feat: release 2.0.6

feat(dream): add memory dream cli and docs
2026-06-02 18:17:11 +08:00 · 2026-04-14 12:37:53 +08:00 · 2026-04-14 12:08:57 +08:00 · 2026-04-14 11:03:53 +08:00 · 2026-04-13 22:08:15 +08:00 · 2026-04-13 21:32:52 +08:00
116 changed files with 6609 additions and 959 deletions
--- a/README.md
+++ b/README.md
@@ -1,13 +1,13 @@
-<p align="center"><img src= "https://github.com/user-attachments/assets/eca9a9ec-8534-4615-9e0f-96c5ac1d10a3" alt="Chatgpt-on-Wechat" width="550" /></p>
+<p align="center"><img src= "https://github.com/user-attachments/assets/eca9a9ec-8534-4615-9e0f-96c5ac1d10a3" alt="CowAgent" width="550" /></p>

 <p align="center">
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/chatgpt-on-wechat" alt="Latest release"></a>
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat/blob/master/LICENSE"><img src="https://img.shields.io/github/license/zhayujie/chatgpt-on-wechat" alt="License: MIT"></a>
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat"><img src="https://img.shields.io/github/stars/zhayujie/chatgpt-on-wechat?style=flat-square" alt="Stars"></a> <br/>
+  <a href="https://github.com/zhayujie/CowAgent/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/CowAgent" alt="Latest release"></a>
+  <a href="https://github.com/zhayujie/CowAgent/blob/master/LICENSE"><img src="https://img.shields.io/github/license/zhayujie/CowAgent" alt="License: MIT"></a>
+  <a href="https://github.com/zhayujie/CowAgent"><img src="https://img.shields.io/github/stars/zhayujie/CowAgent?style=flat-square" alt="Stars"></a> <br/>
  [中文] | [<a href="docs/en/README.md">English</a>] | [<a href="docs/ja/README.md">日本語</a>]
 </p>

-**CowAgent** 是基于大模型的超级 AI 助理，能够主动思考和任务规划、操作计算机和外部资源、创造和执行 Skills、拥有长期记忆并不断成长，比 OpenClaw 更轻量和便捷。CowAgent 支持灵活切换多种模型，能处理文本、语音、图片、文件等多模态消息，可接入微信、飞书、钉钉、企微智能机器人、QQ、企微自建应用、微信公众号、网页中使用，7*24小时运行于你的个人电脑或服务器中。
+**CowAgent** 是基于大模型的超级 AI 助理，能够主动思考和任务规划、操作计算机和外部资源、创造和执行 Skills、拥有长期记忆和知识库并不断成长，比 OpenClaw 更轻量和便捷。CowAgent 支持灵活切换多种模型，能处理文本、语音、图片、文件等多模态消息，可接入微信、飞书、钉钉、企微智能机器人、QQ、企微自建应用、微信公众号、网页中使用，7*24小时运行于你的个人电脑或服务器中。

 <p align="center">
  <a href="https://cowagent.ai/">🌐 官网</a> &nbsp;·&nbsp;
@@ -23,7 +23,8 @@
 > 该项目既是一个可以开箱即用的超级 AI 助理，也是一个支持高扩展的 Agent 框架，可以通过为项目扩展大模型接口、接入渠道、内置工具、Skills 系统来灵活实现各种定制需求。核心能力如下：

 -  ✅  **自主任务规划**：能够理解复杂任务并自主规划执行，持续思考和调用工具直到完成目标
-  ✅  **长期记忆：** 自动将对话记忆持久化至本地文件和数据库中，包括核心记忆和日级记忆，支持关键词及向量检索
+-  ✅  **长期记忆：** 自动将对话记忆持久化至本地文件和数据库中，包括核心记忆、日级记忆和梦境蒸馏，支持关键词及向量检索
+-  ✅  **个人知识库：** 自动整理结构化知识，通过交叉引用构建知识图谱，支持通过对话管理和可视化浏览知识库
 -  ✅  **技能系统：** Skills 安装和运行的引擎，支持从 [Skill Hub](https://skills.cowagent.ai/)、GitHub 等一键安装技能，或通过对话创造 Skills
 -  ✅  **工具系统：** 内置文件读写、终端执行、浏览器操作、定时任务等工具，Agent 自主调用以完成复杂任务
 -  ✅  **CLI系统：** 提供终端命令和对话命令，支持进程管理、技能安装、配置修改等操作
@@ -69,17 +70,19 @@

 # 🏷 更新日志

->**2026.04.01：** [2.0.5版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.5)，Cow CLI 命令系统、Skill Hub 开源、浏览器工具、企微扫码创建、多项优化和修复。
+>**2026.04.14：** [2.0.6版本](https://github.com/zhayujie/CowAgent/releases/tag/2.0.6)，知识库系统、梦境记忆模块、上下文智能压缩、Web 控制台多会话及多项优化。

->**2026.03.22：** [2.0.4版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.4)，新增个人微信通道（微信扫码即用）、新增 MiniMax-M2.7 和 GLM-5-Turbo 模型、run.sh 脚本重构、日文文档及多项修复。
+>**2026.04.01：** [2.0.5版本](https://github.com/zhayujie/CowAgent/releases/tag/2.0.5)，Cow CLI 命令系统、Skill Hub 开源、浏览器工具、企微扫码创建、多项优化和修复。

->**2026.03.18：** [2.0.3版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.3)，新增企微智能机器人和 QQ 通道、支持 Coding Plan、新增多个模型、Web 端文件处理、记忆系统升级。
+>**2026.03.22：** [2.0.4版本](https://github.com/zhayujie/CowAgent/releases/tag/2.0.4)，新增个人微信通道（微信扫码即用）、新增 MiniMax-M2.7 和 GLM-5-Turbo 模型、run.sh 脚本重构、日文文档及多项修复。

->**2026.02.27：** [2.0.2版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.2)，Web 控制台全面升级（流式对话、模型/技能/记忆/通道/定时任务/日志管理）、支持多通道同时运行、会话持久化存储、新增多个模型。
+>**2026.03.18：** [2.0.3版本](https://github.com/zhayujie/CowAgent/releases/tag/2.0.3)，新增企微智能机器人和 QQ 通道、支持 Coding Plan、新增多个模型、Web 端文件处理、记忆系统升级。

->**2026.02.13：** [2.0.1版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.1)，内置 Web Search 工具、智能上下文裁剪策略、运行时信息动态更新、Windows 兼容性适配，修复定时任务记忆丢失、飞书连接等多项问题。
+>**2026.02.27：** [2.0.2版本](https://github.com/zhayujie/CowAgent/releases/tag/2.0.2)，Web 控制台全面升级（流式对话、模型/技能/记忆/通道/定时任务/日志管理）、支持多通道同时运行、会话持久化存储、新增多个模型。

->**2026.02.03：** [2.0.0版本](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.0)，正式升级为超级 Agent 助理，支持多轮任务决策、具备长期记忆、实现多种系统工具、支持 Skills 框架，新增多种模型并优化了接入渠道。
+>**2026.02.13：** [2.0.1版本](https://github.com/zhayujie/CowAgent/releases/tag/2.0.1)，内置 Web Search 工具、智能上下文裁剪策略、运行时信息动态更新、Windows 兼容性适配，修复定时任务记忆丢失、飞书连接等多项问题。
+
+>**2026.02.03：** [2.0.0版本](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0)，正式升级为超级 Agent 助理，支持多轮任务决策、具备长期记忆、实现多种系统工具、支持 Skills 框架，新增多种模型并优化了接入渠道。

 更多更新历史请查看: [更新日志](https://docs.cowagent.ai/releases)

@@ -116,18 +119,18 @@ irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex

 ### 2.环境安装

-支持 Linux、MacOS、Windows 操作系统，可在个人计算机及服务器上运行，需安装 `Python`，Python 版本需在3.7 ~ 3.12 之间。
+支持 Linux、MacOS、Windows 操作系统，可在个人计算机及服务器上运行，需安装 `Python`，Python 版本需在 3.7 ~ 3.13 之间。

 > 注意：Agent 模式推荐使用源码运行，若选择 Docker 部署则无需安装 python 环境和下载源码，可直接快进到下一节。

 **(1) 克隆项目代码：**

 ```bash
-git clone https://github.com/zhayujie/chatgpt-on-wechat
-cd chatgpt-on-wechat/
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
 ```

-若遇到网络问题可使用国内仓库地址：https://gitee.com/zhayujie/chatgpt-on-wechat
+若遇到网络问题可使用国内仓库地址：https://gitee.com/zhayujie/CowAgent

 **(2) 安装核心依赖 (必选)：**

@@ -197,11 +200,13 @@ cow install-browser
  "group_speech_recognition": false,                          # 是否开启群组语音识别
  "voice_reply_voice": false,                                 # 是否使用语音回复语音
  "use_linkai": false,                                        # 是否使用 LinkAI 接口，默认关闭，设置为 true 后可对接 LinkAI 平台模型
+  "web_password": "",                                         # Web 控制台访问密码，留空则不启用密码保护
  "agent": true,                                              # 是否启用 Agent 模式，启用后拥有多轮工具决策、长期记忆、Skills 能力等
  "agent_workspace": "~/cow",                                 # Agent 的工作空间路径，用于存储 memory、skills、系统设定等
-  "agent_max_context_tokens": 40000,                          # Agent 模式下最大上下文 tokens，超出将自动丢弃最早的上下文
-  "agent_max_context_turns": 30,                              # Agent 模式下最大上下文记忆轮次，每轮包括一次用户提问和 AI 回复
-  "agent_max_steps": 15                                       # Agent 模式下单次任务的最大决策步数，超出后将停止继续调用工具
+  "agent_max_context_tokens": 50000,                          # Agent 模式下最大上下文 tokens，超出将自动智能压缩处理
+  "agent_max_context_turns": 20,                              # Agent 模式下最大上下文记忆轮次，一问一答为一轮，超出后智能压缩处理
+  "agent_max_steps": 20,                                      # Agent 模式下单次任务的最大决策步数，超出后将停止继续调用工具
+  "enable_thinking": true                                     # 是否启用深度思考，开启后 Web 端展示模型推理过程，关闭后可加速响应
 }
 ```

@@ -213,12 +218,13 @@ cow install-browser
 + 添加 `"speech_recognition": true` 将开启语音识别，默认使用 openai 的 whisper 模型识别为文字，同时以文字回复，该参数仅支持私聊 (注意由于语音消息无法匹配前缀，一旦开启将对所有语音自动回复，支持语音触发画图)；
 + 添加 `"group_speech_recognition": true` 将开启群组语音识别，默认使用 openai 的 whisper 模型识别为文字，同时以文字回复，参数仅支持群聊 (会匹配 group_chat_prefix 和 group_chat_keyword, 支持语音触发画图)；
 + 添加 `"voice_reply_voice": true` 将开启语音回复语音（同时作用于私聊和群聊）
+ 使用 MiniMax TTS：设置 `"text_to_voice": "minimax"`，并配置 `minimax_api_key`；可通过 `"tts_voice_id"` 指定发音人（如 `English_Graceful_Lady`），`"text_to_voice_model"` 指定模型（如 `speech-2.8-hd`、`speech-2.8-turbo`）
 </details>

 <details>
 <summary>2. 其他配置</summary>

-+ `model`: 模型名称，Agent 模式下推荐使用 `MiniMax-M2.7`、`glm-5-turbo`、`kimi-k2.5`、`qwen3.6-plus`、`claude-sonnet-4-6`、`gemini-3.1-pro-preview`，全部模型名称参考[common/const.py](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/common/const.py)文件
+ `model`: 模型名称，Agent 模式下推荐使用 `MiniMax-M2.7`、`glm-5-turbo`、`kimi-k2.5`、`qwen3.6-plus`、`claude-sonnet-4-6`、`gemini-3.1-pro-preview`，全部模型名称参考[common/const.py](https://github.com/zhayujie/CowAgent/blob/master/common/const.py)文件
 + `character_desc`：普通对话模式下的机器人系统提示词。在 Agent 模式下该配置不生效，由工作空间中的文件内容构成。
 + `subscribe_msg`：订阅消息，公众号和企业微信 channel 中请填写，当被订阅时会自动回复， 可使用特殊占位符。目前支持的占位符有{trigger_prefix}，在程序中它会自动替换成 bot 的触发词。
 </details>
@@ -230,7 +236,7 @@ cow install-browser
 + `linkai_api_key`: LinkAI Api Key，可在 [控制台](https://link-ai.tech/console/interface) 创建
 </details>

-注：全部配置项说明可在 [`config.py`](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/config.py) 文件中查看。
+注：全部配置项说明可在 [`config.py`](https://github.com/zhayujie/CowAgent/blob/master/config.py) 文件中查看。

 ## 三、运行

@@ -357,7 +363,7 @@ sudo docker logs -f chatgpt-on-wechat
    "minimax_api_key": ""
 }
 ```
- - `model`: 可填写 `MiniMax-M2.7、MiniMax-M2.5、MiniMax-M2.1、MiniMax-M2.1-lightning、MiniMax-M2、abab6.5-chat` 等
+ - `model`: 可填写 `MiniMax-M2.7、MiniMax-M2.7-highspeed、MiniMax-M2.5、MiniMax-M2.1、MiniMax-M2.1-lightning、MiniMax-M2、abab6.5-chat` 等
 - `minimax_api_key`：MiniMax 平台的 API-KEY，在 [控制台](https://platform.minimaxi.com/user-center/basic-information/interface-key) 创建

 方式二：OpenAI 兼容方式接入，配置如下：
@@ -370,7 +376,7 @@ sudo docker logs -f chatgpt-on-wechat
 }
 ```
 - `bot_type`: OpenAI 兼容方式
- `model`: 可填 `MiniMax-M2.7、MiniMax-M2.5、MiniMax-M2.1、MiniMax-M2.1-lightning、MiniMax-M2`，参考[API文档](https://platform.minimaxi.com/document/%E5%AF%B9%E8%AF%9D?key=66701d281d57f38758d581d0#QklxsNSbaf6kM4j6wjO5eEek)
+- `model`: 可填 `MiniMax-M2.7、MiniMax-M2.7-highspeed、MiniMax-M2.5、MiniMax-M2.1、MiniMax-M2.1-lightning、MiniMax-M2`，参考[API文档](https://platform.minimaxi.com/document/%E5%AF%B9%E8%AF%9D?key=66701d281d57f38758d581d0#QklxsNSbaf6kM4j6wjO5eEek)
 - `open_ai_api_base`: MiniMax 平台 API 的 BASE URL
 - `open_ai_api_key`: MiniMax 平台的 API-KEY
 </details>
@@ -708,6 +714,7 @@ Coding Plan 是各厂商推出的编程包月套餐，所有厂商均可通过 O
 ```

 - `web_port`: 默认为 9899，可按需更改，需要服务器防火墙和安全组放行该端口
+- `web_password`: 访问密码，留空则不启用密码保护。部署在公网环境时建议设置
 - 如本地运行，启动后请访问 `http://localhost:9899/chat` ；如服务器运行，请访问 `http://ip:9899/chat` 
 > 注：请将上述 url 中的 ip 或者 port 替换为实际的值
 </details>
@@ -878,18 +885,28 @@ QQ 机器人使用 WebSocket 长连接模式，无需公网 IP 和域名，支

 # 🔎 常见问题

-FAQs： <https://github.com/zhayujie/chatgpt-on-wechat/wiki/FAQs>
+FAQs： <https://github.com/zhayujie/CowAgent/wiki/FAQs>

 或直接在线咨询 [项目小助手](https://link-ai.tech/app/Kv2fXJcH)  (知识库持续完善中，回复供参考)

 # 🛠️ 开发

-欢迎接入更多应用通道，参考 [飞书通道](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/channel/feishu/feishu_channel.py) 新增自定义通道，实现接收和发送消息逻辑即可完成接入。同时欢迎贡献新的 Skills，向 [Skill Hub](https://skills.cowagent.ai/submit) 提交技能。
+欢迎接入更多应用通道，参考 [飞书通道](https://github.com/zhayujie/CowAgent/blob/master/channel/feishu/feishu_channel.py) 新增自定义通道，实现接收和发送消息逻辑即可完成接入。同时欢迎贡献新的 Skills，向 [Skill Hub](https://skills.cowagent.ai/submit) 提交技能。

 # ✉ 联系

-欢迎提交PR、Issues进行反馈，以及通过 🌟Star 支持并关注项目更新。项目运行遇到问题可以查看 [常见问题列表](https://github.com/zhayujie/chatgpt-on-wechat/wiki/FAQs) ，以及前往 [Issues](https://github.com/zhayujie/chatgpt-on-wechat/issues) 中搜索。个人开发者可加入开源交流群参与更多讨论，企业用户可联系[产品客服](https://cdn.link-ai.tech/portal/linkai-customer-service.png)咨询。
+欢迎提交PR、Issues进行反馈，以及通过 🌟Star 支持并关注项目更新。项目运行遇到问题可以查看 [常见问题列表](https://github.com/zhayujie/CowAgent/wiki/FAQs) ，以及前往 [Issues](https://github.com/zhayujie/CowAgent/issues) 中搜索。个人开发者可加入开源交流群参与更多讨论，企业用户可联系[产品客服](https://cdn.link-ai.tech/portal/linkai-customer-service.png)咨询。

 # 🌟 贡献者

-![cow contributors](https://contrib.rocks/image?repo=zhayujie/chatgpt-on-wechat&max=1000)
+![cow contributors](https://contrib.rocks/image?repo=zhayujie/CowAgent&max=1000)
+
+# 📌 项目更名说明
+
+本项目原名 `chatgpt-on-wechat`（GitHub 原地址：https://github.com/zhayujie/chatgpt-on-wechat ），
+于 2026.04.13 正式更名为 **CowAgent**。GitHub 已自动设置重定向，原有链接仍可正常访问。
+
+如需更新本地仓库的远程地址（可选）：
+```bash
+git remote set-url origin https://github.com/zhayujie/CowAgent.git
+```
--- a/agent/chat/service.py
+++ b/agent/chat/service.py
@@ -57,7 +57,16 @@ class ChatService:
            event_type = event.get("type")
            data = event.get("data", {})

-            if event_type == "message_update":
+            if event_type == "reasoning_update":
+                delta = data.get("delta", "")
+                if delta:
+                    send_chunk_fn({
+                        "chunk_type": "reasoning",
+                        "delta": delta,
+                        "segment_id": state.segment_id,
+                    })
+
+            elif event_type == "message_update":
                # Incremental text delta
                delta = data.get("delta", "")
                if delta:
--- a/agent/knowledge/init.py
+++ b/agent/knowledge/init.py
--- a/agent/knowledge/service.py
+++ b/agent/knowledge/service.py
@@ -0,0 +1,218 @@
+"""
+Knowledge service for handling knowledge base operations.
+
+Provides a unified interface for listing, reading, and graphing knowledge files,
+callable from the web console, API, or CLI.
+
+Knowledge file layout (under workspace_root):
+    knowledge/index.md
+    knowledge/log.md
+    knowledge/<category>/<slug>.md
+"""
+
+import os
+import re
+from pathlib import Path
+from typing import Optional
+
+from common.log import logger
+from config import conf
+
+
+class KnowledgeService:
+    """
+    High-level service for knowledge base queries.
+    Operates directly on the filesystem.
+    """
+
+    def __init__(self, workspace_root: str):
+        self.workspace_root = workspace_root
+        self.knowledge_dir = os.path.join(workspace_root, "knowledge")
+
+    # ------------------------------------------------------------------
+    # list — directory tree with stats
+    # ------------------------------------------------------------------
+    def list_tree(self) -> dict:
+        """
+        Return the knowledge directory tree grouped by category.
+
+        Returns::
+
+            {
+                "tree": [
+                    {
+                        "dir": "concepts",
+                        "files": [
+                            {"name": "moe.md", "title": "MoE", "size": 1234},
+                            ...
+                        ]
+                    },
+                    ...
+                ],
+                "stats": {"pages": 15, "size": 32768},
+                "enabled": true
+            }
+        """
+        if not os.path.isdir(self.knowledge_dir):
+            return {"tree": [], "stats": {"pages": 0, "size": 0}, "enabled": conf().get("knowledge", True)}
+
+        tree = []
+        total_files = 0
+        total_bytes = 0
+        for name in sorted(os.listdir(self.knowledge_dir)):
+            full = os.path.join(self.knowledge_dir, name)
+            if not os.path.isdir(full) or name.startswith("."):
+                continue
+            files = []
+            for fname in sorted(os.listdir(full)):
+                if fname.endswith(".md") and not fname.startswith("."):
+                    fpath = os.path.join(full, fname)
+                    size = os.path.getsize(fpath)
+                    total_files += 1
+                    total_bytes += size
+                    title = fname.replace(".md", "")
+                    try:
+                        with open(fpath, "r", encoding="utf-8") as f:
+                            first_line = f.readline().strip()
+                        if first_line.startswith("# "):
+                            title = first_line[2:].strip()
+                    except Exception:
+                        pass
+                    files.append({"name": fname, "title": title, "size": size})
+            tree.append({"dir": name, "files": files})
+
+        return {
+            "tree": tree,
+            "stats": {"pages": total_files, "size": total_bytes},
+            "enabled": conf().get("knowledge", True),
+        }
+
+    # ------------------------------------------------------------------
+    # read — single file content
+    # ------------------------------------------------------------------
+    def read_file(self, rel_path: str) -> dict:
+        """
+        Read a single knowledge markdown file.
+
+        :param rel_path: Relative path within knowledge/, e.g. ``concepts/moe.md``
+        :return: dict with ``content`` and ``path``
+        :raises ValueError: if path is invalid or escapes knowledge dir
+        :raises FileNotFoundError: if file does not exist
+        """
+        if not rel_path or ".." in rel_path:
+            raise ValueError("invalid path")
+
+        full_path = os.path.normpath(os.path.join(self.knowledge_dir, rel_path))
+        allowed = os.path.normpath(self.knowledge_dir)
+        if not full_path.startswith(allowed + os.sep) and full_path != allowed:
+            raise ValueError("path outside knowledge dir")
+
+        if not os.path.isfile(full_path):
+            raise FileNotFoundError(f"file not found: {rel_path}")
+
+        with open(full_path, "r", encoding="utf-8") as f:
+            content = f.read()
+        return {"content": content, "path": rel_path}
+
+    # ------------------------------------------------------------------
+    # graph — nodes and links for visualization
+    # ------------------------------------------------------------------
+    def build_graph(self) -> dict:
+        """
+        Parse all knowledge pages and extract cross-reference links.
+
+        Returns::
+
+            {
+                "nodes": [
+                    {"id": "concepts/moe.md", "label": "MoE", "category": "concepts"},
+                    ...
+                ],
+                "links": [
+                    {"source": "concepts/moe.md", "target": "entities/deepseek.md"},
+                    ...
+                ]
+            }
+        """
+        knowledge_path = Path(self.knowledge_dir)
+        if not knowledge_path.is_dir():
+            return {"nodes": [], "links": []}
+
+        nodes = {}
+        links = []
+        link_re = re.compile(r'\[([^\]]*)\]\(([^)]+\.md)\)')
+
+        for md_file in knowledge_path.rglob("*.md"):
+            rel = str(md_file.relative_to(knowledge_path))
+            if rel in ("index.md", "log.md"):
+                continue
+            parts = rel.split("/")
+            category = parts[0] if len(parts) > 1 else "root"
+            title = md_file.stem.replace("-", " ").title()
+            try:
+                content = md_file.read_text(encoding="utf-8")
+                first_line = content.strip().split("\n")[0]
+                if first_line.startswith("# "):
+                    title = first_line[2:].strip()
+                for _, link_target in link_re.findall(content):
+                    resolved = (md_file.parent / link_target).resolve()
+                    try:
+                        target_rel = str(resolved.relative_to(knowledge_path))
+                    except ValueError:
+                        continue
+                    if target_rel != rel:
+                        links.append({"source": rel, "target": target_rel})
+            except Exception:
+                pass
+            nodes[rel] = {"id": rel, "label": title, "category": category}
+
+        valid_ids = set(nodes.keys())
+        links = [l for l in links if l["source"] in valid_ids and l["target"] in valid_ids]
+        seen = set()
+        deduped = []
+        for l in links:
+            key = tuple(sorted([l["source"], l["target"]]))
+            if key not in seen:
+                seen.add(key)
+                deduped.append(l)
+
+        return {"nodes": list(nodes.values()), "links": deduped}
+
+    # ------------------------------------------------------------------
+    # dispatch — single entry point for protocol messages
+    # ------------------------------------------------------------------
+    def dispatch(self, action: str, payload: Optional[dict] = None) -> dict:
+        """
+        Dispatch a knowledge management action.
+
+        :param action: ``list``, ``read``, or ``graph``
+        :param payload: action-specific payload
+        :return: protocol-compatible response dict
+        """
+        payload = payload or {}
+        try:
+            if action == "list":
+                result = self.list_tree()
+                return {"action": action, "code": 200, "message": "success", "payload": result}
+
+            elif action == "read":
+                path = payload.get("path")
+                if not path:
+                    return {"action": action, "code": 400, "message": "path is required", "payload": None}
+                result = self.read_file(path)
+                return {"action": action, "code": 200, "message": "success", "payload": result}
+
+            elif action == "graph":
+                result = self.build_graph()
+                return {"action": action, "code": 200, "message": "success", "payload": result}
+
+            else:
+                return {"action": action, "code": 400, "message": f"unknown action: {action}", "payload": None}
+
+        except ValueError as e:
+            return {"action": action, "code": 403, "message": str(e), "payload": None}
+        except FileNotFoundError as e:
+            return {"action": action, "code": 404, "message": str(e), "payload": None}
+        except Exception as e:
+            logger.error(f"[KnowledgeService] dispatch error: action={action}, error={e}")
+            return {"action": action, "code": 500, "message": str(e), "payload": None}
--- a/agent/memory/conversation_store.py
+++ b/agent/memory/conversation_store.py
@@ -28,11 +28,13 @@ from common.log import logger

 _DDL = """
 CREATE TABLE IF NOT EXISTS sessions (
-    session_id   TEXT    PRIMARY KEY,
-    channel_type TEXT    NOT NULL DEFAULT '',
-    created_at   INTEGER NOT NULL,
-    last_active  INTEGER NOT NULL,
-    msg_count    INTEGER NOT NULL DEFAULT 0
+    session_id        TEXT    PRIMARY KEY,
+    channel_type      TEXT    NOT NULL DEFAULT '',
+    title             TEXT    NOT NULL DEFAULT '',
+    context_start_seq INTEGER NOT NULL DEFAULT 0,
+    created_at        INTEGER NOT NULL,
+    last_active       INTEGER NOT NULL,
+    msg_count         INTEGER NOT NULL DEFAULT 0
 );

 CREATE TABLE IF NOT EXISTS messages (
@@ -57,6 +59,14 @@ _MIGRATION_ADD_CHANNEL_TYPE = """
 ALTER TABLE sessions ADD COLUMN channel_type TEXT NOT NULL DEFAULT '';
 """

+_MIGRATION_ADD_TITLE = """
+ALTER TABLE sessions ADD COLUMN title TEXT NOT NULL DEFAULT '';
+"""
+
+_MIGRATION_ADD_CONTEXT_START_SEQ = """
+ALTER TABLE sessions ADD COLUMN context_start_seq INTEGER NOT NULL DEFAULT 0;
+"""
+
 DEFAULT_MAX_AGE_DAYS: int = 30


@@ -188,8 +198,9 @@ def _group_into_display_turns(
            if text:
                turns.append({"role": "user", "content": text, "created_at": created_at})

-        # Collect all tool_calls and tool_results from the rest of the group
-        all_tool_calls: List[Dict[str, Any]] = []
+        # Build an ordered list of steps preserving the original sequence:
+        #   thinking → content → tool_call → content → ...
+        steps: List[Dict[str, Any]] = []
        tool_results: Dict[str, str] = {}
        final_text = ""
        final_ts: Optional[int] = None
@@ -198,24 +209,46 @@ def _group_into_display_turns(
            if role == "user":
                tool_results.update(_extract_tool_results(content))
            elif role == "assistant":
-                tcs = _extract_tool_calls(content)
-                all_tool_calls.extend(tcs)
-                t = _extract_display_text(content)
-                if t:
-                    final_text = t
+                # Walk content blocks in order to preserve interleaving
+                if isinstance(content, list):
+                    for block in content:
+                        if not isinstance(block, dict):
+                            continue
+                        btype = block.get("type")
+                        if btype == "thinking":
+                            txt = block.get("thinking", "").strip()
+                            if txt:
+                                steps.append({"type": "thinking", "content": txt})
+                        elif btype == "text":
+                            txt = block.get("text", "").strip()
+                            if txt:
+                                steps.append({"type": "content", "content": txt})
+                                final_text = txt
+                        elif btype == "tool_use":
+                            steps.append({
+                                "type": "tool",
+                                "id": block.get("id", ""),
+                                "name": block.get("name", ""),
+                                "arguments": block.get("input", {}),
+                            })
+                elif isinstance(content, str) and content.strip():
+                    steps.append({"type": "content", "content": content.strip()})
+                    final_text = content.strip()
                final_ts = created_at

-        # Attach tool results to their matching tool_call entries
-        for tc in all_tool_calls:
-            tc["result"] = tool_results.get(tc.get("id", ""), "")
+        # Attach tool results to tool steps
+        for step in steps:
+            if step["type"] == "tool":
+                step["result"] = tool_results.get(step.get("id", ""), "")

-        if final_text or all_tool_calls:
-            turns.append({
+        if steps or final_text:
+            turn = {
                "role": "assistant",
                "content": final_text,
-                "tool_calls": all_tool_calls,
+                "steps": steps,
                "created_at": final_ts or (user_row[1] if user_row else 0),
-            })
+            }
+            turns.append(turn)

    return turns

@@ -264,14 +297,21 @@ class ConversationStore:
        with self._lock:
            conn = self._connect()
            try:
+                # Respect context_start_seq: only load messages at or after the boundary
+                ctx_row = conn.execute(
+                    "SELECT context_start_seq FROM sessions WHERE session_id = ?",
+                    (session_id,),
+                ).fetchone()
+                ctx_start = ctx_row[0] if ctx_row else 0
+
                rows = conn.execute(
                    """
                    SELECT seq, role, content
                    FROM messages
-                    WHERE session_id = ?
+                    WHERE session_id = ? AND seq >= ?
                    ORDER BY seq DESC
                    """,
-                    (session_id,),
+                    (session_id, ctx_start),
                ).fetchall()
            finally:
                conn.close()
@@ -279,10 +319,7 @@ class ConversationStore:
        if not rows:
            return []

-        # Walk newest-to-oldest counting *visible* user turns (actual user text,
-        # not tool_result injections).  Record the seq of every visible user
-        # message so we can find a clean cut point later.
-        visible_turn_seqs: List[int] = []  # newest first
+        visible_turn_seqs: List[int] = []
        for seq, role, raw_content in rows:
            if role != "user":
                continue
@@ -293,17 +330,11 @@ class ConversationStore:
            if _is_visible_user_message(content):
                visible_turn_seqs.append(seq)

-        # Determine the seq of the oldest visible user message we want to keep.
-        # If the total turns fit within max_turns, keep everything.
        if len(visible_turn_seqs) <= max_turns:
-            cutoff_seq = None  # keep all
+            cutoff_seq = None
        else:
-            # The Nth visible user message (0-indexed) is the oldest we keep.
            cutoff_seq = visible_turn_seqs[max_turns - 1]

-        # Build result in chronological order, starting from cutoff.
-        # IMPORTANT: we start exactly at cutoff_seq (the visible user message),
-        # never mid-group, so tool_use / tool_result pairs are always complete.
        result = []
        for seq, role, raw_content in reversed(rows):
            if cutoff_seq is not None and seq < cutoff_seq:
@@ -312,6 +343,9 @@ class ConversationStore:
                content = json.loads(raw_content)
            except Exception:
                content = raw_content
+            # Strip thinking blocks — they are stored for UI display only
+            if role == "assistant" and isinstance(content, list):
+                content = [b for b in content if b.get("type") != "thinking"]
            result.append({"role": role, "content": content})
        return result

@@ -389,6 +423,61 @@ class ConversationStore:
                        """,
                        (session_id, session_id),
                    )
+
+                    # Auto-generate title from the first visible user message
+                    cur_title = conn.execute(
+                        "SELECT title FROM sessions WHERE session_id = ?",
+                        (session_id,),
+                    ).fetchone()
+                    if cur_title and not cur_title[0]:
+                        for msg in messages:
+                            if msg.get("role") == "user":
+                                content = msg.get("content", "")
+                                text = _extract_display_text(content)
+                                if text:
+                                    title = text[:50].split("\n")[0]
+                                    conn.execute(
+                                        "UPDATE sessions SET title = ? WHERE session_id = ?",
+                                        (title, session_id),
+                                    )
+                                    break
+            finally:
+                conn.close()
+
+    def clear_context(self, session_id: str) -> int:
+        """
+        Set the context boundary to after the current last message.
+        Messages before this boundary are still stored but excluded from LLM context.
+
+        Returns the new context_start_seq value.
+        """
+        with self._lock:
+            conn = self._connect()
+            try:
+                with conn:
+                    row = conn.execute(
+                        "SELECT COALESCE(MAX(seq), -1) FROM messages WHERE session_id = ?",
+                        (session_id,),
+                    ).fetchone()
+                    new_start = row[0] + 1
+                    conn.execute(
+                        "UPDATE sessions SET context_start_seq = ? WHERE session_id = ?",
+                        (new_start, session_id),
+                    )
+                    return new_start
+            finally:
+                conn.close()
+
+    def get_context_start_seq(self, session_id: str) -> int:
+        """Return the context_start_seq for a session (0 if not set)."""
+        with self._lock:
+            conn = self._connect()
+            try:
+                row = conn.execute(
+                    "SELECT context_start_seq FROM sessions WHERE session_id = ?",
+                    (session_id,),
+                ).fetchone()
+                return row[0] if row else 0
            finally:
                conn.close()

@@ -410,6 +499,7 @@ class ConversationStore:
    def cleanup_old_sessions(self, max_age_days: Optional[int] = None) -> int:
        """
        Delete sessions that have not been active within max_age_days.
+        Web channel sessions are excluded — they are meant to be permanent.

        Args:
            max_age_days: Override the default retention period.
@@ -433,7 +523,8 @@ class ConversationStore:
            try:
                with conn:
                    stale = conn.execute(
-                        "SELECT session_id FROM sessions WHERE last_active < ?",
+                        "SELECT session_id FROM sessions "
+                        "WHERE last_active < ? AND channel_type != 'web'",
                        (cutoff,),
                    ).fetchall()
                    for (sid,) in stale:
@@ -492,9 +583,15 @@ class ConversationStore:
        with self._lock:
            conn = self._connect()
            try:
+                ctx_row = conn.execute(
+                    "SELECT context_start_seq FROM sessions WHERE session_id = ?",
+                    (session_id,),
+                ).fetchone()
+                ctx_start = ctx_row[0] if ctx_row else 0
+
                rows = conn.execute(
                    """
-                    SELECT role, content, created_at
+                    SELECT seq, role, content, created_at
                    FROM messages
                    WHERE session_id = ?
                    ORDER BY seq ASC
@@ -504,7 +601,30 @@ class ConversationStore:
            finally:
                conn.close()

-        visible = _group_into_display_turns(rows)
+        # Strip seq for display grouping, but record max seq per visible user group
+        plain_rows = [(role, content, created_at) for _seq, role, content, created_at in rows]
+        visible = _group_into_display_turns(plain_rows)
+
+        # Build a mapping: find the seq of each visible user message to annotate context boundary.
+        # Walk through rows to find visible user message seqs in order.
+        visible_user_seqs: List[int] = []
+        for seq, role, raw_content, _ts in rows:
+            if role != "user":
+                continue
+            try:
+                content = json.loads(raw_content)
+            except Exception:
+                content = raw_content
+            if _is_visible_user_message(content):
+                visible_user_seqs.append(seq)
+
+        # Each pair of display turns (user+assistant) corresponds to a visible user seq.
+        # Mark which turns are before the context boundary.
+        user_turn_idx = 0
+        for turn in visible:
+            if turn["role"] == "user" and user_turn_idx < len(visible_user_seqs):
+                turn["_seq"] = visible_user_seqs[user_turn_idx]
+                user_turn_idx += 1

        total = len(visible)
        offset = (page - 1) * page_size
@@ -513,12 +633,98 @@ class ConversationStore:

        return {
            "messages": page_items,
+            "context_start_seq": ctx_start,
            "total": total,
            "page": page,
            "page_size": page_size,
            "has_more": offset + page_size < total,
        }

+    def list_sessions(
+        self,
+        channel_type: Optional[str] = None,
+        page: int = 1,
+        page_size: int = 50,
+    ) -> Dict[str, Any]:
+        """
+        List sessions ordered by last_active DESC, with optional channel_type filter.
+
+        Returns:
+            {
+                "sessions": [{session_id, title, created_at, last_active, msg_count}, ...],
+                "total": int,
+                "page": int,
+                "page_size": int,
+                "has_more": bool,
+            }
+        """
+        page = max(1, page)
+        with self._lock:
+            conn = self._connect()
+            try:
+                if channel_type:
+                    total = conn.execute(
+                        "SELECT COUNT(*) FROM sessions WHERE channel_type = ?",
+                        (channel_type,),
+                    ).fetchone()[0]
+                    rows = conn.execute(
+                        """
+                        SELECT session_id, title, created_at, last_active, msg_count
+                        FROM sessions
+                        WHERE channel_type = ?
+                        ORDER BY last_active DESC
+                        LIMIT ? OFFSET ?
+                        """,
+                        (channel_type, page_size, (page - 1) * page_size),
+                    ).fetchall()
+                else:
+                    total = conn.execute(
+                        "SELECT COUNT(*) FROM sessions",
+                    ).fetchone()[0]
+                    rows = conn.execute(
+                        """
+                        SELECT session_id, title, created_at, last_active, msg_count
+                        FROM sessions
+                        ORDER BY last_active DESC
+                        LIMIT ? OFFSET ?
+                        """,
+                        (page_size, (page - 1) * page_size),
+                    ).fetchall()
+            finally:
+                conn.close()
+
+        sessions = [
+            {
+                "session_id": r[0],
+                "title": r[1],
+                "created_at": r[2],
+                "last_active": r[3],
+                "msg_count": r[4],
+            }
+            for r in rows
+        ]
+        return {
+            "sessions": sessions,
+            "total": total,
+            "page": page,
+            "page_size": page_size,
+            "has_more": (page - 1) * page_size + page_size < total,
+        }
+
+    def rename_session(self, session_id: str, title: str) -> bool:
+        """Update the title of a session. Returns True if the session existed."""
+        with self._lock:
+            conn = self._connect()
+            try:
+                with conn:
+                    cur = conn.execute(
+                        "UPDATE sessions SET title = ? WHERE session_id = ?",
+                        (title, session_id),
+                    )
+                    return cur.rowcount > 0
+            finally:
+                conn.close()
+
    def get_stats(self) -> Dict[str, Any]:
        """Return basic stats keyed by channel_type, for monitoring."""
        with self._lock:
@@ -573,6 +779,20 @@ class ConversationStore:
                logger.info("[ConversationStore] Migrated: added channel_type column")
            except Exception as e:
                logger.warning(f"[ConversationStore] Migration failed: {e}")
+        if "title" not in cols:
+            try:
+                conn.execute(_MIGRATION_ADD_TITLE)
+                conn.commit()
+                logger.info("[ConversationStore] Migrated: added title column")
+            except Exception as e:
+                logger.warning(f"[ConversationStore] Migration (title) failed: {e}")
+        if "context_start_seq" not in cols:
+            try:
+                conn.execute(_MIGRATION_ADD_CONTEXT_START_SEQ)
+                conn.commit()
+                logger.info("[ConversationStore] Migrated: added context_start_seq column")
+            except Exception as e:
+                logger.warning(f"[ConversationStore] Migration (context_start_seq) failed: {e}")

    def _connect(self) -> sqlite3.Connection:
        conn = sqlite3.connect(str(self._db_path), timeout=10)
--- a/agent/memory/manager.py
+++ b/agent/memory/manager.py
@@ -285,6 +285,10 @@ class MemoryManager:
        # Scan memory directory (including daily summaries)
        if memory_dir.exists():
            for file_path in memory_dir.rglob("*.md"):
+                # Skip hidden directories (e.g. .dreams/)
+                if any(part.startswith('.') for part in file_path.relative_to(workspace_dir).parts):
+                    continue
+
                # Determine scope and user_id from path
                rel_path = file_path.relative_to(workspace_dir)
                parts = rel_path.parts
@@ -312,6 +316,14 @@ class MemoryManager:
                    scope = "shared"
                
                await self._sync_file(file_path, "memory", scope, user_id)
+
+        # Scan knowledge directory (structured knowledge wiki)
+        from config import conf
+        if conf().get("knowledge", True):
+            knowledge_dir = Path(workspace_dir) / "knowledge"
+            if knowledge_dir.exists():
+                for file_path in knowledge_dir.rglob("*.md"):
+                    await self._sync_file(file_path, "knowledge", "shared", None)
        
        self._dirty = False
    
@@ -389,24 +401,28 @@ class MemoryManager:
        user_id: Optional[str] = None,
        reason: str = "threshold",
        max_messages: int = 10,
+        context_summary_callback=None,
    ) -> bool:
        """
        Flush conversation summary to daily memory file.
-        
+
        Args:
            messages: Conversation message list
            user_id: Optional user ID
            reason: "threshold" | "overflow" | "daily_summary"
            max_messages: Max recent messages to include (0 = all)
-        
+            context_summary_callback: Optional callback(str) invoked with the
+                daily summary text for in-context injection
+
        Returns:
-            True if content was written
+            True if flush was dispatched
        """
        success = self.flush_manager.flush_from_messages(
            messages=messages,
            user_id=user_id,
            reason=reason,
            max_messages=max_messages,
+            context_summary_callback=context_summary_callback,
        )
        if success:
            self._dirty = True
--- a/agent/memory/service.py
+++ b/agent/memory/service.py
@@ -32,68 +32,80 @@ class MemoryService:
    # ------------------------------------------------------------------
    # list — paginated file metadata
    # ------------------------------------------------------------------
-    def list_files(self, page: int = 1, page_size: int = 20) -> dict:
+    def list_files(self, page: int = 1, page_size: int = 20, category: str = "memory") -> dict:
        """
-        List all memory files with metadata (without content).
+        List memory or dream files with metadata (without content).

-        Returns::
-
-            {
-                "page": 1,
-                "page_size": 20,
-                "total": 15,
-                "list": [
-                    {"filename": "MEMORY.md", "type": "global", "size": 2048, "updated_at": "2026-02-20 10:00:00"},
-                    {"filename": "2026-02-20.md", "type": "daily", "size": 512, "updated_at": "2026-02-20 09:30:00"},
-                    ...
-                ]
-            }
+        Args:
+            category: ``"memory"`` (default) — MEMORY.md + daily files;
+                      ``"dream"``  — dream diary files from memory/dreams/
        """
+        if category == "dream":
+            files = self._list_dream_files()
+        else:
+            files = self._list_memory_files()
+
+        total = len(files)
+        start = (page - 1) * page_size
+        end = start + page_size
+
+        return {
+            "page": page,
+            "page_size": page_size,
+            "total": total,
+            "list": files[start:end],
+        }
+
+    def _list_memory_files(self) -> List[dict]:
+        """MEMORY.md + memory/*.md (newest first)."""
        files: List[dict] = []

-        # 1. Global memory — MEMORY.md in workspace root
        global_path = os.path.join(self.workspace_root, "MEMORY.md")
        if os.path.isfile(global_path):
            files.append(self._file_info(global_path, "MEMORY.md", "global"))

-        # 2. Daily memory files — memory/*.md (sorted newest first)
        if os.path.isdir(self.memory_dir):
            daily_files = []
            for name in os.listdir(self.memory_dir):
                full = os.path.join(self.memory_dir, name)
                if os.path.isfile(full) and name.endswith(".md"):
                    daily_files.append((name, full))
-            # Sort by filename descending (newest date first)
            daily_files.sort(key=lambda x: x[0], reverse=True)
            for name, full in daily_files:
                files.append(self._file_info(full, name, "daily"))

-        total = len(files)
+        return files

-        # Paginate
-        start = (page - 1) * page_size
-        end = start + page_size
-        page_items = files[start:end]
+    def _list_dream_files(self) -> List[dict]:
+        """memory/dreams/*.md (newest first)."""
+        files: List[dict] = []
+        dreams_dir = os.path.join(self.memory_dir, "dreams")

-        return {
-            "page": page,
-            "page_size": page_size,
-            "total": total,
-            "list": page_items,
-        }
+        if os.path.isdir(dreams_dir):
+            entries = []
+            for name in os.listdir(dreams_dir):
+                full = os.path.join(dreams_dir, name)
+                if os.path.isfile(full) and name.endswith(".md"):
+                    entries.append((name, full))
+            entries.sort(key=lambda x: x[0], reverse=True)
+            for name, full in entries:
+                files.append(self._file_info(full, name, "dream"))
+
+        return files

    # ------------------------------------------------------------------
    # content — read a single file
    # ------------------------------------------------------------------
-    def get_content(self, filename: str) -> dict:
+    def get_content(self, filename: str, category: str = "memory") -> dict:
        """
-        Read the full content of a memory file.
+        Read the full content of a memory or dream file.

-        :param filename: File name, e.g. ``MEMORY.md`` or ``2026-02-20.md``
+        :param filename: File name, e.g. ``MEMORY.md``, ``2026-02-20.md``
+        :param category: ``"memory"`` or ``"dream"``
        :return: dict with ``filename`` and ``content``
        :raises FileNotFoundError: if the file does not exist
        """
-        path = self._resolve_path(filename)
+        path = self._resolve_path(filename, category)
        if not os.path.isfile(path):
            raise FileNotFoundError(f"Memory file not found: {filename}")

@@ -113,7 +125,7 @@ class MemoryService:
        Dispatch a memory management action.

        :param action: ``list`` or ``content``
-        :param payload: action-specific payload
+        :param payload: action-specific payload (supports ``category``: ``"memory"`` | ``"dream"``)
        :return: protocol-compatible response dict
        """
        payload = payload or {}
@@ -121,14 +133,16 @@ class MemoryService:
            if action == "list":
                page = payload.get("page", 1)
                page_size = payload.get("page_size", 20)
-                result_payload = self.list_files(page=page, page_size=page_size)
+                category = payload.get("category", "memory")
+                result_payload = self.list_files(page=page, page_size=page_size, category=category)
                return {"action": action, "code": 200, "message": "success", "payload": result_payload}

            elif action == "content":
                filename = payload.get("filename")
                if not filename:
                    return {"action": action, "code": 400, "message": "filename is required", "payload": None}
-                result_payload = self.get_content(filename)
+                category = payload.get("category", "memory")
+                result_payload = self.get_content(filename, category=category)
                return {"action": action, "code": 200, "message": "success", "payload": result_payload}

            else:
@@ -145,18 +159,20 @@ class MemoryService:
    # ------------------------------------------------------------------
    # internal helpers
    # ------------------------------------------------------------------
-    def _resolve_path(self, filename: str) -> str:
+    def _resolve_path(self, filename: str, category: str = "memory") -> str:
        """
        Safely resolve a filename to its absolute path within the allowed directory.

        - ``MEMORY.md`` → ``{workspace_root}/MEMORY.md``
-        - ``2026-02-20.md`` → ``{workspace_root}/memory/2026-02-20.md``
+        - ``2026-02-20.md`` (memory) → ``{workspace_root}/memory/2026-02-20.md``
+        - ``2026-02-20.md`` (dream) → ``{workspace_root}/memory/dreams/2026-02-20.md``

-        Raises ValueError if the resolved path escapes the allowed directory
-        (path traversal protection).
+        Raises ValueError if the resolved path escapes the allowed directory.
        """
        if filename == "MEMORY.md":
            base_dir = self.workspace_root
+        elif category == "dream":
+            base_dir = os.path.join(self.memory_dir, "dreams")
        else:
            base_dir = self.memory_dir

--- a/agent/memory/summarizer.py
+++ b/agent/memory/summarizer.py
@@ -1,12 +1,12 @@
 """
-Memory flush manager
+Memory flush manager with Deep Dream distillation

 Handles memory persistence when conversation context is trimmed or overflows:
- Uses LLM to summarize discarded messages into concise key-information entries
+- Uses LLM to summarize discarded messages into concise daily records
 - Writes to daily memory files (lazy creation)
 - Deduplicates trim flushes to avoid repeated writes
 - Runs summarization asynchronously to avoid blocking normal replies
- Provides daily summary interface for scheduler
+- Deep Dream: periodically distills daily memories → refined MEMORY.md + dream diary
 """

 import threading
@@ -16,29 +16,78 @@ from datetime import datetime
 from common.log import logger


-SUMMARIZE_SYSTEM_PROMPT = """你是一个记忆提取助手。你的任务是从对话记录中提炼出值得长期记住的关键事件和核心信息。
+SUMMARIZE_SYSTEM_PROMPT = """你是一个对话记录助手。请将对话内容归纳为当天的日常记录。

-核心原则：
- 按「事件」维度归纳，而不是按对话轮次逐条记录
- 多轮对话如果围绕同一件事，合并为一条摘要
- 只记录有长期价值的信息，忽略闲聊、问候、无意义的短消息
+## 要求

-输出要求：
-1. 每条一行，用 "- " 开头，格式为：事件/主题 + 关键结论或结果
-2. 值得记录的信息类型：用户提出的需求及最终解决方案、重要的事实信息、用户的偏好或决策、关键技术方案或配置变更
-3. 不值得记录的信息：简单问候、闲聊、无实质内容的短消息、重复的中间过程
-4. 每条摘要应当简明扼要，一句话概括事件的核心内容和结果
-5. 直接输出摘要内容，不要加任何前缀说明
-6. 当对话没有任何记录价值（仅含问候或无意义内容），回复"无"
+按「事件」维度归纳发生的事，不要按对话轮次逐条记录：
+- 每条一行，用 "- " 开头
+- 合并同一件事的多轮对话
+- 只记录有意义的事件，忽略闲聊和问候
+- 保留关键的决策、结论和待办事项

-示例（仅供参考格式）：
- 用户配置了 XX 功能，设置参数为 YY，已生效
- 用户反馈了 XX 问题，原因是 YY，通过 ZZ 方式解决"""
+当对话没有任何记录价值（仅含问候或无意义内容），直接回复"无"。"""

-SUMMARIZE_USER_PROMPT = """请从以下对话记录中，按关键事件维度提炼记忆摘要（合并同一事件的多轮对话，不要逐条列出）：
+SUMMARIZE_USER_PROMPT = """请归纳以下对话的日常记录：

 {conversation}"""

