550 lines
21 KiB
Python
550 lines
21 KiB
Python
"""
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Multi-Agent Decision Workshop - 主应用
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多 Agent 决策工作坊：通过多角色辩论帮助用户做出更好的决策
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"""
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import streamlit as st
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import os
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from dotenv import load_dotenv
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# 加载环境变量
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load_dotenv()
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from agents import get_all_agents, get_recommended_agents, AGENT_PROFILES
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from orchestrator import DebateManager, DebateConfig
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from orchestrator.research_manager import ResearchManager, ResearchConfig
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from report import ReportGenerator
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from utils import LLMClient
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import config
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# ==================== 页面配置 ====================
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st.set_page_config(
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page_title="🎭 多 Agent 决策工作坊",
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page_icon="🎭",
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layout="wide",
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initial_sidebar_state="expanded"
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)
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# ==================== 样式 ====================
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st.markdown("""
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<style>
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.agent-card {
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padding: 1rem;
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border-radius: 0.5rem;
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margin-bottom: 0.5rem;
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border-left: 4px solid #4A90A4;
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background-color: #f8f9fa;
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}
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.speech-bubble {
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background-color: #f0f2f6;
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padding: 1rem;
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border-radius: 0.5rem;
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margin: 0.5rem 0;
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}
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.round-header {
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background: linear-gradient(90deg, #667eea 0%, #764ba2 100%);
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color: white;
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padding: 0.5rem 1rem;
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border-radius: 0.5rem;
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margin: 1rem 0;
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}
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.custom-agent-form {
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background-color: #e8f4f8;
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padding: 1rem;
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border-radius: 0.5rem;
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margin: 0.5rem 0;
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}
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.research-step {
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border-left: 3px solid #FF4B4B;
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padding-left: 10px;
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margin-bottom: 10px;
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}
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</style>
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""", unsafe_allow_html=True)
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# ==================== 常量定义 ====================
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# 从环境变量读取 API Key（隐藏在 .env 文件中）
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DEFAULT_API_KEY = os.getenv("AIHUBMIX_API_KEY", "")
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# 支持的模型列表
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from config import AVAILABLE_MODELS, RESEARCH_MODEL_ROLES
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# 决策类型
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DECISION_TYPES = {
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"product": "产品方案",
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"business": "商业决策",
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"tech": "技术选型",
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"personal": "个人规划"
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}
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# ==================== 初始化 Session State ====================
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if "mode" not in st.session_state:
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st.session_state.mode = "Deep Research"
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# Debate State
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if "debate_started" not in st.session_state:
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st.session_state.debate_started = False
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if "debate_finished" not in st.session_state:
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st.session_state.debate_finished = False
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if "speeches" not in st.session_state:
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st.session_state.speeches = []
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if "report" not in st.session_state:
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st.session_state.report = ""
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if "custom_agents" not in st.session_state:
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st.session_state.custom_agents = {}
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# Research State
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if "research_plan" not in st.session_state:
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st.session_state.research_plan = ""
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if "research_started" not in st.session_state:
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st.session_state.research_started = False
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if "research_output" not in st.session_state:
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st.session_state.research_output = "" # Final report
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if "research_steps_output" not in st.session_state:
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st.session_state.research_steps_output = [] # List of step results
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# ==================== 侧边栏：配置 ====================
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with st.sidebar:
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st.header("⚙️ 设置")
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# 全局 API Key 设置
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with st.expander("🔑 API Key 设置", expanded=True):
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use_custom_key = st.checkbox("使用自定义 API Key")
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if use_custom_key:
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api_key = st.text_input(
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"API Key",
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type="password",
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help="留空则使用环境变量中的 Key"
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)
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else:
