update: Readme

apps/docs/memory-api/features/content-cleaner.mdx

@@ -1,86 +0,0 @@
----
-title: "Cleaning and Categorizing"
-description: "Document Cleaning Summaries in supermemory"
-icon: "washing-machine"
----
-
-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
-{
-  "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
-{
-  "shouldLLMFilter": true,
-  "categories": ["positive", "negative", "neutral"],
-  "filterPrompt": "Analyze customer sentiment and identify key themes",
-}
-```
-
-### 2. Content Moderation
-```json
-{
-  "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.