+# ---------------------------------------------------------------------------
+# Deep Dream prompts — distill daily memories → MEMORY.md + dream diary
+# ---------------------------------------------------------------------------
+
+DREAM_SYSTEM_PROMPT = """你是一个记忆整理助手，负责定期整理用户的长期记忆。
+
+你将收到两份材料：
+1. **当前长期记忆** — MEMORY.md 的全部现有内容
+2. **今日日记** — 当天的日常记录
+
+MEMORY.md 会注入每次对话的系统提示词中，因此必须保持精炼，只存放有价值和值得记忆的内容。
+
+**重要：只能基于提供的材料进行整理，严禁编造、推测或添加材料中不存在的信息。**
+
+## 任务
+
+### Part 1: 更新后的长期记忆（[MEMORY]）
+
+在现有记忆基础上进行整理和提炼，输出完整的更新后内容：
+- **合并提炼**：将含义相近的多条合并为一条高密度表述，而非简单罗列
+- **新增萃取**：从今日日记中提取值得永久记住的新信息（偏好、决策、人物、规则、经验）
+- **冲突更新**：当新信息与旧条目矛盾时，以新信息为准，替换旧条目
+- **清理无效**：删除临时性记录、空白条目、格式残留、无意义、重复内容等
+- **删除冗余**：已被更精炼表述涵盖的旧条目应删除，避免信息重复
+- 每条一行，用 "- " 开头，不带日期前缀
+- 目标：控制在 50 条以内，每条尽量一句话概括
+
+### Part 2: 梦境日记（[DREAM]）
+
+用简洁的叙事风格写一篇短日记，记录这次整理的发现，保持格式美观易读：
+- 发现了哪些重复或矛盾
+- 从日记中提取了什么新洞察
+- 做了哪些清理和优化
+- 整体感受和观察
+
+## 输出格式（严格遵守）
+
+```
+[MEMORY]
+- 记忆条目1
+- 记忆条目2
+...
+
+[DREAM]
+梦境日记内容...
+```"""
+
+DREAM_USER_PROMPT = """## 当前长期记忆（MEMORY.md）
+
+{memory_content}
+
+## 近期日记（最近 {days} 天）
+
+{daily_content}"""
+
+

 class MemoryFlushManager:
    """
@@ -65,6 +114,8 @@ class MemoryFlushManager:
        self.last_flush_timestamp: Optional[datetime] = None
        self._trim_flushed_hashes: set = set()  # Content hashes of already-flushed messages
        self._last_flushed_content_hash: str = ""  # Content hash at last flush, for daily dedup
+        self._last_dream_input_hash: str = ""  # Hash of dream input, for dedup
+        self._last_flush_thread: Optional[threading.Thread] = None
    
    def get_today_memory_file(self, user_id: Optional[str] = None, ensure_exists: bool = False) -> Path:
        """Get today's memory file path: memory/YYYY-MM-DD.md"""
@@ -108,21 +159,19 @@ class MemoryFlushManager:
        user_id: Optional[str] = None,
        reason: str = "trim",
        max_messages: int = 0,
+        context_summary_callback: Optional[Callable[[str], None]] = None,
    ) -> bool:
        """
        Asynchronously summarize and flush messages to daily memory.
-        
+
        Deduplication runs synchronously, then LLM summarization + file write
        run in a background thread so the main reply flow is never blocked.
-        
-        Args:
-            messages: Conversation message list (OpenAI/Claude format)
-            user_id: Optional user ID for user-scoped memory
-            reason: Why flush was triggered ("trim" | "overflow" | "daily_summary")
-            max_messages: Max recent messages to summarize (0 = all)
-        
-        Returns:
-            True if flush was dispatched
+
+        If *context_summary_callback* is provided, it is called with the
+        [DAILY] portion of the LLM summary once available. The caller can use
+        this to inject the summary into the live message list for context
+        continuity — one LLM call serves both disk persistence and in-context
+        injection.
        """
        try:
            import hashlib
@@ -137,18 +186,19 @@ class MemoryFlushManager:
                    deduped.append(m)
            if not deduped:
                return False
-            
+
            import copy
            snapshot = copy.deepcopy(deduped)
            thread = threading.Thread(
                target=self._flush_worker,
-                args=(snapshot, user_id, reason, max_messages),
+                args=(snapshot, user_id, reason, max_messages, context_summary_callback),
                daemon=True,
            )
            thread.start()
            logger.info(f"[MemoryFlush] Async flush dispatched (reason={reason}, msgs={len(snapshot)})")
+            self._last_flush_thread = thread
            return True
-            
+
        except Exception as e:
            logger.warning(f"[MemoryFlush] Failed to dispatch flush (reason={reason}): {e}")
            return False
@@ -159,41 +209,69 @@ class MemoryFlushManager:
        user_id: Optional[str],
        reason: str,
        max_messages: int,
+        context_summary_callback: Optional[Callable[[str], None]] = None,
    ):
-        """Background worker: summarize with LLM and write to daily file."""
+        """Background worker: summarize with LLM, write daily memory file."""
        try:
-            summary = self._summarize_messages(messages, max_messages)
-            if not summary or not summary.strip() or summary.strip() == "无":
+            raw_summary = self._summarize_messages(messages, max_messages)
+            if not raw_summary or not raw_summary.strip() or raw_summary.strip() == "无":
                logger.info(f"[MemoryFlush] No valuable content to flush (reason={reason})")
                return
-            
+
+            # Strip legacy [DAILY]/[MEMORY] markers if model still outputs them
+            daily_part = self._clean_summary_output(raw_summary)
+            if not daily_part:
+                return
+
+            # --- Write daily memory ---
            daily_file = ensure_daily_memory_file(self.workspace_dir, user_id)
-            
-            if reason == "overflow":
-                header = f"## Context Overflow Recovery ({datetime.now().strftime('%H:%M')})"
-                note = "The following conversation was trimmed due to context overflow:\n"
-            elif reason == "trim":
-                header = f"## Trimmed Context ({datetime.now().strftime('%H:%M')})"
-                note = ""
-            elif reason == "daily_summary":
-                header = f"## Daily Summary ({datetime.now().strftime('%H:%M')})"
-                note = ""
-            else:
-                header = f"## Session Notes ({datetime.now().strftime('%H:%M')})"
-                note = ""
-            
-            flush_entry = f"\n{header}\n\n{note}{summary}\n"
-            
+
+            headers = {
+                "overflow": f"## Context Overflow Recovery ({datetime.now().strftime('%H:%M')})",
+                "trim": f"## Trimmed Context ({datetime.now().strftime('%H:%M')})",
+                "daily_summary": f"## Daily Summary ({datetime.now().strftime('%H:%M')})",
+            }
+            header = headers.get(reason, f"## Session Notes ({datetime.now().strftime('%H:%M')})")
+
            with open(daily_file, "a", encoding="utf-8") as f:
-                f.write(flush_entry)
-            
+                f.write(f"\n{header}\n\n{daily_part}\n")
+
+            logger.info(f"[MemoryFlush] Wrote daily memory to {daily_file.name} (reason={reason}, chars={len(daily_part)})")
+
+            # --- Inject context summary into live messages (if callback provided) ---
+            if context_summary_callback:
+                try:
+                    context_summary_callback(daily_part)
+                except Exception as e:
+                    logger.warning(f"[MemoryFlush] Context summary callback failed: {e}")
+
            self.last_flush_timestamp = datetime.now()
-            
-            logger.info(f"[MemoryFlush] Wrote to {daily_file.name} (reason={reason}, chars={len(summary)})")
-            
+
        except Exception as e:
            logger.warning(f"[MemoryFlush] Async flush failed (reason={reason}): {e}")
-    
+
+    @staticmethod
+    def _clean_summary_output(raw: str) -> str:
+        """Strip legacy [DAILY]/[MEMORY] markers if present, return clean daily text."""
+        raw = raw.strip()
+        if not raw or raw == "无":
+            return ""
+
+        # Strip [DAILY] marker
+        if "[DAILY]" in raw:
+            start = raw.index("[DAILY]") + len("[DAILY]")
+            end = raw.index("[MEMORY]") if "[MEMORY]" in raw else len(raw)
+            raw = raw[start:end].strip()
+
+        # Remove stray [MEMORY] section entirely
+        if "[MEMORY]" in raw:
+            raw = raw[:raw.index("[MEMORY]")].strip()
+
+        # Remove markdown code fences
+        raw = raw.replace("```", "").strip()
+
+        return raw
+
    def create_daily_summary(
        self,
        messages: List[Dict],
@@ -219,12 +297,187 @@ class MemoryFlushManager:
            reason="daily_summary",
            max_messages=0,
        )
-    
+
+    # ---- Deep Dream (memory distillation) ----
+
+    def deep_dream(self, user_id: Optional[str] = None, lookback_days: int = 1, force: bool = False) -> bool:
+        """
+        Distill recent daily memories into MEMORY.md and generate a dream diary.
+
+        Args:
+            lookback_days: How many days of daily files to read (default 1 for scheduled, 3 for manual)
+            force: Skip input-hash dedup check (used by manual /memory dream trigger)
+        """
+        if not self.llm_model:
+            logger.warning("[DeepDream] No LLM model available, skipping")
+            return False
+
+        logger.info(f"[DeepDream] Starting memory distillation (lookback={lookback_days} days)")
+
+        # Collect materials
+        memory_content = self._read_main_memory(user_id)
+        daily_content, has_content = self._read_recent_dailies(user_id, lookback_days)
+
+        if not has_content:
+            logger.info("[DeepDream] No recent daily records, skipping to preserve existing MEMORY.md")
+            return False
+
+        # Dedup: skip if input materials haven't changed since last dream
+        import hashlib
+        input_hash = hashlib.md5((memory_content + daily_content).encode("utf-8")).hexdigest()
+        if not force and input_hash == self._last_dream_input_hash:
+            logger.debug("[DeepDream] Input unchanged since last dream, skipping")
+            return False
+        self._last_dream_input_hash = input_hash
+
+        logger.info(
+            f"[DeepDream] Materials collected: "
+            f"MEMORY.md={len(memory_content)} chars, "
+            f"daily={len(daily_content)} chars"
+        )
+
+        # Call LLM for distillation
+        import time as _time
+        t0 = _time.monotonic()
+        try:
+            user_msg = DREAM_USER_PROMPT.format(
+                memory_content=memory_content or "(empty)",
+                days=lookback_days,
+                daily_content=daily_content or "(no recent daily records)",
+            )
+            from agent.protocol.models import LLMRequest
+            # Scale max_tokens based on input size to avoid truncating large MEMORY.md
+            input_chars = len(memory_content) + len(daily_content)
+            dream_max_tokens = max(2000, min(input_chars, 8000))
+            request = LLMRequest(
+                messages=[{"role": "user", "content": user_msg}],
+                temperature=0.3,
+                max_tokens=dream_max_tokens,
+                stream=False,
+                system=DREAM_SYSTEM_PROMPT,
+            )
+            response = self.llm_model.call(request)
+            raw = self._extract_response_text(response)
+            elapsed = _time.monotonic() - t0
+            if not raw or not raw.strip():
+                logger.warning(f"[DeepDream] LLM returned empty response ({elapsed:.1f}s)")
+                return False
+            logger.info(f"[DeepDream] LLM distillation completed ({elapsed:.1f}s, {len(raw)} chars)")
+        except Exception as e:
+            elapsed = _time.monotonic() - t0
+            logger.warning(f"[DeepDream] LLM call failed ({elapsed:.1f}s): {e}")
+            return False
+
+        # Parse [MEMORY] and [DREAM] sections
+        new_memory, dream_diary = self._parse_dream_output(raw)
+
+        if not new_memory:
+            logger.warning("[DeepDream] No [MEMORY] section in LLM output, skipping overwrite")
+            return False
+
+        # Overwrite MEMORY.md
+        try:
+            main_file = self.get_main_memory_file(user_id)
+            old_size = len(memory_content)
+            main_file.write_text(new_memory + "\n", encoding="utf-8")
+            logger.info(
+                f"[DeepDream] Updated MEMORY.md "
+                f"({old_size} → {len(new_memory)} chars)"
+            )
+        except Exception as e:
+            logger.warning(f"[DeepDream] Failed to write MEMORY.md: {e}")
+            return False
+
+        # Write dream diary
+        if dream_diary:
+            try:
+                self._write_dream_diary(dream_diary, user_id)
+            except Exception as e:
+                logger.warning(f"[DeepDream] Failed to write dream diary: {e}")
+
+        logger.info("[DeepDream] ✅ Deep Dream completed successfully")
+        return True
+
+    def _read_main_memory(self, user_id: Optional[str] = None) -> str:
+        """Read current MEMORY.md content."""
+        main_file = self.get_main_memory_file(user_id)
+        if main_file.exists():
+            return main_file.read_text(encoding="utf-8").strip()
+        return ""
+
+    def _read_recent_dailies(
+        self, user_id: Optional[str] = None, lookback_days: int = 1
+    ) -> tuple:
+        """
+        Read recent daily memory files.
+
+        Returns:
+            (combined_text, has_content) tuple
+        """
+        from datetime import timedelta
+
+        parts = []
+        has_content = False
+        today = datetime.now().date()
+
+        for offset in range(lookback_days):
+            day = today - timedelta(days=offset)
+            date_str = day.strftime("%Y-%m-%d")
+            if user_id:
+                daily_file = self.memory_dir / "users" / user_id / f"{date_str}.md"
+            else:
+                daily_file = self.memory_dir / f"{date_str}.md"
+
+            if daily_file.exists():
+                content = daily_file.read_text(encoding="utf-8").strip()
+                if content:
+                    parts.append(f"### {date_str}\n\n{content}")
+                    has_content = True
+            else:
+                parts.append(f"### {date_str}\n\n(no records)")
+
+        return "\n\n".join(parts), has_content
+
+    @staticmethod
+    def _parse_dream_output(raw: str) -> tuple:
+        """Parse LLM output into (new_memory, dream_diary)."""
+        raw = raw.strip().replace("```", "")
+        new_memory = ""
+        dream_diary = ""
+
+        if "[MEMORY]" in raw:
+            start = raw.index("[MEMORY]") + len("[MEMORY]")
+            end = raw.index("[DREAM]") if "[DREAM]" in raw else len(raw)
+            new_memory = raw[start:end].strip()
+
+        if "[DREAM]" in raw:
+            start = raw.index("[DREAM]") + len("[DREAM]")
+            dream_diary = raw[start:].strip()
+
+        return new_memory, dream_diary
+
+    def _write_dream_diary(self, content: str, user_id: Optional[str] = None):
+        """Write dream diary to memory/dreams/YYYY-MM-DD.md."""
+        dreams_dir = self.memory_dir / "dreams"
+        if user_id:
+            dreams_dir = self.memory_dir / "users" / user_id / "dreams"
+        dreams_dir.mkdir(parents=True, exist_ok=True)
+
+        today = datetime.now().strftime("%Y-%m-%d")
+        diary_file = dreams_dir / f"{today}.md"
+        diary_file.write_text(
+            f"# Dream Diary: {today}\n\n{content}\n",
+            encoding="utf-8",
+        )
+        logger.info(f"[DeepDream] Wrote dream diary to {diary_file}")
+
    # ---- Internal helpers ----
    
    def _summarize_messages(self, messages: List[Dict], max_messages: int = 0) -> str:
        """
-        Summarize conversation messages using LLM, with rule-based fallback.
+        Summarize conversation messages using LLM.
+        Returns empty string if LLM deems content not worth recording.
+        Rule-based fallback only used when LLM call raises an exception.
        """
        conversation_text = self._format_conversation_for_summary(messages, max_messages)
        if not conversation_text.strip():
@@ -235,13 +488,14 @@ class MemoryFlushManager:
                summary = self._call_llm_for_summary(conversation_text)
                if summary and summary.strip() and summary.strip() != "无":
                    return summary.strip()
-                logger.info(f"[MemoryFlush] LLM returned empty or '无', using fallback")
+                logger.info("[MemoryFlush] LLM returned empty or '无', skipping write")
+                return ""
            except Exception as e:
                logger.warning(f"[MemoryFlush] LLM summarization failed, using fallback: {e}")
+                return self._extract_summary_fallback(messages, max_messages)
        else:
            logger.info("[MemoryFlush] No LLM model available, using rule-based fallback")
-        
-        return self._extract_summary_fallback(messages, max_messages)
+            return self._extract_summary_fallback(messages, max_messages)

    def _format_conversation_for_summary(self, messages: List[Dict], max_messages: int = 0) -> str:
        """Format messages into readable conversation text for LLM summarization."""
@@ -259,6 +513,52 @@ class MemoryFlushManager:
                lines.append(f"助手: {text[:500]}")
        return "\n".join(lines)

+    @staticmethod
+    def _extract_response_text(response) -> str:
+        """
+        Extract text from LLM response regardless of format.
+
+        Handles:
+        - Generator (MiniMax _handle_sync_response yields Claude-format dicts)
+        - Claude format: {"role":"assistant","content":[{"type":"text","text":"..."}]}
+        - OpenAI format: {"choices":[{"message":{"content":"..."}}]}
+        - OpenAI SDK response object with .choices attribute
+        """
+        import types
+
+        # Unwrap generator — consume first yielded item
+        if isinstance(response, types.GeneratorType):
+            try:
+                response = next(response)
+            except StopIteration:
+                return ""
+
+        if not response:
+            return ""
+
+        if isinstance(response, dict):
+            # Check for error
+            if response.get("error"):
+                raise RuntimeError(response.get("message", "LLM call failed"))
+
+            # Claude format: content is a list of blocks
+            content = response.get("content")
+            if isinstance(content, list):
+                for block in content:
+                    if isinstance(block, dict) and block.get("type") == "text":
+                        return block.get("text", "")
+
+            # OpenAI format
+            choices = response.get("choices", [])
+            if choices:
+                return choices[0].get("message", {}).get("content", "")
+
+        # OpenAI SDK response object
+        if hasattr(response, "choices") and response.choices:
+            return response.choices[0].message.content or ""
+
+        return ""
+
    def _call_llm_for_summary(self, conversation_text: str) -> str:
        """Call LLM to generate a concise summary of the conversation."""
        from agent.protocol.models import LLMRequest
@@ -272,27 +572,31 @@ class MemoryFlushManager:
        )
        
        response = self.llm_model.call(request)
-        
-        if isinstance(response, dict):
-            if response.get("error"):
-                raise RuntimeError(response.get("message", "LLM call failed"))
-            # OpenAI format
-            choices = response.get("choices", [])
-            if choices:
-                return choices[0].get("message", {}).get("content", "")
-        
-        # Handle response object with attribute access (e.g. OpenAI SDK response)
-        if hasattr(response, "choices") and response.choices:
-            return response.choices[0].message.content or ""
-        
-        return ""
+        return self._extract_response_text(response)
+
+    @staticmethod
+    def _extract_first_meaningful_line(text: str, max_len: int = 120) -> str:
+        """Extract the first meaningful line from assistant reply, skipping markdown noise."""
+        import re
+        for line in text.split("\n"):
+            line = line.strip()
+            if not line:
+                continue
+            # Skip markdown headings, horizontal rules, code fences, pure emoji/symbols
+            if re.match(r'^(#{1,4}\s|```|---|\*\*\*|[-*]\s*$|[^\w\u4e00-\u9fff]{1,5}$)', line):
+                continue
+            # Strip leading markdown bold/emoji decorations
+            cleaned = re.sub(r'^[\*#>\-\s]+', '', line).strip()
+            cleaned = re.sub(r'^[\U0001f300-\U0001f9ff\u2600-\u27bf\s]+', '', cleaned).strip()
+            if len(cleaned) >= 5:
+                return cleaned[:max_len]
+        return text.split("\n")[0].strip()[:max_len]

    @staticmethod
    def _extract_summary_fallback(messages: List[Dict], max_messages: int = 0) -> str:
        """
-        Rule-based fallback when LLM is unavailable.
-        Groups consecutive user+assistant messages into events instead of
-        listing each message individually.
+        Rule-based summary of discarded messages.
+        Format: "用户问了X; 助手回答了Y" per event, compact and readable.
        """
        msgs = messages if max_messages == 0 else messages[-max_messages * 2:]

@@ -306,19 +610,19 @@ class MemoryFlushManager:
            text = text.strip()

            if role == "user":
-                if len(text) <= 5:
+                if len(text) <= 3:
                    continue
-                current_user_text = text[:150]
+                current_user_text = text[:120]
            elif role == "assistant" and current_user_text:
-                first_line = text.split("\n")[0].strip()
-                if len(first_line) > 10:
-                    events.append(f"- {current_user_text} → {first_line[:150]}")
+                reply_summary = MemoryFlushManager._extract_first_meaningful_line(text)
+                if reply_summary:
+                    events.append(f"- 用户: {current_user_text} → 回复: {reply_summary}")
                else:
-                    events.append(f"- {current_user_text}")
+                    events.append(f"- 用户: {current_user_text}")
                current_user_text = ""

        if current_user_text:
-            events.append(f"- {current_user_text}")
+            events.append(f"- 用户: {current_user_text}")

        return "\n".join(events[:10])
    
--- a/agent/prompt/builder.py
+++ b/agent/prompt/builder.py
@@ -10,6 +10,7 @@ from typing import List, Dict, Optional, Any
 from dataclasses import dataclass

 from common.log import logger
+from config import conf


@dataclass
@@ -92,10 +93,11 @@ def build_agent_system_prompt(
    顺序说明（按重要性和逻辑关系排列）:
    1. 工具系统 - 核心能力，最先介绍
    2. 技能系统 - 紧跟工具，因为技能需要用 read 工具读取
-    3. 记忆系统 - 独立的记忆能力
+    3. 记忆系统 - 记忆检索与写入引导
+    3.5 知识系统 - 结构化知识库（knowledge/index.md 注入）
    4. 工作空间 - 工作环境说明
    5. 用户身份 - 用户信息（可选）
-    6. 项目上下文 - AGENT.md, USER.md, RULE.md, BOOTSTRAP.md（定义人格、身份、规则、初始化引导）
+    6. 项目上下文 - AGENT.md, USER.md, RULE.md, MEMORY.md, BOOTSTRAP.md
    7. 运行时信息 - 元信息（时间、模型等）
    
    Args:
@@ -126,6 +128,10 @@ def build_agent_system_prompt(
    # 3. 记忆系统（独立的记忆能力）
    if memory_manager:
        sections.extend(_build_memory_section(memory_manager, tools, language))
+
+    # 3.5 知识系统（结构化知识库）
+    if conf().get("knowledge", True):
+        sections.extend(_build_knowledge_section(workspace_dir, language))
    
    # 4. 工作空间（工作环境说明）
    sections.extend(_build_workspace_section(workspace_dir, language))
@@ -268,55 +274,105 @@ def _build_memory_section(memory_manager: Any, tools: Optional[List[Any]], langu
    """构建记忆系统section"""
    if not memory_manager:
        return []
-    
-    # 检查是否有memory工具
+
    has_memory_tools = False
    if tools:
        tool_names = [tool.name if hasattr(tool, 'name') else str(tool) for tool in tools]
        has_memory_tools = any(name in ['memory_search', 'memory_get'] for name in tool_names)
-    
+
    if not has_memory_tools:
        return []
-    
+
    from datetime import datetime
    today_file = datetime.now().strftime("%Y-%m-%d") + ".md"
-    
+
    lines = [
        "## 🧠 记忆系统",
        "",
-        "### 检索记忆",
+        "### Memory Recall（mandatory）",
        "",
-        "在回答关于以前的工作、决定、日期、人物、偏好或待办事项的任何问题之前：",
+        "当用户询问过往事件、引用之前的决定、提到人物关系、偏好、待办、或你对某事不确定时，**必须先检索记忆再回答**。",
+        "如果 MEMORY.md 中已有相关信息则无需重复检索。完整内容和每日记忆需要通过工具检索。",
        "",
-        "1. 不确定记忆文件位置 → 先用 `memory_search` 通过关键词和语义检索相关内容",
-        "2. 已知文件位置 → 直接用 `memory_get` 读取相应的行 (例如：MEMORY.md, memory/YYYY-MM-DD.md)",
-        "3. search 无结果 → 尝试用 `memory_get` 读取MEMORY.md及最近两天记忆文件",
+        "1. 不确定位置 → `memory_search` 关键词/语义检索",
+        "2. 已知位置 → `memory_get` 直接读取对应行",
+        "3. search 无结果 → `memory_get` 读最近两天记忆",
        "",
        "**记忆文件结构**:",
-        f"- `MEMORY.md`: 长期记忆（核心信息、偏好、决策等）",
+        "- `MEMORY.md`: 长期记忆索引（已自动加载到上下文，核心信息、偏好、决策等）",
        f"- `memory/YYYY-MM-DD.md`: 每日记忆，今天是 `memory/{today_file}`",
+        "- `knowledge/`: 结构化知识库（见下方知识系统）",
        "",
        "### 写入记忆",
        "",
-        "**主动存储**：遇到以下情况时，应主动将信息写入记忆文件（无需告知用户）：",
+        "遇到以下情况时，**主动**将信息写入记忆文件（无需告知用户）：",
        "",
-        "- 用户明确要求你记住某些信息",
+        "- 用户要求记住某些信息，或使用了「记住」「以后」「总是」「不要」「偏好」等表达",
        "- 用户分享了重要的个人偏好、习惯、决策",
        "- 对话中产生了重要的结论、方案、约定",
        "- 完成了复杂任务，值得记录关键步骤和结果",
-        "- 发现了用户经常遇到的问题或解决方案",
        "",
        "**存储规则**:",
-        f"- 长期有效的核心信息 → `MEMORY.md`（文件保持精简，< 2000 tokens）",
-        f"- 当天的事件、进展、笔记 → `memory/{today_file}`",
-        "- 追加内容 → `edit` 工具，oldText 留空",
-        "- 修改内容 → `edit` 工具，oldText 填写要替换的文本",
-        "- **禁止写入敏感信息**：API密钥、令牌等敏感信息严禁写入记忆文件",
+        f"- 长期核心信息 → `MEMORY.md`",
+        f"- 当天事件/进展 → `memory/{today_file}`",
+        "- 结构化知识 → `knowledge/`（见知识系统）",
+        "- 追加 → `edit` 工具，oldText 留空",
+        "- 修改 → `edit` 工具，oldText 填写要替换的文本",
+        "- **禁止写入敏感信息**（API密钥、令牌等）",
        "",
        "**使用原则**: 自然使用记忆，就像你本来就知道；不用刻意提起，除非用户问起。",
        "",
    ]
-    
+
+    return lines
+
+
+def _build_knowledge_section(workspace_dir: str, language: str) -> List[str]:
+    """Build knowledge wiki section. Injects knowledge/index.md when present."""
+    index_path = os.path.join(workspace_dir, "knowledge", "index.md")
+    if not os.path.exists(index_path):
+        return []
+
+    try:
+        with open(index_path, 'r', encoding='utf-8') as f:
+            index_content = f.read().strip()
+    except Exception:
+        return []
+
+    lines = [
+        "## 📚 知识系统",
+        "",
+        "你拥有一个持续积累的个人知识库 `knowledge/`，这是你的长期结构化知识存储。",
+        "",
+        "### 自动写入规则（mandatory）",
+        "",
+        "以下场景**必须**在回复的同时写入知识库，**直接写入，不要询问用户是否需要**：",
+        "",
+        "1. **用户分享了文章/链接/文档** → 阅读理解后，在同一轮回复中将要点写入 `knowledge/sources/<slug>.md`",
+        "2. **深度讨论产生了结论/方案** → 整理为 `knowledge/analysis/<slug>.md`",
+        "3. **对话涉及重要实体**（人物/公司/项目）→ 创建或更新 `knowledge/entities/<name>.md`",
+        "4. **讨论了技术概念/方法论** → 整理为 `knowledge/concepts/<topic>.md`",
+        "",
+        "每次写入知识页面后，**必须同步更新** `knowledge/index.md` 添加一行索引。",
+        "详细的页面格式和操作规范，请读取技能 `knowledge-wiki` 的 SKILL.md。",
+        "",
+        "⚠️ 不要问「要不要存到知识库」——符合上述场景就直接写入，这是你的本能行为。",
+        "",
+    ]
+
+    if index_content:
+        lines.extend([
+            "### 当前知识索引",
+            "",
+            index_content,
+            "",
+        ])
+
+    lines.extend([
+        "**查询方式**：用 `read` 读取知识页面，或用 `memory_search` 检索（知识已纳入向量索引）。",
+        "",
+    ])
+
    return lines


@@ -375,11 +431,12 @@ def _build_workspace_section(workspace_dir: str, language: str) -> List[str]:
        "",
        "**重要说明 - 文件已自动加载**:",
        "",
-        "以下文件在会话启动时**已经自动加载**到系统提示词的「项目上下文」section 中，你**无需再用 read 工具读取它们**：",
+        "以下文件在会话启动时**已经自动加载**到系统提示词中，你**无需再用 read 工具读取**：",
        "",
        "- ✅ `AGENT.md`: 已加载 - 你的人格和灵魂设定，请严格遵循。当你的名字、性格或交流风格发生变化时，主动用 `edit` 更新此文件",
        "- ✅ `USER.md`: 已加载 - 用户的身份信息。当用户修改称呼、姓名等身份信息时，用 `edit` 更新此文件",
        "- ✅ `RULE.md`: 已加载 - 工作空间使用指南和规则，请严格遵循",
+        "- ✅ `MEMORY.md`: 已加载 - 长期记忆索引",
        "",
        "**💬 交流规范**:",
        "",
--- a/agent/prompt/workspace.py
+++ b/agent/prompt/workspace.py
@@ -67,6 +67,12 @@ def ensure_workspace(workspace_dir: str, create_templates: bool = True) -> Works
    # 创建websites子目录 (for web pages / sites generated by agent)
    websites_dir = os.path.join(workspace_dir, "websites")
    os.makedirs(websites_dir, exist_ok=True)
+
+    from config import conf
+    knowledge_enabled = conf().get("knowledge", True)
+    if knowledge_enabled:
+        knowledge_dir = os.path.join(workspace_dir, "knowledge")
+        os.makedirs(knowledge_dir, exist_ok=True)
    
    # 如果需要，创建模板文件
    if create_templates:
@@ -74,6 +80,15 @@ def ensure_workspace(workspace_dir: str, create_templates: bool = True) -> Works
        _create_template_if_missing(user_path, _get_user_template())
        _create_template_if_missing(rule_path, _get_rule_template())
        _create_template_if_missing(memory_path, _get_memory_template())
+        if knowledge_enabled:
+            _create_template_if_missing(
+                os.path.join(knowledge_dir, "index.md"),
+                _get_knowledge_index_template()
+            )
+            _create_template_if_missing(
+                os.path.join(knowledge_dir, "log.md"),
+                _get_knowledge_log_template()
+            )
        
        # Only create BOOTSTRAP.md for brand new workspaces;
        # agent deletes it after completing onboarding
@@ -109,6 +124,7 @@ def load_context_files(workspace_dir: str, files_to_load: Optional[List[str]] =
            DEFAULT_AGENT_FILENAME,
            DEFAULT_USER_FILENAME,
            DEFAULT_RULE_FILENAME,
+            DEFAULT_MEMORY_FILENAME,     # Long-term memory (frozen snapshot)
            DEFAULT_BOOTSTRAP_FILENAME,  # Only exists when onboarding is incomplete
        ]
    
@@ -138,6 +154,10 @@ def load_context_files(workspace_dir: str, files_to_load: Optional[List[str]] =
            # 跳过空文件或只包含模板占位符的文件
            if not content or _is_template_placeholder(content):
                continue
+
+            # Truncate MEMORY.md to protect context window (frozen snapshot)
+            if filename == DEFAULT_MEMORY_FILENAME:
+                content = _truncate_memory_content(content)
            
            context_files.append(ContextFile(
                path=filename,
@@ -163,6 +183,36 @@ def _create_template_if_missing(filepath: str, template_content: str):
            logger.error(f"[Workspace] Failed to create template {filepath}: {e}")


+_MEMORY_MAX_LINES = 200
+_MEMORY_MAX_BYTES = 25000
+
+
+def _truncate_memory_content(content: str) -> str:
+    """Truncate MEMORY.md to keep system prompt manageable.
+
+    Takes the **last** N lines (newest entries are appended at the bottom),
+    subject to 200 lines / 25 KB limits (whichever is hit first).
+    Prepends a hint when truncated so the model knows older content exists.
+    """
+    lines = content.split('\n')
+    truncated = False
+
+    if len(lines) > _MEMORY_MAX_LINES:
+        lines = lines[-_MEMORY_MAX_LINES:]
+        truncated = True
+
+    result = '\n'.join(lines)
+    if len(result.encode('utf-8')) > _MEMORY_MAX_BYTES:
+        while len(result.encode('utf-8')) > _MEMORY_MAX_BYTES and lines:
+            lines.pop(0)
+            truncated = True
+        result = '\n'.join(lines)
+
+    if truncated:
+        result = "...(older entries truncated, use `memory_search` or `memory_get` for full content)\n\n" + result
+    return result
+
+
 def _is_template_placeholder(content: str) -> bool:
    """检查内容是否为模板占位符"""
    # 常见的占位符模式
@@ -287,39 +337,88 @@ def _get_rule_template() -> str:

 这个文件夹是你的家。好好对待它。

+## 工作空间目录结构
+
+```
+~/cow/
+├── AGENT.md          # 你的身份和灵魂设定
+├── USER.md           # 用户基本信息（静态）
+├── RULE.md           # 工作空间规则（本文件）
+├── MEMORY.md         # 长期记忆索引（会话启动时自动加载）
+│
+├── memory/           # 每日对话记忆
+│   └── YYYY-MM-DD.md # 当天事件、进展、笔记
+│
+├── knowledge/        # 结构化知识库（持续积累的知识）
+│   ├── index.md      # 知识目录索引（必须维护）
+│   ├── log.md        # 知识操作日志
+│   └── <子目录>/     # 按需创建，参考 index.md 已有分类
+│
+├── skills/           # 技能
+├── websites/         # 网页产物
+└── tmp/              # 系统临时文件（自动管理，勿手动存放重要文件）
+```
+
 ## 记忆系统

 你每次会话都是全新的，记忆文件让你保持连续性：

-### 📝 每日记忆：`memory/YYYY-MM-DD.md`
- 原始的对话日志
- 记录当天发生的事情
- 如果 `memory/` 目录不存在，创建它
-
 ### 🧠 长期记忆：`MEMORY.md`
- 你精选的记忆，就像人类的长期记忆
- **仅在主会话中加载**（与用户的直接聊天）
- **不要在共享上下文中加载**（群聊、与其他人的会话）
- 这是为了**安全** - 包含不应泄露给陌生人的个人上下文
- 记录重要事件、想法、决定、观点、经验教训
- 这是你精选的记忆 - 精华，而不是原始日志
- 用 `edit` 工具追加新的记忆内容
+- 你精选的记忆索引，每次会话启动时**自动加载**到上下文中
+- 记录核心事实、偏好、决策、重要人物、教训
+- 保持精简（< 200 行），是精华索引而非原始日志
+- 用 `edit` 工具追加或修改
+
+### 📝 每日记忆：`memory/YYYY-MM-DD.md`
+- 当天的事件、进展、笔记
+- 原始对话日志的沉淀

 ### 📝 写下来 - 不要"记在心里"！
- **记忆是有限的** - 如果你想记住某事，写入文件
+- **记忆是有限的** - 想记住的事就写入文件
 - "记在心里"不会在会话重启后保留，文件才会
 - 当有人说"记住这个" → 更新 `MEMORY.md` 或 `memory/YYYY-MM-DD.md`
 - 当你学到教训 → 更新 RULE.md 或相关技能
- 当你犯错 → 记录下来，这样未来的你不会重复，**文字 > 大脑** 📝
+- 当你犯错 → 记录下来，**文字 > 大脑** 📝

 ### 存储规则

 当用户分享信息时，根据类型选择存储位置：

-1. **你的身份设定 → AGENT.md**（你的名字、角色、性格、交流风格——用户修改时必须用 `edit` 更新）
-2. **用户静态身份 → USER.md**（姓名、称呼、职业、时区、联系方式、生日——用户修改时必须用 `edit` 更新）
-3. **动态记忆 → MEMORY.md**（爱好、偏好、决策、目标、项目、教训、待办事项）
+1. **你的身份设定 → AGENT.md**（名字、角色、性格、风格）
+2. **用户静态身份 → USER.md**（姓名、称呼、职业、联系方式、生日）
+3. **动态记忆 → MEMORY.md**（偏好、决策、目标、教训、待办）
 4. **当天对话 → memory/YYYY-MM-DD.md**（今天聊的内容）
+5. **结构化知识 → knowledge/**（见下方知识系统）
+
+## 知识系统
+
+知识库 `knowledge/` 是你持续积累的结构化知识。与记忆不同，知识是经过整理和编译的，有明确的主题和交叉引用。
+
+### 自动写入（不要询问，直接写入）
+
+当对话中产生了有沉淀价值的知识——无论是用户分享的资料、讨论的结论、学到的概念、还是重要的决策——你**必须**在回复的同时主动写入知识库，**无需问用户"要不要存到知识库"**。
+
+**关键原则**：学完就记是你的本能，不要征求确认。回复中可以顺带告知"已存入知识库"。
+
+### 目录组织
+
+子目录结构**不是固定的**，由你根据实际内容自主决定：
+- **首次写入时**：先读 `knowledge/index.md`，如果已有分类则延续；如果为空，根据内容选择合适的目录名
+- **默认建议**：按信息类型组织（例如sources/、concepts/、entities/、analysis/），如果用户有明确的分类偏好（例如按领域 work/、life/、tech/ 等），则按用户要求调整
+- **保持一致性**：同一用户的知识库应保持统一的组织风格
+
+### 交叉引用
+
+知识的核心价值在于**关联**。每个页面都应通过 markdown 链接引用相关页面，构建知识网络：
+- 提到已有页面的概念时，添加 `[概念名](../category/page.md)` 链接
+- 新建页面时，检查是否有已有页面应该反向链接到新页面
+- **只链接已存在的页面**——不要引用尚未创建的页面。如果某个概念值得单独建页，先创建该页面再添加链接
+
+### 索引维护
+
+每次创建或更新知识页面后，**必须同步更新** `knowledge/index.md`。
+索引格式：每行一个 `[标题](路径) — 一句话摘要`，按分类分组，不要用表格。
+详细操作规范见技能 `knowledge-wiki`。

 ## 安全

@@ -381,4 +480,12 @@ _你刚刚启动，这是你的第一次对话。_ ✨
 """


+def _get_knowledge_index_template() -> str:
+    """Knowledge wiki index template — empty file, agent fills it."""
+    return ""
+
+
+def _get_knowledge_log_template() -> str:
+    """Knowledge wiki operation log template — empty file, agent fills it."""
+    return ""

--- a/agent/protocol/agent_stream.py
+++ b/agent/protocol/agent_stream.py
@@ -78,6 +78,11 @@ class AgentStreamExecutor:
            except Exception as e:
                logger.error(f"Event callback error: {e}")
    
+    def _is_thinking_enabled(self) -> bool:
+        from config import conf
+        channel_type = getattr(self.model, 'channel_type', '') or ''
+        return conf().get("enable_thinking", True) and channel_type == 'web'
+
    def _filter_think_tags(self, text: str) -> str:
        """
        Remove <think> and </think> tags but keep the content inside.
@@ -178,7 +183,10 @@ class AgentStreamExecutor:
            Final response text
        """
        # Log user message with model info
-        logger.info(f"🤖 {self.model.model} | 👤 {user_message}")
+        
+        thinking_enabled = self._is_thinking_enabled()
+        thinking_label = "💭 thinking" if thinking_enabled else "⚡ fast"
+        logger.info(f"🤖 {self.model.model} | {thinking_label} | 👤 {user_message}")        
        
        # Add user message (Claude format - use content blocks for consistency)
        self.messages.append({
@@ -527,6 +535,7 @@ class AgentStreamExecutor:

        # Streaming response
        full_content = ""
+        full_reasoning = ""
        tool_calls_buffer = {}  # {index: {id, name, arguments}}
        gemini_raw_parts = None  # Preserve Gemini thoughtSignature for round-trip
        stop_reason = None  # Track why the stream stopped
@@ -584,10 +593,11 @@ class AgentStreamExecutor:
                    if finish_reason:
                        stop_reason = finish_reason

-                    # Skip reasoning_content (internal thinking from models like GLM-5)
                    reasoning_delta = delta.get("reasoning_content") or ""
-                    # if reasoning_delta:
-                    #     logger.debug(f"🧠 [thinking] {reasoning_delta[:100]}...")
+                    if reasoning_delta:
+                        full_reasoning += reasoning_delta
+                        if self._is_thinking_enabled():
+                            self._emit_event("reasoning_update", {"delta": reasoning_delta})

                    # Handle text content
                    content_delta = delta.get("content") or ""
@@ -788,7 +798,12 @@ class AgentStreamExecutor:
        # Add assistant message to history (Claude format uses content blocks)
        assistant_msg = {"role": "assistant", "content": []}

-        # Add text content block if present
+        if full_reasoning:
+            assistant_msg["content"].append({
+                "type": "thinking",
+                "thinking": full_reasoning
+            })
+
        if full_content:
            assistant_msg["content"].append({
                "type": "text",
@@ -1192,6 +1207,56 @@ class AgentStreamExecutor:
        logger.warning("🔧 Aggressive trim: nothing to trim, will clear history")
        return False

+    def _build_context_summary_callback(self, discarded_turns: list, kept_turns: list):
+        """
+        Build a callback that injects an LLM summary into the first user
+        message of *kept_turns*. Returns None if no valid injection target.
+
+        The callback is passed to flush_from_messages so that the same LLM
+        call that writes daily memory also provides the in-context summary.
+        """
+        if not kept_turns:
+            return None
+
+        # Find the first user text block in kept_turns as injection target
+        target_block = None
+        for turn in kept_turns:
+            for msg in turn["messages"]:
+                if msg.get("role") == "user":
+                    content = msg.get("content", [])
+                    if isinstance(content, list):
+                        for block in content:
+                            if isinstance(block, dict) and block.get("type") == "text":
+                                target_block = block
+                                break
+                    if target_block:
+                        break
+            if target_block:
+                break
+
+        if not target_block:
+            return None
+
+        turn_count = len(discarded_turns)
+        original_text = target_block["text"]
+
+        def _on_summary_ready(summary: str):
+            if not summary or not summary.strip():
+                return
+            target_block["text"] = (
+                f"[System: Previous conversation summary — "
+                f"{turn_count} turns were compacted]\n\n"
+                f"{summary.strip()}\n\n"
+                f"The recent conversation continues below.\n\n---\n\n"
+                f"{original_text}"
+            )
+            logger.info(
+                f"📝 Context summary injected "
+                f"({len(summary)} chars, {turn_count} turns)"
+            )
+
+        return _on_summary_ready
+
    def _trim_messages(self):
        """
        智能清理消息历史，保持对话完整性
@@ -1218,25 +1283,28 @@ class AgentStreamExecutor:
            removed_count = len(turns) // 2
            keep_count = len(turns) - removed_count
            
-            # Flush discarded turns to daily memory
-            if self.agent.memory_manager:
-                discarded_messages = []
-                for turn in turns[:removed_count]:
-                    discarded_messages.extend(turn["messages"])
-                if discarded_messages:
-                    user_id = getattr(self.agent, '_current_user_id', None)
-                    self.agent.memory_manager.flush_memory(
-                        messages=discarded_messages, user_id=user_id,
-                        reason="trim", max_messages=0
-                    )
-            
+            discarded_turns = turns[:removed_count]
            turns = turns[-keep_count:]
-            
+
            logger.info(
                f"💾 上下文轮次超限: {keep_count + removed_count} > {self.max_context_turns}，"
                f"裁剪至 {keep_count} 轮（移除 {removed_count} 轮）"
            )

+            # Flush to daily memory + inject context summary (single async LLM call)
+            if self.agent.memory_manager:
+                discarded_messages = []
+                for turn in discarded_turns:
+                    discarded_messages.extend(turn["messages"])
+                if discarded_messages:
+                    user_id = getattr(self.agent, '_current_user_id', None)
+                    cb = self._build_context_summary_callback(discarded_turns, turns)
+                    self.agent.memory_manager.flush_memory(
+                        messages=discarded_messages, user_id=user_id,
+                        reason="trim", max_messages=0,
+                        context_summary_callback=cb,
+                    )
+
        # Step 3: Token 限制 - 保留完整轮次
        # Get context window from agent (based on model)
        context_window = self.agent._get_model_context_window()
@@ -1312,6 +1380,7 @@ class AgentStreamExecutor:
        # --- Many turns (>=5): discard the older half, keep the newer half ---
        removed_count = len(turns) // 2
        keep_count = len(turns) - removed_count
+        discarded_turns = turns[:removed_count]
        kept_turns = turns[-keep_count:]
        kept_tokens = sum(self._estimate_turn_tokens(t) for t in kept_turns)

@@ -1322,13 +1391,15 @@ class AgentStreamExecutor:

        if self.agent.memory_manager:
            discarded_messages = []
-            for turn in turns[:removed_count]:
+            for turn in discarded_turns:
                discarded_messages.extend(turn["messages"])
            if discarded_messages:
                user_id = getattr(self.agent, '_current_user_id', None)
+                cb = self._build_context_summary_callback(discarded_turns, kept_turns)
                self.agent.memory_manager.flush_memory(
                    messages=discarded_messages, user_id=user_id,
-                    reason="trim", max_messages=0
+                    reason="trim", max_messages=0,
+                    context_summary_callback=cb,
                )

        new_messages = []
--- a/agent/skills/manager.py
+++ b/agent/skills/manager.py
@@ -210,6 +210,10 @@ class SkillManager:
        if not include_disabled:
            entries = [e for e in entries if self.is_skill_enabled(e.skill.name)]

+        from config import conf
+        if not conf().get("knowledge", True):
+            entries = [e for e in entries if e.skill.name != "knowledge-wiki"]
+
        return entries

    def filter_unavailable_skills(
--- a/agent/tools/memory/memory_get.py
+++ b/agent/tools/memory/memory_get.py
@@ -44,6 +44,19 @@ class MemoryGetTool(BaseTool):
        """
        super().__init__()
        self.memory_manager = memory_manager
+
+        from config import conf
+        if conf().get("knowledge", True):
+            self.description = (
+                "Read specific content from memory or knowledge files. "
+                "Use this to get full context from a memory file, knowledge page, or specific line range."
+            )
+            self.params = {**self.params}
+            self.params["properties"] = {**self.params["properties"]}
+            self.params["properties"]["path"] = {
+                "type": "string",
+                "description": "Relative path to the memory or knowledge file (e.g. 'MEMORY.md', 'memory/2026-01-01.md', 'knowledge/concepts/moe.md')"
+            }
    
    def execute(self, args: dict):
        """
@@ -68,11 +81,15 @@ class MemoryGetTool(BaseTool):
            workspace_dir = self.memory_manager.config.get_workspace()
            
            # Auto-prepend memory/ if not present and not absolute path
-            # Exception: MEMORY.md is in the root directory
-            if not path.startswith('memory/') and not path.startswith('/') and path != 'MEMORY.md':
+            # Exceptions: MEMORY.md in root, knowledge/ files at workspace root
+            if not path.startswith('memory/') and not path.startswith('knowledge/') and not path.startswith('/') and path != 'MEMORY.md':
                path = f'memory/{path}'
            
-            file_path = workspace_dir / path
+            file_path = (workspace_dir / path).resolve()
+            workspace_resolved = workspace_dir.resolve()
+            
+            if not str(file_path).startswith(str(workspace_resolved) + '/') and file_path != workspace_resolved:
+                return ToolResult.fail(f"Error: Access denied: path outside workspace")
            
            if not file_path.exists():
                return ToolResult.fail(f"Error: File not found: {path}")
--- a/agent/tools/memory/memory_search.py
+++ b/agent/tools/memory/memory_search.py
@@ -48,6 +48,13 @@ class MemorySearchTool(BaseTool):
        super().__init__()
        self.memory_manager = memory_manager
        self.user_id = user_id
+
+        from config import conf
+        if conf().get("knowledge", True):
+            self.description = (
+                "Search agent's long-term memory and knowledge base using semantic and keyword search. "
+                "Use this to recall past conversations, preferences, and knowledge pages."
+            )
    
    def execute(self, args: dict):
        """
--- a/bridge/agent_bridge.py
+++ b/bridge/agent_bridge.py
@@ -160,13 +160,21 @@ class AgentLLMModel(LLMModel):
                    kwargs['system'] = system_prompt

                # Pass context metadata to bot
-                channel_type = getattr(self, 'channel_type', None)
+                channel_type = getattr(self, 'channel_type', None) or ''
                if channel_type:
                    kwargs['channel_type'] = channel_type
                session_id = getattr(self, 'session_id', None)
                if session_id:
                    kwargs['session_id'] = session_id

+                # Determine thinking: respect global config, then channel_type
+                from config import conf
+                global_thinking = conf().get("enable_thinking", True)
+                if not global_thinking:
+                    kwargs['thinking'] = {"type": "disabled"}
+                else:
+                    kwargs['thinking'] = {"type": "enabled"} if channel_type == "web" else {"type": "disabled"}
+
                response = self.bot.call_with_tools(**kwargs)
                return self._format_response(response)
            else:
@@ -205,13 +213,21 @@ class AgentLLMModel(LLMModel):
                    kwargs['system'] = system_prompt

                # Pass context metadata to bot
-                channel_type = getattr(self, 'channel_type', None)
+                channel_type = getattr(self, 'channel_type', None) or ''
                if channel_type:
                    kwargs['channel_type'] = channel_type
                session_id = getattr(self, 'session_id', None)
                if session_id:
                    kwargs['session_id'] = session_id

+                # Determine thinking: respect global config, then channel_type
+                from config import conf
+                global_thinking = conf().get("enable_thinking", True)
+                if not global_thinking:
+                    kwargs['thinking'] = {"type": "disabled"}
+                else:
+                    kwargs['thinking'] = {"type": "enabled"} if channel_type == "web" else {"type": "disabled"}
+
                stream = self.bot.call_with_tools(**kwargs)
                
                # Convert stream format to our expected format
@@ -499,10 +515,14 @@ class AgentBridge:
                reply.text_content = text_response
            return reply
        
-        # For other unknown file types, return text with file info
-        message = text_response or file_info.get("message", "文件已准备")
-        message += f"\n\n[文件: {file_info.get('file_name', file_path)}]"
-        return Reply(ReplyType.TEXT, message)
+        # For all other file types (tar.gz, zip, etc.), also use FILE type
+        file_url = f"file://{file_path}"
+        logger.info(f"[AgentBridge] Sending generic file: {file_url}")
+        reply = Reply(ReplyType.FILE, file_url)
+        reply.file_name = file_info.get("file_name", os.path.basename(file_path))
+        if text_response:
+            reply.text_content = text_response
+        return reply
    
    def _migrate_config_to_env(self, workspace_root: str):
        """
--- a/bridge/agent_event_handler.py
+++ b/bridge/agent_event_handler.py
@@ -26,8 +26,7 @@ class AgentEventHandler:
        if context:
            self.channel = context.kwargs.get("channel") if hasattr(context, "kwargs") else None
        
-        # Track current thinking for channel output
-        self.current_thinking = ""
+        self.current_content = ""
        self.turn_number = 0
    
    def handle_event(self, event):
@@ -47,6 +46,8 @@ class AgentEventHandler:
            self._handle_message_update(data)
        elif event_type == "message_end":
            self._handle_message_end(data)
+        elif event_type == "reasoning_update":
+            pass
        elif event_type == "tool_execution_start":
            self._handle_tool_execution_start(data)
        elif event_type == "tool_execution_end":
@@ -59,30 +60,26 @@ class AgentEventHandler:
    def _handle_turn_start(self, data):
        """Handle turn start event"""
        self.turn_number = data.get("turn", 0)
-        self.has_tool_calls_in_turn = False
-        self.current_thinking = ""
+        self.current_content = ""
    
    def _handle_message_update(self, data):
-        """Handle message update event (streaming text)"""
+        """Handle message update event (streaming content text)"""
        delta = data.get("delta", "")
-        self.current_thinking += delta
+        self.current_content += delta
    
    def _handle_message_end(self, data):
        """Handle message end event"""
        tool_calls = data.get("tool_calls", [])
        
-        # Only send thinking process if followed by tool calls
        if tool_calls:
-            if self.current_thinking.strip():
-                logger.info(f"💭 {self.current_thinking.strip()[:200]}{'...' if len(self.current_thinking) > 200 else ''}")
-                # Send thinking process to channel
-                self._send_to_channel(f"{self.current_thinking.strip()}")
+            if self.current_content.strip():
+                logger.info(f"💭 {self.current_content.strip()[:200]}{'...' if len(self.current_content) > 200 else ''}")
+                self._send_to_channel(self.current_content.strip())
        else:
-            # No tool calls = final response (logged at agent_stream level)
-            if self.current_thinking.strip():
-                logger.debug(f"💬 {self.current_thinking.strip()[:200]}{'...' if len(self.current_thinking) > 200 else ''}")
+            if self.current_content.strip():
+                logger.debug(f"💬 {self.current_content.strip()[:200]}{'...' if len(self.current_content) > 200 else ''}")
        
-        self.current_thinking = ""
+        self.current_content = ""
    
    def _handle_tool_execution_start(self, data):
        """Handle tool execution start event - logged by agent_stream.py"""
--- a/bridge/agent_initializer.py
+++ b/bridge/agent_initializer.py
@@ -567,7 +567,7 @@ class AgentInitializer:
        t.start()

    def _flush_all_agents(self):
-        """Flush memory for all active agent sessions."""
+        """Flush memory for all active agent sessions, then run Deep Dream."""
        agents = []
        if self.agent_bridge.default_agent:
            agents.append(("default", self.agent_bridge.default_agent))
@@ -577,7 +577,10 @@ class AgentInitializer:
        if not agents:
            return

+        # Phase 1: flush daily summaries
        flushed = 0
+        flush_threads = []
+        dream_candidate = None
        for label, agent in agents:
            try:
                if not agent.memory_manager:
@@ -589,8 +592,26 @@ class AgentInitializer:
                result = agent.memory_manager.flush_manager.create_daily_summary(messages)
                if result:
                    flushed += 1
+                    t = agent.memory_manager.flush_manager._last_flush_thread
+                    if t:
+                        flush_threads.append(t)
+                if dream_candidate is None:
+                    dream_candidate = agent.memory_manager.flush_manager
            except Exception as e:
                logger.warning(f"[DailyFlush] Failed for session {label}: {e}")

        if flushed:
            logger.info(f"[DailyFlush] Flushed {flushed}/{len(agents)} agent session(s)")
+
+        # Wait for all flush threads to finish before dreaming
+        for t in flush_threads:
+            t.join(timeout=60)
+
+        # Phase 2: Deep Dream — distill daily memories → MEMORY.md + dream diary
+        if dream_candidate:
+            try:
+                result = dream_candidate.deep_dream()
+                if result:
+                    logger.info("[DeepDream] Memory distillation completed successfully")
+            except Exception as e:
+                logger.warning(f"[DeepDream] Failed: {e}")
--- a/channel/web/chat.html
+++ b/channel/web/chat.html
@@ -50,16 +50,53 @@
    (function() {
        var theme = localStorage.getItem('cow_theme') || 'dark';
        if (theme === 'dark') document.documentElement.classList.add('dark');
+        var lang = localStorage.getItem('cow_lang') || 'zh';
+        document.documentElement.setAttribute('lang', lang);
    })();
    </script>
 </head>
 <body class="h-screen overflow-hidden bg-gray-50 dark:bg-[#111111] text-slate-800 dark:text-slate-200 font-sans">
+
+    <!-- Login Overlay -->
+    <div id="login-overlay" class="fixed inset-0 z-[200] bg-gray-50 dark:bg-[#111111] flex items-center justify-center hidden">
+        <div class="w-full max-w-sm mx-4">
+            <div class="flex flex-col items-center mb-8">
+                <img src="assets/logo.jpg" alt="CowAgent" class="w-16 h-16 rounded-2xl mb-4 shadow-lg">
+                <h1 class="text-xl font-bold text-slate-800 dark:text-slate-100">CowAgent</h1>
+                <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" id="login-subtitle">请输入密码以访问控制台</p>
+            </div>
+            <form id="login-form" class="space-y-4" onsubmit="return false;">
+                <div class="relative">
+                    <input id="login-password" type="password" autocomplete="current-password"
+                           placeholder="Password"
+                           class="w-full px-4 py-3 rounded-xl border border-slate-200 dark:border-white/10
+                                  bg-white dark:bg-[#1A1A1A] text-slate-800 dark:text-slate-200
+                                  placeholder-slate-400 dark:placeholder-slate-500
+                                  focus:outline-none focus:ring-2 focus:ring-primary-400/50 focus:border-primary-400
+                                  transition-all duration-150 text-sm">
+                    <button type="button" id="login-toggle-pwd"
+                            class="absolute right-3 top-1/2 -translate-y-1/2 text-slate-400 hover:text-slate-600
+                                   dark:hover:text-slate-300 cursor-pointer transition-colors"
+                            onclick="toggleLoginPassword()">
+                        <i class="fas fa-eye text-sm"></i>
+                    </button>
+                </div>
+                <p id="login-error" class="text-sm text-red-500 hidden"></p>
+                <button id="login-btn" type="submit"
+                        class="w-full py-3 rounded-xl bg-primary-500 hover:bg-primary-600 text-white font-medium
+                               text-sm cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed">
+                    登录
+                </button>
+            </form>
+        </div>
+    </div>
+
    <div id="app" class="flex h-screen">

        <!-- ================================================================ -->
        <!-- SIDEBAR                                                          -->
        <!-- ================================================================ -->
-        <aside id="sidebar" class="fixed inset-y-0 left-0 z-50 w-64 bg-[#0A0A0A] text-neutral-400 flex flex-col
+        <aside id="sidebar" class="fixed inset-y-0 left-0 z-50 w-52 bg-[#0A0A0A] text-neutral-400 flex flex-col
                                    transform -translate-x-full lg:relative lg:translate-x-0
                                    transition-transform duration-300 ease-in-out">
            <!-- Logo -->
@@ -67,7 +104,7 @@
                <img src="assets/logo.jpg" alt="CowAgent" class="w-8 h-8 rounded-lg flex-shrink-0">
                <div class="flex flex-col min-w-0">
                    <span class="text-white font-semibold text-sm truncate">CowAgent</span>
-                    <span class="text-neutral-500 text-xs" data-i18n="console">Console</span>
+                    <span class="text-neutral-500 text-xs" data-i18n="console">控制台</span>
                </div>
            </div>

@@ -77,13 +114,13 @@
                <div class="menu-group open" data-group="chat">
                    <button class="w-full flex items-center gap-2 px-3 py-2 text-xs font-semibold uppercase tracking-wider text-neutral-500 hover:text-neutral-300 cursor-pointer transition-colors duration-150">
                        <i class="fas fa-chevron-right text-[10px] chevron"></i>
-                        <span data-i18n="nav_chat">Chat</span>
+                        <span data-i18n="nav_chat">对话</span>
                    </button>
                    <div class="menu-group-items pl-2">
                        <a class="sidebar-item active flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
                           data-view="chat">
                            <i class="fas fa-message item-icon text-xs w-5 text-center"></i>
-                            <span data-i18n="menu_chat">Chat</span>
+                            <span data-i18n="menu_chat">对话</span>
                        </a>
                    </div>
                </div>
@@ -92,33 +129,38 @@
                <div class="menu-group open" data-group="manage">
                    <button class="w-full flex items-center gap-2 px-3 py-2 text-xs font-semibold uppercase tracking-wider text-neutral-500 hover:text-neutral-300 cursor-pointer transition-colors duration-150">
                        <i class="fas fa-chevron-right text-[10px] chevron"></i>
-                        <span data-i18n="nav_manage">Management</span>
+                        <span data-i18n="nav_manage">管理</span>
                    </button>
                    <div class="menu-group-items pl-2">
                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
                           data-view="config">
                            <i class="fas fa-sliders item-icon text-xs w-5 text-center"></i>
-                            <span data-i18n="menu_config">Config</span>
+                            <span data-i18n="menu_config">配置</span>
                        </a>
                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
                           data-view="skills">
                            <i class="fas fa-bolt item-icon text-xs w-5 text-center"></i>
-                            <span data-i18n="menu_skills">Skills</span>
+                            <span data-i18n="menu_skills">技能</span>
                        </a>
                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
                           data-view="memory">
                            <i class="fas fa-brain item-icon text-xs w-5 text-center"></i>
-                            <span data-i18n="menu_memory">Memory</span>
+                            <span data-i18n="menu_memory">记忆</span>
+                        </a>
+                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
+                           data-view="knowledge">
+                            <i class="fas fa-book item-icon text-xs w-5 text-center"></i>
+                            <span data-i18n="menu_knowledge">知识</span>
                        </a>
                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
                           data-view="channels">
                            <i class="fas fa-tower-broadcast item-icon text-xs w-5 text-center"></i>
-                            <span data-i18n="menu_channels">Channels</span>
+                            <span data-i18n="menu_channels">通道</span>
                        </a>
                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
                           data-view="tasks">
                            <i class="fas fa-clock item-icon text-xs w-5 text-center"></i>
-                            <span data-i18n="menu_tasks">Tasks</span>
+                            <span data-i18n="menu_tasks">定时</span>
                        </a>
                    </div>
                </div>
@@ -127,13 +169,13 @@
                <div class="menu-group open" data-group="monitor">
                    <button class="w-full flex items-center gap-2 px-3 py-2 text-xs font-semibold uppercase tracking-wider text-neutral-500 hover:text-neutral-300 cursor-pointer transition-colors duration-150">
                        <i class="fas fa-chevron-right text-[10px] chevron"></i>
-                        <span data-i18n="nav_monitor">Monitor</span>
+                        <span data-i18n="nav_monitor">监控</span>
                    </button>
                    <div class="menu-group-items pl-2">
                        <a class="sidebar-item flex items-center gap-3 px-3 py-2 rounded-lg cursor-pointer transition-all duration-150 hover:bg-white/5 hover:text-neutral-200 text-[14px]"
                           data-view="logs">
                            <i class="fas fa-terminal item-icon text-xs w-5 text-center"></i>
-                            <span data-i18n="menu_logs">Logs</span>
+                            <span data-i18n="menu_logs">日志</span>
                        </a>
                    </div>
                </div>
@@ -154,6 +196,23 @@
        <!-- Mobile Overlay -->
        <div id="sidebar-overlay" class="fixed inset-0 bg-black/50 z-40 hidden lg:hidden cursor-pointer" onclick="toggleSidebar()"></div>

+        <!-- ================================================================ -->
+        <!-- SESSION PANEL (collapsible)                                      -->
+        <!-- ================================================================ -->
+        <aside id="session-panel" class="session-panel hidden">
+            <div class="session-panel-header">
+                <span class="session-panel-title" data-i18n="session_history">历史会话</span>
+                <button class="session-panel-close" onclick="toggleSessionPanel()" title="Close">
+                    <i class="fas fa-times"></i>
+                </button>
+            </div>
+            <button class="session-panel-new" onclick="newChat()">
+                <i class="fas fa-plus"></i>
+                <span data-i18n="new_chat">新对话</span>
+            </button>
+            <div id="session-list" class="session-list"></div>
+        </aside>
+
        <!-- ================================================================ -->
        <!-- MAIN CONTENT                                                     -->
        <!-- ================================================================ -->
@@ -166,11 +225,17 @@
                    <i class="fas fa-bars text-slate-600 dark:text-slate-300"></i>
                </button>

