Monitor emails & send AI-generated auto-replies with Ollama & Telegram alerts

Workflow Overview

This advanced n8n workflow provides intelligent email automation with AI-generated responses. It combines four core functions:

1. Monitors incoming emails via IMAP (e.g., SOGo)
2. Sends instant Telegram notifications for all new emails
3. Uses AI (Ollama LLM) to generate contextual, personalized auto-replies
4. Sends confirmation notifications when auto-replies are sent

Unlike traditional auto-responders, this workflow analyzes email content and creates unique, relevant responses for each message.

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Setup Instructions

Prerequisites

Before setting up this workflow, ensure you have:

• An n8n instance (self-hosted or cloud) with AI/LangChain nodes enabled
• IMAP email account credentials (e.g., SOGo, Gmail, Outlook)
• SMTP server access for sending emails
• Telegram Bot API credentials
• Telegram Chat ID where notifications will be sent
• Ollama installed locally or accessible via network (for AI model)
• The llama3.1 model downloaded in Ollama

Step 1: Install and Configure Ollama

Local Installation

1. Install Ollama on your system:

   • Visit https://ollama.ai and download the installer for your OS
   • Follow installation instructions for your platform

2. Download the llama3.1 model:

   ollama pull llama3.1
   

3. Verify the model is available:

   ollama list
   

4. Start Ollama service (if not already running):

   ollama serve
   

5. Test the model:

   ollama run llama3.1 "Hello, world!"
   

Remote Ollama Instance

If using a remote Ollama server:

• Note the server URL (e.g., http://192.168.1.100:11434)
• Ensure network connectivity between n8n and Ollama server
• Verify firewall allows connections on port 11434

Step 2: Configure IMAP Credentials

1. Navigate to n8n Credentials section
2. Create a new IMAP credential with the following information:
   • Host: Your IMAP server address
   • Port: Usually 993 for SSL/TLS
   • Username: Your email address
   • Password: Your email password or app-specific password
   • Enable SSL/TLS: Yes (recommended)
   • Security: Use STARTTLS or SSL/TLS

Step 3: Configure SMTP Credentials

1. Create a new SMTP credential in n8n
2. Enter the following details:
   • Host: Your SMTP server address (e.g., Postfix server)
   • Port: Usually 587 (STARTTLS) or 465 (SSL)
   • Username: Your email address
   • Password: Your email password or app-specific password
   • Secure connection: Enable based on your server configuration
   • Allow unauthorized certificates: Enable if using self-signed certificates

Step 4: Configure Telegram Bot

1. Create a Telegram bot via BotFather:

   • Open Telegram and search for @BotFather
   • Send /newbot command
   • Follow instructions to create your bot
   • Save the API token provided by BotFather

2. Obtain your Chat ID:

   • Method 1: Send a message to your bot, then visit: https://api.telegram.org/bot<YOUR_BOT_TOKEN>/getUpdates
   • Method 2: Use a Telegram Chat ID bot like @userinfobot
   • Method 3: For group chats, add the bot to the group and check the updates
   • Note: Group chat IDs are negative numbers (e.g., -1234567890123)

3. Add Telegram API credential in n8n:

   • Credential Type: Telegram API
   • Access Token: Your bot token from BotFather

Step 5: Configure Ollama API Credential

1. In n8n Credentials section, create a new Ollama API credential
2. Configure based on your setup:
   • For local Ollama: Base URL is usually http://localhost:11434
   • For remote Ollama: Enter the server URL (e.g., http://192.168.1.100:11434)
3. Test the connection to ensure n8n can reach Ollama

Step 6: Import and Configure Workflow

1. Import the workflow JSON into your n8n instance
2. Update the following nodes with your specific information:

Check Incoming Emails Node

• Verify IMAP credentials are connected
• Configure polling interval (optional):
  • Default behavior checks on workflow trigger schedule
  • Can be set to check every N minutes
• Set mailbox folder if needed (default is INBOX)

Send Notification from Incoming Email Node

• Update chatId parameter with your Telegram Chat ID
• Replace -1234567890123 with your actual chat ID
• Customize notification message template if desired
• Current format includes: Sender, Subject, Date-Time

Dedicate Filtering As No-Response Node

• Review spam filter conditions:
  • Blocks emails from addresses containing "noreply" or "no-reply"
  • Blocks emails with "newsletter" in subject line (case-insensitive)
• Add additional filtering rules as needed:
  • Block specific domains
  • Filter by keywords
  • Whitelist/blacklist specific senders

