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README

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Gmail Integration Tools

Connect your email assistant to Gmail and Google Calendar APIs.

Graph

The src/email_assistant/email_assistant_hitl_memory_gmail.py graph is configured to use Gmail tools.

You simply need to run the setup below to obtain the credentials needed to run the graph with your own email.

Setup Credentials

1. Set up Google Cloud Project and Enable Required APIs

Enable Gmail and Calendar APIs

  1. Go to the Google APIs Library and enable the Gmail API
  2. Go to the Google APIs Library and enable the Google Calendar API

Create OAuth Credentials

  1. Authorize credentials for a desktop application here
  2. Go to Credentials → Create Credentials → OAuth Client ID
  3. Set Application Type to “Desktop app”
  4. Click “Create”

Note: If using a personal email (non-Google Workspace) select “External” under “Audience”

Screenshot 2025-04-26 at 7 43 57 AM

Then, add yourself as a test user

  1. Save the downloaded JSON file (you’ll need this in the next step)

2. Set Up Authentication Files

  1. Move your downloaded client secret JSON file to the .secrets directory
# Create a secrets directory
mkdir -p src/email_assistant/tools/gmail/.secrets
 
# Move your downloaded client secret to the secrets directory
mv /path/to/downloaded/client_secret.json src/email_assistant/tools/gmail/.secrets/secrets.json
  1. Run the Gmail setup script
# Run the Gmail setup script
python src/email_assistant/tools/gmail/setup_gmail.py
  • This will open a browser window for you to authenticate with your Google account
  • This will create a token.json file in the .secrets directory
  • This token will be used for Gmail API access

Use With A Local Deployment

1. Run the Gmail Ingestion Script with Locally Running LangGraph Server

  1. Once you have authentication set up, run LangGraph server locally:
langgraph dev
  1. Run the ingestion script in another terminal with desired parameters:
python src/email_assistant/tools/gmail/run_ingest.py --email [email protected] --minutes-since 1000
  • By default, this will use the local deployment URL (http://127.0.0.1:2024) and fetch emails from the past 1000 minutes.
  • It will use the LangGraph SDK to pass each email to the locally running email assistant.
  • It will use the email_assistant_hitl_memory_gmail graph, which is configured to use Gmail tools.

Parameters:

  • --graph-name: Name of the LangGraph to use (default: “email_assistant_hitl_memory_gmail”)
  • --email: The email address to fetch messages from (alternative to setting EMAIL_ADDRESS)
  • --minutes-since: Only process emails that are newer than this many minutes (default: 60)
  • --url: URL of the LangGraph deployment (default: http://127.0.0.1:2024)
  • --rerun: Process emails that have already been processed (default: false)
  • --early: Stop after processing one email (default: false)
  • --include-read: Include emails that have already been read (by default only unread emails are processed)
  • --skip-filters: Process all emails without filtering (by default only latest messages in threads where you’re not the sender are processed)

Troubleshooting:

  • Missing emails? The Gmail API applies filters to show only important/primary emails by default. You can:
    • Increase the --minutes-since parameter to a larger value (e.g., 1000) to fetch emails from a longer time period
    • Use the --include-read flag to process emails marked as “read” (by default only unread emails are processed)
    • Use the --skip-filters flag to include all messages (not just the latest in a thread, and including ones you sent)
    • Try running with all options to process everything: --include-read --skip-filters --minutes-since 1000
    • Use the --mock flag to test the system with simulated emails

2. Connect to Agent Inbox

After ingestion, you can access your all interrupted threads in Agent Inbox (https://dev.agentinbox.ai/):

  • Deployment URL: http://127.0.0.1:2024
  • Assistant/Graph ID: email_assistant_hitl_memory_gmail
  • Name: Graph Name

Run A Hosted Deployment

1. Deploy to LangGraph Platform

  1. Navigate to the deployments page in LangSmith
  2. Click New Deployment
  3. Connect it to your fork of the this repo and desired branch
  4. Give it a name like Yourname-Email-Assistant
  5. Add the following environment variables:
    • OPENAI_API_KEY
    • GMAIL_SECRET - This is the full dictionary in .secrets/secrets.json
    • GMAIL_TOKEN - This is the full dictionary in .secrets/token.json
  6. Click Submit
  7. Get the API URL (https://your-email-assistant-xxx.us.langgraph.app) from the deployment page

2. Run Ingestion with Hosted Deployment

Once your LangGraph deployment is up and running, you can test the email ingestion with:

python src/email_assistant/tools/gmail/run_ingest.py --email [email protected] --minutes-since 2440 --include-read --url https://your-email-assistant-xxx.us.langgraph.app

3. Connect to Agent Inbox

After ingestion, you can access your all interrupted threads in Agent Inbox (https://dev.agentinbox.ai/):

4. Set up Cron Job

With a hosted deployment, you can set up a cron job to run the ingestion script at a specified interval.

