mirror of
https://gitcode.com/JianFeeeee/TrulyMEM-TrueHumanMEM.git
synced 2026-09-20 08:58:15 +00:00
1a394ddd2b09f41ad3b80410894a034780c86b7c
问题: - _init_graph 正确解析了用户 DB 路径,但未更新 self._db_path - web_api.py 的 create_server() 用 backend_server._db_path 创建 graph_db - 导致所有用户共用一个 CWD/graph_memory.db(回忆图谱页面数据混在一起) - 同时 jianf 的 config.json 首次创建时空 apikey,未正确写回 修复: - _init_graph 解析用户路径后,同步更新 self._db_path - 现在各用户 graph_db 和 config.json 完全隔离
TrulyMEM - TrueHumanMEM
📜 License: GNU General Public License v3.0 (GPLv3)
中文: README.md
Give AI self-awareness, plasticity, and a sense of proportion in long-term memory — The More Human Choice.
In a Nutshell
TrulyMEM gives memory authority back to the LLM. Using graph database (triplets) instead of the traditional messages array, the LLM autonomously decides what to remember and what to forget.
Quick Start
python trulymem_entry.py # from source
./dist/TrulyMEM # packaged binary
First run → TUI login screen → create/sign in → press F2 for API Key → start chatting
📖 Full guide: docs/en/quick_start.md
Features
| Feature | Description |
|---|---|
| 🧠 Graph Memory | Triplet storage, LLM autonomous navigation |
| 🔐 Multi-User | Isolated profiles + Admin/User roles |
| 🌐 Web UI | Embedded Flask server (thread mode) for knowledge graph browsing |
| 🎮 TUI | Textual-based terminal UI with F2 config panel |
| 📦 Single Binary | PyInstaller build, Web server embedded |
Documentation
| Document | Content |
|---|---|
| docs/en/quick_start.md | 🔥 Full setup guide (Web, multi-user, building) |
| docs/en/architecture.md | System architecture and design |
| docs/en/memory.md | Memory working mechanism |
| docs/en/persona.md | Persona Graph mechanism |
| docs/en/api.md | Backend API |
| docs/en/prompts.md | Prompt management |
Special Thanks
- Prof. Meiting Wang — Academic guidance
- 逝水秋生白 — Architecture support
- anzhitinglan — Testing resource support
- 崔莉萍老师 — Theoretical guidance
- Annie — Professional guidance
- 王梓沣、马悦华、隆梦婷 — Neuroscience theory support
License
GNU General Public License v3.0 (GPLv3)
Description
Languages
Python
63.5%
HTML
33.5%
Shell
1.6%
CSS
0.8%
C++
0.3%
Other
0.3%
