Workflow Overview
Workflow Overview This advanced n8n workflow provides intelligent email automation with AI-generated responses. It combines four core functions: Monitors incoming emails via IMAP (e.g., SOGo) Sends instant Telegram notifications for all new emails Uses AI (Ollama LLM) to generate contextual, personalized auto-replies 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. 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 Install Ollama on your system: Visit https://ollama.ai and download the installer for your OS Follow installation instructions for your platform Download the llama3.1 model: ollama pull llama3.1 Verify the model is available: ollama list Start Ollama service (if not already running): ollama serve 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 Navigate to n8n Credentials section 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 Create a new SMTP credential in n8n 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 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 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) Add Telegram API credential in n8n: Credential Type: Telegram API Access Token: Your bot token from BotFather Step 5: Configure Ollama API Credential In n8n Credentials section, create a new Ollama API credential 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) Test the connection to ensure n8n can reach Ollama Step 6: Import and Configure Workflow Import the workflow JSON into your n8n instance 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 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 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 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 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 Send various types of test emails: Different topics (inquiry, complaint, information request) Various email lengths (short, medium, long) Different languages if applicable Review AI-generated responses: Check if topic identification is accurate Verify response appropriateness Ensure tone is professional 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 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 Monitor initial production runs: Review first few auto-replies carefully Check Telegram notifications for any issues Verify SMTP delivery rates Set up monitoring: Enable n8n workflow error notifications Monitor Ollama resource usage Check email server logs periodically How to Use Normal Operation Once activated, the workflow operates fully automatically: Email Monitoring: The workflow continuously checks your IMAP inbox for new messages based on the configured polling interval or trigger schedule. 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 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 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 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 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: Open the "Dedicate Filtering As No-Response" node 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: Open the "Basic LLM Chain" node Modify the prompt text in the "text" parameter 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: Open "Send Notification from Incoming Email" node Modify the "text" parameter 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: Open "Send Notification from Response" node Modify to include additional information 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: 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] Or use language-specific conditions in the filtering node Priority-Based Responses Generate different responses based on sender importance: Add an IF node after filtering to check sender domain Route VIP emails to a different LLM chain with priority messaging Standard emails use the normal AI chain Response Logging To maintain a record of all AI interactions: Add a database node (PostgreSQL, MySQL, etc.) after the auto-reply node Store: timestamp, sender, subject, AI response, delivery status Use for compliance, analytics, or training data A/B Testing AI Prompts Test different prompt variations: Create multiple LLM Chain nodes with different prompts Use a randomizer or round-robin approach Compare response quality and user feedback 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 Workflow Architecture Node Descriptions Check Incoming Emails - IMAP: Polls email server at regular intervals to retrieve new messages from the configured mailbox. Send Notification from Incoming Email: Immediately sends formatted notification to Telegram for every new email detected, regardless of spam status. Dedicate Filtering As No-Response: Evaluates emails against spam filter criteria to determine if AI processing should occur. No Operation: Placeholder node for filtered emails that should not receive an auto-reply (spam, newsletters, automated messages). Ollama Model: Provides the AI language model (llama3.1) used for natural language processing and response generation. Basic LLM Chain: Executes the AI prompt against the email content to generate contextual auto-reply text. Send Auto-Response in SMTP: Sends the AI-generated acknowledgment email back to the original sender via SMTP server. Send Notification from Response: Sends confirmation to Telegram showing the auto-reply was successfully sent, including the AI-generated content. AI Processing Pipeline Email Content Extraction: Email body text is extracted from IMAP data Context Loading: Email content is passed to LLM with prompt instructions Topic Analysis: AI identifies main subject or purpose in 2-4 words Template Population: AI fills response template with identified topic Output Formatting: Response is formatted and cleaned for email delivery Quality Assurance: n8n validates response before sending. An n8n automation workflow template by Vigh Sandor.
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