Feature Request: Enhanced Memory Management System

• Full Memory Export
  Add the ability to export all memories stored in the chat memory area. Currently there's no way to bulk export, which means if memories get lost, corrupted, or need to be transferred, users are stuck. Export should support common formats (JSON, CSV, plain text) so memories can be backed up, migrated between conversations, or imported into other tools.

• Hierarchical Memory Organization
  Implement a structured database-style organization system for memories:

  Category → Subcategory → Subcategory → Data

Example:

Personal → Preferences → Food → Spicy, loves ghost peppers

Work → Projects → Current → Q2 marketing rollout

This would make memories searchable, scannable, and actually useful instead of a flat list that grows unwieldy over time.

• Duplicate Detection & Consolidation
  Add a memory scan feature that:

  • Flags duplicate or near-duplicate entries

  • Suggests consolidating overlapping memories into a single, more complete entry

  • Allows one-click merge for approved consolidations

Example: If one memory says "likes spicy food" and another says "enjoys ghost peppers," the system could suggest merging into "likes spicy food, especially ghost peppers."

• Contradiction Resolution
  Detect when memories conflict and prompt the user to clarify or update:

  • "Memory A says you live in Texas, Memory B says you moved to Colorado. Which is current?"

  • Auto-flag outdated entries for review

  • Allow manual override or date-stamping so newer information takes priority

• Memory Decay & Archiving
  Not everything needs to live in active memory forever. Add the ability to:

  • Mark memories as "archived" — still stored, but not actively pulled into context unless explicitly referenced

  • Set automatic decay rules (e.g., after 90 days of no relevance, prompt to archive or review)

  • Search and retrieve archived memories when needed, so nothing is truly lost

  • Keep active memory lean and relevant while preserving the full history in a separate archive layer

This prevents memory bloat, keeps the AI focused on what actually matters right now, and lets users revisit older context without it cluttering every conversation.