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api_key = DEFAULT_API_KEY
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st.divider()
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# 模式选择
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mode = st.radio(
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"📊 选择模式",
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["Deep Research", "Debate Workshop"],
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index=0 if st.session_state.mode == "Deep Research" else 1
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)
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st.session_state.mode = mode
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st.divider()
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if mode == "Deep Research":
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st.subheader("🧪 研究模型配置")
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# 3 个角色的模型配置
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roles_config = {}
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for role_key, role_info in config.RESEARCH_MODEL_ROLES.items():
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roles_config[role_key] = st.selectbox(
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f"{role_info['name']} ({role_info['description']})",
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options=list(AVAILABLE_MODELS.keys()),
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index=list(AVAILABLE_MODELS.keys()).index(role_info['default_model']) if role_info['default_model'] in AVAILABLE_MODELS else 0,
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key=f"model_{role_key}"
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)
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else: # Debate Workshop
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# 模型选择
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model = st.selectbox(
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"🤖 选择通用模型",
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options=list(AVAILABLE_MODELS.keys()),
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format_func=lambda x: AVAILABLE_MODELS[x],
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index=0,
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help="选择用于辩论的 AI 模型"
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)
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# 辩论配置
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max_rounds = st.slider(
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"🔄 辩论轮数",
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min_value=1,
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max_value=4,
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value=2,
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help="每轮所有 Agent 都会发言一次"
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)
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st.divider()
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# ==================== 自定义角色 (Debate Only) ====================
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st.subheader("✨ 自定义角色")
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with st.expander("➕ 添加新角色", expanded=False):
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new_agent_name = st.text_input("角色名称", placeholder="如：法务顾问", key="new_agent_name")
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new_agent_emoji = st.text_input("角色 Emoji", value="🎯", max_chars=2, key="new_agent_emoji")
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new_agent_perspective = st.text_input("视角定位", placeholder="如：法律合规视角", key="new_agent_perspective")
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new_agent_focus = st.text_input("关注点（逗号分隔）", placeholder="如：合规风险, 法律条款", key="new_agent_focus")
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new_agent_prompt = st.text_area("角色设定 Prompt", placeholder="描述这个角色的思考方式...", height=100, key="new_agent_prompt")
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if st.button("✅ 添加角色", use_container_width=True):
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if new_agent_name and new_agent_prompt:
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agent_id = f"custom_{len(st.session_state.custom_agents)}"
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st.session_state.custom_agents[agent_id] = {
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"name": new_agent_name,
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"emoji": new_agent_emoji,
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"perspective": new_agent_perspective or "自定义视角",
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"focus_areas": [f.strip() for f in new_agent_focus.split(",") if f.strip()],
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"system_prompt": new_agent_prompt
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}
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st.success(f"已添加角色: {new_agent_emoji} {new_agent_name}")
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st.rerun()
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else:
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st.warning("请至少填写角色名称和 Prompt")
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# 显示已添加的自定义角色
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if st.session_state.custom_agents:
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st.markdown("**已添加的自定义角色：**")
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for agent_id, agent_info in list(st.session_state.custom_agents.items()):
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col1, col2 = st.columns([3, 1])
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with col1:
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st.markdown(f"{agent_info['emoji']} {agent_info['name']}")
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with col2:
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if st.button("🗑️", key=f"del_{agent_id}"):
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del st.session_state.custom_agents[agent_id]
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st.rerun()
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# ==================== 主界面逻辑 ====================
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if mode == "Deep Research":
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st.title("🧪 Multi-Model Council V2")
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st.markdown("*多模型智囊团：分析 (Expert A) -> 批判 (Expert B) -> 改进 (Expert A) -> 决策 (Expert C)*")
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# Input
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research_topic = st.text_area("研究/决策主题", placeholder="请输入你想深入研究或决策的主题...", height=100)
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research_context = st.text_area("补充背景 (可选)", placeholder="任何额外的背景信息...", height=80)
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start_research_btn = st.button("🚀 开始多模型协作", type="primary", disabled=not research_topic)
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if start_research_btn and research_topic:
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st.session_state.research_started = True
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st.session_state.research_output = ""
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st.session_state.research_steps_output = []
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manager = ResearchManager(api_key=api_key)
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config_obj = ResearchConfig(
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topic=research_topic,
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context=research_context,
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expert_a_model=roles_config['expert_a'],
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expert_b_model=roles_config['expert_b'],
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expert_c_model=roles_config['expert_c']
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)
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manager.create_agents(config_obj)
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st.divider()
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st.subheader("🧠 智囊团思考中...")
