# PrioritizedFields(prioritized_content_fields)
                #   --> SemanticPrioritizedFields(content_fields)
                semantic_settings = SemanticSearch(
                    configurations=[
                        SemanticConfiguration(
                            name=semantic_configuration_name,
                            prioritized_fields=SemanticPrioritizedFields(
                                content_fields=[
                                    SemanticField(field_name=FIELDS_CONTENT)
                                ],
                            ),
                        )
                    ]
                )
            else:  # < 11.4.0
                semantic_settings = SemanticSettings(
                    configurations=[
                        SemanticConfiguration(
                            name=semantic_configuration_name,
                            prioritized_fields=PrioritizedFields(
                                prioritized_content_fields=[
                                    SemanticField(field_name=FIELDS_CONTENT)
                                ],
                            ),
                        )
                    ]
                )
        # Create the search index with the semantic settings and vector search
        index = SearchIndex(
            name=index_name,
            fields=fields,
            vector_search=vector_search,
            semantic_settings=semantic_settings,
            scoring_profiles=scoring_profiles,
            default_scoring_profile=default_scoring_profile,
            cors_options=cors_options,
        )
        index_client.create_index(index)
    # Create the search client
    return SearchClient(
        endpoint=endpoint,
        index_name=index_name,
        credential=credential,
        user_agent=user_agent,
    )
[docs]class AzureSearch(VectorStore):
    """`Azure Cognitive Search` vector store."""
[docs]    def __init__(
        self,
        azure_search_endpoint: str,
        azure_search_key: str,
        index_name: str,
        embedding_function: Callable,
        search_type: str = "hybrid",
        semantic_configuration_name: Optional[str] = None,
        semantic_query_language: str = "en-us",