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from __future__ import annotations
import concurrent.futures
from pathlib import Path
from typing import Iterator, Literal, Optional, Sequence, Union
from langchain_core.documents import Document
from langchain.document_loaders.base import BaseBlobParser
from langchain.document_loaders.blob_loaders import BlobLoader, FileSystemBlobLoader
from langchain.document_loaders.generic import GenericLoader
from langchain.document_loaders.parsers.registry import get_parser
_PathLike = Union[str, Path]
DEFAULT = Literal["default"]
class ConcurrentLoader(GenericLoader):
"""Load and pars Documents concurrently."""
def __init__(
self, blob_loader: BlobLoader, blob_parser: BaseBlobParser, num_workers: int = 4
) -> None:
super().__init__(blob_loader, blob_parser)
self.num_workers = num_workers
def lazy_load(
self,
) -> Iterator[Document]:
"""Load documents lazily with concurrent parsing."""
with concurrent.futures.ThreadPoolExecutor(
max_workers=self.num_workers
) as executor:
futures = {
executor.submit(self.blob_parser.lazy_parse, blob)
for blob in self.blob_loader.yield_blobs()
}
for future in concurrent.futures.as_completed(futures):
yield from future.result()
@classmethod
def from_filesystem(
cls,
path: _PathLike,
*,
glob: str = "**/[!.]*",
exclude: Sequence[str] = (),
suffixes: Optional[Sequence[str]] = None,
show_progress: bool = False,
parser: Union[DEFAULT, BaseBlobParser] = "default",
num_workers: int = 4,
) -> ConcurrentLoader:
"""
Create a concurrent generic document loader using a
filesystem blob loader.
Args:
path: The path to the directory to load documents from.
glob: The glob pattern to use to find documents.
suffixes: The suffixes to use to filter documents. If None, all files
matching the glob will be loaded.
exclude: A list of patterns to exclude from the loader.
show_progress: Whether to show a progress bar or not (requires tqdm).
Proxies to the file system loader.
parser: A blob parser which knows how to parse blobs into documents
num_workers: Max number of concurrent workers to use.
"""
blob_loader = FileSystemBlobLoader(
path,
glob=glob,
exclude=exclude,
suffixes=suffixes,
show_progress=show_progress,
)
if isinstance(parser, str):
blob_parser = get_parser(parser)
else:
blob_parser = parser
return cls(blob_loader, blob_parser, num_workers=num_workers)