Overview
This workflow automates spam moderation in Discord channels by leveraging AI-powered text classification and human-in-the-loop processes. It ensures efficient, accurate detection and handling of spam messages, reducing manual workload for moderators.
Key Features
- AI Spam Detection: Utilizes LangChain's text classifier and OpenAI language models to analyze and flag potential spam messages in real time.
- Human-in-the-Loop: Escalates ambiguous cases for manual review, ensuring high accuracy and minimizing false positives.
- Automated User Warnings: Automatically sends warnings to users identified as spammers, with options for one-time or repeated notifications.
- Batch Processing: Groups and processes messages by user, optimizing moderation efficiency.
- Duplicate Removal: Ensures only unique messages are processed, reducing redundancy.
Benefits
- Time Savings: Significantly reduces manual moderation efforts by automating repetitive tasks.
- Improved Accuracy: Combines AI and human judgment for balanced, reliable moderation.
- Scalability: Handles large volumes of messages and users without performance loss.
Use Cases
- Moderating large Discord communities with high message traffic.
- Ensuring community guidelines are upheld with minimal moderator intervention.
- Reducing spam and maintaining a positive user experience.
Integrations & Processes
- Integrates Discord for message retrieval and user notifications.
- Employs LangChain and OpenAI for advanced text analysis.
- Utilizes n8n's batch and code nodes for workflow logic and efficiency.
