Source code for langchain_community.document_loaders.kinetica_loader

from __future__ import annotations

from typing import Any, Dict, Iterator, List, Optional, Tuple

from langchain_core.documents import Document

from langchain_community.document_loaders.base import BaseLoader


[docs] class KineticaLoader(BaseLoader): """Load from `Kinetica` API. Each document represents one row of the result. The `page_content_columns` are written into the `page_content` of the document. The `metadata_columns` are written into the `metadata` of the document. By default, all columns are written into the `page_content` and none into the `metadata`. """
[docs] def __init__( self, query: str, host: str, username: str, password: str, parameters: Optional[Dict[str, Any]] = None, page_content_columns: Optional[List[str]] = None, metadata_columns: Optional[List[str]] = None, ): """Initialize Kinetica document loader. Args: query: The query to run in Kinetica. parameters: Optional. Parameters to pass to the query. page_content_columns: Optional. Columns written to Document `page_content`. metadata_columns: Optional. Columns written to Document `metadata`. """ self.query = query self.host = host self.username = username self.password = password self.parameters = parameters self.page_content_columns = page_content_columns self.metadata_columns = metadata_columns if metadata_columns is not None else []
def _execute_query(self) -> List[Dict[str, Any]]: try: from gpudb import GPUdb, GPUdbSqlIterator except ImportError: raise ImportError( "Could not import Kinetica python API. " "Please install it with `pip install gpudb==7.2.0.9`." ) try: options = GPUdb.Options() options.username = self.username options.password = self.password conn = GPUdb(host=self.host, options=options) with GPUdbSqlIterator(conn, self.query) as records: column_names = records.type_map.keys() query_result = [dict(zip(column_names, record)) for record in records] except Exception as e: print(f"An error occurred: {e}") # noqa: T201 query_result = [] return query_result def _get_columns( self, query_result: List[Dict[str, Any]] ) -> Tuple[List[str], List[str]]: page_content_columns = ( self.page_content_columns if self.page_content_columns else [] ) metadata_columns = self.metadata_columns if self.metadata_columns else [] if page_content_columns is None and query_result: page_content_columns = list(query_result[0].keys()) if metadata_columns is None: metadata_columns = [] return page_content_columns or [], metadata_columns
[docs] def lazy_load(self) -> Iterator[Document]: query_result = self._execute_query() if isinstance(query_result, Exception): print(f"An error occurred during the query: {query_result}") # noqa: T201 return [] # type: ignore[return-value] page_content_columns, metadata_columns = self._get_columns(query_result) if "*" in page_content_columns: page_content_columns = list(query_result[0].keys()) for row in query_result: page_content = "\n".join( f"{k}: {v}" for k, v in row.items() if k in page_content_columns ) metadata = {k: v for k, v in row.items() if k in metadata_columns} doc = Document(page_content=page_content, metadata=metadata) yield doc
[docs] def load(self) -> List[Document]: """Load data into document objects.""" return list(self.lazy_load())