Ollama Model Node

• Verify Ollama API credential is connected
• Confirm model name: llama3.1:bf230501 (or adjust to your installed version)
• Context window set to 4096 tokens (sufficient for most emails)
• Can be adjusted based on your needs and hardware capabilities

Basic LLM Chain Node

• Review the AI prompt engineering (pre-configured but customizable)
• Current prompt instructs the AI to:
  • Read the email content
  • Identify main topic in 2-4 words
  • Generate a professional acknowledgment response
  • Keep responses consistent and concise
• Modify prompt if you want different response styles

Send Auto-Response in SMTP Node

• Verify SMTP credentials are connected
• Check fromEmail uses correct email address:
  • Currently set to {{ $('Check Incoming Emails - IMAP (example: SOGo)').item.json.to }}
  • This automatically uses the recipient address (your mailbox)
• Subject automatically includes "Re: " prefix with original subject
• Message text comes from AI-generated content

Send Notification from Response Node

• Update chatId parameter (same as first notification node)
• This sends confirmation that auto-reply was sent
• Includes original email details and the AI-generated response text

Step 7: Test the Workflow

1. Perform initial configuration test:

   • Test Ollama connectivity: curl http://localhost:11434/api/tags
   • Verify all credentials are properly configured
   • Check n8n has access to required network endpoints

2. Execute a test run:

   • Click "Execute Workflow" button in n8n
   • Send a test email to your monitored inbox
   • Use a clear subject and body for better AI response

3. Verify workflow execution:

   • First Telegram notification received (incoming email alert)
   • AI processes the email content
   • Auto-reply is sent to the original sender
   • Second Telegram notification received (confirmation with AI response)
   • Check n8n execution log for any errors

4. Verify email delivery:

   • Check if auto-reply arrived at sender's inbox
   • Verify it's not marked as spam
   • Review AI-generated content for appropriateness

Step 8: Fine-Tune AI Responses

1. Send various types of test emails:

   • Different topics (inquiry, complaint, information request)
   • Various email lengths (short, medium, long)
   • Different languages if applicable

2. Review AI-generated responses:

   • Check if topic identification is accurate
   • Verify response appropriateness
   • Ensure tone is professional

3. Adjust the prompt if needed:

   • Modify topic word count (currently 2-4 words)
   • Change response template
   • Add language-specific instructions
   • Include custom sign-offs or branding

Step 9: Activate the Workflow

1. Once testing is successful and AI responses are satisfactory:

   • Toggle the workflow to "Active" state
   • The workflow will now run automatically on the configured schedule

2. Monitor initial production runs:

   • Review first few auto-replies carefully
   • Check Telegram notifications for any issues
   • Verify SMTP delivery rates

3. Set up monitoring:

   • Enable n8n workflow error notifications
   • Monitor Ollama resource usage
   • Check email server logs periodically

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How to Use

Normal Operation

Once activated, the workflow operates fully automatically:

1. Email Monitoring: The workflow continuously checks your IMAP inbox for new messages based on the configured polling interval or trigger schedule.

2. Immediate Incoming Notification: When a new email arrives, you receive an instant Telegram notification containing:

   • Sender's email address
   • Email subject line
   • Date and time received
   • Note indicating it's from IMAP mailbox

3. Intelligent Filtering: The workflow evaluates each email against spam filter criteria:

   • Emails from "noreply" or "no-reply" addresses are filtered out
   • Emails with "newsletter" in the subject line are filtered out
   • Filtered emails receive notification but no auto-reply
   • Legitimate emails proceed to AI response generation

4. AI Response Generation: For emails that pass the filter:

   • The AI reads the full email content
   • Analyzes the main topic or purpose
   • Generates a personalized acknowledgment
   • Creates a professional response that:
     • Thanks the sender
     • References the specific topic
     • Promises a personal follow-up
     • Maintains professional tone

5. Automatic Reply Delivery: The AI-generated response is sent via SMTP to the original sender with:

   • Subject line: "Re: [Original Subject]"
   • From address: Your monitored mailbox
   • Body: AI-generated contextual message

6. Response Confirmation: After the auto-reply is sent, you receive a second Telegram notification showing:

   • Original email details (sender, subject, date)
   • The complete AI-generated response text
   • Confirmation of successful delivery

Understanding AI Response Generation

The AI analyzes emails intelligently:

Example 1: Business Inquiry

Incoming Email: "I'm interested in your consulting services for our Q4 project..."
AI Topic Identification: "consulting services"
Generated Response: "Dear Correspondent! Thank you for your message regarding consulting services. I will respond with a personal message as soon as possible. Have a nice day!"

