diff --git a/config/__init__.py b/config/__init__.py
new file mode 100644
index 0000000..bbee05c
--- /dev/null
+++ b/config/__init__.py
@@ -0,0 +1,10 @@
+from .llm_config import get_llm_config, PM_PROMPT, QA_PROMPT, DEV_PROMPT, ORCH_PROMPT
+
+
+__all__ = [
+    "get_llm_config",
+    "PM_PROMPT",
+    "QA_PROMPT",
+    "DEV_PROMPT",
+    "ORCH_PROMPT",
+]
diff --git a/frontend/app.py b/frontend/app.py
new file mode 100644
index 0000000..9cf81c1
--- /dev/null
+++ b/frontend/app.py
@@ -0,0 +1,280 @@
+# -*- coding: utf-8 -*-
+"""
+Streamlit 实时 Agent 协作平台
+功能：
+1. 实时展示每个 Agent 的状态和动作
+2. 自动保存生成的文件到 workspace/
+3. 简单稳定的代码结构
+"""
+import streamlit as st
+import os
+from pathlib import Path
+from datetime import datetime
+import time
+
+try:
+    from autogen import AssistantAgent, UserProxyAgent, GroupChat, GroupChatManager
+    AUTOGEN_AVAILABLE = True
+except ImportError:
+    AUTOGEN_AVAILABLE = False
+
+# 添加项目根目录到路径
+import sys
+sys.path.insert(0, str(Path(__file__).parent.parent))
+
+from config.llm_config import get_llm_config, PM_PROMPT, QA_PROMPT, DEV_PROMPT, ORCH_PROMPT
+
+# 页面配置
+st.set_page_config(page_title="多 Agent 协作平台", page_icon="🤖", layout="wide")
+
+# Agent 配置
+AGENTS = {
+    "PM_Agent": {"name": "产品经理", "avatar": "📋", "color": "blue"},
+    "QA_Agent": {"name": "测试工程师", "avatar": "✅", "color": "green"},
+    "Dev_Agent": {"name": "开发工程师", "avatar": "💻", "color": "orange"},
+    "Orchestrator": {"name": "协调器", "avatar": "🎯", "color": "purple"},
+    "User_Proxy": {"name": "用户代理", "avatar": "👤", "color": "gray"}
+}
+
+def init_state():
+    """初始化 session state"""
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+    if "running" not in st.session_state:
+        st.session_state.running = False
+    if "current_agent" not in st.session_state:
+        st.session_state.current_agent = None
+    if "agent_counts" not in st.session_state:
+        st.session_state.agent_counts = {k: 0 for k in AGENTS}
+
+def add_message(agent, content, task=""):
+    """添加消息"""
+    msg = {
+        "agent": agent,
+        "content": content,
+        "task": task,
+        "time": datetime.now().strftime("%H:%M:%S")
+    }
+    st.session_state.messages.append(msg)
+    st.session_state.agent_counts[agent] = st.session_state.agent_counts.get(agent, 0) + 1
+    st.session_state.current_agent = agent
+
+def show_agent_status():
+    """显示 Agent 状态"""
+    cols = st.columns(len(AGENTS))
+    for i, (agent_key, info) in enumerate(AGENTS.items()):
+        with cols[i]:
+            is_active = st.session_state.current_agent == agent_key
+            count = st.session_state.agent_counts.get(agent_key, 0)
+            
+            border_color = info["color"]
+            bg_color = "#e8f5e9" if is_active else "white"
+            
+            st.markdown(f"""
+            <div style='
+                padding: 15px;
+                border-radius: 10px;
+                border: 3px {"solid" if is_active else "dashed"} {border_color};
+                background: {bg_color};
+                text-align: center;
+            '>
+                <div style='font-size: 2.5rem;'>{info["avatar"]}</div>
+                <div style='font-weight: bold; margin: 5px 0;'>{info["name"]}</div>
+                <div style='font-size: 0.8rem; color: #666;'>
+                    {"🟢 发言中" if is_active else "⚪ 等待中"}
+                </div>
+                <div style='font-size: 0.8rem; color: #999; margin-top: 5px;'>
+                    💬 {count} 条消息
+                </div>
+            </div>
+            """, unsafe_allow_html=True)
+
+def show_chat():
+    """显示对话流"""
+    st.subheader("💬 Agent 对话流")
+    
+    if not st.session_state.messages:
+        st.info("👈 暂无对话，请在下方输入需求并启动")
+        return
+    
+    for msg in st.session_state.messages:
+        agent = msg["agent"]
+        info = AGENTS.get(agent, {"name": "未知", "avatar": "🤖", "color": "gray"})
+        
+        with st.chat_message(agent.lower(), avatar=info["avatar"]):
+            st.markdown(f"**{info['name']}** *{msg['time']}* - {msg['task']}")
+            st.markdown(msg["content"][:800] + ("..." if len(msg["content"]) > 800 else ""))
+
+def save_files():
+    """保存生成的文件到 workspace/"""
+    workspace = Path("workspace")
+    workspace.mkdir(exist_ok=True)
+    
+    files = []
+    
+    # 遍历消息，提取并保存文件
+    for msg in st.session_state.messages:
+        agent = msg["agent"]
+        content = msg["content"]
+        
+        # PM Agent 生成 SRS
+        if agent == "PM_Agent" and ("需求" in content or "SRS" in content):
+            file = workspace / "SRS.md"
+            with open(file, "w", encoding="utf-8") as f:
+                f.write(f"# 软件需求规格说明书\n\n生成时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n{content}")
+            files.append(str(file))
+        
+        # QA Agent 生成测试
+        if agent == "QA_Agent" and ("test" in content.lower() or "测试" in content):
+            file = workspace / "test_sample.py"
+            with open(file, "w", encoding="utf-8") as f:
+                f.write(f"# 测试用例\n# 生成时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n{content}")
+            files.append(str(file))
+        
+        # Dev Agent 生成代码
+        if agent == "Dev_Agent" and ("def " in content or "class " in content):
+            file = workspace / "src_sample.py"
+            with open(file, "w", encoding="utf-8") as f:
+                f.write(f"# 源代码\n# 生成时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n{content}")
+            files.append(str(file))
+    
+    return files
+
+def main():
+    st.title("🤖 多 Agent 协作平台")
+    st.markdown("**实时展示 Agent 状态 · 自动生成文件**")
+    
+    init_state()
+    
+    # 侧边栏
+    with st.sidebar:
+        st.title("⚙️ 配置")
+        
+        api_key = st.text_input("API Key", type="password", value=os.getenv("DASHSCOPE_API_KEY", ""))
+        model = st.selectbox("模型", ["qwen3.5-flash", "qwen-max", "qwen-plus"], index=0)
+        max_round = st.slider("最大轮数", 5, 30, 15)
+        
+        st.divider()
+        
+        if st.button("▶️ 启动工作流", type="primary", use_container_width=True):
+            if not api_key:
+                st.error("请先设置 API Key")
+            elif not AUTOGEN_AVAILABLE:
+                st.error("请先安装 AutoGen")
+            else:
+                run_workflow(api_key, model, max_round)
+        
+        st.divider()
+        
+        if st.button("🗑️ 清空对话", use_container_width=True):
+            st.session_state.messages = []
+            st.session_state.current_agent = None
+            st.session_state.agent_counts = {k: 0 for k in AGENTS}
+            st.rerun()
+        
+        # 显示生成的文件
+        st.divider()
+        st.subheader("📁 生成的文件")
+        workspace = Path("workspace")
+        if workspace.exists():
+            for file in workspace.glob("*"):
+                if file.is_file():
+                    st.caption(f"📄 {file.name}")
+    
+    # 主界面
+    show_agent_status()
+    st.divider()
+    show_chat()
+    
+    # 输入框
+    st.divider()
+    if user_input := st.chat_input("输入需求..."):
+        add_message("User_Proxy", user_input, "提出需求")
+        st.rerun()
+
+def run_workflow(api_key, model, max_round):
+    """运行工作流"""
+    st.session_state.running = True
+    st.session_state.messages = []
+    st.session_state.agent_counts = {k: 0 for k in AGENTS}
+    
+    progress = st.empty()
+    progress.info("🚀 启动工作流...")
