mirror of
https://github.com/hwchase17/langchain
synced 2024-11-18 09:25:54 +00:00
ed58eeb9c5
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
361 lines
14 KiB
Python
361 lines
14 KiB
Python
# Prerequisites:
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# 1. Create a Google Cloud project
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# 2. Enable the Google Drive API:
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# https://console.cloud.google.com/flows/enableapi?apiid=drive.googleapis.com
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# 3. Authorize credentials for desktop app:
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# https://developers.google.com/drive/api/quickstart/python#authorize_credentials_for_a_desktop_application # noqa: E501
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# 4. For service accounts visit
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# https://cloud.google.com/iam/docs/service-accounts-create
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import os
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from pathlib import Path
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from typing import Any, Dict, List, Optional, Sequence, Union
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from langchain_core.documents import Document
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from langchain_core.pydantic_v1 import BaseModel, root_validator, validator
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from langchain_community.document_loaders.base import BaseLoader
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SCOPES = ["https://www.googleapis.com/auth/drive.readonly"]
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class GoogleDriveLoader(BaseLoader, BaseModel):
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"""Load Google Docs from `Google Drive`."""
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service_account_key: Path = Path.home() / ".credentials" / "keys.json"
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"""Path to the service account key file."""
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credentials_path: Path = Path.home() / ".credentials" / "credentials.json"
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"""Path to the credentials file."""
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token_path: Path = Path.home() / ".credentials" / "token.json"
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"""Path to the token file."""
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folder_id: Optional[str] = None
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"""The folder id to load from."""
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document_ids: Optional[List[str]] = None
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"""The document ids to load from."""
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file_ids: Optional[List[str]] = None
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"""The file ids to load from."""
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recursive: bool = False
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"""Whether to load recursively. Only applies when folder_id is given."""
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file_types: Optional[Sequence[str]] = None
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"""The file types to load. Only applies when folder_id is given."""
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load_trashed_files: bool = False
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"""Whether to load trashed files. Only applies when folder_id is given."""
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# NOTE(MthwRobinson) - changing the file_loader_cls to type here currently
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# results in pydantic validation errors
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file_loader_cls: Any = None
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"""The file loader class to use."""
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file_loader_kwargs: Dict["str", Any] = {}
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"""The file loader kwargs to use."""
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@root_validator
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def validate_inputs(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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"""Validate that either folder_id or document_ids is set, but not both."""
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if values.get("folder_id") and (
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values.get("document_ids") or values.get("file_ids")
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):
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raise ValueError(
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"Cannot specify both folder_id and document_ids nor "
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"folder_id and file_ids"
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)
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if (
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not values.get("folder_id")
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and not values.get("document_ids")
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and not values.get("file_ids")
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):
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raise ValueError("Must specify either folder_id, document_ids, or file_ids")
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file_types = values.get("file_types")
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if file_types:
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if values.get("document_ids") or values.get("file_ids"):
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raise ValueError(
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"file_types can only be given when folder_id is given,"
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" (not when document_ids or file_ids are given)."
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)
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type_mapping = {
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"document": "application/vnd.google-apps.document",
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"sheet": "application/vnd.google-apps.spreadsheet",
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"pdf": "application/pdf",
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}
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allowed_types = list(type_mapping.keys()) + list(type_mapping.values())
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short_names = ", ".join([f"'{x}'" for x in type_mapping.keys()])
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full_names = ", ".join([f"'{x}'" for x in type_mapping.values()])
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for file_type in file_types:
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if file_type not in allowed_types:
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raise ValueError(
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f"Given file type {file_type} is not supported. "
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f"Supported values are: {short_names}; and "
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f"their full-form names: {full_names}"
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)
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# replace short-form file types by full-form file types
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def full_form(x: str) -> str:
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return type_mapping[x] if x in type_mapping else x
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values["file_types"] = [full_form(file_type) for file_type in file_types]
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return values
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@validator("credentials_path")
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def validate_credentials_path(cls, v: Any, **kwargs: Any) -> Any:
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"""Validate that credentials_path exists."""