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# Collaborative Execution
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current_step_name = ""
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current_step_content = ""
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step_placeholder = st.empty()
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status_container = st.status("正在初始化...", expanded=True)
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try:
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for event in manager.collaborate(research_topic, research_context):
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if event["type"] == "step_start":
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current_step_name = event["step"]
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current_agent = event["agent"]
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current_model = event["model"]
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status_container.update(label=f"🔄 {current_step_name} [{current_agent}] ({current_model})", state="running")
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step_placeholder = st.empty()
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current_step_content = ""
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elif event["type"] == "content":
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current_step_content += event["content"]
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step_placeholder.markdown(f"**Thinking...**\n\n{current_step_content}")
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elif event["type"] == "step_end":
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# Save step result
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st.session_state.research_steps_output.append({
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"step": current_step_name,
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"output": event["output"]
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})
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status_container.write(f"### {current_step_name}\n{event['output']}")
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status_container.update(label=f"✅ {current_step_name} 完成", state="running")
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status_container.update(label="✅ 所有步骤完成", state="complete", expanded=False)
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# The last step output is the final plan
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if st.session_state.research_steps_output:
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final_plan = st.session_state.research_steps_output[-1]["output"]
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st.session_state.research_output = final_plan
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st.success("✅ 综合方案生成完毕")
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except Exception as e:
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st.error(f"发生错误: {str(e)}")
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import traceback
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st.code(traceback.format_exc())
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# Show Final Report if available
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if st.session_state.research_output:
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st.divider()
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st.subheader("📄 最终综合方案")
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st.markdown(st.session_state.research_output)
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st.download_button("📥 下载方案", st.session_state.research_output, "comprehensive_plan.md")
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# Show breakdown history
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with st.expander("查看完整思考过程"):
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for step in st.session_state.research_steps_output:
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st.markdown(f"### {step['step']}")
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st.markdown(step['output'])
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st.divider()
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elif mode == "Debate Workshop":
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# ==================== 原始 Debate UI 逻辑 ====================
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st.title("🎭 多 Agent 决策工作坊")
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st.markdown("*让多个 AI 角色从不同视角辩论，帮助你做出更全面的决策*")
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# ==================== 输入区域 ====================
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col1, col2 = st.columns([2, 1])
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with col1:
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st.subheader("📝 决策议题")
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# 决策类型选择
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decision_type = st.selectbox(
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"决策类型",
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options=list(DECISION_TYPES.keys()),
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format_func=lambda x: DECISION_TYPES[x],
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index=0
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)
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# 议题输入
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topic = st.text_area(
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"请描述你的决策议题",
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placeholder="例如：我们是否应该在 Q2 推出 AI 助手功能？\n\n或者：我应该接受这份新工作 offer 吗？",
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height=120
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)
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# 背景信息（可选）
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with st.expander("➕ 添加背景信息（可选）"):
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context = st.text_area(
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"背景信息",
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placeholder="提供更多上下文信息，如：\n- 当前状况\n- 已有的资源和限制\n- 相关数据和事实",
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height=100
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)
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context = context if 'context' in dir() else ""
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with col2:
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st.subheader("🎭 选择参与角色")
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# 获取推荐的角色
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recommended = get_recommended_agents(decision_type)
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all_agents = get_all_agents()
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# 预设角色选择
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st.markdown("**预设角色：**")
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selected_agents = []
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for agent in all_agents:
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is_recommended = agent["id"] in recommended
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default_checked = is_recommended
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if st.checkbox(
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f"{agent['emoji']} {agent['name']}",
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value=default_checked,
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key=f"agent_{agent['id']}"
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):
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selected_agents.append(agent["id"])
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# 自定义角色选择
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if st.session_state.custom_agents:
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st.markdown("**自定义角色：**")
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for agent_id, agent_info in st.session_state.custom_agents.items():
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if st.checkbox(
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f"{agent_info['emoji']} {agent_info['name']}",
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value=True,
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key=f"agent_{agent_id}"
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):
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selected_agents.append(agent_id)
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# 自定义模型配置 (Advanced)
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agent_model_map = {}
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with st.expander("🛠️ 为每个角色指定模型 (可选)"):
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for agent_id in selected_agents:
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# Find agent name
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agent_name = next((a['name'] for a in all_agents if a['id'] == agent_id), agent_id)
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if agent_id in st.session_state.custom_agents:
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agent_name = st.session_state.custom_agents[agent_id]['name']
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agent_model = st.selectbox(
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f"{agent_name} 的模型",
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options=list(AVAILABLE_MODELS.keys()),
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index=list(AVAILABLE_MODELS.keys()).index(model) if model in AVAILABLE_MODELS else 0,
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key=f"model_for_{agent_id}"
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)
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agent_model_map[agent_id] = agent_model
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# 角色数量提示
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if len(selected_agents) < 2:
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st.warning("请至少选择 2 个角色")
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elif len(selected_agents) > 6:
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st.warning("建议不超过 6 个角色")
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else:
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st.info(f"已选择 {len(selected_agents)} 个角色")
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# ==================== 辩论控制 ====================
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st.divider()
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col_btn1, col_btn2, col_btn3 = st.columns([1, 1, 2])
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with col_btn1:
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start_btn = st.button(
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"🚀 开始辩论",
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disabled=(not topic or len(selected_agents) < 2 or not api_key),
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type="primary",
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use_container_width=True
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)
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with col_btn2:
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reset_btn = st.button(
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"🔄 重置",
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use_container_width=True
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)
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if reset_btn:
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st.session_state.debate_started = False
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st.session_state.debate_finished = False
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st.session_state.speeches = []
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st.session_state.report = ""
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st.rerun()
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# ==================== 辩论展示区 ====================
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if start_btn and topic and len(selected_agents) >= 2:
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st.session_state.debate_started = True
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st.session_state.speeches = []
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st.divider()
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st.subheader("🎬 辩论进行中...")