+                <!-- Session panel toggle -->
+                <button id="session-toggle-btn" class="p-2 rounded-lg hover:bg-slate-100 dark:hover:bg-white/10 cursor-pointer transition-colors duration-150"
+                        onclick="toggleSessionPanel()">
+                    <i class="fas fa-clock-rotate-left text-slate-500 dark:text-slate-400"></i>
+                </button>
+
                <!-- Breadcrumb (hidden on mobile) -->
                <div class="hidden lg:flex items-center gap-2 text-sm min-w-0">
-                    <span id="breadcrumb-group" class="text-slate-400 dark:text-slate-500 truncate" data-i18n="nav_chat">Chat</span>
+                    <span id="breadcrumb-group" class="text-slate-400 dark:text-slate-500 truncate" data-i18n="nav_chat">对话</span>
                    <i class="fas fa-chevron-right text-[10px] text-slate-300 dark:text-slate-600"></i>
-                    <span id="breadcrumb-page" class="font-medium text-slate-700 dark:text-slate-200 truncate" data-i18n="menu_chat">Chat</span>
+                    <span id="breadcrumb-page" class="font-medium text-slate-700 dark:text-slate-200 truncate" data-i18n="menu_chat">对话</span>
                </div>

                <div class="flex-1"></div>
@@ -224,22 +289,22 @@
                    <!-- Messages -->
                    <div id="chat-messages" class="flex-1 overflow-y-auto">
                        <!-- Welcome Screen -->
-                        <div id="welcome-screen" class="flex flex-col items-center justify-center h-full px-6 py-12">
+                        <div id="welcome-screen" class="flex flex-col items-center justify-center h-full px-6 pb-16" style="padding-top: 6vh">
                            <img src="assets/logo.jpg" alt="CowAgent" class="w-16 h-16 rounded-2xl mb-6 shadow-lg shadow-primary-500/20">
                            <h1 id="welcome-title" class="text-2xl font-bold text-slate-800 dark:text-slate-100 mb-3">CowAgent</h1>
                            <p id="welcome-subtitle" class="text-slate-500 dark:text-slate-400 text-center max-w-lg mb-10 leading-relaxed"
-                               data-i18n-html="welcome_subtitle">I can help you answer questions, manage your computer, create and execute skills,<br>and keep growing through long-term memory.</p>
+                               data-i18n-html="welcome_subtitle">我可以帮你解答问题、管理计算机、创造和执行技能，并通过<br>长期记忆和知识库不断成长</p>

-                            <div class="grid grid-cols-1 sm:grid-cols-3 gap-4 w-full max-w-2xl">
+                            <div class="grid grid-cols-2 sm:grid-cols-3 gap-3 w-full max-w-2xl">
                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
                                    <div class="flex items-center gap-2 mb-2">
                                        <div class="w-7 h-7 rounded-lg bg-blue-50 dark:bg-blue-900/30 flex items-center justify-center">
                                            <i class="fas fa-folder-open text-blue-500 text-xs"></i>
                                        </div>
-                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_sys_title">System</span>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_sys_title">系统管理</span>
                                    </div>
-                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_sys_text">Show me the files in the workspace</p>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_sys_text">查看工作空间里有哪些文件</p>
                                </div>
                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
@@ -247,9 +312,9 @@
                                        <div class="w-7 h-7 rounded-lg bg-amber-50 dark:bg-amber-900/30 flex items-center justify-center">
                                            <i class="fas fa-clock text-amber-500 text-xs"></i>
                                        </div>
-                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_task_title">Smart Task</span>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_task_title">定时任务</span>
                                    </div>
-                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_task_text">Remind me to check the server in 5 minutes</p>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_task_text">1分钟后提醒我检查服务器</p>
                                </div>
                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
@@ -257,9 +322,40 @@
                                        <div class="w-7 h-7 rounded-lg bg-emerald-50 dark:bg-emerald-900/30 flex items-center justify-center">
                                            <i class="fas fa-code text-emerald-500 text-xs"></i>
                                        </div>
-                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_code_title">Coding</span>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_code_title">编程助手</span>
                                    </div>
-                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_code_text">Write a Python web scraper script</p>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_code_text">搜索AI资讯并生成可视化网页报告</p>
+                                </div>
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-violet-50 dark:bg-violet-900/30 flex items-center justify-center">
+                                            <i class="fas fa-book text-violet-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_knowledge_title">知识库</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_knowledge_text">查看知识库当前文档情况</p>
+                                </div>
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-rose-50 dark:bg-rose-900/30 flex items-center justify-center">
+                                            <i class="fas fa-puzzle-piece text-rose-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_skill_title">技能系统</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_skill_text">查看所有支持的工具和技能</p>
+                                </div>
+                                <div class="example-card group bg-white dark:bg-[#1A1A1A] border border-slate-200 dark:border-white/10 rounded-xl p-4
+                                            cursor-pointer hover:border-primary-300 dark:hover:border-primary-600 hover:shadow-md transition-all duration-200"
+                                     data-send="/help">
+                                    <div class="flex items-center gap-2 mb-2">
+                                        <div class="w-7 h-7 rounded-lg bg-slate-100 dark:bg-slate-800 flex items-center justify-center">
+                                            <i class="fas fa-terminal text-slate-500 text-xs"></i>
+                                        </div>
+                                        <span class="font-medium text-sm text-slate-700 dark:text-slate-200" data-i18n="example_web_title">指令中心</span>
+                                    </div>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 leading-relaxed" data-i18n="example_web_text">查看全部命令</p>
                                </div>
                            </div>
                        </div>
@@ -274,14 +370,20 @@
                                <div class="flex items-center flex-shrink-0">
                                    <button id="new-chat-btn" class="w-9 h-10 flex items-center justify-center rounded-lg
                                                                     text-slate-400 hover:text-primary-500 hover:bg-primary-50 dark:hover:bg-primary-900/20
-                                                                     cursor-pointer transition-colors duration-150" title="New Chat"
+                                                                     cursor-pointer transition-colors duration-150"
                                            onclick="newChat()">
                                        <i class="fas fa-plus text-base"></i>
                                    </button>
+                                    <button id="clear-context-btn" class="w-9 h-10 flex items-center justify-center rounded-lg
+                                                                          text-slate-400 hover:text-amber-500 hover:bg-amber-50 dark:hover:bg-amber-900/20
+                                                                          cursor-pointer transition-colors duration-150"
+                                            onclick="clearContext()">
+                                        <i class="fas fa-trash-can text-base"></i>
+                                    </button>
                                    <button id="attach-btn" class="w-9 h-10 flex items-center justify-center rounded-lg
                                                                   text-slate-400 hover:text-primary-500 hover:bg-primary-50 dark:hover:bg-primary-900/20
                                                                   cursor-pointer transition-colors duration-150"
-                                            title="Attach file" onclick="document.getElementById('file-input').click()">
+                                            onclick="document.getElementById('file-input').click()">
                                        <i class="fas fa-paperclip text-base"></i>
                                    </button>
                                </div>
@@ -296,7 +398,7 @@
                                                 text-sm leading-relaxed"
                                          rows="1"
                                          data-i18n-placeholder="input_placeholder"
-                                          placeholder="Type a message, or press / for commands"></textarea>
+                                          placeholder="输入消息，或输入 / 使用指令"></textarea>
                                <button id="send-btn"
                                        class="flex-shrink-0 w-10 h-10 flex items-center justify-center rounded-lg
                                               bg-primary-400 text-white hover:bg-primary-500
@@ -318,8 +420,8 @@
                        <div class="max-w-4xl mx-auto">
                            <div class="flex items-center justify-between mb-6">
                                <div>
-                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="config_title">Configuration</h2>
-                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="config_desc">Manage model and agent settings</p>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="config_title">配置管理</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="config_desc">管理模型和 Agent 配置</p>
                                </div>
                            </div>
                            <div class="grid gap-6">
@@ -330,12 +432,12 @@
                                        <div class="w-9 h-9 rounded-lg bg-primary-50 dark:bg-primary-900/30 flex items-center justify-center">
                                            <i class="fas fa-microchip text-primary-500 text-sm"></i>
                                        </div>
-                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_model">Model Configuration</h3>
+                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_model">模型配置</h3>
                                    </div>
                                    <div class="space-y-5">
                                        <!-- Provider -->
                                        <div>
-                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_provider">Provider</label>
+                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_provider">模型厂商</label>
                                            <div id="cfg-provider" class="cfg-dropdown" tabindex="0">
                                                <div class="cfg-dropdown-selected">
                                                    <span class="cfg-dropdown-text">--</span>
@@ -346,7 +448,7 @@
                                        </div>
                                        <!-- Model -->
                                        <div>
-                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_model_name">Model</label>
+                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_model_name">模型</label>
                                            <div id="cfg-model-select" class="cfg-dropdown" tabindex="0">
                                                <div class="cfg-dropdown-selected">
                                                    <span class="cfg-dropdown-text">--</span>
@@ -359,7 +461,7 @@
                                                       class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
                                                              bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
                                                              focus:outline-none focus:border-primary-500 font-mono transition-colors"
-                                                       data-i18n-placeholder="config_custom_model_hint" placeholder="Enter custom model name">
+                                                       data-i18n-placeholder="config_custom_model_hint" placeholder="输入自定义模型名称">
                                            </div>
                                        </div>
                                        <!-- API Key -->
@@ -394,7 +496,7 @@
                                            <button id="cfg-model-save"
                                                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
                                                           cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
-                                                    onclick="saveModelConfig()" data-i18n="config_save">Save</button>
+                                                    onclick="saveModelConfig()" data-i18n="config_save">保存</button>
                                        </div>
                                    </div>
                                </div>
@@ -405,36 +507,86 @@
                                        <div class="w-9 h-9 rounded-lg bg-emerald-50 dark:bg-emerald-900/30 flex items-center justify-center">
                                            <i class="fas fa-robot text-emerald-500 text-sm"></i>
                                        </div>
-                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_agent">Agent Configuration</h3>
+                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_agent">Agent 配置</h3>
                                    </div>
                                    <div class="space-y-4">
                                        <div>
-                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_max_tokens">Max Context Tokens</label>
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                                <span data-i18n="config_max_tokens">最大上下文 Token</span>
+                                                <span class="cfg-tip" data-tip-key="config_max_tokens_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
                                            <input id="cfg-max-tokens" type="number" min="1000" max="200000" step="1000"
                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors">
                                        </div>
                                        <div>
-                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_max_turns">Max Context Turns</label>
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                                <span data-i18n="config_max_turns">最大记忆轮次</span>
+                                                <span class="cfg-tip" data-tip-key="config_max_turns_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
                                            <input id="cfg-max-turns" type="number" min="1" max="100" step="1"
                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors">
                                        </div>
                                        <div>
-                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_max_steps">Max Steps</label>
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5">
+                                                <span data-i18n="config_max_steps">最大执行步数</span>
+                                                <span class="cfg-tip" data-tip-key="config_max_steps_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
                                            <input id="cfg-max-steps" type="number" min="1" max="50" step="1"
                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors">
                                        </div>
+                                        <div class="flex items-center justify-between">
+                                            <label class="flex items-center gap-1.5 text-sm font-medium text-slate-600 dark:text-slate-400">
+                                                <span data-i18n="config_enable_thinking">Deep Thinking</span>
+                                                <span class="cfg-tip" data-tip-key="config_enable_thinking_hint"><i class="fas fa-circle-question"></i></span>
+                                            </label>
+                                            <label class="relative inline-flex items-center cursor-pointer">
+                                                <input id="cfg-enable-thinking" type="checkbox" class="sr-only peer" checked>
+                                                <div class="w-9 h-5 bg-slate-200 dark:bg-slate-700 peer-checked:bg-primary-400 rounded-full
+                                                            after:content-[''] after:absolute after:top-[2px] after:left-[2px] after:bg-white
+                                                            after:rounded-full after:h-4 after:w-4 after:transition-all peer-checked:after:translate-x-full"></div>
+                                            </label>
+                                        </div>
                                        <div class="flex items-center justify-end gap-3 pt-1">
                                            <span id="cfg-agent-status" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
                                            <button id="cfg-agent-save"
                                                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
                                                           cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
-                                                    onclick="saveAgentConfig()" data-i18n="config_save">Save</button>
+                                                    onclick="saveAgentConfig()" data-i18n="config_save">保存</button>
+                                        </div>
+                                    </div>
+                                </div>
+
+                                <!-- Security Config Card -->
+                                <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 p-6">
+                                    <div class="flex items-center gap-3 mb-5">
+                                        <div class="w-9 h-9 rounded-lg bg-amber-50 dark:bg-amber-900/30 flex items-center justify-center">
+                                            <i class="fas fa-lock text-amber-500 text-sm"></i>
+                                        </div>
+                                        <h3 class="font-semibold text-slate-800 dark:text-slate-100" data-i18n="config_security">安全设置</h3>
+                                    </div>
+                                    <div class="space-y-4">
+                                        <div>
+                                            <label class="block text-sm font-medium text-slate-600 dark:text-slate-400 mb-1.5" data-i18n="config_password">访问密码</label>
+                                            <input id="cfg-password" type="password" autocomplete="new-password"
+                                                   class="w-full px-3 py-2 rounded-lg border border-slate-200 dark:border-slate-600
+                                                          bg-slate-50 dark:bg-white/5 text-sm text-slate-800 dark:text-slate-100
+                                                          focus:outline-none focus:border-primary-500 font-mono transition-colors
+                                                          cfg-key-masked"
+                                                   data-masked="1">
+                                            <p class="text-xs text-slate-400 dark:text-slate-500 mt-1.5" data-i18n="config_password_hint">留空则不启用密码保护</p>
+                                        </div>
+                                        <div class="flex items-center justify-end gap-3 pt-1">
+                                            <span id="cfg-password-status" class="text-xs text-primary-500 opacity-0 transition-opacity duration-300"></span>
+                                            <button id="cfg-password-save"
+                                                    class="px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600 text-white text-sm font-medium
+                                                           cursor-pointer transition-colors duration-150 disabled:opacity-50 disabled:cursor-not-allowed"
+                                                    onclick="savePasswordConfig()" data-i18n="config_save">保存</button>
                                        </div>
                                    </div>
                                </div>
@@ -452,25 +604,25 @@
                        <div class="max-w-4xl mx-auto">
                            <div class="flex items-center justify-between mb-6">
                                <div>
-                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="skills_title">Skills</h2>
-                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="skills_desc">View, enable, or disable agent skills</p>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="skills_title">技能管理</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="skills_desc">查看、启用或禁用 Agent 技能</p>
                                </div>
                                <a href="https://skills.cowagent.ai/" target="_blank"
                                   class="inline-flex items-center gap-1.5 px-3 py-1.5 rounded-lg text-xs font-medium text-primary-500 bg-primary-50 dark:bg-primary-900/20 hover:bg-primary-100 dark:hover:bg-primary-900/30 transition-colors">
                                    <i class="fas fa-puzzle-piece text-[10px]"></i>
-                                    <span data-i18n="skills_hub_btn">Skill Hub</span>
+                                    <span data-i18n="skills_hub_btn">探索技能广场</span>
                                </a>
                            </div>

                            <!-- Built-in Tools Section -->
                            <div class="mb-8">
                                <div class="flex items-center gap-2 mb-3">
-                                    <span class="text-xs font-semibold uppercase tracking-wider text-slate-400 dark:text-slate-500" data-i18n="tools_section_title">Built-in Tools</span>
+                                    <span class="text-xs font-semibold uppercase tracking-wider text-slate-400 dark:text-slate-500" data-i18n="tools_section_title">内置工具</span>
                                    <span id="tools-count-badge" class="hidden px-2 py-0.5 rounded-full text-xs bg-slate-100 dark:bg-white/10 text-slate-500 dark:text-slate-400"></span>
                                </div>
                                <div id="tools-empty" class="flex items-center gap-2 py-4 text-slate-400 dark:text-slate-500 text-sm">
                                    <i class="fas fa-spinner fa-spin text-xs"></i>
-                                    <span data-i18n="tools_loading">Loading tools...</span>
+                                    <span data-i18n="tools_loading">加载工具中...</span>
                                </div>
                                <div id="tools-list" class="grid gap-3 sm:grid-cols-2 hidden"></div>
                            </div>
@@ -478,15 +630,15 @@
                            <!-- Skills Section -->
                            <div>
                                <div class="flex items-center gap-2 mb-3">
-                                    <span class="text-xs font-semibold uppercase tracking-wider text-slate-400 dark:text-slate-500" data-i18n="skills_section_title">Skills</span>
+                                    <span class="text-xs font-semibold uppercase tracking-wider text-slate-400 dark:text-slate-500" data-i18n="skills_section_title">技能</span>
                                    <span id="skills-count-badge" class="hidden px-2 py-0.5 rounded-full text-xs bg-slate-100 dark:bg-white/10 text-slate-500 dark:text-slate-400"></span>
                                </div>
                                <div id="skills-empty" class="flex flex-col items-center justify-center py-12">
                                    <div class="w-14 h-14 rounded-2xl bg-amber-50 dark:bg-amber-900/20 flex items-center justify-center mb-3">
                                        <i class="fas fa-bolt text-amber-400 text-lg"></i>
                                    </div>
-                                    <p class="text-slate-500 dark:text-slate-400 font-medium" data-i18n="skills_loading">Loading skills...</p>
-                                    <p class="text-sm text-slate-400 dark:text-slate-500 mt-1" data-i18n="skills_loading_desc">Skills will be displayed here after loading</p>
+                                    <p class="text-slate-500 dark:text-slate-400 font-medium" data-i18n="skills_loading">加载技能中...</p>
+                                    <p class="text-sm text-slate-400 dark:text-slate-500 mt-1" data-i18n="skills_loading_desc">技能加载后将显示在此处</p>
                                </div>
                                <div id="skills-list" class="grid gap-4 sm:grid-cols-2"></div>
                            </div>
@@ -505,26 +657,36 @@
                            <div id="memory-panel-list">
                                <div class="flex items-center justify-between mb-6">
                                    <div>
-                                        <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="memory_title">Memory</h2>
-                                        <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="memory_desc">View agent memory files and contents</p>
+                                        <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="memory_title">记忆管理</h2>
+                                        <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="memory_desc">查看 Agent 记忆文件和内容</p>
+                                    </div>
+                                    <div class="flex items-center bg-slate-100 dark:bg-white/10 rounded-lg p-0.5">
+                                        <button id="memory-tab-files" onclick="switchMemoryTab('files')"
+                                                class="memory-tab px-3 py-1.5 rounded-md text-xs font-medium cursor-pointer transition-colors duration-150 active">
+                                            <i class="fas fa-file-lines mr-1.5"></i><span data-i18n="memory_tab_files">记忆文件</span>
+                                        </button>
+                                        <button id="memory-tab-dreams" onclick="switchMemoryTab('dreams')"
+                                                class="memory-tab px-3 py-1.5 rounded-md text-xs font-medium cursor-pointer transition-colors duration-150">
+                                            <i class="fas fa-moon mr-1.5"></i><span data-i18n="memory_tab_dreams">梦境日记</span>
+                                        </button>
                                    </div>
                                </div>
                                <div id="memory-empty" class="flex flex-col items-center justify-center py-20">
                                    <div class="w-16 h-16 rounded-2xl bg-purple-50 dark:bg-purple-900/20 flex items-center justify-center mb-4">
                                        <i class="fas fa-brain text-purple-400 text-xl"></i>
                                    </div>
-                                    <p class="text-slate-500 dark:text-slate-400 font-medium" data-i18n="memory_loading">Loading memory files...</p>
-                                    <p class="text-sm text-slate-400 dark:text-slate-500 mt-1" data-i18n="memory_loading_desc">Memory files will be displayed here</p>
+                                    <p class="text-slate-500 dark:text-slate-400 font-medium" data-i18n="memory_loading">加载记忆文件中...</p>
+                                    <p class="text-sm text-slate-400 dark:text-slate-500 mt-1" data-i18n="memory_loading_desc">记忆文件将显示在此处</p>
                                </div>
                                <div id="memory-list" class="hidden">
                                    <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden">
                                        <table class="w-full">
                                            <thead>
                                                <tr class="border-b border-slate-200 dark:border-white/10">
-                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_name">Filename</th>
-                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_type">Type</th>
-                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_size">Size</th>
-                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_updated">Updated</th>
+                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_name">文件名</th>
+                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_type">类型</th>
+                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_size">大小</th>
+                                                    <th class="text-left px-4 py-3 text-xs font-semibold uppercase tracking-wider text-slate-500 dark:text-slate-400" data-i18n="memory_col_updated">更新时间</th>
                                                </tr>
                                            </thead>
                                            <tbody id="memory-table-body"></tbody>
@@ -542,7 +704,7 @@
                                                   text-slate-500 dark:text-slate-400 hover:bg-slate-100 dark:hover:bg-white/10
                                                   border border-slate-200 dark:border-white/10 transition-colors cursor-pointer">
                                        <i class="fas fa-arrow-left text-xs"></i>
-                                        <span data-i18n="memory_back">Back</span>
+                                        <span data-i18n="memory_back">返回列表</span>
                                    </button>
                                    <h2 id="memory-viewer-title"
                                        class="text-base font-semibold text-slate-800 dark:text-slate-100 font-mono truncate"></h2>
@@ -558,6 +720,106 @@
                    </div>
                </div>

+                <!-- ====================================================== -->
+                <!-- VIEW: Knowledge                                         -->
+                <!-- ====================================================== -->
+                <div id="view-knowledge" class="view">
+                    <div class="flex-1 overflow-y-auto p-4 md:p-8 lg:p-10">
+                        <div class="w-full max-w-[1600px] mx-auto">
+
+                            <!-- Header -->
+                            <div class="flex flex-col sm:flex-row sm:items-center justify-between gap-3 mb-4 md:mb-6">
+                                <div>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="knowledge_title">知识库</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="knowledge_desc">浏览和探索你的知识库</p>
+                                </div>
+                                <div class="flex items-center gap-2">
+                                    <span id="knowledge-stats" class="text-xs text-slate-400 dark:text-slate-500 hidden sm:inline"></span>
+                                    <div class="flex items-center bg-slate-100 dark:bg-white/10 rounded-lg p-0.5">
+                                        <button id="knowledge-tab-docs" onclick="switchKnowledgeTab('docs')"
+                                                class="knowledge-tab px-3 py-1.5 rounded-md text-xs font-medium cursor-pointer transition-colors duration-150 active">
+                                            <i class="fas fa-folder-tree mr-1.5"></i><span data-i18n="knowledge_tab_docs">文档</span>
+                                        </button>
+                                        <button id="knowledge-tab-graph" onclick="switchKnowledgeTab('graph')"
+                                                class="knowledge-tab px-3 py-1.5 rounded-md text-xs font-medium cursor-pointer transition-colors duration-150">
+                                            <i class="fas fa-diagram-project mr-1.5"></i><span data-i18n="knowledge_tab_graph">图谱</span>
+                                        </button>
+                                    </div>
+                                </div>
+                            </div>
+
+                            <!-- Empty state -->
+                            <div id="knowledge-empty" class="flex flex-col items-center justify-center py-20">
+                                <div class="w-16 h-16 rounded-2xl bg-emerald-50 dark:bg-emerald-900/20 flex items-center justify-center mb-4">
+                                    <i class="fas fa-book text-emerald-400 text-xl"></i>
+                                </div>
+                                <p class="text-slate-500 dark:text-slate-400 font-medium" data-i18n="knowledge_loading">加载知识库中...</p>
+                                <p class="text-sm text-slate-400 dark:text-slate-500 mt-1" data-i18n="knowledge_loading_desc">知识页面将显示在这里</p>
+                                <div id="knowledge-empty-guide" class="hidden mt-6 max-w-sm text-center">
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mb-4" data-i18n="knowledge_empty_guide">在对话中发送文档、链接或主题给 Agent，它会自动整理到你的知识库中。</p>
+                                    <button onclick="navigateTo('chat')"
+                                            class="inline-flex items-center gap-2 px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600
+                                                   text-white text-sm font-medium cursor-pointer transition-colors duration-150">
+                                        <i class="fas fa-message text-xs"></i>
+                                        <span data-i18n="knowledge_go_chat">开始对话</span>
+                                    </button>
+                                </div>
+                            </div>
+
+                            <!-- Documents panel -->
+                            <div id="knowledge-panel-docs" class="hidden">
+                                <div class="flex flex-col md:flex-row gap-4 md:gap-6" style="min-height: calc(100vh - 220px)">
+                                    <!-- File tree -->
+                                    <div id="knowledge-sidebar" class="w-full md:w-72 lg:w-80 flex-shrink-0">
+                                        <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden">
+                                            <div class="px-4 py-3 border-b border-slate-200 dark:border-white/10">
+                                                <div class="relative">
+                                                    <i class="fas fa-search absolute left-3 top-1/2 -translate-y-1/2 text-slate-400 text-xs"></i>
+                                                    <input id="knowledge-search" type="text" placeholder="Search..."
+                                                           class="w-full pl-8 pr-3 py-1.5 text-xs bg-slate-50 dark:bg-white/5 border border-slate-200 dark:border-white/10 rounded-lg text-slate-700 dark:text-slate-200 placeholder-slate-400 dark:placeholder-slate-500 focus:outline-none focus:ring-1 focus:ring-primary-400/50"
+                                                           oninput="filterKnowledgeTree(this.value)">
+                                                </div>
+                                            </div>
+                                            <div id="knowledge-tree" class="p-2 overflow-y-auto max-h-[50vh] md:max-h-[calc(100vh-300px)]"></div>
+                                        </div>
+                                    </div>
+                                    <!-- Content viewer -->
+                                    <div class="flex-1 min-w-0">
+                                        <div id="knowledge-content-placeholder"
+                                             class="flex flex-col items-center justify-center py-20 text-slate-400 dark:text-slate-500">
+                                            <i class="fas fa-file-lines text-3xl mb-3 opacity-40"></i>
+                                            <p class="text-sm" data-i18n="knowledge_select_hint">选择一个文档查看</p>
+                                        </div>
+                                        <div id="knowledge-content-viewer" class="hidden">
+                                            <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden">
+                                                <div class="flex items-center gap-3 px-4 md:px-5 py-3 border-b border-slate-200 dark:border-white/10">
+                                                    <button onclick="knowledgeMobileBack()" class="md:hidden p-1 -ml-1 text-slate-400 hover:text-slate-600 dark:hover:text-slate-300 cursor-pointer">
+                                                        <i class="fas fa-arrow-left text-xs"></i>
+                                                    </button>
+                                                    <i class="fas fa-file-lines text-slate-400 text-sm hidden md:inline"></i>
+                                                    <span id="knowledge-viewer-title" class="text-sm font-medium text-slate-700 dark:text-slate-200 truncate"></span>
+                                                    <span id="knowledge-viewer-path" class="text-xs text-slate-400 dark:text-slate-500 ml-auto font-mono truncate hidden md:inline"></span>
+                                                </div>
+                                                <div id="knowledge-viewer-body"
+                                                     class="p-4 md:p-5 overflow-y-auto text-sm msg-content text-slate-700 dark:text-slate-200"
+                                                     style="max-height: calc(100vh - 280px)"></div>
+                                            </div>
+                                        </div>
+                                    </div>
+                                </div>
+                            </div>
+
+                            <!-- Graph panel -->
+                            <div id="knowledge-panel-graph" class="hidden">
+                                <div class="bg-white dark:bg-[#1A1A1A] rounded-xl border border-slate-200 dark:border-white/10 overflow-hidden">
+                                    <div id="knowledge-graph-container" class="w-full h-[60vh] md:h-[calc(100vh-220px)]"></div>
+                                </div>
+                            </div>
+
+                        </div>
+                    </div>
+                </div>
+
                <!-- ====================================================== -->
                <!-- VIEW: Channels                                          -->
                <!-- ====================================================== -->
@@ -566,14 +828,14 @@
                        <div class="max-w-4xl mx-auto">
                            <div class="flex items-center justify-between mb-6">
                                <div>
-                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="channels_title">Channels</h2>
-                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="channels_desc">View and manage messaging channels</p>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="channels_title">通道管理</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="channels_desc">管理已接入的消息通道</p>
                                </div>
                                <button id="add-channel-btn" onclick="openAddChannelPanel()"
                                        class="flex items-center gap-2 px-4 py-2 rounded-lg bg-primary-500 hover:bg-primary-600
                                               text-white text-sm font-medium cursor-pointer transition-colors duration-150">
                                    <i class="fas fa-plus text-xs"></i>
-                                    <span data-i18n="channels_add">Connect</span>
+                                    <span data-i18n="channels_add">接入通道</span>
                                </button>
                            </div>
                            <div id="channels-content" class="grid gap-4"></div>
@@ -590,8 +852,8 @@
                        <div class="max-w-4xl mx-auto">
                            <div class="flex items-center justify-between mb-6">
                                <div>
-                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="tasks_title">Scheduled Tasks</h2>
-                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="tasks_desc">View and manage scheduled tasks</p>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="tasks_title">定时任务</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="tasks_desc">查看和管理定时任务</p>
                                </div>
                            </div>
                            <div id="tasks-empty" class="flex flex-col items-center justify-center py-20">
@@ -613,8 +875,8 @@
                        <div class="max-w-5xl mx-auto">
                            <div class="flex items-center justify-between mb-6">
                                <div>
-                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="logs_title">Logs</h2>
-                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="logs_desc">Real-time log output (run.log)</p>
+                                    <h2 class="text-xl font-bold text-slate-800 dark:text-slate-100" data-i18n="logs_title">日志</h2>
+                                    <p class="text-sm text-slate-500 dark:text-slate-400 mt-1" data-i18n="logs_desc">实时日志输出 (run.log)</p>
                                </div>
                            </div>
                            <!-- Log Terminal -->
@@ -629,11 +891,11 @@
                                    <div class="flex-1"></div>
                                    <div class="flex items-center gap-1.5">
                                        <span class="w-2 h-2 rounded-full bg-emerald-500 animate-pulse"></span>
-                                        <span class="text-xs text-slate-500" data-i18n="logs_live">Live</span>
+                                        <span class="text-xs text-slate-500" data-i18n="logs_live">实时</span>
                                    </div>
                                </div>
                                <div id="log-output" class="p-4 overflow-y-auto font-mono text-xs leading-relaxed text-slate-300 whitespace-pre-wrap break-all" style="height: calc(100vh - 272px)">
-                                    <p class="text-slate-500" data-i18n="logs_coming_msg">Log streaming will be available here. Connects to run.log for real-time output similar to tail -f.</p>
+                                    <p class="text-slate-500" data-i18n="logs_coming_msg">日志流即将在此提供。将连接 run.log 实现类似 tail -f 的实时输出。</p>
                                </div>
                            </div>
                        </div>
@@ -670,6 +932,7 @@
        </div>
    </div>

+    <script src="https://cdn.jsdelivr.net/npm/d3@7/dist/d3.min.js"></script>
    <script src="assets/js/console.js"></script>
 </body>
 </html>
--- a/channel/web/static/css/console.css
+++ b/channel/web/static/css/console.css
@@ -17,6 +17,45 @@
 .dark ::-webkit-scrollbar-thumb { background: #475569; }
 .dark ::-webkit-scrollbar-thumb:hover { background: #64748b; }

+/* Generic Tooltip (via data-tooltip attribute) */
+[data-tooltip] {
+    position: relative;
+}
+[data-tooltip]::after {
+    content: attr(data-tooltip);
+    position: absolute;
+    left: 50%;
+    bottom: calc(100% + 8px);
+    transform: translateX(-50%);
+    padding: 5px 10px;
+    border-radius: 6px;
+    font-size: 12px;
+    font-weight: 400;
+    line-height: 1.4;
+    white-space: nowrap;
+    background: #1e293b;
+    color: #e2e8f0;
+    box-shadow: 0 4px 12px rgba(0, 0, 0, 0.15);
+    opacity: 0;
+    pointer-events: none;
+    transition: opacity 0.15s ease;
+    z-index: 100;
+}
+[data-tooltip-pos="bottom"]::after {
+    bottom: auto;
+    top: calc(100% + 8px);
+}
+.dark [data-tooltip]::after {
+    background: #334155;
+    color: #f1f5f9;
+}
+[data-tooltip]:hover::after {
+    opacity: 1;
+}
+[data-tooltip=""]:hover::after {
+    display: none;
+}
+
 /* Sidebar */
 .sidebar-item.active {
    background: rgba(255, 255, 255, 0.08);
@@ -24,9 +63,300 @@
 }
 .sidebar-item.active .item-icon { color: #4ABE6E; }

+/* Session Panel */
+.session-panel {
+    width: 220px;
+    flex-shrink: 0;
+    display: flex;
+    flex-direction: column;
+    background: #fafafa;
+    border-right: 1px solid #e5e7eb;
+    height: 100vh;
+    overflow: hidden;
+    transition: width 0.2s ease;
+}
+.dark .session-panel {
+    background: #111111;
+    border-right-color: rgba(255, 255, 255, 0.08);
+}
+.session-panel.hidden { display: none; }
+.session-panel-header {
+    display: flex;
+    align-items: center;
+    justify-content: space-between;
+    padding: 12px 16px;
+    border-bottom: 1px solid #e5e7eb;
+    flex-shrink: 0;
+}
+.dark .session-panel-header { border-bottom-color: rgba(255, 255, 255, 0.08); }
+.session-panel-title {
+    font-size: 14px;
+    font-weight: 600;
+    color: #374151;
+}
+.dark .session-panel-title { color: #d1d5db; }
+.session-panel-close {
+    width: 28px;
+    height: 28px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    border-radius: 6px;
+    border: none;
+    background: none;
+    color: #9ca3af;
+    cursor: pointer;
+    transition: background 0.15s, color 0.15s;
+    font-size: 12px;
+}
+.session-panel-close:hover {
+    background: #f3f4f6;
+    color: #374151;
+}
+.dark .session-panel-close:hover {
+    background: rgba(255, 255, 255, 0.08);
+    color: #e5e5e5;
+}
+.session-panel-new {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    margin: 10px 12px;
+    padding: 8px 14px;
+    border-radius: 8px;
+    border: 1px dashed #d1d5db;
+    background: none;
+    color: #6b7280;
+    font-size: 13px;
+    cursor: pointer;
+    transition: border-color 0.15s, color 0.15s, background 0.15s;
+    flex-shrink: 0;
+}
+.session-panel-new:hover {
+    border-color: #9ca3af;
+    color: #374151;
+    background: #f9fafb;
+}
+.dark .session-panel-new {
+    border-color: rgba(255, 255, 255, 0.12);
+    color: #9ca3af;
+}
+.dark .session-panel-new:hover {
+    border-color: rgba(255, 255, 255, 0.25);
+    color: #e5e5e5;
+    background: rgba(255, 255, 255, 0.04);
+}
+
+/* Session List */
+.session-list {
+    flex: 1;
+    overflow-y: auto;
+    padding: 4px 8px;
+    scrollbar-width: none;
+}
+.session-list:hover { scrollbar-width: thin; }
+.session-list::-webkit-scrollbar { width: 4px; background: transparent; }
+.session-list::-webkit-scrollbar-thumb { background: transparent; border-radius: 2px; }
+.session-list:hover::-webkit-scrollbar-thumb { background: rgba(0,0,0,0.2); }
+.dark .session-list:hover::-webkit-scrollbar-thumb { background: rgba(255,255,255,0.15); }
+.session-group-label {
+    padding: 10px 8px 4px;
+    font-size: 11px;
+    font-weight: 600;
+    text-transform: uppercase;
+    letter-spacing: 0.05em;
+    color: #9ca3af;
+}
+.dark .session-group-label { color: #525252; }
+.session-empty {
+    padding: 20px 12px;
+    text-align: center;
+    font-size: 13px;
+    color: #9ca3af;
+}
+.session-item {
+    display: flex;
+    align-items: center;
+    gap: 8px;
+    padding: 8px 10px;
+    margin: 1px 0;
+    border-radius: 8px;
+    cursor: pointer;
+    transition: background 0.15s, color 0.15s;
+    color: #6b7280;
+    font-size: 13px;
+    position: relative;
+}
+.dark .session-item { color: #a3a3a3; }
+.session-item:hover {
+    background: #f3f4f6;
+    color: #111827;
+}
+.dark .session-item:hover {
+    background: rgba(255, 255, 255, 0.05);
+    color: #e5e5e5;
+}
+.session-item.active {
+    background: #e5e7eb;
+    color: #111827;
+}
+.dark .session-item.active {
+    background: rgba(255, 255, 255, 0.1);
+    color: #ffffff;
+}
+.session-icon {
+    flex-shrink: 0;
+    font-size: 11px;
+    color: #9ca3af;
+    width: 16px;
+    text-align: center;
+}
+.dark .session-icon { color: #525252; }
+.session-item.active .session-icon { color: #4ABE6E; }
+.session-title {
+    flex: 1;
+    min-width: 0;
+    overflow: hidden;
+    text-overflow: ellipsis;
+    white-space: nowrap;
+}
+.session-delete {
+    flex-shrink: 0;
+    width: 22px;
+    height: 22px;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    border-radius: 5px;
+    font-size: 10px;
+    color: #9ca3af;
+    opacity: 0;
+    transition: opacity 0.15s, color 0.15s, background 0.15s;
+    cursor: pointer;
+    background: none;
+    border: none;
+    padding: 0;
+}
+.session-item:hover .session-delete { opacity: 1; }
+.session-delete:hover {
+    color: #ef4444;
+    background: rgba(239, 68, 68, 0.1);
+}
+.dark .session-delete:hover { background: rgba(239, 68, 68, 0.15); }
+
+/* Context Divider */
+.context-divider {
+    display: flex;
+    align-items: center;
+    gap: 12px;
+    padding: 12px 24px;
+    color: #9ca3af;
+}
+.context-divider::before, .context-divider::after {
+    content: '';
+    flex: 1;
+    height: 1px;
+    background: linear-gradient(to right, transparent, #d1d5db, transparent);
+}
+.dark .context-divider::before, .dark .context-divider::after {
+    background: linear-gradient(to right, transparent, rgba(255,255,255,0.12), transparent);
+}
+.context-divider span {
+    font-size: 12px;
+    white-space: nowrap;
+    color: #9ca3af;
+}
+
+/* Confirm Modal */
+.confirm-overlay {
+    position: fixed;
+    inset: 0;
+    z-index: 9999;
+    display: flex;
+    align-items: center;
+    justify-content: center;
+    background: rgba(0, 0, 0, 0.4);
+    opacity: 0;
+    transition: opacity 0.2s ease;
+}
+.confirm-overlay.visible { opacity: 1; }
+.confirm-modal {
+    background: #fff;
+    border-radius: 14px;
+    width: 380px;
+    max-width: 90vw;
+    padding: 28px 24px 20px;
+    box-shadow: 0 20px 60px rgba(0, 0, 0, 0.18);
+    transform: scale(0.92);
+    transition: transform 0.2s ease;
+}
+.confirm-overlay.visible .confirm-modal { transform: scale(1); }
+.dark .confirm-modal {
+    background: #1e1e1e;
+    box-shadow: 0 20px 60px rgba(0, 0, 0, 0.5);
+}
+.confirm-title {
+    font-size: 16px;
+    font-weight: 600;
+    color: #1f2937;
+    margin-bottom: 8px;
+}
+.dark .confirm-title { color: #e5e7eb; }
+.confirm-message {
+    font-size: 14px;
+    color: #6b7280;
+    line-height: 1.5;
+    margin-bottom: 24px;
+}
+.dark .confirm-message { color: #9ca3af; }
+.confirm-actions {
+    display: flex;
+    justify-content: flex-end;
+    gap: 10px;
+}
+.confirm-btn {
+    padding: 8px 20px;
+    border-radius: 8px;
+    font-size: 14px;
+    font-weight: 500;
+    cursor: pointer;
+    border: none;
+    transition: all 0.15s ease;
+}
+.confirm-btn-cancel {
+    background: #f3f4f6;
+    color: #374151;
+}
+.confirm-btn-cancel:hover { background: #e5e7eb; }
+.dark .confirm-btn-cancel {
+    background: rgba(255, 255, 255, 0.08);
+    color: #d1d5db;
+}
+.dark .confirm-btn-cancel:hover { background: rgba(255, 255, 255, 0.14); }
+.confirm-btn-ok {
+    background: #ef4444;
+    color: #fff;
+}
+.confirm-btn-ok:hover { background: #dc2626; }
+
+/* Mobile: session panel as overlay */
+@media (max-width: 768px) {
+    .session-panel {
+        position: fixed;
+        top: 0;
+        left: 0;
+        z-index: 45;
+        width: 220px;
+        box-shadow: 4px 0 24px rgba(0, 0, 0, 0.15);
+    }
+    .dark .session-panel {
+        box-shadow: 4px 0 24px rgba(0, 0, 0, 0.4);
+    }
+}
+
 /* Menu Groups */
 .menu-group-items { max-height: 0; overflow: hidden; transition: max-height 0.25s ease-out; }
-.menu-group.open .menu-group-items { max-height: 500px; transition: max-height 0.35s ease-in; }
+.menu-group.open .menu-group-items { max-height: 2000px; transition: max-height 0.35s ease-in; }
 .menu-group .chevron { transition: transform 0.25s ease; }
 .menu-group.open .chevron { transform: rotate(90deg); }

@@ -45,7 +375,8 @@
 .msg-content h1 { font-size: 1.4em; }
 .msg-content h2 { font-size: 1.25em; }
 .msg-content h3 { font-size: 1.1em; }
-.msg-content ul, .msg-content ol { margin: 0.5em 0; padding-left: 1.8em; }
+.msg-content ul { margin: 0.5em 0; padding-left: 1.8em; list-style: disc; }
+.msg-content ol { margin: 0.5em 0; padding-left: 1.8em; list-style: decimal; }
 .msg-content li { margin: 0.25em 0; }
 .msg-content pre {
    border-radius: 8px; overflow-x: auto; margin: 0.8em 0;
@@ -124,9 +455,8 @@
    cursor: pointer;
    user-select: none;
 }
-.agent-thinking-step .thinking-header.no-toggle { cursor: default; }
-.agent-thinking-step .thinking-header:not(.no-toggle):hover { color: #64748b; }
-.dark .agent-thinking-step .thinking-header:not(.no-toggle):hover { color: #cbd5e1; }
+.agent-thinking-step .thinking-header:hover { color: #64748b; }
+.dark .agent-thinking-step .thinking-header:hover { color: #cbd5e1; }
 .agent-thinking-step .thinking-header i:first-child { font-size: 0.625rem; margin-top: 1px; }
 .agent-thinking-step .thinking-chevron {
    font-size: 0.5rem;
@@ -146,7 +476,7 @@
    font-size: 0.75rem;
    line-height: 1.5;
    color: #94a3b8;
-    max-height: 200px;
+    max-height: 300px;
    overflow-y: auto;
 }
 .dark .agent-thinking-step .thinking-full {
@@ -157,6 +487,25 @@
 .agent-thinking-step .thinking-full p { margin: 0.25em 0; }
 .agent-thinking-step .thinking-full p:first-child { margin-top: 0; }
 .agent-thinking-step .thinking-full p:last-child { margin-bottom: 0; }
+.agent-thinking-step .thinking-duration {
+    font-size: 0.625rem;
+    color: #b0b8c4;
+    margin-bottom: 0.375rem;
+}
+
+/* Content step - real text output frozen before tool calls */
+.agent-content-step {
+    font-size: 0.875rem;
+    line-height: 1.6;
+    color: inherit;
+    margin-bottom: 0.5rem;
+    padding-bottom: 0.5rem;
+    border-bottom: 1px dashed rgba(0, 0, 0, 0.06);
+}
+.dark .agent-content-step { border-bottom-color: rgba(255, 255, 255, 0.06); }
+.agent-content-step .agent-content-body p { margin: 0.25em 0; }
+.agent-content-step .agent-content-body p:first-child { margin-top: 0; }
+.agent-content-step .agent-content-body p:last-child { margin-bottom: 0; }

 /* Tool step - collapsible */
 .agent-tool-step .tool-header {
@@ -535,3 +884,195 @@
 .dark .slash-menu-item .desc {
    color: #64748b;
 }
+
+/* ============================================================
+   Knowledge View
+   ============================================================ */
+
+/* Tab toggle */
+.knowledge-tab, .memory-tab {
+    color: #64748b;
+}
+.knowledge-tab.active, .memory-tab.active {
+    background: #fff;
+    color: #334155;
+    box-shadow: 0 1px 3px rgba(0,0,0,0.08);
+}
+.dark .knowledge-tab.active, .dark .memory-tab.active {
+    background: rgba(255,255,255,0.1);
+    color: #e2e8f0;
+}
+
+/* File tree */
+.knowledge-tree-group {
+    margin-bottom: 2px;
+}
+.knowledge-tree-group-btn {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    width: 100%;
+    padding: 6px 8px;
+    border-radius: 6px;
+    font-size: 12px;
+    font-weight: 600;
+    color: #64748b;
+    cursor: pointer;
+    border: none;
+    background: none;
+    transition: background 0.15s, color 0.15s;
+    text-transform: capitalize;
+}
+.knowledge-tree-group-btn:hover {
+    background: rgba(0,0,0,0.04);
+    color: #334155;
+}
+.dark .knowledge-tree-group-btn:hover {
+    background: rgba(255,255,255,0.06);
+    color: #e2e8f0;
+}
+.knowledge-tree-group-btn i.chevron {
+    font-size: 8px;
+    transition: transform 0.15s;
+}
+.knowledge-tree-group.open .chevron {
+    transform: rotate(90deg);
+}
+.knowledge-tree-group-items {
+    display: none;
+}
+.knowledge-tree-group.open .knowledge-tree-group-items {
+    display: block;
+}
+
+.knowledge-tree-file {
+    display: flex;
+    align-items: center;
+    gap: 6px;
+    padding: 5px 8px 5px 24px;
+    border-radius: 6px;
+    font-size: 12px;
+    color: #64748b;
+    cursor: pointer;
+    border: none;
+    background: none;
+    width: 100%;
+    text-align: left;
+    transition: background 0.15s, color 0.15s;
+    white-space: nowrap;
+    overflow: hidden;
+    text-overflow: ellipsis;
+}
+.knowledge-tree-file:hover {
+    background: rgba(0,0,0,0.04);
+    color: #334155;
+}
+.knowledge-tree-file.active {
+    background: #EDFDF3;
+    color: #228547;
+}
+.dark .knowledge-tree-file:hover {
+    background: rgba(255,255,255,0.06);
+    color: #e2e8f0;
+}
+.dark .knowledge-tree-file.active {
+    background: rgba(74, 190, 110, 0.1);
+    color: #4ABE6E;
+}
+
+/* Graph legend */
+.knowledge-graph-legend {
+    position: absolute;
+    top: 12px;
+    right: 12px;
+    display: flex;
+    flex-wrap: wrap;
+    gap: 8px;
+    font-size: 11px;
+    color: #64748b;
+    z-index: 10;
+}
+.knowledge-graph-legend-item {
+    display: flex;
+    align-items: center;
+    gap: 4px;
+}
+.knowledge-graph-legend-dot {
+    width: 8px;
+    height: 8px;
+    border-radius: 50%;
+}
+
+/* Graph tooltip */
+.knowledge-graph-tooltip {
+    position: absolute;
+    padding: 6px 10px;
+    background: #fff;
+    border: 1px solid #e2e8f0;
+    border-radius: 8px;
+    font-size: 12px;
+    color: #334155;
+    box-shadow: 0 4px 12px rgba(0,0,0,0.08);
+    pointer-events: none;
+    opacity: 0;
+    transition: opacity 0.15s;
+    z-index: 20;
+}
+.dark .knowledge-graph-tooltip {
+    background: #1A1A1A;
+    border-color: rgba(255,255,255,0.1);
+    color: #e2e8f0;
+}
+
+/* Config field tooltip */
+.cfg-tip {
+    position: relative;
+    display: inline-flex;
+    align-items: center;
+    color: #94a3b8;
+    cursor: help;
+    font-size: 12px;
+}
+.cfg-tip:hover { color: #64748b; }
+.dark .cfg-tip:hover { color: #cbd5e1; }
+.cfg-tip::after {
+    content: attr(data-tooltip);
+    position: absolute;
+    left: 50%;
+    bottom: calc(100% + 6px);
+    transform: translateX(-50%);
+    padding: 6px 10px;
+    border-radius: 8px;
+    font-size: 12px;
+    font-weight: 400;
+    line-height: 1.4;
+    white-space: nowrap;
+    background: #1e293b;
+    color: #e2e8f0;
+    box-shadow: 0 4px 12px rgba(0,0,0,0.15);
+    opacity: 0;
+    pointer-events: none;
+    transition: opacity 0.15s;
+    z-index: 50;
+}
+.dark .cfg-tip::after {
+    background: #334155;
+    color: #f1f5f9;
+}
+.cfg-tip:hover::after {
+    opacity: 1;
+}
+
+/* Example cards: equal height via flex stretch + fixed 2-line description area */
+.example-card {
+    display: flex;
+    flex-direction: column;
+}
+.example-card > p {
+    flex: 1;
+    display: -webkit-box;
+    -webkit-line-clamp: 2;
+    -webkit-box-orient: vertical;
+    overflow: hidden;
+    min-height: 2.5em;  /* ~2 lines at text-sm leading-relaxed */
+}
--- a/channel/web/static/js/console.js
+++ b/channel/web/static/js/console.js
--- a/channel/web/web_channel.py
+++ b/channel/web/web_channel.py
@@ -1,3 +1,5 @@
+import hashlib
+import hmac
 import time
 import json
 import logging
@@ -23,6 +25,62 @@ from config import conf
 IMAGE_EXTENSIONS = {".jpg", ".jpeg", ".png", ".gif", ".webp", ".bmp", ".svg"}
 VIDEO_EXTENSIONS = {".mp4", ".webm", ".avi", ".mov", ".mkv"}

+def _is_password_enabled():
+    return bool(conf().get("web_password", ""))
+
+
+def _session_expire_seconds():
+    return int(conf().get("web_session_expire_days", 30)) * 86400
+
+
+def _create_auth_token():
+    """Create a stateless signed token: ``<timestamp_hex>.<hmac_hex>``."""
+    ts = format(int(time.time()), "x")
+    sig = hmac.new(
+        conf().get("web_password", "").encode(),
+        ts.encode(),
+        hashlib.sha256,
+    ).hexdigest()
+    return f"{ts}.{sig}"
+
+
+def _verify_auth_token(token):
+    """Verify a signed token is valid and not expired.
+
+    The token is derived from the password, so it survives server restarts
+    and automatically invalidates when the password changes.
+    """
+    if not token or "." not in token:
+        return False
+    ts_hex, sig = token.split(".", 1)
+    try:
+        ts = int(ts_hex, 16)
+    except ValueError:
+        return False
+    if time.time() - ts > _session_expire_seconds():
+        return False
+    expected = hmac.new(
+        conf().get("web_password", "").encode(),
+        ts_hex.encode(),
+        hashlib.sha256,
+    ).hexdigest()
+    return hmac.compare_digest(sig, expected)
+
+
+def _check_auth():
+    """Return True if request is authenticated or password not enabled."""
+    if not _is_password_enabled():
+        return True
+    return _verify_auth_token(web.cookies().get("cow_auth_token", ""))
+
+
+def _require_auth():
+    """Raise 401 if not authenticated. Call at the top of protected handlers."""
+    if not _check_auth():
+        raise web.HTTPError("401 Unauthorized",
+                            {"Content-Type": "application/json; charset=utf-8"},
+                            json.dumps({"status": "error", "message": "Unauthorized"}))
+

 def _get_upload_dir() -> str:
    from common.utils import expand_path
@@ -32,6 +90,42 @@ def _get_upload_dir() -> str:
    return tmp_dir


+def _generate_session_title(user_message: str, assistant_reply: str = "") -> str:
+    """
+    Generate a short session title by calling the current bot's reply_text.
+    """
+    import re
+    fallback = user_message[:50].split("\n")[0].strip() or "New Chat"
+    try:
+        from bridge.bridge import Bridge
+        from models.session_manager import Session
+        bot = Bridge().get_bot("chat")
+
+        prompt_parts = [f"User: {user_message[:300]}"]
+        if assistant_reply:
+            prompt_parts.append(f"Assistant: {assistant_reply[:300]}")
+
+        session = Session("__title_gen__", system_prompt="")
+        session.messages = [
+            {"role": "user", "content": (
+                "Generate a very short title (max 15 characters for Chinese, max 6 words for English) "
+                "summarizing this conversation. Return ONLY the title text, nothing else.\n\n"
+                + "\n".join(prompt_parts)
+            )}
+        ]
+
+        result = bot.reply_text(session)
+        raw = (result.get("content") or "").strip()
+        # Strip <think>...</think> reasoning blocks
+        title = re.sub(r'<think>.*?</think>', '', raw, flags=re.DOTALL).strip().strip('"\'')
+        logger.info(f"[WebChannel] Title generation result: '{title}' (len={len(title)})")
+        if title and len(title) <= 50:
+            return title
+    except Exception as e:
+        logger.warning(f"[WebChannel] Title generation failed: {e}")
+    return fallback
+
+
 class WebMessage(ChatMessage):
    def __init__(
            self,
@@ -168,7 +262,12 @@ class WebChannel(ChatChannel):
            event_type = event.get("type")
            data = event.get("data", {})

-            if event_type == "message_update":
+            if event_type == "reasoning_update":
+                delta = data.get("delta", "")
+                if delta:
+                    q.put({"type": "reasoning", "content": delta})
+
+            elif event_type == "message_update":
                delta = data.get("delta", "")
                if delta:
                    q.put({"type": "delta", "content": delta})
@@ -195,6 +294,11 @@ class WebChannel(ChatChannel):
                    "execution_time": round(exec_time, 2)
                })

+            elif event_type == "message_end":
+                tool_calls = data.get("tool_calls", [])
+                if tool_calls:
+                    q.put({"type": "message_end", "has_tool_calls": True})
+
            elif event_type == "file_to_send":
                file_path = data.get("path", "")
                file_name = data.get("file_name", os.path.basename(file_path))
@@ -430,6 +534,9 @@ class WebChannel(ChatChannel):

        urls = (
            '/', 'RootHandler',
+            '/auth/login', 'AuthLoginHandler',
+            '/auth/check', 'AuthCheckHandler',
+            '/auth/logout', 'AuthLogoutHandler',
            '/message', 'MessageHandler',
            '/upload', 'UploadHandler',
            '/uploads/(.*)', 'UploadsHandler',
@@ -444,7 +551,14 @@ class WebChannel(ChatChannel):
            '/api/skills', 'SkillsHandler',
            '/api/memory', 'MemoryHandler',
            '/api/memory/content', 'MemoryContentHandler',
+            '/api/knowledge/list', 'KnowledgeListHandler',
+            '/api/knowledge/read', 'KnowledgeReadHandler',
+            '/api/knowledge/graph', 'KnowledgeGraphHandler',
            '/api/scheduler', 'SchedulerHandler',
+            '/api/sessions', 'SessionsHandler',
+            '/api/sessions/(.*)/generate_title', 'SessionTitleHandler',
+            '/api/sessions/(.*)/clear_context', 'SessionClearContextHandler',
+            '/api/sessions/(.*)', 'SessionDetailHandler',
            '/api/history', 'HistoryHandler',
            '/api/logs', 'LogsHandler',
            '/api/version', 'VersionHandler',
@@ -489,24 +603,62 @@ class WebChannel(ChatChannel):

 class RootHandler:
    def GET(self):
-        # 重定向到/chat
        raise web.seeother('/chat')


+class AuthCheckHandler:
+    def GET(self):
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        if not _is_password_enabled():
+            return json.dumps({"status": "success", "auth_required": False})
+        if _check_auth():
+            return json.dumps({"status": "success", "auth_required": True, "authenticated": True})
+        return json.dumps({"status": "success", "auth_required": True, "authenticated": False})
+
+
+class AuthLoginHandler:
+    def POST(self):
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        if not _is_password_enabled():
+            return json.dumps({"status": "success"})
+        try:
+            data = json.loads(web.data())
+        except Exception:
+            return json.dumps({"status": "error", "message": "Invalid request"})
+        password = data.get("password", "")
+        expected = conf().get("web_password", "")
+        if not hmac.compare_digest(password, expected):
+            logger.warning("[WebChannel] Invalid login attempt")
+            return json.dumps({"status": "error", "message": "Wrong password"})
+        token = _create_auth_token()
+        web.setcookie("cow_auth_token", token, expires=_session_expire_seconds(),
+                       path="/", httponly=True, samesite="Lax")
+        return json.dumps({"status": "success"})
+
+
+class AuthLogoutHandler:
+    def POST(self):
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        web.setcookie("cow_auth_token", "", expires=-1, path="/")
+        return json.dumps({"status": "success"})
+
+
 class MessageHandler:
    def POST(self):
+        _require_auth()
        return WebChannel().post_message()


 class UploadHandler:
    def POST(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        return WebChannel().upload_file()


 class UploadsHandler:
    def GET(self, file_name):
-        """Serve uploaded files from workspace/tmp/ for preview."""
+        _require_auth()
        try:
            upload_dir = _get_upload_dir()
            full_path = os.path.normpath(os.path.join(upload_dir, file_name))
@@ -528,7 +680,7 @@ class UploadsHandler:

 class FileServeHandler:
    def GET(self):
-        """Serve a local file by absolute path (for agent send tool)."""
+        _require_auth()
        try:
            params = web.input(path="")
            file_path = params.path
@@ -554,11 +706,13 @@ class FileServeHandler:

 class PollHandler:
    def POST(self):
+        _require_auth()
        return WebChannel().poll_response()


 class StreamHandler:
    def GET(self):
+        _require_auth()
        params = web.input(request_id='')
        request_id = params.request_id
        if not request_id:
@@ -574,10 +728,15 @@ class StreamHandler:

 class ChatHandler:
    def GET(self):
-        # 正常返回聊天页面
+        web.header('Cache-Control', 'no-cache, no-store, must-revalidate')
+        web.header('Pragma', 'no-cache')
        file_path = os.path.join(os.path.dirname(__file__), 'chat.html')
        with open(file_path, 'r', encoding='utf-8') as f:
-            return f.read()
+            html = f.read()
+        cache_bust = str(int(time.time()))
+        html = html.replace('assets/js/console.js', f'assets/js/console.js?v={cache_bust}')
+        html = html.replace('assets/css/console.css', f'assets/css/console.css?v={cache_bust}')
+        return html


 class ConfigHandler:
@@ -600,7 +759,7 @@ class ConfigHandler:
            "api_key_field": "minimax_api_key",
            "api_base_key": None,
            "api_base_default": None,
-            "models": [const.MINIMAX_M2_7, const.MINIMAX_M2_5, const.MINIMAX_M2_1, const.MINIMAX_M2_1_LIGHTNING],
+            "models": [const.MINIMAX_M2_7, const.MINIMAX_M2_7_HIGHSPEED, const.MINIMAX_M2_5, const.MINIMAX_M2_1, const.MINIMAX_M2_1_LIGHTNING],
        }),
        ("zhipu", {
            "label": "智谱AI",
@@ -682,6 +841,7 @@ class ConfigHandler:
        "zhipu_ai_api_key", "dashscope_api_key", "moonshot_api_key",
        "ark_api_key", "minimax_api_key", "linkai_api_key",
        "agent_max_context_tokens", "agent_max_context_turns", "agent_max_steps",
+        "enable_thinking", "web_password",
    }

    @staticmethod
@@ -692,7 +852,7 @@ class ConfigHandler:
        return value[:4] + "*" * (len(value) - 8) + value[-4:]

    def GET(self):
-        """Return configuration info and provider/model metadata."""
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            local_config = conf()
@@ -720,6 +880,9 @@ class ConfigHandler:
                    "api_key_field": p.get("api_key_field"),
                }

+            raw_pwd = local_config.get("web_password", "")
+            masked_pwd = ("*" * len(raw_pwd)) if raw_pwd else ""
+
            return json.dumps({
                "status": "success",
                "use_agent": use_agent,
@@ -730,17 +893,19 @@ class ConfigHandler:
                "channel_type": local_config.get("channel_type", ""),
                "agent_max_context_tokens": local_config.get("agent_max_context_tokens", 50000),
                "agent_max_context_turns": local_config.get("agent_max_context_turns", 20),
-                "agent_max_steps": local_config.get("agent_max_steps", 15),
+                "agent_max_steps": local_config.get("agent_max_steps", 20),
+                "enable_thinking": bool(local_config.get("enable_thinking", True)),
                "api_bases": api_bases,
                "api_keys": api_keys_masked,
                "providers": providers,
+                "web_password_masked": masked_pwd,
            }, ensure_ascii=False)
        except Exception as e:
            logger.error(f"Error getting config: {e}")
            return json.dumps({"status": "error", "message": str(e)})

    def POST(self):
-        """Update configuration values in memory and persist to config.json."""
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            data = json.loads(web.data())
@@ -755,7 +920,7 @@ class ConfigHandler:
                    continue
                if key in ("agent_max_context_tokens", "agent_max_context_turns", "agent_max_steps"):
                    value = int(value)
-                if key == "use_linkai":
+                if key in ("use_linkai", "enable_thinking"):
                    value = bool(value)
                local_config[key] = value
                applied[key] = value
@@ -889,6 +1054,7 @@ class ChannelsHandler:
        return set(cls._parse_channel_list(conf().get("channel_type", "")))

    def GET(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            local_config = conf()
@@ -926,6 +1092,7 @@ class ChannelsHandler:
            return json.dumps({"status": "error", "message": str(e)})

    def POST(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            body = json.loads(web.data())
@@ -1179,6 +1346,7 @@ class WeixinQrHandler:
        return None

    def GET(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            running_ch = self._get_running_channel()
@@ -1211,6 +1379,7 @@ class WeixinQrHandler:
            return json.dumps({"status": "error", "message": str(e)})

    def POST(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            body = json.loads(web.data())
@@ -1298,6 +1467,7 @@ def _get_workspace_root():

 class ToolsHandler:
    def GET(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            from agent.tools.tool_manager import ToolManager
@@ -1322,6 +1492,7 @@ class ToolsHandler:

 class SkillsHandler:
    def GET(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            from agent.skills.service import SkillService
@@ -1336,6 +1507,7 @@ class SkillsHandler:
            return json.dumps({"status": "error", "message": str(e)})

    def POST(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            from agent.skills.service import SkillService
@@ -1362,13 +1534,17 @@ class SkillsHandler:

 class MemoryHandler:
    def GET(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            from agent.memory.service import MemoryService
-            params = web.input(page='1', page_size='20')
+            params = web.input(page='1', page_size='20', category='memory')
            workspace_root = _get_workspace_root()
            service = MemoryService(workspace_root)
-            result = service.list_files(page=int(params.page), page_size=int(params.page_size))
+            result = service.list_files(
+                page=int(params.page), page_size=int(params.page_size),
+                category=params.category,
+            )
            return json.dumps({"status": "success", **result}, ensure_ascii=False)
        except Exception as e:
            logger.error(f"[WebChannel] Memory API error: {e}")
@@ -1377,15 +1553,16 @@ class MemoryHandler:

 class MemoryContentHandler:
    def GET(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            from agent.memory.service import MemoryService
-            params = web.input(filename='')
+            params = web.input(filename='', category='memory')
            if not params.filename:
                return json.dumps({"status": "error", "message": "filename required"})
            workspace_root = _get_workspace_root()
            service = MemoryService(workspace_root)
-            result = service.get_content(params.filename)
+            result = service.get_content(params.filename, category=params.category)
            return json.dumps({"status": "success", **result}, ensure_ascii=False)
        except ValueError:
            return json.dumps({"status": "error", "message": "invalid filename"})
@@ -1398,6 +1575,7 @@ class MemoryContentHandler:

 class SchedulerHandler:
    def GET(self):
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        try:
            from agent.tools.scheduler.task_store import TaskStore
@@ -1411,16 +1589,138 @@ class SchedulerHandler:
            return json.dumps({"status": "error", "message": str(e)})


+class SessionsHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            params = web.input(page='1', page_size='50')
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            result = store.list_sessions(
+                channel_type="web",
+                page=int(params.page),
+                page_size=int(params.page_size),
+            )
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Sessions API error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SessionDetailHandler:
+    def DELETE(self, session_id: str):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        logger.info(f"[WebChannel] DELETE session request: {session_id}")
+        try:
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            store.clear_session(session_id)
+
+            # Also remove the Agent instance from AgentBridge if exists
+            try:
+                from bridge.bridge import Bridge
+                ab = Bridge().get_agent_bridge()
+                if session_id in ab.agents:
+                    del ab.agents[session_id]
+                    logger.info(f"[WebChannel] Removed agent instance for session {session_id}")
+            except Exception:
+                pass
+
+            channel = WebChannel()
+            channel.session_queues.pop(session_id, None)
+
+            logger.info(f"[WebChannel] Session deleted: {session_id}")
+            return json.dumps({"status": "success"})
+        except Exception as e:
+            logger.error(f"[WebChannel] Session delete error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+    def PUT(self, session_id: str):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+            body = json.loads(web.data())
+            title = body.get("title", "").strip()
+            if not title:
+                return json.dumps({"status": "error", "message": "title required"})
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            found = store.rename_session(session_id, title)
+            if not found:
+                return json.dumps({"status": "error", "message": "session not found"})
+            return json.dumps({"status": "success"})
+        except Exception as e:
+            logger.error(f"[WebChannel] Session rename error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SessionTitleHandler:
+    def POST(self, session_id: str):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+
+            body = json.loads(web.data())
+            user_message = body.get("user_message", "")
+            assistant_reply = body.get("assistant_reply", "")
+            if not user_message:
+                return json.dumps({"status": "error", "message": "user_message required"})
+
+            title = _generate_session_title(user_message, assistant_reply)
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            updated = store.rename_session(session_id, title)
+            logger.info(f"[WebChannel] Session title set: sid={session_id}, title='{title}', db_updated={updated}")
+
+            return json.dumps({"status": "success", "title": title}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Title generation error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class SessionClearContextHandler:
+    def POST(self, session_id: str):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            if not session_id:
+                return json.dumps({"status": "error", "message": "session_id required"})
+
+            from agent.memory import get_conversation_store
+            store = get_conversation_store()
+            new_seq = store.clear_context(session_id)
+
+            # Delete the agent instance so a fresh one is created on the next message
+            try:
+                from bridge.bridge import Bridge
+                bridge = Bridge()
+                ab = bridge.get_agent_bridge()
+                if session_id in ab.agents:
+                    del ab.agents[session_id]
+                    logger.info(f"[WebChannel] Cleared agent instance for session {session_id}")
+            except Exception:
+                pass
+
+            return json.dumps({"status": "success", "context_start_seq": new_seq})
+        except Exception as e:
+            logger.error(f"[WebChannel] Clear context error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
 class HistoryHandler:
    def GET(self):
-        """
-        Return paginated conversation history for a session.
-
-        Query params:
-            session_id  (required)
-            page        int, default 1  (1 = most recent messages)
-            page_size   int, default 20
-        """
+        _require_auth()
        web.header('Content-Type', 'application/json; charset=utf-8')
        web.header('Access-Control-Allow-Origin', '*')
        try:
@@ -1444,7 +1744,7 @@ class HistoryHandler:

 class LogsHandler:
    def GET(self):
-        """Stream the last N lines of run.log as SSE, then tail new lines."""
+        _require_auth()
        web.header('Content-Type', 'text/event-stream; charset=utf-8')
        web.header('Cache-Control', 'no-cache')
        web.header('X-Accel-Buffering', 'no')
@@ -1530,6 +1830,50 @@ class AssetsHandler:
            raise web.notfound()


+class KnowledgeListHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.knowledge.service import KnowledgeService
+            svc = KnowledgeService(_get_workspace_root())
+            result = svc.list_tree()
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Knowledge list error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class KnowledgeReadHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.knowledge.service import KnowledgeService
+            params = web.input(path='')
+            svc = KnowledgeService(_get_workspace_root())
+            result = svc.read_file(params.path)
+            return json.dumps({"status": "success", **result}, ensure_ascii=False)
+        except (ValueError, FileNotFoundError) as e:
+            return json.dumps({"status": "error", "message": str(e)})
+        except Exception as e:
+            logger.error(f"[WebChannel] Knowledge read error: {e}")
+            return json.dumps({"status": "error", "message": str(e)})
+
+
+class KnowledgeGraphHandler:
+    def GET(self):
+        _require_auth()
+        web.header('Content-Type', 'application/json; charset=utf-8')
+        try:
+            from agent.knowledge.service import KnowledgeService
+            svc = KnowledgeService(_get_workspace_root())
+            return json.dumps(svc.build_graph(), ensure_ascii=False)
+        except Exception as e:
+            logger.error(f"[WebChannel] Knowledge graph error: {e}")
+            return json.dumps({"nodes": [], "links": []})
+
+
 class VersionHandler:
    def GET(self):
        web.header('Content-Type', 'application/json; charset=utf-8')
--- a/cli/VERSION
+++ b/cli/VERSION
@@ -1 +1 @@
-2.0.5
+2.0.6
--- a/cli/cli.py
+++ b/cli/cli.py
@@ -6,6 +6,7 @@ from cli.commands.skill import skill
 from cli.commands.process import start, stop, restart, update, status, logs
 from cli.commands.context import context
 from cli.commands.install import install_browser
+from cli.commands.knowledge import knowledge


 HELP_TEXT = """Usage: cow COMMAND [ARGS]...
@@ -22,6 +23,7 @@ Commands:
  status   Show CowAgent running status.
  logs     View CowAgent logs.
  skill    Manage CowAgent skills.
+  knowledge  Manage knowledge base.
  install-browser  Install browser tool (Playwright + Chromium).

 Tip: You can also send /help, /skill list, etc. in agent chat."""
@@ -69,6 +71,7 @@ main.add_command(update)
 main.add_command(status)
 main.add_command(logs)
 main.add_command(context)
+main.add_command(knowledge)
 main.add_command(install_browser)


--- a/cli/commands/knowledge.py
+++ b/cli/commands/knowledge.py
@@ -0,0 +1,121 @@
+"""cow knowledge - Knowledge base management commands."""
+
+import os
+
+import click
+
+from cli.utils import get_project_root
+
+
+def _get_knowledge_dir():
+    """Resolve the knowledge directory path from config or default."""
+    try:
+        import sys
+        sys.path.insert(0, get_project_root())
+        from config import conf
+        from common.utils import expand_path
+        workspace = expand_path(conf().get("agent_workspace", "~/cow"))
+    except Exception:
+        workspace = os.path.expanduser("~/cow")
+    return os.path.join(workspace, "knowledge")
+
+
+def _get_knowledge_enabled():
+    try:
+        import sys
+        sys.path.insert(0, get_project_root())
+        from config import conf
+        return conf().get("knowledge", True)
+    except Exception:
+        return True
+
+
+@click.group(invoke_without_command=True)
+@click.pass_context
+def knowledge(ctx):
+    """Manage CowAgent knowledge base."""
+    if ctx.invoked_subcommand is None:
+        click.echo(_stats())
+
+
+@knowledge.command("list")
+def knowledge_list():
+    """Display knowledge base file tree."""
+    click.echo(_tree())
+
+
+def _stats() -> str:
+    knowledge_dir = _get_knowledge_dir()
+    if not os.path.isdir(knowledge_dir):
+        return "Knowledge base directory not found."
+
+    enabled = _get_knowledge_enabled()
+    total_files = 0
+    total_bytes = 0
+    cat_count = {}
+
+    for root, dirs, files in os.walk(knowledge_dir):
+        dirs[:] = [d for d in dirs if not d.startswith(".")]
+        rel_root = os.path.relpath(root, knowledge_dir)
+        category = rel_root.split(os.sep)[0] if rel_root != "." else "root"
+        for f in files:
+            if f.endswith(".md") and f not in ("index.md", "log.md"):
+                total_files += 1
+                total_bytes += os.path.getsize(os.path.join(root, f))
+                cat_count[category] = cat_count.get(category, 0) + 1
+
+    status_icon = click.style("enabled", fg="green") if enabled else click.style("disabled", fg="red")
+    lines = [
+        f"\n  Knowledge Base  [{status_icon}]",
+        "",
+        f"  Pages:  {total_files}",
+        f"  Size:   {total_bytes / 1024:.1f} KB",
+        "",
+    ]
+    if cat_count:
+        lines.append("  Categories:")
+        for cat in sorted(cat_count.keys()):
+            lines.append(f"    {cat}/  ({cat_count[cat]} pages)")
+        lines.append("")
+
+    lines.append(f"  Path: {knowledge_dir}")
+    lines.append("")
+    return "\n".join(lines)
+
+
+def _tree() -> str:
+    knowledge_dir = _get_knowledge_dir()
+    if not os.path.isdir(knowledge_dir):
+        return "Knowledge base directory not found."
+
+    tree_lines = ["  knowledge/"]
+
+    subdirs = sorted([
+        d for d in os.listdir(knowledge_dir)
+        if os.path.isdir(os.path.join(knowledge_dir, d)) and not d.startswith(".")
+    ])
+
+    for i, subdir in enumerate(subdirs):
+        is_last_dir = (i == len(subdirs) - 1)
+        branch = "└── " if is_last_dir else "├── "
+        subdir_path = os.path.join(knowledge_dir, subdir)
+        md_files = sorted([
+            f for f in os.listdir(subdir_path)
+            if f.endswith(".md") and not f.startswith(".")
+        ])
+        tree_lines.append(f"  {branch}{subdir}/ ({len(md_files)})")
+
+        child_prefix = "      " if is_last_dir else "  │   "
+        max_show = 15
+        for j, fname in enumerate(md_files[:max_show]):
+            is_last_file = (j == len(md_files[:max_show]) - 1) and len(md_files) <= max_show
+            fb = "└── " if is_last_file else "├── "
+            name = fname.replace(".md", "")
+            tree_lines.append(f"{child_prefix}{fb}{name}")
+        if len(md_files) > max_show:
+            tree_lines.append(f"{child_prefix}└── ... +{len(md_files) - max_show} more")
+
+    if not subdirs:
+        tree_lines.append("  (empty)")
+
+    return "\n" + "\n".join(tree_lines) + "\n"
--- a/common/cloud_client.py
+++ b/common/cloud_client.py
@@ -54,6 +54,7 @@ class CloudClient(LinkAIClient):
        self.channel_mgr = None
        self._skill_service = None
        self._memory_service = None
+        self._knowledge_service = None
        self._chat_service = None

    @property
@@ -88,6 +89,21 @@ class CloudClient(LinkAIClient):
                logger.error(f"[CloudClient] Failed to init MemoryService: {e}")
        return self._memory_service

+    @property
+    def knowledge_service(self):
+        """Lazy-init KnowledgeService."""
+        if self._knowledge_service is None:
+            try:
+                from agent.knowledge.service import KnowledgeService
+                from config import conf
+                from common.utils import expand_path
+                workspace_root = expand_path(conf().get("agent_workspace", "~/cow"))
+                self._knowledge_service = KnowledgeService(workspace_root)
+                logger.debug("[CloudClient] KnowledgeService initialised")
+            except Exception as e:
+                logger.error(f"[CloudClient] Failed to init KnowledgeService: {e}")
+        return self._knowledge_service
+
    @property
    def chat_service(self):
        """Lazy-init ChatService (requires AgentBridge via Bridge singleton)."""
@@ -468,6 +484,27 @@ class CloudClient(LinkAIClient):

        return svc.dispatch(action, payload)

+    # ------------------------------------------------------------------
+    # knowledge callback
+    # ------------------------------------------------------------------
+    def on_knowledge(self, data: dict) -> dict:
+        """
+        Handle KNOWLEDGE messages from the cloud console.
+        Delegates to KnowledgeService.dispatch for the actual operations.
+
+        :param data: message data with 'action', 'clientId', 'payload'
+        :return: response dict
+        """
+        action = data.get("action", "")
+        payload = data.get("payload")
+        logger.info(f"[CloudClient] on_knowledge: action={action}")
+
+        svc = self.knowledge_service
+        if svc is None:
+            return {"action": action, "code": 500, "message": "KnowledgeService not available", "payload": None}
+
+        return svc.dispatch(action, payload)
+
    # ------------------------------------------------------------------
    # chat callback
    # ------------------------------------------------------------------
--- a/common/const.py
+++ b/common/const.py
@@ -93,6 +93,7 @@ QWQ_PLUS = "qwq-plus"

 # MiniMax
 MINIMAX_M2_7 = "MiniMax-M2.7"  # MiniMax M2.7 - Latest
+MINIMAX_M2_7_HIGHSPEED = "MiniMax-M2.7-highspeed"  # MiniMax M2.7 highspeed
 MINIMAX_M2_5 = "MiniMax-M2.5"  # MiniMax M2.5
 MINIMAX_M2_1 = "MiniMax-M2.1"  # MiniMax M2.1
 MINIMAX_M2_1_LIGHTNING = "MiniMax-M2.1-lightning"  # MiniMax M2.1 极速版
@@ -175,7 +176,7 @@ MODEL_LIST = [
              QWEN36_PLUS, QWEN35_PLUS, QWEN3_MAX, QWEN_MAX, QWEN_PLUS, QWEN_TURBO, QWEN_LONG,
              
              # MiniMax
-              MiniMax, MINIMAX_M2_7, MINIMAX_M2_5, MINIMAX_M2_1, MINIMAX_M2_1_LIGHTNING, MINIMAX_M2, MINIMAX_ABAB6_5,
+              MiniMax, MINIMAX_M2_7, MINIMAX_M2_7_HIGHSPEED, MINIMAX_M2_5, MINIMAX_M2_1, MINIMAX_M2_1_LIGHTNING, MINIMAX_M2, MINIMAX_ABAB6_5,

              # GLM
              ZHIPU_AI, GLM_5_TURBO, GLM_5, GLM_4, GLM_4_PLUS, GLM_4_flash, GLM_4_LONG, GLM_4_ALLTOOLS,
--- a/config-template.json
+++ b/config-template.json
@@ -26,8 +26,10 @@
  "dingtalk_client_secret":"",
  "wecom_bot_id": "",
  "wecom_bot_secret": "",
+  "web_password": "",
  "agent": true,
-  "agent_max_context_tokens": 40000,
+  "agent_max_context_tokens": 50000,
  "agent_max_context_turns": 20,
-  "agent_max_steps": 15
+  "agent_max_steps": 20,
+  "knowledge": true
 }
--- a/config.py
+++ b/config.py
@@ -180,14 +180,14 @@ available_setting = {
    # 豆包(火山方舟) 平台配置
    "ark_api_key": "",
    "ark_base_url": "https://ark.cn-beijing.volces.com/api/v3",
-    #魔搭社区 平台配置
+    # 魔搭社区 平台配置
    "modelscope_api_key": "",
    "modelscope_base_url": "https://api-inference.modelscope.cn/v1/chat/completions",
    # LinkAI平台配置
    "use_linkai": False,
    "linkai_api_key": "",
    "linkai_app_code": "",
-    "linkai_api_base": "https://api.link-ai.tech",  # linkAI服务地址
+    "linkai_api_base": "https://api.link-ai.tech",
    "cloud_host": "client.link-ai.tech",
    "cloud_port": None,
    "cloud_deployment_id": "",
@@ -195,11 +195,15 @@ available_setting = {
    "Minimax_group_id": "",
    "Minimax_base_url": "",
    "web_port": 9899,
+    "web_password": "",  # Web console password; empty means no authentication required
+    "web_session_expire_days": 30,  # Auth session expiry in days
    "agent": True,  # 是否开启Agent模式
    "agent_workspace": "~/cow",  # agent工作空间路径，用于存储skills、memory等
    "agent_max_context_tokens": 50000,  # Agent模式下最大上下文tokens
-    "agent_max_context_turns": 30,  # Agent模式下最大上下文记忆轮次
-    "agent_max_steps": 15,  # Agent模式下单次运行最大决策步数
+    "agent_max_context_turns": 20,  # Agent模式下最大上下文记忆轮次
+    "agent_max_steps": 20,  # Agent模式下单次运行最大决策步数
+    "enable_thinking": True,  # Whether to enable deep thinking for web channel
+    "knowledge": True,  # 是否开启知识库功能
 }


--- a/docker/docker-compose.yml
+++ b/docker/docker-compose.yml
@@ -35,9 +35,10 @@ services:
      DINGTALK_CLIENT_SECRET: ''
      WECOM_BOT_ID: ''
      WECOM_BOT_SECRET: ''
+      WEB_PASSWORD: ''
      AGENT: 'True'
-      AGENT_MAX_CONTEXT_TOKENS: 40000
+      AGENT_MAX_CONTEXT_TOKENS: 50000
      AGENT_MAX_CONTEXT_TURNS: 20
-      AGENT_MAX_STEPS: 15
+      AGENT_MAX_STEPS: 20
    volumes:
      - ./cow:/home/agent/cow
--- a/docs/channels/web.mdx
+++ b/docs/channels/web.mdx
@@ -10,7 +10,9 @@ Web 控制台是 CowAgent 的默认通道，启动后会自动运行，通过浏
 ```json
 {
  "channel_type": "web",
-  "web_port": 9899
+  "web_port": 9899,
+  "web_password": "",
+  "enable_thinking": true
 }
 ```

@@ -18,6 +20,11 @@ Web 控制台是 CowAgent 的默认通道，启动后会自动运行，通过浏
 | --- | --- | --- |
 | `channel_type` | 设为 `web` | `web` |
 | `web_port` | Web 服务监听端口 | `9899` |
+| `web_password` | 访问密码，留空表示不启用密码保护 | `""` |
+| `web_session_expire_days` | 登录会话有效天数 | `30` |
+| `enable_thinking` | 是否启用深度思考，开启后 Web 端展示推理过程，关闭可加速响应 | `true` |
+
+配置密码后，访问控制台时需先输入密码完成登录。登录状态默认保持 30 天，期间重启服务也无需重新登录。密码也支持在控制台的「配置」页面中在线修改。

 ## 访问地址

@@ -34,10 +41,20 @@ Web 控制台是 CowAgent 的默认通道，启动后会自动运行，通过浏

 ### 对话界面

-支持流式输出，可实时展示 Agent 的思考过程（Reasoning）和工具调用过程（Tool Calls），更直观地观察 Agent 的决策过程：
+支持流式输出，可实时展示 Agent 的思考过程（Reasoning）和工具调用过程（Tool Calls），更直观地观察 Agent 的决策过程。深度思考功能可通过配置或控制台的「Agent 配置」开关控制。

 <img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />

+#### 多会话管理
+
+对话界面支持多会话（Session）管理，所有会话记录持久化存储在数据库中：
+
+- **会话列表**：点击左侧历史会话图标可展开/收起会话列表面板，支持滚动加载全部历史会话
+- **AI 生成标题**：新会话在首轮对话完成后，自动调用模型生成简短的会话摘要标题
+- **新建会话**：点击会话列表顶部的「新对话」按钮或输入区的 `+` 按钮创建新会话
+- **删除会话**：点击会话项的删除按钮，确认后永久删除该会话及其所有消息
+- **清除上下文**：点击输入区的清除按钮，在当前会话中插入一条分隔线，分隔线以上的消息仍然展示但不再作为模型的上下文输入
+
 ### 模型管理

 支持在线管理模型配置，无需手动编辑配置文件：
--- a/docs/cli/index.mdx
+++ b/docs/cli/index.mdx
@@ -40,6 +40,10 @@ Service:
 Skills:
  skill     Manage skills (list / search / install / uninstall ...)

+Memory & Knowledge:
+  memory    Memory distillation (dream)
+  knowledge View knowledge base stats and structure
+
 Others:
  help      Show this help message
  version   Show version
@@ -55,6 +59,10 @@ Others:
 | `/status` | 查看服务状态和配置 |
 | `/config` | 查看或修改运行时配置 |
 | `/skill` | 管理技能（安装、卸载、启用、禁用等） |
+| `/memory dream [N]` | 手动触发记忆蒸馏（默认 3 天，最大 30） |
+| `/knowledge` | 查看知识库统计信息 |
+| `/knowledge list` | 查看知识库目录结构 |
+| `/knowledge on\|off` | 开启或关闭知识库 |
 | `/context` | 查看当前会话上下文信息 |
 | `/context clear` | 清空当前会话上下文 |
 | `/logs` | 查看最近日志 |
@@ -76,6 +84,8 @@ Others:
 | logs | ✓ | ✓ |
 | config | ✗ | ✓ |
 | context | — | ✓ |
+| memory (子命令) | ✗ | ✓ |
+| knowledge (子命令) | ✓ | ✓ |
 | skill (子命令) | ✓ | ✓ |
 | start / stop / restart | ✓ | ✗ |
 | update | ✓ | ✗ |
--- a/docs/cli/memory-knowledge.mdx
+++ b/docs/cli/memory-knowledge.mdx
@@ -0,0 +1,77 @@
+---
+title: 记忆与知识库
+description: 记忆蒸馏和知识库管理命令
+---
+
+## memory
+
+管理 Agent 的长期记忆系统。
+
+### memory dream
+
+手动触发记忆蒸馏（Deep Dream），整理近期的天级记忆，蒸馏合并到 MEMORY.md，并生成梦境日记。
+
+```text
+/memory dream [N]
+```
+
+- `N`：整理近 N 天的记忆，默认 3 天，最大 30 天
+- 蒸馏在后台异步执行，完成后会在对话中通知结果
+- 无需等待 Agent 初始化，首次对话前即可使用
+
+**示例：**
+
+```text
+/memory dream       # 整理近 3 天
+/memory dream 7     # 整理近 7 天
+/memory dream 30    # 整理近 30 天（全量）
+```
+
+蒸馏完成后，Web 端会收到带有跳转链接的通知，可直接查看更新后的 MEMORY.md 和梦境日记。
+
+<Tip>
+  系统每天 23:55 会自动执行一次蒸馏（lookback 1 天）。手动触发适用于首次部署后的历史整理，或需要立即更新记忆时使用。
+</Tip>
+
+## knowledge
+
+查看和管理个人知识库。默认显示知识库统计信息。
+
+```text
+/knowledge
+```
+
+输出示例：
+
+```
+📚 知识库
+
+- 状态：已开启
+- 页面数：12
+- 总大小：45.2 KB
+- 分类明细：
+  - concepts/: 5 篇
+  - entities/: 4 篇
+  - sources/: 3 篇
+```
+
+### knowledge list
+
+查看知识库目录树结构。
+
+```text
+/knowledge list
+```
+
+### knowledge on / off
+
+开启或关闭知识库。关闭后不再注入知识提示词和索引知识文件。
+
+```text
+/knowledge on
+/knowledge off
+```
+
+<Note>
+  终端 CLI 中 `cow knowledge` 和 `cow knowledge list` 可用，但 `on|off` 仅支持在对话中使用（需实时生效）。
+</Note>
--- a/docs/docs.json
+++ b/docs/docs.json
@@ -24,13 +24,13 @@
      },
      {
        "label": "GitHub",
-        "href": "https://github.com/zhayujie/chatgpt-on-wechat"
+        "href": "https://github.com/zhayujie/CowAgent"
      }
    ]
  },
  "footer": {
    "socials": {
-      "github": "https://github.com/zhayujie/chatgpt-on-wechat"
+      "github": "https://github.com/zhayujie/CowAgent"
    }
  },
  "navigation": {
@@ -142,7 +142,19 @@
                "group": "记忆系统",
                "pages": [
                  "memory/index",
-                  "memory/context"
+                  "memory/context",
+                  "memory/deep-dream"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "知识",
+            "groups": [
+              {
+                "group": "知识库",
+                "pages": [
+                  "knowledge/index"
                ]
              }
            ]
@@ -174,6 +186,7 @@
                  "cli/index",
                  "cli/process",
                  "cli/skill",
+                  "cli/memory-knowledge",
                  "cli/general"
                ]
              }
@@ -186,6 +199,7 @@
                "group": "发布记录",
                "pages": [
                  "releases/overview",
+                  "releases/v2.0.6",
                  "releases/v2.0.5",
                  "releases/v2.0.4",
                  "releases/v2.0.3",
@@ -303,7 +317,19 @@
                "group": "Memory System",
                "pages": [
                  "en/memory/index",
-                  "en/memory/context"
+                  "en/memory/context",
+                  "en/memory/deep-dream"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "Knowledge",
+            "groups": [
+              {
+                "group": "Knowledge Base",
+                "pages": [
+                  "en/knowledge/index"
                ]
              }
            ]
@@ -335,6 +361,7 @@
                  "en/cli/index",
                  "en/cli/process",
                  "en/cli/skill",
+                  "en/cli/memory-knowledge",
                  "en/cli/chat"
                ]
              }
@@ -347,6 +374,7 @@
                "group": "Release Notes",
                "pages": [
                  "en/releases/overview",
+                  "en/releases/v2.0.6",
                  "en/releases/v2.0.5",
                  "en/releases/v2.0.4",
                  "en/releases/v2.0.2",
@@ -464,7 +492,19 @@
                "group": "メモリシステム",
                "pages": [
                  "ja/memory/index",
-                  "ja/memory/context"
+                  "ja/memory/context",
+                  "ja/memory/deep-dream"
+                ]
+              }
+            ]
+          },
+          {
+            "tab": "ナレッジ",
+            "groups": [
+              {
+                "group": "ナレッジベース",
+                "pages": [
+                  "ja/knowledge/index"
                ]
              }
            ]
@@ -496,6 +536,7 @@
                  "ja/cli/index",
                  "ja/cli/process",
                  "ja/cli/skill",
+                  "ja/cli/memory-knowledge",
                  "ja/cli/general"
                ]
              }
@@ -508,6 +549,7 @@
                "group": "リリースノート",
                "pages": [
                  "ja/releases/overview",
+                  "ja/releases/v2.0.6",
                  "ja/releases/v2.0.5",
                  "ja/releases/v2.0.4",
                  "ja/releases/v2.0.3",
--- a/docs/en/README.md
+++ b/docs/en/README.md
@@ -1,13 +1,13 @@
 <p align="center"><img src="https://github.com/user-attachments/assets/eca9a9ec-8534-4615-9e0f-96c5ac1d10a3" alt="CowAgent" width="550" /></p>

 <p align="center">
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/chatgpt-on-wechat" alt="Latest release"></a>
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat/blob/master/LICENSE"><img src="https://img.shields.io/github/license/zhayujie/chatgpt-on-wechat" alt="License: MIT"></a>
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat"><img src="https://img.shields.io/github/stars/zhayujie/chatgpt-on-wechat?style=flat-square" alt="Stars"></a> <br/>
-  [<a href="https://github.com/zhayujie/chatgpt-on-wechat/blob/master/README.md">中文</a>] | [English] | [<a href="https://github.com/zhayujie/chatgpt-on-wechat/blob/master/docs/ja/README.md">日本語</a>]
+  <a href="https://github.com/zhayujie/CowAgent/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/CowAgent" alt="Latest release"></a>
+  <a href="https://github.com/zhayujie/CowAgent/blob/master/LICENSE"><img src="https://img.shields.io/github/license/zhayujie/CowAgent" alt="License: MIT"></a>
+  <a href="https://github.com/zhayujie/CowAgent"><img src="https://img.shields.io/github/stars/zhayujie/CowAgent?style=flat-square" alt="Stars"></a> <br/>
+  [<a href="https://github.com/zhayujie/CowAgent/blob/master/README.md">中文</a>] | [English] | [<a href="https://github.com/zhayujie/CowAgent/blob/master/docs/ja/README.md">日本語</a>]
 </p>

-**CowAgent** is an AI super assistant powered by LLMs, capable of autonomous task planning, operating computers and external resources, creating and executing Skills, and continuously growing with long-term memory. It supports flexible model switching, handles text, voice, images, and files, and can be integrated into WeChat, Web, Feishu, DingTalk, WeCom Bot, WeCom App, and WeChat Official Account — running 7×24 hours on your personal computer or server.
+**CowAgent** is an AI super assistant powered by LLMs, capable of autonomous task planning, operating computers and external resources, creating and executing Skills, and continuously growing with long-term memory and a personal knowledge base. It supports flexible model switching, handles text, voice, images, and files, and can be integrated into WeChat, Web, Feishu, DingTalk, WeCom Bot, WeCom App, and WeChat Official Account — running 7×24 hours on your personal computer or server.

 <p align="center">
  <a href="https://cowagent.ai/">🌐 Website</a> &nbsp;·&nbsp;
@@ -22,7 +22,8 @@
 > CowAgent is both an out-of-the-box AI super assistant and a highly extensible Agent framework. You can extend it with new model interfaces, channels, built-in tools, and the Skills system to flexibly implement various customization needs.

 - ✅ **Autonomous Task Planning**: Understands complex tasks and autonomously plans execution, continuously thinking and invoking tools until goals are achieved.
- ✅ **Long-term Memory**: Automatically persists conversation memory to local files and databases, including core memory and daily memory, with keyword and vector retrieval support.
+- ✅ **Long-term Memory**: Automatically persists conversation memory to local files and databases, including core memory, daily memory, and Deep Dream distillation, with keyword and vector retrieval support.
+- ✅ **Personal Knowledge Base**: Automatically organizes structured knowledge with cross-references to build a knowledge graph, with web-based visualization and conversational management.
 - ✅ **Skills System**: Implements a Skills creation and execution engine, supports installing skills from [Skill Hub](https://skills.cowagent.ai), GitHub, etc., or creating custom Skills through conversation.
 - ✅ **Tool System**: Built-in tools for file I/O, terminal execution, browser automation, scheduled tasks, messaging, and more — autonomously invoked by the Agent.
 - ✅ **CLI System**: Provides terminal commands and in-chat commands for process management, skill installation, configuration, and more.
@@ -42,19 +43,21 @@ Try online (no deployment needed): [CowAgent](https://link-ai.tech/cowagent/crea

 ## Changelog

-> **2026.04.01:** [v2.0.5](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.5) — Cow CLI, Skill Hub open source, Browser tool, WeCom Bot QR scan, and more.
+> **2026.04.14:** [v2.0.6](https://github.com/zhayujie/CowAgent/releases/tag/2.0.6) — Knowledge Base, Deep Dream Memory Distillation, Smart Context Compression, Web Console upgrades.

-> **2026.02.27:** [v2.0.2](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.2) — Web console overhaul (streaming chat, model/skill/memory/channel/scheduler/log management), multi-channel concurrent running, session persistence, new models including Gemini 3.1 Pro / Claude 4.6 Sonnet / Qwen3.5 Plus.
+> **2026.04.01:** [v2.0.5](https://github.com/zhayujie/CowAgent/releases/tag/2.0.5) — Cow CLI, Skill Hub open source, Browser tool, WeCom Bot QR scan, and more.

-> **2026.02.13:** [v2.0.1](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.1) — Built-in Web Search tool, smart context trimming, runtime info dynamic update, Windows compatibility, fixes for scheduler memory loss, Feishu connection issues, and more.
+> **2026.02.27:** [v2.0.2](https://github.com/zhayujie/CowAgent/releases/tag/2.0.2) — Web console overhaul (streaming chat, model/skill/memory/channel/scheduler/log management), multi-channel concurrent running, session persistence, new models including Gemini 3.1 Pro / Claude 4.6 Sonnet / Qwen3.5 Plus.

-> **2026.02.03:** [v2.0.0](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.0) — Full upgrade to AI super assistant with multi-step task planning, long-term memory, built-in tools, Skills framework, new models, and optimized channels.
+> **2026.02.13:** [v2.0.1](https://github.com/zhayujie/CowAgent/releases/tag/2.0.1) — Built-in Web Search tool, smart context trimming, runtime info dynamic update, Windows compatibility, fixes for scheduler memory loss, Feishu connection issues, and more.

-> **2025.05.23:** [v1.7.6](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.6) — Web channel optimization, AgentMesh multi-agent plugin, Baidu TTS, claude-4-sonnet/opus support.
+> **2026.02.03:** [v2.0.0](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0) — Full upgrade to AI super assistant with multi-step task planning, long-term memory, built-in tools, Skills framework, new models, and optimized channels.

-> **2025.04.11:** [v1.7.5](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.5) — wechatferry protocol, DeepSeek model, Tencent Cloud voice, ModelScope and Gitee-AI support.
+> **2025.05.23:** [v1.7.6](https://github.com/zhayujie/CowAgent/releases/tag/1.7.6) — Web channel optimization, AgentMesh multi-agent plugin, Baidu TTS, claude-4-sonnet/opus support.

-> **2024.12.13:** [v1.7.4](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.4) — Gemini 2.0 model, Web channel, memory leak fix.
+> **2025.04.11:** [v1.7.5](https://github.com/zhayujie/CowAgent/releases/tag/1.7.5) — wechatferry protocol, DeepSeek model, Tencent Cloud voice, ModelScope and Gitee-AI support.
+
+> **2024.12.13:** [v1.7.4](https://github.com/zhayujie/CowAgent/releases/tag/1.7.4) — Gemini 2.0 model, Web channel, memory leak fix.

 Full changelog: [Release Notes](https://docs.cowagent.ai/en/releases/overview)

@@ -83,8 +86,8 @@ Script usage: [One-click Install](https://docs.cowagent.ai/en/guide/quick-start)
 **1. Clone the project**

 ```bash
-git clone https://github.com/zhayujie/chatgpt-on-wechat
-cd chatgpt-on-wechat/
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
 ```

 **2. Install dependencies**
@@ -232,16 +235,16 @@ Multiple channels can be enabled simultaneously, separated by commas: `"channel_

 ## 🔎 FAQ

-FAQs: <https://github.com/zhayujie/chatgpt-on-wechat/wiki/FAQs>
+FAQs: <https://github.com/zhayujie/CowAgent/wiki/FAQs>

 ## 🛠️ Contributing

-Welcome to add new channels, referring to the [Feishu channel](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/channel/feishu/feishu_channel.py) as an example. Also welcome to contribute new Skills, see the [Skill Creation docs](https://docs.cowagent.ai/en/skills/create), or submit to [Skill Hub](https://skills.cowagent.ai/submit).
+Welcome to add new channels, referring to the [Feishu channel](https://github.com/zhayujie/CowAgent/blob/master/channel/feishu/feishu_channel.py) as an example. Also welcome to contribute new Skills, see the [Skill Creation docs](https://docs.cowagent.ai/en/skills/create), or submit to [Skill Hub](https://skills.cowagent.ai/submit).

 ## ✉ Contact

-Welcome to submit PRs and Issues, and support the project with a 🌟 Star. For questions, check the [FAQ list](https://github.com/zhayujie/chatgpt-on-wechat/wiki/FAQs) or search [Issues](https://github.com/zhayujie/chatgpt-on-wechat/issues).
+Welcome to submit PRs and Issues, and support the project with a 🌟 Star. For questions, check the [FAQ list](https://github.com/zhayujie/CowAgent/wiki/FAQs) or search [Issues](https://github.com/zhayujie/CowAgent/issues).

 ## 🌟 Contributors

-![cow contributors](https://contrib.rocks/image?repo=zhayujie/chatgpt-on-wechat&max=1000)
+![cow contributors](https://contrib.rocks/image?repo=zhayujie/CowAgent&max=1000)
--- a/docs/en/channels/web.mdx
+++ b/docs/en/channels/web.mdx
@@ -38,6 +38,16 @@ Supports streaming output with real-time display of the Agent's reasoning proces

 <img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />

+#### Multi-Session Management
+
+The chat interface supports multi-session management. All session records are persistently stored in a SQLite database:
+
+- **Session List**: Click the history icon on the left to expand/collapse the session list panel, with scroll-to-load support for all historical sessions
+- **AI-Generated Titles**: After the first exchange in a new session, the model is automatically called to generate a short summary title
+- **New Session**: Click the "New Chat" button at the top of the session list or the `+` button in the input area to create a new session
+- **Delete Session**: Click the delete button on a session item and confirm to permanently delete the session and all its messages
+- **Clear Context**: Click the clear button in the input area to insert a divider in the current session. Messages above the divider are still displayed but no longer included as context for the model
+
 ### Model Management

 Manage model configurations online without manually editing config files:
--- a/docs/en/cli/index.mdx
+++ b/docs/en/cli/index.mdx
@@ -40,6 +40,10 @@ Service:
 Skills:
  skill     Manage skills (list / search / install / uninstall ...)

+Memory & Knowledge:
+  memory    Memory distillation (dream)
+  knowledge View knowledge base stats and structure
+
 Others:
  help      Show this help message
  version   Show version
@@ -55,6 +59,10 @@ In the Web console or any connected channel, type `/` to see command suggestions
 | `/status` | View service status and configuration |
 | `/config` | View or modify runtime configuration |
 | `/skill` | Manage skills (install, uninstall, enable, disable, etc.) |
+| `/memory dream [N]` | Manually trigger memory distillation (default 3 days, max 30) |
+| `/knowledge` | View knowledge base statistics |
+| `/knowledge list` | View knowledge base directory structure |
+| `/knowledge on\|off` | Enable or disable knowledge base |
 | `/context` | View current session context info |
 | `/context clear` | Clear current session context |
 | `/logs` | View recent logs |
@@ -74,6 +82,8 @@ In the Web console or any connected channel, type `/` to see command suggestions
 | logs | ✓ | ✓ |
 | config | ✗ | ✓ |
 | context | — | ✓ |
+| memory (subcommands) | ✗ | ✓ |
+| knowledge (subcommands) | ✓ | ✓ |
 | skill (subcommands) | ✓ | ✓ |
 | start / stop / restart | ✓ | ✗ |
 | update | ✓ | ✗ |
--- a/docs/en/cli/memory-knowledge.mdx
+++ b/docs/en/cli/memory-knowledge.mdx
@@ -0,0 +1,63 @@
+---
+title: Memory & Knowledge
+description: Memory distillation and knowledge base management commands
+---
+
+## memory
+
+Manage the Agent's long-term memory system.
+
+### memory dream
+
+Manually trigger memory distillation (Deep Dream) — consolidate recent daily memories into MEMORY.md and generate a dream diary.
+
+```text
+/memory dream [N]
+```
+
+- `N`: Consolidate the last N days of memory (default 3, max 30)
+- Runs asynchronously in the background; you'll be notified in chat when complete
+- Works without Agent initialization — can be used before the first conversation
+
+**Examples:**
+
+```text
+/memory dream       # Consolidate last 3 days
+/memory dream 7     # Consolidate last 7 days
+/memory dream 30    # Consolidate last 30 days (full)
+```
+
+On the Web console, the completion notification includes clickable links to view the updated MEMORY.md and dream diary.
+
+<Tip>
+  The system automatically runs distillation daily at 23:55 (lookback 1 day). Manual trigger is useful for consolidating historical memories after first deployment, or when you need an immediate memory update.
+</Tip>
+
+## knowledge
+
+View and manage the personal knowledge base. Shows statistics by default.
+
+```text
+/knowledge
+```
+
+### knowledge list
+
+View the knowledge base directory tree.
+
+```text
+/knowledge list
+```
+
+### knowledge on / off
+
+Enable or disable the knowledge base. When disabled, knowledge prompts and file indexing are not injected.
+
+```text
+/knowledge on
+/knowledge off
+```
+
+<Note>
+  In the terminal CLI, `cow knowledge` and `cow knowledge list` are available, but `on|off` is only supported in chat (requires runtime effect).
+</Note>
--- a/docs/en/guide/manual-install.mdx
+++ b/docs/en/guide/manual-install.mdx
@@ -8,12 +8,12 @@ description: Deploy CowAgent manually (source code / Docker)
 ### 1. Clone the project

 ```bash
-git clone https://github.com/zhayujie/chatgpt-on-wechat
-cd chatgpt-on-wechat/
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
 ```

 <Tip>
-  For network issues, use the mirror: https://gitee.com/zhayujie/chatgpt-on-wechat
+  For network issues, use the mirror: https://gitee.com/zhayujie/CowAgent
 </Tip>

 ### 2. Install dependencies
@@ -141,5 +141,5 @@ sudo docker logs -f chatgpt-on-wechat
 | `agent_max_steps` | Max decision steps per task | `15` |

 <Tip>
-  Full configuration options are in the project [`config.py`](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/config.py).
+  Full configuration options are in the project [`config.py`](https://github.com/zhayujie/CowAgent/blob/master/config.py).
 </Tip>
--- a/docs/en/guide/quick-start.mdx
+++ b/docs/en/guide/quick-start.mdx
@@ -26,7 +26,7 @@ The script automatically performs these steps:

 1. Check Python environment (requires Python 3.7+)
 2. Install required tools (git, curl, etc.)
-3. Clone project to `~/chatgpt-on-wechat`
+3. Clone project to `~/CowAgent`
 4. Install Python dependencies and Cow CLI
 5. Guided configuration for AI model and channel
 6. Start service
--- a/docs/en/intro/architecture.mdx
+++ b/docs/en/intro/architecture.mdx
@@ -11,14 +11,16 @@ CowAgent's architecture consists of the following core modules:

 <img src="https://cdn.link-ai.tech/doc/68ef7b212c6f791e0e74314b912149f9-sz_5847990.png" alt="CowAgent Architecture" />

-### Core Modules
-
 | Module | Description |
 | --- | --- |
-| **Channels** | Message channel layer for receiving and sending messages. Supports Web, Feishu, DingTalk, WeCom, WeChat Official Account, and more |
-| **Agent Core** | Agent engine including task planning, memory system, and skills engine |
-| **Tools** | Tool layer for Agent to access OS resources. 10+ built-in tools |
-| **Models** | Model layer with unified access to mainstream LLMs |
+| **Plan** | Understands user intent, decomposes complex tasks into multi-step plans, and iteratively invokes tools until the goal is achieved |
+| **Memory** | Automatically persists important information as core memory and daily memory, with hybrid keyword and vector retrieval for cross-session context continuity |
+| **Knowledge** | Organizes structured knowledge by topic. The Agent autonomously distills valuable information into Markdown pages, maintaining indexes and cross-references to build a growing knowledge network |
+| **Tools** | Core capability for Agent to access OS resources. 10+ built-in tools including file read/write, terminal, browser, scheduler, memory search, web search, and more |
+| **Skills** | Loads and manages Skills. Supports one-click installation from Skill Hub, GitHub, and more, or custom skill creation through conversation |
+| **Models** | Model layer with unified access to OpenAI, Claude, Gemini, DeepSeek, MiniMax, GLM, Qwen, and other mainstream LLMs |
+| **Channels** | Message channel layer for receiving and sending messages. Supports Web console, WeChat, Feishu, DingTalk, WeCom, WeChat Official Account, and more with a unified protocol |
+| **CLI** | Command-line system providing terminal commands (`cow`) and chat commands (`/`) for process management, skill installation, configuration, knowledge base management, and more |

 ## Agent Mode Workflow

@@ -28,7 +30,7 @@ When Agent mode is enabled, CowAgent runs as an autonomous agent with the follow
 2. **Understand Intent** — Analyze task requirements and context
 3. **Plan Task** — Break complex tasks into multiple steps
 4. **Invoke Tools** — Select and execute appropriate tools for each step
-5. **Update Memory** — Store important information in long-term memory
+5. **Update Memory & Knowledge** — Store important information in long-term memory and organize structured knowledge into the knowledge base
 6. **Return Result** — Send execution results back to the user

 ## Workspace Directory Structure
@@ -39,9 +41,12 @@ The Agent workspace is located at `~/cow` by default and stores system prompts,
 ~/cow/
 ├── system.md          # Agent system prompt
 ├── user.md            # User profile
+├── MEMORY.md          # Core memory
 ├── memory/            # Long-term memory storage
-│   ├── core.md        # Core memory
-│   └── daily/         # Daily memory
+│   └── YYYY-MM-DD.md  # Daily memory
+├── knowledge/         # Personal knowledge base
+│   ├── index.md       # Knowledge index
+│   └── <category>/    # Topic-based pages
 └── skills/            # Custom skills
    ├── skill-1/
    └── skill-2/
@@ -75,3 +80,4 @@ Configure Agent mode parameters in `config.json`:
 | `agent_max_context_tokens` | Max context tokens | `40000` |
 | `agent_max_context_turns` | Max context turns | `30` |
 | `agent_max_steps` | Max decision steps per task | `15` |
+| `knowledge` | Enable personal knowledge base | `true` |
--- a/docs/en/intro/features.mdx
+++ b/docs/en/intro/features.mdx
@@ -5,23 +5,42 @@ description: CowAgent long-term memory, task planning, skills system, CLI comman

 ## 1. Long-term Memory

-The memory system enables the Agent to remember important information over time. The Agent proactively stores information when users share preferences, decisions, or key facts, and automatically extracts summaries when conversations reach a certain length. Memory is divided into core memory and daily memory, with hybrid retrieval supporting both keyword search and vector search.
+The memory system enables the Agent to remember important information over time, using a three-tier memory flow: conversation context (short-term) → daily memory (mid-term) → MEMORY.md (long-term), forming a complete memory lifecycle.

 On first launch, the Agent proactively asks the user for key information and records it in the workspace (default `~/cow`) — including agent settings, user identity, and memory files.

-In subsequent long-term conversations, the Agent intelligently stores or retrieves memory as needed, continuously updating its own settings, user preferences, and memory files, summarizing experiences and lessons learned — truly achieving autonomous thinking and continuous growth.
+In subsequent long-term conversations, the Agent intelligently stores or retrieves memory as needed, continuously updating its own settings, user preferences, and memory files. **Deep Dream** distillation runs daily, consolidating scattered daily memories into refined long-term memory and generating a narrative-style dream diary.

 <Frame>
  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
 </Frame>

-## 2. Task Planning and Tool Use
+See [Long-term Memory](/en/memory) and [Deep Dream](/en/memory/deep-dream) for details.
+
+## 2. Personal Knowledge Base
+
+> The knowledge base system enables the Agent to continuously accumulate and organize structured knowledge. Unlike memory which records along a timeline, the knowledge base is organized by topics, transforming articles, conversation insights, and learning materials into interconnected Markdown pages that form a continuously growing knowledge network.
+
+The Agent automatically organizes valuable information from conversations into knowledge pages, maintaining cross-references and indexes. The Web console provides document browsing and knowledge graph visualization. Knowledge is stored in `~/cow/knowledge/` within the workspace.
+
+- **Auto-organization**: The Agent autonomously extracts and organizes structured knowledge during conversations, maintaining indexes and cross-references
+- **Knowledge graph**: Automatically builds a knowledge graph from cross-references between pages, with interactive graph visualization in the Web console
+- **Chat integration**: Knowledge document links referenced in Agent replies can be clicked directly in the Web console for viewing
+- **CLI management**: Use `/knowledge` commands to view stats, browse directory, and toggle the feature with `/knowledge on|off`
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+See [Personal Knowledge Base](/en/knowledge) for details.
+
+## 3. Task Planning and Tool Use

 Tools are the core of how the Agent accesses operating system resources. The Agent intelligently selects and invokes tools based on task requirements, performing file read/write, command execution, scheduled tasks, and more. Built-in tools are implemented in the project's `agent/tools/` directory.

 **Key tools:** file read/write/edit, Bash terminal, browser, file send, scheduler, memory search, web search, environment config, and more.

-### 2.1 Terminal and File Access
+### 3.1 Terminal and File Access

 Access to the OS terminal and file system is the most fundamental and core capability. Many other tools and skills build on top of this. Users can interact with the Agent from a mobile device to operate resources on their personal computer or server:

@@ -29,15 +48,15 @@ Access to the OS terminal and file system is the most fundamental and core capab
  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
 </Frame>

-### 2.2 Programming Capability
+### 3.2 Programming Capability

 Combining programming and system access, the Agent can execute the complete **Vibecoding workflow** — from information search, asset generation, coding, testing, deployment, Nginx configuration, to publishing — all triggered by a single command from your phone:

 <Frame>
-  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+  <img src="https://cdn.link-ai.tech/doc/20260318211018.png" width="800" />
 </Frame>

-### 2.3 Scheduled Tasks
+### 3.3 Scheduled Tasks

 The `scheduler` tool enables dynamic scheduled tasks, supporting **one-time tasks, fixed intervals, and Cron expressions**. Tasks can be triggered as either a **fixed message send** or an **Agent dynamic task** execution:

@@ -45,7 +64,7 @@ The `scheduler` tool enables dynamic scheduled tasks, supporting **one-time task
  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
 </Frame>

-### 2.4 Browser
+### 3.4 Browser

 The built-in `browser` tool allows the Agent to control a Chromium browser to visit web pages, fill forms, click elements, and take screenshots, with support for dynamic JS-rendered pages. Run `cow install-browser` to install with one command, automatically adapting to server (headless) and desktop environments:

@@ -53,7 +72,7 @@ The built-in `browser` tool allows the Agent to control a Chromium browser to vi
  <img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="800" />
 </Frame>

-### 2.5 Environment Variable Management
+### 3.5 Environment Variable Management

 Secrets required by skills are stored in an environment variable file, managed by the `env_config` tool. You can update secrets through conversation, with built-in security protection and desensitization:

@@ -61,7 +80,7 @@ Secrets required by skills are stored in an environment variable file, managed b
  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
 </Frame>

-## 3. Skills System
+## 4. Skills System

 The Skills system provides infinite extensibility for the Agent. Each Skill consists of a description file, execution scripts (optional), and resources (optional), describing how to complete specific types of tasks. Skills allow the Agent to follow instructions for complex workflows, invoke tools, or integrate third-party systems.

@@ -71,7 +90,7 @@ The Skills system provides infinite extensibility for the Agent. Each Skill cons

 Install skills: `/skill install <name>` or `cow skill install <name>`, supporting Skill Hub, GitHub, ClawHub, URL, and more.

