> ## Documentation Index > Fetch the complete documentation index at: https://langchain-5e9cc07a-preview-opensw-1782332329-96d87c7.mintlify.site/llms.txt > Use this file to discover all available pages before exploring further. # Google drive integration > Integrate with the Google drive document loader using LangChain Python. > [Google Drive](https://en.wikipedia.org/wiki/Google_Drive) is a file storage and synchronization service developed by Google. This notebook covers how to load documents from `Google Drive`. Currently, only `Google Docs` are supported. ## Prerequisites 1. Create a Google Cloud project or use an existing project 2. Enable the [Google Drive API](https://console.cloud.google.com/flows/enableapi?apiid=drive.googleapis.com) 3. [Authorize credentials for desktop app](https://developers.google.com/drive/api/quickstart/python#authorize_credentials_for_a_desktop_application) 4. `pip install -U google-api-python-client google-auth-httplib2 google-auth-oauthlib` ## 🧑 Instructions for ingesting your Google docs data Set the environmental variable `GOOGLE_APPLICATION_CREDENTIALS` to an empty string (`""`). By default, the `GoogleDriveLoader` expects the `credentials.json` file to be located at `~/.credentials/credentials.json`, but this is configurable using the `credentials_path` keyword argument. Same thing with `token.json` - default path: `~/.credentials/token.json`, constructor param: `token_path`. The first time you use GoogleDriveLoader, you will be displayed with the consent screen in your browser for user authentication. After authentication, `token.json` will be created automatically at the provided or the default path. Also, if there is already a `token.json` at that path, then you will not be prompted for authentication. `GoogleDriveLoader` can load from a list of Google Docs document ids or a folder id. You can obtain your folder and document id from the URL: * Folder: [drive.google.com/drive/u/0/folders/1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5](https://drive.google.com/drive/u/0/folders/1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5) -> folder id is `"1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5"` * Document: [docs.google.com/document/d/1bfaMQ18\_i56204VaQDVeAFpqEijJTgvurupdEDiaUQw/edit](https://docs.google.com/document/d/1bfaMQ18_i56204VaQDVeAFpqEijJTgvurupdEDiaUQw/edit) -> document id is `"1bfaMQ18_i56204VaQDVeAFpqEijJTgvurupdEDiaUQw"` ```python theme={null} pip install -qU langchain-google-community[drive] ``` ```python theme={null} from langchain_google_community import GoogleDriveLoader ``` ```python theme={null} loader = GoogleDriveLoader( folder_id="1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5", token_path="/path/where/you/want/token/to/be/created/google_token.json", # Optional: configure whether to recursively fetch files from subfolders. Defaults to False. recursive=False, ) ``` ```python theme={null} docs = loader.load() ``` When you pass a `folder_id` by default all files of type document, sheet and pdf are loaded. You can modify this behaviour by passing a `file_types` argument ```python theme={null} loader = GoogleDriveLoader( folder_id="1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5", file_types=["document", "sheet"], recursive=False, ) ``` ## Passing in optional file loaders When processing files other than Google Docs and Google Sheets, it can be helpful to pass an optional file loader to `GoogleDriveLoader`. If you pass in a file loader, that file loader will be used on documents that do not have a Google Docs or Google Sheets MIME type. Here is an example of how to load an Excel document from Google Drive using a file loader. The `langchain-community` package is no longer maintained. Examples that import from `langchain_community` may be outdated or broken. Use with caution. ```python theme={null} from langchain_community.document_loaders import UnstructuredFileIOLoader from langchain_google_community import GoogleDriveLoader ``` ```python theme={null} file_id = "1x9WBtFPWMEAdjcJzPScRsjpjQvpSo_kz" loader = GoogleDriveLoader( file_ids=[file_id], file_loader_cls=UnstructuredFileIOLoader, file_loader_kwargs={"mode": "elements"}, ) ``` ```python theme={null} docs = loader.load() ``` ```python theme={null} docs[0] ``` You can also process a folder with a mix of files and Google Docs/Sheets using the following pattern: ```python theme={null} folder_id = "1asMOHY1BqBS84JcRbOag5LOJac74gpmD" loader = GoogleDriveLoader( folder_id=folder_id, file_loader_cls=UnstructuredFileIOLoader, file_loader_kwargs={"mode": "elements"}, ) ``` ```python theme={null} docs = loader.load() ``` ```python theme={null} docs[0] ``` ```python theme={null} ``` ## Extended usage An external (unofficial) component can manage the complexity of Google Drive : `langchain-googledrive` It's compatible with the ̀`langchain_community.document_loaders.GoogleDriveLoader` and can be used in its place. To be compatible with containers, the authentication uses an environment variable `̀GOOGLE_ACCOUNT_FILE` to credential file (for user or service). ```python theme={null} pip install -qU langchain-googledrive ``` ```python theme={null} folder_id = "root" # folder_id='1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5' ``` ```python theme={null} # Use the advanced version. from langchain_googledrive.document_loaders import GoogleDriveLoader ``` ```python theme={null} loader = GoogleDriveLoader( folder_id=folder_id, recursive=False, num_results=2, # Maximum number of file to load ) ``` By default, all files with these mime-type can be converted to `Document`. * text/text * text/plain * text/html * text/csv * text/markdown * image/png * image/jpeg * application/epub+zip * application/pdf * application/rtf * application/vnd.google-apps.document (GDoc) * application/vnd.google-apps.presentation (GSlide) * application/vnd.google-apps.spreadsheet (GSheet) * application/vnd.google.colaboratory (Notebook colab) * application/vnd.openxmlformats-officedocument.presentationml.presentation (PPTX) * application/vnd.openxmlformats-officedocument.wordprocessingml.document (DOCX) It's possible to update or customize this. See the documentation of `GDriveLoader`. The corresponding packages must be installed. ```python