Example 2: Technical Support

Incoming Email: "We're experiencing issues with the API integration..."
AI Topic Identification: "API integration issues"
Generated Response: "Dear Correspondent! Thank you for your message regarding API integration issues. I will respond with a personal message as soon as possible. Have a nice day!"

Example 3: General Question

Incoming Email: "Could you provide more information about pricing?"
AI Topic Identification: "pricing information"
Generated Response: "Dear Correspondent! Thank you for your message regarding pricing information. I will respond with a personal message as soon as possible. Have a nice day!"

Customizing Filter Rules

To modify which emails receive AI-generated auto-replies:

1. Open the "Dedicate Filtering As No-Response" node
2. Modify existing conditions or add new ones:

Block specific domains:

{{ $json.from.value[0].address }}
Operation: does not contain
Value: @spam-domain.com

Whitelist VIP senders (only respond to specific people):

{{ $json.from.value[0].address }}
Operation: contains
Value: @important-client.com

Filter by subject keywords:

{{ $json.subject.toLowerCase() }}
Operation: does not contain
Value: unsubscribe

Combine multiple conditions:

• Use AND logic (all must be true) for stricter filtering
• Use OR logic (any can be true) for more permissive filtering

Customizing AI Prompt

To change how the AI generates responses:

1. Open the "Basic LLM Chain" node
2. Modify the prompt text in the "text" parameter
3. Current structure:
   • Context setting (read email, identify topic)
   • Output format specification
   • Rules for AI behavior

Example modifications:

Add company branding:

Return only this response, filling in the [TOPIC]:

Dear Correspondent! 
Thank you for reaching out to [Your Company Name] regarding [TOPIC]. 
I will respond with a personal message as soon as possible. 
Best regards,
[Your Name]
[Your Company Name]

Make it more casual:

Return only this response, filling in the [TOPIC]:

Hi there! 
Thanks for your email about [TOPIC]. 
I'll get back to you personally soon. 
Cheers!

Add urgency classification:

Read the email and classify urgency (Low/Medium/High).
Identify the main topic.

Return:

Dear Correspondent!
Thank you for your message regarding [TOPIC].
Priority: [URGENCY]
I will respond with a personal message as soon as possible.

Customizing Telegram Notifications

Incoming Email Notification:

1. Open "Send Notification from Incoming Email" node
2. Modify the "text" parameter
3. Available variables:
   • {{ $json.from }} - Full sender info
   • {{ $json.from.value[0].address }} - Sender email only
   • {{ $json.from.value[0].name }} - Sender name (if available)
   • {{ $json.subject }} - Email subject
   • {{ $json.date }} - Date received
   • {{ $json.textPlain }} - Email body (use cautiously for privacy)
   • {{ $json.to }} - Recipient address

Response Confirmation Notification:

1. Open "Send Notification from Response" node
2. Modify to include additional information
3. Reference AI response: {{ $('Basic LLM Chain').item.json.text }}

Monitoring and Maintenance

Daily Monitoring

• Check Telegram Notifications: Review incoming email alerts and response confirmations
• Verify AI Quality: Spot-check AI-generated responses for appropriateness
• Email Delivery: Confirm auto-replies are being delivered (not caught in spam)

Weekly Maintenance

• Review Execution Logs: Check n8n execution history for errors or warnings
• Ollama Performance: Monitor resource usage (CPU, RAM, disk space)
• Filter Effectiveness: Assess if spam filters are working correctly
• Response Quality: Review multiple AI responses for consistency

Monthly Maintenance

• Update Ollama Model: Check for new llama3.1 versions or alternative models
• Prompt Optimization: Refine AI prompt based on response quality observations
• Credential Rotation: Update passwords and API tokens for security
• Backup Configuration: Export workflow and credentials (securely)

Advanced Usage

Multi-Language Support

If you receive emails in multiple languages:

1. Modify the AI prompt to detect language:

Detect the email language.
Generate response in the SAME language as the email.