-### 3.1 Creating Skills
+### 4.1 Creating Skills

 The `skill-creator` skill enables rapid skill creation through conversation. You can ask the Agent to codify a workflow as a skill, or send any API documentation and examples for the Agent to complete the integration directly:

@@ -79,7 +98,7 @@ The `skill-creator` skill enables rapid skill creation through conversation. You
  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
 </Frame>

-### 3.2 Web Search and Image Recognition
+### 4.2 Web Search and Image Recognition

 - **Web search:** Built-in `web_search` tool, supports multiple search engines. Configure `BOCHA_API_KEY` or `LINKAI_API_KEY` to enable.
 - **Image recognition:** Built-in `openai-image-vision` skill, supports `gpt-4.1-mini`, `gpt-4.1`, and other models. Requires `OPENAI_API_KEY`.
@@ -88,7 +107,7 @@ The `skill-creator` skill enables rapid skill creation through conversation. You
  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
 </Frame>

-### 3.3 Skill Hub
+### 4.3 Skill Hub

 Visit [skills.cowagent.ai](https://skills.cowagent.ai/) to browse all available skills, or use commands in conversation:

@@ -102,7 +121,7 @@ Also supports installing skills from GitHub, ClawHub, LinkAI, and other third-pa

 <img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />

-## 4. CLI Command System
+## 5. CLI Command System

 CowAgent provides two command interaction methods, covering service management, skill installation, configuration, and more:

--- a/docs/en/intro/index.mdx
+++ b/docs/en/intro/index.mdx
@@ -9,8 +9,8 @@ description: CowAgent - AI Super Assistant powered by LLMs

 CowAgent can proactively think and plan tasks, operate computers and external resources, create and execute Skills, and continuously grow with long-term memory. It supports flexible switching between multiple models, handles text, voice, images, files and other multimodal messages, and can be integrated into WeChat, web, Feishu, DingTalk, WeCom, and WeChat Official Account. It runs 7x24 hours on your personal computer or server.

-<Card title="GitHub" icon="github" href="https://github.com/zhayujie/chatgpt-on-wechat">
-  github.com/zhayujie/chatgpt-on-wechat
+<Card title="GitHub" icon="github" href="https://github.com/zhayujie/CowAgent">
+  github.com/zhayujie/CowAgent
 </Card>

 ## Core Capabilities
@@ -20,7 +20,10 @@ CowAgent can proactively think and plan tasks, operate computers and external re
    Understands complex tasks and autonomously plans execution, continuously thinking and invoking tools until goals are achieved. Supports accessing file systems, terminals, browsers, schedulers, and other system resources through tools.
  </Card>
  <Card title="Long-term Memory" icon="database" href="/en/memory">
-    Automatically persists conversation memory to local files and databases, including core memory and daily memory, with keyword and vector retrieval support.
+    Three-tier memory flow (context → daily memory → global memory) with daily Deep Dream distillation, keyword and vector retrieval support.
+  </Card>
+  <Card title="Knowledge Base" icon="book" href="/en/knowledge">
+    Automatically organizes structured knowledge with knowledge graph visualization, building a continuously growing knowledge network through cross-references.
  </Card>
  <Card title="Skills System" icon="puzzle-piece" href="/en/skills/index">
    Implements a Skills creation and execution engine with built-in skills, and supports custom Skills development through natural language conversation.
@@ -72,7 +75,7 @@ By default, the Web service starts after running. Access `http://localhost:9899/

 ## Disclaimer

-1. This project follows the [MIT License](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/LICENSE) and is intended for technical research and learning. Users must comply with local laws, regulations, policies, and corporate bylaws. Any illegal or rights-infringing use is prohibited.
+1. This project follows the [MIT License](https://github.com/zhayujie/CowAgent/blob/master/LICENSE) and is intended for technical research and learning. Users must comply with local laws, regulations, policies, and corporate bylaws. Any illegal or rights-infringing use is prohibited.
 2. Agent mode consumes more tokens than normal chat mode. Choose models based on effectiveness and cost. Agent has access to the host operating system — deploy with caution.
 3. CowAgent focuses on open-source development and does not participate in, authorize, or issue any cryptocurrency.

--- a/docs/en/knowledge/index.mdx
+++ b/docs/en/knowledge/index.mdx
@@ -0,0 +1,89 @@
+---
+title: Personal Knowledge Base
+description: CowAgent personal knowledge base — structured knowledge accumulation, automatic organization, and knowledge graph
+---
+
+The personal knowledge base is the Agent's long-term structured knowledge store, saved in the `knowledge/` directory within the workspace. Unlike memory, which is organized by timeline, the knowledge base organizes content by topic — articles, conversation insights, and learning materials are structured into interlinked Markdown pages, forming a continuously growing knowledge network.
+
+## Core Concepts
+
+### Knowledge vs Memory
+
+| Dimension | Knowledge Base (knowledge/) | Long-term Memory (memory/) |
+| --- | --- | --- |
+| Organization | By topic, interlinked | By timeline, dated files |
+| Writing | Agent actively structures content | Auto-summarized on context trimming |
+| Content | Refined, structured knowledge | Raw conversation summaries |
+| Use cases | Study notes, tech docs, project knowledge | Conversation history, event records |
+
+### Directory Structure
+
+```
+~/cow/knowledge/
+├── index.md          # Knowledge index, entry point for all pages
+├── log.md            # Change log, records each write
+├── concepts/         # Conceptual knowledge
+│   └── machine-learning.md
+├── entities/         # Entity knowledge (people, orgs, tools)
+│   └── openai.md
+└── sources/          # Source knowledge (articles, papers)
+    └── llm-wiki.md
+```
+
+The directory structure is flexible — the Agent automatically creates appropriate category directories based on actual content. Users can also customize the organization.
+
+## Automatic Organization
+
+Knowledge writing is an autonomous Agent behavior, triggered in these scenarios:
+
+- **User shares an article or document** — The Agent automatically extracts key information and creates a structured knowledge page
+- **Conversation produces valuable conclusions** — The Agent organizes insights into knowledge pages and links them to existing knowledge
+- **User explicitly requests organization** — Users can guide the Agent to organize and update knowledge through conversation
+
+Each knowledge page includes cross-reference links to related pages, gradually building a knowledge graph.
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/3ce92f78-1863-4820-8fa8-660c0f2b7f09" alt="Conversational knowledge ingest" />
+</Frame>
+
+## Knowledge Retrieval
+
+The Agent can retrieve knowledge during conversation through:
+
+- **Index lookup** — Quickly locate relevant pages via `knowledge/index.md`
+- **Semantic search** — Search knowledge content via the `memory_search` tool
+- **Direct read** — Read specific knowledge files via the `memory_get` tool
+
+## Web Console
+
+The web console provides a dedicated "Knowledge" module with:
+
+- **Document browsing** — Tree-style directory structure, searchable and collapsible, click to view content
+- **Knowledge graph** — Interactive graph visualizing relationships between knowledge pages
+- **Chat integration** — Knowledge document links referenced in Agent replies are clickable for direct navigation
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/b7b9d6be-0ac1-4c65-803b-2c6b36bd59a7" alt="Knowledge document browsing" />
+</Frame>
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/44ae68ca-96cc-40b9-ab33-cdbec34c2379" alt="Knowledge graph visualization" />
+</Frame>
+
+## CLI Commands
+
+Manage the knowledge base with the `/knowledge` command:
+
+| Command | Description |
+| --- | --- |
+| `/knowledge` | Show knowledge base statistics |
+| `/knowledge list` | Display file directory as a tree |
+| `/knowledge on` | Enable the knowledge base feature |
+| `/knowledge off` | Disable the knowledge base feature |
+
+## Configuration
+
+| Parameter | Description | Default |
+| --- | --- | --- |
+| `knowledge` | Whether to enable the personal knowledge base | `true` |
+| `agent_workspace` | Workspace path; knowledge is stored under the `knowledge/` subdirectory | `~/cow` |
--- a/docs/en/memory/context.mdx
+++ b/docs/en/memory/context.mdx
@@ -39,14 +39,15 @@ When conversation turns exceed `agent_max_context_turns`:

 - The **oldest half** of complete turns is trimmed (preserving tool call chain integrity)
 - Trimmed messages are summarized by LLM and **written to the daily memory file**
- Remaining turns stay intact
+- Once the LLM summary is ready, it is also **injected into the first user message** of the retained context, helping the model maintain conversational continuity
+- Summary injection runs asynchronously in the background and takes effect from the next turn onward

 ### 3. Token Budget Trimming

 After turn trimming, if tokens still exceed the budget:

 - **Fewer than 5 turns**: All turns undergo **text compression** — each turn keeps only the first user text and last Agent reply, removing intermediate tool call chains
- **5 or more turns**: The **first half** of turns is trimmed again, with discarded content also written to memory
+- **5 or more turns**: The **first half** of turns is trimmed again, with discarded content written to memory and a context summary injected

 ### 4. Overflow Emergency Handling

--- a/docs/en/memory/deep-dream.mdx
+++ b/docs/en/memory/deep-dream.mdx
@@ -0,0 +1,90 @@
+---
+title: Deep Dream
+description: Deep Dream — automatic distillation from conversations to permanent memory
+---
+
+Deep Dream is the core consolidation mechanism of CowAgent's memory system, responsible for distilling scattered daily memories into refined long-term memory and generating dream diaries.
+
+## Memory Flow
+
+CowAgent's memory progresses through three stages from short-term to long-term:
+
+```
+Conversation context (short-term) → Daily memory (mid-term) → MEMORY.md (long-term)
+```
+
+### 1. Conversation → Daily Memory
+
+When conversation context is trimmed or during the daily scheduled summary, the system uses LLM to summarize conversation content into key events, writing them to the daily memory file `memory/YYYY-MM-DD.md`.
+
+Triggers:
+- **Context trimming** — Trimmed content is summarized when turn or token limits are exceeded
+- **Daily schedule** — Automatically triggered at 23:55
+- **API overflow** — Emergency save of current conversation summary
+
+### 2. Daily Memory → MEMORY.md (Distillation)
+
+After the daily summary completes, Deep Dream automatically runs distillation:
+
+1. **Read materials** — Current `MEMORY.md` + today's daily memory
+2. **LLM distillation** — Deduplicate, merge, prune, extract new information
+3. **Overwrite MEMORY.md** — Output the refined long-term memory
+4. **Generate dream diary** — Record discoveries and insights from the consolidation
+
+### 3. Role of MEMORY.md
+
+`MEMORY.md` is injected into the system prompt for every conversation, keeping the Agent aware of user preferences, decisions, and key facts. Therefore it must stay concise — Deep Dream targets approximately 30 entries or fewer.
+
+## Distillation Rules
+
+Deep Dream follows these consolidation rules:
+
+| Operation | Description |
+| --- | --- |
+| **Merge & refine** | Combine similar entries into single high-density statements |
+| **Extract new** | Pull preferences, decisions, people, experiences from daily memory |
+| **Conflict update** | When new info contradicts old entries, newer info takes precedence |
+| **Clean invalid** | Remove temporary records, blank entries, formatting artifacts |
+| **Remove redundancy** | Delete old entries already covered by more refined statements |
+
+## Dream Diary
+
+Each distillation generates a dream diary saved at `memory/dreams/YYYY-MM-DD.md`, written in a narrative style recording:
+
+- Duplications or contradictions found
+- New insights extracted from daily memory
+- Cleanups and optimizations performed
+- Overall observations
+
+Dream diaries can be viewed in the Web console under "Memory → Dream Diary" tab.
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414110032.png" width="800" />
+</Frame>
+
+## Manual Trigger
+
+In addition to the automatic daily run, you can manually trigger distillation in chat:
+
+```text
+/memory dream [N]
+```
+
+- `N`: Consolidate the last N days of memory (default 3, max 30)
+- Runs asynchronously in the background; you'll be notified in chat when complete
+- Web notifications include clickable links to view MEMORY.md and dream diary
+- Works without Agent initialization — can be used before the first conversation
+
+<Tip>
+  After first deployment, it's recommended to run `/memory dream 30` once to distill all historical daily memories into MEMORY.md.
+</Tip>
+
+## Safety Mechanisms
+
+| Mechanism | Description |
+| --- | --- |
+| **Skip on no content** | Distillation skipped when no daily memory exists, avoiding empty overwrites |
+| **Input dedup** | In scheduled tasks, automatically skipped when input materials haven't changed |
+| **Async execution** | Distillation runs in a background thread, never blocking conversation |
+| **Sequential guarantee** | In scheduled tasks, daily flush completes before distillation starts |
+| **No fabrication** | Prompt explicitly constrains consolidation to existing materials only |
--- a/docs/en/memory/index.mdx
+++ b/docs/en/memory/index.mdx
@@ -15,12 +15,17 @@ Stored in `~/cow/MEMORY.md`, containing long-term user preferences, important de

 Stored in `~/cow/memory/` directory, named by date (e.g., `2026-03-08.md`), recording daily conversation summaries and key events. Files are only created on first write to avoid generating empty files.

+### Dream Diary (memory/dreams/YYYY-MM-DD.md)
+
+A byproduct of the Deep Dream (memory distillation) process, recording discoveries, deduplication operations, and new insights from each consolidation. Stored in `~/cow/memory/dreams/` directory, named by date.
+
 ## Automatic Writing

 The Agent automatically persists conversation content to long-term memory through the following mechanisms:

- **On context trimming** — When conversation turns or tokens exceed the configured limit, the oldest half of the context is trimmed, and the discarded content is summarized by LLM into key information and written to the daily memory file
+- **On context trimming** — When conversation turns or tokens exceed the configured limit, the oldest half of the context is trimmed, and the discarded content is summarized by LLM into key information and written to the daily memory file. The summary is also asynchronously injected into the retained context for conversational continuity
 - **Daily scheduled summary** — A full summary is automatically triggered at 23:55 every day, ensuring memory is preserved even on low-activity days (skipped if content hasn't changed)
+- **[Deep Dream (memory distillation)](/en/memory/deep-dream)** — Runs automatically after the daily summary, distilling daily memories into MEMORY.md and generating a dream diary
 - **On API context overflow** — When the model API returns a context overflow error, the current conversation summary is saved as an emergency measure

 All memory writes run asynchronously in a background thread (LLM summarization + file writing), never blocking normal conversation replies.
@@ -44,6 +49,7 @@ On first launch, the Agent will proactively ask the user for key information and
 | `user.md` | User identity information and preferences |
 | `MEMORY.md` | Core memory (long-term) |
 | `memory/YYYY-MM-DD.md` | Daily memory (created on demand) |
+| `memory/dreams/YYYY-MM-DD.md` | Dream diary (auto-generated by Deep Dream) |

 <Frame>
  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
--- a/docs/en/models/index.mdx
+++ b/docs/en/models/index.mdx
@@ -51,5 +51,5 @@ You can also use the [LinkAI](https://link-ai.tech) platform interface to flexib
 </CardGroup>

 <Tip>
-  For a full list of model names, refer to the project's [`common/const.py`](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/common/const.py) file.
+  For a full list of model names, refer to the project's [`common/const.py`](https://github.com/zhayujie/CowAgent/blob/master/common/const.py) file.
 </Tip>
--- a/docs/en/releases/overview.mdx
+++ b/docs/en/releases/overview.mdx
@@ -5,6 +5,7 @@ description: CowAgent version history

 | Version | Date | Description |
 | --- | --- | --- |
+| [2.0.6](/en/releases/v2.0.6) | 2026.04.14 | Knowledge Base, Deep Dream Memory Distillation, Smart Context Compression, Web Console upgrades |
 | [2.0.5](/en/releases/v2.0.5) | 2026.04.01 | Cow CLI, Skill Hub open source, Browser tool, WeCom Bot QR scan, and more |
 | [2.0.4](/en/releases/v2.0.4) | 2026.03.22 | Personal WeChat channel, new model support, Japanese docs, script refactoring and bug fixes |
 | [2.0.2](/en/releases/v2.0.2) | 2026.02.27 | Web Console upgrade, multi-channel concurrency, session persistence |
@@ -22,4 +23,4 @@ description: CowAgent version history
 | 1.5.0 | 2023.11.10 | gpt-4-turbo, dall-e-3, tts multimodal |
 | 1.0.0 | 2022.12.12 | Project created, first ChatGPT integration |

-See [GitHub Releases](https://github.com/zhayujie/chatgpt-on-wechat/releases) for full history.
+See [GitHub Releases](https://github.com/zhayujie/CowAgent/releases) for full history.
--- a/docs/en/releases/v2.0.0.mdx
+++ b/docs/en/releases/v2.0.0.mdx
@@ -5,7 +5,7 @@ description: CowAgent 2.0 - Full upgrade from chatbot to AI super assistant

 CowAgent 2.0 is a comprehensive upgrade from a chatbot to an **AI super assistant** — capable of autonomous thinking and task planning, long-term memory, operating computers, and creating and executing skills.

-**Release Date**: 2026.02.03 | [GitHub Release](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.0)
+**Release Date**: 2026.02.03 | [GitHub Release](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0)

 ## Key Updates

@@ -60,4 +60,4 @@ CowAgent 2.0 is a comprehensive upgrade from a chatbot to an **AI super assistan

 ## Contributing

-Welcome to [submit feedback](https://github.com/zhayujie/chatgpt-on-wechat/issues) and [contribute code](https://github.com/zhayujie/chatgpt-on-wechat/pulls).
+Welcome to [submit feedback](https://github.com/zhayujie/CowAgent/issues) and [contribute code](https://github.com/zhayujie/CowAgent/pulls).
--- a/docs/en/releases/v2.0.1.mdx
+++ b/docs/en/releases/v2.0.1.mdx
@@ -3,34 +3,34 @@ title: v2.0.1
 description: CowAgent 2.0.1 - Built-in Web Search, smart context management, multiple fixes
 ---

-**Release Date**: 2026.02.27 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.0..2.0.1)
+**Release Date**: 2026.02.27 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.0..2.0.1)

 ## New Features

- **Built-in Web Search tool**: Integrated web search as a built-in Agent tool, reducing decision cost ([4f0ea5d](https://github.com/zhayujie/chatgpt-on-wechat/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
- **Claude Opus 4.6 model support**: Added support for Claude Opus 4.6 model ([#2661](https://github.com/zhayujie/chatgpt-on-wechat/pull/2661))
- **WeCom image recognition**: Support image message recognition in WeCom channel ([#2667](https://github.com/zhayujie/chatgpt-on-wechat/pull/2667))
+- **Built-in Web Search tool**: Integrated web search as a built-in Agent tool, reducing decision cost ([4f0ea5d](https://github.com/zhayujie/CowAgent/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
+- **Claude Opus 4.6 model support**: Added support for Claude Opus 4.6 model ([#2661](https://github.com/zhayujie/CowAgent/pull/2661))
+- **WeCom image recognition**: Support image message recognition in WeCom channel ([#2667](https://github.com/zhayujie/CowAgent/pull/2667))

 ## Improvements

- **Smart context management**: Resolved chat context overflow with intelligent context trimming strategy to prevent token limits ([cea7fb7](https://github.com/zhayujie/chatgpt-on-wechat/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/chatgpt-on-wechat/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/chatgpt-on-wechat/issues/2663)
- **Runtime info dynamic update**: Automatic update of timestamps and other runtime info in system prompts via dynamic functions ([#2655](https://github.com/zhayujie/chatgpt-on-wechat/pull/2655), [#2657](https://github.com/zhayujie/chatgpt-on-wechat/pull/2657))
- **Skill prompt optimization**: Improved Skill system prompt generation, simplified tool descriptions for better Agent performance ([6c21833](https://github.com/zhayujie/chatgpt-on-wechat/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
- **GLM custom API Base URL**: Support custom API Base URL for GLM models ([#2660](https://github.com/zhayujie/chatgpt-on-wechat/pull/2660))
- **Startup script optimization**: Improved `run.sh` script interaction and configuration flow ([#2656](https://github.com/zhayujie/chatgpt-on-wechat/pull/2656))
- **Decision step logging**: Added Agent decision step logging for debugging ([cb303e6](https://github.com/zhayujie/chatgpt-on-wechat/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))
+- **Smart context management**: Resolved chat context overflow with intelligent context trimming strategy to prevent token limits ([cea7fb7](https://github.com/zhayujie/CowAgent/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/CowAgent/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/CowAgent/issues/2663)
+- **Runtime info dynamic update**: Automatic update of timestamps and other runtime info in system prompts via dynamic functions ([#2655](https://github.com/zhayujie/CowAgent/pull/2655), [#2657](https://github.com/zhayujie/CowAgent/pull/2657))
+- **Skill prompt optimization**: Improved Skill system prompt generation, simplified tool descriptions for better Agent performance ([6c21833](https://github.com/zhayujie/CowAgent/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
+- **GLM custom API Base URL**: Support custom API Base URL for GLM models ([#2660](https://github.com/zhayujie/CowAgent/pull/2660))
+- **Startup script optimization**: Improved `run.sh` script interaction and configuration flow ([#2656](https://github.com/zhayujie/CowAgent/pull/2656))
+- **Decision step logging**: Added Agent decision step logging for debugging ([cb303e6](https://github.com/zhayujie/CowAgent/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))

 ## Bug Fixes

- **Scheduler memory loss**: Fixed memory loss caused by Scheduler dispatcher ([a77a874](https://github.com/zhayujie/chatgpt-on-wechat/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
- **Empty tool calls & long results**: Fixed handling of empty tool calls and excessively long tool results ([0542700](https://github.com/zhayujie/chatgpt-on-wechat/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
- **OpenAI Function Call**: Fixed function call compatibility with OpenAI models ([158c87a](https://github.com/zhayujie/chatgpt-on-wechat/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
- **Claude tool name field**: Removed extraneous tool name field from Claude model responses ([eec10cb](https://github.com/zhayujie/chatgpt-on-wechat/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
- **MiniMax reasoning**: Optimized MiniMax model reasoning content handling, hidden thinking process output ([c72cda3](https://github.com/zhayujie/chatgpt-on-wechat/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/chatgpt-on-wechat/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
- **GLM thinking process**: Hidden GLM model thinking process display ([72b1cac](https://github.com/zhayujie/chatgpt-on-wechat/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
- **Feishu connection & SSL**: Fixed Feishu channel SSL certificate errors and connection issues ([229b14b](https://github.com/zhayujie/chatgpt-on-wechat/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/chatgpt-on-wechat/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
- **model_type validation**: Fixed `AttributeError` caused by non-string `model_type` ([#2666](https://github.com/zhayujie/chatgpt-on-wechat/pull/2666))
+- **Scheduler memory loss**: Fixed memory loss caused by Scheduler dispatcher ([a77a874](https://github.com/zhayujie/CowAgent/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
+- **Empty tool calls & long results**: Fixed handling of empty tool calls and excessively long tool results ([0542700](https://github.com/zhayujie/CowAgent/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
+- **OpenAI Function Call**: Fixed function call compatibility with OpenAI models ([158c87a](https://github.com/zhayujie/CowAgent/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
+- **Claude tool name field**: Removed extraneous tool name field from Claude model responses ([eec10cb](https://github.com/zhayujie/CowAgent/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
+- **MiniMax reasoning**: Optimized MiniMax model reasoning content handling, hidden thinking process output ([c72cda3](https://github.com/zhayujie/CowAgent/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **GLM thinking process**: Hidden GLM model thinking process display ([72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **Feishu connection & SSL**: Fixed Feishu channel SSL certificate errors and connection issues ([229b14b](https://github.com/zhayujie/CowAgent/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/CowAgent/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
+- **model_type validation**: Fixed `AttributeError` caused by non-string `model_type` ([#2666](https://github.com/zhayujie/CowAgent/pull/2666))

 ## Platform Compatibility

- **Windows compatibility**: Fixed path handling, file encoding, and `os.getuid()` unavailability on Windows across multiple tool modules ([051ffd7](https://github.com/zhayujie/chatgpt-on-wechat/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/chatgpt-on-wechat/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
+- **Windows compatibility**: Fixed path handling, file encoding, and `os.getuid()` unavailability on Windows across multiple tool modules ([051ffd7](https://github.com/zhayujie/CowAgent/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/CowAgent/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
--- a/docs/en/releases/v2.0.2.mdx
+++ b/docs/en/releases/v2.0.2.mdx
@@ -3,7 +3,7 @@ title: v2.0.2
 description: CowAgent 2.0.2 - Web Console upgrade, multi-channel concurrency, session persistence
 ---

-**Release Date**: 2026.02.27 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.1...master)
+**Release Date**: 2026.02.27 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.1...master)

 ## Highlights

@@ -53,7 +53,7 @@ View Agent runtime logs in real-time for monitoring and troubleshooting:

 <img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />

-Related commits: [f1a1413](https://github.com/zhayujie/chatgpt-on-wechat/commit/f1a1413), [c0702c8](https://github.com/zhayujie/chatgpt-on-wechat/commit/c0702c8), [394853c](https://github.com/zhayujie/chatgpt-on-wechat/commit/394853c), [1c71c4e](https://github.com/zhayujie/chatgpt-on-wechat/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/chatgpt-on-wechat/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/chatgpt-on-wechat/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/chatgpt-on-wechat/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d258b5)
+Related commits: [f1a1413](https://github.com/zhayujie/CowAgent/commit/f1a1413), [c0702c8](https://github.com/zhayujie/CowAgent/commit/c0702c8), [394853c](https://github.com/zhayujie/CowAgent/commit/394853c), [1c71c4e](https://github.com/zhayujie/CowAgent/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/CowAgent/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/CowAgent/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/CowAgent/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5)

 ### 🔀 Multi-Channel Concurrency

@@ -67,24 +67,24 @@ Configuration: Set multiple channels in `config.json` via `channel_type` separat
 }
 ```

-Related commits: [4694594](https://github.com/zhayujie/chatgpt-on-wechat/commit/4694594), [7cce224](https://github.com/zhayujie/chatgpt-on-wechat/commit/7cce224), [7d258b5](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d258b5), [c9adddb](https://github.com/zhayujie/chatgpt-on-wechat/commit/c9adddb)
+Related commits: [4694594](https://github.com/zhayujie/CowAgent/commit/4694594), [7cce224](https://github.com/zhayujie/CowAgent/commit/7cce224), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5), [c9adddb](https://github.com/zhayujie/CowAgent/commit/c9adddb)

 ### 💾 Session Persistence

 Session history is now persisted to a local SQLite database. Conversation context is automatically restored after service restarts. Historical conversations in the Web Console are also restored.

-Related commits: [29bfbec](https://github.com/zhayujie/chatgpt-on-wechat/commit/29bfbec), [9917552](https://github.com/zhayujie/chatgpt-on-wechat/commit/9917552), [925d728](https://github.com/zhayujie/chatgpt-on-wechat/commit/925d728)
+Related commits: [29bfbec](https://github.com/zhayujie/CowAgent/commit/29bfbec), [9917552](https://github.com/zhayujie/CowAgent/commit/9917552), [925d728](https://github.com/zhayujie/CowAgent/commit/925d728)

 ## New Models

- **Gemini 3.1 Pro Preview**: Added `gemini-3.1-pro-preview` model support ([52d7cad](https://github.com/zhayujie/chatgpt-on-wechat/commit/52d7cad))
- **Claude 4.6 Sonnet**: Added `claude-4.6-sonnet` model support ([52d7cad](https://github.com/zhayujie/chatgpt-on-wechat/commit/52d7cad))
- **Qwen3.5 Plus**: Added `qwen3.5-plus` model support ([e59a289](https://github.com/zhayujie/chatgpt-on-wechat/commit/e59a289))
- **MiniMax M2.5**: Added `Minimax-M2.5` model support ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **GLM-5**: Added `glm-5` model support ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **Kimi K2.5**: Added `kimi-k2.5` model support ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **Doubao 2.0 Code**: Added `doubao-2.0-code` coding-specialized model ([ab28ee5](https://github.com/zhayujie/chatgpt-on-wechat/commit/ab28ee5))
- **DashScope Models**: Added Alibaba Cloud DashScope model name support ([ce58f23](https://github.com/zhayujie/chatgpt-on-wechat/commit/ce58f23))
+- **Gemini 3.1 Pro Preview**: Added `gemini-3.1-pro-preview` model support ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Claude 4.6 Sonnet**: Added `claude-4.6-sonnet` model support ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Qwen3.5 Plus**: Added `qwen3.5-plus` model support ([e59a289](https://github.com/zhayujie/CowAgent/commit/e59a289))
+- **MiniMax M2.5**: Added `Minimax-M2.5` model support ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **GLM-5**: Added `glm-5` model support ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Kimi K2.5**: Added `kimi-k2.5` model support ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Doubao 2.0 Code**: Added `doubao-2.0-code` coding-specialized model ([ab28ee5](https://github.com/zhayujie/CowAgent/commit/ab28ee5))
+- **DashScope Models**: Added Alibaba Cloud DashScope model name support ([ce58f23](https://github.com/zhayujie/CowAgent/commit/ce58f23))

 ## Website & Documentation

@@ -93,6 +93,6 @@ Related commits: [29bfbec](https://github.com/zhayujie/chatgpt-on-wechat/commit/

 ## Bug Fixes

- **Gemini DingTalk image recognition**: Fixed Gemini unable to process image markers in DingTalk channel ([05a3304](https://github.com/zhayujie/chatgpt-on-wechat/commit/05a3304)) ([#2670](https://github.com/zhayujie/chatgpt-on-wechat/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
- **Startup script dependencies**: Fixed dependency installation issue in `run.sh` script ([b6fc9fa](https://github.com/zhayujie/chatgpt-on-wechat/commit/b6fc9fa))
- **Bare except cleanup**: Replaced `bare except` with `except Exception` for better exception handling ([adca89b](https://github.com/zhayujie/chatgpt-on-wechat/commit/adca89b)) ([#2674](https://github.com/zhayujie/chatgpt-on-wechat/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)
+- **Gemini DingTalk image recognition**: Fixed Gemini unable to process image markers in DingTalk channel ([05a3304](https://github.com/zhayujie/CowAgent/commit/05a3304)) ([#2670](https://github.com/zhayujie/CowAgent/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
+- **Startup script dependencies**: Fixed dependency installation issue in `run.sh` script ([b6fc9fa](https://github.com/zhayujie/CowAgent/commit/b6fc9fa))
+- **Bare except cleanup**: Replaced `bare except` with `except Exception` for better exception handling ([adca89b](https://github.com/zhayujie/CowAgent/commit/adca89b)) ([#2674](https://github.com/zhayujie/CowAgent/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)
--- a/docs/en/releases/v2.0.4.mdx
+++ b/docs/en/releases/v2.0.4.mdx
@@ -16,40 +16,40 @@ Added personal WeChat (`weixin`) channel — the most important update in this r

 Documentation: [WeChat Channel](https://docs.cowagent.ai/channels/weixin).

-Related commits: [ce89869](https://github.com/zhayujie/chatgpt-on-wechat/commit/ce89869), [a483ec0](https://github.com/zhayujie/chatgpt-on-wechat/commit/a483ec0), [c1421e0](https://github.com/zhayujie/chatgpt-on-wechat/commit/c1421e0)
+Related commits: [ce89869](https://github.com/zhayujie/CowAgent/commit/ce89869), [a483ec0](https://github.com/zhayujie/CowAgent/commit/a483ec0), [c1421e0](https://github.com/zhayujie/CowAgent/commit/c1421e0)

 ## 🤖 New Models

 - **MiniMax-M2.7**: Added MiniMax-M2.7 model support
 - **GLM-5-Turbo**: Added Zhipu glm-5-turbo model support

-Related commits: [9192f6f](https://github.com/zhayujie/chatgpt-on-wechat/commit/9192f6f)
+Related commits: [9192f6f](https://github.com/zhayujie/CowAgent/commit/9192f6f)

 ## 🔧 Script Refactoring

- **run.sh Refactoring**: Extracted shared logic and eliminated duplication, reducing from 600+ lines to 177 lines ([49d8707](https://github.com/zhayujie/chatgpt-on-wechat/commit/49d8707))
- **Executable Permission**: Fixed `run.sh` file permission issue ([652156e](https://github.com/zhayujie/chatgpt-on-wechat/commit/652156e))
+- **run.sh Refactoring**: Extracted shared logic and eliminated duplication, reducing from 600+ lines to 177 lines ([49d8707](https://github.com/zhayujie/CowAgent/commit/49d8707))
+- **Executable Permission**: Fixed `run.sh` file permission issue ([652156e](https://github.com/zhayujie/CowAgent/commit/652156e))

 ## ⚡ Improvements

- **Unified Request Headers**: Added identification headers to external requests across Agent services (Chat, Embedding, Vision, WebSearch, etc.) ([b4e711f](https://github.com/zhayujie/chatgpt-on-wechat/commit/b4e711f))
- **Auto-Repair Messages**: Enhanced message protocol fault tolerance with automatic repair of malformed message sequences ([b8b57e3](https://github.com/zhayujie/chatgpt-on-wechat/commit/b8b57e3))
+- **Unified Request Headers**: Added identification headers to external requests across Agent services (Chat, Embedding, Vision, WebSearch, etc.) ([b4e711f](https://github.com/zhayujie/CowAgent/commit/b4e711f))
+- **Auto-Repair Messages**: Enhanced message protocol fault tolerance with automatic repair of malformed message sequences ([b8b57e3](https://github.com/zhayujie/CowAgent/commit/b8b57e3))

 ## 🌍 Japanese Documentation

 Added complete Japanese documentation covering getting started guide, channel integration, model configuration and other major sections. Thanks [@Ikko Ashimine](https://github.com/ikoamu)

-Related commits: [5487c0b](https://github.com/zhayujie/chatgpt-on-wechat/commit/5487c0b)
+Related commits: [5487c0b](https://github.com/zhayujie/CowAgent/commit/5487c0b)

 ## 🐛 Bug Fixes

- **WeCom Bot Compatibility**: Fixed compatibility with older `websocket-client` versions, added unified WebSocket compatibility layer ([bc7f627](https://github.com/zhayujie/chatgpt-on-wechat/commit/bc7f627))
- **run.sh PID**: Fixed process PID retrieval error in `run.sh` ([9febb07](https://github.com/zhayujie/chatgpt-on-wechat/commit/9febb07))
- **Feishu Encoding**: Fixed message and log encoding issue in Feishu channel ([7d0e156](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d0e156))
- **Feishu Config**: Removed redundant `feishu_bot_name` dependency in `run.sh` ([1b5be1b](https://github.com/zhayujie/chatgpt-on-wechat/commit/1b5be1b))
+- **WeCom Bot Compatibility**: Fixed compatibility with older `websocket-client` versions, added unified WebSocket compatibility layer ([bc7f627](https://github.com/zhayujie/CowAgent/commit/bc7f627))
+- **run.sh PID**: Fixed process PID retrieval error in `run.sh` ([9febb07](https://github.com/zhayujie/CowAgent/commit/9febb07))
+- **Feishu Encoding**: Fixed message and log encoding issue in Feishu channel ([7d0e156](https://github.com/zhayujie/CowAgent/commit/7d0e156))
+- **Feishu Config**: Removed redundant `feishu_bot_name` dependency in `run.sh` ([1b5be1b](https://github.com/zhayujie/CowAgent/commit/1b5be1b))

 ## 📦 Upgrade

 Run `./run.sh update` for a one-click upgrade, or manually pull the latest code and restart. See [Upgrade Guide](https://docs.cowagent.ai/guide/upgrade) for details.

-**Release Date**: 2026.03.22 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.3...master)
+**Release Date**: 2026.03.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.3...master)
--- a/docs/en/releases/v2.0.5.mdx
+++ b/docs/en/releases/v2.0.5.mdx
@@ -57,21 +57,21 @@ WeCom Bot channel now supports QR code scan for one-click bot creation:

 Docs: [WeCom Bot](https://docs.cowagent.ai/en/channels/wecom-bot)

-PR: [#2735](https://github.com/zhayujie/chatgpt-on-wechat/pull/2735). Thanks [@WecomTeam](https://github.com/WecomTeam)
+PR: [#2735](https://github.com/zhayujie/CowAgent/pull/2735). Thanks [@WecomTeam](https://github.com/WecomTeam)

 ## 🐛 Other Improvements & Fixes

- **DeepSeek module**: Independent DeepSeek Bot with dedicated `deepseek_api_key` config ([#2719](https://github.com/zhayujie/chatgpt-on-wechat/pull/2719)). Thanks [@6vision](https://github.com/6vision)
- **Web console**: Slash command menu, input history, new model options, mobile optimization ([#2731](https://github.com/zhayujie/chatgpt-on-wechat/pull/2731)). Thanks [@zkjqd](https://github.com/zkjqd)
- **Context loss**: Fix context loss after trimming ([393f0c0](https://github.com/zhayujie/chatgpt-on-wechat/commit/393f0c0))
- **System prompt**: Fix system prompt not rebuilding on every turn ([13f5fde](https://github.com/zhayujie/chatgpt-on-wechat/commit/13f5fde))
- **Gemini**: Fix missing model attribute in GoogleGeminiBot ([#2716](https://github.com/zhayujie/chatgpt-on-wechat/pull/2716)). Thanks [@cowagent](https://github.com/cowagent)
- **WeChat channel**: Fix file send failures and filename loss ([6d9b7ba](https://github.com/zhayujie/chatgpt-on-wechat/commit/6d9b7ba), [45faa9c](https://github.com/zhayujie/chatgpt-on-wechat/commit/45faa9c))
- **Docker**: Fix volume permissions, reduce image size ([3eb8348](https://github.com/zhayujie/chatgpt-on-wechat/commit/3eb8348), [4470d4c](https://github.com/zhayujie/chatgpt-on-wechat/commit/4470d4c))
+- **DeepSeek module**: Independent DeepSeek Bot with dedicated `deepseek_api_key` config ([#2719](https://github.com/zhayujie/CowAgent/pull/2719)). Thanks [@6vision](https://github.com/6vision)
+- **Web console**: Slash command menu, input history, new model options, mobile optimization ([#2731](https://github.com/zhayujie/CowAgent/pull/2731)). Thanks [@zkjqd](https://github.com/zkjqd)
+- **Context loss**: Fix context loss after trimming ([393f0c0](https://github.com/zhayujie/CowAgent/commit/393f0c0))
+- **System prompt**: Fix system prompt not rebuilding on every turn ([13f5fde](https://github.com/zhayujie/CowAgent/commit/13f5fde))
+- **Gemini**: Fix missing model attribute in GoogleGeminiBot ([#2716](https://github.com/zhayujie/CowAgent/pull/2716)). Thanks [@cowagent](https://github.com/cowagent)
+- **WeChat channel**: Fix file send failures and filename loss ([6d9b7ba](https://github.com/zhayujie/CowAgent/commit/6d9b7ba), [45faa9c](https://github.com/zhayujie/CowAgent/commit/45faa9c))
+- **Docker**: Fix volume permissions, reduce image size ([3eb8348](https://github.com/zhayujie/CowAgent/commit/3eb8348), [4470d4c](https://github.com/zhayujie/CowAgent/commit/4470d4c))
 - **Security**: Fix Memory Content path traversal risk. Thanks [@August829](https://github.com/August829)

 ## 📦 Upgrade

 Run `cow update` or `./run.sh update` to upgrade, or pull the latest code and restart. See [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade).

-**Release Date**: 2026.04.01 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.4...master)
+**Release Date**: 2026.04.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.4...master)
--- a/docs/en/releases/v2.0.6.mdx
+++ b/docs/en/releases/v2.0.6.mdx
@@ -0,0 +1,83 @@
+---
+title: v2.0.6
+description: CowAgent 2.0.6 - Knowledge Base, Deep Dream Memory Distillation, Smart Context Compression, Web Console Multi-Session and More
+---
+
+## Project Renamed to CowAgent
+
+The repository has been officially renamed from `chatgpt-on-wechat` to **CowAgent**, evolving into a full-featured AI Agent assistant.
+
+- New URL: [github.com/zhayujie/CowAgent](https://github.com/zhayujie/CowAgent) — GitHub auto-redirects the old URL
+- CLI commands, config files, and documentation links remain compatible — no extra steps needed
+
+## 📚 Knowledge Base
+
+New personal knowledge base system — Agent can autonomously build and maintain structured knowledge, retrieving it on demand during conversations:
+
+- **Index-driven self-organizing structure**: Knowledge is stored in `knowledge/` directory, auto-organized by category, with each knowledge page as an independent Markdown file
+- **Auto-write**: Send files, links, or other knowledge to the Agent, or it will automatically create/update knowledge pages when valuable information is identified in conversation
+- **Hybrid retrieval**: Supports keyword full-text search and vector semantic retrieval, loading relevant knowledge on demand during conversations
+- **Visualization**: File tree browsing and knowledge graph visualization, with in-document links for direct navigation
+- **Command management**: `/knowledge` for stats, `/knowledge list` for directory structure, `/knowledge on|off` to toggle
+
+<img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="750" />
+
+
+Docs: [Knowledge Base](https://docs.cowagent.ai/en/knowledge)
+
+## 🌙 Deep Dream Memory Distillation
+
+A new memory consolidation mechanism that automatically distills scattered conversation memories into refined long-term memory daily:
+
+- **Three-tier memory flow**: Conversation context (short-term) → Daily memory (mid-term) → MEMORY.md (long-term), forming a complete memory lifecycle
+- **Auto-distillation**: Runs daily at 23:55, reads the day's daily memory and MEMORY.md, performs deduplication, merging, and pruning via LLM, outputting a refined MEMORY.md
+- **Dream diary**: Each distillation generates a narrative-style dream diary recording discoveries and insights, stored in `memory/dreams/`
+- **Manual trigger**: `/memory dream [N]` to manually trigger with configurable lookback days (default 3, max 30), with chat notification on completion
+- **Web console**: Memory management page now includes a "Dream Diary" tab for browsing all dream diaries
+
+Docs: [Deep Dream](https://docs.cowagent.ai/en/memory/deep-dream)
+
+<img src="https://cdn.link-ai.tech/doc/20260414120158.png" width="750" />
+
+## 🧠 Smart Context Compression
+
+When context exceeds limits, trimmed portions are summarized by LLM and asynchronously injected to maintain conversation continuity:
+
+- **Async LLM summary**: Trimmed messages are summarized into key information by LLM, written to daily memory files and injected into retained context
+- **Multi-model compatible**: Uses the primary model for summarization, compatible with Claude, OpenAI, MiniMax and other model message format requirements
+
+Docs: [Short-term Memory](https://docs.cowagent.ai/en/memory/context)
+
+## 💬 Web Console Upgrades
+
+Multiple enhancements to the Web console:
+
+- **Multi-session management**: Create and switch between independent sessions, sidebar session list with auto-generated and manually editable titles
+- **Password protection**: Set a login password via `web_console_password` config option
+- **Deep thinking**: Display model thinking process in Web console, controlled by `enable_thinking` config option
+- **Scheduled push**: Scheduled task results can be pushed to Web console
+- **Message copy**: One-click copy of raw Markdown content from AI reply bubbles
+- **Language toggle**: Top language switch button now shows current language for more intuitive interaction
+
+## 🤖 Model Updates
+
+- **Vision optimization**: Image recognition tool prefers the primary model with automatic multi-provider fallback. Docs: [Vision Tool](https://docs.cowagent.ai/en/tools/vision)
+- **MiniMax new model**: Added MiniMax-M2.7-highspeed model and MiniMax TTS voice synthesis support. Thanks @octo-patch
+- **Qwen**: Added qwen3.6-plus model support
+
+## 🐛 Other Improvements & Fixes
+
+- **Memory prompts**: `MEMORY.md` injected into system prompt by default, with refined memory retrieval and write trigger conditions for enhanced proactive writing
+- **System prompt**: Optimized system prompt style and tone guidance
+- **Browser tool**: Enhanced implicit interactive element detection
+- **File send**: Fixed common file types (tar.gz, zip, etc.) not being sent correctly. Thanks @6vision
+- **macOS compatibility**: Fixed network pre-check timeout compatibility issue. Thanks @Moliang Zhou
+- **Windows compatibility**: Fixed PowerShell compatibility, process updates, terminal encoding and other issues on Windows
+- **Python 3.13+**: Fixed missing `legacy-cgi` dependency for Python 3.13+
+- **WeChat channel**: Updated personal WeChat channel version
+
+## 📦 Upgrade
+
+Run `cow update` or `./run.sh update` to upgrade, or pull the latest code and restart. See [Upgrade Guide](https://docs.cowagent.ai/en/guide/upgrade).
+
+**Release Date**: 2026.04.14 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.5...master)
--- a/docs/en/skills/create.mdx
+++ b/docs/en/skills/create.mdx
@@ -54,5 +54,5 @@ Detailed instructions...
 | `metadata.always` | Always load (default false) |

 <Tip>
-  See the [Skill Creator documentation](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/skills/skill-creator/SKILL.md) for details.
+  See the [Skill Creator documentation](https://github.com/zhayujie/CowAgent/blob/master/skills/skill-creator/SKILL.md) for details.
 </Tip>
--- a/docs/en/tools/memory.mdx
+++ b/docs/en/tools/memory.mdx
@@ -1,9 +1,11 @@
 ---
-title: memory - Memory
-description: Search and read long-term memory
+title: memory - Memory & Knowledge
+description: Search and read long-term memory and knowledge base files
 ---

-The memory tool contains two sub-tools: `memory_search` (search memory) and `memory_get` (read memory files).
+The memory tool contains two sub-tools: `memory_search` (search memory) and `memory_get` (read memory or knowledge files).
+
+When the [knowledge base](/en/knowledge) feature is enabled, both tools also support accessing files under the `knowledge/` directory.

 ## Dependencies

@@ -11,7 +13,7 @@ No extra dependencies, available by default. Managed by the Agent Core memory sy

 ## memory_search

-Search historical memory with hybrid keyword and vector retrieval.
+Search historical memory and knowledge base content with hybrid keyword and vector retrieval.

 | Parameter | Type | Required | Description |
 | --- | --- | --- | --- |
@@ -19,11 +21,11 @@ Search historical memory with hybrid keyword and vector retrieval.

 ## memory_get

-Read the content of a specific memory file.
+Read the content of a specific memory or knowledge file.

 | Parameter | Type | Required | Description |
 | --- | --- | --- | --- |
-| `path` | string | Yes | Relative path to memory file (e.g. `MEMORY.md`, `memory/2026-01-01.md`) |
+| `path` | string | Yes | Relative path to the file (e.g. `MEMORY.md`, `memory/2026-01-01.md`, `knowledge/concepts/rag.md`) |
 | `start_line` | integer | No | Start line number |
 | `end_line` | integer | No | End line number |

@@ -34,3 +36,8 @@ The Agent automatically invokes memory tools in these scenarios:
 - When the user shares important information → stores to memory
 - When historical context is needed → searches relevant memory
 - When conversation reaches a certain length → extracts summary for storage
+- When discussing domain knowledge → retrieves relevant pages from the knowledge base
+
+<Note>
+  When `knowledge` is set to `false` in config, the tool descriptions and search scope automatically adjust to include only memory files.
+</Note>
--- a/docs/guide/manual-install.mdx
+++ b/docs/guide/manual-install.mdx
@@ -8,12 +8,12 @@ description: 手动部署 CowAgent（源码 / Docker）
 ### 1. 克隆项目代码

 ```bash
-git clone https://github.com/zhayujie/chatgpt-on-wechat
-cd chatgpt-on-wechat/
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
 ```

 <Tip>
-  若遇到网络问题可使用国内仓库地址：https://gitee.com/zhayujie/chatgpt-on-wechat
+  若遇到网络问题可使用国内仓库地址：https://gitee.com/zhayujie/CowAgent
 </Tip>

 ### 2. 安装依赖
@@ -173,5 +173,5 @@ sudo docker logs -f chatgpt-on-wechat
 | `agent_max_steps` | `AGENT_MAX_STEPS` | 单次任务最大决策步数 | `15` |

 <Tip>
-  全部配置项可在项目 [`config.py`](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/config.py) 文件中查看。Docker 部署时，配置项名称需转为大写环境变量格式。
+  全部配置项可在项目 [`config.py`](https://github.com/zhayujie/CowAgent/blob/master/config.py) 文件中查看。Docker 部署时，配置项名称需转为大写环境变量格式。
 </Tip>
--- a/docs/guide/quick-start.mdx
+++ b/docs/guide/quick-start.mdx
@@ -26,7 +26,7 @@ description: 使用脚本一键安装和管理 CowAgent

 1. 检查 Python 环境（需要 Python 3.7+）
 2. 安装必要工具（git、curl 等）
-3. 克隆项目代码到 `~/chatgpt-on-wechat`
+3. 克隆项目代码到 `~/CowAgent`
 4. 安装 Python 依赖和 Cow CLI
 5. 引导配置 AI 模型和通信渠道
 6. 启动服务
--- a/docs/intro/architecture.mdx
+++ b/docs/intro/architecture.mdx
@@ -11,25 +11,27 @@ CowAgent 的整体架构由以下核心模块组成：

 <img src="https://cdn.link-ai.tech/doc/68ef7b212c6f791e0e74314b912149f9-sz_5847990.png" alt="CowAgent Architecture" />

-### 核心模块说明
-
 | 模块 | 说明 |
 | --- | --- |
-| **Channels** | 消息通道层，负责接收和发送消息，支持 Web、飞书、钉钉、企微、公众号等 |
-| **Agent Core** | 智能体核心引擎，包括任务规划、记忆系统和技能引擎 |
-| **Tools** | 工具层，Agent 通过工具访问操作系统资源，内置 10+ 种工具 |
-| **Models** | 模型层，支持国内外主流大语言模型的统一接入 |
+| **Plan** | 理解用户意图，将复杂任务分解为多步骤计划，循环调用工具直到完成目标 |
+| **Memory** | 自动将重要信息持久化为核心记忆和日级记忆，支持关键词和向量混合检索，跨会话保持上下文连续性 |
+| **Knowledge** | 以主题维度组织结构化知识，Agent 自主整理有价值信息为 Markdown 页面，维护索引和交叉引用，构建持续增长的知识网络 |
+| **Tools** | Agent 访问操作系统资源的核心能力，内置文件读写、终端执行、浏览器操作、定时调度、记忆检索、联网搜索等 10+ 种工具 |
+| **Skills** | 加载和管理 Skills，支持从 Skill Hub、GitHub 等一键安装，或通过对话创建自定义技能 |
+| **Models** | 模型层，统一接入 OpenAI、Claude、Gemini、DeepSeek、MiniMax、GLM、Qwen 等国内外主流大语言模型 |
+| **Channels** | 消息通道层，负责接收和发送消息，支持 Web 控制台、微信、飞书、钉钉、企微、公众号等，统一消息协议 |
+| **CLI** | 命令行系统，提供终端命令（`cow`）和对话命令（`/`），支持进程管理、技能安装、配置修改、知识库管理等操作 |

 ## Agent 模式

 启用 Agent 模式后，CowAgent 会以自主智能体的方式运行，核心工作流如下：

-1. **接收消息** - 通过通道接收用户输入
-2. **理解意图** - 分析任务需求和上下文
-3. **规划任务** - 将复杂任务分解为多个步骤
-4. **调用工具** - 选择合适的工具执行每个步骤
-5. **记忆更新** - 将重要信息存入长期记忆
-6. **返回结果** - 将执行结果发送回用户
+1. **接收消息** — 通过通道接收用户输入
+2. **理解意图** — 分析任务需求和上下文
+3. **规划任务** — 将复杂任务分解为多个步骤
+4. **调用工具** — 选择合适的工具执行每个步骤
+5. **记忆与知识更新** — 将重要信息存入长期记忆，将结构化知识整理至知识库
+6. **返回结果** — 将执行结果发送回用户

 ## 工作空间

@@ -37,11 +39,14 @@ Agent 的工作空间默认位于 `~/cow` 目录，用于存储系统提示词

