Google Drive

Connect Google Drive to your preprocessing pipeline, and use the Unstructured Ingest CLI or the Unstructured Ingest Python library to batch process all your documents and store structured outputs locally on your filesystem.

The requirements are as follows.

• A Google Cloud account.

• The Google Drive API enabled in the account. Learn how.

• Within the account, a Google Cloud service account and its related credentials.json key file or its contents in JSON format. Create a service account. Create credentials for a service account.

  To ensure maximum compatibility across Unstructured service offerings, you should give the service account key information to Unstructured as a single-line string that contains the contents of the downloaded service account key file (and not the service account key file itself). To print this single-line string without line breaks, suitable for copying, you can run one of the following commands from your Terminal or Command Prompt. In this command, replace <path-to-downloaded-key-file> with the path to the credentials.json key file that you downloaded by following the preceding instructions.

  • For macOS or Linux:

    Copy

    Ask AI

    tr -d '\n' < <path-to-downloaded-key-file>
    

  • For Windows:

    Copy

    Ask AI

    (Get-Content -Path "<path-to-downloaded-key-file>" -Raw).Replace("`r`n", "").Replace("`n", "")
    

• A Google Drive shared folder or shared drive.

• Give the service account access to the shared folder or shared drive. To do this, share the folder or drive with the service account’s email address. Learn how. Learn more.

• Get the shared folder’s ID or shared drive’s ID. This is a part of the URL for your Google Drive shared folder or shared drive, represented in the following URL as {folder_id}: https://drive.google.com/drive/folders/{folder-id}.

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Document permissions metadata

The source connector outputs any permissions information that it can find in the source location about the processed source documents and associates that information with each corresponding element that is generated. This permissions information is output into the permissions_data field, which is within the data_source field under the element’s metadata field. This information lists the users or groups, if any, that have permissions to read, update, or delete the element’s associated source document.

The following example shows what the output looks like. Ellipses indicate content that has been omitted from this example for brevity.

[
    {
        "...": "...",
        "metadata": {
            "...": "...",
            "data_source": {
                "...": "...",
                "permissions_data": [
                    {
                        "read": {
                            "users": [
                                "11111111111111111111"
                            ],
                            "groups": [
                                "22222222222222222222",
                                "33333333333333333333"
                            ]
                        }
                    },
                    {
                        "update": {
                            "users": [
                                "44444444444444444444",
                                "55555555555555555555"
                            ],
                            "groups": [
                                "66666666666666666666",
                            ]
                        }
                    },
                    {
                        "delete": {
                            "users": [
                                "77777777777777777777"
                            ],
                            "groups": [
                                "88888888888888888888"
                            ]
                        }
                    }
                ],
                "...": "..."
            }
        }
    }
]

To look up information about a particular Google Cloud user, use the user’s ID along with the Admin SDK API or the People API for Google Cloud.

To look up information about a particular Google Cloud group, use the group’s ID along with the Admin SDK API or the Cloud Identity API for Google Cloud.

The Google Drive connector dependencies:

pip install "unstructured-ingest[google-drive]"

You might also need to install additional dependencies, depending on your needs. Learn more.

The following environment variables:

• GOOGLE_DRIVE_FOLDER_ID - The folder or drive ID, represented by --drive-id (CLI) or drive_id (Python).

• One of the following:

  • GCP_SERVICE_ACCOUNT_KEY_FILEPATH - The path to the credentials.json key file, represented by --service-account-key-path (CLI) or service_account_key_path (Python).
  • GCP_SERVICE_ACCOUNT_KEY_STRING - The contents of the credentials.json key file as a string, represented by --service-account-key (CLI) or service_account_key (Python).

Now call the Unstructured CLI or Python. The destination connector can be any of the ones supported. This example uses the local destination connector.

This example sends data to Unstructured for processing by default. To process data locally instead, see the instructions at the end of this page.

