init: first commit to Gitea mirror, update README with Docker quick start and new repo URL
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
P0lar1s
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README.md
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# Ombre Brain
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一个给提供给Claude 用的长期情绪记忆系统。基于 Russell 效价/唤醒度坐标打标，Obsidian 做存储层，MCP 接入，带遗忘曲线。
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A long-term emotional memory system for Claude. Tags memories using Russell's valence/arousal coordinates, stores them as Obsidian-compatible Markdown, connects via MCP, and has a forgetting curve.
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> **⚠️ 仓库临时迁移 / Repo temporarily moved**
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> GitHub 访问受限期间，代码暂时托管在 Gitea：
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> **https://git.p0lar1s.uk/P0lar1s/Ombre_Brain**
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> 下面的 `git clone` 地址请替换为上面这个。
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---
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## 快速开始 / Quick Start（Docker，推荐）
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> 这是最简单的方式，不需要装 Python，不需要懂命令行，跟着做就行。
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**前置条件：** 电脑上装了 [Docker Desktop](https://www.docker.com/products/docker-desktop/)，并且已经打开。
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**第一步：拉取代码**
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```bash
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git clone https://git.p0lar1s.uk/P0lar1s/Ombre_Brain.git
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cd Ombre_Brain
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```
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**第二步：创建 `.env` 文件**
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在项目目录下新建一个叫 `.env` 的文件（注意有个点），内容填：
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```
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OMBRE_API_KEY=你的DeepSeek或其他API密钥
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```
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没有 API key 也能用，脱水压缩会降级到本地模式，只是效果差一点。那就写：
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```
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OMBRE_API_KEY=
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```
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**第三步：配置 `docker-compose.yml`（指向你的 Obsidian Vault）**
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用文本编辑器打开 `docker-compose.yml`，找到这一行：
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```yaml
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- ./buckets:/data
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```
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改成你的 Obsidian Vault 里 `Ombre Brain` 文件夹的路径，例如：
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```yaml
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- /Users/你的用户名/Documents/Obsidian Vault/Ombre Brain:/data
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```
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> 不知道路径？在 Obsidian 里右键那个文件夹 → 「在访达中显示」，然后把地址栏的路径复制过来。
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> 不想挂载 Obsidian 也行，保持 `./buckets:/data` 不动，数据会存在项目目录的 `buckets/` 文件夹里。
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**第四步：启动**
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```bash
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docker compose up -d
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```
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等它跑完，看到 `Started` 就好了。
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**验证是否正常运行：**
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```bash
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docker logs ombre-brain
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```
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看到 `Uvicorn running on http://0.0.0.0:8000` 说明成功了。
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---
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**接入 Claude.ai（远程访问）**
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需要额外配置 Cloudflare Tunnel，把服务暴露到公网。参考下面「接入 Claude.ai (远程)」章节。
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**接入 Claude Desktop（本地）**
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不需要 Docker，直接用 Python 本地跑。参考下面「安装 / Setup」章节。
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---
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[](https://render.com/deploy?repo=https://github.com/P0lar1zzZ/Ombre-Brain)
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---
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## 它是什么 / What is this
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Claude 没有跨对话记忆。每次对话结束，之前聊过的所有东西都会消失。
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Ombre Brain 给了它一套持久记忆——不是那种冷冰冰的键值存储，而是带情感坐标的、会自然衰减的、像人类记忆一样会遗忘和浮现的系统。
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Claude has no cross-conversation memory. Everything from a previous chat vanishes once it ends.
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Ombre Brain gives it persistent memory — not cold key-value storage, but a system with emotional coordinates, natural decay, and forgetting/surfacing mechanics that loosely mimic how human memory works.
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核心特点 / Key features:
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- **情感坐标打标 / Emotional tagging**: 每条记忆用 Russell 环形情感模型的 valence（效价）和 arousal（唤醒度）两个连续维度标记。不是"开心/难过"这种离散标签。
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Each memory is tagged with two continuous dimensions from Russell's circumplex model: valence and arousal. Not discrete labels like "happy/sad".
