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Update azuresearch.py following recent change from azure-search-documents library (#13472)
- **Description:** Reference library azure-search-documents has been adapted in version 11.4.0: 1. Notebook explaining Azure AI Search updated with most recent info 2. HnswVectorSearchAlgorithmConfiguration --> HnswAlgorithmConfiguration 3. PrioritizedFields(prioritized_content_fields) --> SemanticPrioritizedFields(content_fields) 4. SemanticSettings --> SemanticSearch 5. VectorSearch(algorithm_configurations) --> VectorSearch(configurations) --> Changes now reflected on Langchain: default vector search config from langchain is now compatible with officially released library from Azure. - **Issue:** Issue creating a new index (due to wrong class used for default vector search configuration) if using latest version of azure-search-documents with current langchain version - **Dependencies:** azure-search-documents>=11.4.0, - **Tag maintainer:** , --------- Co-authored-by: Erick Friis <erick@langchain.dev>
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guillaumedelande
GitHub
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5cb3393e20
commit
ea0afd07ca
@ -6,18 +6,17 @@
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"collapsed": false
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},
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"source": [
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"# Azure Cognitive Search\n",
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"# Azure AI Search\n",
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"\n",
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"[Azure Cognitive Search](https://learn.microsoft.com/azure/search/search-what-is-azure-search) (formerly known as `Azure Search`) is a cloud search service that gives developers infrastructure, APIs, and tools for building a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications.\n",
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"\n",
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"Vector search is currently in public preview. It's available through the Azure portal, preview REST API and beta client libraries. [More info](https://learn.microsoft.com/en-us/azure/search/vector-search-overview) Beta client libraries are subject to potential breaking changes, please be sure to use the SDK package version identified below. azure-search-documents==11.4.0b8"
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"[Azure AI Search](https://learn.microsoft.com/azure/search/search-what-is-azure-search) (formerly known as `Azure Search` and `Azure Cognitive Search`) is a cloud search service that gives developers infrastructure, APIs, and tools for building a rich search experience over private, heterogeneous content in web, mobile, and enterprise applications.\n",
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"\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# Install Azure Cognitive Search SDK"
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"# Install Azure AI Search SDK"
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]
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},
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{
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@ -26,7 +25,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install azure-search-documents==11.4.0b8\n",
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"!pip install azure-search-documents\n",
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"!pip install azure-identity"
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]
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},
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@ -14,6 +14,7 @@ from typing import (
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Optional,
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Tuple,
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Type,
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Union,
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)
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import numpy as np
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@ -36,10 +37,13 @@ if TYPE_CHECKING:
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from azure.search.documents.indexes.models import (
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ScoringProfile,
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SearchField,
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SemanticSettings,
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VectorSearch,
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)
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try:
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from azure.search.documents.indexes.models import SemanticSearch
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except ImportError:
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from azure.search.documents.indexes.models import SemanticSettings # <11.4.0
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# Allow overriding field names for Azure Search
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FIELDS_ID = get_from_env(
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@ -69,7 +73,7 @@ def _get_search_client(
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semantic_configuration_name: Optional[str] = None,
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fields: Optional[List[SearchField]] = None,
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vector_search: Optional[VectorSearch] = None,
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semantic_settings: Optional[SemanticSettings] = None,
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semantic_settings: Optional[Union[SemanticSearch, SemanticSettings]] = None,
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scoring_profiles: Optional[List[ScoringProfile]] = None,
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default_scoring_profile: Optional[str] = None,
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default_fields: Optional[List[SearchField]] = None,
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@ -81,15 +85,30 @@ def _get_search_client(
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from azure.search.documents import SearchClient
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from azure.search.documents.indexes import SearchIndexClient
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from azure.search.documents.indexes.models import (
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HnswVectorSearchAlgorithmConfiguration,
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PrioritizedFields,
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SearchIndex,
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SemanticConfiguration,
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SemanticField,
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SemanticSettings,
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VectorSearch,
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)
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# class names changed for versions >= 11.4.0
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try:
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from azure.search.documents.indexes.models import (
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HnswAlgorithmConfiguration, # HnswVectorSearchAlgorithmConfiguration is old
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SemanticPrioritizedFields, # PrioritizedFields outdated
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SemanticSearch, # SemanticSettings outdated
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)
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NEW_VERSION = True
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except ImportError:
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from azure.search.documents.indexes.models import (
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HnswVectorSearchAlgorithmConfiguration,
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PrioritizedFields,
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SemanticSettings,
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)
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NEW_VERSION = False
