diff --git a/README.md b/README.md
index 3b30371a..3582bb05 100644
--- a/README.md
+++ b/README.md
@@ -58,7 +58,9 @@ memory, then continuously indexes, links, and consolidates that memory for futur
 
 ## 📰 News
 
-- [2026.07] - Our paper [Remember Me, Refine Me: A Dynamic Procedural Memory Framework for Experience-Driven Agent Evolution](https://aclanthology.org/2026.findings-acl.829/) has been accepted to Findings of ACL 2026.
+- [2026.07] - Our
+  paper [Remember Me, Refine Me: A Dynamic Procedural Memory Framework for Experience-Driven Agent Evolution](https://aclanthology.org/2026.findings-acl.829/)
+  has been accepted to Findings of ACL 2026.
 
 ## 🚀 Quick Start
 
@@ -82,13 +84,14 @@ pip install -e ".[core]"
 
 ### Environment Variables
 
-Configure environment variables when you want LLM-powered memory evolution or embedding retrieval:
+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: enables semantic retrieval when the embedding store is configured.
-EMBEDDING_API_KEY=sk-xxx
-EMBEDDING_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
+# 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
@@ -98,6 +101,12 @@ 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
@@ -193,7 +202,8 @@ ReMe treats **memory as files**, progressively processing raw conversations and
 
 ## 🧭 Memory Design Philosophy
 
-> Capture raw dialogs and resources, refine them into long-term preferences, reusable experience, and valuable knowledge,
+> Capture raw dialogs and resources, refine them into long-term preferences, reusable experience, and valuable
+> knowledge,
 > while keeping the result editable by humans and agents.
 
 ### Automatic Memory Flow
@@ -202,13 +212,13 @@ ReMe follows a capture → index → consolidate → recall loop. Conversations
 background jobs keep files searchable; `auto_dream` distills stable knowledge into `digest/`; agents recall memory
 through search, wikilinks, or proactive topics.
 
-| Capability                                  | Entry point                                      | What it does                                                                                  | Output                                                   |
-|---------------------------------------------|--------------------------------------------------|-----------------------------------------------------------------------------------------------|----------------------------------------------------------|
-| [`auto_memory`](docs/en/auto_memory.md)     | Agent hook or `reme auto_memory`                 | Distills useful conversation facts while preserving the raw session.                          | `session/dialog/*.jsonl`, `daily/<date>/<session>.md`    |
-| [`auto_resource`](docs/en/auto_resource.md) | Resource watcher or `reme auto_resource`         | Turns files under `resource/<date>/` into source-linked daily cards.                          | `daily/<date>/<resource-card>.md`                        |
-| [`auto_index`](docs/en/memory_search.md)    | Background watcher or `reme reindex`             | Maintains chunks, BM25/embedding indexes, and the wikilink graph.                             | Searchable `daily/`, `digest/`, and `resource/` content  |
-| [`auto_dream`](docs/en/auto_dream.md)       | `dream_cron` or `reme auto_dream`                | Consolidates changed daily cards into long-term personal, procedure, and wiki memory.         | `digest/**`, `daily/<date>/interests.yaml`               |
-| [`proactive`](docs/en/proactive.md)         | `reme proactive` before an agent decides to act  | Reads topics generated by `auto_dream`; the host agent decides whether and how to mention them. | Structured topics from `daily/<date>/interests.yaml`     |
+| Capability                                  | Entry point                                     | What it does                                                                                    | Output                                                  |
+|---------------------------------------------|-------------------------------------------------|-------------------------------------------------------------------------------------------------|---------------------------------------------------------|
+| [`auto_memory`](docs/en/auto_memory.md)     | Agent hook or `reme auto_memory`                | Distills useful conversation facts while preserving the raw session.                            | `session/dialog/*.jsonl`, `daily/<date>/<session>.md`   |
+| [`auto_resource`](docs/en/auto_resource.md) | Resource watcher or `reme auto_resource`        | Turns files under `resource/<date>/` into source-linked daily cards.                            | `daily/<date>/<resource-card>.md`                       |
+| [`auto_index`](docs/en/memory_search.md)    | Background watcher or `reme reindex`            | Maintains chunks, the BM25 index, the wikilink graph, and the optional embedding index.         | Searchable `daily/`, `digest/`, and `resource/` content |
+| [`auto_dream`](docs/en/auto_dream.md)       | `dream_cron` or `reme auto_dream`               | Consolidates changed daily cards into long-term personal, procedure, and wiki memory.           | `digest/**`, `daily/<date>/interests.yaml`              |
+| [`proactive`](docs/en/proactive.md)         | `reme proactive` before an agent decides to act | Reads topics generated by `auto_dream`; the host agent decides whether and how to mention them. | Structured topics from `daily/<date>/interests.yaml`    |
 
 <table>
   <tr>
@@ -234,11 +244,11 @@ through search, wikilinks, or proactive topics.
 ReMe runs as a local memory service and offers multiple integration paths: CLI, HTTP API, MCP server, and SDK. Different
 agents can choose the path that fits their runtime while sharing the same local memory workspace.
 