 ```
 ~/cow/
-├── system.md          # Agent system prompt
-├── user.md            # User profile
+├── SYSTEM.md          # Agent system prompt
+├── USER.md            # User profile
+├── MEMORY.md          # Core memory
 ├── memory/            # Long-term memory storage
-│   ├── core.md        # Core memory
-│   └── daily/         # Daily memory
+│   └── YYYY-MM-DD.md  # Daily memory
+├── knowledge/         # Personal knowledge base
+│   ├── index.md       # Knowledge index
+│   └── <category>/    # Topic-based pages
 └── skills/            # Custom skills
    ├── skill-1/
    └── skill-2/
@@ -64,7 +69,8 @@ Agent 的工作空间默认位于 `~/cow` 目录，用于存储系统提示词
  "agent_workspace": "~/cow",
  "agent_max_context_tokens": 40000,
  "agent_max_context_turns": 30,
-  "agent_max_steps": 15
+  "agent_max_steps": 15,
+  "enable_thinking": true
 }
 ```

@@ -72,6 +78,8 @@ Agent 的工作空间默认位于 `~/cow` 目录，用于存储系统提示词
 | --- | --- | --- |
 | `agent` | 是否启用 Agent 模式 | `true` |
 | `agent_workspace` | 工作空间路径 | `~/cow` |
-| `agent_max_context_tokens` | 最大上下文 token 数 | `40000` |
-| `agent_max_context_turns` | 最大上下文记忆轮次 | `30` |
-| `agent_max_steps` | 单次任务最大决策步数 | `15` |
+| `agent_max_context_tokens` | 最大上下文 token 数 | `50000` |
+| `agent_max_context_turns` | 最大上下文记忆轮次 | `20` |
+| `agent_max_steps` | 单次任务最大决策步数 | `20` |
+| `enable_thinking` | 是否启用深度思考，开启后 Web 端展示推理过程，关闭可加速响应 | `true` |
+| `knowledge` | 是否启用个人知识库 | `true` |
--- a/docs/intro/features.mdx
+++ b/docs/intro/features.mdx
@@ -1,27 +1,46 @@
 ---
 title: 功能介绍
-description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、浏览器工具详细说明
+description: CowAgent 长期记忆、个人知识库、任务规划、技能系统、CLI 命令、浏览器工具详细说明
 ---

 ## 1. 长期记忆

-> 记忆系统让 Agent 能够长期记住重要信息。Agent 会在用户分享偏好、决策、事实等重要信息时主动存储，也会在对话达到一定长度时自动提取摘要。记忆分为核心记忆、天级记忆，支持语义搜索和向量检索的混合检索模式。
+> 记忆系统让 Agent 能够长期记住重要信息，采用三层记忆流转架构：对话上下文（短期）→ 天级记忆（中期）→ MEMORY.md（长期），形成完整的记忆生命周期。

 第一次启动 Agent 时，Agent 会主动询问关键信息，并记录至工作空间（默认 `~/cow`）中的智能体设定、用户身份、记忆文件中。

-在后续的长期对话中，Agent 会在需要时智能记录或检索记忆，并对自身设定、用户偏好、记忆文件等进行不断更新，总结和记录经验和教训，真正实现自主思考和不断成长。
+在后续的长期对话中，Agent 会在需要时智能记录或检索记忆，并对自身设定、用户偏好、记忆文件等进行不断更新。每日自动执行 **梦境蒸馏（Deep Dream）**，将分散的天级记忆整合为精炼的长期记忆，同时生成叙事风格的梦境日记。

 <Frame>
  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
 </Frame>

-## 2. 任务规划和工具调用
+详细说明请参考 [长期记忆](/memory) 和 [梦境蒸馏](/memory/deep-dream)。
+
+## 2. 个人知识库
+
+> 知识库系统让 Agent 能够持续积累和组织结构化知识。与按时间线记录的记忆不同，知识库以主题为维度，将文章、对话洞察、学习材料等整理为互相关联的 Markdown 页面，形成持续增长的知识网络。
+
+Agent 会在对话中自动将有价值的信息整理为知识页面，维护交叉引用和索引，通过 Web 控制台可浏览文档和查看知识图谱。知识库存储在工作空间的 `~/cow/knowledge/` 目录下。
+
+- **自动整理**：Agent 在对话中自主提取和整理结构化知识，维护索引和交叉引用
+- **知识图谱**：基于页面间的交叉引用自动构建知识图谱，Web 控制台提供可视化关系图浏览
+- **对话联动**：Agent 回复中引用的知识文档链接可在 Web 控制台中直接点击跳转查看
+- **CLI 管理**：通过 `/knowledge` 命令查看统计、浏览目录，通过 `/knowledge on|off` 开关功能
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+详细说明请参考 [个人知识库](/knowledge)。
+
+## 3. 任务规划和工具调用

 工具是 Agent 访问操作系统资源的核心，Agent 会根据任务需求智能选择和调用工具，完成文件读写、命令执行、定时任务等各类操作。内置工具的实现在项目的 `agent/tools/` 目录下。

 **主要工具：** 文件读写编辑、Bash 终端、浏览器操作、文件发送、定时调度、记忆搜索、联网搜索、环境配置等。

-### 2.1 终端和文件访问
+### 3.1 终端和文件访问

 针对操作系统的终端和文件的访问能力，是最基础和核心的工具，其他很多工具或技能都是基于此进行扩展。用户可通过手机端与 Agent 交互，操作个人电脑或服务器上的资源：

@@ -29,15 +48,15 @@ description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、
  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
 </Frame>

-### 2.2 编程能力
+### 3.2 编程能力

 基于编程能力和系统访问能力，Agent 可以实现从信息搜索、图片等素材生成、编码、测试、部署、Nginx 配置修改、发布的 **Vibecoding 全流程**，通过手机端简单的一句命令完成应用的快速 demo：

 <Frame>
-  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+  <img src="https://cdn.link-ai.tech/doc/20260318211018.png" width="800" />
 </Frame>

-### 2.3 定时任务
+### 3.3 定时任务

 基于 `scheduler` 工具实现动态定时任务，支持**一次性任务、固定时间间隔、Cron 表达式**三种形式，任务触发可选择**固定消息发送**或 **Agent 动态任务**执行两种模式：

@@ -45,7 +64,7 @@ description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、
  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
 </Frame>

-### 2.4 浏览器操作
+### 3.4 浏览器操作

 内置 `browser` 工具，Agent 可控制浏览器访问网页、填写表单、点击元素、截图，支持动态 JS 渲染页面。运行 `cow install-browser` 一键安装，自动适配服务器（无头模式）和桌面环境：

@@ -53,7 +72,7 @@ description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、
  <img src="https://cdn.link-ai.tech/doc/20260401115728.png" width="750" />
 </Frame>

-### 2.5 环境变量管理
+### 3.5 环境变量管理

 技能所需的秘钥存储在环境变量文件中，由 `env_config` 工具进行管理，你可以通过对话的方式更新秘钥，工具内置安全保护和脱敏策略：

@@ -61,7 +80,7 @@ description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、
  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
 </Frame>

-## 3. 技能系统
+## 4. 技能系统

 技能系统为 Agent 提供无限的扩展性，每个 Skill 由说明文件、运行脚本（可选）、资源（可选）组成，描述如何完成特定类型的任务。通过 Skill 可以让 Agent 遵循说明完成复杂流程、调用各类工具或对接第三方系统。

@@ -71,7 +90,7 @@ description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、

 安装技能：`/skill install <名称>` 或 `cow skill install <名称>`，支持从 Skill Hub、GitHub、ClawHub、URL 等来源安装。

-### 3.1 创建技能
+### 4.1 创建技能

 通过 `skill-creator` 技能可以通过对话的方式快速创建技能。你可以让 Agent 将某个工作流程固化为技能，或者把任意接口文档和示例发送给 Agent，让他直接完成对接：

@@ -79,7 +98,7 @@ description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、
  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
 </Frame>

-### 3.2 搜索和图像识别
+### 4.2 搜索和图像识别

 - **联网搜索：** 内置 `web_search` 工具，支持多种搜索引擎，配置 `BOCHA_API_KEY` 或 `LINKAI_API_KEY` 后启用。
 - **图像识别：** 内置 `openai-image-vision` 技能，可使用 `gpt-4.1-mini`、`gpt-4.1` 等模型，依赖 `OPENAI_API_KEY`。
@@ -88,7 +107,7 @@ description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、
  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
 </Frame>

-### 3.3 技能广场
+### 4.3 技能广场

 访问 [skills.cowagent.ai](https://skills.cowagent.ai/) 浏览所有可用技能，或在对话中执行：

@@ -103,7 +122,7 @@ description: CowAgent 长期记忆、任务规划、技能系统、CLI 命令、
 <img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />


-## 4. CLI 命令系统
+## 5. CLI 命令系统

 CowAgent 提供两种命令交互方式，覆盖服务管理、技能安装、配置调整等日常运维操作：

--- a/docs/intro/index.mdx
+++ b/docs/intro/index.mdx
@@ -5,12 +5,12 @@ description: CowAgent - 基于大模型的超级AI助理

 <img src="https://cdn.link-ai.tech/doc/78c5dd674e2c828642ecc0406669fed7.png" alt="CowAgent" width="450px"/>

-**CowAgent** 是基于大模型的超级AI助理，能够主动思考和任务规划、操作计算机和外部资源、创造和执行Skills、拥有长期记忆并不断成长。
+**CowAgent** 是基于大模型的超级AI助理，能够主动思考和任务规划、操作计算机和外部资源、创造和执行Skills、拥有长期记忆和知识库并不断成长。

 CowAgent 支持灵活切换多种模型，能处理文本、语音、图片、文件等多模态消息，可接入微信、飞书、钉钉、企业微信应用、微信公众号、网页中使用，7×24小时运行于你的个人电脑或服务器中。

 <CardGroup cols={2}>
-  <Card title="GitHub" icon="github" href="https://github.com/zhayujie/chatgpt-on-wechat">
+  <Card title="GitHub" icon="github" href="https://github.com/zhayujie/CowAgent">
    开源代码仓库，欢迎 Star 和贡献
  </Card>
  <Card title="免部署在线体验" icon="cloud" href="https://link-ai.tech/cowagent/create">
@@ -25,14 +25,14 @@ CowAgent 支持灵活切换多种模型，能处理文本、语音、图片、
    能够理解复杂任务并自主规划执行，持续思考和调用各类工具和技能直到完成目标。
  </Card>
  <Card title="长期记忆" icon="database" href="/memory">
-    自动将对话记忆持久化至本地文件和数据库中，包括全局记忆和天级记忆，支持关键词及向量检索。
+    三层记忆流转（上下文→天级记忆→全局记忆），每日梦境蒸馏整理，支持关键词及向量检索。
+  </Card>
+  <Card title="个人知识库" icon="book" href="/knowledge">
+    自动整理结构化知识，支持知识图谱可视化，通过交叉引用构建持续增长的知识网络。
  </Card>
  <Card title="技能系统" icon="puzzle-piece" href="/skills/index">
    实现了Skills创建和运行的引擎，内置多种技能，并支持通过自然语言对话完成自定义Skills开发。
  </Card>
-  <Card title="多模态消息" icon="image" href="/channels/web">
-    支持对文本、图片、语音、文件等多类型消息进行解析、处理、生成、发送等操作。
-  </Card>
  <Card title="工具系统" icon="wrench" href="/tools/index">
    内置文件读写、终端执行、浏览器操作、定时任务、消息发送等工具，Agent 可自主调用工具完成复杂任务。
  </Card>
--- a/docs/ja/README.md
+++ b/docs/ja/README.md
@@ -1,13 +1,13 @@
 <p align="center"><img src="https://github.com/user-attachments/assets/eca9a9ec-8534-4615-9e0f-96c5ac1d10a3" alt="CowAgent" width="550" /></p>

 <p align="center">
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/chatgpt-on-wechat" alt="Latest release"></a>
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat/blob/master/LICENSE"><img src="https://img.shields.io/github/license/zhayujie/chatgpt-on-wechat" alt="License: MIT"></a>
-  <a href="https://github.com/zhayujie/chatgpt-on-wechat"><img src="https://img.shields.io/github/stars/zhayujie/chatgpt-on-wechat?style=flat-square" alt="Stars"></a> <br/>
-  [<a href="https://github.com/zhayujie/chatgpt-on-wechat/blob/master/README.md">中文</a>] | [<a href="https://github.com/zhayujie/chatgpt-on-wechat/blob/master/docs/en/README.md">English</a>] | [日本語]
+  <a href="https://github.com/zhayujie/CowAgent/releases/latest"><img src="https://img.shields.io/github/v/release/zhayujie/CowAgent" alt="Latest release"></a>
+  <a href="https://github.com/zhayujie/CowAgent/blob/master/LICENSE"><img src="https://img.shields.io/github/license/zhayujie/CowAgent" alt="License: MIT"></a>
+  <a href="https://github.com/zhayujie/CowAgent"><img src="https://img.shields.io/github/stars/zhayujie/CowAgent?style=flat-square" alt="Stars"></a> <br/>
+  [<a href="https://github.com/zhayujie/CowAgent/blob/master/README.md">中文</a>] | [<a href="https://github.com/zhayujie/CowAgent/blob/master/docs/en/README.md">English</a>] | [日本語]
 </p>

-**CowAgent** はLLMを搭載したAIスーパーアシスタントです。自律的なタスク計画、コンピュータや外部リソースの操作、Skillの作成・実行、長期記憶による継続的な成長が可能です。柔軟なモデル切り替えに対応し、テキスト・音声・画像・ファイルを処理でき、WeChat、Web、Feishu（飛書）、DingTalk（釘釘）、WeCom Bot（企業微信ボット）、WeComアプリ、WeChat公式アカウントに統合可能で、個人のPCやサーバー上で24時間365日稼働できます。
+**CowAgent** はLLMを搭載したAIスーパーアシスタントです。自律的なタスク計画、コンピュータや外部リソースの操作、Skillの作成・実行、長期記憶とパーソナルナレッジベースによる継続的な成長が可能です。柔軟なモデル切り替えに対応し、テキスト・音声・画像・ファイルを処理でき、WeChat、Web、Feishu（飛書）、DingTalk（釘釘）、WeCom Bot（企業微信ボット）、WeComアプリ、WeChat公式アカウントに統合可能で、個人のPCやサーバー上で24時間365日稼働できます。

 <p align="center">
  <a href="https://cowagent.ai/">🌐 ウェブサイト</a> &nbsp;·&nbsp;
@@ -22,7 +22,8 @@
 > CowAgentは、すぐに使えるAIスーパーアシスタントであると同時に、高い拡張性を持つAgentフレームワークでもあります。新しいモデルインターフェース、チャネル、組み込みツール、Skillシステムを拡張することで、さまざまなカスタマイズニーズに柔軟に対応できます。

 - ✅ **自律的タスク計画**: 複雑なタスクを理解し、自律的に実行計画を立て、目標達成までツールを呼び出しながら継続的に思考します。
- ✅ **長期記憶**: 会話の記憶をローカルファイルやデータベースに自動的に永続化します。コアメモリとデイリーメモリを含み、キーワード検索やベクトル検索に対応しています。
+- ✅ **長期記憶**: 会話の記憶をローカルファイルやデータベースに自動的に永続化します。コアメモリ、デイリーメモリ、Deep Dream 蒸留を含み、キーワード検索やベクトル検索に対応しています。
+- ✅ **パーソナルナレッジベース**: 構造化された知識を自動整理し、相互参照によるナレッジグラフを構築。Web での可視化ブラウジングと対話による管理をサポートします。
 - ✅ **Skillシステム**: Skillの作成・実行エンジンを実装。[Skill Hub](https://skills.cowagent.ai)、GitHubなどからSkillをインストールでき、会話を通じたカスタムSkill作成もサポートしています。
 - ✅ **ツールシステム**: ファイル読み書き、ターミナル実行、ブラウザ操作、スケジュールタスク、メッセージ送信などの組み込みツールを提供。Agentが自律的に呼び出して複雑なタスクを完了します。
 - ✅ **CLIシステム**: ターミナルコマンドとチャットコマンドを提供し、プロセス管理、Skillインストール、設定変更などの操作をサポートします。
@@ -42,19 +43,21 @@

 ## 更新履歴

-> **2026.04.01:** [v2.0.5](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.5) — Cow CLI、Skill Hubオープンソース化、ブラウザツール、WeCom Botスキャン作成など。
+> **2026.04.14:** [v2.0.6](https://github.com/zhayujie/CowAgent/releases/tag/2.0.6) — ナレッジベース、Deep Dream 記憶蒸留、スマートコンテキスト圧縮、Web コンソールアップグレード。

-> **2026.02.27:** [v2.0.2](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.2) — Webコンソールの全面刷新（ストリーミングチャット、モデル/Skill/メモリ/チャネル/スケジューラ/ログ管理）、マルチチャネル同時実行、セッション永続化、Gemini 3.1 Pro / Claude 4.6 Sonnet / Qwen3.5 Plusなど新モデル追加。
+> **2026.04.01:** [v2.0.5](https://github.com/zhayujie/CowAgent/releases/tag/2.0.5) — Cow CLI、Skill Hubオープンソース化、ブラウザツール、WeCom Botスキャン作成など。

-> **2026.02.13:** [v2.0.1](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.1) — 組み込みWeb検索ツール、スマートコンテキストトリミング、ランタイム情報の動的更新、Windows互換性、スケジューラのメモリ喪失やFeishu接続問題などの修正。
+> **2026.02.27:** [v2.0.2](https://github.com/zhayujie/CowAgent/releases/tag/2.0.2) — Webコンソールの全面刷新（ストリーミングチャット、モデル/Skill/メモリ/チャネル/スケジューラ/ログ管理）、マルチチャネル同時実行、セッション永続化、Gemini 3.1 Pro / Claude 4.6 Sonnet / Qwen3.5 Plusなど新モデル追加。

-> **2026.02.03:** [v2.0.0](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.0) — マルチステップタスク計画、長期記憶、組み込みツール、Skillフレームワーク、新モデル、チャネル最適化を備えたAIスーパーアシスタントへの全面アップグレード。
+> **2026.02.13:** [v2.0.1](https://github.com/zhayujie/CowAgent/releases/tag/2.0.1) — 組み込みWeb検索ツール、スマートコンテキストトリミング、ランタイム情報の動的更新、Windows互換性、スケジューラのメモリ喪失やFeishu接続問題などの修正。

-> **2025.05.23:** [v1.7.6](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.6) — Webチャネル最適化、AgentMeshマルチエージェントプラグイン、Baidu TTS、claude-4-sonnet/opus対応。
+> **2026.02.03:** [v2.0.0](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0) — マルチステップタスク計画、長期記憶、組み込みツール、Skillフレームワーク、新モデル、チャネル最適化を備えたAIスーパーアシスタントへの全面アップグレード。

-> **2025.04.11:** [v1.7.5](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.5) — wechatferryプロトコル、DeepSeekモデル、Tencent Cloud音声、ModelScope・Gitee-AI対応。
+> **2025.05.23:** [v1.7.6](https://github.com/zhayujie/CowAgent/releases/tag/1.7.6) — Webチャネル最適化、AgentMeshマルチエージェントプラグイン、Baidu TTS、claude-4-sonnet/opus対応。

-> **2024.12.13:** [v1.7.4](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/1.7.4) — Gemini 2.0モデル、Webチャネル、メモリリーク修正。
+> **2025.04.11:** [v1.7.5](https://github.com/zhayujie/CowAgent/releases/tag/1.7.5) — wechatferryプロトコル、DeepSeekモデル、Tencent Cloud音声、ModelScope・Gitee-AI対応。
+
+> **2024.12.13:** [v1.7.4](https://github.com/zhayujie/CowAgent/releases/tag/1.7.4) — Gemini 2.0モデル、Webチャネル、メモリリーク修正。

 全更新履歴: [リリースノート](https://docs.cowagent.ai/en/releases/overview)

@@ -83,8 +86,8 @@ irm https://cdn.link-ai.tech/code/cow/run.ps1 | iex
 **1. プロジェクトのクローン**

 ```bash
-git clone https://github.com/zhayujie/chatgpt-on-wechat
-cd chatgpt-on-wechat/
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
 ```

 **2. 依存関係のインストール**
@@ -232,16 +235,16 @@ Coding Planは各プロバイダーが提供する月額サブスクリプショ

 ## 🔎 よくある質問

-FAQ: <https://github.com/zhayujie/chatgpt-on-wechat/wiki/FAQs>
+FAQ: <https://github.com/zhayujie/CowAgent/wiki/FAQs>

 ## 🛠️ コントリビューション

-新しいチャネルの追加を歓迎します。[Feishuチャネル](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/channel/feishu/feishu_channel.py)を参考にしてください。また、新しいSkillのコントリビューションも歓迎します。[Skill作成ドキュメント](https://docs.cowagent.ai/ja/skills/create)を参照するか、[Skill Hub](https://skills.cowagent.ai/submit)に提出してください。
+新しいチャネルの追加を歓迎します。[Feishuチャネル](https://github.com/zhayujie/CowAgent/blob/master/channel/feishu/feishu_channel.py)を参考にしてください。また、新しいSkillのコントリビューションも歓迎します。[Skill作成ドキュメント](https://docs.cowagent.ai/ja/skills/create)を参照するか、[Skill Hub](https://skills.cowagent.ai/submit)に提出してください。

 ## ✉ お問い合わせ

-PRやIssueの提出を歓迎します。🌟 Starでプロジェクトをサポートしてください。ご質問がある場合は、[FAQリスト](https://github.com/zhayujie/chatgpt-on-wechat/wiki/FAQs)を確認するか、[Issues](https://github.com/zhayujie/chatgpt-on-wechat/issues)を検索してください。
+PRやIssueの提出を歓迎します。🌟 Starでプロジェクトをサポートしてください。ご質問がある場合は、[FAQリスト](https://github.com/zhayujie/CowAgent/wiki/FAQs)を確認するか、[Issues](https://github.com/zhayujie/CowAgent/issues)を検索してください。

 ## 🌟 コントリビューター

-![cow contributors](https://contrib.rocks/image?repo=zhayujie/chatgpt-on-wechat&max=1000)
+![cow contributors](https://contrib.rocks/image?repo=zhayujie/CowAgent&max=1000)
--- a/docs/ja/channels/web.mdx
+++ b/docs/ja/channels/web.mdx
@@ -38,6 +38,16 @@ Web コンソールは CowAgent のデフォルトチャネルです。起動後

 <img width="850" src="https://cdn.link-ai.tech/doc/20260227180120.png" />

+#### マルチセッション管理
+
+チャット画面はマルチセッション管理に対応しています。すべてのセッション記録は SQLite データベースに永続的に保存されます：
+
+- **セッション一覧**：左側の履歴アイコンをクリックしてセッション一覧パネルを展開/折りたたみでき、スクロールですべての履歴セッションを読み込めます
+- **AI によるタイトル生成**：新しいセッションの最初のやり取りが完了すると、自動的にモデルを呼び出して短い要約タイトルを生成します
+- **新規セッション**：セッション一覧上部の「新しい会話」ボタン、または入力エリアの `+` ボタンをクリックして新しいセッションを作成します
+- **セッション削除**：セッション項目の削除ボタンをクリックし、確認後にそのセッションとすべてのメッセージを完全に削除します
+- **コンテキストクリア**：入力エリアのクリアボタンをクリックすると、現在のセッションに区切り線が挿入されます。区切り線より上のメッセージは表示されたままですが、モデルのコンテキストには含まれなくなります
+
 ### モデル管理

 設定ファイルを手動で編集せずに、オンラインでモデル設定を管理できます：
--- a/docs/ja/cli/index.mdx
+++ b/docs/ja/cli/index.mdx
@@ -40,6 +40,10 @@ Service:
 Skills:
  skill     Manage skills (list / search / install / uninstall ...)

+Memory & Knowledge:
+  memory    Memory distillation (dream)
+  knowledge View knowledge base stats and structure
+
 Others:
  help      Show this help message
  version   Show version
@@ -55,6 +59,10 @@ Web コンソールや接続されたチャネルの会話で `/` を入力す
 | `/status` | サービスの状態と設定を表示 |
 | `/config` | 実行時設定の表示・変更 |
 | `/skill` | スキル管理（インストール、アンインストール、有効化、無効化など） |
+| `/memory dream [N]` | 記憶蒸留を手動トリガー（デフォルト 3 日、最大 30） |
+| `/knowledge` | ナレッジベースの統計情報を表示 |
+| `/knowledge list` | ナレッジベースのディレクトリ構造を表示 |
+| `/knowledge on\|off` | ナレッジベースの有効化・無効化 |
 | `/context` | 現在のセッションのコンテキスト情報を表示 |
 | `/context clear` | 現在のセッションのコンテキストをクリア |
 | `/logs` | 最近のログを表示 |
@@ -74,6 +82,8 @@ Web コンソールや接続されたチャネルの会話で `/` を入力す
 | logs | ✓ | ✓ |
 | config | ✗ | ✓ |
 | context | — | ✓ |
+| memory（サブコマンド） | ✗ | ✓ |
+| knowledge（サブコマンド） | ✓ | ✓ |
 | skill（サブコマンド） | ✓ | ✓ |
 | start / stop / restart | ✓ | ✗ |
 | update | ✓ | ✗ |
--- a/docs/ja/cli/memory-knowledge.mdx
+++ b/docs/ja/cli/memory-knowledge.mdx
@@ -0,0 +1,63 @@
+---
+title: 記憶とナレッジベース
+description: 記憶蒸留とナレッジベース管理コマンド
+---
+
+## memory
+
+Agent の長期記憶システムを管理します。
+
+### memory dream
+
+記憶蒸留（Deep Dream）を手動でトリガーします — 最近の日次記憶を整理し、MEMORY.md に統合し、夢日記を生成します。
+
+```text
+/memory dream [N]
+```
+
+- `N`：直近 N 日間の記憶を整理（デフォルト 3 日、最大 30 日）
+- バックグラウンドで非同期に実行され、完了するとチャットで通知されます
+- Agent の初期化不要 — 最初の会話前でも使用可能
+
+**例：**
+
+```text
+/memory dream       # 直近 3 日間を整理
+/memory dream 7     # 直近 7 日間を整理
+/memory dream 30    # 直近 30 日間を整理（全量）
+```
+
+Web コンソールでは、完了通知にクリック可能なリンクが含まれ、更新された MEMORY.md と夢日記を直接確認できます。
+
+<Tip>
+  システムは毎日 23:55 に自動で蒸留を実行します（lookback 1 日）。手動トリガーは、初回デプロイ後の履歴整理や、即座に記憶を更新したい場合に使用します。
+</Tip>
+
+## knowledge
+
+パーソナルナレッジベースの表示と管理。デフォルトで統計情報を表示します。
+
+```text
+/knowledge
+```
+
+### knowledge list
+
+ナレッジベースのディレクトリツリーを表示します。
+
+```text
+/knowledge list
+```
+
+### knowledge on / off
+
+ナレッジベースの有効化・無効化。無効化すると、ナレッジプロンプトとファイルインデックスが注入されなくなります。
+
+```text
+/knowledge on
+/knowledge off
+```
+
+<Note>
+  ターミナル CLI では `cow knowledge` と `cow knowledge list` が利用可能ですが、`on|off` はチャットでのみサポートされます（ランタイム効果が必要なため）。
+</Note>
--- a/docs/ja/guide/manual-install.mdx
+++ b/docs/ja/guide/manual-install.mdx
@@ -8,12 +8,12 @@ description: CowAgentの手動デプロイ（ソースコード / Docker）
 ### 1. プロジェクトをクローン

 ```bash
-git clone https://github.com/zhayujie/chatgpt-on-wechat
-cd chatgpt-on-wechat/
+git clone https://github.com/zhayujie/CowAgent
+cd CowAgent/
 ```

 <Tip>
-  ネットワークに問題がある場合は、ミラーを使用してください: https://gitee.com/zhayujie/chatgpt-on-wechat
+  ネットワークに問題がある場合は、ミラーを使用してください: https://gitee.com/zhayujie/CowAgent
 </Tip>

 ### 2. 依存パッケージをインストール
@@ -141,5 +141,5 @@ sudo docker logs -f chatgpt-on-wechat
 | `agent_max_steps` | タスクごとの最大判断ステップ数 | `15` |

 <Tip>
-  すべての設定オプションはプロジェクトの [`config.py`](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/config.py) に記載されています。
+  すべての設定オプションはプロジェクトの [`config.py`](https://github.com/zhayujie/CowAgent/blob/master/config.py) に記載されています。
 </Tip>
--- a/docs/ja/guide/quick-start.mdx
+++ b/docs/ja/guide/quick-start.mdx
@@ -26,7 +26,7 @@ Linux、macOS、Windowsに対応しています。Python 3.7〜3.12が必要で

 1. Python環境の確認（Python 3.7以上が必要）
 2. 必要なツールのインストール（git、curlなど）
-3. プロジェクトを `~/chatgpt-on-wechat` にクローン
+3. プロジェクトを `~/CowAgent` にクローン
 4. Pythonの依存パッケージと Cow CLI をインストール
 5. AIモデルとチャネルの対話式設定
 6. サービスの起動
--- a/docs/ja/intro/architecture.mdx
+++ b/docs/ja/intro/architecture.mdx
@@ -11,14 +11,16 @@ CowAgent のアーキテクチャは以下のコアモジュールで構成さ

 <img src="https://cdn.link-ai.tech/doc/68ef7b212c6f791e0e74314b912149f9-sz_5847990.png" alt="CowAgent Architecture" />

-### コアモジュール
-
 | モジュール | 説明 |
 | --- | --- |
-| **Channels** | メッセージの受信と送信を行うメッセージチャネル層。Web、Feishu（飛書）、DingTalk（釘釘）、WeCom（企業微信）、WeChat公式アカウントなどをサポート |
-| **Agent Core** | タスク計画、記憶システム、Skill エンジンを含む Agent エンジン |
-| **Tools** | Agent が OS リソースにアクセスするためのツール層。10 以上の組み込みツール |
-| **Models** | 主要な LLM への統一アクセスを提供するモデル層 |
+| **Plan** | ユーザーの意図を理解し、複雑なタスクをマルチステップの計画に分解、目標達成までツールを反復的に呼び出す |
+| **Memory** | 重要な情報をコアメモリとデイリーメモリとして自動永続化し、キーワードとベクトルのハイブリッド検索でセッション間の連続性を実現 |
+| **Knowledge** | トピック別に構造化された知識を整理。Agent が価値ある情報を Markdown ページとして自律的に整理し、インデックスと相互参照で成長するナレッジネットワークを構築 |
+| **Tools** | Agent が OS リソースにアクセスするための中核能力。ファイル読み書き、ターミナル、ブラウザ、スケジューラ、記憶検索、Web 検索など 10 以上の組み込みツール |
+| **Skills** | Skill の読み込み・管理。Skill Hub や GitHub からのワンクリックインストール、または会話を通じたカスタム Skill の作成をサポート |
+| **Models** | モデル層。OpenAI、Claude、Gemini、DeepSeek、MiniMax、GLM、Qwen など主要 LLM への統一アクセスを提供 |
+| **Channels** | メッセージチャネル層。Web コンソール、WeChat、Feishu、DingTalk、WeCom、公式アカウントなど複数チャネルを統一プロトコルでサポート |
+| **CLI** | コマンドラインシステム。ターミナルコマンド（`cow`）とチャットコマンド（`/`）で、プロセス管理、Skill インストール、設定変更、ナレッジベース管理などをサポート |

 ## Agent モードのワークフロー

@@ -28,7 +30,7 @@ Agent モードが有効な場合、CowAgent は以下のワークフローで
 2. **意図の理解** — タスク要件とコンテキストを分析
 3. **タスク計画** — 複雑なタスクを複数のステップに分解
 4. **ツール呼び出し** — 各ステップに適切なツールを選択・実行
-5. **記憶の更新** — 重要な情報を長期記憶に保存
+5. **記憶・ナレッジの更新** — 重要な情報を長期記憶に保存し、構造化された知識をナレッジベースに整理
 6. **結果の返却** — 実行結果をユーザーに送信

 ## ワークスペースのディレクトリ構成
@@ -39,9 +41,12 @@ Agent のワークスペースはデフォルトで `~/cow` にあり、シス
 ~/cow/
 ├── system.md          # Agent システムプロンプト
 ├── user.md            # ユーザープロフィール
+├── MEMORY.md          # コアメモリ
 ├── memory/            # 長期記憶ストレージ
-│   ├── core.md        # コアメモリ
-│   └── daily/         # デイリーメモリ
+│   └── YYYY-MM-DD.md  # デイリーメモリ
+├── knowledge/         # パーソナルナレッジベース
+│   ├── index.md       # ナレッジインデックス
+│   └── <category>/    # トピック別ページ
 └── skills/            # カスタム Skill
    ├── skill-1/
    └── skill-2/
@@ -75,3 +80,4 @@ Agent のワークスペースはデフォルトで `~/cow` にあり、シス
 | `agent_max_context_tokens` | 最大コンテキストトークン数 | `40000` |
 | `agent_max_context_turns` | 最大コンテキストターン数 | `30` |
 | `agent_max_steps` | タスクあたりの最大判断ステップ数 | `15` |
+| `knowledge` | パーソナルナレッジベースの有効化 | `true` |
--- a/docs/ja/intro/features.mdx
+++ b/docs/ja/intro/features.mdx
@@ -5,23 +5,42 @@ description: CowAgent の長期記憶、タスク計画、Skill システム、C

 ## 1. 長期記憶

-記憶システムにより、Agent は重要な情報を長期にわたって記憶できます。ユーザーが好みや決定、重要な事実を共有すると、Agent は自発的に情報を保存し、会話が一定の長さに達すると自動的に要約を抽出します。記憶はコアメモリとデイリーメモリに分かれており、キーワード検索とベクトル検索の両方をサポートするハイブリッド検索が可能です。
+記憶システムにより、Agent は重要な情報を長期にわたって記憶できます。三層記憶フローを採用：会話コンテキスト（短期）→ デイリーメモリ（中期）→ MEMORY.md（長期）、完全な記憶ライフサイクルを形成します。

 初回起動時、Agent はユーザーに重要な情報を自発的に尋ね、ワークスペース（デフォルト `~/cow`）に記録します。これには Agent の設定、ユーザーの身元情報、記憶ファイルが含まれます。

-その後の長期的な会話において、Agent は必要に応じてインテリジェントに記憶を保存・取得し、自身の設定やユーザーの好み、記憶ファイルを継続的に更新し、経験と教訓を要約します。これにより、真に自律的な思考と継続的な成長を実現しています。
+その後の長期的な会話において、Agent は必要に応じてインテリジェントに記憶を保存・取得し、自身の設定やユーザーの好み、記憶ファイルを継続的に更新します。毎日 **Deep Dream（夢境蒸留）** が自動実行され、散在するデイリーメモリを精製された長期記憶に統合し、ナラティブスタイルの夢日記を生成します。

 <Frame>
  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
 </Frame>

-## 2. タスク計画とツール活用
+詳細は [長期記憶](/ja/memory) と [Deep Dream](/ja/memory/deep-dream) を参照してください。
+
+## 2. パーソナルナレッジベース
+
+> ナレッジベースシステムにより、Agent は構造化された知識を継続的に蓄積・整理できます。時系列で記録されるメモリとは異なり、ナレッジベースはトピック別に整理され、記事、会話からの洞察、学習資料などを相互にリンクされた Markdown ページとして整理し、継続的に成長するナレッジネットワークを形成します。
+
+Agent は会話中に価値ある情報を自動的にナレッジページとして整理し、相互参照とインデックスを維持します。Web コンソールではドキュメントの閲覧とナレッジグラフの可視化が可能です。ナレッジはワークスペースの `~/cow/knowledge/` ディレクトリに保存されます。
+
+- **自動整理**：Agent が会話中に構造化された知識を自律的に抽出・整理し、インデックスと相互参照を維持
+- **ナレッジグラフ**：ページ間の相互参照から自動的にナレッジグラフを構築し、Web コンソールでインタラクティブな関係図として可視化
+- **チャット連携**：Agent の回答で参照されるナレッジドキュメントのリンクを Web コンソールで直接クリックして閲覧可能
+- **CLI 管理**：`/knowledge` コマンドで統計表示、ディレクトリ閲覧、`/knowledge on|off` で機能の切り替えが可能
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+詳細は [パーソナルナレッジベース](/ja/knowledge) を参照してください。
+
+## 3. タスク計画とツール活用

 ツールは Agent がオペレーティングシステムのリソースにアクセスするための中核です。Agent はタスク要件に基づいてインテリジェントにツールを選択・呼び出し、ファイルの読み書き、コマンド実行、スケジュールタスクなどを実行します。組み込みツールはプロジェクトの `agent/tools/` ディレクトリに実装されています。

 **主なツール：** ファイルの読み書き・編集、Bash ターミナル、ブラウザ操作、ファイル送信、スケジューラ、記憶検索、Web 検索、環境設定など。

-### 2.1 ターミナルとファイルアクセス
+### 3.1 ターミナルとファイルアクセス

 OS のターミナルとファイルシステムへのアクセスは、最も基本的かつ中核的な機能です。多くの他のツールや Skill はこの機能の上に構築されています。ユーザーはモバイルデバイスから Agent とやり取りし、パソコンやサーバーのリソースを操作できます：

@@ -29,15 +48,15 @@ OS のターミナルとファイルシステムへのアクセスは、最も
  <img src="https://cdn.link-ai.tech/doc/20260202181130.png" width="800" />
 </Frame>

-### 2.2 プログラミング能力
+### 3.2 プログラミング能力

 プログラミングとシステムアクセスを組み合わせることで、Agent は完全な **Vibecoding ワークフロー** を実行できます。情報検索、アセット生成、コーディング、テスト、デプロイ、Nginx 設定、公開まで、すべてスマートフォンからの一つのコマンドで実行可能です：

 <Frame>
-  <img src="https://cdn.link-ai.tech/doc/20260203121008.png" width="800" />
+  <img src="https://cdn.link-ai.tech/doc/20260318211018.png" width="800" />
 </Frame>

-### 2.3 スケジュールタスク
+### 3.3 スケジュールタスク

 `scheduler` ツールにより動的なスケジュールタスクが可能で、**ワンタイムタスク、固定間隔、Cron 式**をサポートしています。タスクは**固定メッセージ送信**または **Agent 動的タスク**実行としてトリガーできます：

@@ -45,7 +64,7 @@ OS のターミナルとファイルシステムへのアクセスは、最も
  <img src="https://cdn.link-ai.tech/doc/20260202195402.png" width="800" />
 </Frame>

-### 2.4 ブラウザ操作
+### 3.4 ブラウザ操作

 組み込みの `browser` ツールにより、Agent は Chromium ブラウザを制御して Web ページへのアクセス、フォームの入力、要素のクリック、スクリーンショットの撮影が可能です。動的 JS レンダリングページにも対応しています。`cow install-browser` でワンコマンドインストール、サーバー（ヘッドレス）とデスクトップ環境に自動対応します：

@@ -53,7 +72,7 @@ OS のターミナルとファイルシステムへのアクセスは、最も
  <img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="800" />
 </Frame>

-### 2.5 環境変数管理
+### 3.5 環境変数管理

 Skill が必要とするシークレットキーは環境変数ファイルに保存され、`env_config` ツールによって管理されます。会話を通じてシークレットを更新でき、セキュリティ保護とマスキング機能が組み込まれています：

@@ -61,7 +80,7 @@ Skill が必要とするシークレットキーは環境変数ファイルに
  <img src="https://cdn.link-ai.tech/doc/20260202234939.png" width="800" />
 </Frame>

-## 3. Skill システム
+## 4. Skill システム

 Skill システムは Agent に無限の拡張性を提供します。各 Skill は説明ファイル、実行スクリプト（任意）、リソース（任意）で構成され、特定のタイプのタスクを完了する方法を記述します。Skill により Agent は複雑なワークフローの指示に従い、ツールを呼び出し、サードパーティシステムと連携できます。

@@ -71,7 +90,7 @@ Skill システムは Agent に無限の拡張性を提供します。各 Skill

 Skill のインストール：`/skill install <名前>` または `cow skill install <名前>`。Skill Hub、GitHub、ClawHub、URL などからインストール可能。

-### 3.1 Skill の作成
+### 4.1 Skill の作成

 `skill-creator` Skill により、会話を通じて Skill を素早く作成できます。ワークフローを Skill としてコード化するよう Agent に依頼したり、API ドキュメントやサンプルを送信して Agent に直接連携を完成させることができます：

@@ -79,7 +98,7 @@ Skill のインストール：`/skill install <名前>` または `cow skill ins
  <img src="https://cdn.link-ai.tech/doc/20260202202247.png" width="800" />
 </Frame>

-### 3.2 Web 検索と画像認識
+### 4.2 Web 検索と画像認識

 - **Web 検索：** 組み込みの `web_search` ツールで、複数の検索エンジンをサポートします。`BOCHA_API_KEY` または `LINKAI_API_KEY` を設定して有効化してください。
 - **画像認識：** 組み込みの `openai-image-vision` Skill で、`gpt-4.1-mini`、`gpt-4.1` などのモデルをサポートします。`OPENAI_API_KEY` が必要です。
@@ -88,7 +107,7 @@ Skill のインストール：`/skill install <名前>` または `cow skill ins
  <img src="https://cdn.link-ai.tech/doc/20260202213219.png" width="800" />
 </Frame>

-### 3.3 Skill Hub
+### 4.3 Skill Hub

 [skills.cowagent.ai](https://skills.cowagent.ai/) で利用可能なすべての Skill を閲覧するか、会話内でコマンドを実行できます：

@@ -102,7 +121,7 @@ GitHub、ClawHub、LinkAI などサードパーティプラットフォームの

 <img src="https://cdn.link-ai.tech/doc/20260401110103.png" width="750" />

-## 4. CLI コマンドシステム
+## 5. CLI コマンドシステム

 CowAgent はサービス管理、Skill インストール、設定変更などをカバーする2つのコマンドインターフェースを提供します：

--- a/docs/ja/intro/index.mdx
+++ b/docs/ja/intro/index.mdx
@@ -9,8 +9,8 @@ description: CowAgent - LLM を活用した AI スーパーアシスタント

 CowAgent は自ら思考しタスクを計画し、コンピュータや外部リソースを操作し、Skill を作成・実行し、長期記憶により継続的に成長します。複数モデルの柔軟な切り替えをサポートし、テキスト、音声、画像、ファイルなどのマルチモーダルメッセージを処理でき、WeChat、Web、Feishu（飛書）、DingTalk（釘釘）、WeCom（企業微信）、WeChat公式アカウントに統合できます。お使いのパソコンやサーバー上で24時間365日稼働します。

-<Card title="GitHub" icon="github" href="https://github.com/zhayujie/chatgpt-on-wechat">
-  github.com/zhayujie/chatgpt-on-wechat
+<Card title="GitHub" icon="github" href="https://github.com/zhayujie/CowAgent">
+  github.com/zhayujie/CowAgent
 </Card>

 ## コア機能
@@ -20,7 +20,10 @@ CowAgent は自ら思考しタスクを計画し、コンピュータや外部
    複雑なタスクを理解し、自律的に実行計画を立て、目標が達成されるまで思考とツール呼び出しを続けます。ツールを通じてファイルシステム、ターミナル、ブラウザ、スケジューラなどのシステムリソースにアクセスできます。
  </Card>
  <Card title="長期記憶" icon="database" href="/ja/memory">
-    会話の記憶をローカルファイルやデータベースに自動的に永続化します。コアメモリとデイリーメモリを含み、キーワード検索とベクトル検索に対応しています。
+    三層記憶フロー（コンテキスト→デイリーメモリ→グローバルメモリ）、毎日 Deep Dream 蒸留で整理、キーワード検索とベクトル検索に対応。
+  </Card>
+  <Card title="ナレッジベース" icon="book" href="/ja/knowledge">
+    構造化された知識を自動整理し、ナレッジグラフの可視化をサポート。相互参照により継続的に成長するナレッジネットワークを構築します。
  </Card>
  <Card title="Skill システム" icon="puzzle-piece" href="/ja/skills/index">
    Skill の作成・実行エンジンを実装し、組み込み Skill を搭載。自然言語の会話を通じてカスタム Skill の開発もサポートしています。
@@ -72,7 +75,7 @@ CowAgent は自ら思考しタスクを計画し、コンピュータや外部

 ## 免責事項

-1. 本プロジェクトは [MIT License](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/LICENSE) に基づき、技術研究および学習を目的としています。利用者は現地の法律、規制、ポリシー、および企業の社内規程を遵守する必要があります。違法行為や権利侵害につながる利用は禁止されています。
+1. 本プロジェクトは [MIT License](https://github.com/zhayujie/CowAgent/blob/master/LICENSE) に基づき、技術研究および学習を目的としています。利用者は現地の法律、規制、ポリシー、および企業の社内規程を遵守する必要があります。違法行為や権利侵害につながる利用は禁止されています。
 2. Agent モードは通常のチャットモードよりも多くのトークンを消費します。効果とコストを考慮してモデルを選択してください。Agent はホスト OS にアクセスできるため、デプロイには十分注意してください。
 3. CowAgent はオープンソース開発に注力しており、いかなる暗号通貨の発行、認可、参加も行っておりません。

--- a/docs/ja/knowledge/index.mdx
+++ b/docs/ja/knowledge/index.mdx
@@ -0,0 +1,89 @@
+---
+title: パーソナルナレッジベース
+description: CowAgent のパーソナルナレッジベース — 構造化された知識の蓄積、自動整理、ナレッジグラフ
+---
+
+パーソナルナレッジベースは、Agent の長期的な構造化知識ストレージで、ワークスペースの `knowledge/` ディレクトリに保存されます。タイムラインで整理されるメモリとは異なり、ナレッジベースはトピック別にコンテンツを整理します。記事、会話のインサイト、学習資料が相互リンクされた Markdown ページとして構造化され、継続的に成長するナレッジネットワークを形成します。
+
+## コアコンセプト
+
+### ナレッジ vs メモリ
+
+| 次元 | ナレッジベース（knowledge/） | 長期記憶（memory/） |
+| --- | --- | --- |
+| 整理方法 | トピック別、相互リンク | タイムライン順、日付ファイル |
+| 書き込み | Agent が能動的に構造化 | コンテキストトリミング時に自動要約 |
+| コンテンツ | 精製された構造化知識 | 生の会話要約 |
+| 用途 | 学習ノート、技術ドキュメント、プロジェクト知識 | 会話履歴、イベント記録 |
+
+### ディレクトリ構造
+
+```
+~/cow/knowledge/
+├── index.md          # ナレッジインデックス、全ページのエントリポイント
+├── log.md            # 変更ログ、各書き込みの記録
+├── concepts/         # 概念的な知識
+│   └── machine-learning.md
+├── entities/         # エンティティ知識（人物、組織、ツール）
+│   └── openai.md
+└── sources/          # ソース知識（記事、論文）
+    └── llm-wiki.md
+```
+
+ディレクトリ構造は柔軟です — Agent は実際のコンテンツに基づいて適切なカテゴリディレクトリを自動作成します。ユーザーが整理方法をカスタマイズすることも可能です。
+
+## 自動整理
+
+ナレッジの書き込みは Agent の自律的な動作で、以下のシナリオでトリガーされます：
+
+- **ユーザーが記事やドキュメントを共有** — Agent が自動的にキー情報を抽出し、構造化されたナレッジページを作成
+- **会話から価値ある結論が生まれた場合** — Agent がインサイトをナレッジページに整理し、既存の知識とリンク
+- **ユーザーが明示的に整理を要求** — ユーザーは会話を通じて Agent にナレッジの整理・更新を指示可能
+
+各ナレッジページには関連ページへの相互参照リンクが含まれ、ナレッジグラフを段階的に構築します。
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/3ce92f78-1863-4820-8fa8-660c0f2b7f09" alt="会話によるナレッジの取り込み" />
+</Frame>
+
+## ナレッジ検索
+
+Agent は会話中に以下の方法でナレッジを検索できます：
+
+- **インデックス参照** — `knowledge/index.md` で関連ページを素早く特定
+- **セマンティック検索** — `memory_search` ツールでナレッジコンテンツをセマンティック検索
+- **直接読み取り** — `memory_get` ツールで特定のナレッジファイルを読み取り
+
+## Web コンソール
+
+Web コンソールには専用の「ナレッジ」モジュールがあり、以下をサポートします：
+
+- **ドキュメント閲覧** — ツリー形式のディレクトリ構造、検索・折りたたみ可能、クリックでコンテンツ表示
+- **ナレッジグラフ** — インタラクティブなグラフによるナレッジ間の関係を可視化
+- **チャット連携** — Agent の返信で参照されたナレッジドキュメントリンクはクリックで直接ナビゲーション
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/b7b9d6be-0ac1-4c65-803b-2c6b36bd59a7" alt="ナレッジドキュメント閲覧" />
+</Frame>
+
+<Frame>
+  <img src="https://gist.github.com/user-attachments/assets/44ae68ca-96cc-40b9-ab33-cdbec34c2379" alt="ナレッジグラフの可視化" />
+</Frame>
+
+## CLI コマンド
+
+`/knowledge` コマンドでナレッジベースを管理：
+
+| コマンド | 説明 |
+| --- | --- |
+| `/knowledge` | ナレッジベースの統計情報を表示 |
+| `/knowledge list` | ファイルディレクトリをツリー形式で表示 |
+| `/knowledge on` | ナレッジベース機能を有効化 |
+| `/knowledge off` | ナレッジベース機能を無効化 |
+
+## 設定
+
+| パラメータ | 説明 | デフォルト |
+| --- | --- | --- |
+| `knowledge` | パーソナルナレッジベースの有効/無効 | `true` |
+| `agent_workspace` | ワークスペースパス、ナレッジは `knowledge/` サブディレクトリに保存されます | `~/cow` |
--- a/docs/ja/memory/context.mdx
+++ b/docs/ja/memory/context.mdx
@@ -39,14 +39,15 @@ description: 会話コンテキスト — メッセージ管理、圧縮戦略

 - **最も古い半分** の完全なターンがトリミングされます（ツール呼び出しチェーンの完全性を保証）
 - トリミングされたメッセージは LLM によって要約され、**日次記憶ファイルに書き込まれます**
- 残りのターンはそのまま保持されます
+- LLM 要約が完了すると、保持されたコンテキストの最初のユーザーメッセージの先頭に要約が**注入**され、モデルが会話の文脈を維持できるようにします
+- 要約注入はバックグラウンドで非同期に実行され、次のターンから有効になります

 ### 3. トークン予算のトリミング

 ターンのトリミング後、トークン数がまだ予算を超えている場合：

 - **5 ターン未満の場合**：すべてのターンで**テキスト圧縮**を実行 — 各ターンは最初のユーザーテキストと最後の Agent 返信のみを保持し、中間のツール呼び出しチェーンを削除
- **5 ターン以上の場合**：**前半のターン**を再度トリミングし、破棄されたコンテンツも記憶に書き込まれます
+- **5 ターン以上の場合**：**前半のターン**を再度トリミングし、破棄されたコンテンツも記憶に書き込まれ、コンテキスト要約も注入されます

 ### 4. オーバーフロー緊急処理

--- a/docs/ja/memory/deep-dream.mdx
+++ b/docs/ja/memory/deep-dream.mdx
@@ -0,0 +1,90 @@
+---
+title: 夢境蒸留
+description: Deep Dream — 会話から永続記憶への自動蒸留メカニズム
+---
+
+夢境蒸留（Deep Dream）は CowAgent の記憶システムの中核的な整理メカニズムであり、散在する日次記憶を精錬された長期記憶に蒸留し、夢日記を生成します。
+
+## 記憶の流れ
+
+CowAgent の記憶は短期から長期まで 3 つの段階を経ます：
+
+```
+会話コンテキスト（短期）→ 日次記憶（中期）→ MEMORY.md（長期）
+```
+
+### 1. 会話 → 日次記憶
+
+会話コンテキストがトリミングされた時、または毎日のスケジュール要約時に、LLM が会話内容を重要イベントに要約し、日次記憶ファイル `memory/YYYY-MM-DD.md` に書き込みます。
+
+トリガー：
+- **コンテキストトリミング** — ターン数またはトークン制限を超えた時、トリミングされた内容が要約されます
+- **毎日のスケジュール** — 23:55 に自動トリガー
+- **API オーバーフロー** — 現在の会話要約の緊急保存
+
+### 2. 日次記憶 → MEMORY.md（蒸留）
+
+毎日の要約完了後、Deep Dream が自動的に蒸留を実行します：
+
+1. **材料の読み込み** — 現在の `MEMORY.md` + 当日の日次記憶
+2. **LLM 蒸留** — 重複排除、統合、剪定、新情報の抽出
+3. **MEMORY.md の上書き** — 精錬された長期記憶を出力
+4. **夢日記の生成** — 整理過程の発見と洞察を記録
+
+### 3. MEMORY.md の役割
+
+`MEMORY.md` は毎回の会話のシステムプロンプトに注入され、Agent がユーザーの好み、決定、重要な事実を常に把握できるようにします。そのため簡潔に保つ必要があり、Deep Dream は約 30 項目以内に制御します。
+
+## 蒸留ルール
+
+Deep Dream は以下の整理ルールに従います：
+
+| 操作 | 説明 |
+| --- | --- |
+| **統合・精錬** | 類似する複数の項目を 1 つの高密度な表現に統合 |
+| **新規抽出** | 日次記憶から好み、決定、人物、経験を抽出 |
+| **矛盾更新** | 新情報が古い項目と矛盾する場合、新情報を優先 |
+| **無効クリーン** | 一時的な記録、空白項目、フォーマット残留を削除 |
+| **冗長削除** | より精錬された表現でカバーされた古い項目を削除 |
+
+## 夢日記
+
+各蒸留で夢日記が生成され、`memory/dreams/YYYY-MM-DD.md` に保存されます。ナラティブスタイルで以下を記録します：
+
+- 発見された重複や矛盾
+- 日次記憶から抽出された新しい洞察
+- 実行されたクリーンアップと最適化
+- 全体的な観察
+
+夢日記は Web コンソールの「メモリ管理 → 夢日記」タブで確認できます。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414110032.png" width="800" />
+</Frame>
+
+## 手動トリガー
+
+毎日の自動実行に加えて、チャットで手動トリガーできます：
+
+```text
+/memory dream [N]
+```
+
+- `N`：直近 N 日間の記憶を整理（デフォルト 3 日、最大 30 日）
+- バックグラウンドで非同期に実行され、完了するとチャットで通知されます
+- Web 通知にはクリック可能なリンクが含まれ、MEMORY.md と夢日記を直接確認できます
+- Agent の初期化不要 — 最初の会話前でも使用可能
+
+<Tip>
+  初回デプロイ後は `/memory dream 30` を一度実行して、すべての履歴日次記憶を MEMORY.md に蒸留することをお勧めします。
+</Tip>
+
+## 安全メカニズム
+
+| メカニズム | 説明 |
+| --- | --- |
+| **コンテンツなしでスキップ** | 日次記憶がない場合、蒸留をスキップし空の上書きを回避 |
+| **入力重複排除** | スケジュールタスクで、入力材料が変更されていない場合自動スキップ |
+| **非同期実行** | 蒸留はバックグラウンドスレッドで実行、会話をブロックしない |
+| **順序保証** | スケジュールタスクで、日次フラッシュ完了後に蒸留を開始 |
+| **捏造禁止** | プロンプトで既存の材料のみに基づく整理を明示的に制約 |
--- a/docs/ja/memory/index.mdx
+++ b/docs/ja/memory/index.mdx
@@ -15,12 +15,17 @@ description: CowAgent の長期記憶システム — ファイル永続化、

 `~/cow/memory/` ディレクトリに保存され、日付で命名されます（例：`2026-03-08.md`）。日々の会話の要約と主要なイベントを記録します。空ファイルの生成を避けるため、最初の書き込み時にのみファイルが作成されます。

+### 夢日記（memory/dreams/YYYY-MM-DD.md）
+
+Deep Dream（記憶蒸留）プロセスの副産物で、各整理で発見された重複、統合操作、新しい洞察を記録します。`~/cow/memory/dreams/` ディレクトリに日付で命名されて保存されます。
+
 ## 自動書き込み

 Agent は以下のメカニズムにより、会話内容を長期記憶に自動的に永続化します：

- **コンテキストトリミング時** — 会話ターン数またはトークン数が設定上限を超えた場合、最も古い半分のコンテキストがトリミングされ、LLM によって要約されて日次記憶ファイルに書き込まれます
+- **コンテキストトリミング時** — 会話ターン数またはトークン数が設定上限を超えた場合、最も古い半分のコンテキストがトリミングされ、LLM によって要約されて日次記憶ファイルに書き込まれます。要約は保持されたコンテキストにも非同期で注入され、会話の連続性を維持します
 - **毎日のスケジュール要約** — 毎日 23:55 に自動的にフル要約がトリガーされ、アクティビティが少ない日でも記憶が保存されます（内容が変更されていない場合はスキップ）
+- **[夢境蒸留（Deep Dream）](/ja/memory/deep-dream)** — 毎日の要約完了後に自動実行され、日次記憶を MEMORY.md に蒸留し、夢日記を生成します
 - **API コンテキストオーバーフロー時** — モデル API がコンテキストオーバーフローエラーを返した場合、緊急措置として現在の会話要約が保存されます

 すべての記憶書き込みはバックグラウンドスレッドで非同期に実行され（LLM の要約 + ファイル書き込み）、通常の会話応答をブロックしません。
@@ -35,6 +40,7 @@ Agent は以下のメカニズムにより、会話内容を長期記憶に自
 | `user.md` | ユーザーの身元情報と好み |
 | `MEMORY.md` | コア記憶（長期） |
 | `memory/YYYY-MM-DD.md` | 日次記憶（オンデマンドで作成） |
+| `memory/dreams/YYYY-MM-DD.md` | 夢日記（Deep Dream で自動生成） |

 <Frame>
  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
--- a/docs/ja/models/index.mdx
+++ b/docs/ja/models/index.mdx
@@ -51,5 +51,5 @@ CowAgentは国内外の主要なLLMをサポートしています。モデルイ
 </CardGroup>

 <Tip>
-  モデル名の完全なリストについては、プロジェクトの[`common/const.py`](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/common/const.py)ファイルを参照してください。
+  モデル名の完全なリストについては、プロジェクトの[`common/const.py`](https://github.com/zhayujie/CowAgent/blob/master/common/const.py)ファイルを参照してください。
 </Tip>
--- a/docs/ja/releases/overview.mdx
+++ b/docs/ja/releases/overview.mdx
@@ -5,6 +5,7 @@ description: CowAgent バージョン履歴

 | バージョン | 日付 | 説明 |
 | --- | --- | --- |
+| [2.0.6](/ja/releases/v2.0.6) | 2026.04.14 | ナレッジベース、Deep Dream 記憶蒸留、スマートコンテキスト圧縮、Web コンソールアップグレード |
 | [2.0.5](/ja/releases/v2.0.5) | 2026.04.01 | Cow CLI、Skill Hub オープンソース、ブラウザツール、企業微信スキャン作成、その他改善 |
 | [2.0.4](/ja/releases/v2.0.4) | 2026.03.22 | 個人WeChatチャネル追加、新モデルサポート、日本語ドキュメント、スクリプトリファクタリングおよび複数修正 |
 | [2.0.2](/ja/releases/v2.0.2) | 2026.02.27 | Web Console アップグレード、マルチチャネル同時実行、セッション永続化 |
@@ -22,4 +23,4 @@ description: CowAgent バージョン履歴
 | 1.5.0 | 2023.11.10 | gpt-4-turbo、dall-e-3、tts マルチモーダル |
 | 1.0.0 | 2022.12.12 | プロジェクト作成、初の ChatGPT 統合 |

-完全な履歴は [GitHub Releases](https://github.com/zhayujie/chatgpt-on-wechat/releases) をご覧ください。
+完全な履歴は [GitHub Releases](https://github.com/zhayujie/CowAgent/releases) をご覧ください。
--- a/docs/ja/releases/v2.0.0.mdx
+++ b/docs/ja/releases/v2.0.0.mdx
@@ -5,7 +5,7 @@ description: CowAgent 2.0 - チャットボットから AI スーパーアシス

 CowAgent 2.0 は、チャットボットから **AI スーパーアシスタント** への包括的なアップグレードです。自律的な思考とタスク計画、長期記憶、コンピューターの操作、Skill の作成と実行が可能です。

-**リリース日**: 2026.02.03 | [GitHub Release](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.0)
+**リリース日**: 2026.02.03 | [GitHub Release](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0)

 ## 主な更新内容

@@ -60,4 +60,4 @@ CowAgent 2.0 は、チャットボットから **AI スーパーアシスタン

 ## コントリビューション

-[フィードバックの送信](https://github.com/zhayujie/chatgpt-on-wechat/issues) や [コードのコントリビューション](https://github.com/zhayujie/chatgpt-on-wechat/pulls) を歓迎します。
+[フィードバックの送信](https://github.com/zhayujie/CowAgent/issues) や [コードのコントリビューション](https://github.com/zhayujie/CowAgent/pulls) を歓迎します。
--- a/docs/ja/releases/v2.0.1.mdx
+++ b/docs/ja/releases/v2.0.1.mdx
@@ -3,34 +3,34 @@ title: v2.0.1
 description: CowAgent 2.0.1 - 組み込み Web Search、スマートコンテキスト管理、複数の修正
 ---

-**リリース日**: 2026.02.27 | [全変更履歴](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.0..2.0.1)
+**リリース日**: 2026.02.27 | [全変更履歴](https://github.com/zhayujie/CowAgent/compare/2.0.0..2.0.1)

 ## 新機能

- **組み込み Web Search ツール**: Web 検索を Agent の組み込みツールとして統合し、判断コストを削減 ([4f0ea5d](https://github.com/zhayujie/chatgpt-on-wechat/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
- **Claude Opus 4.6 モデル対応**: Claude Opus 4.6 モデルのサポートを追加 ([#2661](https://github.com/zhayujie/chatgpt-on-wechat/pull/2661))
- **企业微信の画像認識**: 企业微信チャネルでの画像メッセージ認識をサポート ([#2667](https://github.com/zhayujie/chatgpt-on-wechat/pull/2667))
+- **組み込み Web Search ツール**: Web 検索を Agent の組み込みツールとして統合し、判断コストを削減 ([4f0ea5d](https://github.com/zhayujie/CowAgent/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
+- **Claude Opus 4.6 モデル対応**: Claude Opus 4.6 モデルのサポートを追加 ([#2661](https://github.com/zhayujie/CowAgent/pull/2661))
+- **企业微信の画像認識**: 企业微信チャネルでの画像メッセージ認識をサポート ([#2667](https://github.com/zhayujie/CowAgent/pull/2667))

 ## 改善

- **スマートコンテキスト管理**: インテリジェントなコンテキストトリミング戦略により、チャットコンテキストのオーバーフローを解決し、トークン制限超過を防止 ([cea7fb7](https://github.com/zhayujie/chatgpt-on-wechat/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/chatgpt-on-wechat/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/chatgpt-on-wechat/issues/2663)
- **ランタイム情報の動的更新**: 動的関数によるシステムプロンプト内のタイムスタンプおよびその他のランタイム情報の自動更新 ([#2655](https://github.com/zhayujie/chatgpt-on-wechat/pull/2655), [#2657](https://github.com/zhayujie/chatgpt-on-wechat/pull/2657))
- **Skill プロンプトの最適化**: Skill システムプロンプト生成を改善し、ツールの説明を簡素化して Agent のパフォーマンスを向上 ([6c21833](https://github.com/zhayujie/chatgpt-on-wechat/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
- **GLM カスタム API Base URL**: GLM モデルのカスタム API Base URL をサポート ([#2660](https://github.com/zhayujie/chatgpt-on-wechat/pull/2660))
- **起動スクリプトの最適化**: `run.sh` スクリプトのインタラクションと設定フローを改善 ([#2656](https://github.com/zhayujie/chatgpt-on-wechat/pull/2656))
- **判断ステップのログ記録**: デバッグ用の Agent 判断ステップログを追加 ([cb303e6](https://github.com/zhayujie/chatgpt-on-wechat/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))
+- **スマートコンテキスト管理**: インテリジェントなコンテキストトリミング戦略により、チャットコンテキストのオーバーフローを解決し、トークン制限超過を防止 ([cea7fb7](https://github.com/zhayujie/CowAgent/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/CowAgent/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/CowAgent/issues/2663)
+- **ランタイム情報の動的更新**: 動的関数によるシステムプロンプト内のタイムスタンプおよびその他のランタイム情報の自動更新 ([#2655](https://github.com/zhayujie/CowAgent/pull/2655), [#2657](https://github.com/zhayujie/CowAgent/pull/2657))
+- **Skill プロンプトの最適化**: Skill システムプロンプト生成を改善し、ツールの説明を簡素化して Agent のパフォーマンスを向上 ([6c21833](https://github.com/zhayujie/CowAgent/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
+- **GLM カスタム API Base URL**: GLM モデルのカスタム API Base URL をサポート ([#2660](https://github.com/zhayujie/CowAgent/pull/2660))
+- **起動スクリプトの最適化**: `run.sh` スクリプトのインタラクションと設定フローを改善 ([#2656](https://github.com/zhayujie/CowAgent/pull/2656))
+- **判断ステップのログ記録**: デバッグ用の Agent 判断ステップログを追加 ([cb303e6](https://github.com/zhayujie/CowAgent/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))

 ## バグ修正

- **Scheduler の記憶喪失**: Scheduler ディスパッチャーによる記憶喪失を修正 ([a77a874](https://github.com/zhayujie/chatgpt-on-wechat/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
- **空のツール呼び出しと長い結果**: 空のツール呼び出しおよび過度に長いツール結果の処理を修正 ([0542700](https://github.com/zhayujie/chatgpt-on-wechat/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
- **OpenAI Function Call**: OpenAI モデルとの Function Call 互換性を修正 ([158c87a](https://github.com/zhayujie/chatgpt-on-wechat/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
- **Claude ツール名フィールド**: Claude モデルのレスポンスから余分なツール名フィールドを削除 ([eec10cb](https://github.com/zhayujie/chatgpt-on-wechat/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
- **MiniMax 推論**: MiniMax モデルの推論コンテンツ処理を最適化し、思考プロセスの出力を非表示化 ([c72cda3](https://github.com/zhayujie/chatgpt-on-wechat/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/chatgpt-on-wechat/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
- **GLM 思考プロセス**: GLM モデルの思考プロセス表示を非表示化 ([72b1cac](https://github.com/zhayujie/chatgpt-on-wechat/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
- **飞书の接続と SSL**: 飞书チャネルの SSL 証明書エラーおよび接続問題を修正 ([229b14b](https://github.com/zhayujie/chatgpt-on-wechat/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/chatgpt-on-wechat/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
- **model_type バリデーション**: 非文字列の `model_type` による `AttributeError` を修正 ([#2666](https://github.com/zhayujie/chatgpt-on-wechat/pull/2666))
+- **Scheduler の記憶喪失**: Scheduler ディスパッチャーによる記憶喪失を修正 ([a77a874](https://github.com/zhayujie/CowAgent/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
+- **空のツール呼び出しと長い結果**: 空のツール呼び出しおよび過度に長いツール結果の処理を修正 ([0542700](https://github.com/zhayujie/CowAgent/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
+- **OpenAI Function Call**: OpenAI モデルとの Function Call 互換性を修正 ([158c87a](https://github.com/zhayujie/CowAgent/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
+- **Claude ツール名フィールド**: Claude モデルのレスポンスから余分なツール名フィールドを削除 ([eec10cb](https://github.com/zhayujie/CowAgent/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
+- **MiniMax 推論**: MiniMax モデルの推論コンテンツ処理を最適化し、思考プロセスの出力を非表示化 ([c72cda3](https://github.com/zhayujie/CowAgent/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **GLM 思考プロセス**: GLM モデルの思考プロセス表示を非表示化 ([72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **飞书の接続と SSL**: 飞书チャネルの SSL 証明書エラーおよび接続問題を修正 ([229b14b](https://github.com/zhayujie/CowAgent/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/CowAgent/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
+- **model_type バリデーション**: 非文字列の `model_type` による `AttributeError` を修正 ([#2666](https://github.com/zhayujie/CowAgent/pull/2666))

 ## プラットフォーム互換性

- **Windows 互換性**: 複数のツールモジュールにおける Windows でのパス処理、ファイルエンコーディング、および `os.getuid()` の利用不可問題を修正 ([051ffd7](https://github.com/zhayujie/chatgpt-on-wechat/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/chatgpt-on-wechat/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
+- **Windows 互換性**: 複数のツールモジュールにおける Windows でのパス処理、ファイルエンコーディング、および `os.getuid()` の利用不可問題を修正 ([051ffd7](https://github.com/zhayujie/CowAgent/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/CowAgent/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
--- a/docs/ja/releases/v2.0.2.mdx
+++ b/docs/ja/releases/v2.0.2.mdx
@@ -3,7 +3,7 @@ title: v2.0.2
 description: CowAgent 2.0.2 - Web Console アップグレード、マルチチャネル同時実行、セッション永続化
 ---

-**リリース日**: 2026.02.27 | [全変更履歴](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.1...master)
+**リリース日**: 2026.02.27 | [全変更履歴](https://github.com/zhayujie/CowAgent/compare/2.0.1...master)

 ## ハイライト

@@ -53,7 +53,7 @@ Agent のランタイムログをリアルタイムで表示し、監視とト

 <img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />

-関連コミット: [f1a1413](https://github.com/zhayujie/chatgpt-on-wechat/commit/f1a1413), [c0702c8](https://github.com/zhayujie/chatgpt-on-wechat/commit/c0702c8), [394853c](https://github.com/zhayujie/chatgpt-on-wechat/commit/394853c), [1c71c4e](https://github.com/zhayujie/chatgpt-on-wechat/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/chatgpt-on-wechat/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/chatgpt-on-wechat/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/chatgpt-on-wechat/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d258b5)
+関連コミット: [f1a1413](https://github.com/zhayujie/CowAgent/commit/f1a1413), [c0702c8](https://github.com/zhayujie/CowAgent/commit/c0702c8), [394853c](https://github.com/zhayujie/CowAgent/commit/394853c), [1c71c4e](https://github.com/zhayujie/CowAgent/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/CowAgent/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/CowAgent/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/CowAgent/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5)

 ### 🔀 マルチチャネル同時実行

@@ -67,24 +67,24 @@ Agent のランタイムログをリアルタイムで表示し、監視とト
 }
 ```