To automate email ingestion, set up a scheduled cron job using the included setup script:

python src/email_assistant/tools/gmail/setup_cron.py --email [email protected] --url https://lance-email-assistant-4681ae9646335abe9f39acebbde8680b.us.langgraph.app

Parameters:

  • --email: Email address to fetch messages for (required)
  • --url: LangGraph deployment URL (required)
  • --minutes-since: Only fetch emails newer than this many minutes (default: 60)
  • --schedule: Cron schedule expression (default: ”*/10 * * * *” = every 10 minutes)
  • --graph-name: Name of the graph to use (default: “email_assistant_hitl_memory_gmail”)
  • --include-read: Include emails marked as read (by default only unread emails are processed) (default: false)

How the Cron Works

The cron consists of two main components:

  1. src/email_assistant/cron.py: Defines a simple LangGraph graph that:

    • Calls the same fetch_and_process_emails function used by run_ingest.py
    • Wraps this in a simple graph so that it can be run as a hosted cron using LangGraph Platform

  2. src/email_assistant/tools/gmail/setup_cron.py: Creates the scheduled cron job:

    • Uses LangGraph SDK client.crons.create to create a cron job for the hosted cron.py graph

Managing Cron Jobs

To view, update, or delete existing cron jobs, you can use the LangGraph SDK:

from langgraph_sdk import get_client
 
# Connect to deployment
client = get_client(url="https://your-deployment-url.us.langgraph.app")
 
# List all cron jobs
cron_jobs = await client.crons.list()
print(cron_jobs)
 
# Delete a cron job
await client.crons.delete(cron_job_id)

How Gmail Ingestion Works

The Gmail ingestion process works in three main stages:

1. CLI Parameters → Gmail Search Query

CLI parameters are translated into a Gmail search query:

For example, running:

python run_ingest.py --email [email protected] --minutes-since 1440 --include-read

Creates a Gmail API search query like:

(to:[email protected] OR from:[email protected]) after:1745432245

2. Search Results → Thread Processing

For each message returned by the search:

  1. The script obtains the thread ID
  2. Using this thread ID, it fetches the complete thread with all messages
  3. Messages in the thread are sorted by date to identify the latest message
  4. Depending on filtering options, it processes either:
    • The specific message found in the search (default behavior)
    • The latest message in the thread (when using --skip-filters)

3. Default Filters and --skip-filters Behavior

Default Filters Applied

Without --skip-filters, the system applies these three filters in sequence:

  1. Unread Filter (controlled by --include-read):

    • Default behavior: Only processes unread messages
    • With --include-read: Processes both read and unread messages
    • Implementation: Adds is:unread to the Gmail search query
    • This filter happens at the search level before any messages are retrieved

  2. Sender Filter:

    • Default behavior: Skips messages sent by your own email address
    • Implementation: Checks if your email appears in the “From” header
    • Logic: is_from_user = email_address in from_header
    • This prevents the assistant from responding to your own emails

  3. Thread-Position Filter:

    • Default behavior: Only processes the most recent message in each thread
    • Implementation: Compares message ID with the last message in thread
    • Logic: is_latest_in_thread = message["id"] == last_message["id"]
    • Prevents processing older messages when a newer reply exists

The combination of these filters means only the latest message in each thread that was not sent by you and is unread (unless --include-read is specified) will be processed.

Effect of --skip-filters Flag

When --skip-filters is enabled:

  1. Bypasses Sender and Thread-Position Filters:

    • Messages sent by you will be processed
    • Messages that aren’t the latest in thread will be processed
    • Logic: should_process = skip_filters or (not is_from_user and is_latest_in_thread)

  2. Changes Which Message Is Processed:

    • Without --skip-filters: Uses the specific message found by search
    • With --skip-filters: Always uses the latest message in the thread
    • Even if the latest message wasn’t found in the search results

  3. Unread Filter Still Applies (unless overridden):

    • --skip-filters does NOT bypass the unread filter
    • To process read messages, you must still use --include-read
    • This is because the unread filter happens at the search level

In summary:

  • Default: Process only unread messages where you’re not the sender and that are the latest in their thread
  • --skip-filters: Process all messages found by search, using the latest message in each thread
  • --include-read: Include read messages in the search
  • --include-read --skip-filters: Most comprehensive, processes the latest message in all threads found by search

Important Gmail API Limitations

The Gmail API has several limitations that affect email ingestion:

  1. Search-Based API: Gmail doesn’t provide a direct “get all emails from timeframe” endpoint

    • All email retrieval relies on Gmail’s search functionality
    • Search results can be delayed for very recent messages (indexing lag)
    • Search results might not include all messages that technically match criteria

  2. Two-Stage Retrieval Process:

    • Initial search to find relevant message IDs
    • Secondary thread retrieval to get complete conversations
    • This two-stage process is necessary because search doesn’t guarantee complete thread information

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