#!/usr/bin/env bash

# Chunking and embedding are optional.

unstructured-ingest \
  google-drive \
    --download-dir $LOCAL_FILE_DOWNLOAD_DIR \
    --drive-id $GOOGLE_DRIVE_FOLDER_ID \
    --service-account-key-path $GCP_SERVICE_ACCOUNT_KEY_FILEPATH \ # Or
    --service-account-key $GCP_SERVICE_ACCOUNT_KEY_STRING \
    --partition-by-api \
    --api-key $UNSTRUCTURED_API_KEY \
    --partition-endpoint $UNSTRUCTURED_API_URL \
    --strategy hi_res \
    --chunking-strategy by_title \
    --embedding-provider huggingface \
    --additional-partition-args="{\"split_pdf_page\":\"true\", \"split_pdf_allow_failed\":\"true\", \"split_pdf_concurrency_level\": 15}" \
  local \
    --output-dir $LOCAL_FILE_OUTPUT_DIR

For the Unstructured Ingest CLI and the Unstructured Ingest Python library, you can use the --partition-by-api option (CLI) or partition_by_api (Python) parameter to specify where files are processed:

• To do local file processing, omit --partition-by-api (CLI) or partition_by_api (Python), or explicitly specify partition_by_api=False (Python).

  Local file processing does not use an Unstructured API key or API URL, so you can also omit the following, if they appear:

  • --api-key $UNSTRUCTURED_API_KEY (CLI) or api_key=os.getenv("UNSTRUCTURED_API_KEY") (Python)
  • --partition-endpoint $UNSTRUCTURED_API_URL (CLI) or partition_endpoint=os.getenv("UNSTRUCTURED_API_URL") (Python)
  • The environment variables UNSTRUCTURED_API_KEY and UNSTRUCTURED_API_URL

• To send files to the Unstructured Partition Endpoint for processing, specify --partition-by-api (CLI) or partition_by_api=True (Python).

  Unstructured also requires an Unstructured API key and API URL, by adding the following:

  • --api-key $UNSTRUCTURED_API_KEY (CLI) or api_key=os.getenv("UNSTRUCTURED_API_KEY") (Python)
  • --partition-endpoint $UNSTRUCTURED_API_URL (CLI) or partition_endpoint=os.getenv("UNSTRUCTURED_API_URL") (Python)
  • The environment variables UNSTRUCTURED_API_KEY and UNSTRUCTURED_API_URL, representing your API key and API URL, respectively.
  You must specify the API URL only if you are not using the default API URL for Unstructured Ingest, for example, if you are using a self-hosted instance of the Unstructured API.

  The default API URL for Unstructured Ingest is https://api.unstructuredapp.io/general/v0/general, which is the API URL for the Unstructured Partition Endpoint.

  If you do not have an API key, get one now.

  If the Unstructured API is self-hosted, the process for generating Unstructured API keys, and the Unstructured API URL that you use, are different. For details, contact Unstructured Sales at sales@unstructured.io.

​

Output a key file’s contents as a string

If you need to convert the contents of a credentials.json file into a string, you could use a Python script such as the following. This script takes the local path to the key file as input and outputs the key file’s contents as a string.

# Filename: json_file_to_string.py

import json
import sys

def json_file_to_string(file_path):
    try:
        # Read the JSON file.
        with open(file_path, 'r') as file:
            # Load the JSON data.
            data = json.load(file)
        
        # Convert the JSON data back to a string, with no whitespace.
        json_string = json.dumps(data, separators=(',', ':'))
        
        return json_string
    
    except FileNotFoundError:
        print(f"Error: File '{file_path}' not found.")
        return None
    except json.JSONDecodeError:
        print(f"Error: '{file_path}' is not a valid JSON file.")
        return None
    except Exception as e:
        print(f"An unexpected error occurred: {e}")
        return None

if __name__ == "__main__":
    if len(sys.argv) != 2:
        print("Usage: python json_file_to_string.py <path_to_json_file>")
        sys.exit(1)
    
    file_path = sys.argv[1]
    result = json_file_to_string(file_path)
    
    if result:
        print(result)