Source code for langchain_community.document_loaders.gcs_file

import os
import tempfile
from typing import Callable, List, Optional

from langchain_core._api.deprecation import deprecated
from langchain_core.documents import Document

from langchain_community.document_loaders.base import BaseLoader
from langchain_community.document_loaders.unstructured import UnstructuredFileLoader
from langchain_community.utilities.vertexai import get_client_info

[docs]@deprecated( since="0.0.32", removal="0.3.0", alternative_import="langchain_google_community.GCSFileLoader", ) class GCSFileLoader(BaseLoader): """Load from GCS file."""
[docs] def __init__( self, project_name: str, bucket: str, blob: str, loader_func: Optional[Callable[[str], BaseLoader]] = None, ): """Initialize with bucket and key name. Args: project_name: The name of the project to load bucket: The name of the GCS bucket. blob: The name of the GCS blob to load. loader_func: A loader function that instantiates a loader based on a file_path argument. If nothing is provided, the UnstructuredFileLoader is used. Examples: To use an alternative PDF loader: >> from from langchain_community.document_loaders import PyPDFLoader >> loader = GCSFileLoader(..., loader_func=PyPDFLoader) To use UnstructuredFileLoader with additional arguments: >> loader = GCSFileLoader(..., >> loader_func=lambda x: UnstructuredFileLoader(x, mode="elements")) """ self.bucket = bucket self.blob = blob self.project_name = project_name def default_loader_func(file_path: str) -> BaseLoader: return UnstructuredFileLoader(file_path) self._loader_func = loader_func if loader_func else default_loader_func
[docs] def load(self) -> List[Document]: """Load documents.""" try: from import storage except ImportError: raise ImportError( "Could not import google-cloud-storage python package. " "Please install it with `pip install google-cloud-storage`." ) # initialize a client storage_client = storage.Client( self.project_name, client_info=get_client_info("google-cloud-storage") ) # Create a bucket object for our bucket bucket = storage_client.get_bucket(self.bucket) # Create a blob object from the filepath blob = bucket.blob(self.blob) # retrieve custom metadata associated with the blob metadata = bucket.get_blob(self.blob).metadata with tempfile.TemporaryDirectory() as temp_dir: file_path = f"{temp_dir}/{self.blob}" os.makedirs(os.path.dirname(file_path), exist_ok=True) # Download the file to a destination blob.download_to_filename(file_path) loader = self._loader_func(file_path) docs = loader.load() for doc in docs: if "source" in doc.metadata: doc.metadata["source"] = f"gs://{self.bucket}/{self.blob}" if metadata: doc.metadata.update(metadata) return docs