-関連コミット: [4694594](https://github.com/zhayujie/chatgpt-on-wechat/commit/4694594), [7cce224](https://github.com/zhayujie/chatgpt-on-wechat/commit/7cce224), [7d258b5](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d258b5), [c9adddb](https://github.com/zhayujie/chatgpt-on-wechat/commit/c9adddb)
+関連コミット: [4694594](https://github.com/zhayujie/CowAgent/commit/4694594), [7cce224](https://github.com/zhayujie/CowAgent/commit/7cce224), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5), [c9adddb](https://github.com/zhayujie/CowAgent/commit/c9adddb)

 ### 💾 セッション永続化

 セッション履歴がローカルの SQLite データベースに永続化されるようになりました。サービス再起動後も会話コンテキストが自動的に復元されます。Web Console の過去の会話も復元されます。

-関連コミット: [29bfbec](https://github.com/zhayujie/chatgpt-on-wechat/commit/29bfbec), [9917552](https://github.com/zhayujie/chatgpt-on-wechat/commit/9917552), [925d728](https://github.com/zhayujie/chatgpt-on-wechat/commit/925d728)
+関連コミット: [29bfbec](https://github.com/zhayujie/CowAgent/commit/29bfbec), [9917552](https://github.com/zhayujie/CowAgent/commit/9917552), [925d728](https://github.com/zhayujie/CowAgent/commit/925d728)

 ## 新モデル

- **Gemini 3.1 Pro Preview**: `gemini-3.1-pro-preview` モデルのサポートを追加 ([52d7cad](https://github.com/zhayujie/chatgpt-on-wechat/commit/52d7cad))
- **Claude 4.6 Sonnet**: `claude-4.6-sonnet` モデルのサポートを追加 ([52d7cad](https://github.com/zhayujie/chatgpt-on-wechat/commit/52d7cad))
- **Qwen3.5 Plus**: `qwen3.5-plus` モデルのサポートを追加 ([e59a289](https://github.com/zhayujie/chatgpt-on-wechat/commit/e59a289))
- **MiniMax M2.5**: `Minimax-M2.5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **GLM-5**: `glm-5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **Kimi K2.5**: `kimi-k2.5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **Doubao 2.0 Code**: コーディング特化型 `doubao-2.0-code` モデルを追加 ([ab28ee5](https://github.com/zhayujie/chatgpt-on-wechat/commit/ab28ee5))
- **DashScope モデル**: 阿里云 DashScope モデル名のサポートを追加 ([ce58f23](https://github.com/zhayujie/chatgpt-on-wechat/commit/ce58f23))
+- **Gemini 3.1 Pro Preview**: `gemini-3.1-pro-preview` モデルのサポートを追加 ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Claude 4.6 Sonnet**: `claude-4.6-sonnet` モデルのサポートを追加 ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Qwen3.5 Plus**: `qwen3.5-plus` モデルのサポートを追加 ([e59a289](https://github.com/zhayujie/CowAgent/commit/e59a289))
+- **MiniMax M2.5**: `Minimax-M2.5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **GLM-5**: `glm-5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Kimi K2.5**: `kimi-k2.5` モデルのサポートを追加 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Doubao 2.0 Code**: コーディング特化型 `doubao-2.0-code` モデルを追加 ([ab28ee5](https://github.com/zhayujie/CowAgent/commit/ab28ee5))
+- **DashScope モデル**: 阿里云 DashScope モデル名のサポートを追加 ([ce58f23](https://github.com/zhayujie/CowAgent/commit/ce58f23))

 ## ウェブサイトとドキュメント

@@ -93,6 +93,6 @@ Agent のランタイムログをリアルタイムで表示し、監視とト

 ## バグ修正

- **Gemini 钉钉画像認識**: 钉钉チャネルで Gemini が画像マーカーを処理できない問題を修正 ([05a3304](https://github.com/zhayujie/chatgpt-on-wechat/commit/05a3304)) ([#2670](https://github.com/zhayujie/chatgpt-on-wechat/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
- **起動スクリプトの依存関係**: `run.sh` スクリプトの依存関係インストール問題を修正 ([b6fc9fa](https://github.com/zhayujie/chatgpt-on-wechat/commit/b6fc9fa))
- **bare except の整理**: より適切な例外処理のため `bare except` を `except Exception` に置換 ([adca89b](https://github.com/zhayujie/chatgpt-on-wechat/commit/adca89b)) ([#2674](https://github.com/zhayujie/chatgpt-on-wechat/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)
+- **Gemini 钉钉画像認識**: 钉钉チャネルで Gemini が画像マーカーを処理できない問題を修正 ([05a3304](https://github.com/zhayujie/CowAgent/commit/05a3304)) ([#2670](https://github.com/zhayujie/CowAgent/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
+- **起動スクリプトの依存関係**: `run.sh` スクリプトの依存関係インストール問題を修正 ([b6fc9fa](https://github.com/zhayujie/CowAgent/commit/b6fc9fa))
+- **bare except の整理**: より適切な例外処理のため `bare except` を `except Exception` に置換 ([adca89b](https://github.com/zhayujie/CowAgent/commit/adca89b)) ([#2674](https://github.com/zhayujie/CowAgent/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)
--- a/docs/ja/releases/v2.0.3.mdx
+++ b/docs/ja/releases/v2.0.3.mdx
@@ -11,7 +11,7 @@ description: CowAgent 2.0.3 - 企業微信スマートボットとQQチャネル

 接続ドキュメント：[企業微信スマートボット接続](https://docs.cowagent.ai/channels/wecom-bot)。

-関連コミット：[d4480b6](https://github.com/zhayujie/chatgpt-on-wechat/commit/d4480b6), [a42f31f](https://github.com/zhayujie/chatgpt-on-wechat/commit/a42f31f), [4ecd4df](https://github.com/zhayujie/chatgpt-on-wechat/commit/4ecd4df), [8b45d6c](https://github.com/zhayujie/chatgpt-on-wechat/commit/8b45d6c)
+関連コミット：[d4480b6](https://github.com/zhayujie/CowAgent/commit/d4480b6), [a42f31f](https://github.com/zhayujie/CowAgent/commit/a42f31f), [4ecd4df](https://github.com/zhayujie/CowAgent/commit/4ecd4df), [8b45d6c](https://github.com/zhayujie/CowAgent/commit/8b45d6c)

 ### QQ チャネル

@@ -19,18 +19,18 @@ QQ 公式ボット（`qq`）チャネルを追加しました。テキストと

 接続ドキュメント：[QQボット接続](https://docs.cowagent.ai/channels/qq)。

-関連コミット：[005a0e1](https://github.com/zhayujie/chatgpt-on-wechat/commit/005a0e1), [a4d54f5](https://github.com/zhayujie/chatgpt-on-wechat/commit/a4d54f5)
+関連コミット：[005a0e1](https://github.com/zhayujie/CowAgent/commit/005a0e1), [a4d54f5](https://github.com/zhayujie/CowAgent/commit/a4d54f5)

 ## 🖥️ Web コンソールのファイル入力・処理対応

 Web コンソールのチャット画面でファイルや画像のアップロードが可能になり、Agent に直接ファイルを送信して処理できます。また、Read ツールに Office ドキュメント（Word、Excel、PPT）の解析機能を追加しました。

-関連コミット：[30c6d9b](https://github.com/zhayujie/chatgpt-on-wechat/commit/30c6d9b)
+関連コミット：[30c6d9b](https://github.com/zhayujie/CowAgent/commit/30c6d9b)

 ## 🤖 新規モデル

- **GPT-5.4 シリーズ**：`gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano` モデルのサポートを追加 ([1623deb](https://github.com/zhayujie/chatgpt-on-wechat/commit/1623deb))
- **Gemini 3.1 Flash Lite Preview**：`gemini-3.1-flash-lite-preview` モデルのサポートを追加 ([ba915f2](https://github.com/zhayujie/chatgpt-on-wechat/commit/ba915f2))
+- **GPT-5.4 シリーズ**：`gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano` モデルのサポートを追加 ([1623deb](https://github.com/zhayujie/CowAgent/commit/1623deb))
+- **Gemini 3.1 Flash Lite Preview**：`gemini-3.1-flash-lite-preview` モデルのサポートを追加 ([ba915f2](https://github.com/zhayujie/CowAgent/commit/ba915f2))

 ## 💰 Coding Plan サポート

@@ -48,12 +48,12 @@ Web コンソールのチャット画面でファイルや画像のアップロ
 - 日次定期フラッシュのフォールバック機能を追加し、低アクティビティシナリオでのメモリ損失を防止
 - コンテキストメモリの損失問題を修正

-関連コミット：[022c13f](https://github.com/zhayujie/chatgpt-on-wechat/commit/022c13f), [c116235](https://github.com/zhayujie/chatgpt-on-wechat/commit/c116235)
+関連コミット：[022c13f](https://github.com/zhayujie/CowAgent/commit/022c13f), [c116235](https://github.com/zhayujie/CowAgent/commit/c116235)

 ## 🔧 ツールリファクタリング

- **画像認識**：画像認識（Image Vision）を Skill から内蔵 Tool にリファクタリングし、独立した画像ビジョンプロバイダー（Vision Provider）設定を追加。安定性と保守性を向上 ([a50fafa](https://github.com/zhayujie/chatgpt-on-wechat/commit/a50fafa), [3b8b562](https://github.com/zhayujie/chatgpt-on-wechat/commit/3b8b562))
- **Webスクレイピング**：Webスクレイピング（Web Fetch）を Skill から内蔵 Tool にリファクタリング。リモートドキュメントファイル（PDF、Word、Excel、PPT）のダウンロードと解析をサポート ([ccb9030](https://github.com/zhayujie/chatgpt-on-wechat/commit/ccb9030), [fa61744](https://github.com/zhayujie/chatgpt-on-wechat/commit/fa61744))
+- **画像認識**：画像認識（Image Vision）を Skill から内蔵 Tool にリファクタリングし、独立した画像ビジョンプロバイダー（Vision Provider）設定を追加。安定性と保守性を向上 ([a50fafa](https://github.com/zhayujie/CowAgent/commit/a50fafa), [3b8b562](https://github.com/zhayujie/CowAgent/commit/3b8b562))
+- **Webスクレイピング**：Webスクレイピング（Web Fetch）を Skill から内蔵 Tool にリファクタリング。リモートドキュメントファイル（PDF、Word、Excel、PPT）のダウンロードと解析をサポート ([ccb9030](https://github.com/zhayujie/CowAgent/commit/ccb9030), [fa61744](https://github.com/zhayujie/CowAgent/commit/fa61744))

 ## 🐳 Docker デプロイメントの最適化

@@ -64,28 +64,28 @@ Web コンソールのチャット画面でファイルや画像のアップロ

 ## ⚡ パフォーマンス最適化

- **起動高速化**：飛書チャネルで依存関係の遅延読み込みを採用し、4-10秒の起動遅延を回避 ([924dc79](https://github.com/zhayujie/chatgpt-on-wechat/commit/924dc79))
- **チャネルの安定性**：チャネル接続の安定性を最適化し、環境変数によるチャネル設定をサポート ([f1c04bc](https://github.com/zhayujie/chatgpt-on-wechat/commit/f1c04bc), [46d97fd](https://github.com/zhayujie/chatgpt-on-wechat/commit/46d97fd))
+- **起動高速化**：飛書チャネルで依存関係の遅延読み込みを採用し、4-10秒の起動遅延を回避 ([924dc79](https://github.com/zhayujie/CowAgent/commit/924dc79))
+- **チャネルの安定性**：チャネル接続の安定性を最適化し、環境変数によるチャネル設定をサポート ([f1c04bc](https://github.com/zhayujie/CowAgent/commit/f1c04bc), [46d97fd](https://github.com/zhayujie/CowAgent/commit/46d97fd))

 ## 🐛 バグ修正

- **bot_type 設定**：Agent モードでの `bot_type` 設定の受け渡し問題を修正 ([#2691](https://github.com/zhayujie/chatgpt-on-wechat/pull/2691)) Thanks [@Weikjssss](https://github.com/Weikjssss)
- **bot_type 優先順位**：Agent モードでの `bot_type` の解析優先順位を調整 ([#2692](https://github.com/zhayujie/chatgpt-on-wechat/pull/2692)) Thanks [@6vision](https://github.com/6vision)
- **智譜モデル設定**：智譜の `bot_type` 命名、Web コンソールの永続化、正規表現エスケープの問題を修正 ([#2693](https://github.com/zhayujie/chatgpt-on-wechat/pull/2693)) Thanks [@6vision](https://github.com/6vision)
- **OpenAI 互換レイヤー**：`openai_compat` レイヤーによる統一エラー処理 ([#2688](https://github.com/zhayujie/chatgpt-on-wechat/pull/2688)) Thanks [@JasonOA888](https://github.com/JasonOA888)
- **OpenAI 互換移行**：全モデル Bot の `openai_compat` 移行を完了 ([#2689](https://github.com/zhayujie/chatgpt-on-wechat/pull/2689))
- **Gemini ツール呼び出し**：Gemini モデルのツール呼び出しマッチング問題を修正 ([eda82ba](https://github.com/zhayujie/chatgpt-on-wechat/commit/eda82ba))
- **セッション並行処理**：セッション並行シナリオでの競合条件の問題を修正 ([9879878](https://github.com/zhayujie/chatgpt-on-wechat/commit/9879878))
- **履歴メッセージの復元**：履歴セッションメッセージの不完全な問題を修正。user/assistant のテキストメッセージのみを復元し、ツール呼び出しを除外 ([b788a3d](https://github.com/zhayujie/chatgpt-on-wechat/commit/b788a3d), [a33ce97](https://github.com/zhayujie/chatgpt-on-wechat/commit/a33ce97))
- **飛書グループチャット**：飛書グループチャットシナリオでの `bot_name` 依存を削除 ([b641bff](https://github.com/zhayujie/chatgpt-on-wechat/commit/b641bff))
- **Safari 互換性**：Safari ブラウザでの IME Enter キーによるメッセージ誤送信の問題を修正 ([0687916](https://github.com/zhayujie/chatgpt-on-wechat/commit/0687916))
- **Windows 互換性**：Windows での bash スタイル `$VAR` 環境変数を `%VAR%` に変換する問題を修正 ([7c67513](https://github.com/zhayujie/chatgpt-on-wechat/commit/7c67513))
- **MiniMax パラメータ**：MiniMax モデルの `max_tokens` 制限を追加 ([1767413](https://github.com/zhayujie/chatgpt-on-wechat/commit/1767413))
- **.gitignore 更新**：Python ディレクトリの無視ルールを追加 ([#2683](https://github.com/zhayujie/chatgpt-on-wechat/pull/2683)) Thanks [@pelioo](https://github.com/pelioo)
+- **bot_type 設定**：Agent モードでの `bot_type` 設定の受け渡し問題を修正 ([#2691](https://github.com/zhayujie/CowAgent/pull/2691)) Thanks [@Weikjssss](https://github.com/Weikjssss)
+- **bot_type 優先順位**：Agent モードでの `bot_type` の解析優先順位を調整 ([#2692](https://github.com/zhayujie/CowAgent/pull/2692)) Thanks [@6vision](https://github.com/6vision)
+- **智譜モデル設定**：智譜の `bot_type` 命名、Web コンソールの永続化、正規表現エスケープの問題を修正 ([#2693](https://github.com/zhayujie/CowAgent/pull/2693)) Thanks [@6vision](https://github.com/6vision)
+- **OpenAI 互換レイヤー**：`openai_compat` レイヤーによる統一エラー処理 ([#2688](https://github.com/zhayujie/CowAgent/pull/2688)) Thanks [@JasonOA888](https://github.com/JasonOA888)
+- **OpenAI 互換移行**：全モデル Bot の `openai_compat` 移行を完了 ([#2689](https://github.com/zhayujie/CowAgent/pull/2689))
+- **Gemini ツール呼び出し**：Gemini モデルのツール呼び出しマッチング問題を修正 ([eda82ba](https://github.com/zhayujie/CowAgent/commit/eda82ba))
+- **セッション並行処理**：セッション並行シナリオでの競合条件の問題を修正 ([9879878](https://github.com/zhayujie/CowAgent/commit/9879878))
+- **履歴メッセージの復元**：履歴セッションメッセージの不完全な問題を修正。user/assistant のテキストメッセージのみを復元し、ツール呼び出しを除外 ([b788a3d](https://github.com/zhayujie/CowAgent/commit/b788a3d), [a33ce97](https://github.com/zhayujie/CowAgent/commit/a33ce97))
+- **飛書グループチャット**：飛書グループチャットシナリオでの `bot_name` 依存を削除 ([b641bff](https://github.com/zhayujie/CowAgent/commit/b641bff))
+- **Safari 互換性**：Safari ブラウザでの IME Enter キーによるメッセージ誤送信の問題を修正 ([0687916](https://github.com/zhayujie/CowAgent/commit/0687916))
+- **Windows 互換性**：Windows での bash スタイル `$VAR` 環境変数を `%VAR%` に変換する問題を修正 ([7c67513](https://github.com/zhayujie/CowAgent/commit/7c67513))
+- **MiniMax パラメータ**：MiniMax モデルの `max_tokens` 制限を追加 ([1767413](https://github.com/zhayujie/CowAgent/commit/1767413))
+- **.gitignore 更新**：Python ディレクトリの無視ルールを追加 ([#2683](https://github.com/zhayujie/CowAgent/pull/2683)) Thanks [@pelioo](https://github.com/pelioo)
 - **AGENT.md の能動的進化**：システムプロンプトでの AGENT.md 更新ガイダンスを最適化。受動的な「ユーザーが変更した時に更新」から、会話中の性格やスタイルの変化を能動的に検出して自動更新するように改善

 ## 📦 アップグレード方法

 ソースコードデプロイの場合は `./run.sh update` でワンクリックアップグレードできます。または手動でコードをプルして再起動してください。詳細は [アップデートドキュメント](https://docs.cowagent.ai/guide/upgrade) を参照。

-**リリース日**：2026.03.18 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.2...master)
+**リリース日**：2026.03.18 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.2...master)
--- a/docs/ja/releases/v2.0.4.mdx
+++ b/docs/ja/releases/v2.0.4.mdx
@@ -16,40 +16,40 @@ description: CowAgent 2.0.4 - 個人WeChat チャネルの追加、新モデル

 接続ドキュメント：[WeChat 接続](https://docs.cowagent.ai/channels/weixin)。

-関連コミット：[ce89869](https://github.com/zhayujie/chatgpt-on-wechat/commit/ce89869), [a483ec0](https://github.com/zhayujie/chatgpt-on-wechat/commit/a483ec0), [c1421e0](https://github.com/zhayujie/chatgpt-on-wechat/commit/c1421e0)
+関連コミット：[ce89869](https://github.com/zhayujie/CowAgent/commit/ce89869), [a483ec0](https://github.com/zhayujie/CowAgent/commit/a483ec0), [c1421e0](https://github.com/zhayujie/CowAgent/commit/c1421e0)

 ## 🤖 新規モデル

 - **MiniMax-M2.7**：MiniMax-M2.7 モデルのサポートを追加
 - **GLM-5-Turbo**：智譜 glm-5-turbo モデルのサポートを追加

-関連コミット：[9192f6f](https://github.com/zhayujie/chatgpt-on-wechat/commit/9192f6f)
+関連コミット：[9192f6f](https://github.com/zhayujie/CowAgent/commit/9192f6f)

 ## 🔧 スクリプトリファクタリング

- **run.sh リファクタリング**：共通ロジックを抽出し、大量の重複コードを削除。スクリプトの行数を 600+ 行から 177 行に圧縮 ([49d8707](https://github.com/zhayujie/chatgpt-on-wechat/commit/49d8707))
- **実行権限**：`run.sh` ファイルの権限問題を修正 ([652156e](https://github.com/zhayujie/chatgpt-on-wechat/commit/652156e))
+- **run.sh リファクタリング**：共通ロジックを抽出し、大量の重複コードを削除。スクリプトの行数を 600+ 行から 177 行に圧縮 ([49d8707](https://github.com/zhayujie/CowAgent/commit/49d8707))
+- **実行権限**：`run.sh` ファイルの権限問題を修正 ([652156e](https://github.com/zhayujie/CowAgent/commit/652156e))

 ## ⚡ 最適化

- **リクエストヘッダー統一**：Agent の各サービス（Chat、Embedding、Vision、WebSearch 等）の外部リクエストに統一的な識別ヘッダーを追加 ([b4e711f](https://github.com/zhayujie/chatgpt-on-wechat/commit/b4e711f))
- **メッセージ自動修復**：メッセージプロトコルのフォールトトレランスを強化し、フォーマット異常なメッセージシーケンスを自動修復 ([b8b57e3](https://github.com/zhayujie/chatgpt-on-wechat/commit/b8b57e3))
+- **リクエストヘッダー統一**：Agent の各サービス（Chat、Embedding、Vision、WebSearch 等）の外部リクエストに統一的な識別ヘッダーを追加 ([b4e711f](https://github.com/zhayujie/CowAgent/commit/b4e711f))
+- **メッセージ自動修復**：メッセージプロトコルのフォールトトレランスを強化し、フォーマット異常なメッセージシーケンスを自動修復 ([b8b57e3](https://github.com/zhayujie/CowAgent/commit/b8b57e3))

 ## 🌍 日本語ドキュメント

 完全な日本語ドキュメントを追加しました。入門ガイド、チャネル接続、モデル設定などの主要セクションをカバーしています。Thanks [@Ikko Ashimine](https://github.com/ikoamu)

-関連コミット：[5487c0b](https://github.com/zhayujie/chatgpt-on-wechat/commit/5487c0b)
+関連コミット：[5487c0b](https://github.com/zhayujie/CowAgent/commit/5487c0b)

 ## 🐛 バグ修正

- **企業微信ボット互換性**：旧バージョンの `websocket-client` との互換性問題を修正し、統一的な WebSocket 互換レイヤーを追加 ([bc7f627](https://github.com/zhayujie/chatgpt-on-wechat/commit/bc7f627))
- **run.sh PID 取得**：`run.sh` でのプロセス PID 取得エラーを修正 ([9febb07](https://github.com/zhayujie/chatgpt-on-wechat/commit/9febb07))
- **飛書エンコーディング**：飛書チャネルのメッセージとログのエンコーディング問題を修正 ([7d0e156](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d0e156))
- **飛書設定**：`run.sh` での `feishu_bot_name` への冗長な依存を削除 ([1b5be1b](https://github.com/zhayujie/chatgpt-on-wechat/commit/1b5be1b))
+- **企業微信ボット互換性**：旧バージョンの `websocket-client` との互換性問題を修正し、統一的な WebSocket 互換レイヤーを追加 ([bc7f627](https://github.com/zhayujie/CowAgent/commit/bc7f627))
+- **run.sh PID 取得**：`run.sh` でのプロセス PID 取得エラーを修正 ([9febb07](https://github.com/zhayujie/CowAgent/commit/9febb07))
+- **飛書エンコーディング**：飛書チャネルのメッセージとログのエンコーディング問題を修正 ([7d0e156](https://github.com/zhayujie/CowAgent/commit/7d0e156))
+- **飛書設定**：`run.sh` での `feishu_bot_name` への冗長な依存を削除 ([1b5be1b](https://github.com/zhayujie/CowAgent/commit/1b5be1b))

 ## 📦 アップグレード方法

 ソースコードデプロイの場合は `./run.sh update` でワンクリックアップグレードできます。または手動でコードをプルして再起動してください。詳細は [アップデートドキュメント](https://docs.cowagent.ai/guide/upgrade) を参照。

-**リリース日**：2026.03.22 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.3...master)
+**リリース日**：2026.03.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.3...master)
--- a/docs/ja/releases/v2.0.5.mdx
+++ b/docs/ja/releases/v2.0.5.mdx
@@ -57,21 +57,21 @@ description: CowAgent 2.0.5 - Cow CLI、Skill Hub オープンソース、ブラ

 ドキュメント：[企業微信 Bot](https://docs.cowagent.ai/ja/channels/wecom-bot)

-PR：[#2735](https://github.com/zhayujie/chatgpt-on-wechat/pull/2735)。Thanks [@WecomTeam](https://github.com/WecomTeam)
+PR：[#2735](https://github.com/zhayujie/CowAgent/pull/2735)。Thanks [@WecomTeam](https://github.com/WecomTeam)

 ## 🐛 その他の改善と修正

- **DeepSeek モジュール**：独立 DeepSeek Bot、`deepseek_api_key` 専用設定対応（[#2719](https://github.com/zhayujie/chatgpt-on-wechat/pull/2719)）。Thanks [@6vision](https://github.com/6vision)
- **Web コンソール**：スラッシュコマンドメニュー、入力履歴、新モデル選択肢、モバイル最適化（[#2731](https://github.com/zhayujie/chatgpt-on-wechat/pull/2731)）。Thanks [@zkjqd](https://github.com/zkjqd)
- **コンテキスト**：トリミング後のコンテキスト喪失を修正（[393f0c0](https://github.com/zhayujie/chatgpt-on-wechat/commit/393f0c0)）
- **システムプロンプト**：毎ターン再構築されない問題を修正（[13f5fde](https://github.com/zhayujie/chatgpt-on-wechat/commit/13f5fde)）
- **Gemini**：GoogleGeminiBot の model 属性欠落を修正（[#2716](https://github.com/zhayujie/chatgpt-on-wechat/pull/2716)）。Thanks [@cowagent](https://github.com/cowagent)
- **WeChat チャネル**：ファイル送信失敗・ファイル名消失の修正（[6d9b7ba](https://github.com/zhayujie/chatgpt-on-wechat/commit/6d9b7ba)、[45faa9c](https://github.com/zhayujie/chatgpt-on-wechat/commit/45faa9c)）
- **Docker**：ボリューム権限修正、イメージサイズ削減（[3eb8348](https://github.com/zhayujie/chatgpt-on-wechat/commit/3eb8348)、[4470d4c](https://github.com/zhayujie/chatgpt-on-wechat/commit/4470d4c)）
+- **DeepSeek モジュール**：独立 DeepSeek Bot、`deepseek_api_key` 専用設定対応（[#2719](https://github.com/zhayujie/CowAgent/pull/2719)）。Thanks [@6vision](https://github.com/6vision)
+- **Web コンソール**：スラッシュコマンドメニュー、入力履歴、新モデル選択肢、モバイル最適化（[#2731](https://github.com/zhayujie/CowAgent/pull/2731)）。Thanks [@zkjqd](https://github.com/zkjqd)
+- **コンテキスト**：トリミング後のコンテキスト喪失を修正（[393f0c0](https://github.com/zhayujie/CowAgent/commit/393f0c0)）
+- **システムプロンプト**：毎ターン再構築されない問題を修正（[13f5fde](https://github.com/zhayujie/CowAgent/commit/13f5fde)）
+- **Gemini**：GoogleGeminiBot の model 属性欠落を修正（[#2716](https://github.com/zhayujie/CowAgent/pull/2716)）。Thanks [@cowagent](https://github.com/cowagent)
+- **WeChat チャネル**：ファイル送信失敗・ファイル名消失の修正（[6d9b7ba](https://github.com/zhayujie/CowAgent/commit/6d9b7ba)、[45faa9c](https://github.com/zhayujie/CowAgent/commit/45faa9c)）
+- **Docker**：ボリューム権限修正、イメージサイズ削減（[3eb8348](https://github.com/zhayujie/CowAgent/commit/3eb8348)、[4470d4c](https://github.com/zhayujie/CowAgent/commit/4470d4c)）
 - **セキュリティ**：Memory Content パストラバーサルリスクを修正。Thanks [@August829](https://github.com/August829)

 ## 📦 アップグレード

 `cow update` または `./run.sh update` でアップグレード、またはコードを手動で pull して再起動。詳細は[アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade)を参照。

-**リリース日**：2026.04.01 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.4...master)
+**リリース日**：2026.04.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.4...master)
--- a/docs/ja/releases/v2.0.6.mdx
+++ b/docs/ja/releases/v2.0.6.mdx
@@ -0,0 +1,83 @@
+---
+title: v2.0.6
+description: CowAgent 2.0.6 - ナレッジベース、Deep Dream 記憶蒸留、スマートコンテキスト圧縮、Web コンソールマルチセッションなど
+---
+
+## プロジェクト名を CowAgent に改称
+
+リポジトリが `chatgpt-on-wechat` から **CowAgent** に正式改称され、フル機能の AI Agent アシスタントへ進化しました。
+
+- 新アドレス：[github.com/zhayujie/CowAgent](https://github.com/zhayujie/CowAgent)、旧アドレスは GitHub が自動リダイレクト
+- CLI コマンド、設定ファイル、ドキュメントリンクはすべて互換性を維持、追加操作は不要
+
+## 📚 ナレッジベース
+
+新しいパーソナルナレッジベースシステム — Agent が構造化された知識を自律的に構築・維持し、会話中に必要に応じて検索・引用：
+
+- **インデックス駆動の自己組織構造**：ナレッジは `knowledge/` ディレクトリに保存、カテゴリ別に自動整理、各ナレッジページは独立した Markdown ファイル
+- **自動書き込み**：Agent にファイルやリンクなどの知識を送信、または会話で価値ある情報を識別した際にナレッジページを自動作成・更新
+- **ハイブリッド検索**：キーワード全文検索とベクトル意味検索をサポート、会話中に関連ナレッジをオンデマンドで読み込み
+- **ビジュアライゼーション**：ファイルツリー閲覧とナレッジグラフの可視化、ドキュメント内リンクで直接ナビゲーション
+- **コマンド管理**：`/knowledge` で統計表示、`/knowledge list` でディレクトリ構造、`/knowledge on|off` でオン・オフ
+
+<img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="750" />
+
+
+ドキュメント：[ナレッジベース](https://docs.cowagent.ai/ja/knowledge)
+
+## 🌙 Deep Dream 記憶蒸留
+
+散在する会話記憶を毎日自動的に精製された長期記憶へ蒸留する新しい記憶整理メカニズム：
+
+- **三層記憶フロー**：会話コンテキスト（短期）→ デイリーメモリ（中期）→ MEMORY.md（長期）、完全な記憶ライフサイクルを形成
+- **自動蒸留**：毎日 23:55 に定期実行、当日のデイリーメモリと MEMORY.md を読み取り、LLM で重複排除・統合・剪定を行い、精製された新しい MEMORY.md を出力
+- **夢日記**：各蒸留でナラティブスタイルの夢日記を生成、整理過程の発見と洞察を記録、`memory/dreams/` ディレクトリに保存
+- **手動トリガー**：`/memory dream [N]` で手動トリガー、整理日数を指定可能（デフォルト 3 日、最大 30 日）、完了後にチャットで通知
+- **Web コンソール**：記憶管理ページに「夢日記」タブを追加、すべての夢日記を閲覧可能
+
+ドキュメント：[Deep Dream](https://docs.cowagent.ai/ja/memory/deep-dream)
+
+<img src="https://cdn.link-ai.tech/doc/20260414120158.png" width="750" />
+
+## 🧠 スマートコンテキスト圧縮
+
+コンテキストが上限を超えた場合、トリミング部分を LLM で要約し非同期で注入、会話の連続性を維持：
+
+- **LLM 非同期要約**：トリミングされたメッセージを LLM がキー情報に要約、デイリーメモリファイルへの書き込みと保持コンテキストへの注入を同時実行
+- **マルチモデル対応**：メインモデルを優先使用、Claude、OpenAI、MiniMax など異なるモデルのメッセージ形式要件に対応
+
+ドキュメント：[短期記憶](https://docs.cowagent.ai/ja/memory/context)
+
+## 💬 Web コンソールアップグレード
+
+Web コンソールの複数機能を強化：
+
+- **マルチセッション管理**：独立セッションの作成と切り替え、サイドバーにセッションリスト表示、タイトルの自動生成と手動編集をサポート
+- **パスワード保護**：`web_console_password` 設定でコンソールにログインパスワードを設定可能
+- **深い思考**：Web 端でモデルの思考プロセスを表示、`enable_thinking` 設定で制御
+- **定期プッシュ**：定期タスクの結果を Web コンソールにプッシュ
+- **メッセージコピー**：AI 回答バブルから元の Markdown コンテンツをワンクリックコピー
+- **言語切替**：上部の言語切替ボタンが現在の言語を表示するように改善、より直感的な操作
+
+## 🤖 モデル関連
+
+- **視覚認識の最適化**：画像認識ツールがメインモデルを優先使用、複数プロバイダーの自動フォールバック対応。ドキュメント：[ビジョンツール](https://docs.cowagent.ai/ja/tools/vision)
+- **MiniMax 新モデル**：MiniMax-M2.7-highspeed モデルと MiniMax TTS 音声合成サポートを追加。Thanks @octo-patch
+- **通義千問**：qwen3.6-plus モデルサポートを追加
+
+## 🐛 その他の改善と修正
+
+- **記憶プロンプト最適化**：`MEMORY.md` をシステムプロンプトにデフォルト注入、記憶検索と書き込みのトリガー条件を精緻化、主動的な書き込み能力を強化
+- **システムプロンプト**：システムプロンプトのスタイルとトーンガイダンスを最適化
+- **ブラウザツール**：暗黙的なインタラクティブ要素の検出を強化
+- **ファイル送信**：汎用ファイルタイプ（tar.gz、zip 等）が正しく送信されない問題を修正。Thanks @6vision
+- **macOS 互換性**：ネットワークプリチェックタイムアウトの互換性問題を修正。Thanks @Moliang Zhou
+- **Windows 互換性**：Windows での PowerShell 互換性、プロセス更新、ターミナルエンコーディングなどの問題を修正
+- **Python 3.13+**：Python 3.13 以降で `legacy-cgi` 依存関係が不足する問題を修正
+- **個人 WeChat**：個人 WeChat チャネルバージョンを更新
+
+## 📦 アップグレード
+
+`cow update` または `./run.sh update` でアップグレード、またはコードを手動で pull して再起動。詳細は[アップグレードガイド](https://docs.cowagent.ai/ja/guide/upgrade)を参照。
+
+**リリース日**：2026.04.14 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.5...master)
--- a/docs/ja/skills/create.mdx
+++ b/docs/ja/skills/create.mdx
@@ -54,5 +54,5 @@ Detailed instructions...
 | `metadata.always` | 常に読み込む（デフォルトは false） |

 <Tip>
-  詳細は [Skill Creator のドキュメント](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/skills/skill-creator/SKILL.md)をご覧ください。
+  詳細は [Skill Creator のドキュメント](https://github.com/zhayujie/CowAgent/blob/master/skills/skill-creator/SKILL.md)をご覧ください。
 </Tip>
--- a/docs/ja/tools/memory.mdx
+++ b/docs/ja/tools/memory.mdx
@@ -1,9 +1,11 @@
 ---
-title: memory - メモリ
-description: 長期メモリの検索と読み取り
+title: memory - メモリ & ナレッジ
+description: 長期メモリとナレッジベースファイルの検索・読み取り
 ---

-メモリToolには `memory_search`（メモリ検索）と `memory_get`（メモリファイル読み取り）の2つのサブToolがあります。
+メモリToolには `memory_search`（メモリ検索）と `memory_get`（メモリまたはナレッジファイル読み取り）の2つのサブToolがあります。
+
+[ナレッジベース](/ja/knowledge) 機能が有効な場合、両ツールとも `knowledge/` ディレクトリのファイルへのアクセスもサポートします。

 ## 依存関係

@@ -11,7 +13,7 @@ description: 長期メモリの検索と読み取り

 ## memory_search

-キーワードとベクトルのハイブリッド検索で過去のメモリを検索します。
+キーワードとベクトルのハイブリッド検索で過去のメモリとナレッジベースの内容を検索します。

 | パラメータ | 型 | 必須 | 説明 |
 | --- | --- | --- | --- |
@@ -19,11 +21,11 @@ description: 長期メモリの検索と読み取り

 ## memory_get

-特定のメモリファイルの内容を読み取ります。
+特定のメモリファイルまたはナレッジファイルの内容を読み取ります。

 | パラメータ | 型 | 必須 | 説明 |
 | --- | --- | --- | --- |
-| `path` | string | はい | メモリファイルの相対パス（例：`MEMORY.md`、`memory/2026-01-01.md`） |
+| `path` | string | はい | ファイルの相対パス（例：`MEMORY.md`、`memory/2026-01-01.md`、`knowledge/concepts/rag.md`） |
 | `start_line` | integer | いいえ | 開始行番号 |
 | `end_line` | integer | いいえ | 終了行番号 |

@@ -34,3 +36,8 @@ Agentは以下のシナリオでメモリToolを自動的に呼び出します
 - ユーザーが重要な情報を共有した場合 → メモリに保存
 - 過去のコンテキストが必要な場合 → 関連するメモリを検索
 - 会話が一定の長さに達した場合 → 要約を抽出して保存
+- 専門知識について議論する場合 → ナレッジベースから関連ページを検索
+
+<Note>
+  設定で `knowledge` が `false` に設定されている場合、ツールの説明と検索範囲は自動的にメモリファイルのみに調整されます。
+</Note>
--- a/docs/knowledge/index.mdx
+++ b/docs/knowledge/index.mdx
@@ -0,0 +1,96 @@
+---
+title: 个人知识库
+description: CowAgent 的个人知识库系统 — 结构化知识沉淀、自动整理与知识图谱
+---
+
+个人知识库是 Agent 的长期结构化知识存储，保存在工作空间的 `knowledge/` 目录下。与按时间线组织的记忆不同，知识库以主题为维度，将用户分享的文章、对话中的洞察、学习材料等整理为互相关联的 Markdown 页面，形成可持续增长的知识网络。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="800" />
+</Frame>
+
+## 核心概念
+
+### 知识 vs 记忆
+
+| 维度 | 知识库（knowledge/） | 长期记忆（memory/） |
+| --- | --- | --- |
+| 组织方式 | 按主题分类、互相关联 | 按时间线、日期文件 |
+| 写入方式 | Agent 主动整理结构化内容 | 上下文裁剪时自动摘要 |
+| 内容特点 | 提炼后的结构化知识 | 原始对话摘要 |
+| 典型用途 | 学习笔记、技术文档、项目知识 | 对话历史、事件记录 |
+
+### 目录结构
+
+```
+~/cow/knowledge/
+├── index.md          # 知识索引，所有页面的入口
+├── log.md            # 变更日志，记录每次写入
+├── concepts/         # 概念类知识
+│   └── machine-learning.md
+├── entities/         # 实体类知识（人物、组织、工具）
+│   └── openai.md
+└── sources/          # 来源类知识（文章、论文）
+    └── llm-wiki.md
+```
+
+目录结构是灵活的 — Agent 会根据实际内容自动创建合适的分类目录。用户也可以通过对话的方式自定义目录组织方式。
+
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413110104.png" width="800" />
+</Frame>
+
+## 自动整理
+
+知识库的写入是 Agent 的自主行为，在以下场景中触发：
+
+- **用户分享文章或文档** — Agent 自动提取关键信息，创建结构化知识页面
+- **对话产生有价值的结论** — Agent 将洞察整理为知识页面，并与已有知识建立关联
+- **用户主动要求整理** — 用户可以通过对话指导 Agent 组织和更新知识
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/17aad553d3e9e428c52ff9dc31726fda.png" width="800" />
+</Frame>
+
+
+每个知识页面都包含与其他页面的交叉引用链接，逐步构建起一个知识图谱。
+
+## 知识检索
+
+Agent 在对话中可以通过以下方式检索知识：
+
+- **索引查阅** — 通过 `knowledge/index.md` 快速定位相关知识页面
+- **语义搜索** — 通过 `memory_search` 工具对知识库内容进行语义检索
+- **直接读取** — 通过 `memory_get` 工具读取特定知识文件
+
+## Web 控制台
+
+Web 控制台提供了专用的「知识」模块，支持：
+
+- **文档浏览** — 树状目录结构，可搜索、可折叠，点击查看文档内容
+- **知识图谱** — 可视化展示知识之间的关联关系，节点可直接跳转至文档
+- **对话联动** — Agent 回复中引用的知识文档链接可直接点击跳转查看
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260413105402.png" width="800" />
+</Frame>
+
+
+## CLI 命令
+
+通过 `/knowledge` 命令管理知识库：
+
+| 命令 | 说明 |
+| --- | --- |
+| `/knowledge` | 显示知识库统计信息 |
+| `/knowledge list` | 以树状结构显示文件目录 |
+| `/knowledge on` | 开启知识库功能 |
+| `/knowledge off` | 关闭知识库功能 |
+
+## 相关配置
+
+| 参数 | 说明 | 默认值 |
+| --- | --- | --- |
+| `knowledge` | 是否启用个人知识库功能 | `true` |
+| `agent_workspace` | 工作空间路径，知识库存储在此目录的 `knowledge/` 子目录下 | `~/cow` |
--- a/docs/memory/context.mdx
+++ b/docs/memory/context.mdx
@@ -39,14 +39,15 @@ description: 对话上下文 — 消息管理、压缩策略和上下文操作

 - 裁剪 **最早一半** 的完整轮次（保证工具调用链的完整性）
 - 被裁剪的消息会通过 LLM 总结后**写入当天的日级记忆文件**
- 剩余轮次保持不变
+- LLM 摘要完成后，同时将摘要**注入到保留消息的第一条用户消息开头**，帮助模型在后续对话中保持上下文连贯性
+- 摘要注入在后台异步完成，不阻塞当前回复；注入的摘要在下一轮对话时生效

 ### 3. Token 预算裁剪

 裁剪轮次后，如果 token 数仍超出预算：

 - **轮次 < 5 时**：对所有轮次进行**文本压缩** — 每轮只保留第一条用户文本和最后一条 Agent 回复，去掉中间的工具调用链
- **轮次 ≥ 5 时**：再次裁剪**前半轮次**，被丢弃内容同样写入记忆
+- **轮次 ≥ 5 时**：再次裁剪**前半轮次**，被丢弃内容同样写入记忆并注入上下文摘要

 ### 4. 溢出应急处理

--- a/docs/memory/deep-dream.mdx
+++ b/docs/memory/deep-dream.mdx
@@ -0,0 +1,94 @@
+---
+title: 梦境蒸馏
+description: Deep Dream — 从对话到永久记忆的自动蒸馏机制
+---
+
+梦境蒸馏（Deep Dream）是 CowAgent 记忆系统的核心整理机制，负责将分散的天级记忆蒸馏为精炼的长期记忆，并生成梦境日记。
+
+## 记忆流转
+
+CowAgent 的记忆从短期到长期经历三个阶段：
+
+```
+对话上下文（短期）→ 天级记忆（中期）→ MEMORY.md（长期）
+```
+
+### 1. 对话 → 天级记忆
+
+当对话上下文被裁剪或每日定时总结时，系统使用 LLM 将对话内容摘要为关键事件，写入当天的天级记忆文件 `memory/YYYY-MM-DD.md`。
+
+触发时机：
+- **上下文裁剪** — 轮次或 token 超限时，裁剪的内容被总结写入
+- **每日定时** — 23:55 自动触发全量总结
+- **API 溢出** — 紧急保存当前对话摘要
+
+### 2. 天级记忆 → MEMORY.md（蒸馏）
+
+每日总结完成后，Deep Dream 自动执行蒸馏：
+
+1. **读取材料** — 当前 `MEMORY.md` + 当天的天级记忆
+2. **LLM 蒸馏** — 去重、合并、修剪、提取新信息
+3. **覆写 MEMORY.md** — 输出精炼后的长期记忆
+4. **生成梦境日记** — 记录整理过程的发现和洞察
+
+### 3. MEMORY.md 的作用
+
+`MEMORY.md` 会被注入到每次对话的系统提示词中，让 Agent 始终了解用户的偏好、决策和关键事实。因此它必须保持精炼——Deep Dream 会控制在约 30 条以内。
+
+## 蒸馏规则
+
+Deep Dream 遵循以下整理规则：
+
+| 操作 | 说明 |
+| --- | --- |
+| **合并提炼** | 含义相近的多条合并为一条高密度表述 |
+| **新增萃取** | 从天级记忆中提取偏好、决策、人物、经验等 |
+| **冲突更新** | 新信息与旧条目矛盾时，以新信息为准 |
+| **清理无效** | 删除临时性记录、空白条目、格式残留 |
+| **删除冗余** | 已被更精炼表述涵盖的旧条目删除 |
+
+## 梦境日记
+
+每次蒸馏会生成一篇梦境日记，保存在 `memory/dreams/YYYY-MM-DD.md`，用叙事风格记录：
+
+- 发现了哪些重复或矛盾
+- 从天级记忆中提取了什么新洞察
+- 做了哪些清理和优化
+- 整体感受和观察
+
+梦境日记可在 Web 控制台的「记忆管理 → 梦境日记」tab 中查看。
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414110032.png" width="800" />
+</Frame>
+
+## 手动触发
+
+除了每日自动执行外，也可以在对话中手动触发：
+
+```text
+/memory dream [N]
+```
+
+- `N`：整理近 N 天的记忆（默认 3 天，最大 30 天）
+- 蒸馏在后台异步执行，完成后在对话中通知结果
+- Web 端通知包含可点击链接，直接跳转查看 MEMORY.md 和梦境日记
+- 无需 Agent 初始化，首次对话前即可使用
+
+<Frame>
+  <img src="https://cdn.link-ai.tech/doc/20260414120158.png" width="800" />
+</Frame>
+
+<Tip>
+  首次部署后可以手动执行一次 `/memory dream 30`，将历史天级记忆全量蒸馏到 MEMORY.md。
+</Tip>
+
+## 安全机制
+
+| 机制 | 说明 |
+| --- | --- |
+| **无新内容跳过** | 没有天级记忆时不执行蒸馏，避免空覆写 |
+| **输入去重** | 定时任务中，输入材料未变化时自动跳过 |
+| **异步执行** | 蒸馏在后台线程运行，不阻塞对话 |
+| **顺序保证** | 定时任务中，天级 flush 全部完成后才启动蒸馏 |
+| **禁止编造** | 提示词明确约束只能基于已有材料整理，不得推测或添加 |
--- a/docs/memory/index.mdx
+++ b/docs/memory/index.mdx
@@ -15,12 +15,17 @@ description: CowAgent 的长期记忆系统 — 文件持久化、自动写入

 存储在 `~/cow/memory/` 目录下，按日期命名（如 `2026-03-08.md`），记录每天的对话摘要和关键事件。仅在首次写入时创建，避免生成空文件。

+### 梦境日记（memory/dreams/YYYY-MM-DD.md）
+
+Deep Dream（记忆蒸馏）过程的副产物，记录每次整理的发现、去重合并操作和新洞察。存储在 `~/cow/memory/dreams/` 目录下，按日期命名。
+
 ## 自动写入

 Agent 通过以下机制自动将对话内容持久化为长期记忆：

- **上下文裁剪时** — 当对话轮次或 token 超出配置上限时，裁剪最早一半的上下文，使用 LLM 将被裁剪的内容总结为关键信息写入当天记忆文件
+- **上下文裁剪时** — 当对话轮次或 token 超出配置上限时，裁剪最早一半的上下文，使用 LLM 将被裁剪的内容总结为关键信息写入当天记忆文件，并将摘要异步注入到保留的上下文中，帮助模型保持对话连贯性
 - **每日定时总结** — 每天 23:55 自动触发一次全量总结，防止低活跃日无记忆留存（内容无变化时自动跳过）
+- **[梦境蒸馏（Deep Dream）](/memory/deep-dream)** — 每日总结完成后自动执行，将天级记忆蒸馏合并到 MEMORY.md，并生成梦境日记
 - **API 上下文溢出时** — 当模型 API 返回上下文溢出错误时，紧急保存当前对话摘要

 所有记忆写入均在后台异步执行（LLM 总结 + 文件写入），不阻塞正常对话回复。
@@ -44,6 +49,7 @@ Agent 会在对话中根据需要自动触发记忆检索，将相关历史信
 | `user.md` | 用户身份信息和偏好 |
 | `MEMORY.md` | 核心记忆（长期） |
 | `memory/YYYY-MM-DD.md` | 日级记忆（按需创建） |
+| `memory/dreams/YYYY-MM-DD.md` | 梦境日记（Deep Dream 自动生成） |

 <Frame>
  <img src="https://cdn.link-ai.tech/doc/20260203000455.png" width="800" />
--- a/docs/models/index.mdx
+++ b/docs/models/index.mdx
@@ -57,5 +57,5 @@ CowAgent 支持国内外主流厂商的大语言模型，模型接口实现在


 <Tip>
-  全部模型名称可参考项目 [`common/const.py`](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/common/const.py) 文件。
+  全部模型名称可参考项目 [`common/const.py`](https://github.com/zhayujie/CowAgent/blob/master/common/const.py) 文件。
 </Tip>
--- a/docs/releases/overview.mdx
+++ b/docs/releases/overview.mdx
@@ -5,6 +5,7 @@ description: CowAgent 版本更新历史

 | 版本 | 日期 | 说明 |
 | --- | --- | --- |
+| [2.0.6](/releases/v2.0.6) | 2026.04.14 | 项目更名、知识库系统、梦境记忆蒸馏、上下文智能压缩、Web 控制台多会话及多项优化 |
 | [2.0.5](/releases/v2.0.5) | 2026.04.01 | Cow CLI、Skill Hub 开源、浏览器工具、企微扫码创建、多项优化和修复 |
 | [2.0.4](/releases/v2.0.4) | 2026.03.22 | 新增个人微信通道、新模型支持、日文文档、脚本重构及多项修复 |
 | [2.0.3](/releases/v2.0.3) | 2026.03.18 | 新增企微智能机器人和 QQ 通道、支持Coding Plan、新增多个模型、Web端文件处理、记忆系统升级 |
@@ -25,4 +26,4 @@ description: CowAgent 版本更新历史
 | 1.5.0 | 2023.11.10 | gpt-4-turbo、dall-e-3、tts 多模态 |
 | 1.0.0 | 2022.12.12 | 项目创建，首次接入 ChatGPT 模型 |

