Source code for langchain_core.document_loaders.base
"""Abstract interface for document loader implementations."""
from __future__ import annotations
from abc import ABC, abstractmethod
from collections.abc import AsyncIterator, Iterator
from typing import TYPE_CHECKING, Optional
from langchain_core.documents import Document
from langchain_core.runnables import run_in_executor
if TYPE_CHECKING:
from langchain_text_splitters import TextSplitter
from langchain_core.documents.base import Blob
[docs]
class BaseLoader(ABC): # noqa: B024
"""Interface for Document Loader.
Implementations should implement the lazy-loading method using generators
to avoid loading all Documents into memory at once.
`load` is provided just for user convenience and should not be overridden.
"""
# Sub-classes should not implement this method directly. Instead, they
# should implement the lazy load method.
[docs]
def load(self) -> list[Document]:
"""Load data into Document objects."""
return list(self.lazy_load())
[docs]
async def aload(self) -> list[Document]:
"""Load data into Document objects."""
return [document async for document in self.alazy_load()]
[docs]
def load_and_split(
self, text_splitter: Optional[TextSplitter] = None
) -> list[Document]:
"""Load Documents and split into chunks. Chunks are returned as Documents.
Do not override this method. It should be considered to be deprecated!
Args:
text_splitter: TextSplitter instance to use for splitting documents.
Defaults to RecursiveCharacterTextSplitter.
Returns:
List of Documents.
"""
if text_splitter is None:
try:
from langchain_text_splitters import RecursiveCharacterTextSplitter
except ImportError as e:
msg = (
"Unable to import from langchain_text_splitters. Please specify "
"text_splitter or install langchain_text_splitters with "
"`pip install -U langchain-text-splitters`."
)
raise ImportError(msg) from e
_text_splitter: TextSplitter = RecursiveCharacterTextSplitter()
else:
_text_splitter = text_splitter
docs = self.load()
return _text_splitter.split_documents(docs)
# Attention: This method will be upgraded into an abstractmethod once it's
# implemented in all the existing subclasses.
[docs]
def lazy_load(self) -> Iterator[Document]:
"""A lazy loader for Documents."""
if type(self).load != BaseLoader.load:
return iter(self.load())
msg = f"{self.__class__.__name__} does not implement lazy_load()"
raise NotImplementedError(msg)
[docs]
async def alazy_load(self) -> AsyncIterator[Document]:
"""A lazy loader for Documents."""
iterator = await run_in_executor(None, self.lazy_load)
done = object()
while True:
doc = await run_in_executor(None, next, iterator, done) # type: ignore[call-arg, arg-type]
if doc is done:
break
yield doc # type: ignore[misc]
[docs]
class BaseBlobParser(ABC):
"""Abstract interface for blob parsers.
A blob parser provides a way to parse raw data stored in a blob into one
or more documents.
The parser can be composed with blob loaders, making it easy to reuse
a parser independent of how the blob was originally loaded.
"""
[docs]
@abstractmethod
def lazy_parse(self, blob: Blob) -> Iterator[Document]:
"""Lazy parsing interface.
Subclasses are required to implement this method.
Args:
blob: Blob instance
Returns:
Generator of documents
"""
[docs]
def parse(self, blob: Blob) -> list[Document]:
"""Eagerly parse the blob into a document or documents.
This is a convenience method for interactive development environment.
Production applications should favor the lazy_parse method instead.
Subclasses should generally not over-ride this parse method.
Args:
blob: Blob instance
Returns:
List of documents
"""
return list(self.lazy_parse(blob))