Merge remote-tracking branch 'upstream/main' into dev/dj_agent

Author: cmgzn

.pre-commit-config.yaml

@@ -34,12 +34,8 @@ If you'd like a feature or new type of example that doesn't exist in AgentScope
 ### Setup
 
 1. **Fork and clone** the repository
-2. **Install pre-commit**:
-   ```bash
-   pip install pre-commit
-   pre-commit install
-   ```
-3. **Create a branch**:
+
+2. **Create a branch**:
    ```bash
    git checkout -b feature/your-sample-name
    ```
@@ -126,23 +122,6 @@ Your README.md **must** include:
 
 Each example must include a standalone `requirements.txt` file listing all necessary dependencies to ensure it can be installed and run independently without relying on other examples.
 
-#### Code Quality
-
-We enforce the following using pre-commit hooks:
-
-- **Black**: Code formatting (line length 79)
-- **flake8** and **pylint**: Code linting
-- **mypy**: Type checking
-
-When writing example code:
-- Add clear comments and follow existing code style
-- Add type hints to function signatures
-- Keep code simple and focused on demonstrating specific features
-
-Ensure all checks pass:
-```bash
-pre-commit run --all-files
-```
 
 ### Submitting Your Contribution
 

CONTRIBUTING.md

@@ -34,12 +34,8 @@
 ### 设置
 
 1. **Fork 并克隆**仓库
-2. **安装 pre-commit**：
-   ```bash
-   pip install pre-commit
-   pre-commit install
-   ```
-3. **创建分支**：
+
+2. **创建分支**：
    ```bash
    git checkout -b feature/your-sample-name
    ```
@@ -126,24 +122,6 @@ your_sample_fullstack_runtime/
 
 每个示例需包含独立的 `requirements.txt` 文件，列出所有必需的依赖项，以确保可独立安装和运行，不依赖其他示例。
 
-#### 代码质量
-
-我们使用 pre-commit hooks 强制执行：
-
-- **Black**：代码格式化（行长度 79）
-- **flake8** 和 **pylint**：代码检查
-- **mypy**：类型检查
-
-编写示例代码时：
-- 添加清晰的注释，遵循现有代码风格
-- 为函数签名添加类型提示
-- 保持代码简单，专注于演示特定功能
-
-确保通过所有检查：
-```bash
-pre-commit run --all-files
-```
-
 ### 提交您的贡献
 
