# 1.构建向量数据库存储对象实例
vector_store = ElasticsearchStore(
    index_name="my_index",
    es_url="http://localhost:9200",
)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
# 加载本地的数据集
documents = SimpleDirectoryReader('data').load_data()
# 构建索引
index = VectorStoreIndex.from_documents(documents,storage_context=storage_context)
# 服务对象，构建query引擎
service_context = ServiceContext.from_defaults(llm=OpenAI())
query_engine = index.as_query_engine(service_context=service_context)
# 问问题
resp=query_engine.query("住院起付线多少钱?")
# 响应答案
print(resp)

DEFAULT_FILE_READER_CLS: Dict[str, Type[BaseReader]] = {
    ".hwp": HWPReader,
    ".pdf": PDFReader,
    ".docx": DocxReader,
    ".pptx": PptxReader,
    ".ppt": PptxReader,
    ".pptm": PptxReader,
    ".jpg": ImageReader,
    ".png": ImageReader,
    ".jpeg": ImageReader,
    ".mp3": VideoAudioReader,
    ".mp4": VideoAudioReader,
    ".csv": PandasCSVReader,
    ".epub": EpubReader,
    ".md": MarkdownReader,
    ".mbox": MboxReader,
    ".ipynb": IPYNBReader,
}


class SimpleDirectoryReader(BaseReader):
    """Simple directory reader.

    Load files from file directory.
    Automatically select the best file reader given file extensions.

    Args:
        input_dir (str): Path to the directory.
        input_files (List): List of file paths to read
            (Optional; overrides input_dir, exclude)
        exclude (List): glob of python file paths to exclude (Optional)
        exclude_hidden (bool): Whether to exclude hidden files (dotfiles).
        encoding (str): Encoding of the files.
            Default is utf-8.
        errors (str): how encoding and decoding errors are to be handled,
              see https://docs.python.org/3/library/functions.html#open
        recursive (bool): Whether to recursively search in subdirectories.
            False by default.
        filename_as_id (bool): Whether to use the filename as the document id.
            False by default.
        required_exts (Optional[List[str]]): List of required extensions.
            Default is None.
        file_extractor (Optional[Dict[str, BaseReader]]): A mapping of file
            extension to a BaseReader class that specifies how to convert that file
            to text. If not specified, use default from DEFAULT_FILE_READER_CLS.
        num_files_limit (Optional[int]): Maximum number of files to read.
            Default is None.
        file_metadata (Optional[Callable[str, Dict]]): A function that takes
            in a filename and returns a Dict of metadata for the Document.
            Default is None.
    """

    supported_suffix = list(DEFAULT_FILE_READER_CLS.keys())
    //....

@dataclass
class VectorStoreQuery:
    """Vector store query."""
    # knn搜索的查询Embedding浮点型数组
    query_embedding: Optional[List[float]] = None
    # knn搜索的top k取值
    similarity_top_k: int = 1
    doc_ids: Optional[List[str]] = None
    node_ids: Optional[List[str]] = None
    query_str: Optional[str] = None
    output_fields: Optional[List[str]] = None
    embedding_field: Optional[str] = None

    mode: VectorStoreQueryMode = VectorStoreQueryMode.DEFAULT

    # NOTE: only for hybrid search (0 for bm25, 1 for vector search)
    alpha: Optional[float] = None

    # metadata filters
    filters: Optional[MetadataFilters] = None

    # only for mmr
    mmr_threshold: Optional[float] = None

    # NOTE: currently only used by postgres hybrid search
    sparse_top_k: Optional[int] = None
    # NOTE: return top k results from hybrid search. similarity_top_k is used for dense search top k
    hybrid_top_k: Optional[int] = None