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if not v.exists():
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raise ValueError(f"credentials_path {v} does not exist")
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return v
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def _load_credentials(self) -> Any:
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"""Load credentials."""
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# Adapted from https://developers.google.com/drive/api/v3/quickstart/python
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try:
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from google.auth import default
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from google.auth.transport.requests import Request
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from google.oauth2 import service_account
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from google.oauth2.credentials import Credentials
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from google_auth_oauthlib.flow import InstalledAppFlow
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except ImportError:
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raise ImportError(
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"You must run "
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"`pip install --upgrade "
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"google-api-python-client google-auth-httplib2 "
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"google-auth-oauthlib` "
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"to use the Google Drive loader."
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)
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creds = None
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if self.service_account_key.exists():
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return service_account.Credentials.from_service_account_file(
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str(self.service_account_key), scopes=SCOPES
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)
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if self.token_path.exists():
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creds = Credentials.from_authorized_user_file(str(self.token_path), SCOPES)
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if not creds or not creds.valid:
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if creds and creds.expired and creds.refresh_token:
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creds.refresh(Request())
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elif "GOOGLE_APPLICATION_CREDENTIALS" not in os.environ:
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creds, project = default()
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creds = creds.with_scopes(SCOPES)
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# no need to write to file
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if creds:
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return creds
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else:
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flow = InstalledAppFlow.from_client_secrets_file(
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str(self.credentials_path), SCOPES
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)
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creds = flow.run_local_server(port=0)
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with open(self.token_path, "w") as token:
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token.write(creds.to_json())
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return creds
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def _load_sheet_from_id(self, id: str) -> List[Document]:
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"""Load a sheet and all tabs from an ID."""
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from googleapiclient.discovery import build
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creds = self._load_credentials()
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sheets_service = build("sheets", "v4", credentials=creds)
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spreadsheet = sheets_service.spreadsheets().get(spreadsheetId=id).execute()
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sheets = spreadsheet.get("sheets", [])
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documents = []
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for sheet in sheets:
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sheet_name = sheet["properties"]["title"]
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result = (
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sheets_service.spreadsheets()
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.values()
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.get(spreadsheetId=id, range=sheet_name)
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.execute()
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)
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values = result.get("values", [])
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if not values:
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continue # empty sheet
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header = values[0]
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for i, row in enumerate(values[1:], start=1):
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metadata = {
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"source": (
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f"https://docs.google.com/spreadsheets/d/{id}/"
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f"edit?gid={sheet['properties']['sheetId']}"
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),
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"title": f"{spreadsheet['properties']['title']} - {sheet_name}",
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"row": i,
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}
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content = []
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for j, v in enumerate(row):
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title = header[j].strip() if len(header) > j else ""
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content.append(f"{title}: {v.strip()}")
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page_content = "\n".join(content)
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documents.append(Document(page_content=page_content, metadata=metadata))
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return documents
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def _load_document_from_id(self, id: str) -> Document:
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"""Load a document from an ID."""
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from io import BytesIO
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from googleapiclient.discovery import build
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from googleapiclient.errors import HttpError
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from googleapiclient.http import MediaIoBaseDownload
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creds = self._load_credentials()
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service = build("drive", "v3", credentials=creds)
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file = (
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service.files()
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.get(fileId=id, supportsAllDrives=True, fields="modifiedTime,name")
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.execute()
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)
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request = service.files().export_media(fileId=id, mimeType="text/plain")
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fh = BytesIO()
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downloader = MediaIoBaseDownload(fh, request)
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done = False
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try:
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while done is False:
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status, done = downloader.next_chunk()
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except HttpError as e:
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if e.resp.status == 404:
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print("File not found: {}".format(id))
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else:
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print("An error occurred: {}".format(e))
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text = fh.getvalue().decode("utf-8")
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metadata = {
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"source": f"https://docs.google.com/document/d/{id}/edit",
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"title": f"{file.get('name')}",
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"when": f"{file.get('modifiedTime')}",
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}
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return Document(page_content=text, metadata=metadata)
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def _load_documents_from_folder(
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self, folder_id: str, *, file_types: Optional[Sequence[str]] = None
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) -> List[Document]:
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"""Load documents from a folder."""