+    
+    try:
+        # 获取需求
+        user_msgs = [m for m in st.session_state.messages if m["agent"] == "User_Proxy"]
+        requirement = user_msgs[-1]["content"] if user_msgs else "开发一个电池健康预测 API"
+        
+        # 创建 Agent
+        llm_config = get_llm_config(model=model, api_key=api_key)
+        
+        pm = AssistantAgent("PM_Agent", system_message=PM_PROMPT, llm_config=llm_config, human_input_mode="NEVER")
+        qa = AssistantAgent("QA_Agent", system_message=QA_PROMPT, llm_config=llm_config, human_input_mode="NEVER")
+        dev = AssistantAgent("Dev_Agent", system_message=DEV_PROMPT, llm_config=llm_config, human_input_mode="NEVER")
+        orch = AssistantAgent("Orchestrator", system_message=ORCH_PROMPT, llm_config=llm_config, human_input_mode="NEVER")
+        user = UserProxyAgent("User_Proxy", human_input_mode="NEVER", max_consecutive_auto_reply=0, 
+                             code_execution_config={"work_dir": "workspace", "use_docker": False})
+        
+        # 创建 GroupChat
+        groupchat = GroupChat(
+            agents=[pm, qa, dev, orch, user],
+            messages=[],
+            max_round=max_round,
+            speaker_selection_method="round_robin"
+        )
+        manager = GroupChatManager(groupchat=groupchat, llm_config=llm_config)
+        
+        # 初始消息
+        initial_msg = f"""请启动完整的 SDLC 流程：
+
+【用户需求】{requirement}
+
+【流程】
+1. PM_Agent → SRS 文档
+2. QA_Agent → 测试用例
+3. Dev_Agent → 编写代码
+4. User_Proxy → 执行测试
+5. Orchestrator → 汇总
+
+开始协作！"""
+        
+        # 执行对话
+        with st.spinner("💬 Agent 们正在协作中..."):
+            chat_result = user.initiate_chat(manager, message=initial_msg, max_turns=max_round)
+        
+        # 记录所有对话
+        task_map = {
+            "PM_Agent": "需求分析",
+            "QA_Agent": "测试设计", 
+            "Dev_Agent": "代码实现",
+            "Orchestrator": "流程协调",
+            "User_Proxy": "测试执行"
+        }
+        
+        for msg in groupchat.messages:
+            agent = msg.get("name", "Unknown")
+            content = msg.get("content", "")
+            task = task_map.get(agent, "工作中")
+            add_message(agent, content, task)
+        
+        # 保存文件
+        progress.info("💾 正在保存文件...")
+        files = save_files()
+        
+        if files:
+            progress.success(f"✅ 完成！已保存 {len(files)} 个文件到 workspace/")
+        else:
+            progress.success("✅ 工作流完成！")
+        
+        st.session_state.running = False
+        st.rerun()
+        
+    except Exception as e:
+        st.session_state.running = False
+        progress.error(f"❌ 错误：{e}")
+        import traceback
+        st.error(traceback.format_exc())
+
+if __name__ == "__main__":
+    main()
diff --git a/frontend/streamlit_app.py b/frontend/streamlit_app.py
deleted file mode 100644
index 5246027..0000000
--- a/frontend/streamlit_app.py
+++ /dev/null
@@ -1,442 +0,0 @@
-"""
-Streamlit 前端 - 多智能体实时聊天界面
-提供可视化的 Agent 协同工作展示和人机交互
-"""
-import streamlit as st
-import os
-import sys
-from pathlib import Path
-from datetime import datetime
-import time
-from typing import Dict, Any, List
-
-# 添加项目根目录到路径
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-from autogen import AssistantAgent, UserProxyAgent, GroupChat, GroupChatManager
-from config.llm_config import (
-    get_llm_config, 
-    PM_PROMPT, 
-    QA_PROMPT, 
-    DEV_PROMPT, 
-    ORCH_PROMPT
-)
-
-
-# 页面配置
-st.set_page_config(
-    page_title="AutoGen SDLC 多智能体系统",
-    page_icon="🤖",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
-
-# 自定义 CSS 样式
-st.markdown("""
-<style>
-.agent-message {
-    padding: 1rem;
-    border-radius: 0.5rem;
-    margin-bottom: 1rem;
-}
-.pm-agent { background-color: #e3f2fd; border-left: 4px solid #2196f3; }
-.qa-agent { background-color: #e8f5e9; border-left: 4px solid #4caf50; }
-.dev-agent { background-color: #fff3e0; border-left: 4px solid #ff9800; }
-.orchestrator { background-color: #f3e5f5; border-left: 4px solid #9c27b0; }
-.system { background-color: #fce4ec; border-left: 4px solid #e91e63; }
-.user { background-color: #efebe9; border-left: 4px solid #795548; }
-</style>
-""", unsafe_allow_html=True)
-
-
-def init_session_state():
-    """初始化 session state"""
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
-    if "is_running" not in st.session_state:
-        st.session_state.is_running = False
-    if "workflow_result" not in st.session_state:
-        st.session_state.workflow_result = None
-    if "conversation_history" not in st.session_state:
-        st.session_state.conversation_history = []
-    if "current_step" not in st.session_state:
-        st.session_state.current_step = 0
-
-
-def create_agents(api_key: str, base_url: str, model: str):
-    """创建所有 Agent"""
-    llm_config = get_llm_config(model=model, api_key=api_key, base_url=base_url)
-    
-    pm_agent = AssistantAgent(
-        name="PM_Agent",
-        system_message=PM_PROMPT,
-        llm_config=llm_config,
-        description="资深软件产品经理",
-        human_input_mode="NEVER"
-    )
-    
-    qa_agent = AssistantAgent(
-        name="QA_Agent",
-        system_message=QA_PROMPT,
-        llm_config=llm_config,
-        description="资深测试工程师",
-        human_input_mode="NEVER"
-    )
-    
-    dev_agent = AssistantAgent(
-        name="Dev_Agent",
-        system_message=DEV_PROMPT,
-        llm_config=llm_config,
-        description="资深软件工程师",
-        human_input_mode="NEVER"
-    )
-    
-    orchestrator = AssistantAgent(
-        name="Orchestrator",
-        system_message=ORCH_PROMPT,
-        llm_config=llm_config,
-        description="多智能体协调器",
-        human_input_mode="NEVER"
-    )
-    
-    user_proxy = UserProxyAgent(
-        name="User_Proxy",
-        human_input_mode="NEVER",  # 修复：Web 环境不支持 TERMINAL
-        max_consecutive_auto_reply=0,
-        code_execution_config={
-            "work_dir": "workspace",
-            "use_docker": False,
-        },
-        is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE")
-    )
-    
-    return pm_agent, qa_agent, dev_agent, orchestrator, user_proxy, llm_config
-
-
-def get_agent_color(agent_name: str) -> str:
-    """根据 Agent 名称返回颜色类"""
-    color_map = {
-        "PM_Agent": "pm-agent",
-        "QA_Agent": "qa-agent",
-        "Dev_Agent": "dev-agent",
-        "Orchestrator": "orchestrator",
-        "User_Proxy": "user",
-        "system": "system"
-    }
-    return color_map.get(agent_name, "system")
-
-
-def display_message(agent_name: str, message: str, timestamp: str):
-    """显示单条消息"""
-    color_class = get_agent_color(agent_name)
-    
-    # 头像映射
-    avatar_map = {
-        "PM_Agent": "📋",
-        "QA_Agent": "✅",
-        "Dev_Agent": "💻",
-        "Orchestrator": "🎯",
-        "User_Proxy": "👤",
-        "system": "⚙️"
-    }
-    
-    avatar = avatar_map.get(agent_name, "🤖")
-    
-    with st.chat_message(name=agent_name.lower().replace("_", ""), avatar=avatar):
-        st.markdown(f"**{avatar} {agent_name}** *({timestamp})*")
-        st.markdown(f"<div class='agent-message {color_class}'>{message}</div>", 
-                   unsafe_allow_html=True)
-
-
-def export_conversation(messages: List[Dict]) -> str:
-    """导出对话为 Markdown"""
-    md_content = "# AutoGen SDLC 对话历史\n\n"
-    md_content += f"**导出时间**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
-    md_content += "---\n\n"
-    
-    for msg in messages:
-        timestamp = msg.get("timestamp", "")[:19].replace('T', ' ')
-        agent = msg.get("agent_name", "Unknown")
-        content = msg.get("message", "")
-        
-        md_content += f"### [{timestamp}] {agent}\n\n"
-        md_content += f"{content}\n\n"
-        md_content += "---\n\n"
-    
-    return md_content
-
-
-def main():
-    """主应用"""
-    init_session_state()
-    
-    # ===== 左侧边栏 - 配置区域 =====
-    with st.sidebar:
-        st.title("⚙️ 配置")
-        
-        # API 配置
-        st.subheader("模型配置")
-        api_key = st.text_input(
-            "API Key",
-            type="password",
-            value=os.getenv("DASHSCOPE_API_KEY", ""),
-            help="阿里云 DashScope API Key"
-        )
-        
-        base_url = st.text_input(
-            "Base URL",
-            value="https://dashscope.aliyuncs.com/compatible-mode/v1",
-            help="API Base URL"
-        )
-        
-        model = st.selectbox(
-            "模型选择",
-            options=["qwen3.5-flash", "qwen-max", "qwen-plus", "qwen-turbo"],
-            index=0,
-            help="选择使用的 Qwen 模型"
-        )
-        
-        # Agent 参数
-        st.subheader("Agent 参数")
-        max_round = st.slider(
-            "最大对话轮数",
-            min_value=5,
-            max_value=50,
-            value=15,
-            step=1
-        )
-        
-        temperature = st.slider(
-            "温度参数",
-            min_value=0.0,
-            max_value=1.0,
-            value=0.7,
-            step=0.1
-        )
-        
-        st.divider()
-        
-        # 控制按钮
-        st.subheader("控制")
-        col1, col2 = st.columns(2)
-        
-        with col1:
-            start_btn = st.button("▶️ 启动", use_container_width=True)
-        with col2:
-            stop_btn = st.button("⏸️ 暂停", use_container_width=True)
-        
-        st.divider()
-        
-        # 导出选项
-        st.subheader("导出")
-        if st.button("📄 导出 JSON", use_container_width=True):
-            if st.session_state.messages:
-                import json
-                json_str = json.dumps(st.session_state.messages, ensure_ascii=False, indent=2)
-                st.download_button(
-                    label="下载 JSON",
-                    data=json_str,
-                    file_name=f"conversation_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json",
-                    mime="application/json"
-                )
-        
-        if st.button("📝 导出 Markdown", use_container_width=True):
-            if st.session_state.messages:
-                md_content = export_conversation(st.session_state.messages)
-                st.download_button(
-                    label="下载 Markdown",
-                    data=md_content,
-                    file_name=f"conversation_{datetime.now().strftime('%Y%m%d_%H%M%S')}.md",
-                    mime="text/markdown"
-                )
-    
-    # ===== 主区域 - 聊天展示 =====
-    st.title("🤖 AutoGen SDLC 多智能体协同系统")
-    st.markdown("**基于 AutoGen + Qwen3.5-flash 的端到端软件交付系统**")
-    
-    # 状态指示器
-    status_col1, status_col2, status_col3 = st.columns(3)
-    with status_col1:
-        st.metric("对话轮数", len(st.session_state.messages))
-    with status_col2:
-        status = "🟢 运行中" if st.session_state.is_running else "🔴 已停止"
-        st.metric("系统状态", status)
-    with status_col3:
-        result_status = "✅ 成功" if st.session_state.workflow_result and st.session_state.workflow_result.get("success") else "⏳ 未开始"
-        st.metric("工作流状态", result_status)
-    
-    st.divider()
-    
-    # 聊天历史展示区
-    chat_container = st.container()
-    with chat_container:
-        if not st.session_state.messages:
-            st.info("👈 请在左侧配置后，输入需求并点击启动按钮开始工作流")
-        else:
-            for msg in st.session_state.messages:
-                display_message(
-                    agent_name=msg.get("agent_name", "Unknown"),
-                    message=msg.get("message", ""),
-                    timestamp=msg.get("timestamp", "")
-                )
-    
-    # ===== 右侧边栏 - 进度和日志 =====
-    with st.sidebar:
-        st.divider()
-        
-        # 工作流进度
-        st.subheader("📊 工作流进度")
-        
-        workflow_steps = [
-            "需求分析",
-            "测试设计",
-            "代码实现",
-            "测试执行",
-            "最终验证"
-        ]
-        
-        current_step = st.session_state.get("current_step", 0)
-        for i, step in enumerate(workflow_steps):
-            if i < current_step:
-                st.success(f"✅ {step}")
-            elif i == current_step:
-                st.info(f"🔄 {step}")
-            else:
-                st.write(f"⚪ {step}")
-    
-    # ===== 用户输入区域 =====
-    st.divider()
-    
-    # 用户需求输入
-    user_input = st.chat_input("请输入您的软件需求...")
-    
-    if user_input:
-        # 添加用户消息到历史
-        user_msg = {
-            "timestamp": datetime.now().isoformat(),
-            "agent_name": "User",
-            "role": "user",
-            "message": user_input
-        }
-        st.session_state.messages.append(user_msg)
-        st.session_state.conversation_history.append(user_msg)
-        
-        # 如果正在运行，添加到队列等待处理
-        if st.session_state.is_running:
-            # 这里会触发工作流执行
-            pass
-    
-    # ===== 工作流执行逻辑 =====
-    if start_btn:
-        if not api_key:
-            st.error("请先设置 API Key！")
-            st.stop()
-        
-        # 获取最后一条用户消息
-        user_messages = [m for m in st.session_state.messages if m.get("role") == "user"]
-        if not user_messages:
-            st.warning("请先输入需求！")
-            st.stop()
-        
-        latest_requirement = user_messages[-1]["message"]
-        
-        # 设置运行状态
-        st.session_state.is_running = True
-        st.session_state.current_step = 0
-        
-        # 创建占位符用于实时更新
-        status_placeholder = st.empty()
-        message_placeholder = st.empty()
-        
-        with status_placeholder:
-            st.info("🚀 正在启动 SDLC 工作流...")
-        
-        try:
-            # 创建 Agent
-            pm_agent, qa_agent, dev_agent, orchestrator, user_proxy, llm_config = create_agents(
-                api_key=api_key,
-                base_url=base_url,
-                model=model
-            )
-            
-            # 创建 GroupChat
-            groupchat = GroupChat(
-                agents=[pm_agent, qa_agent, dev_agent, orchestrator, user_proxy],
-                messages=[],
-                max_round=max_round,
-                speaker_selection_method="round_robin"
-            )
-            
-            manager = GroupChatManager(groupchat=groupchat, llm_config=llm_config)
-            
-            # 构建初始消息
-            initial_message = f"""
-请启动完整的 SDLC 流程：
-
-【用户需求】
-{latest_requirement}
-
-【工作流程】
-1. PM_Agent → 生成 SRS
-2. QA_Agent → 生成测试用例
-3. Dev_Agent → 编写代码
-4. User_Proxy → 执行测试
-5. Orchestrator → 汇总报告
-
-开始协作！
-"""
-            
-            # 记录第一条消息
-            first_msg = {
-                "timestamp": datetime.now().isoformat(),
-                "agent_name": "Orchestrator",
-                "role": "assistant",
-                "message": f"🎯 启动 SDLC 工作流，需求：{latest_requirement[:100]}..."
-            }
-            st.session_state.messages.append(first_msg)
-            st.session_state.current_step = 0
-            
-            # 启动对话（简化版本，实际应该用异步）
-            with message_placeholder:
-                st.info("💬 Agent 们正在协作中，请稍候...")
-            
-            # 这里简化处理，实际应该使用异步回调
-            chat_result = user_proxy.initiate_chat(
-                manager,
-                message=initial_message,
-                max_turns=max_round
-            )
-            
-            # 记录结果
-            for msg in groupchat.messages:
-                chat_msg = {
-                    "timestamp": datetime.now().isoformat(),
-                    "agent_name": msg.get("name", "Unknown"),
-                    "role": msg.get("role", "assistant"),
-                    "message": msg.get("content", "")
-                }
-                st.session_state.messages.append(chat_msg)
-            
-            # 更新状态
-            st.session_state.workflow_result = {
-                "success": True,
-                "summary": chat_result.summary if hasattr(chat_result, 'summary') else "完成"
-            }
-            st.session_state.current_step = 5  # 完成所有步骤
-            st.session_state.is_running = False
-            
-            # 刷新显示
-            st.rerun()
-            
-        except Exception as e:
-            st.session_state.is_running = False
-            st.error(f"❌ 错误：{str(e)}")
-            st.session_state.workflow_result = {"success": False, "error": str(e)}
-    
-    if stop_btn:
-        st.session_state.is_running = False
-        st.info("⏸️ 工作流已暂停")
-
-
-if __name__ == "__main__":
-    main()
diff --git a/frontend/streamlit_app_v2.py b/frontend/streamlit_app_v2.py
deleted file mode 100644
index da8c9d1..0000000
--- a/frontend/streamlit_app_v2.py
+++ /dev/null
@@ -1,725 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Streamlit 前端 v2 - 增强版多智能体实时协作可视化界面
-功能：
-1. Agent 协作流程图（桑基图）
-2. 实时状态监控面板
-3. 分屏对话展示
-4. 生成的文件预览
-5. 时间线视图
-"""
-import streamlit as st
-import os
-import sys
-from pathlib import Path
-from datetime import datetime
-import time
-from typing import Dict, Any, List
-import json
-
-# 添加项目根目录到路径
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-try:
-    from autogen import AssistantAgent, UserProxyAgent, GroupChat, GroupChatManager
-    AUTOGEN_AVAILABLE = True
-except ImportError:
-    AUTOGEN_AVAILABLE = False
-
-from config.llm_config import (
-    get_llm_config, 
-    PM_PROMPT, 
-    QA_PROMPT, 
-    DEV_PROMPT, 
-    ORCH_PROMPT
-)
-
-
-# 页面配置
-st.set_page_config(
-    page_title="AutoGen SDLC 多智能体协作平台",
-    page_icon="🤖",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
-
-# 自定义 CSS 样式
-st.markdown("""
-<style>
-/* Agent 消息样式 */
-.agent-message {
-    padding: 1rem;
-    border-radius: 0.5rem;
-    margin-bottom: 1rem;
-    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
-}
-.pm-agent { background: linear-gradient(135deg, #e3f2fd 0%, #bbdefb 100%); border-left: 5px solid #2196f3; }
-.qa-agent { background: linear-gradient(135deg, #e8f5e9 0%, #c8e6c9 100%); border-left: 5px solid #4caf50; }
-.dev-agent { background: linear-gradient(135deg, #fff3e0 0%, #ffe0b2 100%); border-left: 5px solid #ff9800; }
-.orchestrator { background: linear-gradient(135deg, #f3e5f5 0%, #e1bee7 100%); border-left: 5px solid #9c27b0; }
-.system { background: linear-gradient(135deg, #fce4ec 0%, #f8bbd9 100%); border-left: 5px solid #e91e63; }
-.user { background: linear-gradient(135deg, #efebe9 0%, #d7ccc8 100%); border-left: 5px solid #795548; }
-
-/* 状态卡片 */
-.status-card {
-    padding: 1.5rem;
-    border-radius: 0.5rem;
-    text-align: center;
-    color: white;
-    font-weight: bold;
-}
-.status-running { background: linear-gradient(135deg, #4caf50, #8bc34a); }
-.status-stopped { background: linear-gradient(135deg, #f44336, #e91e63); }
-.status-pending { background: linear-gradient(135deg, #ff9800, #ffc107); }
-
-/* Agent 状态指示器 */
-.agent-status-indicator {
-    display: inline-block;
-    width: 12px;
-    height: 12px;
-    border-radius: 50%;
-    margin-right: 8px;
-    animation: pulse 2s infinite;
-}
-@keyframes pulse {
-    0% { opacity: 1; }
-    50% { opacity: 0.5; }
-    100% { opacity: 1; }
-}
-
-/* 文件卡片 */
-.file-card {
-    padding: 1rem;
-    border: 1px solid #ddd;
-    border-radius: 0.5rem;
-    margin-bottom: 0.5rem;
-    background: #f9f9f9;
-}
-
-/* 时间线 */
-.timeline-item {
-    padding: 1rem;
-    border-left: 3px solid #2196f3;
-    margin-left: 1rem;
-    position: relative;
-}
-.timeline-item::before {
-    content: '';
-    position: absolute;
-    left: -8px;
-    top: 1rem;
-    width: 13px;
-    height: 13px;
-    border-radius: 50%;
-    background: #2196f3;
-}
-</style>
-""", unsafe_allow_html=True)
-
-
-# Agent 配置信息
-AGENT_CONFIG = {
-    "PM_Agent": {
-        "name": "产品经理",
-        "avatar": "📋",
