bugfix: The artifact name autofix.ci is not valid

.github/workflows/autofix.yml

@@ -34,4 +34,4 @@ jobs:
       - name: Run prettier
         run: pnpm run format
 
-      - uses: autofix-ci/action@d3e591514b99d0fca6779455ff8338516663f7cc
+      - uses: autofix-ci/action@v1.3.1

src/en/guide/get_started/configuration/llm_api_configuration.md

@@ -1,5 +1,6 @@
 # LLM API Configuration
- # LLM API Configuration
+
+# LLM API Configuration
 
 After completing the installation, follow these steps to configure the LLM API, using the OpenAI API as an example. This process is similar for other LLM APIs.
 

src/en/guide/in_depth_guides/environment/mgx.md

@@ -11,11 +11,12 @@ MGXEnv is a generic multi-agent collaboration environment that provides a flexib
 MGXEnv mainly handles message routing and publishing in a multi-agent environment. The core message space is defined by the Message class with the following structure:
 
 Definition:
+
 ```python
 from gymnasium import spaces
 
 space = {
-    "role": spaces.Text(16),         # Message role type 
+    "role": spaces.Text(16),         # Message role type
     "content": spaces.Text(1024),    # Actual message content
     "sent_from": spaces.Text(32),    # Sender name
     "send_to": spaces.Set(spaces.Text(32)),  # Set of recipient names
@@ -25,21 +26,22 @@ space = {
 
 Message Space Components:
 
-| Field | Description | Value Range |
-|-------|-------------|-------------|
-| role | Message role type | One of ["user", "assistant", "system"] |
-| content | Actual message content | Maximum length 1024 characters |
-| sent_from | Message sender name | Maximum length 32 characters |
-| send_to | Set of recipient names | Each name maximum 32 characters |
-| metadata | Additional message metadata | Dictionary containing optional fields (like images) |
+| Field     | Description                 | Value Range                                         |
+| --------- | --------------------------- | --------------------------------------------------- |
+| role      | Message role type           | One of ["user", "assistant", "system"]              |
+| content   | Actual message content      | Maximum length 1024 characters                      |
+| sent_from | Message sender name         | Maximum length 32 characters                        |
+| send_to   | Set of recipient names      | Each name maximum 32 characters                     |
+| metadata  | Additional message metadata | Dictionary containing optional fields (like images) |
 
 Message Example:
+
 ```python
 from metagpt.schema import Message
 
 Message(
     role="assistant",
-    content="Analysis completed.", 
+    content="Analysis completed.",
     sent_from="Alice",
     send_to={"Mike", "<all>"},
     metadata={"agent": "Emma"}
@@ -51,11 +53,13 @@ Message(
 The environment supports two communication modes:
 
 1. Public Chat Mode (default)
+
 - All messages visible to all roles (send_to includes <all>)
 - Message flow coordinated by team leader (Mike)
 - Messages stored in environment history
 
-2. Direct Chat Mode 
+2. Direct Chat Mode
+
 - Triggered when user directly messages a specific role
 - Communication only between user and target role
 - Bypasses team leader
@@ -93,4 +97,4 @@ requirement = "create a 2048 game"
 tl = env.get_role("Mike")
 env.publish_message(Message(content=requirement, send_to=tl.name))
 await tl.run()
-```
+```

src/zh/guide/in_depth_guides/environment/mgx.md

@@ -10,11 +10,12 @@ MGXEnv 是一个通用的多智能体协作环境，提供了一个灵活而强
 MGXEnv 主要处理多智能体环境中的消息路由和发布。核心消息空间由 Message 类定义,结构如下:
 
 定义:
+
 ```python
 from gymnasium import spaces
 
 space = {
-    "role": spaces.Text(16),         # 消息角色类型 
+    "role": spaces.Text(16),         # 消息角色类型
     "content": spaces.Text(1024),    # 实际消息内容
     "sent_from": spaces.Text(32),    # 发送者名称
     "send_to": spaces.Set(spaces.Text(32)),  # 接收者名称集合
@@ -24,21 +25,22 @@ space = {
 
 消息空间组件说明:
 
-| 字段 | 说明 | 取值说明 |
-|------|------|----------|
-| role | 消息角色类型 | ["user", "assistant", "system"] 之一 |
-| content | 实际消息内容 | 最大长度1024字符 |
-| sent_from | 消息发送者名称 | 最大长度32字符 |
-| send_to | 接收者名称集合 | 每个名称最大32字符 |
-| metadata | 额外的消息元数据 | 包含可选字段(如图片)的字典 |
+| 字段      | 说明             | 取值说明                             |
+| --------- | ---------------- | ------------------------------------ |
+| role      | 消息角色类型     | ["user", "assistant", "system"] 之一 |
+| content   | 实际消息内容     | 最大长度1024字符                     |
+| sent_from | 消息发送者名称   | 最大长度32字符                       |
+| send_to   | 接收者名称集合   | 每个名称最大32字符                   |
+| metadata  | 额外的消息元数据 | 包含可选字段(如图片)的字典           |
 
 消息示例:
+
 ```python
 from metagpt.schema import Message
 
 Message(
     role="assistant",
-    content="我已完成分析。", 
+    content="我已完成分析。",
     sent_from="Alice",
     send_to={"Mike", "<all>"},
     metadata={"agent": "Emma"}
@@ -50,19 +52,20 @@ Message(
 环境支持两种通信模式:
 
 1. 公共聊天模式(默认)
+
 - 所有消息对所有角色可见(send_to 包含 <all>)
 - 由团队领导(Mike)协调消息流
 - 消息存储在环境历史记录中
 
-2. 直接聊天模式 
+2. 直接聊天模式
+
 - 当用户直接与特定角色对话时触发
 - 仅在用户和目标角色之间进行
 - 绕过团队领导
 - 消息是否发布给所有人取决于 is_public_chat 标志
 
 这个环境主要关注消息的路由和协调,而不是其他环境中常见的状态/动作空间。
 
-
 ## 使用
 
 ```python
@@ -95,4 +98,3 @@ env.publish_message(Message(content=requirement, send_to=tl.name))
 await tl.run()
 
 ```
-