-| Agents                                               | Recommended path                                                            | What works out of the box                                                                      |
-|------------------------------------------------------|-----------------------------------------------------------------------------|------------------------------------------------------------------------------------------------|
-| **QwenPaw**                                          | Embed ReMe via the Python SDK.                                              | Reuse the app's own lifecycle and model config while keeping memory local and file-based.      |
-| **Claude Code**                                      | Start ReMe as an MCP service and install [plugins/reme](plugins/reme).      | MCP recall tools, a `reme-memory` skill, and a Stop hook that records sessions automatically.  |
-| **Other CLI-capable agents (OpenClaw/Hermes/Codex)** | Copy or install [skills/reme_memory/SKILL.md](skills/reme_memory/SKILL.md). | Search/read/write memory and call `auto_memory`, `auto_dream`, and `proactive` via the CLI.    |
+| Agents                                               | Recommended path                                                            | What works out of the box                                                                     |
+|------------------------------------------------------|-----------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------|
+| **QwenPaw**                                          | Embed ReMe via the Python SDK.                                              | Reuse the app's own lifecycle and model config while keeping memory local and file-based.     |
+| **Claude Code**                                      | Start ReMe as an MCP service and install [plugins/reme](plugins/reme).      | MCP recall tools, a `reme-memory` skill, and a Stop hook that records sessions automatically. |
+| **Other CLI-capable agents (OpenClaw/Hermes/Codex)** | Copy or install [skills/reme_memory/SKILL.md](skills/reme_memory/SKILL.md). | Search/read/write memory and call `auto_memory`, `auto_dream`, and `proactive` via the CLI.   |
 
 <p align="center"><b>Integration demos</b></p>
 
@@ -274,22 +284,23 @@ ReMe operates the workspace through a unified job interface exposed by the CLI.
 reading, writing, editing, and automatic memory commands. Lower-level indexing, frontmatter, and file operation commands
 are mainly for maintenance, debugging, or advanced integration. Run `reme help` for the full job list.
 
-| Command                                   | Purpose                                                                              |
-|-------------------------------------------|--------------------------------------------------------------------------------------|
-| `reme start`                              | Start the local ReMe service.                                                        |
-| `reme version` / `reme health_check`      | Check package and component status.                                                  |
-| [`reme search`](docs/en/memory_search.md) | Retrieve memory with hybrid search.                                                  |
-| `reme read` / `reme write` / `reme edit`  | Inspect and maintain Markdown memory files.                                          |
-| `reme auto_memory`                        | Turn conversation messages into daily memory cards. Requires LLM credentials.        |
+| Command                                   | Purpose                                                                                |
+|-------------------------------------------|----------------------------------------------------------------------------------------|
+| `reme start`                              | Start the local ReMe service.                                                          |
+| `reme version` / `reme health_check`      | Check package and component status.                                                    |
+| [`reme search`](docs/en/memory_search.md) | Retrieve memory with BM25 and wikilinks by default, plus vectors when enabled.         |
+| `reme read` / `reme write` / `reme edit`  | Inspect and maintain Markdown memory files.                                            |
+| `reme auto_memory`                        | Turn conversation messages into daily memory cards. Requires LLM credentials.          |
 | `reme auto_resource`                      | Interpret files under `resource/` into daily resource cards. Requires LLM credentials. |
-| `reme auto_dream` / `reme proactive`      | Consolidate daily memory into long-term digest and surface topics worth attention.   |
-| `reme reindex`                            | Rebuild search and wikilink indexes from existing files.                             |
+| `reme auto_dream` / `reme proactive`      | Consolidate daily memory into long-term digest and surface topics worth attention.     |
+| `reme reindex`                            | Rebuild search and wikilink indexes from existing files.                               |
 
