o -hz*@sddlmZddlZddlmZddlmZddlmZddlm Z ddl m Z ddl m Z Gdd d eZ Gd d d eZGd d d eZGdddeZeGdddZGdddZGddde jZdS)) annotationsN) dataclass)Enum)Optional)Union)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 rrc/var/www/html/pro-man-master/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)r r rrrrrrrrrrr)src@r)VectorStorageFormatzEnum representing the data format used to store vector components. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 INT8BINARYFLOAT32FLOAT64N)r r rrrrrrrrrrrHsrc@r)VectorStorageTypez}Enum representing the vector type, See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.43 SPARSEDENSEN)r r rrrrrrrrrcs 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__)r r rrr r r!__annotations__r"r#r$r%r&r'r(r)r2rrrrr xs 2         r c@s"eZdZdZd ddZd d Zd S) SparseVectorz Lightweight SQLAlchemy-side version of SparseVector. This mimics oracledb.SparseVector. .. versionadded:: 2.0.43 num_dimensionsr,indicesUnion[list, array.array]valuescCsht|tjr |jdkrtd|}t|tjstd|}t|t|kr)td||_||_||_dS)NIdz.indices and values must be of the same length!)r+arraytypecodelenr-r5r6r8)r/r5r6r8rrr__init__s    zSparseVector.__init__cCs$d|jdt|jd|jjdS)NzSparseVector(num_dimensions=z, size=z , typecode=))r5r=r6r8r<)r/rrr__str__s zSparseVector.__str__N)r5r,r6r7r8r7)r r rrr>r@rrrrr4s  r4c@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)r/rErFrGrrrr>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_typecoderFr4dbapir5r6r8r-)r1r<dialectr/rrprocess(s    z.VECTOR._cached_bind_processor..processr)r/rLrMrrKr_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)r5r6r8)r+r;rHrJr4r5r6r8)r1rLrrrMMs z0VECTOR._cached_result_processor..processr)r/rLcoltyperMrrOr_cached_result_processorDs zVECTOR._cached_result_processorcCs|j|dS)z7 Map storage format to array typecode. r:) _typecode_mapget)r/r<rrrrI^szVECTOR._array_typecodec@s$eZdZddZddZddZdS)zVECTOR.comparator_factorycC|jdtd|S)Nz<-> return_typeoprr/otherrrr l2_distanceez%VECTOR.comparator_factory.l2_distancecCrT)Nz<#>rUrWrYrrr inner_producthr\z'VECTOR.comparator_factory.inner_productcCrT)Nz<=>rUrWrYrrrcosine_distancekr\z)VECTOR.comparator_factory.cosine_distanceN)r r rr[r]r^rrrrcomparator_factoryds r_)NNN)r r rrcache_ok__visit_name__rrrrrrRr>rNrQrItypes TypeEngine Comparatorr_rrrrrAs  ##rA) __future__rr; dataclassesrenumrtypingrrsqlalchemy.typesrbrr rrrr r4rcrArrrrs       P!