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#

text

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#

bash

# 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#

bash

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 KeywordsTagDefault Importance决定, 选择, 采用, 改为, 升级, 弃用decision7项目名, 产品名, 公司, 版本, 价格fact6喜欢, 偏好, 习惯, 不要, 推荐preference6技术栈, 框架, 语言, 数据库, API, 部署tech5问题, bug, 报错, 异常, 失败problem5

AGENTS.md Integration#

Add to your AGENTS.md (or the relevant agent's config):

markdown

## 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#

text

~/.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:X tags 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.