Build a Facebook Messenger customer service AI chatbot with Google Gemini

🤖 Build a customer service AI chatbot for Facebook Messenger with Google Gemini

📌 Overview A streamlined Facebook Messenger chatbot powered by AI with conversation memory.
This is a simplified version designed for quick deployment, learning, and testing — not suitable for production environments.

Base workflows: Smart message batching AI-powered Facebook Messenger chatbot use Data Table
Smart human takeover & auto pause AI-powered Facebook Messenger chatbot

🎯 What This Workflow Does

✅ Core Features: Receives messages from Facebook Messenger via webhook
Processes user messages with Google Gemini AI
Maintains conversation context using Simple Memory node
Automatically responds with AI-generated replies
Handles webhook verification for Facebook setup
Send image or video to customer through Facebook Messenger

🔹 Simplified Approach: Memory**: Simple Memory node (10-message window)
Format**: Cleans text, strips markdown, truncates >1900 chars
Response**: Single message delivery

⚠️ Limitations & Trade-offs: No Smart Batching → fragmented user messages cause spam-like replies
No Human Takeover Detection → bot continues even when admin joins
Basic Memory Management → no persistence, not reliable in production
Basic Text Formatting → strips markdown, truncates brutally, no smart splitting

🚀 When to Upgrade Upgrade to full workflows when you need:
Production deployment with reliability & persistence
Analytics & tracking (query history, reports)
Professional formatting (bold, italic, lists, code blocks)
Handling long messages (>2000 chars)
Smart batching for fragmented inputs
Human handoff detection
Full conversation persistence

Key upgrades available: Smart message batching workflow
Smart human takeover workflow

⚙️ Setup Requirements

Facebook Setup Create Facebook App at developers.facebook.com
Add Messenger product
Configure webhook:
URL: https://your-domain.com/webhook/your-path
Verify token: secure string
Subscribe to: messages, messaging_postbacks
Generate Page Access Token
Copy token to "Set Context" node

n8n Setup Import workflow
Edit "Set Context" node → update page_access_token
Configure "Gemini Flash" node credentials
Deploy workflow (must be publicly accessible)

🔄 How It Works User Message → Facebook Webhook → Validation ↓ Set Context (extract user_id, message, token) ↓ Mark Seen → Show Typing ↓ AI Agent (Gemini + 10-message memory) ↓ Format Output (remove markdown, truncate) ↓ Send Response via Facebook API

🏗️ Architecture Overview

Section 1: Webhook & Initial Processing Facebook Webhook: handles GET (verification) & POST (messages)
Confirm Webhook: returns challenge / acknowledges receipt
Filters text messages only
Blocks echo messages from bot itself

Section 2: AI Processing with Memory Set Context: extracts user_id, message, token
Seen & Typing: user feedback
Conversation Memory: 10-message window, per-user isolation
Process Merged Message: AI Agent with Jenix persona
Gemini Flash: Google’s AI model for response generation

Section 3: Format & Delivery Cuts replies >2000 chars, strips markdown
Sends text via Facebook Graph API

🎨 Customisation Guide Bot Personality**: edit system prompt in "Process Merged Message" node
Memory**: adjust contextWindowLength (default 10), change sessionKey if needed
AI Model**: replace Gemini Flash with OpenAI, Anthropic Claude, or other LLMs

📌 Important Notes ⚠️ Production Warning: testing only, memory lost on n8n restart in queue mode
📊 No Analytics: no history storage, no reporting
🔧 Format Limitations: responses ≤1800 chars, markdown stripped, no complex formatting

🛠️ Troubleshooting Bot not responding** → check token, webhook accessibility, event subscriptions
Memory not working** → verify session key, ensure not in queue mode, restart workflow
Messages truncated** → adjust system prompt for conciseness, reduce response length

📜 License & Credits Created by: Nguyễn Thiệu Toàn (Jay Nguyen)
Email: me@nguyenthieutoan.com Website: nguyenthieutoan.com
n8n Creator: n8n.io/creators/nguyenthieutoan
Company: GenStaff