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RecallWeaver (织忆)

Local memory for evolving AI agents.

Python 3.11+ MIT License PyPI version

纯本地、零 Docker、无向量库,基于 SQLite 的 AI 动态记忆引擎。

Core Features

  • 双时间戳时空图谱:记录事实演变,支持历史回溯。
  • 动态遗忘打分池:指数衰减评分,过滤低价值噪音。
  • 混合检索:FTS5 trigram 全文检索与图谱召回、重排。

Benchmarks

指标 结果
长稳测试 1,800 秒,50 并发,0 死锁
P99 延迟 10.5 ms
检索 Precision / Recall 1.0 / 1.0(100 组评测数据)

基准结果来自项目当前记录,实际表现取决于硬件、SQLite 版本和数据集。

Quick Start

python -m pip install recallweaver

当前发行元数据要求 Python 3.11.9。

from recallweaver import RecallWeaverAPI
api = RecallWeaverAPI("recallweaver.db")
api.add_memory("我对花生过敏", tenant_id="user-1")
memories = api.recall("过敏", limit=3, tenant_id="user-1")
print(memories[0].content if memories else "无相关记忆")

DSH 桌宠接入

安装 DSH 插件依赖并注册 Cordis 插件:

python -m pip install recallweaver==1.2.1

在 DSH profile 的 cordis.patch.yml 中加入:

- insert:
    - id: recallweaver-memory
      name: recallweaver-dsh
      inject: [systemPrompt]
      config:
        python: python
        timeoutMs: 10000

插件从当前会话读取最新用户消息,在本地写入并召回记忆,然后将结果加入 System Prompt。配置 RECALLWEAVER_PYTHON 可指定 Python 解释器; RECALLWEAVER_DB_PATH 可指定 SQLite 文件路径。

完整安装步骤与配置说明见 DSH 桌宠接入指南。

Disclaimer

本项目仅供学习、研究和合法用途,不构成法律、医疗或其他专业建议。用户应 自行评估并负责其输入数据、数据库备份与访问控制,以及基于 AI 输出采取的 任何行动。项目按现状提供,不保证数据永不丢失、输出准确或适用于特定用途。 使用者应遵守适用法律、服务条款及他人权利;请勿输入未获授权的敏感信息。

Architecture

src/recallweaver/
├── api.py
├── db.py
├── memory_manager.py
├── graph.py
├── retrieval.py
├── decay_engine.py
├── server.py
├── extraction/
├── migrations/
└── observability/

架构决策记录见 docs/adr/。

License

MIT

Metadata

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