Azure aisearch vector store issue with metadata fields mapping

# Define metadata fields mapping
metadata_fields = {
    "doc_id": ("doc_id", MetadataIndexFieldType.STRING),
    "page_num": ("page_num", MetadataIndexFieldType.INT64),
    "image_path": ("image_path", MetadataIndexFieldType.STRING),
    "parsed_text_markdown": ("parsed_text_markdown", MetadataIndexFieldType.STRING),
    "context": ("context", MetadataIndexFieldType.STRING),
}

# Initialize Azure AI Search vector store
vector_store = AzureAISearchVectorStore(
    search_or_index_client=index_client,
    index_name="llamaindex-multimodal-contextual-retreival",
    index_management=IndexManagement.CREATE_IF_NOT_EXISTS,
    id_field_key="id",
    chunk_field_key="parsed_text_markdown",  
    embedding_field_key="embedding",
    embedding_dimensionality=1536,  # Based on embedding model
    metadata_string_field_key="metadata",  # Stores all metadata as a JSON string
    doc_id_field_key="doc_id",
    filterable_metadata_field_keys=metadata_fields,
    language_analyzer="en.lucene",
    vector_algorithm_type="exhaustiveKnn",
)

# Create storage context
storage_context = StorageContext.from_defaults(vector_store=vector_store)

# Build the index
index = VectorStoreIndex.from_documents(
    new_text_nodes,
    storage_context=storage_context,
    llm=llm,
    embed_model=embed_model,
)