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default_fields = default_fields or []
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if key is None:
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credential = DefaultAzureCredential()
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@ -135,34 +154,71 @@ def _get_search_client(
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fields = default_fields
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# Vector search configuration
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if vector_search is None:
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vector_search = VectorSearch(
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algorithm_configurations=[
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HnswVectorSearchAlgorithmConfiguration(
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name="default",
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kind="hnsw",
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parameters={ # type: ignore
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"m": 4,
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"efConstruction": 400,
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"efSearch": 500,
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"metric": "cosine",
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},
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)
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]
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)
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if NEW_VERSION:
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# >= 11.4.0:
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# VectorSearch(algorithm_configuration) --> VectorSearch(algorithms)
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# HnswVectorSearchAlgorithmConfiguration --> HnswAlgorithmConfiguration
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vector_search = VectorSearch(
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algorithms=[
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HnswAlgorithmConfiguration(
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name="default",
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kind="hnsw",
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parameters={ # type: ignore
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"m": 4,
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"efConstruction": 400,
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"efSearch": 500,
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"metric": "cosine",
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},
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)
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]
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)
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else: # < 11.4.0
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vector_search = VectorSearch(
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algorithm_configurations=[
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HnswVectorSearchAlgorithmConfiguration(
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name="default",
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kind="hnsw",
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parameters={ # type: ignore
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"m": 4,
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"efConstruction": 400,
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"efSearch": 500,
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"metric": "cosine",
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},
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)
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]
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)
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# Create the semantic settings with the configuration
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if semantic_settings is None and semantic_configuration_name is not None:
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semantic_settings = SemanticSettings(
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configurations=[
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SemanticConfiguration(
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name=semantic_configuration_name,
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prioritized_fields=PrioritizedFields(
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prioritized_content_fields=[
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SemanticField(field_name=FIELDS_CONTENT)
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],
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),
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)
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]
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)
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if NEW_VERSION:
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# <=11.4.0: SemanticSettings --> SemanticSearch
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# PrioritizedFields(prioritized_content_fields)
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# --> SemanticPrioritizedFields(content_fields)
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semantic_settings = SemanticSearch(
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configurations=[
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SemanticConfiguration(
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name=semantic_configuration_name,
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prioritized_fields=SemanticPrioritizedFields(
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content_fields=[
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SemanticField(field_name=FIELDS_CONTENT)
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],
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),
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)
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]
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)
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else: # < 11.4.0
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semantic_settings = SemanticSettings(
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configurations=[
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SemanticConfiguration(
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name=semantic_configuration_name,
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prioritized_fields=PrioritizedFields(
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prioritized_content_fields=[
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SemanticField(field_name=FIELDS_CONTENT)
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],
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),
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)
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]
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)
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# Create the search index with the semantic settings and vector search
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index = SearchIndex(
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name=index_name,
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@ -196,7 +252,7 @@ class AzureSearch(VectorStore):
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semantic_query_language: str = "en-us",
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fields: Optional[List[SearchField]] = None,
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vector_search: Optional[VectorSearch] = None,
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semantic_settings: Optional[SemanticSettings] = None,
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semantic_settings: Optional[Union[SemanticSearch, SemanticSettings]] = None,
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scoring_profiles: Optional[List[ScoringProfile]] = None,
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default_scoring_profile: Optional[str] = None,
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**kwargs: Any,
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