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- **自然遗忘 / Natural forgetting**: 改进版艾宾浩斯遗忘曲线。不活跃的记忆自动衰减归档，高情绪强度的记忆衰减更慢。
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Modified Ebbinghaus forgetting curve. Inactive memories naturally decay and archive. High-arousal memories decay slower.
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- **权重池浮现 / Weight pool surfacing**: 记忆不是被动检索的，它们会主动浮现——未解决的、情绪强烈的记忆权重更高，会在对话开头自动推送。
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Memories aren't just passively retrieved — they actively surface. Unresolved, emotionally intense memories carry higher weight and get pushed at conversation start.
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- **Obsidian 原生 / Obsidian-native**: 每个记忆桶就是一个 Markdown 文件，YAML frontmatter 存元数据。可以直接在 Obsidian 里浏览、编辑、搜索。自动注入 `[[双链]]`。
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Each memory bucket is a Markdown file with YAML frontmatter. Browse, edit, and search directly in Obsidian. Wikilinks are auto-injected.
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- **API 降级 / API degradation**: 脱水压缩和自动打标优先用廉价 LLM API（DeepSeek 等），API 不可用时自动降级到本地关键词分析——始终可用。
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Dehydration and auto-tagging prefer a cheap LLM API (DeepSeek etc.). When the API is unavailable, it degrades to local keyword analysis — always functional.
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## 边界说明 / Design boundaries
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官方记忆功能已经在做身份层的事了——你是谁，你有什么偏好，你们的关系是什么。那一层交给它，Ombre Brain不打算造重复的轮子。
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Ombre Brain 的边界是时间里发生的事，不是你是谁。它记住的是：你们聊过什么，经历了什么，哪些事情还悬在那里没有解决。两层配合用，才是完整的。
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每次新对话，Claude 从零开始——但它能从 Ombre Brain 里找回跟你有关的一切。不是重建，是接续。
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---
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Official memory already handles the identity layer — who you are, what you prefer, what your relationship is. That layer belongs there. Ombre Brain isn't trying to duplicate it.
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Ombre Brain's boundary is *what happened in time*, not *who you are*. It holds conversations, experiences, unresolved things. The two layers together are what make it feel complete.
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Each new conversation starts fresh — but Claude can reach back through Ombre Brain and find everything that happened between you. Not a rebuild. A continuation.
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## 架构 / Architecture
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```
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Claude ←→ MCP Protocol ←→ server.py
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│
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┌───────────────┼───────────────┐
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│ │ │
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bucket_manager dehydrator decay_engine
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(CRUD + 搜索) (压缩 + 打标) (遗忘曲线)
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│
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Obsidian Vault (Markdown files)
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```
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5 个 MCP 工具 / 5 MCP tools:
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| 工具 Tool | 作用 Purpose |
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|-----------|-------------|
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| `breath` | 浮现或检索记忆。无参数=推送未解决记忆；有参数=关键词+情感检索 / Surface or search memories |
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| `hold` | 存储单条记忆，自动打标+合并相似桶 / Store a single memory with auto-tagging |
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| `grow` | 日记归档，自动拆分长内容为多个记忆桶 / Diary digest, auto-split into multiple buckets |
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| `trace` | 修改元数据、标记已解决、删除 / Modify metadata, mark resolved, delete |
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| `pulse` | 系统状态 + 所有记忆桶列表 / System status + bucket listing |
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## 安装 / Setup
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### 环境要求 / Requirements
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- Python 3.11+
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- 一个 Obsidian Vault（可选，不用也行，会在项目目录下自建 `buckets/`）
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An Obsidian vault (optional — without one, it uses a local `buckets/` directory)
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### 步骤 / Steps
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```bash
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git clone https://github.com/P0lar1zzZ/Ombre-Brain.git
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cd Ombre-Brain
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python -m venv .venv
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source .venv/bin/activate # Windows: .venv\Scripts\activate
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pip install -r requirements.txt
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```
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复制配置文件并按需修改 / Copy config and edit as needed:
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```bash
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cp config.example.yaml config.yaml
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```
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如果你要用 API 做脱水压缩和自动打标（推荐，效果好很多），设置环境变量：
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If you want API-powered dehydration and tagging (recommended, much better quality):
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```bash
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export OMBRE_API_KEY="your-api-key"
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```
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支持任何 OpenAI 兼容 API。在 `config.yaml` 里改 `base_url` 和 `model` 就行。
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Supports any OpenAI-compatible API. Just change `base_url` and `model` in `config.yaml`.