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from googleapiclient.discovery import build
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creds = self._load_credentials()
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service = build("drive", "v3", credentials=creds)
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files = self._fetch_files_recursive(service, folder_id)
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# If file types filter is provided, we'll filter by the file type.
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if file_types:
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_files = [f for f in files if f["mimeType"] in file_types] # type: ignore
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else:
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_files = files
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returns = []
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for file in _files:
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if file["trashed"] and not self.load_trashed_files:
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continue
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elif file["mimeType"] == "application/vnd.google-apps.document":
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returns.append(self._load_document_from_id(file["id"])) # type: ignore
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elif file["mimeType"] == "application/vnd.google-apps.spreadsheet":
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returns.extend(self._load_sheet_from_id(file["id"])) # type: ignore
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elif (
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file["mimeType"] == "application/pdf"
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or self.file_loader_cls is not None
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):
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returns.extend(self._load_file_from_id(file["id"])) # type: ignore
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else:
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pass
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return returns
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def _fetch_files_recursive(
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self, service: Any, folder_id: str
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) -> List[Dict[str, Union[str, List[str]]]]:
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"""Fetch all files and subfolders recursively."""
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results = (
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service.files()
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.list(
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q=f"'{folder_id}' in parents",
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pageSize=1000,
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includeItemsFromAllDrives=True,
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supportsAllDrives=True,
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fields="nextPageToken, files(id, name, mimeType, parents, trashed)",
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)
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.execute()
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)
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files = results.get("files", [])
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returns = []
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for file in files:
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if file["mimeType"] == "application/vnd.google-apps.folder":
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if self.recursive:
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returns.extend(self._fetch_files_recursive(service, file["id"]))
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else:
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returns.append(file)
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return returns
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def _load_documents_from_ids(self) -> List[Document]:
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"""Load documents from a list of IDs."""
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if not self.document_ids:
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raise ValueError("document_ids must be set")
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return [self._load_document_from_id(doc_id) for doc_id in self.document_ids]
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def _load_file_from_id(self, id: str) -> List[Document]:
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"""Load a file from an ID."""
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from io import BytesIO
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from googleapiclient.discovery import build
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from googleapiclient.http import MediaIoBaseDownload
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creds = self._load_credentials()
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service = build("drive", "v3", credentials=creds)
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file = service.files().get(fileId=id, supportsAllDrives=True).execute()
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request = service.files().get_media(fileId=id)
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fh = BytesIO()
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downloader = MediaIoBaseDownload(fh, request)
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done = False
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while done is False:
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status, done = downloader.next_chunk()
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if self.file_loader_cls is not None:
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fh.seek(0)
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loader = self.file_loader_cls(file=fh, **self.file_loader_kwargs)
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docs = loader.load()
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for doc in docs:
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doc.metadata["source"] = f"https://drive.google.com/file/d/{id}/view"
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if "title" not in doc.metadata:
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doc.metadata["title"] = f"{file.get('name')}"
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return docs
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else:
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from PyPDF2 import PdfReader
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content = fh.getvalue()
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pdf_reader = PdfReader(BytesIO(content))
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return [
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Document(
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page_content=page.extract_text(),
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metadata={
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"source": f"https://drive.google.com/file/d/{id}/view",
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"title": f"{file.get('name')}",
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"page": i,
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},
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)
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for i, page in enumerate(pdf_reader.pages)
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]
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def _load_file_from_ids(self) -> List[Document]:
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"""Load files from a list of IDs."""
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if not self.file_ids:
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raise ValueError("file_ids must be set")
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docs = []
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for file_id in self.file_ids:
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docs.extend(self._load_file_from_id(file_id))
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return docs
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def load(self) -> List[Document]:
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"""Load documents."""
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if self.folder_id:
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return self._load_documents_from_folder(
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self.folder_id, file_types=self.file_types
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)
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elif self.document_ids:
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return self._load_documents_from_ids()
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else:
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return self._load_file_from_ids()
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