-        "color": "#2196f3",
-        "description": "需求分析与 SRS 生成",
-        "icon": "📊"
-    },
-    "QA_Agent": {
-        "name": "测试工程师",
-        "avatar": "✅",
-        "color": "#4caf50",
-        "description": "测试用例设计与 TDD",
-        "icon": "🧪"
-    },
-    "Dev_Agent": {
-        "name": "开发工程师",
-        "avatar": "💻",
-        "color": "#ff9800",
-        "description": "代码实现与修复",
-        "icon": "⚙️"
-    },
-    "Orchestrator": {
-        "name": "协调器",
-        "avatar": "🎯",
-        "color": "#9c27b0",
-        "description": "流程调度与验证",
-        "icon": "🎭"
-    },
-    "User_Proxy": {
-        "name": "用户代理",
-        "avatar": "👤",
-        "color": "#795548",
-        "description": "人机交互接口",
-        "icon": "🔌"
-    }
-}
-
-
-def init_session_state():
-    """初始化 session state"""
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
-    if "is_running" not in st.session_state:
-        st.session_state.is_running = False
-    if "workflow_result" not in st.session_state:
-        st.session_state.workflow_result = None
-    if "conversation_history" not in st.session_state:
-        st.session_state.conversation_history = []
-    if "current_step" not in st.session_state:
-        st.session_state.current_step = 0
-    if "agent_stats" not in st.session_state:
-        st.session_state.agent_stats = {
-            "PM_Agent": {"messages": 0, "last_active": None},
-            "QA_Agent": {"messages": 0, "last_active": None},
-            "Dev_Agent": {"messages": 0, "last_active": None},
-            "Orchestrator": {"messages": 0, "last_active": None},
-            "User_Proxy": {"messages": 0, "last_active": None}
-        }
-    if "generated_files" not in st.session_state:
-        st.session_state.generated_files = []
-    if "active_agent" not in st.session_state:
-        st.session_state.active_agent = None
-
-
-def create_agents(api_key: str, base_url: str, model: str):
-    """创建所有 Agent"""
-    llm_config = get_llm_config(model=model, api_key=api_key, base_url=base_url)
-    
-    pm_agent = AssistantAgent(
-        name="PM_Agent",
-        system_message=PM_PROMPT,
-        llm_config=llm_config,
-        description="资深软件产品经理",
-        human_input_mode="NEVER"
-    )
-    
-    qa_agent = AssistantAgent(
-        name="QA_Agent",
-        system_message=QA_PROMPT,
-        llm_config=llm_config,
-        description="资深测试工程师",
-        human_input_mode="NEVER"
-    )
-    
-    dev_agent = AssistantAgent(
-        name="Dev_Agent",
-        system_message=DEV_PROMPT,
-        llm_config=llm_config,
-        description="资深软件工程师",
-        human_input_mode="NEVER"
-    )
-    
-    orchestrator = AssistantAgent(
-        name="Orchestrator",
-        system_message=ORCH_PROMPT,
-        llm_config=llm_config,
-        description="多智能体协调器",
-        human_input_mode="NEVER"
-    )
-    
-    user_proxy = UserProxyAgent(
-        name="User_Proxy",
-        human_input_mode="NEVER",  # 修复：Web 环境不支持 TERMINAL
-        max_consecutive_auto_reply=0,
-        code_execution_config={
-            "work_dir": "workspace",
-            "use_docker": False,
-        },
-        is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE")
-    )
-    
-    return pm_agent, qa_agent, dev_agent, orchestrator, user_proxy, llm_config
-
-
-def display_agent_status_panel():
-    """显示 Agent 状态面板"""
-    st.subheader("🎭 Agent 实时状态")
-    
-    cols = st.columns(5)
-    agent_names = list(AGENT_CONFIG.keys())
-    
-    for i, (agent_name, config) in enumerate(AGENT_CONFIG.items()):
-        with cols[i]:
-            stats = st.session_state.agent_stats.get(agent_name, {})
-            msg_count = stats.get("messages", 0)
-            last_active = stats.get("last_active")
-            
-            is_active = st.session_state.active_agent == agent_name
-            
-            status_color = config["color"]
-            if is_active:
-                status_html = f'<span class="agent-status-indicator" style="background: {status_color}; animation: pulse 1s infinite;"></span>'
-            else:
-                status_html = f'<span style="display:inline-block;width:12px;height:12px;border-radius:50%;background:{status_color};opacity:0.3;"></span>'
-            
-            st.markdown(f"""
-            <div style="text-align:center;padding:1rem;border:2px {'solid' if is_active else 'dashed'} {status_color};border-radius:0.5rem;">
-                <div style="font-size:2rem;">{config['avatar']}</div>
-                <div style="font-weight:bold;color:{status_color};">{config['name']}</div>
-                <div style="font-size:0.8rem;color:#666;">消息：{msg_count}</div>
-                <div style="font-size:0.7rem;color:#999;">{status_html}{'工作中' if is_active else '等待中'}</div>
-            </div>
-            """, unsafe_allow_html=True)
-
-
-def display_workflow_diagram():
-    """显示工作流程图"""
-    st.subheader("🔄 工作流程图")
-    
-    # 使用 Mermaid 绘制流程图
-    mermaid_code = """
-    ```mermaid
-    graph LR
-        A[👤 用户需求] --> B[📋 PM Agent]
-        B --> C[📄 SRS 文档]
-        C --> D[✅ QA Agent]
-        D --> E[🧪 测试用例]
-        E --> F[💻 Dev Agent]
-        F --> G[💾 源代码]
-        G --> H[🔧 自动测试]
-        H -->|失败 | F
-        H -->|通过 | I[🎯 Orchestrator]
-        I --> J[✅ 最终报告]
-        
-        style B fill:#e3f2fd,stroke:#2196f3,stroke-width:3px
-        style D fill:#e8f5e9,stroke:#4caf50,stroke-width:3px
-        style F fill:#fff3e0,stroke:#ff9800,stroke-width:3px
-        style I fill:#f3e5f5,stroke:#9c27b0,stroke-width:3px
-    ```
-    """
-    st.markdown(mermaid_code)
-
-
-def display_message(agent_name: str, message: str, timestamp: str, index: int):
-    """显示单条消息（增强版）"""
-    config = AGENT_CONFIG.get(agent_name, {"name": agent_name, "avatar": "🤖", "color": "#999"})
-    
-    # 折叠长消息
-    if len(message) > 500:
-        with st.expander(f"{config['avatar']} {config['name']} - {timestamp[:16]}"):
-            st.markdown(message)
-    else:
-        with st.chat_message(name=agent_name.lower().replace("_", ""), avatar=config['avatar']):
-            st.markdown(f"**{config['avatar']} {config['name']}** *({timestamp[:16]})*")
-            st.markdown(message)
-
-
-def display_timeline():
-    """显示时间线视图"""
-    st.subheader("⏱️ 执行时间线")
-    
-    if not st.session_state.messages:
-        st.info("暂无执行记录")
-        return
-    
-    # 按时间分组显示关键事件
-    timeline_data = []
-    for msg in st.session_state.messages:
-        agent = msg.get("agent_name", "Unknown")
-        timestamp = msg.get("timestamp", "")[:19].replace('T', ' ')
-        message = msg.get("message", "")[:100]
-        
-        if agent in AGENT_CONFIG:
-            timeline_data.append({
-                "time": timestamp,
-                "agent": agent,
-                "message": message,
-                "icon": AGENT_CONFIG[agent]["avatar"]
-            })
-    
-    # 倒序显示（最新的在前）
-    for item in reversed(timeline_data[-10:]):  # 只显示最近 10 条
-        with st.container():
-            st.markdown(f"""
-            <div class="timeline-item">
-                <strong>{item['icon']} {item['time']}</strong><br>
-                <span style="color:#666;">{AGENT_CONFIG.get(item['agent'], {}).get('name', item['agent'])}</span><br>
-                {item['message']}...
