanceType` specifies the metric for calculating distance between VECTORS. :param accuracy: interger. Should be in the range 0 to 100 Specifies the accuracy of the nearest neighbor search during query execution. :param parallel: integer. Specifies degree of parallelism. :param hnsw_neighbors: interger. Should be in the range 0 to 2048. Specifies the number of nearest neighbors considered during the search. The attribute :attr:`.VectorIndexConfig.hnsw_neighbors` is HNSW index specific. :param hnsw_efconstruction: integer. Should be in the range 0 to 65535. Controls the trade-off between indexing speed and recall quality during index construction. The attribute :attr:`.VectorIndexConfig.hnsw_efconstruction` is HNSW index specific. :param ivf_neighbor_partitions: integer. Should be in the range 0 to 10,000,000. Specifies the number of partitions used to divide the dataset. The attribute :attr:`.VectorIndexConfig.ivf_neighbor_partitions` is IVF index specific. :param ivf_sample_per_partition: integer. Should be between 1 and ``num_vectors / neighbor partitions``. Specifies the number of samples used per partition. The attribute :attr:`.VectorIndexConfig.ivf_sample_per_partition` is IVF index specific. :param ivf_min_vectors_per_partition: integer. From 0 (no trimming) to the total number of vectors (results in 1 partition). Specifies the minimum number of vectors per partition. The attribute :attr:`.VectorIndexConfig.ivf_min_vectors_per_partition` is IVF index specific. r index_typeNzOptional[VectorDistanceType]distancez Optional[int]accuracyhnsw_neighborshnsw_efconstructionivf_neighbor_partitionsivf_sample_per_partitionivf_min_vectors_per_partitionparallelc[UR5UlSHKn[X5nUcM[U[5(aM*[ US[ U5R35e g)N)r0r1r2r3r4r5r/z$ must be an integer ifprovided, got )r r-getattr isinstanceint TypeErrortyper)selffieldvalues r __post_init__VectorIndexConfig.__post_init__sh)$//: ED(E E3)?)?g%%)%[%9%9$:< r)r-)rrrrrr r r-__annotations__r.r/r0r1r2r3r4r5r?rrrrr+r+xst0d#2"6"6J6-1H*1"Hm"$(NM()---1]1.2m237!=7"Hm"rr+c4\rSrSrSrSSjrSrSrg) SparseVectorzt Lightweight SQLAlchemy-side version of SparseVector. This mimics oracledb.SparseVector. .. versionadded:: 2.0.43 cf[U[R5(aURS:wa[R"SU5n[U[R5(d[R"SU5n[U5[U5:wa [ S5eXlX lX0lg)NIdz.indices and values must be of the same length!)r8arraytypecodelenr:num_dimensionsindicesvalues)r<rKrLrMs r__init__SparseVector.__init__s '5;;//73C3Cs3Jkk#w/G&%++..[[f-F w<3v; &LM M,  rc|SURS[UR5SURRS3$)NzSparseVector(num_dimensions=z, size=z , typecode=))rKrJrLrMrI)r<s r__str__SparseVector.__str__sC*4+>+>*?@ %&k$++2F2F1Gq J r)rLrKrMN)rKr9rLUnion[list, array.array]rMrT)rrrrrrNrRrrrrrCrCs-*) " rrCc\rSrSrSrSrSr\RS\RS\RS\RS0r SS jr S rS rS r"S S\R$R&5rSrg)VECTORzOracle VECTOR datatype. For complete background on using this type, see :ref:`oracle_vector_datatype`. .. versionadded:: 2.0.41 TbBfrGNcUb [U[5(d [S5eUb [U[5(d [S5eUb [U[5(d [S5eXlX lX0lg)aConstruct a VECTOR. :param dim: integer. The dimension of the VECTOR datatype. This should be an integer value. :param storage_format: VectorStorageFormat. The VECTOR storage type format. This should be Enum values form :class:`.VectorStorageFormat` INT8, BINARY, FLOAT32, or FLOAT64. :param storage_type: VectorStorageType. The Vector storage type. This should be Enum values from :class:`.VectorStorageType` SPARSE or DENSE. Nzdim must be an intergerz:storage_format must be an enum of type VectorStorageFormatz6storage_type must be an enum of type VectorStorageType)r8r9r:rr&dimstorage_format storage_type)r<r\r]r^s rrNVECTOR.__init__s ?:c3#7#756 6  %j // / L   #J +- - H ,(rc^^UU4SjnU$)z Converts a Python-side SparseVector instance into an oracledb.SparseVectormor a compatible array format before binding it to the database. c>Ub[U[R5(aU$[U[5(a3TRTR5n[R"X5nU$[U[ 5(a;TR R URURUR5$[S5e)Nz Invalid input for VECTOR: expected a list, an array.array, or a SparseVector object. ) r8rHlist_array_typecoder]rCdbapirKrLrMr:)r>rIdialectr<s rprocess.VECTOR._cached_bind_processor..process(s} 5%++ > > E4((//0C0CD H4 E<00}}11((MMLL rr)r<rerfs`` r_cached_bind_processorVECTOR._cached_bind_processor!s 4rc^U4SjnU$)z Converts database-returned values into Python-native representations. If the value is an oracledb.SparseVector, it is converted into the SQLAlchemy-side SparseVector class. If the value is a array.array, it is converted to a plain Python list. c>Ucg[U[R5(a [U5$[UTRR5(a)[ UR UR URS9$g)N)rKrLrM)r8rHrbrdrCrKrLrM)r>res rrf0VECTOR._cached_result_processor..processMsh}E5;;//E{"E7==#=#=>>##(#7#7!MM <<?rr)r<recoltyperfs ` r_cached_result_processorVECTOR._cached_result_processorDs rc:URRUS5$)z' Map storage format to array typecode. rG) _typecode_mapget)r<rIs rrcVECTOR._array_typecode^s!!%%h44rc&\rSrSrSrSrSrSrg)VECTOR.comparator_factoryidc6URS[S9"U5$)Nz<-> return_typeoprr<others r l2_distance%VECTOR.comparator_factory.l2_distancee775e74U; ;rc6URS[S9"U5$)Nz<#>rwryr{s r inner_product'VECTOR.comparator_factory.inner_producthrrc6URS[S9"U5$)Nz<=>rwryr{s rcosine_distance)VECTOR.comparator_factory.cosine_distancekrrrN)rrrrr}rrrrrrcomparator_factoryruds < < rs# ! "d&>$6* MM M`  BB