If English: [English template]
If Hungarian: [Hungarian template]
If German: [German template]

1. Or use language-specific conditions in the filtering node

Priority-Based Responses

Generate different responses based on sender importance:

1. Add an IF node after filtering to check sender domain
2. Route VIP emails to a different LLM chain with priority messaging
3. Standard emails use the normal AI chain

Response Logging

To maintain a record of all AI interactions:

1. Add a database node (PostgreSQL, MySQL, etc.) after the auto-reply node
2. Store: timestamp, sender, subject, AI response, delivery status
3. Use for compliance, analytics, or training data

A/B Testing AI Prompts

Test different prompt variations:

1. Create multiple LLM Chain nodes with different prompts
2. Use a randomizer or round-robin approach
3. Compare response quality and user feedback
4. Optimize based on results

Troubleshooting

Notifications Not Received

Problem: Telegram notifications not appearing

Solutions:

• Verify Chat ID is correct (positive for personal chats, negative for groups)
• Check if bot has permissions to send messages
• Ensure bot wasn't blocked or removed from group
• Test Telegram API credential independently
• Review n8n execution logs for Telegram API errors

AI Responses Not Generated

Problem: Auto-replies sent but content is empty or error messages

Solutions:

• Check Ollama service is running: ollama list
• Verify llama3.1 model is downloaded: ollama list
• Test Ollama directly: ollama run llama3.1 "Test message"
• Review Ollama API credential URL in n8n
• Check network connectivity between n8n and Ollama
• Increase context window if emails are very long
• Monitor Ollama logs for errors

Poor Quality AI Responses

Problem: AI generates irrelevant or inappropriate responses

Solutions:

• Review and refine the prompt engineering
• Add more specific rules and constraints
• Provide examples in the prompt of good vs bad responses
• Adjust topic word count (increase from 2-4 to 3-6 words)
• Test with different Ollama models (e.g., llama3.1:70b for better quality)
• Ensure email content is being passed correctly to AI

Auto-Replies Not Sent

Problem: Workflow executes but emails not delivered

Solutions:

• Verify SMTP credentials and server connectivity
• Check fromEmail address is correct
• Review SMTP server logs for errors
• Test SMTP sending independently
• Ensure "Allow unauthorized certificates" is enabled if needed
• Check if emails are being filtered by spam filters
• Verify SPF/DKIM records for your domain

High Resource Usage

Problem: Ollama consuming excessive CPU/RAM

Solutions:

• Reduce context window size (from 4096 to 2048)
• Use a smaller model variant (llama3.1:8b instead of default)
• Limit concurrent workflow executions in n8n
• Add delay/throttling between email processing
• Consider using a remote Ollama instance with better hardware
• Monitor email volume and processing time

IMAP Connection Failures

Problem: Workflow can't connect to email server

Solutions:

• Verify IMAP credentials are correct
• Check if IMAP is enabled on email account
• Ensure SSL/TLS settings match server requirements
• For Gmail: enable "Less secure app access" or use App Passwords
• Check firewall allows outbound connections on IMAP port (993)
• Test IMAP connection using email client (Thunderbird, Outlook)

Workflow Not Triggering

Problem: Workflow doesn't execute automatically

Solutions:

• Verify workflow is in "Active" state
• Check trigger node configuration and schedule
• Review n8n system logs for scheduler issues
• Ensure n8n instance has sufficient resources
• Test manual execution to isolate trigger issues
• Check if n8n workflow execution queue is backed up

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Workflow Architecture

Node Descriptions

1. Check Incoming Emails - IMAP: Polls email server at regular intervals to retrieve new messages from the configured mailbox.

2. Send Notification from Incoming Email: Immediately sends formatted notification to Telegram for every new email detected, regardless of spam status.

3. Dedicate Filtering As No-Response: Evaluates emails against spam filter criteria to determine if AI processing should occur.

4. No Operation: Placeholder node for filtered emails that should not receive an auto-reply (spam, newsletters, automated messages).

5. Ollama Model: Provides the AI language model (llama3.1) used for natural language processing and response generation.

6. Basic LLM Chain: Executes the AI prompt against the email content to generate contextual auto-reply text.

7. Send Auto-Response in SMTP: Sends the AI-generated acknowledgment email back to the original sender via SMTP server.

8. Send Notification from Response: Sends confirmation to Telegram showing the auto-reply was successfully sent, including the AI-generated content.

AI Processing Pipeline

1. Email Content Extraction: Email body text is extracted from IMAP data
2. Context Loading: Email content is passed to LLM with prompt instructions
3. Topic Analysis: AI identifies main subject or purpose in 2-4 words
4. Template Population: AI fills response template with identified topic
5. Output Formatting: Response is formatted and cleaned for email delivery
6. Quality Assurance: n8n validates response before sending