 1. **提交**时使用清晰的消息：

CONTRIBUTING_zh.md

@@ -79,19 +79,7 @@ It includes **agent deployment** and **secure sandboxed tool execution**, and ca
 ├── evaluation/
 │   └── ace_bench/                          # Benchmarks and evaluation tools
 │
-├── functionality/
-│   ├── long_term_memory_mem0/              # Long-term memory integration
-│   ├── mcp/                                # Memory/Context Protocol demo
-│   ├── plan/                               # Plan with ReAct Agent
-│   ├── rag/                                # RAG in AgentScope
-│   ├── session_with_sqlite/                # Persistent conversation with SQLite
-│   ├── stream_printing_messages/           # Streaming and printing messages
-│   ├── structured_output/                  # Structured output parsing and validation
-│   ├── multiagent_concurrent/              # Concurrent multi-agent task execution
-│   └── meta_planner_agent/                 # Planning agent with tool orchestration
-│
 ├── data_juicer_agent/                      # Data processing multi-agent system
-│
 ├── sample_template/                        # Template for new sample contributions
 └── README.md
 ```
@@ -112,15 +100,6 @@ It includes **agent deployment** and **secure sandboxed tool execution**, and ca
 |                         | conversational_agents/multiagent_conversation         | ✅               | ❌            | Multi-agent dialogue scenario                    |
 |                         | conversational_agents/multiagent_debate               | ✅               | ❌            | Agents engaging in debates                       |
 | **Evaluation**          | evaluation/ace_bench                                  | ✅               | ❌            | Benchmarks with ACE Bench                        |
-| **Functionality Demos** | functionality/long_term_memory_mem0                   | ✅               | ❌            | Long-term memory with mem0 support               |
-|                         | functionality/mcp                                     | ✅               | ❌            | Memory/Context Protocol demo                     |
-|                         | functionality/session_with_sqlite                     | ✅               | ❌            | Persistent context with SQLite                   |
-|                         | functionality/structured_output                       | ✅               | ❌            | Structured data extraction and validation        |
-|                         | functionality/multiagent_concurrent                   | ✅               | ❌            | Concurrent task execution by multiple agents     |
-|                         | functionality/meta_planner_agent                      | ✅               | ❌            | Planning agent with tool orchestration           |
-|                         | functionality/plan                                    | ✅               | ❌            | Task planning with ReAct agent                   |
-|                         | functionality/rag                                     | ✅               | ❌            | Retrieval-Augmented Generation (RAG) integration |
-|                         | functionality/stream_printing_messages                | ✅               | ❌            | Real-time message streaming and printing         |
 | **Data Processing**     | data_juicer_agent/                                   | ✅               | ❌            | Multi-agent data processing with Data-Juicer     |
 
 ------

README.md

@@ -79,19 +79,7 @@ AgentScope Runtime 是一个**全面的运行时框架**，主要解决部署和
 ├── evaluation/
 │   └── ace_bench/                          # 基准测试与评估工具
 │
-├── functionality/
-│   ├── long_term_memory_mem0/              # 长期记忆集成
-│   ├── mcp/                                # Memory/Context 协议演示
-│   ├── plan/                               # ReAct Agent 任务计划
-│   ├── rag/                                # AgentScope 中的 RAG
-│   ├── session_with_sqlite/                # 基于 SQLite 的持久对话
-│   ├── stream_printing_messages/           # 信息流式输出与打印
-│   ├── structured_output/                  # 结构化输出解析与验证
-│   ├── multiagent_concurrent/              # 多 Agent 并发任务执行
-│   └── meta_planner_agent/                 # 带工具编排的计划 Agent
-│
 ├── data_juicer_agent/                      # 数据处理多智能体系统
-│
 ├── sample_template/                        # 新样例贡献模板
 └── README.md
 ```
@@ -112,15 +100,6 @@ AgentScope Runtime 是一个**全面的运行时框架**，主要解决部署和
 |                         | conversational_agents/multiagent_conversation       | ✅               | ❌                       | 多 Agent 对话场景 |
 |                         | conversational_agents/multiagent_debate             | ✅               | ❌                       | Agent 辩论 |
 | **评估**                | evaluation/ace_bench                                | ✅               | ❌                       | ACE Bench 基准测试 |
-| **功能演示**            | functionality/long_term_memory_mem0                 | ✅               | ❌                       | 长期记忆（mem0 支持） |
-|                         | functionality/mcp                                   | ✅               | ❌                       | Memory/Context 协议 Demo |
-|                         | functionality/session_with_sqlite                   | ✅               | ❌                       | 基于 SQLite 的持久上下文 |
-|                         | functionality/structured_output                     | ✅               | ❌                       | 结构化数据提取与验证 |
-|                         | functionality/multiagent_concurrent                 | ✅               | ❌                       | 多 Agent 并发任务执行 |
-|                         | functionality/meta_planner_agent                    | ✅               | ❌                       | 带工具编排的计划 Agent |
-|                         | functionality/plan                                  | ✅               | ❌                       | 使用 ReAct Agent 规划任务 |
-|                         | functionality/rag                                   | ✅               | ❌                       | 检索增强生成 (RAG) 集成 |
-|                         | functionality/stream_printing_messages              | ✅               | ❌                       | 实时信息流输出与打印 |
 | **数据处理**            | data_juicer_agent/                                 | ✅               | ❌                       | 基于 Data-Juicer 的多智能体数据处理 |
 
 ---