# -*- 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 extract_code(content): """从 Markdown 代码块中提取纯代码""" # 检查是否有 ```python 标记 if "```python" in content: # 提取 ```python 和 ``` 之间的内容 parts = content.split("```python") if len(parts) > 1: code = parts[1].split("```")[0].strip() return code elif "```" in content: # 通用的 ``` 标记 parts = content.split("```") if len(parts) > 1: code = parts[1].strip() return code # 没有标记，返回原内容 return content 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") f.write(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 or "def test_" in content): file = workspace / "test_sample.py" # 提取纯代码 code = extract_code(content) 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") f.write(code) 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" # 提取纯代码 code = extract_code(content) 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") f.write(code) 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""" # 保存现有消息（包括用户需求） existing_messages = list(st.session_state.messages) # 只清空计数，不清空消息 st.session_state.running = True 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 - 在清空前已经保存了 user_msgs = [m for m in existing_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" # 显示需求 st.info(f"📋 用户需求：{requirement}") # 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()