langchain/libs/community/langchain_community/document_loaders/dropbox.py
Bagatur ed58eeb9c5
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 13:53:30 -08:00

174 lines
6.1 KiB
Python

# Prerequisites:
# 1. Create a Dropbox app.
# 2. Give the app these scope permissions: `files.metadata.read`
# and `files.content.read`.
# 3. Generate access token: https://www.dropbox.com/developers/apps/create.
# 4. `pip install dropbox` (requires `pip install unstructured[pdf]` for PDF filetype).
import os
import tempfile
from pathlib import Path
from typing import Any, Dict, List, Optional
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import BaseModel, root_validator
from langchain_community.document_loaders.base import BaseLoader
class DropboxLoader(BaseLoader, BaseModel):
"""Load files from `Dropbox`.
In addition to common files such as text and PDF files, it also supports
*Dropbox Paper* files.
"""
dropbox_access_token: str
"""Dropbox access token."""
dropbox_folder_path: Optional[str] = None
"""The folder path to load from."""
dropbox_file_paths: Optional[List[str]] = None
"""The file paths to load from."""
recursive: bool = False
"""Flag to indicate whether to load files recursively from subfolders."""
@root_validator
def validate_inputs(cls, values: Dict[str, Any]) -> Dict[str, Any]:
"""Validate that either folder_path or file_paths is set, but not both."""
if (
values.get("dropbox_folder_path") is not None
and values.get("dropbox_file_paths") is not None
):
raise ValueError("Cannot specify both folder_path and file_paths")
if values.get("dropbox_folder_path") is None and not values.get(
"dropbox_file_paths"
):
raise ValueError("Must specify either folder_path or file_paths")
return values
def _create_dropbox_client(self) -> Any:
"""Create a Dropbox client."""
try:
from dropbox import Dropbox, exceptions
except ImportError:
raise ImportError("You must run " "`pip install dropbox")
try:
dbx = Dropbox(self.dropbox_access_token)
dbx.users_get_current_account()
except exceptions.AuthError as ex:
raise ValueError(
"Invalid Dropbox access token. Please verify your token and try again."
) from ex
return dbx
def _load_documents_from_folder(self, folder_path: str) -> List[Document]:
"""Load documents from a Dropbox folder."""
dbx = self._create_dropbox_client()
try:
from dropbox import exceptions
from dropbox.files import FileMetadata
except ImportError:
raise ImportError("You must run " "`pip install dropbox")
try:
results = dbx.files_list_folder(folder_path, recursive=self.recursive)
except exceptions.ApiError as ex:
raise ValueError(
f"Could not list files in the folder: {folder_path}. "
"Please verify the folder path and try again."
) from ex
files = [entry for entry in results.entries if isinstance(entry, FileMetadata)]
documents = [
doc
for doc in (self._load_file_from_path(file.path_display) for file in files)
if doc is not None
]
return documents
def _load_file_from_path(self, file_path: str) -> Optional[Document]:
"""Load a file from a Dropbox path."""
dbx = self._create_dropbox_client()
try:
from dropbox import exceptions
except ImportError:
raise ImportError("You must run " "`pip install dropbox")
try:
file_metadata = dbx.files_get_metadata(file_path)
if file_metadata.is_downloadable:
_, response = dbx.files_download(file_path)
# Some types such as Paper, need to be exported.
elif file_metadata.export_info:
_, response = dbx.files_export(file_path, "markdown")
except exceptions.ApiError as ex:
raise ValueError(
f"Could not load file: {file_path}. Please verify the file path"
"and try again."
) from ex
try:
text = response.content.decode("utf-8")
except UnicodeDecodeError:
file_extension = os.path.splitext(file_path)[1].lower()
if file_extension == ".pdf":
print(f"File {file_path} type detected as .pdf")
from langchain_community.document_loaders import UnstructuredPDFLoader
# Download it to a temporary file.
temp_dir = tempfile.TemporaryDirectory()
temp_pdf = Path(temp_dir.name) / "tmp.pdf"
with open(temp_pdf, mode="wb") as f:
f.write(response.content)
try:
loader = UnstructuredPDFLoader(str(temp_pdf))
docs = loader.load()
if docs:
return docs[0]
except Exception as pdf_ex:
print(f"Error while trying to parse PDF {file_path}: {pdf_ex}")
return None
else:
print(
f"File {file_path} could not be decoded as pdf or text. Skipping."
)
return None
metadata = {
"source": f"dropbox://{file_path}",
"title": os.path.basename(file_path),
}
return Document(page_content=text, metadata=metadata)
def _load_documents_from_paths(self) -> List[Document]:
"""Load documents from a list of Dropbox file paths."""
if not self.dropbox_file_paths:
raise ValueError("file_paths must be set")
return [
doc
for doc in (
self._load_file_from_path(file_path)
for file_path in self.dropbox_file_paths
)
if doc is not None
]
def load(self) -> List[Document]:
"""Load documents."""
if self.dropbox_folder_path is not None:
return self._load_documents_from_folder(self.dropbox_folder_path)
else:
return self._load_documents_from_paths()