-            </div>
-            """, unsafe_allow_html=True)
-
-
-def display_generated_files():
-    """显示生成的文件"""
-    st.subheader("📁 生成的文件")
-    
-    workspace_dir = Path("workspace")
-    if not workspace_dir.exists():
-        st.info("工作目录为空")
-        return
-    
-    files = list(workspace_dir.glob("*"))
-    
-    if not files:
-        st.info("暂无生成的文件")
-        return
-    
-    for file_path in files:
-        if file_path.is_file():
-            file_size = file_path.stat().st_size
-            file_type = file_path.suffix
-            
-            icon_map = {
-                ".py": "🐍",
-                ".md": "📝",
-                ".txt": "📄",
-                ".json": "📊"
-            }
-            
-            icon = icon_map.get(file_type, "📎")
-            
-            with st.container():
-                st.markdown(f"""
-                <div class="file-card">
-                    <div style="display:flex;justify-content:space-between;align-items:center;">
-                        <div>
-                            <span style="font-size:1.5rem;">{icon}</span>
-                            <strong>{file_path.name}</strong>
-                            <span style="color:#666;font-size:0.9rem;margin-left:1rem;">
-                                {file_size:,} bytes
-                            </span>
-                        </div>
-                    </div>
-                </div>
-                """, unsafe_allow_html=True)
-                
-                # 文件内容预览
-                if st.button(f"👁️ 预览 {file_path.name}", key=f"preview_{file_path.name}"):
-                    try:
-                        with open(file_path, 'r', encoding='utf-8') as f:
-                            content = f.read()
-                        st.code(content[:2000] + ("..." if len(content) > 2000 else ""))
-                    except Exception as e:
-                        st.error(f"读取失败：{e}")
-
-
-def display_chat_interface():
-    """显示聊天界面"""
-    st.subheader("💬 Agent 对话实录")
-    
-    if not st.session_state.messages:
-        st.info("👈 暂无对话，请在下方输入需求并启动工作流")
-    else:
-        # 使用容器显示消息
-        chat_container = st.container()
-        with chat_container:
-            for idx, msg in enumerate(st.session_state.messages):
-                display_message(
-                    agent_name=msg.get("agent_name", "Unknown"),
-                    message=msg.get("message", ""),
-                    timestamp=msg.get("timestamp", ""),
-                    index=idx
-                )
-
-
-def export_conversation(messages: List[Dict]) -> str:
-    """导出对话为 Markdown"""
-    md_content = "# AutoGen SDLC 对话历史\n\n"
-    md_content += f"**导出时间**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n"
-    md_content += "---\n\n"
-    
-    for msg in messages:
-        timestamp = msg.get("timestamp", "")[:19].replace('T', ' ')
-        agent = msg.get("agent_name", "Unknown")
-        content = msg.get("message", "")
-        
-        config = AGENT_CONFIG.get(agent, {"avatar": "🤖", "name": agent})
-        
-        md_content += f"### {config['avatar']} [{timestamp}] {config['name']}\n\n"
-        md_content += f"{content}\n\n"
-        md_content += "---\n\n"
-    
-    return md_content
-
-
-def main():
-    """主应用"""
-    init_session_state()
-    
-    # ===== 顶部标题区 =====
-    st.title("🤖 AutoGen SDLC 多智能体协作平台")
-    st.markdown("**基于 AutoGen + Qwen3.5-flash 的端到端软件交付系统 · 实时可视化 Agent 协作**")
-    
-    # ===== 侧边栏 - 配置区域 =====
-    with st.sidebar:
-        st.title("⚙️ 控制中心")
-        
-        # API 配置
-        st.subheader("🔑 模型配置")
-        api_key = st.text_input(
-            "API Key",
-            type="password",
-            value=os.getenv("DASHSCOPE_API_KEY", ""),
-            help="阿里云 DashScope API Key"
-        )
-        
-        base_url = st.text_input(
-            "Base URL",
-            value="https://dashscope.aliyuncs.com/compatible-mode/v1",
-            help="API Base URL"
-        )
-        
-        model = st.selectbox(
-            "模型选择",
-            options=["qwen3.5-flash", "qwen-max", "qwen-plus", "qwen-turbo"],
-            index=0,
-            help="选择使用的 Qwen 模型"
-        )
-        
-        # Agent 参数
-        st.subheader("🎛️ Agent 参数")
-        max_round = st.slider(
-            "最大对话轮数",
-            min_value=5,
-            max_value=50,
-            value=20,
-            step=1
-        )
-        
-        temperature = st.slider(
-            "温度参数",
-            min_value=0.0,
-            max_value=1.0,
-            value=0.7,
-            step=0.1
-        )
-        
-        st.divider()
-        
-        # 控制按钮
-        st.subheader("🎮 流程控制")
-        col1, col2 = st.columns(2)
-        
-        with col1:
-            start_btn = st.button("▶️ 启动", use_container_width=True, type="primary")
-        with col2:
-            stop_btn = st.button("⏸️ 暂停", use_container_width=True)
-        
-        st.divider()
-        
-        # 导出选项
-        st.subheader("💾 数据导出")
-        if st.button("📄 导出 JSON", use_container_width=True):
-            if st.session_state.messages:
-                json_str = json.dumps(st.session_state.messages, ensure_ascii=False, indent=2)
-                st.download_button(
-                    label="下载 JSON",
-                    data=json_str,
-                    file_name=f"conversation_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json",
-                    mime="application/json"
-                )
-        
-        if st.button("📝 导出 Markdown", use_container_width=True):
-            if st.session_state.messages:
-                md_content = export_conversation(st.session_state.messages)
-                st.download_button(
-                    label="下载 Markdown",
-                    data=md_content,
-                    file_name=f"conversation_{datetime.now().strftime('%Y%m%d_%H%M%S')}.md",
-                    mime="text/markdown"
-                )
-    
-    # ===== 主区域 - 三栏布局 =====
-    # 第一行：状态指标
-    status_col1, status_col2, status_col3, status_col4 = st.columns(4)
-    
-    with status_col1:
-        total_msgs = len(st.session_state.messages)
-        st.metric("💬 总消息数", total_msgs)
-    
-    with status_col2:
-        status = "🟢 运行中" if st.session_state.is_running else "🔴 已停止"
-        status_class = "running" if st.session_state.is_running else "stopped"
-        st.markdown(f"""
-        <div class="status-card status-{status_class}">
-            {status}
-        </div>
-        """, unsafe_allow_html=True)
-    
-    with status_col3:
-        result_status = "✅ 成功" if st.session_state.workflow_result and st.session_state.workflow_result.get("success") else "⏳ 未开始"
-        st.metric("📊 工作流状态", result_status)
-    
-    with status_col4:
-        files_count = len(list(Path("workspace").glob("*"))) if Path("workspace").exists() else 0
-        st.metric("📁 生成文件数", files_count)
-    
-    st.divider()
-    
-    # 第二行：左侧 - Agent 状态 + 流程图，右侧 - 时间线
-    left_col, right_col = st.columns([2, 1])
-    
-    with left_col:
-        display_agent_status_panel()
-        st.divider()
-        display_workflow_diagram()
-    
-    with right_col:
-        display_timeline()
-    
-    st.divider()
-    
-    # 第三行：聊天界面
-    display_chat_interface()
-    
-    # ===== 底部 - 用户需求输入 =====
-    st.divider()
-    
-    # 用户输入
-    user_input = st.chat_input("💡 请输入您的软件需求，例如：我需要一个电池健康状态预测 API...")
-    
-    if user_input:
-        # 添加用户消息
-        user_msg = {
-            "timestamp": datetime.now().isoformat(),
-            "agent_name": "User_Proxy",
-            "role": "user",
-            "message": user_input
-        }
-        st.session_state.messages.append(user_msg)
-        st.session_state.conversation_history.append(user_msg)
-        
-        # 更新统计
-        st.session_state.agent_stats["User_Proxy"]["messages"] += 1
-        st.session_state.agent_stats["User_Proxy"]["last_active"] = datetime.now().isoformat()
-        
-        # 刷新显示
-        st.rerun()
-    
-    # ===== 工作流执行逻辑 =====
-    if start_btn:
-        if not api_key:
-            st.error("请先设置 API Key！")
-            st.stop()
-        
-        if not AUTOGEN_AVAILABLE:
-            st.error("请先安装 AutoGen: pip install pyautogen")
-            st.stop()
-        
-        # 获取最后一条用户消息
-        user_messages = [m for m in st.session_state.messages if m.get("role") == "user"]
-        if not user_messages:
-            st.warning("请先输入需求！")
-            st.stop()
-        
-        latest_requirement = user_messages[-1]["message"]
-        
-        # 设置运行状态
-        st.session_state.is_running = True
-        st.session_state.current_step = 0
-        
-        # 创建进度占位符
-        progress_placeholder = st.empty()
-        
-        with progress_placeholder:
-            st.info("🚀 正在启动 SDLC 工作流，请稍候...")