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# 临时将自定义角色添加到 agent_profiles
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from agents import agent_profiles
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original_profiles = dict(agent_profiles.AGENT_PROFILES)
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agent_profiles.AGENT_PROFILES.update(st.session_state.custom_agents)
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try:
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# 初始化默认客户端
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llm_client = LLMClient(
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provider="aihubmix",
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api_key=api_key,
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base_url="https://aihubmix.com/v1",
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model=model
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)
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# 初始化特定角色的客户端
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agent_clients = {}
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for ag_id, ag_model in agent_model_map.items():
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if ag_model != model: # Only create new client if different from default
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agent_clients[ag_id] = LLMClient(
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provider="aihubmix",
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api_key=api_key,
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base_url="https://aihubmix.com/v1",
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model=ag_model
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)
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debate_manager = DebateManager(llm_client)
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# 配置辩论
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debate_config = DebateConfig(
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topic=topic,
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context=context,
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agent_ids=selected_agents,
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max_rounds=max_rounds,
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agent_clients=agent_clients
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)
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debate_manager.setup_debate(debate_config)
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# 运行辩论（流式）
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current_round = 0
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speech_placeholder = None
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|
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for event in debate_manager.run_debate_stream():
|
||
if event["type"] == "round_start":
|
||
current_round = event["round"]
|
||
st.markdown(
|
||
f'<div class="round-header">📢 第 {current_round} 轮讨论</div>',
|
||
unsafe_allow_html=True
|
||
)
|
||
|
||
elif event["type"] == "speech_start":
|
||
# 显示模型名称
|
||
model_display = f" <span style='font-size:0.8em; color:gray'>({event.get('model_name', 'Unknown')})</span>"
|
||
st.markdown(f"**{event['emoji']} {event['agent_name']}**{model_display}", unsafe_allow_html=True)
|
||
speech_placeholder = st.empty()
|
||
current_content = ""
|
||
|
||
elif event["type"] == "speech_chunk":
|
||
current_content += event["chunk"]
|
||
speech_placeholder.markdown(current_content)
|
||
|
||
elif event["type"] == "speech_end":
|
||
st.session_state.speeches.append({
|
||
"agent_id": event["agent_id"],
|
||
"content": event["content"],
|
||
"round": current_round
|
||
})
|
||
st.divider()
|
||
|
||
elif event["type"] == "debate_end":
|
||
st.session_state.debate_finished = True
|
||
st.success("✅ 辩论结束！正在生成决策报告...")
|
||
|
||
# 生成报告
|
||
if st.session_state.debate_finished:
|
||
report_generator = ReportGenerator(llm_client)
|
||
speeches = debate_manager.get_all_speeches()
|
||
|
||
st.subheader("📊 决策报告")
|
||
report_placeholder = st.empty()
|
||
report_content = ""
|
||
|
||
for chunk in report_generator.generate_report_stream(
|
||
topic=topic,
|
||
speeches=speeches,
|
||
context=context
|
||
):
|
||
report_content += chunk
|
||
report_placeholder.markdown(report_content)
|
||
|
||
st.session_state.report = report_content
|
||
|
||
# 下载按钮
|
||
st.download_button(
|
||
label="📥 下载报告 (Markdown)",
|
||
data=report_content,
|
||
file_name="decision_report.md",
|
||
mime="text/markdown"
|
||
)
|
||
|
||
except Exception as e:
|
||
st.error(f"发生错误: {str(e)}")
|
||
import traceback
|
||
st.code(traceback.format_exc())
|
||
st.info("请检查你的 API Key 和模型设置是否正确")
|
||
|
||
finally:
|
||
# 恢复原始角色配置
|
||
agent_profiles.AGENT_PROFILES = original_profiles
|
||
|
||
# ==================== 历史报告展示 ====================
|
||
elif st.session_state.report and not start_btn:
|
||
st.divider()
|
||
st.subheader("📊 上次的决策报告")
|
||
st.markdown(st.session_state.report)
|
||
|
||
st.download_button(
|
||
label="📥 下载报告 (Markdown)",
|
||
data=st.session_state.report,
|
||
file_name="decision_report.md",
|
||
mime="text/markdown"
|
||
)
|
||
|
||
# ==================== 底部信息 ====================
|
||
st.divider()
|
||
col_footer1, col_footer2, col_footer3 = st.columns(3)
|
||
with col_footer2:
|
||
st.markdown(
|
||
"<div style='text-align: center; color: #888;'>"
|
||
"🎭 Multi-Agent Decision Workshop<br>多 Agent 决策工作坊"
|
||
"</div>",
|
||
unsafe_allow_html=True
|
||
)
|