mirror of
https://github.com/agentscope-ai/ReMe.git
synced 2026-09-05 08:06:15 +00:00
docs: move environment setup before service start (#509)
This commit is contained in:
jinliyl
GitHub
parent
fc4a5398a8
commit
bec7e48772
2 changed files with 50 additions and 50 deletions
50
README.md
50
README.md
|
|
@ -88,6 +88,31 @@ cd ..
|
|||
|
||||
The static build requires Node.js 22.13 or newer and makes Studio available from the source tree.
|
||||
|
||||
### Environment Variables
|
||||
|
||||
Configure environment variables when you want LLM-powered memory evolution or embedding retrieval. Embeddings are
|
||||
disabled by default, so the default setup does not start an embedding model or require an embedding API key.
|
||||
|
||||
```bash
|
||||
cat > .env <<'EOF'
|
||||
# Optional: used only after embedding components are explicitly enabled in the config.
|
||||
# EMBEDDING_API_KEY=sk-xxx
|
||||
# EMBEDDING_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
|
||||
# Required for auto_memory, auto_resource, and auto_dream.
|
||||
LLM_API_KEY=sk-xxx
|
||||
LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
EOF
|
||||
```
|
||||
|
||||
Basic file operations, BM25 search, wikilink traversal, and reading proactive topics can run without LLM credentials.
|
||||
|
||||
> [!NOTE]
|
||||
> To enable embedding-based semantic retrieval, uncomment `components.as_embedding` and
|
||||
> `components.embedding_store` in [`reme/config/default.yaml`](reme/config/default.yaml), then change
|
||||
> `components.file_store.default.embedding_store` from `""` to `default`. See the
|
||||
> [memory search guide](docs/en/memory_search.md) for details.
|
||||
|
||||
### Start the Service
|
||||
|
||||
```bash
|
||||
|
|
@ -148,31 +173,6 @@ The `core` installation includes Studio. After starting ReMe, open <http://127.0
|
|||
the workspace. To add Studio to a base installation, use `pip install "reme-ai[web]"`. See the
|
||||
[ReMe Studio guide](https://reme.agentscope.io/?doc=studio-en) for source builds, configuration, and development.
|
||||
|
||||
### Optional Model Configuration
|
||||
|
||||
Configure environment variables when you want LLM-powered memory evolution or embedding retrieval. Embeddings are
|
||||
disabled by default, so the default setup does not start an embedding model or require an embedding API key.
|
||||
|
||||
```bash
|
||||
cat > .env <<'EOF'
|
||||
# Optional: used only after embedding components are explicitly enabled in the config.
|
||||
# EMBEDDING_API_KEY=sk-xxx
|
||||
# EMBEDDING_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
|
||||
# Required for auto_memory, auto_resource, and auto_dream.
|
||||
LLM_API_KEY=sk-xxx
|
||||
LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
EOF
|
||||
```
|
||||
|
||||
Basic file operations, BM25 search, wikilink traversal, and reading proactive topics can run without LLM credentials.
|
||||
|
||||
> [!NOTE]
|
||||
> To enable embedding-based semantic retrieval, uncomment `components.as_embedding` and
|
||||
> `components.embedding_store` in [`reme/config/default.yaml`](reme/config/default.yaml), then change
|
||||
> `components.file_store.default.embedding_store` from `""` to `default`. See the
|
||||
> [memory search guide](docs/en/memory_search.md) for details.
|
||||
|
||||
## 🤝 Use ReMe with Your Agent
|
||||
|
||||
ReMe can run as a local memory service accessed through the CLI, HTTP API, or MCP server, or it can be embedded in the
|
||||
|
|
|
|||
50
README_ZH.md
50
README_ZH.md
|
|
@ -87,6 +87,31 @@ cd ..
|
|||
|
||||
静态构建要求 Node.js 22.13 或更高版本，并让源码安装可以直接使用 Studio。
|
||||
|
||||
### 环境变量配置
|
||||
|
||||
如果需要 LLM 驱动的记忆演化或 embedding 检索，请在启动服务前配置环境变量。embedding 默认关闭，因此默认配置不会启动
|
||||
embedding 模型，也不需要 embedding API key。
|
||||
|
||||
```bash
|
||||
cat > .env <<'EOF'
|
||||
# 可选：仅在配置中显式启用 embedding 组件后使用。
|
||||
# EMBEDDING_API_KEY=sk-xxx
|
||||
# EMBEDDING_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
|
||||
# 必须：auto_memory、auto_resource 和 auto_dream 需要 LLM。
|
||||
LLM_API_KEY=sk-xxx
|
||||
LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
EOF
|
||||
```
|
||||
|
||||
基础文件读写、BM25 检索、wikilink 遍历和 proactive topics 读取不需要 LLM 凭证，可以跳过此步骤并直接启动服务。
|
||||
|
||||
> [!NOTE]
|
||||
> 如需启用基于 embedding 的语义检索，请取消 [`reme/config/default.yaml`](reme/config/default.yaml) 中
|
||||
> `components.as_embedding` 和 `components.embedding_store` 的注释，并将
|
||||
> `components.file_store.default.embedding_store` 从 `""` 改为 `default`。完整说明见
|
||||
> [记忆检索文档](docs/zh/memory_search.md)。
|
||||
|
||||
### 启动服务
|
||||
|
||||
```bash
|
||||
|
|
@ -147,31 +172,6 @@ ReMe 会把 Agent 记忆保存为可读的 Markdown。
|
|||
如需为基础安装单独添加 Studio，可使用 `pip install "reme-ai[web]"`。源码构建、配置和开发说明见
|
||||
[ReMe Studio 指南](https://reme.agentscope.io/?doc=studio-zh)。
|
||||
|
||||
### 可选模型配置
|
||||
|
||||
如果需要 LLM 驱动的记忆演化或 embedding 检索，可以配置环境变量。embedding 默认关闭，因此默认配置不会启动 embedding 模型，也不需要
|
||||
embedding API key。
|
||||
|
||||
```bash
|
||||
cat > .env <<'EOF'
|
||||
# 可选：仅在配置中显式启用 embedding 组件后使用。
|
||||
# EMBEDDING_API_KEY=sk-xxx
|
||||
# EMBEDDING_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
|
||||
# 必须：auto_memory、auto_resource 和 auto_dream 需要 LLM。
|
||||
LLM_API_KEY=sk-xxx
|
||||
LLM_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
|
||||
EOF
|
||||
```
|
||||
|
||||
基础文件读写、BM25 检索、wikilink 遍历和 proactive topics 读取可以先不配置 LLM 凭证。
|
||||
|
||||
> [!NOTE]
|
||||
> 如需启用基于 embedding 的语义检索，请取消 [`reme/config/default.yaml`](reme/config/default.yaml) 中
|
||||
> `components.as_embedding` 和 `components.embedding_store` 的注释，并将
|
||||
> `components.file_store.default.embedding_store` 从 `""` 改为 `default`。完整说明见
|
||||
> [记忆检索文档](docs/zh/memory_search.md)。
|
||||
|
||||
## 🤝 将 ReMe 接入你的 Agent
|
||||
|
||||
ReMe 既可以作为本地记忆服务，通过 CLI、HTTP API 或 MCP server 接入，也可以通过 Python API 嵌入宿主进程。宿主集成可根据不同
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue