Get Started
Back to Templates

Build a Facebook Messenger customer service AI chatbot with Google Gemini

Created by

Created by: Nguyễn Thiệu Toàn (Jay Nguyen) || nguyenthieutoan

Nguyễn Thiệu Toàn (Jay Nguyen)

Last update

Last update a day ago

Categories

Share

🤖 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:

🎯 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:

  1. No Smart Batching → fragmented user messages cause spam-like replies
  2. No Human Takeover Detection → bot continues even when admin joins
  3. Basic Memory Management → no persistence, not reliable in production
  4. 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:

⚙️ Setup Requirements

Facebook Setup

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

n8n Setup

  1. Import workflow
  2. Edit "Set Context" node → update page_access_token
  3. Configure "Gemini Flash" node credentials
  4. 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)