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Google drive integration

This notebook walks through connecting a LangChain to the Google Drive API.

Prerequisites

  1. Create a Google Cloud project or use an existing project
  2. Enable the Google Drive API
  3. Authorize credentials for desktop app
  4. pip install -U google-api-python-client google-auth-httplib2 google-auth-oauthlib

Instructions for retrieving your Google docs data

By default, the GoogleDriveTools and GoogleDriveWrapper expects the credentials.json file to be ~/.credentials/credentials.json, but this is configurable by setting the GOOGLE_ACCOUNT_FILE environment variable to your custom/path/to/credentials.json. The location of token.json use the same directory (or use the parameter token_path). Note that token.json will be created automatically the first time you use the tool.

GoogleDriveSearchTool can retrieve a selection of files with some requests.

By default, If you use a folder_id, all the files inside this folder can be retrieved to Document, if the name match the query.

pip install -qU  google-api-python-client google-auth-httplib2 google-auth-oauthlib

You can obtain your folder and document id from the URL:

The special value root is for your personal home.

folder_id = "root"
# folder_id='1yucgL9WGgWZdM1TOuKkeghlPizuzMYb5'

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 GoogleDriveAPIWrapper.

The corresponding packages must be installed.

pip install -qU  unstructured langchain-googledrive
import os

from langchain_googledrive.tools.google_drive.tool import GoogleDriveSearchTool
from langchain_googledrive.utilities.google_drive import GoogleDriveAPIWrapper

os.environ["GOOGLE_ACCOUNT_FILE"] = "custom/path/to/credentials.json"

# By default, search only in the filename.
tool = GoogleDriveSearchTool(
    api_wrapper=GoogleDriveAPIWrapper(
        folder_id=folder_id,
        num_results=2,
        template="gdrive-query-in-folder",  # Search in the body of documents
    )
)
import logging

logging.basicConfig(level=logging.INFO)
tool.run("machine learning")
tool.description
"A wrapper around Google Drive Search. Useful for when you need to find a document in google drive. The input should be formatted as a list of entities separated with a space. As an example, a list of keywords is 'hello word'."

Use the tool within a ReAct agent

In order to create an agent that uses the Google Jobs tool install LangGraph

pip install -qU langgraph langchain-openai

and use the create_agent functionality to initialize a ReAct agent. You will also need to set up your OPEN_API_KEY (visit platform.openai.com) in order to access OpenAI's chat models.

import os

from langchain.chat_models import init_chat_model
from langchain.agents import create_agent


os.environ["OPENAI_API_KEY"] = "your-openai-api-key"


model = init_chat_model("gpt-5.4-mini", model_provider="openai", temperature=0)
agent = create_agent(model, tools=[tool])

stream = agent.stream_events(
    {"messages": [("user", "Search in google drive, who is 'Yann LeCun' ?")]},
    version="v3",
)
for snapshot in stream.values:
    snapshot["messages"][-1].pretty_print()