Myscale

MyScaleReader

Bases: BaseReader

MyScale reader.

Parameters:

Name	Type	Description	Default
myscale_host	str)	An URL to connect to MyScale backend.	required
username	str)	Usernamed to login.	required
password	str)	Password to login.	required
myscale_port	int)	URL port to connect with HTTP. Defaults to 8443.	8443
database	str)	Database name to find the table. Defaults to 'default'.	'default'
table	str)	Table name to operate on. Defaults to 'vector_table'.	'llama_index'
index_type	str	index type string. Default to "IVFLAT"	'IVFLAT'
metric	str)	Metric to compute distance, supported are ('l2', 'cosine', 'ip'). Defaults to 'cosine'	'cosine'
batch_size	int	the size of documents to insert. Defaults to 32.	32
index_params	dict	The index parameters for MyScale. Defaults to None.	None
search_params	dict	The search parameters for a MyScale query. Defaults to None.	None

Source code in llama-index-integrations/readers/llama-index-readers-myscale/llama_index/readers/myscale/base.py

class MyScaleReader(BaseReader):
    """MyScale reader.

    Args:
        myscale_host (str) : An URL to connect to MyScale backend.
        username (str) : Usernamed to login.
        password (str) : Password to login.
        myscale_port (int) : URL port to connect with HTTP. Defaults to 8443.
        database (str) : Database name to find the table. Defaults to 'default'.
        table (str) : Table name to operate on. Defaults to 'vector_table'.
        index_type (str): index type string. Default to "IVFLAT"
        metric (str) : Metric to compute distance, supported are ('l2', 'cosine', 'ip').
            Defaults to 'cosine'
        batch_size (int, optional): the size of documents to insert. Defaults to 32.
        index_params (dict, optional): The index parameters for MyScale.
            Defaults to None.
        search_params (dict, optional): The search parameters for a MyScale query.
            Defaults to None.

    """

    def __init__(
        self,
        myscale_host: str,
        username: str,
        password: str,
        myscale_port: Optional[int] = 8443,
        database: str = "default",
        table: str = "llama_index",
        index_type: str = "IVFLAT",
        metric: str = "cosine",
        batch_size: int = 32,
        index_params: Optional[dict] = None,
        search_params: Optional[dict] = None,
        **kwargs: Any,
    ) -> None:
        """Initialize params."""
        self.client = clickhouse_connect.get_client(
            host=myscale_host,
            port=myscale_port,
            username=username,
            password=password,
        )

        self.config = MyScaleSettings(
            table=table,
            database=database,
            index_type=index_type,
            metric=metric,
            batch_size=batch_size,
            index_params=index_params,
            search_params=search_params,
            **kwargs,
        )

    def load_data(
        self,
        query_vector: List[float],
        where_str: Optional[str] = None,
        limit: int = 10,
    ) -> List[Document]:
        """Load data from MyScale.

        Args:
            query_vector (List[float]): Query vector.
            where_str (Optional[str], optional): where condition string.
                Defaults to None.
            limit (int): Number of results to return.

        Returns:
            List[Document]: A list of documents.
        """
        query_statement = self.config.build_query_statement(
            query_embed=query_vector,
            where_str=where_str,
            limit=limit,
        )

        return [
            Document(id_=r["doc_id"], text=r["text"], metadata=r["metadata"])
            for r in self.client.query(query_statement).named_results()
        ]

load_data

load_data(query_vector: List[float], where_str: Optional[str] = None, limit: int = 10) -> List[Document]

Load data from MyScale.

Parameters:

Name	Type	Description	Default
query_vector	List[float]	Query vector.	required
where_str	Optional[str]	where condition string. Defaults to None.	None
limit	int	Number of results to return.	10

Returns:

Type	Description
List[Document]	List[Document]: A list of documents.

Source code in llama-index-integrations/readers/llama-index-readers-myscale/llama_index/readers/myscale/base.py

def load_data(
    self,
    query_vector: List[float],
    where_str: Optional[str] = None,
    limit: int = 10,
) -> List[Document]:
    """Load data from MyScale.

    Args:
        query_vector (List[float]): Query vector.
        where_str (Optional[str], optional): where condition string.
            Defaults to None.
        limit (int): Number of results to return.

    Returns:
        List[Document]: A list of documents.
    """
    query_statement = self.config.build_query_statement(
        query_embed=query_vector,
        where_str=where_str,
        limit=limit,
    )

    return [
        Document(id_=r["doc_id"], text=r["text"], metadata=r["metadata"])
        for r in self.client.query(query_statement).named_results()
    ]