> ## Documentation Index
> Fetch the complete documentation index at: https://supermemory.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Cleaning and Categorizing

> Document Cleaning Summaries in supermemory

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

```json theme={null}
{
  "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

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

### 2. Content Moderation

```json theme={null}
{
  "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.