Search index types
- class yandex_cloud_ml_sdk._search_indexes.file.SearchIndexFile
- class yandex_cloud_ml_sdk._search_indexes.index_type.BaseSearchIndexType
- class yandex_cloud_ml_sdk._search_indexes.index_type.TextSearchIndexType
- class yandex_cloud_ml_sdk._search_indexes.index_type.VectorSearchIndexType
- class yandex_cloud_ml_sdk._search_indexes.index_type.HybridSearchIndexType
- class yandex_cloud_ml_sdk._search_indexes.chunking_strategy.BaseIndexChunkingStrategy
- class yandex_cloud_ml_sdk._search_indexes.chunking_strategy.StaticIndexChunkingStrategy
- class yandex_cloud_ml_sdk._search_indexes.combination_strategy.BaseIndexCombinationStrategy
- class yandex_cloud_ml_sdk._search_indexes.combination_strategy.MeanIndexEvaluationTechnique
- class yandex_cloud_ml_sdk._search_indexes.combination_strategy.MeanIndexCombinationStrategy
- class yandex_cloud_ml_sdk._search_indexes.combination_strategy.ReciprocalRankFusionIndexCombinationStrategy
- class yandex_cloud_ml_sdk._search_indexes.normalization_strategy.IndexNormalizationStrategy
class yandex_cloud_ml_sdk._search_indexes.file.SearchIndexFile
This class represents a file associated with a search index.
search_index_id: str
the unique identifier for the search index
created_by: str
the identifier of the user or system that created the file
created_at: datetime
the timestamp when the file was created
id: str
class yandex_cloud_ml_sdk._search_indexes.index_type.BaseSearchIndexType
A class for search index types.
chunking_strategy: BaseIndexChunkingStrategy | None
the strategy used for chunking the index
class yandex_cloud_ml_sdk._search_indexes.index_type.TextSearchIndexType
A class which represents a text search index type.
chunking_strategy: BaseIndexChunkingStrategy | None
the strategy used for chunking the index
class yandex_cloud_ml_sdk._search_indexes.index_type.VectorSearchIndexType
A class which represents a vector search index type.
doc_embedder_uri: str
URI for the document embedder
query_embedder_uri: str
URI for the query embedder
chunking_strategy: BaseIndexChunkingStrategy | None
the strategy used for chunking the index
class yandex_cloud_ml_sdk._search_indexes.index_type.HybridSearchIndexType
A class which represents a hybrid search index type combining text and vector search indices.
text_search_index: TextSearchIndexType | None
the text search index associated with the hybrid index
vector_search_index: VectorSearchIndexType | None
the vector search index associated with the hybrid index
normalization_strategy: IndexNormalizationStrategy | str
the strategy for normalizing index results
combination_strategy: BaseIndexCombinationStrategy | None
the strategy for combining results from different indices
chunking_strategy: BaseIndexChunkingStrategy | None
the strategy used for chunking the index
class yandex_cloud_ml_sdk._search_indexes.chunking_strategy.BaseIndexChunkingStrategy
A class for an index chunking strategy, from which all other strategies are inherited.
class yandex_cloud_ml_sdk._search_indexes.chunking_strategy.StaticIndexChunkingStrategy
This class implements a static chunking strategy (i.e. a specific strategy with specific properties).
It is characterized by maximum chunk size and overlap in tokens.
max_chunk_size_tokens: int
the maximum size of each chunk in tokens
chunk_overlap_tokens: int
the number of overlapping tokens between consecutive chunks
class yandex_cloud_ml_sdk._search_indexes.combination_strategy.BaseIndexCombinationStrategy
A class for index combination strategies.
class yandex_cloud_ml_sdk._search_indexes.combination_strategy.MeanIndexEvaluationTechnique
A class with enumeration for mean index evaluation techniques.
MEAN_EVALUATION_TECHNIQUE_UNSPECIFIED = 0
an unspecified mean evaluation technique
ARITHMETIC = 1
the arithmetic mean, calculated as the sum of values divided by the count of values
GEOMETRIC = 2
the geometric mean, calculated as the n-th root of the product of n values
HARMONIC = 3
the harmonic mean, calculated as the reciprocal of the arithmetic mean of the reciprocals of the values
__new__(value)
conjugate()
Returns self, the complex conjugate of any int.
bit_length()
Number of bits necessary to represent self in binary.
>>> bin(37)
'0b100101'
>>> (37).bit_length()
6
bit_count()
Number of ones in the binary representation of the absolute value of self.
Also known as the population count.
>>> bin(13)
'0b1101'
>>> (13).bit_count()
3
as_integer_ratio()
Return a pair of integers, whose ratio is equal to the original int.
The ratio is in lowest terms and has a positive denominator.
>>> (10).as_integer_ratio()
(10, 1)
>>> (-10).as_integer_ratio()
(-10, 1)
>>> (0).as_integer_ratio()
(0, 1)
is_integer()
Returns True. Exists for duck type compatibility with float.is_integer.
real
the real part of a complex number
imag
the imaginary part of a complex number
numerator
the numerator of a rational number in lowest terms
denominator
the denominator of a rational number in lowest terms
__init__(*args, **kwds)
class yandex_cloud_ml_sdk._search_indexes.combination_strategy.MeanIndexCombinationStrategy
A class which contains mean index combination strategy with evaluation technique and weights.
mean_evaluation_technique: MeanIndexEvaluationTechnique | None
the technique used for mean evaluation
weights: Collection
the weights associated with the evaluation technique
__init__(mean_evaluation_technique, weights)
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Parameters |
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Return type |
None |
class yandex_cloud_ml_sdk._search_indexes.combination_strategy.ReciprocalRankFusionIndexCombinationStrategy
A class which describes reciprocal rank fusion index combination strategy. Reciprocal rank fusion is a method for combining multiple result sets with different relevance indicators into a single result set.
the parameter k for RRFscore. Default is 60.
__init__(k=None)
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Parameters |
k (int |
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Return type |
None |
class yandex_cloud_ml_sdk._search_indexes.normalization_strategy.IndexNormalizationStrategy
Enumeration for index normalization strategies.
This class defines the various normalization strategies that can be applied to an index.
NORMALIZATION_STRATEGY_UNSPECIFIED = 0
indicates that no normalization strategy has been specified
MIN_MAX = 1
represents the Min-Max normalization strategy
L2 = 2
represents the L2 normalization strategy
__new__(value)
conjugate()
Returns self, the complex conjugate of any int.
bit_length()
Number of bits necessary to represent self in binary.
>>> bin(37)
'0b100101'
>>> (37).bit_length()
6
bit_count()
Number of ones in the binary representation of the absolute value of self.
Also known as the population count.
>>> bin(13)
'0b1101'
>>> (13).bit_count()
3
as_integer_ratio()
Return a pair of integers, whose ratio is equal to the original int.
The ratio is in lowest terms and has a positive denominator.
>>> (10).as_integer_ratio()
(10, 1)
>>> (-10).as_integer_ratio()
(-10, 1)
>>> (0).as_integer_ratio()
(0, 1)
is_integer()
Returns True. Exists for duck type compatibility with float.is_integer.
real
the real part of a complex number
imag
the imaginary part of a complex number
numerator
the numerator of a rational number in lowest terms
denominator
the denominator of a rational number in lowest terms
__init__(*args, **kwds)