-        
-        try:
-            # 创建 Agent
-            pm_agent, qa_agent, dev_agent, orchestrator, user_proxy, llm_config = create_agents(
-                api_key=api_key,
-                base_url=base_url,
-                model=model
-            )
-            
-            # 创建 GroupChat
-            groupchat = GroupChat(
-                agents=[pm_agent, qa_agent, dev_agent, orchestrator, user_proxy],
-                messages=[],
-                max_round=max_round,
-                speaker_selection_method="round_robin"
-            )
-            
-            manager = GroupChatManager(groupchat=groupchat, llm_config=llm_config)
-            
-            # 构建初始消息
-            initial_message = f"""
-请启动完整的 SDLC 流程：
-
-【用户需求】
-{latest_requirement}
-
-【工作流程】
-1. PM_Agent → 生成 SRS
-2. QA_Agent → 生成测试用例
-3. Dev_Agent → 编写代码
-4. User_Proxy → 执行测试
-5. Orchestrator → 汇总报告
-
-开始协作！
-"""
-            
-            # 记录第一条消息
-            first_msg = {
-                "timestamp": datetime.now().isoformat(),
-                "agent_name": "Orchestrator",
-                "role": "assistant",
-                "message": f"🎯 启动 SDLC 工作流，需求：{latest_requirement[:100]}..."
-            }
-            st.session_state.messages.append(first_msg)
-            
-            # 更新统计
-            st.session_state.agent_stats["Orchestrator"]["messages"] += 1
-            st.session_state.active_agent = "Orchestrator"
-            
-            # 执行对话
-            chat_result = user_proxy.initiate_chat(
-                manager,
-                message=initial_message,
-                max_turns=max_round
-            )
-            
-            # 记录所有对话
-            for msg in groupchat.messages:
-                chat_msg = {
-                    "timestamp": datetime.now().isoformat(),
-                    "agent_name": msg.get("name", "Unknown"),
-                    "role": msg.get("role", "assistant"),
-                    "message": msg.get("content", "")
-                }
-                
-                # 避免重复添加
-                if chat_msg not in st.session_state.messages:
-                    st.session_state.messages.append(chat_msg)
-                    
-                    # 更新统计
-                    agent_name = msg.get("name", "Unknown")
-                    if agent_name in st.session_state.agent_stats:
-                        st.session_state.agent_stats[agent_name]["messages"] += 1
-                        st.session_state.agent_stats[agent_name]["last_active"] = datetime.now().isoformat()
-            
-            # 扫描生成的文件
-            if Path("workspace").exists():
-                files = list(Path("workspace").glob("*"))
-                st.session_state.generated_files = [str(f) for f in files if f.is_file()]
-            
-            # 更新状态
-            st.session_state.workflow_result = {
-                "success": True,
-                "summary": chat_result.summary if hasattr(chat_result, 'summary') else "完成"
-            }
-            st.session_state.current_step = 5
-            st.session_state.is_running = False
-            st.session_state.active_agent = None
-            
-            progress_placeholder.success("✅ SDLC 工作流完成！")
-            
-            # 刷新显示
-            st.rerun()
-            
-        except Exception as e:
-            st.session_state.is_running = False
-            st.session_state.active_agent = None
-            st.error(f"❌ 错误：{str(e)}")
-            st.session_state.workflow_result = {"success": False, "error": str(e)}
-    
-    if stop_btn:
-        st.session_state.is_running = False
-        st.session_state.active_agent = None
-        st.info("⏸️ 工作流已暂停")
-
-
-if __name__ == "__main__":
-    main()
diff --git a/frontend/streamlit_app_v3.py b/frontend/streamlit_app_v3.py
deleted file mode 100644
index a90c22a..0000000
--- a/frontend/streamlit_app_v3.py
+++ /dev/null
@@ -1,756 +0,0 @@
-# -*- coding: utf-8 -*-
-"""
-Streamlit 前端 v3 - Agent 对话流可视化版本
-核心特性：
-1. 清晰展示每个 Agent 当前在做什么（任务标签）
-2. Agent 之间的对话流（类似聊天室）
-3. 实时活动指示器（高亮当前发言的 Agent）
-4. 对话历史完整记录
-"""
-import streamlit as st
-import os
-import sys
-from pathlib import Path
-from datetime import datetime
-import time
-from typing import Dict, Any, List
-import json
-
-# 添加项目根目录到路径
-sys.path.insert(0, str(Path(__file__).parent.parent))
-
-try:
-    from autogen import AssistantAgent, UserProxyAgent, GroupChat, GroupChatManager
-    AUTOGEN_AVAILABLE = True
-except ImportError:
-    AUTOGEN_AVAILABLE = False
-
-from config.llm_config import (
-    get_llm_config, 
-    PM_PROMPT, 
-    QA_PROMPT, 
-    DEV_PROMPT, 
-    ORCH_PROMPT
-)
-
-
-# 页面配置
-st.set_page_config(
-    page_title="AutoGen SDLC - Agent 对话流",
-    page_icon="💬",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
-
-# 自定义 CSS 样式 - 突出对话流
-st.markdown("""
-<style>
-/* 主对话区域 */
-.chat-flow-container {
-    background: #f0f2f6;
-    padding: 20px;
-    border-radius: 10px;
-    margin-bottom: 20px;
-}
-
-/* Agent 对话气泡 */
-.agent-chat-bubble {
-    padding: 15px 20px;
-    margin: 10px 0;
-    border-radius: 15px;
-    max-width: 85%;
-    position: relative;
-    animation: bubble-in 0.3s ease;
-    box-shadow: 0 2px 8px rgba(0,0,0,0.1);
-}
-
-@keyframes bubble-in {
-    from {
-        opacity: 0;
-        transform: translateY(10px);
-    }
-    to {
-        opacity: 1;
-        transform: translateY(0);
-    }
-}
-
-/* 不同 Agent 的气泡样式 */
-.pm-bubble { 
-    background: linear-gradient(135deg, #e3f2fd 0%, #bbdefb 100%); 
-    border: 2px solid #2196f3;
-    margin-left: 0;
-}
-
-.qa-bubble { 
-    background: linear-gradient(135deg, #e8f5e9 0%, #c8e6c9 100%); 
-    border: 2px solid #4caf50;
-    margin-left: 0;
-}
-
-.dev-bubble { 
-    background: linear-gradient(135deg, #fff3e0 0%, #ffe0b2 100%); 
-    border: 2px solid #ff9800;
-    margin-left: 0;
-}
-
-.orchestrator-bubble { 
-    background: linear-gradient(135deg, #f3e5f5 0%, #e1bee7 100%); 
-    border: 2px solid #9c27b0;
-    margin-left: 0;
-}
-
-.user-bubble { 
-    background: linear-gradient(135deg, #efebe9 0%, #d7ccc8 100%); 
-    border: 2px solid #795548;
-    margin-left: auto;
-}
-
-/* Agent 头像和名称 */
-.agent-chat-header {
-    display: flex;
-    align-items: center;
-    margin-bottom: 8px;
-    font-weight: bold;
-}
-
-.agent-chat-avatar {
-    font-size: 1.5rem;
-    margin-right: 8px;
-}
-
-.agent-chat-name {
-    font-size: 1rem;
-    color: #333;
-}
-
-.agent-chat-time {
-    margin-left: auto;
-    font-size: 0.75rem;
-    color: #666;
-}
-
-/* 任务标签 */
-.task-badge {
-    display: inline-block;
-    padding: 3px 10px;
-    border-radius: 12px;
-    font-size: 0.75rem;
-    font-weight: bold;
-    margin-left: 8px;
-    color: white;
-}
-
-.pm-task { background: #2196f3; }
-.qa-task { background: #4caf50; }
-.dev-task { background: #ff9800; }
-.orchestrator-task { background: #9c27b0; }
-.user-task { background: #795548; }
-
-/* Agent 状态卡片 */
-.agent-status-card {
-    padding: 15px;
-    border-radius: 10px;
-    text-align: center;
-    border: 3px solid #e0e0e0;
-    transition: all 0.3s ease;
-    background: white;
-}
-
-.agent-status-card.active {
-    border-color: #4caf50;
-    background: linear-gradient(135deg, #e8f5e9 0%, #c8e6c9 100%);
-    animation: agent-pulse 1.5s infinite;
-}
-
-@keyframes agent-pulse {
-    0%, 100% { transform: scale(1); }
-    50% { transform: scale(1.02); }
-}
-
-.agent-status-avatar {
-    font-size: 2.5rem;
-    margin-bottom: 5px;
-}
-
-.agent-status-name {
-    font-weight: bold;
-    font-size: 0.9rem;
-    margin-bottom: 5px;
-}
-
-.agent-status-task {
-    font-size: 0.75rem;
-    color: #666;
-    min-height: 20px;
-}
-
-.agent-status-indicator {
-    display: inline-block;
-    width: 8px;
-    height: 8px;
-    border-radius: 50%;
-    margin-right: 5px;
-}
-
-.status-active {
-    background: #4caf50;
-    animation: dot-pulse 1s infinite;
-}
-
-.status-waiting {
-    background: #ffc107;
-}
-
-.status-inactive {
-    background: #e0e0e0;
-}
-
-@keyframes dot-pulse {
-    0%, 100% { opacity: 1; }
-    50% { opacity: 0.3; }
-}
-
-/* 对话流指示器 */
-.chat-flow-indicator {
-    display: flex;
-    align-items: center;
-    margin: 10px 0;
-    padding: 10px;
-    background: white;
-    border-radius: 8px;
-}
-
-.flow-arrow {
-    font-size: 1.5rem;
-    color: #2196f3;
-    margin: 0 10px;
-}
-
-/* 当前活动提示 */
-.active-agent-banner {
-    background: linear-gradient(135deg, #4caf50, #8bc34a);
-    color: white;
-    padding: 10px 20px;
-    border-radius: 8px;
-    text-align: center;
-    font-weight: bold;
-    margin-bottom: 20px;
-    animation: banner-pulse 2s infinite;
-}
-
-@keyframes banner-pulse {
-    0%, 100% { opacity: 1; }
-    50% { opacity: 0.8; }
-}
-</style>
-""", unsafe_allow_html=True)
-
-
-# Agent 配置
-AGENT_CONFIG = {
-    "PM_Agent": {
-        "name": "产品经理",
-        "avatar": "📋",