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### 接入 Claude Desktop / Connect to Claude Desktop
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在 Claude Desktop 配置文件中添加（macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`）：
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Add to your Claude Desktop config:
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```json
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{
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"mcpServers": {
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"ombre-brain": {
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"command": "python",
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"args": ["/path/to/Ombre-Brain/server.py"],
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"env": {
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"OMBRE_API_KEY": "your-api-key"
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}
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}
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}
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}
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```
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### 接入 Claude.ai (远程) / Connect to Claude.ai (remote)
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需要 HTTP 传输 + 隧道。可以用 Docker：
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Requires HTTP transport + tunnel. Docker setup:
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```bash
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echo "OMBRE_API_KEY=your-api-key" > .env
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docker-compose up -d
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```
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`docker-compose.yml` 里配好了 Cloudflare Tunnel。你需要自己在 `~/.cloudflared/` 下放凭证和路由配置。
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The `docker-compose.yml` includes Cloudflare Tunnel. You'll need your own credentials under `~/.cloudflared/`.
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### 指向 Obsidian / Point to Obsidian
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在 `config.yaml` 里设置 `buckets_dir`：
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Set `buckets_dir` in `config.yaml`:
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```yaml
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buckets_dir: "/path/to/your/Obsidian Vault/Ombre Brain"
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```
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不设的话，默认用项目目录下的 `buckets/`。
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If not set, defaults to `buckets/` in the project directory.
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## 配置 / Configuration
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所有参数在 `config.yaml`（从 `config.example.yaml` 复制）。关键的几个：
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All parameters in `config.yaml` (copy from `config.example.yaml`). Key ones:
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| 参数 Parameter | 说明 Description | 默认 Default |
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|---|---|---|
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| `transport` | `stdio`（本地）/ `streamable-http`（远程）| `stdio` |
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| `buckets_dir` | 记忆桶存储路径 / Bucket storage path | `./buckets/` |
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| `dehydration.model` | 脱水用的 LLM 模型 / LLM model for dehydration | `deepseek-chat` |
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| `dehydration.base_url` | API 地址 / API endpoint | `https://api.deepseek.com/v1` |
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| `decay.lambda` | 衰减速率，越大越快忘 / Decay rate | `0.05` |
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| `decay.threshold` | 归档阈值 / Archive threshold | `0.3` |
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| `merge_threshold` | 合并相似度阈值 (0-100) / Merge similarity | `75` |
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敏感配置用环境变量：
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Sensitive config via env vars:
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- `OMBRE_API_KEY` — LLM API 密钥
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- `OMBRE_TRANSPORT` — 覆盖传输方式
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- `OMBRE_BUCKETS_DIR` — 覆盖存储路径
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## 衰减公式 / Decay Formula
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$$final\_score = time\_weight \times base\_score$$
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$$base\_score = Importance \times activation\_count^{0.3} \times e^{-\lambda \times days} \times (base + arousal \times boost)$$
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时间系数（乘数，优先级最高）/ Time weight (multiplier, highest priority):
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| 距今天数 Days since active | 时间系数 Weight |
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|---|---|
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| 0–1 天 | 1.0 |
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| 第 2 天 | 0.9 |
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| 之后每天约降 10% | `max(0.3, 0.9 × e^{-0.2197 × (days-2)})` |
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| 7 天后稳定 | ≈ 0.3（不归零）|
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- `importance`: 1-10，记忆重要性 / memory importance
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- `activation_count`: 被检索的次数，越常被想起衰减越慢 / retrieval count; more recalls = slower decay
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- `days`: 距上次激活的天数 / days since last activation
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- `arousal`: 唤醒度，越强烈的记忆越难忘 / arousal; intense memories are harder to forget
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- 已解决的记忆权重降到 5%，沉底等被关键词唤醒 / resolved memories drop to 5%, sink until keyword-triggered
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- `pinned=true` 的桶：不衰减、不合并、importance 锁定 10 / `pinned` buckets: never decay, never merge, importance locked at 10
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## 给 Claude 的使用指南 / Usage Guide for Claude
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`CLAUDE_PROMPT.md` 是写给 Claude 看的使用说明。放到你的 system prompt 或 custom instructions 里就行。
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`CLAUDE_PROMPT.md` is the usage guide written for Claude. Put it in your system prompt or custom instructions.
