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

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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 --upgrade google-api-python-client google-auth-httplib2 google-auth-oauthlib

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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 --upgrade --quiet  google-api-python-client google-auth-httplib2 google-auth-oauthlib langchain-community
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. But, the corresponding packages must installed. 
%pip install --upgrade --quiet  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'."

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Use the tool within a ReAct agent

In order to create an agent that uses the Google Jobs tool install Langgraph 
%pip install --upgrade --quiet langgraph langchain-openai
and use the create_react_agent functionality to initialize a ReAct agent. You will also need to set up your OPEN_API_KEY (visit https://platform.openai.com) in order to access OpenAI’s chat models. 
import os

from langchain.chat_models import init_chat_model
from langgraph.prebuilt import create_react_agent

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


llm = init_chat_model("gpt-4o-mini", model_provider="openai", temperature=0)
agent = create_react_agent(llm, tools=[tool])

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