# coding=utf-8
# --------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for license information.
# Code generated by Microsoft (R) AutoRest Code Generator.
# Changes may cause incorrect behavior and will be lost if the code is regenerated.
# --------------------------------------------------------------------------
from enum import Enum, EnumMeta
from six import with_metaclass
class _CaseInsensitiveEnumMeta(EnumMeta):
def __getitem__(self, name):
return super().__getitem__(name.upper())
def __getattr__(cls, name):
"""Return the enum member matching `name`
We use __getattr__ instead of descriptors or inserting into the enum
class' __dict__ in order to support `name` and `value` being both
properties for enum members (which live in the class' __dict__) and
enum members themselves.
"""
try:
return cls._member_map_[name.upper()]
except KeyError:
raise AttributeError(name)
[docs]class Answers(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""This parameter is only valid if the query type is 'semantic'. If set, the query returns answers
extracted from key passages in the highest ranked documents. The number of answers returned can
be configured by appending the pipe character '|' followed by the 'count-:code:`<number of
answers>`' option after the answers parameter value, such as 'extractive|count-3'. Default
count is 1.
"""
#: Do not return answers for the query.
NONE = "none"
#: Extracts answer candidates from the contents of the documents returned in response to a query
#: expressed as a question in natural language.
EXTRACTIVE = "extractive"
[docs]class AutocompleteMode(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""Specifies the mode for Autocomplete. The default is 'oneTerm'. Use 'twoTerms' to get shingles
and 'oneTermWithContext' to use the current context in producing autocomplete terms.
"""
#: Only one term is suggested. If the query has two terms, only the last term is completed. For
#: example, if the input is 'washington medic', the suggested terms could include 'medicaid',
#: 'medicare', and 'medicine'.
ONE_TERM = "oneTerm"
#: Matching two-term phrases in the index will be suggested. For example, if the input is 'medic',
#: the suggested terms could include 'medicare coverage' and 'medical assistant'.
TWO_TERMS = "twoTerms"
#: Completes the last term in a query with two or more terms, where the last two terms are a
#: phrase that exists in the index. For example, if the input is 'washington medic', the suggested
#: terms could include 'washington medicaid' and 'washington medical'.
ONE_TERM_WITH_CONTEXT = "oneTermWithContext"
class Captions(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""This parameter is only valid if the query type is 'semantic'. If set, the query returns
captions extracted from key passages in the highest ranked documents. When Captions is set to
'extractive', highlighting is enabled by default, and can be configured by appending the pipe
character '|' followed by the 'highlight-<true/false>' option, such as
'extractive|highlight-true'. Defaults to 'None'.
"""
#: Do not return captions for the query.
NONE = "none"
#: Extracts captions from the matching documents that contain passages relevant to the search
#: query.
EXTRACTIVE = "extractive"
class IndexActionType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""The operation to perform on a document in an indexing batch.
"""
#: Inserts the document into the index if it is new and updates it if it exists. All fields are
#: replaced in the update case.
UPLOAD = "upload"
#: Merges the specified field values with an existing document. If the document does not exist,
#: the merge will fail. Any field you specify in a merge will replace the existing field in the
#: document. This also applies to collections of primitive and complex types.
MERGE = "merge"
#: Behaves like merge if a document with the given key already exists in the index. If the
#: document does not exist, it behaves like upload with a new document.
MERGE_OR_UPLOAD = "mergeOrUpload"
#: Removes the specified document from the index. Any field you specify in a delete operation
#: other than the key field will be ignored. If you want to remove an individual field from a
#: document, use merge instead and set the field explicitly to null.
DELETE = "delete"
[docs]class QueryLanguage(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""The language of the query.
"""
#: Query language not specified.
NONE = "none"
#: English.
EN_US = "en-us"
[docs]class QueryType(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""Specifies the syntax of the search query. The default is 'simple'. Use 'full' if your query
uses the Lucene query syntax and 'semantic' if query syntax is not needed.
"""
#: Uses the simple query syntax for searches. Search text is interpreted using a simple query
#: language that allows for symbols such as +, * and "". Queries are evaluated across all
#: searchable fields by default, unless the searchFields parameter is specified.
SIMPLE = "simple"
#: Uses the full Lucene query syntax for searches. Search text is interpreted using the Lucene
#: query language which allows field-specific and weighted searches, as well as other advanced
#: features.
FULL = "full"
#: Best suited for queries expressed in natural language as opposed to keywords. Improves
#: precision of search results by re-ranking the top search results using a ranking model trained
#: on the Web corpus.
SEMANTIC = "semantic"
class ScoringStatistics(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""A value that specifies whether we want to calculate scoring statistics (such as document
frequency) globally for more consistent scoring, or locally, for lower latency. The default is
'local'. Use 'global' to aggregate scoring statistics globally before scoring. Using global
scoring statistics can increase latency of search queries.
"""
#: The scoring statistics will be calculated locally for lower latency.
LOCAL = "local"
#: The scoring statistics will be calculated globally for more consistent scoring.
GLOBAL_ENUM = "global"
[docs]class SearchMode(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""Specifies whether any or all of the search terms must be matched in order to count the document
as a match.
"""
#: Any of the search terms must be matched in order to count the document as a match.
ANY = "any"
#: All of the search terms must be matched in order to count the document as a match.
ALL = "all"
[docs]class Speller(with_metaclass(_CaseInsensitiveEnumMeta, str, Enum)):
"""Improve search recall by spell-correcting individual search query terms.
"""
#: Speller not enabled.
NONE = "none"
#: Speller corrects individual query terms using a static lexicon for the language specified by
#: the queryLanguage parameter.
LEXICON = "lexicon"