theme={null} pip install -qU unstructured ``` ```python theme={null} for doc in loader.load(): print("---") print(doc.page_content.strip()[:60] + "...") ``` ### Loading auth identities Authorized identities for each file ingested by Google Drive Loader can be loaded along with metadata per Document. ```python theme={null} from langchain_google_community import GoogleDriveLoader loader = GoogleDriveLoader( folder_id=folder_id, load_auth=True, # Optional: configure whether to load authorized identities for each Document. ) doc = loader.load() ``` You can pass load\_auth=True, to add Google Drive document access identities to metadata. ```python theme={null} doc[0].metadata ``` ### Loading extended metadata Following extra fields can also be fetched within metadata of each Document: * full\_path - Full path of the file/s in google drive. * owner - owner of the file/s. * size - size of the file/s. ```python theme={null} from langchain_google_community import GoogleDriveLoader loader = GoogleDriveLoader( folder_id=folder_id, load_extended_matadata=True, # Optional: configure whether to load extended metadata for each Document. ) doc = loader.load() ``` You can pass load\_extended\_matadata=True, to add Google Drive document extended details to metadata. ```python theme={null} doc[0].metadata ``` ### Customize the search pattern All parameter compatible with Google [`list()`](https://developers.google.com/drive/api/v3/reference/files/list) API can be set. To specify the new pattern of the Google request, you can use a `PromptTemplate()`. The variables for the prompt can be set with `kwargs` in the constructor. Some pre-formated request are proposed (use `{query}`, `{folder_id}` and/or `{mime_type}`): You can customize the criteria to select the files. A set of predefined filter are proposed: | template | description | | -------------------------------------- | ------------------------------------------------------------------- | | gdrive-all-in-folder | Return all compatible files from a `folder_id` | | gdrive-query | Search `query` in all drives | | gdrive-by-name | Search file with name `query` | | gdrive-query-in-folder | Search `query` in `folder_id` (and sub-folders if `recursive=true`) | | gdrive-mime-type | Search a specific `mime_type` | | gdrive-mime-type-in-folder | Search a specific `mime_type` in `folder_id` | | gdrive-query-with-mime-type | Search `query` with a specific `mime_type` | | gdrive-query-with-mime-type-and-folder | Search `query` with a specific `mime_type` and in `folder_id` | ```python theme={null} loader = GoogleDriveLoader( folder_id=folder_id, recursive=False, template="gdrive-query", # Default template to use query="machine learning", num_results=2, # Maximum number of file to load supportsAllDrives=False, # GDrive `list()` parameter ) for doc in loader.load(): print("---") print(doc.page_content.strip()[:60] + "...") ``` You can customize your pattern. ```python theme={null} from langchain_core.prompts.prompt import PromptTemplate loader = GoogleDriveLoader( folder_id=folder_id, recursive=False, template=PromptTemplate( input_variables=["query", "query_name"], template="fullText contains '{query}' and name contains '{query_name}' and trashed=false", ), # Default template to use query="machine learning", query_name="ML", num_results=2, # Maximum number of file to load ) for doc in loader.load(): print("---") print(doc.page_content.strip()[:60] + "...") ``` The conversion can manage in Markdown format: * bullet * link * table * titles Set the attribute `return_link` to `True` to export links. #### Modes for GSlide and GSheet The parameter mode accepts different values: * "document": return the body of each document * "snippets": return the description of each file (set in metadata of Google Drive files). The parameter `gslide_mode` accepts different values: * "single" : one document with \ * "slide" : one document by slide * "elements" : one document for each elements. ```python theme={null} loader = GoogleDriveLoader( template="gdrive-mime-type", mime_type="application/vnd.google-apps.presentation", # Only GSlide files gslide_mode="slide", num_results=2, # Maximum number of file to load ) for doc in loader.load(): print("---") print(doc.page_content.strip()[:60] + "...") ``` The parameter `gsheet_mode` accepts different values: * `"single"`: Generate one document by line * `"elements"` : one document with markdown array and \ tags. ```python theme={null} loader = GoogleDriveLoader( template="gdrive-mime-type", mime_type="application/vnd.google-apps.spreadsheet", # Only GSheet files gsheet_mode="elements", num_results=2, # Maximum number of file to load ) for doc in loader.load(): print("---") print(doc.page_content.strip()[:60] + "...") ``` ### Advanced usage All Google File have a 'description' in the metadata. This field can be used to memorize a summary of the document or others indexed tags (See method `lazy_update_description_with_summary()`). If you use the `mode="snippet"`, only the description will be used for the body. Else, the `metadata['summary']` has the field. Sometime, a specific filter can be used to extract some information from the filename, to select some files with specific criteria. You can use a filter. Sometimes, many documents are returned. It's not necessary to have all documents in memory at the same time. You can use the lazy versions of methods, to get one document at a time. It's better to use a complex query in place of a recursive search. For each folder, a query must be applied if you activate `recursive=True`. ```python theme={null} import os loader = GoogleDriveLoader( gdrive_api_file=os.environ["GOOGLE_ACCOUNT_FILE"], num_results=2, template="gdrive-query", filter=lambda search, file: "#test" not in file.get("description", ""), query="machine learning", supportsAllDrives=False, ) for doc in loader.load(): print("---") print(doc.page_content.strip()[:60] + "...") ``` ***
[Connect these docs](/use-these-docs) to Claude, VSCode, and more via MCP for real-time answers. [Edit this page on GitHub](https://github.com/langchain-ai/docs/edit/main/src/oss/python/integrations/document_loaders/google_drive.mdx) or [file an issue](https://github.com/langchain-ai/docs/issues/new/choose).