 ## 🤝 Community and Support
 
 - **Issues and requests**: Check [Open Issues](https://github.com/agentscope-ai/ReMe/issues) first. If there is no
   related discussion, open a new issue with background, expected behavior, and impact scope.
-- **Code contributions**: Before making changes, read the [contribution guide](https://docs.agentscope.io/reme/stable/en/contributing). Source,
+- **Code contributions**: Before making changes, read
+  the [contribution guide](https://docs.agentscope.io/reme/stable/en/contributing). Source,
   schemas, and tests are the authoritative architecture and extension guide.
 - **Documentation contributions**: Submit user-facing documentation changes to the
   [unified documentation repository](https://github.com/agentscope-ai/docs) under `reme/<version>/{en,zh}/`.
diff --git a/README_ZH.md b/README_ZH.md
index 44d405e8..6a01a79b 100644
--- a/README_ZH.md
+++ b/README_ZH.md
@@ -26,7 +26,8 @@
 > [0.2.x](https://github.com/agentscope-ai/ReMe/tree/v0.2.0.6) ·
 > [MemoryScope](https://github.com/agentscope-ai/ReMe/tree/memoryscope_branch)
 
-🧠 ReMe 是一个面向 **AI 智能体** 的 local-first 记忆层。它把对话和资料沉淀为文件化长期记忆，并持续完成索引、链接和整理，让后续 Agent 能够可靠召回。
+🧠 ReMe 是一个面向 **AI 智能体** 的 local-first 记忆层。它把对话和资料沉淀为文件化长期记忆，并持续完成索引、链接和整理，让后续
+Agent 能够可靠召回。
 
 ## ✨ 核心创新
 
@@ -50,8 +51,9 @@
 
 ## 📰 新闻
 
-- [2026.07] - 我们的论文 [Remember Me, Refine Me: A Dynamic Procedural Memory Framework for Experience-Driven Agent Evolution](https://aclanthology.org/2026.findings-acl.829/)
-已被 Findings of ACL 2026 接收。
+- [2026.07] -
+  我们的论文 [Remember Me, Refine Me: A Dynamic Procedural Memory Framework for Experience-Driven Agent Evolution](https://aclanthology.org/2026.findings-acl.829/)
+  已被 Findings of ACL 2026 接收。
 
 ## 🚀 快速开始
 
@@ -75,13 +77,14 @@ pip install -e ".[core]"
 