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## 工具脚本 / Utility Scripts
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| 脚本 Script | 用途 Purpose |
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|---|---|
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||||
| `write_memory.py` | 手动写入记忆，绕过 MCP / Manually write memories, bypass MCP |
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| `migrate_to_domains.py` | 迁移平铺文件到域子目录 / Migrate flat files to domain subdirs |
|
||||
| `reclassify_domains.py` | 基于关键词重分类 / Reclassify by keywords |
|
||||
| `reclassify_api.py` | 用 API 重打标未分类桶 / Re-tag uncategorized buckets via API |
|
||||
| `test_smoke.py` | 冒烟测试 / Smoke test |
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||||
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||||
## 部署 / Deploy
|
||||
|
||||
### Render
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||||
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||||
[](https://render.com/deploy?repo=https://github.com/P0lar1zzZ/Ombre-Brain)
|
||||
|
||||
> ⚠️ **免费层不可用**：Render 免费层**不支持持久化磁盘**，服务重启后记忆数据会丢失，且会在无流量时休眠。**必须使用 Starter（$7/mo）或以上**才能正常使用。
|
||||
> **Free tier won't work**: Render free tier has **no persistent disk** — all memory data is lost on restart. It also sleeps on inactivity. **Starter plan ($7/mo) or above is required.**
|
||||
|
||||
项目根目录已包含 `render.yaml`，点击按钮后：
|
||||
1. （可选）设置 `OMBRE_API_KEY`：任何 OpenAI 兼容 API 的 key，不填则自动降级为本地关键词提取
|
||||
2. （可选）设置 `OMBRE_BASE_URL`：API 地址，支持任意 OpenAI 化地址，如 `https://api.deepseek.com/v1` / `http://123.1.1.1:7689/v1` / `http://your-ollama:11434/v1`
|
||||
3. Render 自动挂载持久化磁盘到 `/opt/render/project/src/buckets`
|
||||
4. 部署后 MCP URL：`https://<你的服务名>.onrender.com/mcp`
|
||||
|
||||
`render.yaml` is included. After clicking the button:
|
||||
1. (Optional) `OMBRE_API_KEY`: any OpenAI-compatible key; omit to fall back to local keyword extraction
|
||||
2. (Optional) `OMBRE_BASE_URL`: any OpenAI-compatible endpoint, e.g. `https://api.deepseek.com/v1`, `http://123.1.1.1:7689/v1`, `http://your-ollama:11434/v1`
|
||||
3. Persistent disk auto-mounts at `/opt/render/project/src/buckets`
|
||||
4. MCP URL after deploy: `https://<your-service>.onrender.com/mcp`
|
||||
|
||||
### Zeabur
|
||||
|
||||
> 💡 **Zeabur 的定价模式**：Zeabur 是「买 VPS + 平台托管」，你先购买一台服务器（最低腾讯云新加坡 $2/mo、火山引擎 $3/mo），Volume 直接挂在该服务器上，**数据天然持久化，无丢失问题**。另需订阅 Zeabur 管理方案（Developer $5/mo），总计约 $7-8/mo 起。
|
||||
> **Zeabur pricing model**: You buy a VPS first (cheapest: Tencent Cloud Singapore ~$2/mo, Volcano Engine ~$3/mo), then add Zeabur's Developer plan ($5/mo) for management. Volumes mount directly on your server — **data is always persistent, no cold-start data loss**. Total ~$7-8/mo minimum.