-        "color": "#2196f3",
-        "bubble_class": "pm-bubble",
-        "task_class": "pm-task",
-        "default_task": "待命"
-    },
-    "QA_Agent": {
-        "name": "测试工程师",
-        "avatar": "✅",
-        "color": "#4caf50",
-        "bubble_class": "qa-bubble",
-        "task_class": "qa-task",
-        "default_task": "待命"
-    },
-    "Dev_Agent": {
-        "name": "开发工程师",
-        "avatar": "💻",
-        "color": "#ff9800",
-        "bubble_class": "dev-bubble",
-        "task_class": "dev-task",
-        "default_task": "待命"
-    },
-    "Orchestrator": {
-        "name": "协调器",
-        "avatar": "🎯",
-        "color": "#9c27b0",
-        "bubble_class": "orchestrator-bubble",
-        "task_class": "orchestrator-task",
-        "default_task": "待命"
-    },
-    "User_Proxy": {
-        "name": "用户代理",
-        "avatar": "👤",
-        "color": "#795548",
-        "bubble_class": "user-bubble",
-        "task_class": "user-task",
-        "default_task": "待命"
-    }
-}
-
-
-def init_session_state():
-    """初始化 session state"""
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
-    if "is_running" not in st.session_state:
-        st.session_state.is_running = False
-    if "current_agent" not in st.session_state:
-        st.session_state.current_agent = None
-    if "agent_tasks" not in st.session_state:
-        st.session_state.agent_tasks = {
-            "PM_Agent": "待命",
-            "QA_Agent": "待命",
-            "Dev_Agent": "待命",
-            "Orchestrator": "待命",
-            "User_Proxy": "待命"
-        }
-    if "agent_stats" not in st.session_state:
-        st.session_state.agent_stats = {agent: 0 for agent in AGENT_CONFIG}
-
-
-def display_agent_status_row():
-    """显示 Agent 状态行 - 突出当前活动的 Agent"""
-    st.subheader("🎭 Agent 实时状态")
-    
-    cols = st.columns(5)
-    
-    for i, (agent_key, config) in enumerate(AGENT_CONFIG.items()):
-        with cols[i]:
-            is_active = st.session_state.current_agent == agent_key
-            current_task = st.session_state.agent_tasks.get(agent_key, "待命")
-            msg_count = st.session_state.agent_stats.get(agent_key, 0)
-            
-            status_class = "active" if is_active else ""
-            indicator_class = "status-active" if is_active else "status-inactive"
-            
-            st.markdown(f"""
-            <div class="agent-status-card {status_class}">
-                <div class="agent-status-avatar">{config['avatar']}</div>
-                <div class="agent-status-name">
-                    <span class="agent-status-indicator {indicator_class}"></span>
-                    {config['name']}
-                </div>
-                <div class="agent-status-task">
-                    📝 {current_task}
-                </div>
-                <div style="font-size:0.7rem;color:#999;margin-top:5px;">
-                    💬 {msg_count} 条消息
-                </div>
-            </div>
-            """, unsafe_allow_html=True)
-
-
-def display_active_agent_banner():
-    """显示当前活动 Agent 的横幅"""
-    if st.session_state.current_agent:
-        config = AGENT_CONFIG.get(st.session_state.current_agent, {})
-        st.markdown(f"""
-        <div class="active-agent-banner">
-            {config.get('avatar', '🤖')} 当前发言：{config.get('name', 'Unknown')} - {st.session_state.agent_tasks.get(st.session_state.current_agent, '工作中...')}
-        </div>
-        """, unsafe_allow_html=True)
-
-
-def display_chat_flow():
-    """显示 Agent 对话流 - 核心功能"""
-    st.subheader("💬 Agent 对话流")
-    
-    if not st.session_state.messages:
-        st.info("👈 暂无对话，请启动工作流")
-        return
-    
-    # 使用容器显示对话流
-    chat_container = st.container()
-    
-    for idx, msg in enumerate(st.session_state.messages):
-        agent_key = msg.get("agent_key", "Unknown")
-        config = AGENT_CONFIG.get(agent_key, {"name": "未知", "avatar": "🤖", "bubble_class": ""})
-        task_class = AGENT_CONFIG.get(agent_key, {}).get("task_class", "")
-        
-        timestamp = msg.get("timestamp", "")
-        if timestamp:
-            time_str = datetime.fromisoformat(timestamp).strftime("%H:%M:%S")
-        else:
-            time_str = datetime.now().strftime("%H:%M:%S")
-        
-        content = msg.get("content", "")
-        task = msg.get("task", "工作中")
-        
-        # 显示对话气泡
-        st.markdown(f"""
-        <div class="agent-chat-bubble {config['bubble_class']}">
-            <div class="agent-chat-header">
-                <span class="agent-chat-avatar">{config['avatar']}</span>
-                <span class="agent-chat-name">{config['name']}</span>
-                <span class="task-badge {task_class}">{task}</span>
-                <span class="agent-chat-time">{time_str}</span>
-            </div>
-            <div style="color:#333;line-height:1.6;">{content}</div>
-        </div>
-        """, unsafe_allow_html=True)
-        
-        # 显示对话流指示器（下一条消息的箭头）
-        if idx < len(st.session_state.messages) - 1:
-            next_msg = st.session_state.messages[idx + 1]
-            next_agent = next_msg.get("agent_key", "")
-            next_config = AGENT_CONFIG.get(next_agent, {})
-            
-            if next_agent != agent_key:
-                st.markdown(f"""
-                <div class="chat-flow-indicator">
-                    <div style="flex:1;"></div>
-                    <div class="flow-arrow">⬇️</div>
-                    <div style="flex:1;text-align:center;color:#666;font-size:0.8rem;">
-                        传递给 {next_config.get('name', 'Unknown')}
-                    </div>
-                </div>
-                """, unsafe_allow_html=True)
-
-
-def save_generated_files():
-    """从对话中提取并保存生成的文件到 workspace 目录"""
-    workspace_dir = Path("workspace")
-    workspace_dir.mkdir(parents=True, exist_ok=True)
-    
-    files_saved = []
-    
-    # 遍历所有消息，提取文件内容
-    for msg in st.session_state.messages:
-        content = msg.get("content", "")
-        agent_key = msg.get("agent_key", "")
-        
-        # PM Agent 生成 SRS.md
-        if agent_key == "PM_Agent" and ("SRS" in content or "软件需求规格" in content):
-            srs_file = workspace_dir / "SRS.md"
-            # 提取 SRS 内容（查找包含 FR- 或 NFR- 的段落）
-            srs_content = content
-            if "功能性需求" in content:
-                srs_content = content[content.find("功能性需求"):]
-            with open(srs_file, 'w', encoding='utf-8') as f:
-                f.write(f"# 软件需求规格说明书 (SRS)\n\n")
-                f.write(f"**生成时间**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n")
-                f.write(srs_content)
-            files_saved.append(str(srs_file))
-        
-        # QA Agent 生成测试文件
-        if agent_key == "QA_Agent" and ("test_" in content or "def test_" in content):
-            test_file = workspace_dir / "test_battery_health.py"
-            # 提取 Python 代码
-            if "```python" in content:
-                code = content.split("```python")[1].split("```")[0]
-            else:
-                code = content
-            with open(test_file, 'w', encoding='utf-8') as f:
-                f.write(f'"""\n电池健康状态测试用例\n生成时间：{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}\n"""\n\n')
-                f.write(code)
-            files_saved.append(str(test_file))
-        
-        # Dev Agent 生成源代码
-        if agent_key == "Dev_Agent" and ("def " in content or "class " in content):
-            src_file = workspace_dir / "src_battery_health.py"
-            # 提取 Python 代码
-            if "```python" in content:
-                code = content.split("```python")[1].split("```")[0]
-            else:
-                code = content
-            with open(src_file, 'w', encoding='utf-8') as f:
-                f.write(f'"""\n电池健康状态计算模块\n生成时间：{datetime.now().strftime("%Y-%m-%d %H:%M:%S")}\n"""\n\n')
-                f.write(code)
-            files_saved.append(str(src_file))
-        
-        # Orchestrator 生成最终报告
-        if agent_key == "Orchestrator" and ("完成" in content and "SDLC" in content):
-            report_file = workspace_dir / "FINAL_REPORT.md"
-            with open(report_file, 'w', encoding='utf-8') as f:
-                f.write(f"# SDLC 项目最终报告\n\n")
-                f.write(f"**生成时间**: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}\n\n")
-                f.write("## 项目概述\n\n")
-                f.write("基于 AutoGen 多智能体系统完成的软件交付项目。\n\n")
-                f.write("## 生成文件列表\n\n")
-                for i, saved_file in enumerate(files_saved, 1):
-                    f.write(f"{i}. {saved_file}\n")
-                f.write(f"\n## 项目总结\n\n{content}\n")
-            files_saved.append(str(report_file))
-    
-    return files_saved
-
-
-def create_agents(api_key: str, base_url: str, model: str):
-    """创建所有 Agent"""
-    llm_config = get_llm_config(model=model, api_key=api_key, base_url=base_url)