 ### 环境变量
 
-如果需要 LLM 驱动的记忆演化或 embedding 检索，可以配置环境变量：
+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：配置 embedding store 后启用语义检索。
-EMBEDDING_API_KEY=sk-xxx
-EMBEDDING_BASE_URL=https://dashscope.aliyuncs.com/compatible-mode/v1
+# 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
@@ -91,6 +94,12 @@ 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)。
+
 ### 启动服务
 
 ```bash
@@ -193,13 +202,13 @@ ReMe 将**记忆视为文件**，让原始对话和外部资料从 `session/`、
 ReMe 遵循 capture → index → consolidate → recall 的循环。对话和资料先变成 daily 记忆卡片；后台任务保持文件可检索；
 `auto_dream` 将稳定知识沉淀到 `digest/`；Agent 再通过搜索、wikilink 或 proactive topics 召回记忆。
 
-| 能力                                          | 入口                                | 作用                                  | 输出                                                       |
-|---------------------------------------------|-----------------------------------|-------------------------------------|----------------------------------------------------------|
-| [`auto_memory`](docs/zh/auto_memory.md)     | Agent hook 或 `reme auto_memory`   | 提炼有长期价值的对话事实，同时保留原始 session。      | `session/dialog/*.jsonl`、`daily/<date>/<session>.md`     |
-| [`auto_resource`](docs/zh/auto_resource.md) | 资源监听或 `reme auto_resource`       | 将 `resource/<date>/` 下的文件转为带来源链接的 daily 卡片。 | `daily/<date>/<resource-card>.md`                         |
-| [`auto_index`](docs/zh/memory_search.md)    | 后台监听或 `reme reindex`             | 维护 chunks、BM25/embedding 索引和 wikilink 图谱。 | 可检索的 `daily/`、`digest/`、`resource/` 内容                 |
-| [`auto_dream`](docs/zh/auto_dream.md)       | `dream_cron` 或 `reme auto_dream`   | 将变化的 daily 卡片整理为长期 personal、procedure 和 wiki 记忆。 | `digest/**`、`daily/<date>/interests.yaml`                 |
-| [`proactive`](docs/zh/proactive.md)         | Agent 决定主动行动前调用 `reme proactive` | 读取 `auto_dream` 生成的 topics；是否以及如何提醒用户由宿主 Agent 决定。 | 来自 `daily/<date>/interests.yaml` 的结构化 topics           |
+| 能力                                          | 入口                               | 作用                                                 | 输出                                                   |
+|---------------------------------------------|----------------------------------|----------------------------------------------------|------------------------------------------------------|
+| [`auto_memory`](docs/zh/auto_memory.md)     | Agent hook 或 `reme auto_memory`  | 提炼有长期价值的对话事实，同时保留原始 session。                       | `session/dialog/*.jsonl`、`daily/<date>/<session>.md` |
+| [`auto_resource`](docs/zh/auto_resource.md) | 资源监听或 `reme auto_resource`       | 将 `resource/<date>/` 下的文件转为带来源链接的 daily 卡片。        | `daily/<date>/<resource-card>.md`                    |
+| [`auto_index`](docs/zh/memory_search.md)    | 后台监听或 `reme reindex`             | 维护 chunks、BM25 索引、wikilink 图谱及可选的 embedding 索引。    | 可检索的 `daily/`、`digest/`、`resource/` 内容               |
+| [`auto_dream`](docs/zh/auto_dream.md)       | `dream_cron` 或 `reme auto_dream` | 将变化的 daily 卡片整理为长期 personal、procedure 和 wiki 记忆。   | `digest/**`、`daily/<date>/interests.yaml`            |
+| [`proactive`](docs/zh/proactive.md)         | Agent 决定主动行动前调用 `reme proactive` | 读取 `auto_dream` 生成的 topics；是否以及如何提醒用户由宿主 Agent 决定。 | 来自 `daily/<date>/interests.yaml` 的结构化 topics         |
 
 <table>
   <tr>
@@ -225,10 +234,10 @@ ReMe 遵循 capture → index → consolidate → recall 的循环。对话和
 ReMe 作为本地记忆服务运行，并提供 CLI、HTTP API、MCP server 和 SDK 等多种接入方式。不同 Agent 可以选择适合自身 runtime
 的路径，同时共享同一个本地 memory workspace。
 
-| Agent                                                | 推荐接入方式                                                              | 开箱可用能力                                                             |
-|------------------------------------------------------|-----------------------------------------------------------------------|--------------------------------------------------------------------|
-| **QwenPaw**                                          | 通过 Python SDK 嵌入 ReMe。                                                | 复用应用自身生命周期和模型配置，同时保持 memory 本地、文件化。                         |
-| **Claude Code**                                      | 以 MCP service 启动 ReMe，并安装 [plugins/reme](plugins/reme)。              | MCP recall tools、`reme-memory` skill，以及自动记录会话的 Stop hook。          |
+| Agent                                                | 推荐接入方式                                                            | 开箱可用能力                                                          |
+|------------------------------------------------------|-------------------------------------------------------------------|-----------------------------------------------------------------|
+| **QwenPaw**                                          | 通过 Python SDK 嵌入 ReMe。                                            | 复用应用自身生命周期和模型配置，同时保持 memory 本地、文件化。                             |