|
||||
|
||||
**步骤 / Steps：**
|
||||
|
||||
1. **创建项目 / Create project**
|
||||
- 打开 [zeabur.com](https://zeabur.com) → 购买一台服务器 → **New Project** → **Deploy from GitHub**
|
||||
- 先 Fork 本仓库到自己 GitHub 账号，然后在 Zeabur 选择 `你的用户名/Ombre-Brain`
|
||||
- Zeabur 会自动检测到根目录的 `Dockerfile` 并使用 Docker 方式构建
|
||||
- Go to [zeabur.com](https://zeabur.com) → buy a server → **New Project** → **Deploy from GitHub**
|
||||
- Fork this repo first, then select `your-username/Ombre-Brain` in Zeabur
|
||||
- Zeabur auto-detects the `Dockerfile` in root and builds via Docker
|
||||
|
||||
2. **设置环境变量 / Set environment variables**（服务页面 → **Variables** 标签页）
|
||||
- `OMBRE_API_KEY`（可选）— LLM API 密钥，不填则自动降级为本地关键词提取
|
||||
- `OMBRE_BASE_URL`（可选）— API 地址，如 `https://api.deepseek.com/v1`
|
||||
|
||||
> ⚠️ **不需要**手动设置 `OMBRE_TRANSPORT` 和 `OMBRE_BUCKETS_DIR`，Dockerfile 里已经设好了默认值。Zeabur 对单阶段 Dockerfile 会自动注入控制台设置的环境变量。
|
||||
> You do **NOT** need to set `OMBRE_TRANSPORT` or `OMBRE_BUCKETS_DIR` — defaults are baked into the Dockerfile. Zeabur auto-injects dashboard env vars for single-stage Dockerfiles.
|
||||
|
||||
3. **挂载持久存储 / Mount persistent volume**（服务页面 → **Volumes** 标签页）
|
||||
- Volume ID：填 `ombre-buckets`（或任意名）
|
||||
- 挂载路径 / Path：**`/app/buckets`**
|
||||
- ⚠️ 不挂载的话，每次重新部署记忆数据会丢失
|
||||
- ⚠️ Without this, memory data is lost on every redeploy
|
||||
|
||||
4. **配置端口 / Configure port**（服务页面 → **Networking** 标签页）
|
||||
- Port Name：`web`（或任意名）
|
||||
- Port：**`8000`**
|
||||
- Port Type：**`HTTP`**
|
||||
- 然后点 **Generate Domain** 生成一个 `xxx.zeabur.app` 域名
|
||||
- Then click **Generate Domain** to get a `xxx.zeabur.app` domain
|
||||
|
||||
5. **验证 / Verify**
|
||||
- 访问 `https://<你的域名>.zeabur.app/health`，应返回 JSON
|
||||
- Visit `https://<your-domain>.zeabur.app/health` — should return JSON
|
||||
- 最终 MCP 地址 / MCP URL：`https://<你的域名>.zeabur.app/mcp`
|
||||
|
||||
**常见问题 / Troubleshooting：**
|
||||
|
||||
| 现象 Symptom | 原因 Cause | 解决 Fix |
|
||||
|---|---|---|
|
||||
| 域名无法访问 / Domain unreachable | 没配端口 / Port not configured | Networking 标签页加 port 8000 (HTTP) |
|
||||
| 域名无法访问 / Domain unreachable | `OMBRE_TRANSPORT` 未设置，服务以 stdio 模式启动，不监听任何端口 / Service started in stdio mode — no port is listened | **Variables 标签页确认设置 `OMBRE_TRANSPORT=streamable-http`，然后重新部署** |
|
||||
| 构建失败 / Build failed | Dockerfile 未被识别 / Dockerfile not detected | 确认仓库根目录有 `Dockerfile`（大小写敏感） |
|
||||
| 服务启动后立刻退出 | `OMBRE_TRANSPORT` 被覆盖为 `stdio` | 检查 Variables 里有没有多余的 `OMBRE_TRANSPORT=stdio`，删掉即可 |
|
||||
| 重启后记忆丢失 / Data lost on restart | Volume 未挂载 | Volumes 标签页挂载到 `/app/buckets` |
|
||||
|
||||
### 使用 Cloudflare Tunnel 或 ngrok 连接 / Connecting via Cloudflare Tunnel or ngrok
|
||||
|
||||
> ℹ️ 自 v1.1 起，server.py 在 HTTP 模式下已自动添加 CORS 中间件，无需额外配置。
|
||||
> Since v1.1, server.py automatically enables CORS middleware in HTTP mode — no extra config needed.
