algorithm_configurations=[
                VectorSearchAlgorithmConfiguration(
                    name="default",
                    kind="hnsw",
                    hnsw_parameters={
                        "m": 4,
                        "efConstruction": 400,
                        "efSearch": 500,
                        "metric": "cosine",
                    },
                )
            ]
        )
        # Create the semantic settings with the configuration
        semantic_settings = (
            None
            if semantic_configuration_name is None
            else 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,
        )
        index_client.create_index(index)
    # Create the search client
    return SearchClient(endpoint=endpoint, index_name=index_name, credential=credential)
[docs]class AzureSearch(VectorStore):
    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",
        **kwargs: Any,
    ):
        """Initialize with necessary components."""
        # Initialize base class
        self.embedding_function = embedding_function
        self.client = _get_search_client(
            azure_search_endpoint,
            azure_search_key,
rtdocs_stable/api.python.langchain.com/en/stable/_modules/langchain/vectorstores/azuresearch.html