o V\ih*@sddlmZddlZddlmZddlmZddlmZddlm Z ddl m Z dd l m Z Gd d d eZ Gd d d eZGdddeZGdddeZeGdddZGdddZGddde jZdS)) annotationsN) dataclass)Enum)Optional)Union)types)Floatc@eZdZdZdZ dZdS)VectorIndexTypezEnum representing different types of VECTOR index structures. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 HNSWIVFN)__name__ __module__ __qualname____doc__r r rr/var/www/www-root/data/www/176.119.141.140/sports-predictor/venv/lib/python3.10/site-packages/sqlalchemy/dialects/oracle/vector.pyr s r c@&eZdZdZdZ dZ dZ dZdS)VectorDistanceTypezEnum representing different types of vector distance metrics. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 EUCLIDEANDOTCOSINE MANHATTANN)rrrrrrrrrrrrr)src@r)VectorStorageFormatzEnum representing the data format used to store vector components. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 INT8BINARYFLOAT32FLOAT64N)rrrrrrrrrrrrrHsrc@r )VectorStorageTypez}Enum representing the vector type, See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.43 SPARSEDENSEN)rrrrr r!rrrrrcs rc@seZdZUdZejZded<dZded<dZ ded<dZ ded <dZ ded <dZ ded <dZ ded <dZded <dZded<ddZdS)VectorIndexConfigaDefine 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_partitionparallelcCsNt|j|_dD]}t||}|dur$t|ts$t|dt|jqdS)N)r&r'r(r)r*r+r%z$ must be an integer ifprovided, got )r r#getattr isinstanceint TypeErrortyper)selffieldvaluerrr __post_init__s  zVectorIndexConfig.__post_init__)rrrrr r r#__annotations__r$r%r&r'r(r)r*r+r4rrrrr"xs 2         r"c@s"eZdZdZd ddZd d Zd S) SparseVectorz Lightweight SQLAlchemy-side version of SparseVector. This mimics oracledb.SparseVector. .. versionadded:: 2.0.43 num_dimensionsr.indicesUnion[list, array.array]valuescCsht|tjr |jdkrtd|}t|tjstd|}t|t|kr)td||_||_||_dS)NIdz.indices and values must be of the same length!)r-arraytypecodelenr/r7r8r:)r1r7r8r:rrr__init__s    zSparseVector.__init__cCs$d|jdt|jd|jjdS)NzSparseVector(num_dimensions=z, size=z , typecode=))r7r?r8r:r>)r1rrr__str__s zSparseVector.__str__N)r7r.r8r9r:r9)rrrrr@rBrrrrr6s  r6c@sjeZdZdZdZdZejdejdej dej diZ ddd Z d d Z d d ZddZGdddejjZdS)VECTORzOracle VECTOR datatype. For complete background on using this type, see :ref:`oracle_vector_datatype`. .. versionadded:: 2.0.41 TbBfr<NcCsd|dur t|ts td|durt|tstd|dur't|ts'td||_||_||_dS)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)r-r.r/rrdimstorage_format storage_type)r1rGrHrIrrrr@s"   zVECTOR.__init__csfdd}|S)z Converts a Python-side SparseVector instance into an oracledb.SparseVectormor a compatible array format before binding it to the database. csf|dus t|tjr |St|trj}t||}|St|tr/j|j|j|j St d)Nz Invalid input for VECTOR: expected a list, an array.array, or a SparseVector object. ) r-r=list_array_typecoderHr6dbapir7r8r:r/)r3r>dialectr1rrprocess)s    z.VECTOR._cached_bind_processor..processr)r1rNrOrrMr_cached_bind_processor"szVECTOR._cached_bind_processorcsfdd}|S)a 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. csF|durdSt|tjrt|St|jjr!t|j|j|jdSdS)N)r7r8r:)r-r=rJrLr6r7r8r:)r3rNrrrONs z0VECTOR._cached_result_processor..processr)r1rNcoltyperOrrQr_cached_result_processorEs zVECTOR._cached_result_processorcCs|j|dS)z7 Map storage format to array typecode. r<) _typecode_mapget)r1r>rrrrK_szVECTOR._array_typecodec@s$eZdZddZddZddZdS)zVECTOR.comparator_factorycC|jdtd|S)Nz<-> return_typeopr r1otherrrr l2_distancefz%VECTOR.comparator_factory.l2_distancecCrV)Nz<#>rWrYr[rrr inner_productir^z'VECTOR.comparator_factory.inner_productcCrV)Nz<=>rWrYr[rrrcosine_distancelr^z)VECTOR.comparator_factory.cosine_distanceN)rrrr]r_r`rrrrcomparator_factoryes ra)NNN)rrrrcache_ok__visit_name__rrrrrrTr@rPrSrKr TypeEngine ComparatorrarrrrrCs  ##rC) __future__rr= dataclassesrenumrtypingrrrr r rrrr"r6rdrCrrrrs       P!