mirror of
https://github.com/agentscope-ai/ReMe.git
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ef3f99f019
* refactor(packaging): reorganize published packages * fix(packaging): install AgentScope extra in wheel smoke * docs: align package guides and documentation site * ci(workflow): add core dependency verification step in Python package build - Add a workflow step to verify released core dependencies by installing the wheel with core extras - Assert the presence of the static index.html file to ensure proper package contents - Create and use a temporary virtual environment for isolation during verification - Keep existing artifacts upload step intact and conditional on inputs.upload_artifacts flag * fix(ci): update package installation dependencies in Windows workflow - Change pip install from editable reme_studio and core to only dev and as extras - Remove installation of reme_studio and core to streamline dependency setup - Ensure Windows CI uses the correct extras for testing environment * fix(tests): add missing commas in toml file reads in package version tests - Added trailing commas in the tomllib.loads calls for auto-fin and daily_paper configs - Ensured consistent syntax to prevent potential tuple misinterpretation - Improved readability and correctness of the test setup code * fix(packaging): protect qwenpaw releases and test Studio health
228 lines
5.4 KiB
Markdown
228 lines
5.4 KiB
Markdown
# 快速开始
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## 安装
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ReMe 要求 Python 3.11+。
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从 pip 安装：
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```bash
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pip install "reme-ai[core]"
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```
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从源码安装：
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```bash
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git clone https://github.com/agentscope-ai/ReMe.git
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cd ReMe
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pip install -e reme_studio -e ".[core]"
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cd reme_studio
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npm ci
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npm run build:static
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cd ..
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```
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静态构建步骤需要 Node.js 22.13 或更高版本，用于在从源码运行 ReMe 时提供 Studio。
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`core` extra 建议安装：当前代码会导入 AgentScope wrapper，自进化记忆也依赖它。
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如果要使用 `auto_memory`、`auto_resource`、`auto_dream` 这类 Agent 流程，再配置 LLM：
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```bash
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cat > .env <<'EOF'
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LLM_BACKEND=openai
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LLM_MODEL_NAME=qwen3.7-plus
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LLM_API_KEY=your_api_key
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LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
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EOF
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```
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只跑基础文件读写和 BM25 检索，可以先不配。
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---
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## 启动
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```bash
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reme start
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```
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默认服务地址是 `127.0.0.1:2333`。如果端口被占用：
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```bash
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reme start service.port=8181
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```
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```bash
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reme version
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reme health_check
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reme help
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```
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`reme help` 会列出服务端 action。普通命令会通过 HTTP 调用服务端 Job。
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基础 `reme-ai` 包不包含前端资源。安装 `reme-ai[web]` 或 `reme-ai[core]` 后，浏览器打开
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<http://127.0.0.1:2333/> 即可进入 ReMe Studio，在同一服务中浏览、编辑和搜索
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workspace，并查看 digest Wikilink 图。可用 `service.web_enabled=false` 关闭，或通过 `service.web_static_dir` /
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`REME_WEB_STATIC_DIR`
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指定自定义静态目录；找不到构建产物时，Job API 仍会正常启动。
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---
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## Workspace 目录
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默认 workspace 是当前目录下的 `.reme/`，启动时会自动创建：
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```text
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.reme/
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├── metadata/ # 索引、图谱、catalog 等持久状态
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├── session/ # 对话来源记录
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├── mem_session/ # Agent wrapper 生成的 session/配置
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├── resource/ # 外部资料
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├── daily/ # daily note
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└── digest/ # 长期记忆
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```
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目录分层、Markdown frontmatter 和 wikilink 语义见 [Memory as File](./memory_as_file.md)。
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也可以启动时指定：
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```bash
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reme start workspace_dir=/tmp/reme-demo service.port=8181
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```
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---
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## 写入、索引、检索
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```bash
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reme write \
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path=digest/wiki/quick-start-demo \
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name="Quick Start Demo" \
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description="快速开始示例记忆" \
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content="# Quick Start Demo
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默认实时 watcher 会索引 daily 和 digest 目录中的 Markdown。
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相关链接：[[digest/wiki/search-demo.md]]"
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```
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`path` 是 workspace 内路径；没有后缀时会自动补 `.md`；Markdown 文件会写入 `name` 和 `description` front matter。
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后台 watcher 会自动建索引；也可以手动重建：
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```bash
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reme reindex
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```
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搜索：
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```bash
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reme search query="快速开始 示例 记忆" limit=5
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```
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读取：
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```bash
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reme read path=digest/wiki/quick-start-demo start_line=1 end_line=20
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```
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默认配置下，检索主要是 BM25 + wikilink 图谱扩展；向量检索能力在代码中支持，但默认未启用 embedding store。完整检索流程见
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[Memory Search](./memory_search.md)。
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---
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## 文件与 Daily Note
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```bash
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reme stat path=digest/wiki/quick-start-demo
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reme edit path=digest/wiki/quick-start-demo old="会索引" new="会持续索引"
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reme frontmatter_read path=digest/wiki/quick-start-demo
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reme frontmatter_update path=digest/wiki/quick-start-demo metadata='{"tags":["demo"]}'
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```
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文件列表 Job 可以直接通过 CLI 调用：
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```bash
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reme list path=digest recursive=true limit=50
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```
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等价的 HTTP 调用是：
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```bash
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curl -s http://127.0.0.1:2333/list \
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-H 'Content-Type: application/json' \
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-d '{"path":"digest","recursive":true,"limit":50}'
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```
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Daily note：
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```bash
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reme write path=daily/2026-06-20/demo-session.md name=demo-session description="Demo session" content="记录内容"
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reme daily_list
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reme daily_reindex
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```
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`write` 可直接创建 daily note；需要刷新当天索引时运行 `daily_reindex`。
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---
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## 自动记忆
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```bash
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reme auto_memory \
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session_id=chat-demo \
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messages='[{"role":"user","content":"我偏好把项目经验沉淀成 Markdown。"},{"role":"assistant","content":"已记录。"}]' \
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memory_hint="记录用户偏好"
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```
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外部资料放入 `resource/YYYY-MM-DD/` 或直接放在 `resource/` 下后，默认后台会监听 `md/txt/json/jsonl/csv/yaml/html`。
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也可以手动触发：
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```bash
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reme auto_resource changes='[{"path":"resource/2026-06-20/report.md","change":"added"}]'
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```
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把 daily 整理到长期 digest：
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```bash
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reme auto_dream date=2026-06-20
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reme proactive date=2026-06-20
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```
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这些流程需要可用 LLM；未配置 LLM 时请先使用 `write/read/search` 这类基础能力。
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更多细节见 [Auto Memory](./auto_memory.md)、[Auto Resource](./auto_resource.md)、[Auto Dream](./auto_dream.md) 和
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[Proactive](./proactive.md)。
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---
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## HTTP 与配置
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每个可服务 Job 都暴露为 `POST /<job>`：
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```bash
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curl -s http://127.0.0.1:2333/version \
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-H 'Content-Type: application/json' \
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-d '{}'
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curl -s http://127.0.0.1:2333/search \
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-H 'Content-Type: application/json' \
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-d '{"query":"快速开始","limit":5}'
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```
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默认配置来自 `reme/config/default.yaml`。启动时可以用 dot notation 覆盖：
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```bash
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reme start \
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workspace_dir=/tmp/reme-demo \
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service.host=127.0.0.1 \
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service.port=8181 \
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enable_logo=false
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```
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也可以指定 YAML/JSON 配置文件：
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```bash
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reme start config=/path/to/custom.yaml
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```
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