Long-Term Memory — AI 记忆中间件
Overview
为 AI Agent 提供 长期记忆 能力，解决大模型「过目就忘」的痛点。自动捕获关键事实、决策、用户偏好和项目上下文，支持语义搜索和向量检索，让 AI 真正记住你。
🚀 版本与定价
社区版（开源免费）
当前版本为开源社区版，适合个人开发者本地自部署。 ✅ 所有功能无限制使用 ✅ 无记忆条数限制 ✅ 无需注册、无需付费
💼 企业版 / 技术支持服务
本地部署遇到困难？需要定制化配置？我来帮你搞定。
| 服务项目 | 价格 | 说明 |
|---|---|---|
| 远程部署 | ¥199/次 | 远程帮你搭好完整环境，跑通持久化记忆 |
| 定制开发 | 另议 | 根据需求定制功能、对接现有系统 |
| 技术咨询 | 另议 | 架构设计、方案评审、性能优化 |
📞 联系我们：微信 18923788188（王工）
☁️ MaaS 云服务（2026年6月公测预告）
即插即用的云端记忆服务，无需部署，开箱即用。
| 套餐 | 价格 | 容量 | 功能 |
|---|---|---|---|
| 公测版 | 免费 | 前100条免费 | 云端API、基础记忆存储 |
| Starter | ¥49/月 | 1万条记忆，3个项目 | 标签分类、项目隔离 |
| Pro | ¥199/月 | 10万条记忆，无限项目 | 向量检索、语义搜索 |
| Enterprise | 定制报价 | 无限容量 | 私有部署、SLA保障、专属存储、审计日志 |
⏰ 公测时间：2026年6月 🔗 支付方式：支付宝（微信：18923788188 王工）
Core Workflow
Session Start → 1. inject_context() → get relevant history
Session Run → 2. remember() / auto_capture() → save important info
Session End → 3. summarize() → compress session into memory
Scripts
scripts/memory_engine.py — Core engine
# Save a memory
python3 scripts/memory_engine.py remember "决定: 使用FastAPI框架" --tags decision,tech --importance 8 --project saas
# Search memories
python3 scripts/memory_engine.py search "技术方案" --tags tech --min-imp 5
# Get context for prompt injection
python3 scripts/memory_engine.py inject "当前任务描述..."
# Auto-capture from text (scans for decisions, facts, preferences)
python3 scripts/memory_engine.py auto "我们决定采用SQLite作为数据库，技术栈为FastAPI..."
# Session management
python3 scripts/memory_engine.py session-start # returns session_id + context
python3 scripts/memory_engine.py session-end <session_id> --summary "..."
# Stats
python3 scripts/memory_engine.py stats
scripts/setup.py — One-time workspace setup
python3 scripts/setup.py
Memory Structure
- Storage: SQLite + FTS5 full-text search
- Fields: content, tags[], importance(1-10), source, session, project, timestamps
- Tags: Tag memories for filtering (e.g.,
decision,tech,user,project:X) - Importance: 1-10 scale. 8+ = key fact, 6-7 = useful context, 1-5 = normal
Auto-Capture
The engine automatically detects important content from text:
| Trigger Keywords | Tag | Default Importance |
|---|---|---|
| 决定, 选择, 采用, 改为, 升级, 弃用 | decision |
7 |
| 项目名, 产品名, 公司, 版本, 价格 | fact |
6 |
| 喜欢, 偏好, 习惯, 不要, 推荐 | preference |
6 |
| 技术栈, 框架, 语言, 数据库, API, 部署 | tech |
5 |
| 问题, bug, 报错, 异常, 失败 | problem |
5 |
AGENTS.md Integration
Add to your AGENTS.md (or the relevant agent's config):
## Long-Term Memory Rules
1. On session start: Run `python3 scripts/memory_engine.py inject "current task"` and use the output as context
2. When user shares important info: Use `remember()` to save it
3. Track decisions: Save key decisions with `--importance 8` and tag `decision`
4. Before answering "remember" or "previous" questions: Search memory first
5. On session end: Summarize key outcomes for next session
Data Storage
~/.openclaw/workspace/long-term-memory/
├── memory.db # SQLite database
├── config.json # Configuration
└── current_context.md # Last built context (for debugging)
Tips
- Be selective: Not everything needs remembering. Save decisions, preferences, problems.
- Use tags:
project:Xtags make cross-project memory searchable. - Importance matters: 8+ for permanent facts, 5-7 for useful context, 3-4 for temporary.
- Search before answering: If user asks "do you remember X?", search memory first.