-更多历史版本请查看 [GitHub Releases](https://github.com/zhayujie/chatgpt-on-wechat/releases)。
+更多历史版本请查看 [GitHub Releases](https://github.com/zhayujie/CowAgent/releases)。
--- a/docs/releases/v2.0.0.mdx
+++ b/docs/releases/v2.0.0.mdx
@@ -5,7 +5,7 @@ description: CowAgent 2.0 - 从聊天机器人到超级智能助理的全面升

 CowAgent 2.0 实现了从聊天机器人到**超级智能助理**的全面升级！现在它能够主动思考和规划任务、拥有长期记忆、操作计算机和外部资源、创造和执行技能，真正理解你并和你一起成长。

-**发布日期**：2026.02.03 | [GitHub Release](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.0)
+**发布日期**：2026.02.03 | [GitHub Release](https://github.com/zhayujie/CowAgent/releases/tag/2.0.0)

 ## 重点更新

@@ -102,4 +102,4 @@ Agent 根据任务需求智能选择和调用工具，完成各类复杂操作

 ## 参与共建

-2.0 版本后，项目将持续升级 Agent 能力、拓展接入渠道、内置工具、技能系统，降低模型成本和提升安全性。欢迎 [提出反馈](https://github.com/zhayujie/chatgpt-on-wechat/issues) 和 [贡献代码](https://github.com/zhayujie/chatgpt-on-wechat/pulls)。
+2.0 版本后，项目将持续升级 Agent 能力、拓展接入渠道、内置工具、技能系统，降低模型成本和提升安全性。欢迎 [提出反馈](https://github.com/zhayujie/CowAgent/issues) 和 [贡献代码](https://github.com/zhayujie/CowAgent/pulls)。
--- a/docs/releases/v2.0.1.mdx
+++ b/docs/releases/v2.0.1.mdx
@@ -3,34 +3,34 @@ title: v2.0.1
 description: CowAgent 2.0.1 - 内置 Web Search、智能上下文管理、多项修复
 ---

-**发布日期**：2026.02 | [GitHub Release](https://github.com/zhayujie/chatgpt-on-wechat/releases/tag/2.0.1) | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.0..2.0.1)
+**发布日期**：2026.02 | [GitHub Release](https://github.com/zhayujie/CowAgent/releases/tag/2.0.1) | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.0..2.0.1)

 ## 新特性

- **内置 Web Search 工具**：将网络搜索作为 Agent 内置工具集成，降低决策成本 ([4f0ea5d](https://github.com/zhayujie/chatgpt-on-wechat/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
- **Claude Opus 4.6 模型支持**：新增对 Claude Opus 4.6 模型的支持 ([#2661](https://github.com/zhayujie/chatgpt-on-wechat/pull/2661))
- **企业微信图片消息识别**：支持企业微信渠道的图片消息识别功能 ([#2667](https://github.com/zhayujie/chatgpt-on-wechat/pull/2667))
+- **内置 Web Search 工具**：将网络搜索作为 Agent 内置工具集成，降低决策成本 ([4f0ea5d](https://github.com/zhayujie/CowAgent/commit/4f0ea5d7568d61db91ff69c91c429e785fd1b1c2))
+- **Claude Opus 4.6 模型支持**：新增对 Claude Opus 4.6 模型的支持 ([#2661](https://github.com/zhayujie/CowAgent/pull/2661))
+- **企业微信图片消息识别**：支持企业微信渠道的图片消息识别功能 ([#2667](https://github.com/zhayujie/CowAgent/pull/2667))

 ## 优化

- **智能上下文管理**：解决聊天上下文溢出问题，新增智能上下文裁剪策略，防止 token 超限 ([cea7fb7](https://github.com/zhayujie/chatgpt-on-wechat/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/chatgpt-on-wechat/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/chatgpt-on-wechat/issues/2663)
- **运行时信息动态更新**：通过动态函数方案实现系统提示词中时间戳等运行时信息的自动更新 ([#2655](https://github.com/zhayujie/chatgpt-on-wechat/pull/2655), [#2657](https://github.com/zhayujie/chatgpt-on-wechat/pull/2657))
- **Skill 提示词优化**：改进 Skill 系统提示词生成逻辑，简化工具描述，提升 Agent 表现 ([6c21833](https://github.com/zhayujie/chatgpt-on-wechat/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
- **智谱 AI 自定义 API Base URL**：支持智谱 AI 配置自定义 API Base URL ([#2660](https://github.com/zhayujie/chatgpt-on-wechat/pull/2660))
- **启动脚本优化**：改进 `run.sh` 脚本的交互体验和配置流程 ([#2656](https://github.com/zhayujie/chatgpt-on-wechat/pull/2656))
- **决策轮次日志**：新增 Agent 决策轮次的日志记录，便于调试 ([cb303e6](https://github.com/zhayujie/chatgpt-on-wechat/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))
+- **智能上下文管理**：解决聊天上下文溢出问题，新增智能上下文裁剪策略，防止 token 超限 ([cea7fb7](https://github.com/zhayujie/CowAgent/commit/cea7fb7490c53454602bf05955a0e9f059bcf0fd), [8acf2db](https://github.com/zhayujie/CowAgent/commit/8acf2dbdfe713b84ad74b761b7f86674b1c1904d)) [#2663](https://github.com/zhayujie/CowAgent/issues/2663)
+- **运行时信息动态更新**：通过动态函数方案实现系统提示词中时间戳等运行时信息的自动更新 ([#2655](https://github.com/zhayujie/CowAgent/pull/2655), [#2657](https://github.com/zhayujie/CowAgent/pull/2657))
+- **Skill 提示词优化**：改进 Skill 系统提示词生成逻辑，简化工具描述，提升 Agent 表现 ([6c21833](https://github.com/zhayujie/CowAgent/commit/6c218331b1f1208ea8be6bf226936d3b556ade3e))
+- **智谱 AI 自定义 API Base URL**：支持智谱 AI 配置自定义 API Base URL ([#2660](https://github.com/zhayujie/CowAgent/pull/2660))
+- **启动脚本优化**：改进 `run.sh` 脚本的交互体验和配置流程 ([#2656](https://github.com/zhayujie/CowAgent/pull/2656))
+- **决策轮次日志**：新增 Agent 决策轮次的日志记录，便于调试 ([cb303e6](https://github.com/zhayujie/CowAgent/commit/cb303e6109c50c8dfef1f5e6c1ec47223bf3cd11))

 ## 问题修复

- **定时任务记忆丢失**：修复 Scheduler 调度器导致的记忆丢失问题 ([a77a874](https://github.com/zhayujie/chatgpt-on-wechat/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
- **空工具调用与超长结果**：修复空 tool calls 及过长工具返回结果的异常处理 ([0542700](https://github.com/zhayujie/chatgpt-on-wechat/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
- **OpenAI Function Call**：修复 OpenAI 模型的 function call 调用兼容性问题 ([158c87a](https://github.com/zhayujie/chatgpt-on-wechat/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
- **Claude 工具名字段**：移除 Claude 模型响应中多余的 tool name 字段 ([eec10cb](https://github.com/zhayujie/chatgpt-on-wechat/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
- **MiniMax 推理优化**：优化 MiniMax 模型 reasoning content 处理，隐藏思考过程输出 ([c72cda3](https://github.com/zhayujie/chatgpt-on-wechat/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/chatgpt-on-wechat/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
- **智谱 AI 思考过程**：隐藏智谱 AI 模型的思考过程展示 ([72b1cac](https://github.com/zhayujie/chatgpt-on-wechat/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
- **飞书连接与证书**：修复飞书渠道的 SSL 证书错误和连接异常问题 ([229b14b](https://github.com/zhayujie/chatgpt-on-wechat/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/chatgpt-on-wechat/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
- **model_type 类型校验**：修复非字符串 `model_type` 导致的 `AttributeError` ([#2666](https://github.com/zhayujie/chatgpt-on-wechat/pull/2666))
+- **定时任务记忆丢失**：修复 Scheduler 调度器导致的记忆丢失问题 ([a77a874](https://github.com/zhayujie/CowAgent/commit/a77a8741b500a408c6f5c8868856fb4b018fe9db))
+- **空工具调用与超长结果**：修复空 tool calls 及过长工具返回结果的异常处理 ([0542700](https://github.com/zhayujie/CowAgent/commit/0542700f9091ebb08c1a56103b0f0f45f24aa621))
+- **OpenAI Function Call**：修复 OpenAI 模型的 function call 调用兼容性问题 ([158c87a](https://github.com/zhayujie/CowAgent/commit/158c87ab8b05bae054cc1b4eacdbb64fc1062ba9))
+- **Claude 工具名字段**：移除 Claude 模型响应中多余的 tool name 字段 ([eec10cb](https://github.com/zhayujie/CowAgent/commit/eec10cb5db6a3d5bc12ef606606532237d2c5f6e))
+- **MiniMax 推理优化**：优化 MiniMax 模型 reasoning content 处理，隐藏思考过程输出 ([c72cda3](https://github.com/zhayujie/CowAgent/commit/c72cda33864bd1542012ee6e0a8bd8c6c88cb5ed), [72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **智谱 AI 思考过程**：隐藏智谱 AI 模型的思考过程展示 ([72b1cac](https://github.com/zhayujie/CowAgent/commit/72b1cacea1ba0d1f3dedacbab2e088e98fd7e172))
+- **飞书连接与证书**：修复飞书渠道的 SSL 证书错误和连接异常问题 ([229b14b](https://github.com/zhayujie/CowAgent/commit/229b14b6fcabe7123d53cab1dea39f38dab26d6d), [8674421](https://github.com/zhayujie/CowAgent/commit/867442155e7f095b4f38b0856f8c1d8312b5fcf7))
+- **model_type 类型校验**：修复非字符串 `model_type` 导致的 `AttributeError` ([#2666](https://github.com/zhayujie/CowAgent/pull/2666))

 ## 平台兼容

- **Windows 兼容性适配**：修复 Windows 平台下路径处理、文件编码及 `os.getuid()` 不可用等问题，涉及多个工具模块 ([051ffd7](https://github.com/zhayujie/chatgpt-on-wechat/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/chatgpt-on-wechat/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
+- **Windows 兼容性适配**：修复 Windows 平台下路径处理、文件编码及 `os.getuid()` 不可用等问题，涉及多个工具模块 ([051ffd7](https://github.com/zhayujie/CowAgent/commit/051ffd78a372f71a967fd3259e37fe19131f83cf), [5264f7c](https://github.com/zhayujie/CowAgent/commit/5264f7ce18360ee4db5dcb4ebe67307977d40014))
--- a/docs/releases/v2.0.2.mdx
+++ b/docs/releases/v2.0.2.mdx
@@ -51,7 +51,7 @@ description: CowAgent 2.0.2 - Web 控制台升级、多通道同时运行、会

 <img width="850" src="https://cdn.link-ai.tech/doc/20260227173514.png" />

-相关提交：[f1a1413](https://github.com/zhayujie/chatgpt-on-wechat/commit/f1a1413), [c0702c8](https://github.com/zhayujie/chatgpt-on-wechat/commit/c0702c8), [394853c](https://github.com/zhayujie/chatgpt-on-wechat/commit/394853c), [1c71c4e](https://github.com/zhayujie/chatgpt-on-wechat/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/chatgpt-on-wechat/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/chatgpt-on-wechat/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/chatgpt-on-wechat/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d258b5)
+相关提交：[f1a1413](https://github.com/zhayujie/CowAgent/commit/f1a1413), [c0702c8](https://github.com/zhayujie/CowAgent/commit/c0702c8), [394853c](https://github.com/zhayujie/CowAgent/commit/394853c), [1c71c4e](https://github.com/zhayujie/CowAgent/commit/1c71c4e), [5e3eccb](https://github.com/zhayujie/CowAgent/commit/5e3eccb), [e1dc037](https://github.com/zhayujie/CowAgent/commit/e1dc037), [5edbf4c](https://github.com/zhayujie/CowAgent/commit/5edbf4c), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5)

 ### 🔀 多通道同时运行

@@ -65,24 +65,24 @@ description: CowAgent 2.0.2 - Web 控制台升级、多通道同时运行、会
 }
 ```

-相关提交：[4694594](https://github.com/zhayujie/chatgpt-on-wechat/commit/4694594), [7cce224](https://github.com/zhayujie/chatgpt-on-wechat/commit/7cce224), [7d258b5](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d258b5), [c9adddb](https://github.com/zhayujie/chatgpt-on-wechat/commit/c9adddb)
+相关提交：[4694594](https://github.com/zhayujie/CowAgent/commit/4694594), [7cce224](https://github.com/zhayujie/CowAgent/commit/7cce224), [7d258b5](https://github.com/zhayujie/CowAgent/commit/7d258b5), [c9adddb](https://github.com/zhayujie/CowAgent/commit/c9adddb)

 ### 💾 会话持久化

 会话历史支持持久化存储至本地 SQLite 数据库，服务重启后会话上下文自动恢复，不再丢失。Web 控制台中的历史对话记录也会同步恢复展示。

-相关提交：[29bfbec](https://github.com/zhayujie/chatgpt-on-wechat/commit/29bfbec), [9917552](https://github.com/zhayujie/chatgpt-on-wechat/commit/9917552), [925d728](https://github.com/zhayujie/chatgpt-on-wechat/commit/925d728)
+相关提交：[29bfbec](https://github.com/zhayujie/CowAgent/commit/29bfbec), [9917552](https://github.com/zhayujie/CowAgent/commit/9917552), [925d728](https://github.com/zhayujie/CowAgent/commit/925d728)

 ### 🤖 新增模型

- **Gemini 3.1 Pro Preview**：新增 `gemini-3.1-pro-preview` 模型支持 ([52d7cad](https://github.com/zhayujie/chatgpt-on-wechat/commit/52d7cad))
- **Claude 4.6 Sonnet**：新增 `claude-4.6-sonnet` 模型支持 ([52d7cad](https://github.com/zhayujie/chatgpt-on-wechat/commit/52d7cad))
- **Qwen3.5 Plus**：新增 `qwen3.5-plus` 模型支持 ([e59a289](https://github.com/zhayujie/chatgpt-on-wechat/commit/e59a289))
- **MiniMax M2.5**：新增 `Minimax-M2.5` 模型支持 ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **GLM-5**：新增 `glm-5` 模型支持 ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **Kimi K2.5**：新增 `kimi-k2.5` 模型支持 ([48db538](https://github.com/zhayujie/chatgpt-on-wechat/commit/48db538))
- **Doubao 2.0 Code**：新增 `doubao-2.0-code` 编程专用模型 ([ab28ee5](https://github.com/zhayujie/chatgpt-on-wechat/commit/ab28ee5))
- **DashScope 模型**：新增阿里云 DashScope 模型名称支持 ([ce58f23](https://github.com/zhayujie/chatgpt-on-wechat/commit/ce58f23))
+- **Gemini 3.1 Pro Preview**：新增 `gemini-3.1-pro-preview` 模型支持 ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Claude 4.6 Sonnet**：新增 `claude-4.6-sonnet` 模型支持 ([52d7cad](https://github.com/zhayujie/CowAgent/commit/52d7cad))
+- **Qwen3.5 Plus**：新增 `qwen3.5-plus` 模型支持 ([e59a289](https://github.com/zhayujie/CowAgent/commit/e59a289))
+- **MiniMax M2.5**：新增 `Minimax-M2.5` 模型支持 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **GLM-5**：新增 `glm-5` 模型支持 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Kimi K2.5**：新增 `kimi-k2.5` 模型支持 ([48db538](https://github.com/zhayujie/CowAgent/commit/48db538))
+- **Doubao 2.0 Code**：新增 `doubao-2.0-code` 编程专用模型 ([ab28ee5](https://github.com/zhayujie/CowAgent/commit/ab28ee5))
+- **DashScope 模型**：新增阿里云 DashScope 模型名称支持 ([ce58f23](https://github.com/zhayujie/CowAgent/commit/ce58f23))

 ### 🌐 新增官网和文档中心

@@ -91,8 +91,8 @@ description: CowAgent 2.0.2 - Web 控制台升级、多通道同时运行、会

 ### 🐛 问题修复

- **Gemini 钉钉图片识别**：修复 Gemini 在钉钉通道中无法处理图片标记的问题 ([05a3304](https://github.com/zhayujie/chatgpt-on-wechat/commit/05a3304)) ([#2670](https://github.com/zhayujie/chatgpt-on-wechat/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
- **启动脚本依赖**：修复 `run.sh` 脚本的依赖安装问题 ([b6fc9fa](https://github.com/zhayujie/chatgpt-on-wechat/commit/b6fc9fa))
- **裸异常捕获**：将代码中的 `bare except` 替换为 `except Exception`，提升异常处理规范性 ([adca89b](https://github.com/zhayujie/chatgpt-on-wechat/commit/adca89b)) ([#2674](https://github.com/zhayujie/chatgpt-on-wechat/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)
+- **Gemini 钉钉图片识别**：修复 Gemini 在钉钉通道中无法处理图片标记的问题 ([05a3304](https://github.com/zhayujie/CowAgent/commit/05a3304)) ([#2670](https://github.com/zhayujie/CowAgent/pull/2670)) Thanks [@SgtPepper114](https://github.com/SgtPepper114)
+- **启动脚本依赖**：修复 `run.sh` 脚本的依赖安装问题 ([b6fc9fa](https://github.com/zhayujie/CowAgent/commit/b6fc9fa))
+- **裸异常捕获**：将代码中的 `bare except` 替换为 `except Exception`，提升异常处理规范性 ([adca89b](https://github.com/zhayujie/CowAgent/commit/adca89b)) ([#2674](https://github.com/zhayujie/CowAgent/pull/2674)) Thanks [@haosenwang1018](https://github.com/haosenwang1018)

-**发布日期**：2026.02.27 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.1...master)
+**发布日期**：2026.02.27 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.1...master)
--- a/docs/releases/v2.0.3.mdx
+++ b/docs/releases/v2.0.3.mdx
@@ -11,7 +11,7 @@ description: CowAgent 2.0.3 - 新增企微智能机器人和 QQ 通道、Web 控

 接入文档：[企微智能机器人接入](https://docs.cowagent.ai/channels/wecom-bot)。

-相关提交：[d4480b6](https://github.com/zhayujie/chatgpt-on-wechat/commit/d4480b6), [a42f31f](https://github.com/zhayujie/chatgpt-on-wechat/commit/a42f31f), [4ecd4df](https://github.com/zhayujie/chatgpt-on-wechat/commit/4ecd4df), [8b45d6c](https://github.com/zhayujie/chatgpt-on-wechat/commit/8b45d6c)
+相关提交：[d4480b6](https://github.com/zhayujie/CowAgent/commit/d4480b6), [a42f31f](https://github.com/zhayujie/CowAgent/commit/a42f31f), [4ecd4df](https://github.com/zhayujie/CowAgent/commit/4ecd4df), [8b45d6c](https://github.com/zhayujie/CowAgent/commit/8b45d6c)

 ### QQ 通道

@@ -19,18 +19,18 @@ description: CowAgent 2.0.3 - 新增企微智能机器人和 QQ 通道、Web 控

 接入文档参考：[QQ机器人接入](https://docs.cowagent.ai/channels/qq)。

-相关提交：[005a0e1](https://github.com/zhayujie/chatgpt-on-wechat/commit/005a0e1), [a4d54f5](https://github.com/zhayujie/chatgpt-on-wechat/commit/a4d54f5)
+相关提交：[005a0e1](https://github.com/zhayujie/CowAgent/commit/005a0e1), [a4d54f5](https://github.com/zhayujie/CowAgent/commit/a4d54f5)

 ## 🖥️ Web 控制台支持文件输入和处理

 Web 控制台对话界面支持文件和图片上传，可直接发送文件给 Agent 进行处理。同时 Read 工具新增对 Office 文档（Word、Excel、PPT）的解析能力。

-相关提交：[30c6d9b](https://github.com/zhayujie/chatgpt-on-wechat/commit/30c6d9b)
+相关提交：[30c6d9b](https://github.com/zhayujie/CowAgent/commit/30c6d9b)

 ## 🤖 新增模型

- **GPT-5.4 系列**：新增 `gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano` 模型支持 ([1623deb](https://github.com/zhayujie/chatgpt-on-wechat/commit/1623deb))
- **Gemini 3.1 Flash Lite Preview**：新增 `gemini-3.1-flash-lite-preview` 模型支持 ([ba915f2](https://github.com/zhayujie/chatgpt-on-wechat/commit/ba915f2))
+- **GPT-5.4 系列**：新增 `gpt-5.4`、`gpt-5.4-mini`、`gpt-5.4-nano` 模型支持 ([1623deb](https://github.com/zhayujie/CowAgent/commit/1623deb))
+- **Gemini 3.1 Flash Lite Preview**：新增 `gemini-3.1-flash-lite-preview` 模型支持 ([ba915f2](https://github.com/zhayujie/CowAgent/commit/ba915f2))

 ## 💰 Coding Plan 支持

@@ -48,12 +48,12 @@ Web 控制台对话界面支持文件和图片上传，可直接发送文件给
 - 新增每日定时冲刷兜底机制，避免低活跃场景下记忆丢失
 - 修复上下文记忆丢失问题

-相关提交：[022c13f](https://github.com/zhayujie/chatgpt-on-wechat/commit/022c13f), [c116235](https://github.com/zhayujie/chatgpt-on-wechat/commit/c116235)
+相关提交：[022c13f](https://github.com/zhayujie/CowAgent/commit/022c13f), [c116235](https://github.com/zhayujie/CowAgent/commit/c116235)

 ## 🔧 工具重构

- **图片识别**：将图片识别（Image Vision）从 Skill 重构为内置 Tool，新增独立的图片视觉提供方（Vision Provider）配置，提升稳定性和可维护性 ([a50fafa](https://github.com/zhayujie/chatgpt-on-wechat/commit/a50fafa), [3b8b562](https://github.com/zhayujie/chatgpt-on-wechat/commit/3b8b562))
- **网页抓取**：将网页抓取（Web Fetch）从 Skill 重构为内置 Tool，支持远程文档文件（PDF、Word、Excel、PPT）的下载和解析 ([ccb9030](https://github.com/zhayujie/chatgpt-on-wechat/commit/ccb9030), [fa61744](https://github.com/zhayujie/chatgpt-on-wechat/commit/fa61744))
+- **图片识别**：将图片识别（Image Vision）从 Skill 重构为内置 Tool，新增独立的图片视觉提供方（Vision Provider）配置，提升稳定性和可维护性 ([a50fafa](https://github.com/zhayujie/CowAgent/commit/a50fafa), [3b8b562](https://github.com/zhayujie/CowAgent/commit/3b8b562))
+- **网页抓取**：将网页抓取（Web Fetch）从 Skill 重构为内置 Tool，支持远程文档文件（PDF、Word、Excel、PPT）的下载和解析 ([ccb9030](https://github.com/zhayujie/CowAgent/commit/ccb9030), [fa61744](https://github.com/zhayujie/CowAgent/commit/fa61744))

 ## 🐳 Docker 部署优化

@@ -64,28 +64,28 @@ Web 控制台对话界面支持文件和图片上传，可直接发送文件给

 ## ⚡ 性能优化

- **启动加速**：飞书通道采用懒加载方式导入依赖，避免 4-10 秒的启动延迟 ([924dc79](https://github.com/zhayujie/chatgpt-on-wechat/commit/924dc79))
- **通道稳定性**：优化通道连接稳定性，支持通道配置通过环境变量设置 ([f1c04bc](https://github.com/zhayujie/chatgpt-on-wechat/commit/f1c04bc), [46d97fd](https://github.com/zhayujie/chatgpt-on-wechat/commit/46d97fd))
+- **启动加速**：飞书通道采用懒加载方式导入依赖，避免 4-10 秒的启动延迟 ([924dc79](https://github.com/zhayujie/CowAgent/commit/924dc79))
+- **通道稳定性**：优化通道连接稳定性，支持通道配置通过环境变量设置 ([f1c04bc](https://github.com/zhayujie/CowAgent/commit/f1c04bc), [46d97fd](https://github.com/zhayujie/CowAgent/commit/46d97fd))

 ## 🐛 问题修复

- **bot_type 配置**：修复 Agent 模式下 `bot_type` 配置传递问题 ([#2691](https://github.com/zhayujie/chatgpt-on-wechat/pull/2691)) Thanks [@Weikjssss](https://github.com/Weikjssss)
- **bot_type 优先级**：调整 Agent 模式下 `bot_type` 的解析优先级 ([#2692](https://github.com/zhayujie/chatgpt-on-wechat/pull/2692)) Thanks [@6vision](https://github.com/6vision)
- **智谱模型配置**：修复智谱 `bot_type` 命名、Web 控制台持久化及正则转义问题 ([#2693](https://github.com/zhayujie/chatgpt-on-wechat/pull/2693)) Thanks [@6vision](https://github.com/6vision)
- **OpenAI 兼容层**：使用 `openai_compat` 层统一错误处理 ([#2688](https://github.com/zhayujie/chatgpt-on-wechat/pull/2688)) Thanks [@JasonOA888](https://github.com/JasonOA888)
- **OpenAI 兼容迁移**：完成所有模型 Bot 的 `openai_compat` 迁移 ([#2689](https://github.com/zhayujie/chatgpt-on-wechat/pull/2689))
- **Gemini 工具调用**：修复 Gemini 模型的工具调用匹配问题 ([eda82ba](https://github.com/zhayujie/chatgpt-on-wechat/commit/eda82ba))
- **会话并发**：修复会话并发场景下的竞态条件问题 ([9879878](https://github.com/zhayujie/chatgpt-on-wechat/commit/9879878))
- **历史消息恢复**：修复历史会话消息不完整问题，仅恢复 user/assistant 文本消息，剥离工具调用 ([b788a3d](https://github.com/zhayujie/chatgpt-on-wechat/commit/b788a3d), [a33ce97](https://github.com/zhayujie/chatgpt-on-wechat/commit/a33ce97))
- **飞书群聊**：移除飞书群聊场景下对 `bot_name` 的依赖 ([b641bff](https://github.com/zhayujie/chatgpt-on-wechat/commit/b641bff))
- **Safari 兼容**：修复 Safari 浏览器 IME 回车键误触发消息发送问题 ([0687916](https://github.com/zhayujie/chatgpt-on-wechat/commit/0687916))
- **Windows 兼容**：修复 Windows 下 bash 风格 `$VAR` 环境变量转换为 `%VAR%` 的问题 ([7c67513](https://github.com/zhayujie/chatgpt-on-wechat/commit/7c67513))
- **MiniMax 参数**：增加 MiniMax 模型的 `max_tokens` 限制 ([1767413](https://github.com/zhayujie/chatgpt-on-wechat/commit/1767413))
- **.gitignore 更新**：添加 Python 目录忽略规则 ([#2683](https://github.com/zhayujie/chatgpt-on-wechat/pull/2683)) Thanks [@pelioo](https://github.com/pelioo)
+- **bot_type 配置**：修复 Agent 模式下 `bot_type` 配置传递问题 ([#2691](https://github.com/zhayujie/CowAgent/pull/2691)) Thanks [@Weikjssss](https://github.com/Weikjssss)
+- **bot_type 优先级**：调整 Agent 模式下 `bot_type` 的解析优先级 ([#2692](https://github.com/zhayujie/CowAgent/pull/2692)) Thanks [@6vision](https://github.com/6vision)
+- **智谱模型配置**：修复智谱 `bot_type` 命名、Web 控制台持久化及正则转义问题 ([#2693](https://github.com/zhayujie/CowAgent/pull/2693)) Thanks [@6vision](https://github.com/6vision)
+- **OpenAI 兼容层**：使用 `openai_compat` 层统一错误处理 ([#2688](https://github.com/zhayujie/CowAgent/pull/2688)) Thanks [@JasonOA888](https://github.com/JasonOA888)
+- **OpenAI 兼容迁移**：完成所有模型 Bot 的 `openai_compat` 迁移 ([#2689](https://github.com/zhayujie/CowAgent/pull/2689))
+- **Gemini 工具调用**：修复 Gemini 模型的工具调用匹配问题 ([eda82ba](https://github.com/zhayujie/CowAgent/commit/eda82ba))
+- **会话并发**：修复会话并发场景下的竞态条件问题 ([9879878](https://github.com/zhayujie/CowAgent/commit/9879878))
+- **历史消息恢复**：修复历史会话消息不完整问题，仅恢复 user/assistant 文本消息，剥离工具调用 ([b788a3d](https://github.com/zhayujie/CowAgent/commit/b788a3d), [a33ce97](https://github.com/zhayujie/CowAgent/commit/a33ce97))
+- **飞书群聊**：移除飞书群聊场景下对 `bot_name` 的依赖 ([b641bff](https://github.com/zhayujie/CowAgent/commit/b641bff))
+- **Safari 兼容**：修复 Safari 浏览器 IME 回车键误触发消息发送问题 ([0687916](https://github.com/zhayujie/CowAgent/commit/0687916))
+- **Windows 兼容**：修复 Windows 下 bash 风格 `$VAR` 环境变量转换为 `%VAR%` 的问题 ([7c67513](https://github.com/zhayujie/CowAgent/commit/7c67513))
+- **MiniMax 参数**：增加 MiniMax 模型的 `max_tokens` 限制 ([1767413](https://github.com/zhayujie/CowAgent/commit/1767413))
+- **.gitignore 更新**：添加 Python 目录忽略规则 ([#2683](https://github.com/zhayujie/CowAgent/pull/2683)) Thanks [@pelioo](https://github.com/pelioo)
 - **AGENT.md 主动演进**：优化系统提示词中对 AGENT.md 的更新引导，从被动的"用户修改时更新"改为主动识别对话中的性格、风格变化并自动更新

 ## 📦 升级方式

 源码部署可执行 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。

-**发布日期**：2026.03.18 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.2...master)
+**发布日期**：2026.03.18 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.2...master)
--- a/docs/releases/v2.0.4.mdx
+++ b/docs/releases/v2.0.4.mdx
@@ -16,36 +16,36 @@ description: CowAgent 2.0.4 - 新增个人微信通道、新模型支持、日

 接入文档：[微信接入](https://docs.cowagent.ai/channels/weixin)。

-相关提交：[ce89869](https://github.com/zhayujie/chatgpt-on-wechat/commit/ce89869)
+相关提交：[ce89869](https://github.com/zhayujie/CowAgent/commit/ce89869)

 ## 🤖 新增模型

 - **MiniMax-M2.7**：新增 MiniMax-M2.7 模型支持
 - **GLM-5-Turbo**：新增智谱 glm-5-turbo 模型支持

-相关提交：[9192f6f](https://github.com/zhayujie/chatgpt-on-wechat/commit/9192f6f)
+相关提交：[9192f6f](https://github.com/zhayujie/CowAgent/commit/9192f6f)

 ## 🔧 脚本重构

- **run.sh 重构**：提取公共逻辑，精简脚本代码([49d8707](https://github.com/zhayujie/chatgpt-on-wechat/commit/49d8707))
- **可执行权限**：修复 `run.sh` 文件权限问题 ([652156e](https://github.com/zhayujie/chatgpt-on-wechat/commit/652156e))
- **PID 获取**：修复 `run.sh` 中进程 PID 获取错误的问题 ([9febb07](https://github.com/zhayujie/chatgpt-on-wechat/commit/9febb07))
+- **run.sh 重构**：提取公共逻辑，精简脚本代码([49d8707](https://github.com/zhayujie/CowAgent/commit/49d8707))
+- **可执行权限**：修复 `run.sh` 文件权限问题 ([652156e](https://github.com/zhayujie/CowAgent/commit/652156e))
+- **PID 获取**：修复 `run.sh` 中进程 PID 获取错误的问题 ([9febb07](https://github.com/zhayujie/CowAgent/commit/9febb07))

 ## 🌍 文档更新

 新增完整的日文文档，覆盖入门指南、通道接入、模型配置等主要章节。Thanks [@Ikko Ashimine](https://github.com/ikoamu)

-相关提交：[5487c0b](https://github.com/zhayujie/chatgpt-on-wechat/commit/5487c0b)
+相关提交：[5487c0b](https://github.com/zhayujie/CowAgent/commit/5487c0b)

 ## 🐛 问题修复

- **企微机器人兼容**：修复旧版 `websocket-client` 的兼容性问题，新增统一的 WebSocket 兼容层 ([bc7f627](https://github.com/zhayujie/chatgpt-on-wechat/commit/bc7f627))
- **消息自动修复**：增强消息协议的容错能力，自动修复格式异常的消息序列 ([b8b57e3](https://github.com/zhayujie/chatgpt-on-wechat/commit/b8b57e3))
- **飞书编码**：修复飞书通道消息和日志的编码问题 ([7d0e156](https://github.com/zhayujie/chatgpt-on-wechat/commit/7d0e156))
- **飞书配置**：移除 `run.sh` 中对 `feishu_bot_name` 的冗余依赖 ([1b5be1b](https://github.com/zhayujie/chatgpt-on-wechat/commit/1b5be1b))
+- **企微机器人兼容**：修复旧版 `websocket-client` 的兼容性问题，新增统一的 WebSocket 兼容层 ([bc7f627](https://github.com/zhayujie/CowAgent/commit/bc7f627))
+- **消息自动修复**：增强消息协议的容错能力，自动修复格式异常的消息序列 ([b8b57e3](https://github.com/zhayujie/CowAgent/commit/b8b57e3))
+- **飞书编码**：修复飞书通道消息和日志的编码问题 ([7d0e156](https://github.com/zhayujie/CowAgent/commit/7d0e156))
+- **飞书配置**：移除 `run.sh` 中对 `feishu_bot_name` 的冗余依赖 ([1b5be1b](https://github.com/zhayujie/CowAgent/commit/1b5be1b))

 ## 📦 升级方式

 源码部署可执行 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。

-**发布日期**：2026.03.22 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.3...master)
+**发布日期**：2026.03.22 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.3...master)
--- a/docs/releases/v2.0.5.mdx
+++ b/docs/releases/v2.0.5.mdx
@@ -59,26 +59,26 @@ Skill Hub 开源仓库：[cow-skill-hub](https://github.com/zhayujie/cow-skill-h

 相关文档：[企微智能机器人接入](https://docs.cowagent.ai/channels/wecom-bot)。

-相关提交：[#2735](https://github.com/zhayujie/chatgpt-on-wechat/pull/2735)
+相关提交：[#2735](https://github.com/zhayujie/CowAgent/pull/2735)

 Thanks [@WecomTeam](https://github.com/WecomTeam)

 ## 🐛 其他优化与修复

- **DeepSeek 独立模块**：新增独立的 DeepSeek Bot 模块，支持 `deepseek_api_key` 专属配置，无需再通过 OpenAI 兼容方式接入（[#2719](https://github.com/zhayujie/chatgpt-on-wechat/pull/2719)）。Thanks [@6vision](https://github.com/6vision)
- **Web 控制台优化**：新增斜杠指令菜单和输入历史回溯，新增模型选项，优化移动端适配（[#2731](https://github.com/zhayujie/chatgpt-on-wechat/pull/2731)）。Thanks [@zkjqd](https://github.com/zkjqd)
- **上下文丢失**：修复上下文裁剪后丢失的问题 ([393f0c0](https://github.com/zhayujie/chatgpt-on-wechat/commit/393f0c0))
- **系统提示词**：修复系统提示词未在每轮重建的问题 ([13f5fde](https://github.com/zhayujie/chatgpt-on-wechat/commit/13f5fde))
- **Agent 响应**：去除 Agent 响应首尾空白字符 ([f890318](https://github.com/zhayujie/chatgpt-on-wechat/commit/f890318))
- **视觉压缩**：优化视觉图片压缩策略 ([22b8ca0](https://github.com/zhayujie/chatgpt-on-wechat/commit/22b8ca0))
- **Gemini 模型**：修复 GoogleGeminiBot 缺少 model 属性的问题（[#2716](https://github.com/zhayujie/chatgpt-on-wechat/pull/2716)）。Thanks [@cowagent](https://github.com/cowagent)
- **微信通道**：修复文件发送失败、文件名丢失等问题 ([6d9b7ba](https://github.com/zhayujie/chatgpt-on-wechat/commit/6d9b7ba)、[baf66a1](https://github.com/zhayujie/chatgpt-on-wechat/commit/baf66a1)、[45faa9c](https://github.com/zhayujie/chatgpt-on-wechat/commit/45faa9c))
- **Docker 优化**：修复卷权限问题，精简镜像体积 ([3eb8348](https://github.com/zhayujie/chatgpt-on-wechat/commit/3eb8348)、[4470d4c](https://github.com/zhayujie/chatgpt-on-wechat/commit/4470d4c))
- **README 排版**：优化中英文排版空格（[#2723](https://github.com/zhayujie/chatgpt-on-wechat/pull/2723)）。Thanks [@Xiaozhou345](https://github.com/Xiaozhou345)
+- **DeepSeek 独立模块**：新增独立的 DeepSeek Bot 模块，支持 `deepseek_api_key` 专属配置，无需再通过 OpenAI 兼容方式接入（[#2719](https://github.com/zhayujie/CowAgent/pull/2719)）。Thanks [@6vision](https://github.com/6vision)
+- **Web 控制台优化**：新增斜杠指令菜单和输入历史回溯，新增模型选项，优化移动端适配（[#2731](https://github.com/zhayujie/CowAgent/pull/2731)）。Thanks [@zkjqd](https://github.com/zkjqd)
+- **上下文丢失**：修复上下文裁剪后丢失的问题 ([393f0c0](https://github.com/zhayujie/CowAgent/commit/393f0c0))
+- **系统提示词**：修复系统提示词未在每轮重建的问题 ([13f5fde](https://github.com/zhayujie/CowAgent/commit/13f5fde))
+- **Agent 响应**：去除 Agent 响应首尾空白字符 ([f890318](https://github.com/zhayujie/CowAgent/commit/f890318))
+- **视觉压缩**：优化视觉图片压缩策略 ([22b8ca0](https://github.com/zhayujie/CowAgent/commit/22b8ca0))
+- **Gemini 模型**：修复 GoogleGeminiBot 缺少 model 属性的问题（[#2716](https://github.com/zhayujie/CowAgent/pull/2716)）。Thanks [@cowagent](https://github.com/cowagent)
+- **微信通道**：修复文件发送失败、文件名丢失等问题 ([6d9b7ba](https://github.com/zhayujie/CowAgent/commit/6d9b7ba)、[baf66a1](https://github.com/zhayujie/CowAgent/commit/baf66a1)、[45faa9c](https://github.com/zhayujie/CowAgent/commit/45faa9c))
+- **Docker 优化**：修复卷权限问题，精简镜像体积 ([3eb8348](https://github.com/zhayujie/CowAgent/commit/3eb8348)、[4470d4c](https://github.com/zhayujie/CowAgent/commit/4470d4c))
+- **README 排版**：优化中英文排版空格（[#2723](https://github.com/zhayujie/CowAgent/pull/2723)）。Thanks [@Xiaozhou345](https://github.com/Xiaozhou345)
 - **安全修复**：修复 Memory Content路径遍历风险，Thanks [@August829](https://github.com/August829)

 ## 📦 升级方式

 源码部署可执行 `cow update` 或 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。

-**发布日期**：2026.04.01 | [Full Changelog](https://github.com/zhayujie/chatgpt-on-wechat/compare/2.0.4...master)
+**发布日期**：2026.04.01 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.4...master)
--- a/docs/releases/v2.0.6.mdx
+++ b/docs/releases/v2.0.6.mdx
@@ -0,0 +1,82 @@
+---
+title: v2.0.6
+description: CowAgent 2.0.6 - 知识库系统、梦境记忆蒸馏、上下文智能压缩、Web 控制台多会话及多项优化
+---
+
+## 项目正式更名为 CowAgent
+
+项目仓库正式从 `chatgpt-on-wechat` 更名为 **CowAgent**，演进为功能完备的 AI Agent 助理。
+
+- 新地址：[github.com/zhayujie/CowAgent](https://github.com/zhayujie/CowAgent)，旧地址 GitHub 会自动重定向
+- CLI 命令、配置文件、文档链接均保持兼容，无需额外操作
+
+## 📚 知识库系统
+
+新增个人知识库系统，Agent 可自主构建和维护结构化知识，并在对话中按需检索引用：
+
+- **索引驱动的自组织结构**：知识库采用 `knowledge/` 目录，按分类自动组织，每个知识页面为独立的 Markdown 文件
+- **自动写入**：向 Agent 发送文件、链接等知识，或在讨论中识别到有价值的知识时，自动创建或更新知识页面
+- **混合检索**：支持关键词全文搜索和向量语义检索，在对话中按需加载相关知识
+- **可视化**：支持文件树浏览和知识图谱可视化，文档内链接可直接跳转查看
+- **命令管理**：`/knowledge` 查看统计、`/knowledge list` 查看目录结构、`/knowledge on|off` 开关知识库
+
+<img src="https://cdn.link-ai.tech/doc/20260413105435.png" width="750" />
+
+
+相关文档：[知识库](https://docs.cowagent.ai/knowledge)
+
+## 🌙 梦境记忆蒸馏（Deep Dream）
+
+全新的记忆整理机制，每日自动将分散的对话记忆蒸馏为精炼的长期记忆：
+
+- **三层记忆流转**：对话上下文（短期）→ 天级记忆（中期）→ MEMORY.md（长期），形成完整的记忆生命周期
+- **自动蒸馏**：每日 23:55 定时执行，读取当天天级记忆和 MEMORY.md，通过 LLM 进行去重、合并、修剪，输出精炼的新版 MEMORY.md
+- **梦境日记**：每次蒸馏生成一篇叙事风格的梦境日记，记录整理过程的发现和洞察，存储在 `memory/dreams/` 目录
+- **手动触发**：支持 `/memory dream [N]` 手动触发，可指定整理天数（默认 3 天，最大 30 天），完成后在对话中通知结果
+- **Web 控制台**：记忆管理页面新增「梦境日记」tab，可浏览和查看所有梦境日记
+
+相关文档：[梦境蒸馏](https://docs.cowagent.ai/memory/deep-dream)
+
+<img src="https://cdn.link-ai.tech/doc/20260414120158.png" width="750" />
+
+## 🧠 上下文智能压缩
+
+上下文超出限制时将裁剪的部分通过 LLM 总结后异步注入，保持对话连贯性：
+
+- **LLM 异步摘要**：裁剪的消息由 LLM 总结为关键信息，同时写入天级记忆文件和注入保留的上下文
+- **多模型兼容**：优先使用主模型进行摘要，兼容 Claude、OpenAI、MiniMax 等不同模型的消息格式要求
+
+相关文档：[短期记忆](https://docs.cowagent.ai/memory/context)
+
+## 💬 Web 控制台升级
+
+Web 控制台多项功能增强：
+
+- **多会话管理**：支持创建和切换多个独立会话，侧边栏展示会话列表，支持会话标题自动生成和手动编辑
+- **密码保护**：支持为控制台设置登录密码，可通过 `web_console_password` 配置项控制
+- **深度思考**：支持在 Web 端展示模型的思考过程，可通过`enable_thinking` 配置项控制
+- **定时推送**：支持定时任务结果推送到 Web 控制台
+- **消息复制**：AI 回复支持一键复制原始 Markdown 内容
+
+## 🤖 模型相关
+
+- **视觉识别优化**：图片识别工具优先使用主模型，支持多模型厂商自动降级。相关文档：[视觉工具](https://docs.cowagent.ai/tools/vision)
+- **MiniMax 新模型**：新增 MiniMax-M2.7-highspeed 模型和 MiniMax TTS 语音合成支持。Thanks @octo-patch
+- **通义千问**：新增 qwen3.6-plus 模型支持
+
+## 🐛 其他优化与修复
+
+- **记忆提示词优化**：`MEMORY.md` 默认注入系统提示词，精细化记忆检索和写入的触发条件，增强主动写入能力
+- **系统提示词**：优化系统提示词的风格和语气引导
+- **浏览器工具**：增强隐式交互元素检测
+- **文件发送**：修复通用文件类型（tar.gz、zip 等）未能正确发送的问题。Thanks @6vision
+- **macOS 兼容**：修复网络预检超时兼容性问题。Thanks @Moliang Zhou
+- **Windows 兼容**：修复 Windows 下 PowerShell 兼容性、进程更新、终端编码等多项问题
+- **Python 3.13+**：修复 Python 3.13 及以上版本缺少 `legacy-cgi` 依赖的问题
+- **个人微信**：更新个人微信通道版本
+
+## 📦 升级方式
+
+源码部署可执行 `cow update` 或 `./run.sh update` 一键升级，或手动拉取代码后重启。详见 [更新升级文档](https://docs.cowagent.ai/guide/upgrade)。
+
+**发布日期**：2026.04.14 | [Full Changelog](https://github.com/zhayujie/CowAgent/compare/2.0.5...master)
--- a/docs/skills/create.mdx
+++ b/docs/skills/create.mdx
@@ -54,5 +54,5 @@ Detailed instructions...
 | `metadata.always` | 是否始终加载（默认 false） |

 <Tip>
-  详细开发文档可参考 [Skill Creator 说明](https://github.com/zhayujie/chatgpt-on-wechat/blob/master/skills/skill-creator/SKILL.md)。
+  详细开发文档可参考 [Skill Creator 说明](https://github.com/zhayujie/CowAgent/blob/master/skills/skill-creator/SKILL.md)。
 </Tip>
--- a/docs/tools/memory.mdx
+++ b/docs/tools/memory.mdx
@@ -1,9 +1,11 @@
 ---
-title: memory - 记忆
-description: 搜索和读取长期记忆
+title: memory - 记忆与知识
+description: 搜索和读取长期记忆及知识库文件
 ---

-记忆工具包含两个子工具：`memory_search`（搜索记忆）和 `memory_get`（读取记忆文件）。
+记忆工具包含两个子工具：`memory_search`（搜索记忆）和 `memory_get`（读取记忆或知识文件）。
+
+当 [知识库](/knowledge) 功能开启时，这两个工具同时支持访问 `memory/` 和 `knowledge/` 目录下的文件。

 ## 依赖

@@ -11,7 +13,7 @@ description: 搜索和读取长期记忆

 ## memory_search

-搜索历史记忆，支持关键词和向量混合检索。
+搜索历史记忆和知识库内容，支持关键词和向量混合检索。

 | 参数 | 类型 | 必填 | 说明 |
 | --- | --- | --- | --- |
@@ -19,11 +21,11 @@ description: 搜索和读取长期记忆

 ## memory_get

-读取特定记忆文件的内容。
+读取特定记忆文件或知识库文件的内容。

 | 参数 | 类型 | 必填 | 说明 |
 | --- | --- | --- | --- |
-| `path` | string | 是 | 记忆文件的相对路径（如 `MEMORY.md`、`memory/2026-01-01.md`） |
+| `path` | string | 是 | 文件的相对路径（如 `MEMORY.md`、`memory/2026-01-01.md`、`knowledge/concepts/rag.md`） |
 | `start_line` | integer | 否 | 起始行号 |
 | `end_line` | integer | 否 | 结束行号 |

@@ -34,3 +36,8 @@ Agent 会在以下场景自动调用记忆工具：
 - 用户分享重要信息时 → 存储到记忆
 - 需要参考历史信息时 → 搜索相关记忆
 - 对话达到一定长度时 → 提取摘要存储
+- 讨论到专业知识时 → 检索知识库中的相关页面
+
+<Note>
+  当 `knowledge` 配置为 `false` 时，工具的描述和搜索范围会自动调整为仅包含记忆文件。
+</Note>
--- a/Show More
+++ b/Show More
Author	SHA1	Message	Date
zhayujie	60e9d98d0a	feat: release 2.0.6	2026-04-14 12:37:53 +08:00
zhayujie	83f6625e0c	feat: release 2.0.6	2026-04-14 12:08:57 +08:00
zhayujie	acc09543b7	feat(dream): add memory dream cli and docs - New memory/deep-dream.mdx (zh/en/ja): memory flow, distillation rules, dream diary, manual trigger, safety mechanisms - Simplify long-term memory page, link to deep-dream for details - New cli/memory-knowledge.mdx (zh/en/ja): memory and knowledge commands - Move knowledge commands from general.mdx to memory-knowledge.mdx - Register new pages in docs.json navigation for all languages - Add /memory dream to cli/index.mdx command tables	2026-04-14 11:03:53 +08:00
zhayujie	94d8c7e366	feat(dream): add Dream Diary tab to memory management page - Backend: MemoryService supports category param (memory/dream), lists memory/dreams/*.md - Backend: MemoryContentHandler resolves dream files from memory/dreams/ directory - Frontend: add tab switcher (Memory Files / Dream Diary) matching knowledge tab style - Frontend: dream entries show purple "Dream" badge, empty state with moon icon - Cloud dispatch passes category param for consistency	2026-04-13 22:08:15 +08:00
zhayujie	ea1a0c8b3d	feat(memory): add Deep Dream module for daily memory distillation - Add Deep Dream: nightly distill daily memories → refined MEMORY.md + dream diary - Simplify flush prompt to daily-only, defer MEMORY.md maintenance to Deep Dream - Remove dead code (_append_to_main_memory) and fix fallback summary logic - Add shrinkage protection and input dedup for dream process - Ensure flush threads complete before dream starts - Update docs (zh/en/ja) with dream diary and distillation mechanism	2026-04-13 21:32:52 +08:00
zhayujie	7bc88c17e4	Merge branch 'master' of github.com:zhayujie/chatgpt-on-wechat	2026-04-13 20:13:30 +08:00
zhayujie	33cf1bc4c3	feat(memory): async LLM context summary injection on trim - Unified flush + context injection into a single async LLM call (flush_from_messages accepts context_summary_callback) - Fixed response parsing bug: handle generator returns and Claude-format dicts from bot.call_with_tools, which previously caused all LLM summaries to silently fail (falling back to rule-based extraction) - Removed standalone context summary prompts and methods; reuse the existing [DAILY]/[MEMORY] summarization pipeline - Updated docs (zh/en/ja) to reflect the new injection behavior	2026-04-13 20:13:05 +08:00
zhayujie	9402e63fe1	Merge pull request #2766 from zhayujie/feat-mulit-session feat(web): add multi-session management for web console	2026-04-13 18:51:07 +08:00
zhayujie	90e4d494b2	feat(web): add multi-session management for web console	2026-04-13 18:50:31 +08:00
zhayujie	da97e948ca	feat: refine memory recall/write prompts for better precision and proactivity	2026-04-13 18:02:06 +08:00
zhayujie	89a07e8e74	feat: add enable_thinking config to control deep reasoning on web console	2026-04-13 16:06:28 +08:00
zhayujie	3f3d0381e5	feat: update knowledge docs and fix claude error	2026-04-13 11:16:26 +08:00
zhayujie	3649499dba	fix: optimize the stability of network pre-checks	2026-04-13 10:35:38 +08:00
zhayujie	a989d088fd	Merge pull request #2764 from WilliamOnVoyage/fix/macos-timeout-fallback fix: Fix run.sh for MacOS via add timeout fallback	2026-04-13 10:21:44 +08:00
Moliang Zhou	f79a915136	fix: add timeout fallback for macOS compatibility The `timeout` command (GNU Coreutils) is not available by default on macOS, causing the installation script to fail with 'timeout: command not found' during git clone. This adds a shell function fallback that: - Uses `gtimeout` if Homebrew coreutils is installed - Otherwise skips the timeout and runs the command directly	2026-04-12 11:18:44 -07:00
zhayujie	12e8c3d449	Merge pull request #2763 from zhayujie/feat-web-console-upgrade feat(web): support scheduler push messages and enrich welcome screen	2026-04-12 21:20:34 +08:00
zhayujie	4f7064575e	feat(web): support scheduler push messages and enrich welcome screen - Expand welcome screen from 3 to 6 example cards covering core capabilities - Enable background polling on page load so scheduler task notifications are received in real-time - Fix duplicate poll loops via generation-based cancellation, reduce poll frequency to 5s/10s - Ensure equal card height and adjust layout position for better visual balance	2026-04-12 21:19:50 +08:00
zhayujie	070df826f1	Merge pull request #2762 from zhayujie/feat-web-console-upgrade feat(web): add password protection for web console	2026-04-12 20:38:45 +08:00
zhayujie	fbe48a4b4e	feat(web): add password protection for web console - Add `web_password` config to enable login authentication - Use stateless HMAC-signed token (survives restart, invalidates on password change) - Add `web_session_expire_days` config (default 30 days) - Protect all API endpoints with auth check (401 on failure) - Add login page UI with auto-redirect on session expiry - Add password management in config page (masked display, inline edit) - Add tooltip hints for Agent config fields - Update default agent_max_context_turns to 20, agent_max_steps to 20 - Update docs and docker-compose.yml	2026-04-12 20:37:04 +08:00
zhayujie	4dd497fb6d	fix: run.ps1 git clone in windows	2026-04-12 17:52:37 +08:00
zhayujie	907882c0a7	fix: git clone pre-check	2026-04-12 17:36:45 +08:00
zhayujie	d36d5aee3f	feat: rename repository name from chatgpt-on-wechat to CowAgent - Update GitHub URLs in README.md (badges, release links, clone address, wiki, issues, contributors) - Add project rename notice with SEO keywords and git remote update command - Update docs/docs.json GitHub links - Update all docs (zh/en/ja) across guide, intro, models, releases, skills - Update run.sh and scripts/run.ps1 clone URLs and directory names - Docker image name (zhayujie/chatgpt-on-wechat) kept unchanged for compatibility	2026-04-12 17:09:07 +08:00
zhayujie	c6824e5f5e	fix: add legacy-cgi dependency for Python 3.13+ #2758 Add conditional dependency `legacy-cgi` for Python 3.13+ to resolve `web.py` installation failure caused by the removal of the `cgi` module (PEP 594). Thanks @sha156 for reporting.	2026-04-12 16:49:00 +08:00
zhayujie	199c21eede	Merge pull request #2761 from zhayujie/feat-knowledge feat: personal knowledge base system	2026-04-12 16:47:07 +08:00
zhayujie	5162da5654	Merge branch 'master' into feat-knowledge	2026-04-12 16:46:38 +08:00
zhayujie	a1d82f6193	feat(knowledge): add cli and update docs	2026-04-12 16:39:06 +08:00
zhayujie	ea78e3d0c6	feat(knowledge): document link supports jumping to view	2026-04-11 20:16:43 +08:00
zhayujie	3497f00cb4	Merge pull request #2759 from zhayujie/feat-multimodel feat(vision): prioritize main model for image recognition	2026-04-11 19:55:15 +08:00
zhayujie	5355d45031	Merge pull request #2756 from octo-patch/feature/add-minimax-m2.7-highspeed-tts feat: add MiniMax-M2.7-highspeed model and MiniMax TTS support	2026-04-11 19:54:03 +08:00
zhayujie	76e9fef3b2	feat(knowledge): add file list and graph in web channel	2026-04-11 19:02:55 +08:00
octo-patch	c34308cbd4	feat: add MiniMax-M2.7-highspeed model and MiniMax TTS support - Add MiniMax-M2.7-highspeed constant to const.py and MODEL_LIST - Update MinimaxBot default model from MiniMax-M2.1 to MiniMax-M2.7 - Add MinimaxVoice TTS provider (voice/minimax/minimax_voice.py) - Supports speech-2.8-hd and speech-2.8-turbo models - SSE streaming with hex-decoded audio chunks - Reuses MINIMAX_API_KEY - Register MinimaxVoice in voice factory - Add unit tests (14 tests, all passing) - Update README with MiniMax-M2.7-highspeed and TTS configuration	2026-04-11 17:03:44 +08:00
zhayujie	5a10476010	feat: add knowledge switch and cli	2026-04-11 16:44:25 +08:00
zhayujie	46e80dceec	Merge pull request #2755 from 6vision/fix/generic-file-send fix: send generic file types (tar.gz, zip, etc.) as FILE instead of TEXT	2026-04-11 16:36:34 +08:00
6vision	90d1835353	fix: send generic file types (tar.gz, zip, etc.) as FILE instead of TEXT Previously, files with extensions not in the known categories (image, document, video, audio) fell through to a fallback that returned ReplyType.TEXT, causing the file to never actually be sent to the user. Now the fallback uses ReplyType.FILE so all file types are delivered. Made-with: Cursor	2026-04-11 15:45:34 +08:00
zhayujie	845fadd0aa	fix(knowledge): modify knowledge skill	2026-04-10 18:22:54 +08:00
zhayujie	5748ded52c	feat(knowledge): change knowledge base to index-driven self-organizing structure	2026-04-10 16:06:04 +08:00
zhayujie	6a737fb734	feat: display thinking content in web console	2026-04-10 15:07:23 +08:00
zhayujie	54e81aba11	feat(memory+knowledge): add knowledge wiki system and Light Dream memory extraction - Add knowledge/ directory structure and knowledge-wiki skill for structured knowledge accumulation - Auto-inject MEMORY.md into system prompt with truncation (last 200 lines) - Light Dream: extend flush_memory to extract long-term memories into MEMORY.md with date stamps - Add mandatory knowledge auto-write rules in system prompt (no user confirmation needed) - Expand MemoryManager.sync() to index knowledge/ files for vector search - Update RULE.md template with workspace conventions and knowledge guidelines	2026-04-09 21:22:43 +08:00
@@ -1 +1 @@
 .0.5
 .0.6