+| **Claude Code**                                      | 以 MCP service 启动 ReMe，并安装 [plugins/reme](plugins/reme)。           | MCP recall tools、`reme-memory` skill，以及自动记录会话的 Stop hook。       |
 | **Other CLI-capable agents (OpenClaw/Hermes/Codex)** | 复制或安装 [skills/reme_memory/SKILL.md](skills/reme_memory/SKILL.md)。 | 通过 CLI 搜索/读取/写入记忆，并调用 `auto_memory`、`auto_dream` 和 `proactive`。 |
 
 <p align="center"><b>集成演示</b></p>
@@ -264,22 +273,23 @@ ReMe 作为本地记忆服务运行，并提供 CLI、HTTP API、MCP server 和
 ReMe 通过 CLI 暴露的统一 job interface 操作 workspace。Agent 通常只需要使用检索、读取、写入、编辑和自动记忆相关命令；更底层的索引、
 frontmatter 和文件操作接口主要用于维护、调试或高级集成。完整 job 列表可以运行 `reme help` 查看。
 
-| 命令                                      | 作用                                          |
-|-----------------------------------------|---------------------------------------------|
-| `reme start`                            | 启动本地 ReMe 服务。                               |
-| `reme version` / `reme health_check`    | 检查包版本和组件状态。                                |
-| [`reme search`](docs/zh/memory_search.md) | 执行混合记忆检索。                                  |
-| `reme read` / `reme write` / `reme edit` | 检查和维护 Markdown 记忆文件。                       |
-| `reme auto_memory`                      | 将对话 messages 转为 daily 记忆卡片；需要 LLM 凭证。      |
-| `reme auto_resource`                    | 将 `resource/` 下的文件解读为 daily 资料卡片；需要 LLM 凭证。 |
-| `reme auto_dream` / `reme proactive`    | 将 daily 记忆整理为长期 digest，并暴露值得关注的主题。         |
-| `reme reindex`                          | 基于已有文件重建检索和 wikilink 索引。                   |
+| 命令                                        | 作用                                          |
+|-------------------------------------------|---------------------------------------------|
+| `reme start`                              | 启动本地 ReMe 服务。                               |
+| `reme version` / `reme health_check`      | 检查包版本和组件状态。                                 |
+| [`reme search`](docs/zh/memory_search.md) | 默认使用 BM25 和 wikilink 检索，启用后增加向量检索。          |
+| `reme read` / `reme write` / `reme edit`  | 检查和维护 Markdown 记忆文件。                        |
+| `reme auto_memory`                        | 将对话 messages 转为 daily 记忆卡片；需要 LLM 凭证。       |
+| `reme auto_resource`                      | 将 `resource/` 下的文件解读为 daily 资料卡片；需要 LLM 凭证。 |
+| `reme auto_dream` / `reme proactive`      | 将 daily 记忆整理为长期 digest，并暴露值得关注的主题。          |
+| `reme reindex`                            | 基于已有文件重建检索和 wikilink 索引。                    |
 
 ## 🤝 社区与支持
 
 - **问题反馈与需求**：请先查看 [Open Issues](https://github.com/agentscope-ai/ReMe/issues)；如无相关讨论，可新建 Issue
   说明背景、目标行为和影响范围。
-- **代码贡献**：改动前建议阅读 [贡献指南](https://docs.agentscope.io/reme/stable/zh/contributing)。架构与扩展方式以源码、schema 和测试为准。
+- **代码贡献**：改动前建议阅读 [贡献指南](https://docs.agentscope.io/reme/stable/zh/contributing)。架构与扩展方式以源码、schema
+  和测试为准。
 - **文档贡献**：用户可见文档请提交到[统一文档仓库](https://github.com/agentscope-ai/docs)的 `reme/<version>/{en,zh}/` 目录。
 - **提交规范**：建议使用 Conventional Commits，例如 `feat(search): add link expansion option`、
   `docs(zh): update quick start`。
diff --git a/reme/__init__.py b/reme/__init__.py
index bbeacdc9..0ca5442f 100644
--- a/reme/__init__.py
+++ b/reme/__init__.py
@@ -1,6 +1,6 @@
 """ReMe CLI package."""
 
-__version__ = "0.4.0.9"
+__version__ = "0.4.1.0"
 
 from . import config
 from . import constants
diff --git a/reme/config/default.yaml b/reme/config/default.yaml
index 12928842..2276ca23 100644
--- a/reme/config/default.yaml
+++ b/reme/config/default.yaml
@@ -599,20 +599,20 @@ components:
     default:
       backend: regex
 
-  as_embedding:
-    default:
-      backend: ${EMBEDDING_BACKEND:-openai}
-      model: ${EMBEDDING_MODEL_NAME:-text-embedding-v4}
-      dimensions: 1024
-      credential:
-        api_key: ${EMBEDDING_API_KEY:-}
-        base_url: ${EMBEDDING_BASE_URL:-https://dashscope.aliyuncs.com/compatible-mode/v1}
-      parameters: { }
-
-  embedding_store:
-    default:
-      backend: local
-      as_embedding: default
+#  as_embedding:
+#    default:
+#      backend: ${EMBEDDING_BACKEND:-openai}
+#      model: ${EMBEDDING_MODEL_NAME:-text-embedding-v4}
+#      dimensions: 1024
+#      credential:
+#        api_key: ${EMBEDDING_API_KEY:-}
+#        base_url: ${EMBEDDING_BASE_URL:-https://dashscope.aliyuncs.com/compatible-mode/v1}
+#      parameters: { }
+#
+#  embedding_store:
+#    default:
+#      backend: local
+#      as_embedding: default
 
   as_llm:
     default:
@@ -687,7 +687,7 @@ components:
     default:
       backend: local
       store_name: local
-      #  embedding_store: default
+#      embedding_store: default
       embedding_store: ""
       keyword_index: default
       file_graph: default