U uie*@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@seZdZdZdZdZdS)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[/home/lhs5088/backend/venv/lib/python3.8/site-packages/sqlalchemy/dialects/oracle/vector.pyr sr c@s eZdZdZdZdZdZdZdS)VectorDistanceTypezEnum representing different types of vector distance metrics. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 EUCLIDEANDOTCOSINE MANHATTANN)r rrrrrrrrrrrr)s rc@s eZdZdZdZdZdZdZdS)VectorStorageFormatzEnum representing the data format used to store vector components. See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.41 INT8BINARYFLOAT32FLOAT64N)r rrrrrrrrrrrrHs rc@seZdZdZdZdZdS)VectorStorageTypez}Enum representing the vector type, See :ref:`oracle_vector_datatype` for background. .. versionadded:: 2.0.43 SPARSEDENSEN)r rrrrrrrrrrcsrc@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: integer. 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: integer. 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]8}t||}|dk rt|tst|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 rrrr r r!__annotations__r"r#r$r%r&r'r(r)r2rrrrr xs 2        r c@s*eZdZdZddddddZddZd S) SparseVectorz Lightweight SQLAlchemy-side version of SparseVector. This mimics oracledb.SparseVector. .. versionadded:: 2.0.43 r,zUnion[list, array.array]num_dimensionsindicesvaluescCsht|tjr|jdkr"td|}t|tjs:td|}t|t|krRtd||_||_||_dS)NIdz.indices and values must be of the same length!)r+arraytypecodelenr-r6r7r8)r/r6r7r8rrr__init__s   zSparseVector.__init__cCs$d|jdt|jd|jjdS)NzSparseVector(num_dimensions=z, size=z , typecode=))r6r=r7r8r<)r/rrr__str__s"zSparseVector.__str__N)r rrrr>r@rrrrr4sr4c@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|dk rt|tstd|dk r4t|ts4td|dk rNt|tsNtd||_||_||_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 integerz: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. csj|dkst|tjr|St|tr>j}t||}|St|tr^j|j|j|j St ddS)Nz Invalid input for VECTOR: expected a list, an array.array, or a SparseVector object. ) r+r;list_array_typecoderFr4dbapir6r7r8r-)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|dkr dSt|tjr t|St|jjrBt|j|j|jdSdS)Nr5)r+r;rHrJr4r6r7r8)r1rLrrrMNs z0VECTOR._cached_result_processor..processr)r/rLZcoltyperMrrOr_cached_result_processorEs 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_factorycCs|jdtd|S)Nz<-> return_typeopr r/otherrrr l2_distancefsz%VECTOR.comparator_factory.l2_distancecCs|jdtd|S)Nz<#>rSrUrWrrr inner_productisz'VECTOR.comparator_factory.inner_productcCs|jdtd|S)Nz<=>rSrUrWrrrcosine_distancelsz)VECTOR.comparator_factory.cosine_distanceN)r rrrYrZr[rrrrcomparator_factoryesr\)NNN)r rrrZcache_okZ__visit_name__rrrrrrQr>rNrPrIr TypeEngineZ Comparatorr\rrrrrAs"  ##rA) __future__rr; dataclassesrenumrtypingrrrr r rrrr r4r]rArrrr s       P!