How to Build an AI Agent to Auto Reply to Facebook Comments (Save 7 Hours/Week) - n8n Tutorial
🤖 Learn how I built an AI-powered Facebook comment moderator that saves me 7+ hours every week! In this complete tutorial, I'll show you how to create an automated system using n8n, FastAPI, and Claude AI to intelligently respond to, moderate, and manage Facebook comments.
📂 PROJECT FILES:
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🚀 SCALE YOUR AGENCY:
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⏰ TIMESTAMPS:
00:00 - Introduction & System Overview
00:42 - FastAPI & DSPy Framework Setup
02:14 - n8n Workflow Components Explained
03:11 - Human-in-the-Loop Safety Process
03:50 - Live n8n Workflow Demo
05:30 - Live Comment Processing Demo
08:12 - Business Rules & Prompt Optimization
09:18 - Training Data & Learning System
12:47 - n8n Technical Walkthrough Begins
13:04 - Facebook API Integration
14:22 - Post ID Processing & Database Setup
15:33 - FastAPI & Railway Hosting Setup
17:02 - PostgreSQL Database Deep Dive
18:04 - Comment Filtering & Processing
19:11 - Loop Processing & Batch Handling
20:15 - Google Sheets Integration
20:36 - Feedback Processing System
22:32 - Training Data Storage & Management
23:48 - Final Execution & API Endpoints
24:32 - Project Insights & Non-Technical Approach
🔧 WHAT YOU'LL LEARN:
✅ Set up Facebook API integration with n8n
✅ Build intelligent comment classification system
✅ Create automated response generation with Claude AI
✅ Implement human approval workflow
✅ Set up PostgreSQL database for training data
✅ Deploy FastAPI backend with Railway hosting
✅ Configure Slack notifications for daily reports
💡 KEY FEATURES:
Processes 200-300 comments weekly automatically
Handles inappropriate content deletion
Generates contextual responses for customer inquiries
Learns from approved responses over time
Maintains brand safety with human oversight
Works for both Facebook and Instagram (adaptable)
🛠️ TECH STACK:
n8n (workflow automation)
FastAPI (Python web framework)
DSPy (Stanford NLP framework)
Claude AI (Anthropic)
PostgreSQL database
Railway hosting
Facebook Graph API
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