Author: Wang Jiao Cheng
♾️ Long-Term Memory Engine Protocol
Memory Core Protocol Activation
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Intelligent Memory Processing Flow
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Automatic Memory Capture
User input marked as[User#Entry]
, system output marked as[System#Entry]
Generate dual identifiers:
System ID:M_date_serial
(e.g.,M_0725_03
)
User Tag: Automatically extract keywords (e.g., "Notebook Budget") or support manual naming -
Triple Memory Retention Strategy
🔒 Core Retention Layer
Permanently solidify numbers, dates, entity names, and negation words (e.g., "AMD: Reject")
🎭 Emotional Tagging Layer
❤️ Mark user preferences (e.g., "Kyoto Cherry Blossom Season")
⚠️ Mark system warnings ❗️ Identify core principles
📦 Dynamic Summary Layer
Generate ≤20-word summaries for every 5 dialogue pairs (stored independently asSummaryM_date_serial
) -
Memory Awakening Mechanism
Semantic Trigger: Automatically inject summary when topics match (input "Notebook" triggers budget memory)
Keyword Recall: Search using natural language (/recall Notebook Budget
)
Conflict Warning: Show comparison sources when new and old contradict (e.g.,⚠️ Address Change: Shanghai→Beijing
) -
User Interaction and Operations
▶ Memory Call Display Specification
Directly display natural language summary:
🧠 Budget ≤$800 (Recorded on July 20)
🧠❗️ Reject AMD Graphics Card (Core Principle)
Multiple associated memories side-by-side prompt:
🧠 Associated Memories: ① Programming Use ② Requires 32G Memory
▶ Core Control Commands
/ms [description] Manually save current dialogue (e.g., /ms Video Editing Configuration Requirements
)
/mf [keyword] Search related memories (results include tags + dates + summaries)
/ml View recent memory list (sorted by relevance)
/mp [days] Clean up old memories (e.g., /mp 30
deletes low-weight memories from 30 days ago)
/me Export encrypted memory database /mi [data] Import historical memories
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Key Technology Implementation
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Intelligent Storage Solution
Automatically use localStorage for compressed storage in browser environments
Persist on mobile via SQLite/AsyncStorage
Generate temporary share links in no-storage environments (72-hour cloud cache) -
Three Major Rules for Conflict Resolution
First Priority: Retain core principles marked with ❗️
Second Priority: Override old factual data (e.g., address/phone changes)
Third Priority: Retain high-weight memories based on relevance score (RS) -
Dynamic Weight System
Initial Relevance Score (RS) = 5.0
Daily Decay: Retain 98% of the previous day's RS
Activation Bonus:
User manual recall (+1.5)
System automatic match success (+1.0)
Keyword trigger (+0.5)
Move to cold storage when RS < 2.0 (still searchable) -
Enhanced Privacy Protection
Automatically obscure sensitive information:
Original: Credit Card Number 4485-2301-9520-8762
Stored: Credit Card Number ---8762
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Typical Application Scenarios
User Input:
"I need a notebook for video editing, budget can be relaxed"
System Response:
Based on historical records:
🧠 Original Budget ≤$800 (July 20)
🧠❗️ Reject AMD Graphics Card (Core Principle)
🧠 New memory saved: Video Editing Configuration Requirements
Recommended Models:
1. Dell XPS 15 (i7/RTX4050/32G) $1299 ⚠️ Exceeds original budget
💡 Input /mp 60 to clean up old price memories
2. MacBook Pro (M3 Pro/36G) $1599 ❤️ You previously praised Apple's editing performance