langchain/libs/community/langchain_community/document_loaders/rocksetdb.py

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community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463) Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
2023-12-11 21:53:30 +00:00
from typing import Any, Callable, Iterator, List, Optional, Tuple
from langchain_core.documents import Document
from langchain_community.document_loaders.base import BaseLoader
def default_joiner(docs: List[Tuple[str, Any]]) -> str:
"""Default joiner for content columns."""
return "\n".join([doc[1] for doc in docs])
class ColumnNotFoundError(Exception):
"""Column not found error."""
def __init__(self, missing_key: str, query: str):
super().__init__(f'Column "{missing_key}" not selected in query:\n{query}')
class RocksetLoader(BaseLoader):
"""Load from a `Rockset` database.
To use, you should have the `rockset` python package installed.
Example:
.. code-block:: python
# This code will load 3 records from the "langchain_demo"
# collection as Documents, with the `text` column used as
# the content
from langchain_community.document_loaders import RocksetLoader
from rockset import RocksetClient, Regions, models
loader = RocksetLoader(
RocksetClient(Regions.usw2a1, "<api key>"),
models.QueryRequestSql(
query="select * from langchain_demo limit 3"
),
["text"]
)
)
"""
def __init__(
self,
client: Any,
query: Any,
content_keys: List[str],
metadata_keys: Optional[List[str]] = None,
content_columns_joiner: Callable[[List[Tuple[str, Any]]], str] = default_joiner,
):
"""Initialize with Rockset client.
Args:
client: Rockset client object.
query: Rockset query object.
content_keys: The collection columns to be written into the `page_content`
of the Documents.
metadata_keys: The collection columns to be written into the `metadata` of
the Documents. By default, this is all the keys in the document.
content_columns_joiner: Method that joins content_keys and its values into a
string. It's method that takes in a List[Tuple[str, Any]]],
representing a list of tuples of (column name, column value).
By default, this is a method that joins each column value with a new
line. This method is only relevant if there are multiple content_keys.
"""
try:
from rockset import QueryPaginator, RocksetClient
from rockset.models import QueryRequestSql
except ImportError:
raise ImportError(
"Could not import rockset client python package. "
"Please install it with `pip install rockset`."
)
if not isinstance(client, RocksetClient):
raise ValueError(
f"client should be an instance of rockset.RocksetClient, "
f"got {type(client)}"
)
if not isinstance(query, QueryRequestSql):
raise ValueError(
f"query should be an instance of rockset.model.QueryRequestSql, "
f"got {type(query)}"
)
self.client = client
self.query = query
self.content_keys = content_keys
self.content_columns_joiner = content_columns_joiner
self.metadata_keys = metadata_keys
self.paginator = QueryPaginator
self.request_model = QueryRequestSql
try:
self.client.set_application("langchain")
except AttributeError:
# ignore
pass
def load(self) -> List[Document]:
return list(self.lazy_load())
def lazy_load(self) -> Iterator[Document]:
query_results = self.client.Queries.query(
sql=self.query
).results # execute the SQL query
for doc in query_results: # for each doc in the response
try:
yield Document(
page_content=self.content_columns_joiner(
[(col, doc[col]) for col in self.content_keys]
),
metadata={col: doc[col] for col in self.metadata_keys}
if self.metadata_keys is not None
else doc,
) # try to yield the Document
except (
KeyError
) as e: # either content_columns or metadata_columns is invalid
raise ColumnNotFoundError(
e.args[0], self.query
) # raise that the column isn't in the db schema