langchain/libs/community/langchain_community/document_loaders/kinetica_loader.py
am-kinetica b54b19ba1c
community[minor]: Implemented Kinetica Document Loader and added notebooks (#20002)
- [ ] **Kinetica Document Loader**: "community: a class to load
Documents from Kinetica"



- [ ] **Kinetica Document Loader**: 
- **Description:** implemented KineticaLoader in `kinetica_loader.py`
- **Dependencies:** install the Kinetica API using `pip install
gpudb==7.2.0.1 `
2024-04-25 13:39:00 -07:00

104 lines
3.8 KiB
Python

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
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`.
"""
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==7.2.0.1`."
)
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
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 []
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
def load(self) -> List[Document]:
"""Load data into document objects."""
return list(self.lazy_load())