-    
-    pm_agent = AssistantAgent(
-        name="PM_Agent",
-        system_message=PM_PROMPT,
-        llm_config=llm_config,
-        description="资深软件产品经理",
-        human_input_mode="NEVER"
-    )
-    
-    qa_agent = AssistantAgent(
-        name="QA_Agent",
-        system_message=QA_PROMPT,
-        llm_config=llm_config,
-        description="资深测试工程师",
-        human_input_mode="NEVER"
-    )
-    
-    dev_agent = AssistantAgent(
-        name="Dev_Agent",
-        system_message=DEV_PROMPT,
-        llm_config=llm_config,
-        description="资深软件工程师",
-        human_input_mode="NEVER"
-    )
-    
-    orchestrator = AssistantAgent(
-        name="Orchestrator",
-        system_message=ORCH_PROMPT,
-        llm_config=llm_config,
-        description="多智能体协调器",
-        human_input_mode="NEVER"
-    )
-    
-    user_proxy = UserProxyAgent(
-        name="User_Proxy",
-        human_input_mode="NEVER",
-        max_consecutive_auto_reply=0,
-        code_execution_config={
-            "work_dir": "workspace",
-            "use_docker": False,
-        },
-        is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE")
-    )
-    
-    return pm_agent, qa_agent, dev_agent, orchestrator, user_proxy, llm_config
-
-
-def add_message(agent_key: str, content: str, task: str = "工作中"):
-    """添加消息到对话流"""
-    msg = {
-        "agent_key": agent_key,
-        "content": content,
-        "timestamp": datetime.now().isoformat(),
-        "task": task
-    }
-    st.session_state.messages.append(msg)
-    
-    # 更新统计
-    st.session_state.agent_stats[agent_key] = st.session_state.agent_stats.get(agent_key, 0) + 1
-    
-    # 更新当前 Agent
-    st.session_state.current_agent = agent_key
-    
-    # 更新任务
-    st.session_state.agent_tasks[agent_key] = task
-
-
-def main():
-    """主应用"""
-    init_session_state()
-    
-    # 标题
-    st.title("💬 AutoGen SDLC - Agent 对话流可视化")
-    st.markdown("**清晰展示每个 Agent 在做什么 · 实时追踪 Agent 之间的对话交互**")
-    
-    # 侧边栏配置
-    with st.sidebar:
-        st.title("⚙️ 控制中心")
-        
-        api_key = st.text_input("API Key", type="password", value=os.getenv("DASHSCOPE_API_KEY", ""))
-        base_url = st.text_input("Base URL", value="https://dashscope.aliyuncs.com/compatible-mode/v1")
-        model = st.selectbox("模型选择", ["qwen3.5-flash", "qwen-max", "qwen-plus", "qwen-turbo"], index=0)
-        
-        max_round = st.slider("最大对话轮数", 5, 50, 20)
-        
-        st.divider()
-        
-        col1, col2 = st.columns(2)
-        with col1:
-            start_btn = st.button("▶️ 启动对话流", type="primary", use_container_width=True)
-        with col2:
-            stop_btn = st.button("⏸️ 暂停", use_container_width=True)
-        
-        st.divider()
-        
-        if st.button("🗑️ 清空对话", use_container_width=True):
-            st.session_state.messages = []
-            st.session_state.current_agent = None
-            st.session_state.agent_tasks = {k: "待命" for k in AGENT_CONFIG}
-            st.session_state.agent_stats = {k: 0 for k in AGENT_CONFIG}
-            st.rerun()
-        
-        if st.button("📥 导出对话", use_container_width=True):
-            if st.session_state.messages:
-                json_str = json.dumps(st.session_state.messages, ensure_ascii=False, indent=2)
-                st.download_button(
-                    label="下载 JSON",
-                    data=json_str,
-                    file_name=f"agent_chat_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json",
-                    mime="application/json"
-                )
-        
-        st.divider()
-        
-        # 显示生成的文件
-        st.subheader("📁 生成的文件")
-        workspace_dir = Path("workspace")
-        if workspace_dir.exists():
-            files = list(workspace_dir.glob("*"))
-            if files:
-                for file in files:
-                    if file.is_file():
-                        with st.expander(f"📄 {file.name}"):
-                            try:
-                                content = file.read_text(encoding='utf-8')
-                                st.code(content[:500] + ("..." if len(content) > 500 else ""))
-                                st.download_button(
-                                    label="⬇️ 下载",
-                                    data=content,
-                                    file_name=file.name,
-                                    mime="text/plain",
-                                    key=f"download_{file.name}"
-                                )
-                            except Exception as e:
-                                st.error(f"读取失败：{e}")
-            else:
-                st.info("工作目录为空，请先运行工作流")
-        else:
-            st.info("工作目录不存在")
-    
-    # 主界面
-    display_agent_status_row()
-    st.divider()
-    
-    display_active_agent_banner()
-    
-    display_chat_flow()
-    
-    # 用户输入
-    st.divider()
-    user_input = st.chat_input("💡 输入需求，或点击启动按钮开始...")
-    
-    if user_input:
-        add_message("User_Proxy", user_input, "提出需求")
-        st.rerun()
-    
-    # 启动工作流
-    if start_btn:
-        if not api_key:
-            st.error("请先设置 API Key")
-            st.stop()
-        
-        if not AUTOGEN_AVAILABLE:
-            st.error("请先安装 AutoGen: pip install pyautogen")
-            st.stop()
-        
-        # 获取需求
-        user_msgs = [m for m in st.session_state.messages if m.get("agent_key") == "User_Proxy"]
-        if not user_msgs:
-            add_message("User_Proxy", "请开发一个电池健康状态预测 API", "提出需求")
-        
-        latest_requirement = user_msgs[-1]["content"] if user_msgs else "请开发一个电池健康状态预测 API"
-        
-        st.session_state.is_running = True
-        
-        # 进度提示
-        progress_placeholder = st.empty()
-        progress_placeholder.info("🚀 启动 SDLC 工作流，Agent 开始协作...")
-        
-        try:
-            # 创建 Agent
-            pm_agent, qa_agent, dev_agent, orchestrator, user_proxy, llm_config = create_agents(
-                api_key=api_key,
-                base_url=base_url,
-                model=model
-            )
-            
-            # 添加 Orchestrator 启动消息
-            add_message("Orchestrator", f"🚀 启动 SDLC 工作流！用户需求：{latest_requirement[:100]}...", "启动流程")
-            
-            # 创建 GroupChat
-            groupchat = GroupChat(
-                agents=[pm_agent, qa_agent, dev_agent, orchestrator, user_proxy],
-                messages=[],
-                max_round=max_round,
-                speaker_selection_method="round_robin"
-            )
-            
-            manager = GroupChatManager(groupchat=groupchat, llm_config=llm_config)
-            
-            # 初始消息
-            initial_message = f"""
-请启动完整的 SDLC 流程：
-
-【用户需求】
-{latest_requirement}
-
-【工作流程】
-1. PM_Agent → 生成 SRS 文档
-2. QA_Agent → 生成测试用例  
-3. Dev_Agent → 编写代码
-4. User_Proxy → 执行测试
-5. Orchestrator → 汇总报告
-
-开始协作！每个步骤完成后请明确说明。
-"""
-            
-            # 执行对话
-            with st.spinner("💬 Agent 们正在协作中，请稍候..."):
-                chat_result = user_proxy.initiate_chat(
-                    manager,
-                    message=initial_message,
-                    max_turns=max_round
-                )
-            
-            # 记录所有对话
-            for msg in groupchat.messages:
-                agent_name = msg.get("name", "Unknown")
-                content = msg.get("content", "")
-                
-                # 推断任务
-                task_map = {
-                    "PM_Agent": "需求分析",
-                    "QA_Agent": "测试设计",
-                    "Dev_Agent": "代码实现",
-                    "Orchestrator": "流程协调",
-                    "User_Proxy": "测试执行"
-                }
-                task = task_map.get(agent_name, "工作中")
-                
-                add_message(agent_name, content, task)
-            
-            # 完成
-            add_message("Orchestrator", "✅ SDLC 流程完成！所有任务已完成。", "总结完成")
-            
-            # 保存生成的文件
-            progress_placeholder.info("💾 正在保存生成的文件...")
-            saved_files = save_generated_files()
-            
-            if saved_files:
-                progress_placeholder.success(f"✅ SDLC 工作流完成！已保存 {len(saved_files)} 个文件到 workspace/ 目录")
-            else:
-                progress_placeholder.success("✅ SDLC 工作流完成！查看上方的对话流了解详情。")
-            
-            st.session_state.is_running = False
-            
-            st.rerun()
-            
-        except Exception as e:
-            st.session_state.is_running = False
-            st.session_state.current_agent = None
-            progress_placeholder.error(f"❌ 错误：{str(e)}")
-            st.error("请检查 API Key 和网络连接")
-    
-    if stop_btn:
-        st.session_state.is_running = False
-        st.session_state.current_agent = None
-        st.info("⏸️ 工作流已暂停")
-
-
-if __name__ == "__main__":
-    main()