Auto-Respond to Gmail Inquiries Using GPT-4o, Dumpling AI, and LangChain Agent

Introduction

Answering inbound emails manually is one of the most repetitive and time-consuming tasks in any business. Whether you’re handling sales inquiries, service questions, or general leads, response delays can cost you opportunities.

This automation solves that.

With this setup in n8n, every incoming email is:

• Analyzed in real time
  
• Classified as an “inquiry” or not using GPT-4o
  
• Understood and processed by a LangChain Agent
  
• Enriched with contextual data via Dumpling AI
  
• Replied to instantly with a personalized response — through Gmail
  

This gives you a fully autonomous AI-powered helpdesk that doesn’t just reply — it replies smartly, accurately, and at scale.

Let’s walk through every piece.

Step 1: Monitor Your Gmail Inbox for New Emails

Node: Watch Gmail for New Incoming Emails

What this does:
Checks your Gmail inbox every minute for any new messages.

Configuration:

• Connect your Gmail account via OAuth2
  
• Choose polling mode: every minute (can adjust frequency)

Why it matters:
This is your real-time trigger. The entire workflow begins the moment a new message lands in your inbox, no delay, no manual checks.

Step 2: Classify the Email Using GPT-4o

Node: Classify Email Type with GPT-4o

Goal:
Determine whether the email is actually an inquiry worth responding to.

Prompt sent to GPT-4o:

Classify the following email content. Determine if it is an enquiry.

If it is an enquiry, return only this word: enquiry

If it is not an enquiry, return only this word: false

Input used:
{{ $json.snippet }} (the email body preview from Gmail)

Why this step is smart:
You don’t want your automation responding to spam, receipts, newsletters, or calendar invites. This step filters only the real inquiries.

Mapping:

Step 3: Filter Out Non-Inquiries

Node: Only Proceed if Email is an Enquiry

Logic:
Checks whether GPT-4o returned the exact word “enquiry”.

If yes, the workflow continues. If not, it stops quietly.

Pro Tip:
You can later tag or forward non-inquiries elsewhere for archival or manual handling.

Mapping:

Step 4: Launch LangChain Agent to Handle the Reply

Node: LangChain Agent Handles Reply Logic

This is where it gets powerful.

The LangChain Agent:

• Reads the email snippet
  
• Searches for additional context via tools
  
• Generates a reply using GPT-4o-mini
  
• Stores short-term memory of the last 10 messages (optional)
  

Connected AI tools:

• Language Model: GPT-4o-mini
  
• Memory Buffer: Stores the last 10 messages for consistent tone or follow-up
  
• Dumpling AI Tool: Can search the web or docs for related context
  
• Gmail Tool: Sends the reply
  

System Prompt (Summary):

You are a helpful assistant. Use the search for information tool to search for users’ information. Use the Gmail tool to send the email.

Why this is essential:
Instead of replying with a template, this step generates personalized responses, based on email context, recent interactions, and external data — in one pass.

Step 5: Dumpling AI Enrichment (Optional but Powerful)

Node: Dumpling AI – Search for Relevant Info

This node feeds the incoming email into a Dumpling AI that can search the web, scrape documents, or find relevant data to enrich the response.

Use Case Examples:

• Someone asks “Do you offer monthly plans?” → Dumpling AI checks pricing page
  
• A lead says “Can you support Shopify integrations?” → Agent looks up documentation
  

Payload Sent:

{

  “messages”: [

    {

      “role”: “user”,

      “content”: “{{ $json.snippet }}”

    }

  ],

  “agentId”: “<your-agent-id>”,

  “parseJson”: “True”

}

Pro Tip:
You can customize your Dumpling AI to focus on helpdocs, blog content, or pricing FAQs, whatever matches your niche.

Step 6: Auto-Send the Final Reply via Gmail

Node: Send Email Response via Gmail

The LangChain Agent provides:

• The subject line
  
• The full reply message

This node:

• Sends the message to the original sender
  
• Uses your connected Gmail account
  
• Optionally adds a label or logs the message elsewhere

Why this closes the loop:
The person gets a real reply, in their inbox, within seconds, without you lifting a finger.

Bonus: Memory Buffer for Contextual Responses

Node: Memory Buffer (Past 10 Interactions)

This tracks recent email interactions so GPT can:

• Avoid repeating replies
  
• Reference prior conversations
  
• Maintain tone consistency

Workflow Summary

Here’s how this automation flows from start to finish:

1. Detect new email in Gmail
   
2. Classify it as an inquiry using GPT-4o
   
3. Run LangChain Agent to search, think, and generate reply
   
4. Enrich with Dumpling AI
   
5. Send reply via Gmail automatically

Conclusion: The Smartest Gmail Responder You’ve Ever Built

This is not a rule-based auto-responder.
It’s a complete, intelligent system that:

• Knows what to reply to (and what to ignore)
  
• Understands what the user is really asking
  
• Can search for information to improve accuracy
  
• Writes tailored responses with the tone and context that fits
  
• Sends back real replies, without human delay
  

This gives you:

• Faster turnaround time for leads and customers
  
• A more human, brand-aligned customer experience
  
• Less manual support work and inbox clutter

Ideas to Take It Further

• Add webhook logging to track replies in Airtable or Notion
  
• Feed high-priority inquiries into Slack for visibility
  
• Train a custom GPT model using your own documentation
  
• Route different types of emails to different LangChain agents (sales, support, billing)