Cleaning and Categorizing

supermemory provides advanced configuration options to customize your content processing pipeline. At its core is an AI-powered system that can automatically analyze, categorize, and filter your content based on your specific needs.

Configuration Schema

{
  "shouldLLMFilter": true,
  "categories": ["feature-request", "bug-report", "positive", "negative"],
  "filterPrompt": "Analyze feedback sentiment and identify feature requests",
  "includeItems": ["critical", "high-priority"],
  "excludeItems": ["spam", "irrelevant"]
}

Core Settings

shouldLLMFilter

• Type: boolean
• Required: No (defaults to false)
• Description: Master switch for AI-powered content analysis. Must be enabled to use any of the advanced filtering features.

categories

• Type: string[]
• Limits: Each category must be 1-50 characters
• Required: No
• Description: Define custom categories for content classification. When specified, the AI will only use these categories. If not specified, it will generate 3-5 relevant categories automatically.

filterPrompt

• Type: string
• Limits: 1-750 characters
• Required: No
• Description: Custom instructions for the AI on how to analyze and categorize content. Use this to guide the categorization process based on your specific needs.

includeItems & excludeItems

• Type: string[]
• Limits: Each item must be 1-20 characters
• Required: No
• Description: Fine-tune content filtering by specifying items to explicitly include or exclude during processing.

Content Processing Pipeline

When content is ingested with LLM filtering enabled:

1. Initial Processing

   • Content is extracted and normalized
   • Basic metadata (title, description) is captured

2. AI Analysis

   • Content is analyzed based on your filterPrompt
   • Categories are assigned (either from your predefined list or auto-generated)
   • Tags are evaluated and scored

3. Chunking & Indexing

   • Content is split into semantic chunks
   • Each chunk is embedded for efficient search
   • Metadata and classifications are stored

Example Use Cases

1. Customer Feedback System

{
  "shouldLLMFilter": true,
  "categories": ["positive", "negative", "neutral"],
  "filterPrompt": "Analyze customer sentiment and identify key themes",
}

2. Content Moderation

{
  "shouldLLMFilter": true,
  "categories": ["safe", "needs-review", "flagged"],
  "filterPrompt": "Identify potentially inappropriate or sensitive content",
  "excludeItems": ["spam", "offensive"],
  "includeItems": ["user-generated"]
}

Important: All filtering features (categories, filterPrompt, includeItems, excludeItems) require shouldLLMFilter to be enabled. Attempting to use these features without enabling shouldLLMFilter will result in a 400 error.