From c8aef9319b97916486260cda5166558941acd6c1 Mon Sep 17 00:00:00 2001 From: ZhuJW <1421267742@qq.com> Date: Thu, 12 Mar 2026 15:04:03 +0800 Subject: [PATCH] fix --- config/__init__.py | 10 + frontend/app.py | 280 +++++++++++++ frontend/streamlit_app.py | 442 -------------------- frontend/streamlit_app_v2.py | 725 --------------------------------- frontend/streamlit_app_v3.py | 756 ----------------------------------- 5 files changed, 290 insertions(+), 1923 deletions(-) create mode 100644 config/__init__.py create mode 100644 frontend/app.py delete mode 100644 frontend/streamlit_app.py delete mode 100644 frontend/streamlit_app_v2.py delete mode 100644 frontend/streamlit_app_v3.py 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""" +
+
{info["avatar"]}
+
{info["name"]}
+
+ {"🟢 发言中" if is_active else "⚪ 等待中"} +
+
+ 💬 {count} 条消息 +
+
+ """, 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(""" - -""", 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"
{message}
", - 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(""" - -""", 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'' - else: - status_html = f'' - - st.markdown(f""" -
-
{config['avatar']}
-
{config['name']}
-
消息：{msg_count}
-
{status_html}{'工作中' if is_active else '等待中'}
-
- """, 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""" -
- {item['icon']} {item['time']}
- {AGENT_CONFIG.get(item['agent'], {}).get('name', item['agent'])}
- {item['message']}... -
- """, 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""" -
-
-
- {icon} - {file_path.name} - - {file_size:,} bytes - -
-
-
- """, 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""" -
- {status} -
- """, 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(""" - -""", 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""" -
-
{config['avatar']}
-
- - {config['name']} -
-
- 📝 {current_task} -
-
- 💬 {msg_count} 条消息 -
-
- """, 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""" -
- {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...')} -
- """, 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""" -
-
- {config['avatar']} - {config['name']} - {task} - {time_str} -
-
{content}
-
- """, 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""" -
-
-
⬇️
-
- 传递给 {next_config.get('name', 'Unknown')} -
-
- """, 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()