|
||||
|
||||
使用隧道连接时，确保以下条件满足：
|
||||
When connecting via tunnel, ensure:
|
||||
|
||||
1. **服务器必须运行在 HTTP 模式** / Server must use HTTP transport
|
||||
```bash
|
||||
OMBRE_TRANSPORT=streamable-http python server.py
|
||||
```
|
||||
或 Docker：
|
||||
```bash
|
||||
docker-compose up -d
|
||||
```
|
||||
|
||||
2. **在 Claude.ai 网页版添加 MCP 服务器** / Adding to Claude.ai web
|
||||
- URL 格式 / URL format: `https://<tunnel-subdomain>.trycloudflare.com/mcp`
|
||||
- 或 ngrok / or ngrok: `https://<xxxx>.ngrok-free.app/mcp`
|
||||
- 先访问 `/health` 验证连接 / Verify first: `https://<your-tunnel>/health` should return `{"status":"ok",...}`
|
||||
|
||||
3. **已知限制 / Known limitations**
|
||||
- Cloudflare Tunnel 免费版有空闲超时（约 10 分钟），系统内置保活 ping 可缓解但不能完全消除
|
||||
- Free Cloudflare Tunnel has idle timeout (~10 min); built-in keepalive pings mitigate but can't fully prevent it
|
||||
- ngrok 免费版有请求速率限制 / ngrok free tier has rate limits
|
||||
- 如果连接仍失败，检查隧道是否正在运行、服务是否以 `streamable-http` 模式启动
|
||||
- If connection still fails, verify the tunnel is running and the server started in `streamable-http` mode
|
||||
|
||||
| 现象 Symptom | 原因 Cause | 解决 Fix |
|
||||
|---|---|---|
|
||||
| 网页版无法连接隧道 URL / Web can't connect to tunnel URL | 服务以 stdio 模式运行 / Server in stdio mode | 设置 `OMBRE_TRANSPORT=streamable-http` 后重启 |
|
||||
| 网页版无法连接隧道 URL / Web can't connect to tunnel URL | 旧版 server.py 缺少 CORS 头 / Missing CORS headers | 拉取最新代码，CORS 已内置 / Pull latest — CORS is now built-in |
|
||||
| `/health` 返回 200 但 MCP 连不上 / `/health` 200 but MCP fails | 路径错误 / Wrong path | MCP URL 末尾必须是 `/mcp` 而非 `/` |
|
||||
| 隧道连接偶尔断开 / Tunnel disconnects intermittently | Cloudflare Tunnel 空闲超时 / Idle timeout | 保活 ping 已内置，若仍断开可缩短隧道超时配置 |
|
||||
|
||||
---
|
||||
|
||||
### Session Start Hook（自动 breath）
|
||||
|
||||
部署后，如果你使用 Claude Code，可以在项目内激活自动浮现 hook：
|
||||
`.claude/settings.json` 已配置好 `SessionStart` hook，每次新会话或恢复会话时自动触发 `breath`，把最高权重未解决记忆推入上下文。
|
||||
|
||||
**仅在远程 HTTP 模式下有效**（`OMBRE_TRANSPORT=streamable-http`）。本地 stdio 模式下 hook 会安静退出，不影响正常使用。
|
||||
|
||||
可以通过 `OMBRE_HOOK_URL` 环境变量指定服务器地址（默认 `http://localhost:8000`），或者设置 `OMBRE_HOOK_SKIP=1` 临时禁用。
|
||||
|
||||
If using Claude Code, `.claude/settings.json` configures a `SessionStart` hook that auto-calls `breath` on each new or resumed session, surfacing your highest-weight unresolved memories as context. Only active in remote HTTP mode. Set `OMBRE_HOOK_SKIP=1` to disable temporarily.
|
||||
|
||||
## License
|
||||
|
||||
MIT
|
||||
Reference in New Issue
Block a user